Cumulative impacts of peat mining project final project report

[From the U.S. Government Printing Office, www.gpo.gov]

Impacts of Peat Mining
Cumulative
Final Project Report

Edited by
Judith A. Gale
David A. Adams
Department of Forestry
North Carolina State University

AUGUST 1984

North Carolina
Coastal Energy Impact Program
Office of Coastal Management
North Carolina Department of Natural Resources
and Community Development

COASTAL ZONE
INFORMATION CENTER

CEIP REPORT NO. 40

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Series Edited by James F. Smith
Cover Design by Jill Miller

CUMULATIVE IMPACTS OF PEAT MINING PROJECT

FINAL PROJECT REPORT

U DEPARTMENT OF COMMERCE NOAA
COASTAL SERVICES CENTER
Edited by 2234 SOUTH HOBSON AVENUE
Judith A. Gale CHARLESTON , SC 29405-2413

and

David A. Adams

Department of Forestry
North Carolina State University
Raleigh, NC 27695-8002

The preparation of this report was financed through a
Coastal Energy Impact Program grant provided by the
North Carolina Coastal Management Program, through
funds provided by the Coastal Zone Management Act of
1972, as amended, which is administered by the office
of Coastal Management, National oceanic and
Atmospheric Administration. This CEIP grant was part
of NOAA NA-83-AA-D-CZ028. This project was
administered by the Water Resources Research Institute
of The University of North Carolina.

August 1984

CEIP Report No. 40

PrOPOrtY Of CSC Library

ACKNOWLEDGMENTS

The preparation of this document was a cooperative effort
by a research team consisting of the following persons:
Richard T. DiGiulio, David W. Evans and Curtis J. Richardson,
Duke University; Lee J. Otte, East Carolina University; David
A. Adams, Richard G. Broadhead, Leon E. Danielson, Judith A.
Gale, Melvin Huish, Margery F. Overton, Joseph A. Phillips and
R. Wayne Skaggs, North Carolina State University; William A.
Campbell, Edward J. Kuenzler and Hans W. Paerl, the Universi"--y
of North Carolina at Chapel Hill; and James F. Smith, North
Carolina Department of Natural Resources and Community
Development (see section 8 for further information).

.Special thanks are due David H. Moreau, James M. Stewart,
Linda Kiger and the staff of the Water Resources Research
.Institute of The University of North Carolina for their
assistance in project administration.

We are particularly indebted to Roy L. Ingram, Department
of Geology, University of North Carolina at Chapel Hill, for
providing raw data on peat volumes obtained through grants
from the North Carolina Energy Institute and the U.S.
Department of Energy (grants AC01 and FG18-79ET-14693); Leslie
Oster and Robert Hornstein, Koppers Company, Inc., for
reviewing and commenting on the alternative peat, mining
scenarios (section 5); Lucy L. Mauger, Institute for Coastal
and Marine Resources, East Carolina University, for preparing
the habitat type/land use data (Appendix 10.1) used throughout
section 6; Mike Lyle, Department of Geology, East Carolina
University, for collecting the fire data (section 6.6);
Kathleen Kenney, Department of Foresty, North Carolina State
University, for assistance with the wildlife simulation
(section 6.1.4) and recreation section (6.1.5), and for typing
much of this report; and the many other industry
representatives and state and federal agency personnel who
contributed to this effort.

1. ABSTRACT

1.1 Description of the Project

Three alternative 20-year peat mining development scenarios
and a no change alternative were constructed for a study area
consisting of Hyde, Tyrrell and Washington Counties, North
Carolina. The scenarios included: 1) currently permitted acreage
mined as proposed (as of summer, 1983) (22,690 acres permitted
and 17,360 acres mined during a 20-year period); 2) upper
boundary (84,000 acres permitted and mined); and 3) industry
failure at year 10 (22,960 acres permitted and 8,520 acres mined
by year 10).

Probable cumulative environmental and economic impacts
associated with each scenario were examined. These included
.impacts on agriculture; forest products; fish; wildlife;
recreation; surface water runoff; nutrient, trace element,
coliform bacteria and pesticide yields; groundwater; land use
conversion; air quality; solid waste; occurrence of fire; and
local economics.

Critical potential impacts of peat mining and related land
conversion activities were identified and recommended approaches
to address these impacts were outlined. In cases where impacts
from other forms of land conversion, such as agriculture and
forestry, were believed to be similar to impacts of peat mining,
the recommended approach was broadened to address impacts of
land conversion in general.

1.2 Critical Impacts and Recommended Approaches

1.2.1 Estuarine Impacts

Large-scale conversion of peatlands to agriculture,
forestry and peat mining on the Albemarle-Pamlico Peninsula will
alter primary nursery areas in peripheral estuarine systems.
Changes in salinity regimes; surface water runoff rates;
nutrient loading; suspended solids; sedimentation; trace
element, pesticide and coliform bacteria levels; and
interactions among these factors are believed to be the most
significant potential estuarine impacts from land conversion.

The recommended approach includes the initiation of an
integrated, multidisciplinary effort toward: 1) identifying the
most significant gaps in data relating to the estuarine impacts
described above and 2) developing a predictive numerical model
for use by decision makers in assessing the impacts of existing
and proposed coastal land use on the state's estuarine
resources. Such a model could also be used to support effluent
limitations to meet water quality standards for primary nursery
areas.

1.2.2 Wildlife

A wildlife habitat simulation was used to analyze the
consequences of large-scale peat mining on the Albemarle-Pamlico
Peninsula. A significant proportion of the currently existing
black bear and bobcat habitat will. be lost if extensive mining
takes place.

Field validation of habitat suitability indices for
important species used in the simulation is needed. In addition,
linking of the spatial and temporal aspects of the wildlife
habitat simulation model is necessary to enable land managers to
evaluate the impacts of alternative land use decisions on
wildlife.

1.2.3 Upland Water Management

Extensive peat mining may increase annual runoff from the
mined areas by up to 30% above the pre-mining flow. As the mined
areas are reclaimed to agriculture and forestry, annual flows
will decrease or increase slightly from the pre-mining flow,
depending on the crops planted.

Impacts of drainage systems and seasonal pumping on the
location of the fresh/saltwater interface in estuarine areas are
not known.

The cumulative impacts of groundwater withdrawals for peat
processing and drainage from mining sites are not well
understood. However, the potential exists for saltwater
intrusion into areas where peat is mined close to and below sea
level.

Further research is needed in the following areas:
hydrology of undisturbed peatlands; nutrient transformation in
canal. and river networks; field measurement techniques and
modeling of surface runoff from actively mined sites; long-terra
effectiveness of wetland buffers for filtration of nutrients,
trace elements and sediments and for control of freshwater flow
rates; effectiveness of storage lakes in reducing negative
estuarine impacts of land drainage; and effects of peat mining
on groundwater supplies, including the location of the
fresh/saltwater interface.

The data from the research listed above will provide input:
to an existing hydrological model estimating the effects of
alternative upland water management strategies on surface
runoff. The output from this model could provide input to an
estuarine model.

1.2.4 Hurricane Flooding

Approximately one-half to two-thirds of the Albemarle-
Pamlico Peninsula is subject to flood inundation caused by wind
tides having a 1% chance of being equalled or exceeded in any
one year.

Hurricane tides may push saline water from the sounds up
rivers and canals into low lying areas created by peat mining,
damaging areas reclaimed to agriculture and forestry. In
addition, the effects of hurricane flooding on shallow aquifers
under such conditions is not known.

Rain associated with hurricanes may accumulate in low lying
areas faster than the capacity of pumps to remove it. Thus the
potential also exists for freshwater damage to crop and forest
land, depending on the duration of the flooding.

The recommended approach is to develop a new series-of,maps
delineating flood susceptibility based on land elevations that
would exist if substantial peat deposits were removed from the
region. Sediments underlying the peat deposits should be
examined to determine their susceptibility to floodwater
infiltration.

1.2.5 Unique Natural Areas

Large-scale peat mining on the peninsula will be
accompanied by a loss of part of the state's largest and least
disturbed wetland complex, and a large proportion of the area
underlain by peat of depths greater than four feet. Some of
these areas contain prime Atlantic white cedar habitat.
Extensive mining will remove a significant proportion of these
unique areas and the biota they support.

An attempt should be made to determine if the peninsula
contains other areas that are unique in biological,
hydrological, geological, pedological, chemical or other natural
aspects and worthy of consideration for preservation or
protection.

1.2.6 Air Quality

The cumulative effects of multiple source air pollutants
(from peat harvesting and multiple stacks) from large-scale peat
mining and processing on the peninsula are not known and should
be monitored and modeled to assess potentially negative impacts.

In addition, refinement of emissions estimates is needed to
determine whether fugitive dust emissions during peat mining and
transport and storage of peat will have significant negative
impacts if extensive mining occurs.

1.2.7 Solid Waste

The capacity of potential disposal sites on the Albemarle-
Pamlico Peninsula to handle the volume of non-hazardous waste
that would be created by extensive processing of peat on the
peninsula is uncertain. Additional research on site selection
and evaluation for solid waste disposal is needed.

Impacts of onsite use of some of this waste, for example,
on roadbeds or for agricultural land treatment, are not well
documented. Further characterization of the properties of
leachates of peat combustion ashes is needed to adequately
evaluate the impacts of such practices.

1.2.8 Local Economics

Fiscal problems may arise when new residents (migrating to
the area to work in peat mining operations) locate outside the
political boundaries of local governments having the power to
tax peat mining facilites. Distributional aspects of tax
revenues and public services required may create deficits in
some cities and counties and surpluses in others. Short-term
fiscal problems may also arise where generated revenues lag
costs.

The development of two simulation models is recommended:
1) a model to address the impact of potential peat mining
facilities on tax rates and revenues and 2) a model to examine
the overall fiscal impacts Of Peat mining on state and local
government.

In addition, the economic consequences of large-scale peat
mining and other land conversion activities in coastal areas oil
the recreation, tourism and commercial and sport fishery sectors
should be examined.

TABLE OF CONTENTS

ACKNOWLEDGMENTS .........................................

1. ABSTRACT .................................................

1.1 Description of the Project ...........................
1.2 Critical Impacts and Recommended Approaches .......... iii
1.2.1 Estuarine Impacts .............................. iii
1.2.2 Wildlife ....................................... iv
1.2.3 Upland Water Management ........................ iv
1.2.4 Hurricane Flooding ............. 9............... v
1.2.5 Unique Natural Areas ........................... v
1.2.6 Air Quality .................................... v
1.2.7 Solid Waste .................................... vi
1.2.8 Local Economics ................................ vi

TABLE OF CONTENTS ........................................ vii

LIST OF FIGURES AND TABLES .............. ................ xi

2. INTRODUCTION ............................................. 1

2.1 Origin and Background of the Study ................... 1
2.2 Funding and Organization of the Study ................ 2
2.3 Tasks ................................................ 2
2.4 Study Area ........................................... 3
2.5 Scope and Limitations of the Study ................... 3
2.6 Abbreviations ........................................ 4
2.7 Use of the Term "Wetlands .. ...................... 4

3. SUMMARY ......... o ........................................ 6

3.1 Affected Environment ............ o .................... 6
3.1.1 Biophysical En v ironment .................... o ... 6
3.1.2 Socioeconomic Environment ...................... 6
3.1.3 Legal-institutional Environment ................ 7
3.2 Alternatives ....................................... o. 8
3.2.1 No Change .... o........................ o ........ 8
3.2.2 Scenario #1: Currently Permitted Acreage ....... 8
3.2.3 Scenario #2: Upper Boundary .....o .............. 8
3.2.4 Scenario #3: Industry Failure .................. 9
3.3 Primary Environmental Impacts of the Alternatives .... 9
3.3.1 Amount of Runoff ................ o .............. 9
3.3.2 Wastewater Discharges . ......................... 10
3.3.3 Groundwater .................................... 10
3.3.4 Hurricane Flooding ............................. 10
3.3.5 Air Quality .................................... 11
3.3.6 Solid Waste ......... o......... o ................ 11

Vii

3.4 Cumulative Environmental and Economic Impacts of the
Alternatives ......................................... 11
3.4.1 Agriculture .................................... 11
3.4.2 Forest Products ................................ 11
3.4.3 Fish ........................................... 12
3.4.4 Wildlife ....................................... 12
3.4.5 Recreation ..................................... 13
3.4.6 Amount of Surface water Runoff ................. 13
3.4.7 Nutrient Yields and Surface Water, Eutrophica-
tion ........................................... 14
3.4.8 Trace Element, Pesticide and Coliform
Bacteria Yields ................................ 15
3.4.9 Groundwater .................................... 15
3.4.10 Land Use Conversions .......................... 15
3.4.11 Air Quality ................................... 16
3.4.12 Solid Waste ................................... 16
3.4.13 Fire .......................................... 16
3.4.14 Local Economics and Employment ................ 16
3.5 Summary of Critical Environmental and Economic
Impacts and Recommended Approaches .................... 18
3.5.1 Estuarine Impacts .............................. 18
3.5.2 Wildlife ....................................... 18
3.5.3 Upland Water Management ........................ 19
3.5.4 Hurricane Flooding ............................. 19
3.5.5 Unique Natural Areas ........................... 20
3.5.6 Air Quality .................................... 20
3.5.7 Solid Waste .................................... 20
3.5.8 Local Economics ................................ 21
3.6 Non-significant Impacts .............................. 21

4. AFFECTED ENVIRONMENT ..................................... 22

4.1 Biophysical Environment .............................. 22
4.1.1 General Setting ................................ 22
4.1.2 Hydrology ...................................... 22
4.1.3 Fishery Resources .............................. 29
4.1.4 Soils and Farmland ............................. 31
4.1.5 Forests ......................................... 31
4.1.6 Mineral and Energy Resources ................... 32
4.1.7 Wildlife ....................................... 33
4.1.8'Parks, Refuges and Natural Areas ............... 33
4.2 Socioeconomic Environment ............................ 36
4.2.1 Population ..................................... 36
4.2.2 Employment ..................................... 36
4.2.3 Income ......................................... 36
4.2.4 Economic Sectors ............................... 36
4.2.5 Transportation Infrastructure .................. 40
4.3 Legal-institutional Environment ...................... 41
4.3.1 Local and County Government .................... 41
4.3.2 major Regulatory Controls ...................... 41
4.3.2.1 State Regulatory Controls ................. 41
4.3.2.2 Federal Regulatory Controls ............... 43
4.3.3 Coun'Ly Responses ............................... 45

Viii

5. ALTERNATIVE PEAT MINING DEVELOPMENT SCENARIOS ............ 47

5.1 Introductory Section ................................. 47
5.2 Alternatives ......................................... 48
5.2.1 No Change ...................................... 48
5.2.2 Scenario #1: Currently Permitted Acreage ....... 49
5.2.3 Scenario #2: Upper Boundary .................... 78
5.2.4 Scenario #3: Industry Failure .................. 102

6. ENVIRONMENTAL AND ECONOMIC ASSESSMENT OF THE SCENARIOS ... 120

6.1 Resource Production/Consumption ....................... 120
6.1.1 Agriculture ..................................... 120
6.1.2 Forest Products ................................. 1145
6.1.3 Fish ..................... o ...................... 147
6.1.4 Wildlife ........................... o............ 151
6.1.5 Recreation .... o........ o ....o...... o....... 169
6.2 Water o .................. o........ o ....... oo ...... o... 171
6.2.1 Surface water ............ o........ oo ............. 171
6.2.1.1 Amount of Surface Water Runoff ..... o....... 171
6.2.1.2 Nutrient Yields and Surface Water
Eutrophication ........- ..... o........... o185
6o2.lo3 Trace Element, Pesticide and Coliform
Bacteria Yields ... ........ o......... o ... -.196
6.2.2 Groundwater . .................... oo ...... o....... 201
6.2.3 Hurricane flooding .......o............. oo ....... 205
6.3 Land Use Conversions .......... o ..... 206
6.4 Air Quality ...... o ........... o...
6.5 Solid Waste . ..................................... o... 223
6.6 Fire .. ...... o .............. o .......... o....... o ...... 227
6.7 Local Economics and Employment ...... o.... o...... o .... 231

7. EVALUATION PROCESS .......... o..o ............ **ee*ee,o**oo243

7.1 Estuarine Impacts ........ o ........... o... o.o.o ....... 243
7.2 Wildlife ............................... o .... o ........ 260
7.3 Upland Water Management .............................. 267
7.3.1 Hydrology of Existing Natural Conditions .......267
7.3.2 Nutrient Transformation in Canal and River
Networks ......... --oo-e-e- ..... ese-268
7o3.3 Improved Field Data and Modeling for Actively
Mined Areas .................................. o.269
7.3.4 Wet Reclamation and Perpetual Pumping .......... 270
7.3.5 Wetland Filter Areas for Overland Treatment
of Runoff ........ oo ... o................... o.oo.271
7.3.6 Effects of Peat Mining on Groundwater and
Saltwater Intrusion ................ o........... 272
7.4 Hurricane Flooding ....................... o.oo.o.274
7.5 Natural Area Inventory ............. o.............. o..278
7.6 Air Quality ...................................... o... 281
7.7 Solid Wastes ........... o...- ....................... 285
7.8 Local Economics . .................................. o..288

8. LIST OF PREPARERS .................... oo ...... oo-o-e-291

9. REFERENCES ............................................... 29-3

10. APPENDICES .............................................. 308

10.1 Habitat Type/Land Use Data ........................... 30EI
10.2 Appendix for Section 6.1.1: Agriculture .............. 31CI
10.3 Appendix for Section 6.1.3: Fish ..................... 31EI
10.4 Appendix for Section 6.1.4: Wildlife ................. 331
10.5 Appendix for Section 6.2.1.1: Amount of Surface
Water Runoff ......................................... 374
10.6 Appendix for Section 6.2.1.2: Nutrient Yields and
Surface Water Eutrophication ......................... 381-
10.7 Appendix for Section 6.2.1.3: Trace Element,
Pesticide and Coliform Bacteria Yields ............... 385
10.8 Appendix for Section 6.4: Air Quality ................ 388
10.9 Appendix for Section 6.7: Local Economics and
Employment ........................................... 4041
10.10 Abbreviations Used in the Report .................... 416)

LIST OF FIGURES AND TABLES

FIGURES PAGE

Figure 2A: Location map showing the Albemarle-Pamlico
Peninsula and the project study area: Hyde,
Tyrrell and Washington Counties .................. 5

Figure 4A: Drainage divides and probable paths of overland
runoff prior to artificial drainage systems ...... 24

Figure 4B: Isopach map of peat deposits on the Albemarle-
Pamlico Peninsula ................................ 34

Figure 4C: State and federal lands on the Albemarle-Pamlico
Peninsula ........................................ 35

Figure 4D: Total population, 1980, and percentage change in
total population, 1970-80 ........................ 37

Figure 5A: Scenario #1-- Acreage disturbed .................. 50

Figure 5B: Scenario #I-- Currently Permitted Acreage ........ 51

Figure 5C: Generalized topographic map of the Albemarle-
Pamlico Peninsula .............................. 54

Figure 5D: Area subject to flood inundation caused by wind
tides having a 1% chance of being equalled or
exceeded in any one year ....................... 68

Figure 5E: Schematic of typical wildlife buffer plan ........ 74

Figure 5F: Scenario #2-- Acreage disturbed .................. 79

Figure 5G: Scenario #2-- Upper Boundary ..................... 80

Figure 5H: Scenario #3-- Acreage disturbed .................. 103

Figure 6.2.1.1A: Scenario #1, Area 1-- Total annual flow .... 175

Figure 6.2.1.1B: Scenario #1, Area 2-- Total annual flow .... 176

Figure 6.2.1.1C: Scenario #2, Area 1-- Total annual flow .... 177

Figure 6.2.1.1D: Scenario #2, Area 2-- Total annual flow .... 178

Figure 6.2.1.1E: Scenario #2, Area 3-- Total annual flow ....179

Figure 6.2.1.1F: Scenario #2, Area 4-- Total annual flow .... 180

Figure 6.2.1.1G: Comparison of peak flows from a 320-acre
block under three different land uses ...... 181

Figure 6.2.2A: Generalized hydro geologic units in Scenario
#1, Area 1 .................................. @202

Figure 7.4A: Area subject to flood inundation caused by wind
tides having A, 50% chance of being equalled or
exceeded in any one year; B, 1% chance of being
equalled or exceeded in any one year ........... 27@

Figure 7.6A: Isopleths of annual average particulate concen-
trations predicted to be added by peat-to-
methanol conversion at a plant of the size of
that postulated in Scenario #1 ................. 283

Figure 7.6B: Isopleths of annual average particulate concen-
trations predicted to be added by peat-to-
methanol facilities the size of Scenario #2 .... 284:

Figure 10.6A: Box plots of phosphorus export coefficients
from various land uses ........................ 383

Figure 10.6B: Box plots of nitrogen export coefficients from
various land uses ............................. 384:

TABLES

Table 4A: Employment summary by industry groups by county,
1960, 1970 ........................................ 36:

Table 4B: median family income by county, 1960, 1970 ........ 39

Table 4C: Per capita personal income by county, 1970, 1975,
1977 .............................................. 39

Table 4D: Commercial fishing vessel licenses, pounds landed
and dockside value by county, 1975-1980 ........... 40

Table 6.1.IA: Value of mined areas reclaimed to row crops
with pumped drainage at years 10 and 20
(Run #1) ...................................... 122'.

Table 6.1.1B: Value of mined areas reclaimed to row crops
with pumped drainage at years 10 and 20
(Run #2) ...................................... 125

Table 6.1.1C: Summary-- Value of mined areas reclaimed to
agriculture with pumped drainage at years 10
and 20 (Run #1) ............................... 128

Table 6.1.1D: Summary-- Value of mined areas reclaimed to
agriculture with pumped drainage at years 10
and 20 (Run #2) ............................... 128

Xii

Table 6.1.1E: Cumulative value of total acreage in row crops
with the mining projects (Run #1) ............. 129

Table 6.1.1F: Cumulative value of total acreage in row crops
without the mining projects (Run #1) .......... 132

Table 6.1.1G: Cumulative value of total acreage in row crops
with the mining projects (Run #2) ............. 135

Table 6.1.1H: Cumulative value of total acreage in row crops
without the mining projects (Run #2) .......... 138

Table 6.1.11: Summary-- Cumulative value of total acreage in
row crops with the mining projects (Run #1) ...141

Table 6.1.11: Summary-- Cumulative value of total acreage
in row crops without the mining projects
(Run #1) ...................................... 141

Table 6.1.1K: Summary-- Cumulative impact on row crop
agriculture with and without the projects
(Run #1) - Net income minus drainage costs .... 142

Table 6.1.IL: Summary-- Cumulative value of total acreage in
row crops with the mining projects (Run #2) ...142

Table 6.1.1M: Summary-- Cumulative value of total acreage
in row crops without the mining projects
(Run #2) ...................................... 143

Table 6.1.1N: Summary-- Cumulative impact on row crop
agriculture with and without the projects
(Run #2) - Net income minus drainage costs .... 143

Table 6.1.2A: Scenario #2 (Areas 1 and 3)-- Value of timber
harvested prior to peat mining ................ 146

Table 6.1.2B: Scenario #2-- Value of plantation pine if
harvested at year 20 .......................... 146

Table 6.1.4A: Scenario #1-- Total accrued annualized habitat
units at the end of the project period, with
and without the project ....................... 153

Table 6.1.4B: Scenario #1, Area 1-- Accrued annualized habi-
tat units at the end of the project period,
with and without the project, by species ...... 154

Table 6.1.4C: Scenario #1, Area 2-- Accrued annualized habi-
tat units at the end of the project period,
with and without the project, by species ...... 154

xiii

Table 6.1.4D: Scenario Average Habitat Suitability Index,
by species, for the beginning and end of the
project period, with and without the project ..155

Table 6.1.4E: Scenario #2-- Total accrued annualized habitat
units at the end of the project period, with
and without the project ....................... 156

Table 6.1.4F: Scenario #2, Area 1-- Accrued annualized habi-
tat units at the end of the project period,
with and without the project, by species ...... 156

Table 6.1.4G: Scenario #2, Area 2-- @%ccrued annualized habi-
tat units at the end of the project period,
with and without the project, by species ...... 157

Table 6.1.4H: Scenario #2, Area 3-- Accrued annualized habi-
tat units at the end of the project period,
with and without the project, by species ...... 157

Table 6.1.41: Scenario #2, Area 4-- @%ccrued annualized habi-
tat units at the end of the project period,
with and without the project, by species ...... 158

Table 6.1.4J: Scenario #2-- Average Habitat Suitability Index,
by species, for the beginning and end of the
project period, with and without the project ..159

Table 6.1.4K: Scenario #3-- Total accrued annualized habitat
units at the end of the project period, with
and without the project ....................... 161

Table 6.1.4L: Scenario #3, Area 1-- Accrued annualized habi-
tat units at the end of the project period,
with and without the project, by species ...... 161

Table 6.1.4M: Scenario #3, Area 2-- Accrued annualized habi-
tat units at the end of the project period,
with and without the project, by species ...... 162

Table 6.1.4N: Scenario #3-- Average Habitat Suitability Index,
by species, for the beginning and end of the
project period, with and without the project ..163

Table 6.1.5A: Estimated changes in recreational value
primarily hunting) based on a value of $36 per
acre over 20 years ............................ 170

Table 6.2.1.lA: Annual flow totals generated from 20 years
of simulation ............................... 174

Table 6.2.1.2A: Concentrations (mg/1) of nutrients in runoff
water from various land uses ................ 186

Xiv

Table 6.2.1.2B: Areal yields (lb/acre.yr) of nutrients from
watersheds with various land uses ........... 187

Table 6.2.1.2C: Total annual yields of nutrients from peat-
lands under the alternative scenarios ....... 188

Table 6.2.1.2D: Nutrient loadings to lakes and lagoons ...... 189

Table 6.2.1.2E: Nutrient loadings to estuaries .............. 190

Table 6.2.1.3A: Total annual yields of three trace elements
in drainage waters from peatlands under
alternative scenarios ........................ 197

Table 6.2.1.3B: Total annual yields of selected trace ele-
ments from wastewater effluent discharged by
methanol plants in the scenarios (lb/yr) .... 198

Table 6.2.1.3C: Average fecal and total coliform bacteria
concentrations measured in drainage waters
from organic soil sites (no./lOOml) ......... 198

Table 6.3A: Scenario #1, Areas 1 and 2-- Land use/land cover,
pre- and post-mining (% of total acreage) ....... 208

Table 6.3B: Scenario #2, Areas 1, 2, 3 and 4-- Land use/land
cover, pre- and post-mining (% total acreage) ...208

Table 6.4A: Scenario #1, Area 1-- Fugitive dust emissions
from peat mining, transport and field pile
storage of peat for methanol production ......... 215

Table 6.4B: Scenario #1, Area 1-- Criteria pollutant
emissions from a methanol plant processing
about 1,600 (dry) tons of peat per year ......... 215

Table 6.4C: Scenario #1, Area I- Non-criteria pollutant
emissions from a methanol plant processing
about 1,600 (dry) tons of peat per year ......... 216

Table 6.4D: Scenario #1, Area 1-- Fugitive particulate
analysis, maximum off-property concentrations
from peat for methanol project .................. 216

Table 6.4E: Scenario #1, Area 1-- Fugitive particulate
analysis, maximum off-property concentrations
from peat for methanol project .................. 217

Table 6.4F: Scenario #1, Area 1-- Modeling results: Maximum
off-property predicted concentrations from peat
for methanol project ............................ 218

Table 6.5A: Non-hazardous wastes from peat-to-methanol
conver3ion ...................................... 224

Table 6.5B: Hazardous wastes from peat-to-methanol
conversion ...................................... 224

Table 6.6A: Cause of fire (Hyde, Tyrrell and Washington
Counties) ....................................... 227

Table 6.6B: Size of fire (Hyde, Tyrrell and Washington
Counties) ....................................... 228

Table 6.7A: Scenario #1, Area 1-- Long-run impacts of
525,000 (dry) ton methanol plant ................ 232

Table 6.7B: Scenario #1, Area 1-- Long-run direct plus
indirect impacts of 525,1300 (dry) ton methanol
plant ........................................... 232

Table 6.7C: Scenario #1, Area 1-- Short-run impacts of
525,000 (dry) ton methanol plant ................ 233

Table 6.7D: Scenario #2, Area 1 & 3-.- Long-run direct plus
indirect impacts of methanol plants processing
4.1 million (dry) tons of peat .................. 233

Table 6.7E: Scenarios #1 and #2, Areas 1,2 and 4-- Estimated
employment for horticultural peat and peat for
fuel ............................................ 234

Table 10.1A: Scenarios #1 and #3-- Approximate acreages of
peatland by habitat type/land use category at
year 0 ................ ......................... 308

Table 10.IB: Scenario #2-- Approximate acreages of peatland
by habitat type/land use category at year 0 ....

Table 10.5A: Scenario #1, Area 1: Acreage by land use
categories for the 20 year study period ......... 375

Table 10.5B: Scenario #1, Area 2: Acreage by land use
category for the 20 year study period .......... 376

Table 10.5C: Scenario #2, Area 1: Acreage by land use
category for the 20 year study period .......... 377

Table 10.5D: Scenario #2, Area 2: Acreage by land use
category for the 20 year study period .......... 378

Table 10.5E: Scenario #2, Area 3: Acreage by land use
category for the 20 year study period .......... 379

Table 10.5F: Scenario #2, Area 4: Acreage by land use
category for the 20 year study period .......... 380

xvi

Table 10.6A: Land use acreages used in calculations for
sections 6.2.1.2 and 6.2.1.3 ................... 381

Table 10.6B: General ranges of primary productivity of
phytoplankton of lakes of different trophic
categories ..................................... 382

Table 10.8A: National Ambient Air Quality Standards ......... 392

Table 10.8B: Maximum allowable increases under Prevention of
Significant Deterioration (PSD) regulations .... 393

Table 10.10A: Abbreviations used in the report .............. 416

xvii

2. INTRODUCTION

2.1 origin and Background of the Study

The Albemarle-Pamlico Peninsula of North Carolina lies in a
region characterized by low surface elevations, a water table
that lies close to the surface and extensive wetlands (Heath,
1975). The peninsula contains about 582 square miles (373,000
acres) of peat deposits that occur in shallow depressions to a
depth of 10 feet and in narrow former stream channels to a depth
of 16 feet (Ingram and Otte, 1982).

During the past 10 to 20 years, increasing concerns in the
United States relating to energy sources and availability have
led to heightened interest in the potential of peat as a fuel.
North Carolina peat is characterized by low ash and sulfur
contents (usually less than 10% and 0.5%, respectively) and a
high heating value (median heating value: 10,200 Btu/lb) (Ingram
and Otte, 1981). Its quality is thus high as a fuel for direct
combustion. The low bulk density of peat, however, renders the
economic feasibility of transporting it any significant distance
questionable. Other potential uses of peat include chemical
feedstock for the production of methanol, benzene, peat coke,
activated carbon, synthetic gas and gasoline, tars and phenols;
absorbent; and insulating material (Ingram and Otte, 1981).

In response to growing interest in peat mining, the North
Carolina Department of Natural Resources and Community,
Development (NRCD) organized a task force in December 1980 to
review the status of peat mining activities in the state,
evaluate the adequacy of state government's management of this
activity, and recommend actions to be taken by NRCD.

Four peat mining permits had been issued for areas located
on the Albemarle-Pamlico Peninsula, as of April, 1984. These
permits cover 22,960 acres in Hyde, Tyrrell and Washington
Counties. Mining for horticultural peat is already occurring on
a small scale and a 300-acre experimental mine has been operated
since 1978 to test mining equipment and methods.

After studying the legal and regulatory aspects of peat
mining, the Peat Mining Task Force (1983) concluded that the
state has an adequate framework for the management of peat
mining through provisions of the Mining Act of 1971 and permits
for water use, wastewater discharge, air quality management and
coastal development. However, in its analysis, the Task Force
cited the urgent need for additional research and policy
development on the long-term cumulative effects of peat mining
and related land conversion operations as those activities
become widespread in the coastal region. The cumulative impacts
of multiple mining and related developments are believed likely
to extend beyond the scope of regulatory permits applied to
individual establishments. In response to the issues raised by
the task force, the Cumulative Impacts of Peat Mining Project
was initiated in June, 1984.

This study is part of an ongoing effort by the North
Carolina Department of Natural Resources and Community
Development, federal agencies concerned with natural resource
management, such as EPA, the U.S. Army Corps of Engineers and
the U.S. Fish and Wildlife Service, scientists and industry to
identify significant negative impacts of land conversion in
coastal areas and to develop means for avoiding or mitigating
such impacts. For example, the Governor's Coastal Water,
Management Task Force was established in 1981 to assess and seek
resolutions to conflicts between the interests of those involved
with agriculture and forestry, in clearing and draining coastal.
land, and the interests of those concerned with fisheries and
wildlife, in maintaining productive saline nursery areas and.
wildlife habitat. The task force has made a number of
recommendations to the Governor toward this goal (1982, 1984),
some of which have already been implemented. The impacts of
large-scale coastal land conversion to agriculture have been
further explored in a draft environmental impact statement
prepared by the U.S. Army Corps of Engineers, Wilmington
District (1982), in response to an application by Prulean Farms,
Inc. for a Section 404 permit to place excavated materials in
wetlands as part of a project to clear and drain areas for
agricultural operations in Dare County.

2.2 Funding and Organization of the Study

The Cumulative Impacts of Peat Mining Project was financed
through a Coastal Energy Impact Program grant provided by the
North Carolina Coastal Management Program, through funds
provided by the Coastal Zone Management Act of 1972, as amended,
which is administered by the office of Coastal Management,
National oceanic and Atmospheric Administration. The project was
administered by the Water Resources Research Institute of The
University of North Carolina. Project Coordinator Dr. David
Adams of the Department of Forestry, North Carolina State
University, directed the efforts of a research team consisting
of faculty and staff members from North Carolina State
University, the University of North Carolina at Chapel Hill,
East Carolina University and Duke University (see section 8).

2.3 Tasks

The one-year project was charged with four tasks:

1. Construct alternative 20-year peat mining development
scenarios (Alternative Scenarios).

2. Identify and assess the probable environmental and economic
impacts associated with the alternative peat mining
development scenarios (Environmental Assessment).

3. Identify critical impacts that should be addressed in an
evaluation plan (Scoping Process).

4. Design a real time evaluation process to address the
critical cumulative impacts identified in the scoping
process, reviewing existing monitoring programs and
identifying specific needs for further research
(Evaluation Process).

2.4 Study Area

The primary study area for Tasks 1 and 2 (see sections 5
and 6) of the project encompassed Washington, Tyrrell and Hyde
Counties (Figure 2A); however, when cumulative impacts were
believed to affect an area larger than these three counties, the
study area was enlarged. For Tasks 3 and 4 (see section 7), the
study area was expanded to include Dare County and the scope of
the study was expanded to include other forms of land
conversion, when effects of other land conversion activities
(e.g., large-scale agriculture and silviculture) were believed
to be similar to impacts of peat mining.

2.5 Scope and Limitations of the Study

In assessing the cumulative impacts of each scenario, the
project's research team members have made and stated additional
reasonable assumptions as necessary to conduct their analyses.
In some cases the assumptions made by team members have not been
identical. Attempts have been made to ensure that assumptions
made are not contradictory; however, because of the extremely
short time frame of the project, it was not possible to revise
analyses to render all assumptions identical.

Analyses performed and conclusions reached in the
environmental assessment (section 6) are admittedly based on
insufficient data and inadequate models. The team elected to
proceed as far as possible within project constraints,
acknowledging that much of their work would be subject to
professional criticism but believing that state-of-the-art
analyses with existing data bases, yielding concrete results,
were preferable to generalizations, rationalizations and delays.
Thus the conclusions discussed here should be viewed as
preliminary best estimates. Hopefully, the weaknesses in data
and methodology exposed in this work will lead to improvements
in the environmental assessment process and to a better
understanding of the biophysical and socioeconomic processes
operative in the project area.

2.6 Abbreviations

Abbreviations used in this report are listed in Appendix
10.10.

2.7 Use of the Term "Wetlands"

.Except where otherwise noted, the term "wetlands" is used
in this report in a general ecological sense, and does not imply
any particular regulatory meaning.

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NORTH CAROLINA

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Figure 2A: Location map showing the Albemarle-Pamlico Peninsula and the project s
llyde, Tyrrell and Washington Counties

3. SUMMARY

3.1 Affected Environment

3.1.1 Biophysical Environment

The Albemarle-Pamlico Peninsula is a low lying, tidewater
region bordered by two sounds, Albemarle and Pamlico, and arl
estuarine river, the Pamlico (see Figure 2A). The area is
characterized by poorly integrated coastal streams, deep organic
soils, extensive swamps, marshes and evergreen wetlands, and a.
low astronomical tidal range.

Drainage projects aimed at lowering the water table and
removing surface water in peatlands on the peninsula have been
undertaken to enhance agricultural and lumbering operations
since the late 1700s. The historical development of drainage
systems in the area has been documented by Heath (1975), Lilly
(1981), Richardson (1981, 1983) and McMullan (1984). Drainage
patterns have thus been altered over the years by a widespread
system of canals, ditches and associated roads.

Approximately 20% of the land area on the peninsula was
cultivated in 1978-79. Forests cover roughly 70% of the area.
Most forested areas occur on deep organic soils.

The peninsula contains approximately 582 square miles
(373,000 acres) of peat deposits ranging in depth to 16 feet.
The volume of these peat resources has been estimated at 278
million (dry) tons.

The Albemarle-Pamlico Peninsula is considered one of the
most productive areas in the state in terms of the richness of
its wildlife resources. Four National Wildlife Refuges, a state
park and a state gameland are located on the peninsula.

Pamlico Sound and its tributaries constitute the most
productive fisheries resource in North Carolina.

The air quality on the peninsula meets or exceeds that
required by national air quality standards, and the peninsula
has been designated a Prevention of Significant Deterioration
(PSD) area.

3.1.2 Socioeconomic Environment

The Albemarle-Pamlico Peninsula is sparsely populated and
has few cities and towns. The rE?gional growth rate is 5.1%,
one-third of the state growth rate fox: 1970-80.

Agriculture, forestry and fishing have traditionally
dominated economic activity on the peninsula; however, in recent
years the composition of the labor force has shifted toward
employment in the industrial and service sectors.
Median family income for Hyde, Tyrrell and Washington
Counties in 1970 ranged from $4,000 to $7,000 per year. In 1970,
24-38% of the families in the three counties fell below the
poverty line.

Commercial fishing in the three counties produced fish and
shellfish worth $4.5 million in 1980, while agricultural
products were estimated at $42.3 million. Forestry output in
1982 was approximately $3.9 million.

Highway access in the region is good east-west and limited
north-south. Water access is good via the sounds and the
Intracoastal Waterway (IWW), which bisects'the peninsula. Rail
access is available only at the western end of the region. No
petroleum product pipelines exist in the area, and Dare and
Tyrrell Counties have no natural gas service.

3.1.3 Legal-institutional Environment

The major state regulatory tool for the control of
environmental impacts of peat mining is the Mining Act of 1971.
Other state laws mandating regulation and permitting of certain
aspects of peat mining include the Water Use Act of 1967
(groundwater withdrawals in excess of 100,000 gallons per day in
a designated capacity use area) and the Coastal Area Management
Act of 1971 (development in designated Areas of Environmental
Concern).

The scope of federal jurisdiction over peat mining
activities is established by the Clean Water Act (NPDES
permitting of wastewater discharges, which is administered by
the state, and Section 404 dredge and fill permitting
administered by the U.S. Army Corps of Engineers), the Clean Air
Act, the National Environmental Policy Act, and the Endangered
Species Act.

Possible county responses to peat mining include local
environmental impact statements, adoption of land use ordinances
requiring county mining permits, and severance taxes (if
authorized by state enabling legislation).

3.2 Alternatives

3.2.1 No Change

The no change alternative assumes that no peat mining
occurs on the permitted area and that the area is not developed
further for any other use during the 20-year period of study.

3.2.2 Scenario #1: Currently Permitted Acreage

Scenario #1 is based as much as possible on the plans of
peat mining permit holders or companies that have submitted peat
mining applications for land located in the study area. When no
specific plans were available for a particular aspect of the
scenario, "reasonable" assumptions were made.

In this scenario, 22,690 acres are permitted for peat
mining and 17,360 acres are actually mined in two areas over a
period of 20 years (see Figures 5A and 5B). By year 20, 12,480
acres have been reclaimed, primarily to row crop agriculture
requiring pumping (to maintain acceptable canal water levels).
Ten percent of the reclaimed land has been re-established to
native vegetation and 10% has been reclaimed to low intensity
managed forests (pine plantations).

Minimum elevations of mined areas range from 1 to 12 feet
above mean sea level, depending on original surface elevation
and depth of the peat deposit.

Annual volume of peat mined in Scenario #1 (Areas 1 and 2)
averages 665,000 dry tons, or 1.1 million tons at 40% moisture.
Seventy-five percent of this peat is converted to methanol, 21%
is exported as peat for industrial use (as fuel), and 4% is
exported as horticultural peat.

3.2.3 Scenario #2: Upper Boundary

Scenario #2 assumes that most peat deposits greater than or
equal to four feet in depth in the study area are mined during
the 20-year period (see Figures 5F and 5G). Exceptions are
deposits within one-half mile of open water.
Four mining areas are outlined based on drainage
characteristics and geographical location. Areas 1 and 2 of this
scenario are expansions of Areas I and 2 in Scenario #1. Areas 3
and 4 of Scenario #2 are areas for which no mining permit
applications have been submitted to date, but in which
substantial peat deposits are located.

Scenario #2 is based entirely on assumption and does not
represent the stated plans of any peat mining industry or
landowner in the study area.

By year 20, 84,000 acres have been mined and 68,600 acres
reclaimed, primarily to row crop agriculture requiring pumping
and to open water. At least 10% of each area has been reclaimed
to native vegetation and at least 10% to low intensity managed
forest (pine plantations).

Minimum elevations of mined areas range from 4 feet above
to 9 feet below mean sea level, depending on surface elevation
and depth of the peat deposit.
Annual volume of peat mined in all four areas of Scenario
#2 averages approximately 2.1 million dry tons (3.5 million tons
at 40% moisture) at year 10 and 6.6 million dry tons (11 million
tons at 40% moisture) at year 20. By year 20, 63% of the peat
mined is being converted to methanol, 35% is exported as peat
for industrial use (as fuel), and 2% is exported as
horticultural peat.

3.2.4 Scenario #3: Industry Failure

Scenario #3 is based on Scenario #1, with assumptions for
years 1 through 10 identical in the two scenarios (see Figures
5B and 5H). In the third scenario, however, the peat mining
industry fails at year 10. Acreage mined through year 8 is
reclaimed according to schedule, but acreage mined in the last 2
years is abandoned. All pumping ceases at year 10, and by year
20, all mined and reclaimed acreage has flooded.

The course of events outlined in Scenario #3 between years
11 and 20 is based entirely on assumption.

3.3 Primary Environmental Impacts of the Alternatives

3.3.1 Amount of Runoff

In all scenarios, runoff from a 2,000-acre mining block
will increase from 1,046 million gallons per year (mgy) to 1,336
mgy during mining, and then decrease to 808 mgy on lands
reclaimed to agriculture.

In Scenario #3, between years 11 and 20, drainage ditches
will become clogged with sediment and debris. All mined acreage
will gradually become flooded, remaining open water or becoming
swamp. Total annual runoff for both areas (Scenario #3) by year
20 will be roughly equivalent to rainfall minus lake
evaporation. When the water level of the lakes becomes high
enough, the runoff will flow overland in a direction determined
by the slope of the land.

3.3.2 Wastewater Discharges

Wastewater discharges from the methanol. plant (Area 1) in
Scenario #1 will average 870,000 gallons per day. Discharges,
will be the same in Scenario #3, but will cease at year 10.

Average daily wastewater discharges from methanol plants in.
Area 1 and 3 (Scenario #2) will reach 3.1 to 4.1 million gallons
per day by year 20.

3. 3. 3 Groundwater

For all scenarios, in areas where peat is removed,
groundwater levels will decline by the depth of peat mined.
Re-establishment of vegetation will cause the groundwater level
to drop an additional foot. 'In Scenario #3, surficial
groundwater levels will return to pre-mining conditions
following failure of the industry and cessation of pumping.

No perceptible change in recharge to the Castle Hayne
Aquifer will occur as a result of peat mining in the permitted
areas in any scenario.

No significant lateral movement in the fresh/saltwater
interface in the aquifers underlying any area of the scenarios
will occur as a result of mining or processing operations.

In Scenario #2, Area 1, localized upconing of brackish
water may occur at production wells if groundwater is withdrawn
from the Castle Hayne Aquifer. In Area 3, localized upconing of
brackish water may occur at production wells if groundwater is
pumped from the Yorktown or Tertiary Sand Aquifer.

3.3.4 Hurricane Flooding

Area 1 (all scenarios) is not susceptible to flood
inundation caused by wind tides having a 1% chance of being
equalled or exceeded in any one year (see Figure 5D).
Approximately 50% of Area 2 (all scenarios) is susceptible to
such flooding in the absence of protective barriers.

For Areas 3 and 4 (Scenario #2), approximately 75% and 100%
of the land area, respectively, is susceptible to flood
inundation caused by wind tides having a 1% chance of being
equalled or exceeded in any one year (in the absence of
protective barriers).

3.3.5 Air Quality
State air quality standards for particulates will not be
exceeded by the mining or processing operations in any of the
scenarios if adequate buffer strips and appropriate spacing of
methanol plants (as determined by computer simulations) are
instituted and necessary mitigative measures are used.

3.3.6 Solid Waste
In Scenario #1 (and Scenario #3 through year 10),
approximately 851,000 cubic feet per year of non-hazardous waste
and 1,000 cubic feet per year of hazardous waste will be
generated in Area 1. Mining operations in Area 2 will not
generate any significant amount of waste material.
In Scenario #2, approximately 7 million cubic feet per year
of non-hazardous waste and 8,200 cubic feet per year of
hazardous waste will be generated by year 20 in Areas 1 and 3.
Mining operations in Areas 2 and 4 will not generate significant
amounts of waste material.

3.4 Cumulative Environmental and Economic Impacts of the
Alternatives

3.4.1 Agriculture
Net annual income (minus drainage cost and based on the
prices stated in the assumptions in section 6.1.1.1.1) resulting
from reclamation of mined lands to agriculture in both areas of
Scenario #1 is estimated at $232,000 - $677,000 at year 20. in
all four areas of Scenario #2, net annual income from row crop
reclamation of mined lands is estimated at $1.1 - $3.3 million
at year 20. For both areas in Scenario #3, increased
agricultural production due to reclamation will produce a net
annual income of $36,000 - $107,000 at year 10, after which
pumping ceases and all mined lands gradually become flooded.
Cumulative impacts of the mining projects under Scenarios
#1 and #2 will be a net gain of between $2.9 and $6.9 million or
$9.1 and $22 million, respectively, to the local agricultural
economy over the 20-year period. Under Scenario #3, the local
agricultural economy will lose between $114,000 and $278,000.

3.4.2 Forest Products
The peat mining and reclamation activities outlined in the
scenarios will have no significant negative economic impact on
the forestry production value of the study area. However,
removal of large areas of deep peats will result in the loss of

a significant proportion of the state's prime Atlantic white
cedar habitat.

3.4.3 Fish

Impacts on the fisheries of Area I (all scenarios), will be
related to reduction of stream flows during much of the year in
the canals and low order streams that provide fish habitat in
this area. Accelerated removal of waters in late winter and
spring may limit migration and spawning of some species, but no
significant effects on anadromous species in this area or on the
fisheries of Lake Phelps or Pungo Lake are anticipated unless
greater seepage from the lakes oc-curs or there is increased
sedimentation due to wind blown material. Increased
sedimentation due to wind blown material could be a significant
problem to Lake Phelps since the present level.s of suspended
residue in this lake are extremely low.

Impacts in Area 2 (all scenarios) will be similar to those
in Area 1. Effects on Lake Mattamuskeet fisheries will be
negligible. However, increased freshwater flows to the
Intracoastal Waterway and to Pamlico Sound via the Pungo River
and Albemarle Sound via the Alligator River in periods of high
flows and reduced flows and seepage during low flow periods may
adversely affect estuarine nursery areas. Increased nutrients in
drainage waters and siltation due to high volume water movements
may also impact nursery areas.

Impacts on fisheries due to mining and reclamation
activities in Areas 3 and 4 (Scenario #2) are not known.

The abandonment of mining areas in Scenario #3 will
probably result in the development of fish populations similar
to those of Pungo Lake, depending upon size, depth and quality
of the water bodies created. Abandoned drainage canals may be
used by anadromous and catadromous 1-ish, depending on flows and
the extent of clogging in the canals.

3.4.4 Wildlife

Of the ten species evaluated, pine warblers and hairy
woodpeckers will sustain the greatest overall habitat
degradation (generally 50-60%) under conditions created by the
scenarios. However, both species are relatively common, widely
distributed and tolerant of human activity. Thus no population
of either species will be jeopardized.

The marsh rabbit, widely distributed through the lower
Coastal Plain, will be moderately, though variably, impacted by
peat mining and reclamation activities created by the
alternative scenarios.

Whitetail deer and the great horned owl will be only
.slightly affected by mining activity, except in Area 4 of
Scenario #2, where residential development and open water
reclamation will decrease available habitat.

Species benefitting from the mining and reclamation
activities will include muskrat, bobwhite and mourning dove.

3.4.5 Recreation

Lost recreational hunting value over the 20-year mining
period due to land conversion in Scenario #1 is estimated at
roughly $513,000 (based on a $5.00 value per hunting trip and
assuming that croplands are not accessible to hunters).

For Scenario #2 (all areas) lost recreational hunting value
over the 20-year mining period is estimated at approximately
$2.6 million.

3.4.6 Amount of Surface Water Runoff

The average annual total flow over the 20-year mining
period in Area 1, Scenario #1, will not vary by more than about
5% from the pre-mined condition. A slight steady decline in the
total annual water loss from the area will occur as the
proportion of the area reclaimed in row crops increases.
However, a slight increase in runoff will follow the abandonment
of the large area of temporary evaporation ponds (2550 acres) in
favor of the smaller permanent lake (1450 acres).

In Area 2 (Scenario #1) the initial increase in total
annual flows will be greater than for Area 1 because there will
be no storage lake. Once the maximum disturbed area has been
reached, total flows will level off as the area of reclaimed
land slowly increases. Once all mined acreage has been
reclaimed, the average flow will drop to close to or below
pre-mining levels, depending on crops planted and drainage
systems installed.

In both areas of Scenario #1, the major factor controlling
the occurrence of floods will be the capacity of the pumps
removing water from the canal system to the lakes (Area 1) and
the Intracoastal Waterway (Area 2). If water can not be pumped
into the deep storage available in the lake (Area 1) at a high
enough rate during high rainfall events, the canals may be
breached, causing flooding. However, because of the low lying
aspect of the mi,ied land in relation to the surrounding terrain,
the flooding involved should remain localized for most events.

The lowered elevations due to mining will increase the capacity
to store water on the surface; therefore, the occurrence of
downstream flooding should be reduced from the pre-mining
condition for all scenarios and areas except for Canal B in Area
1. The volume of flow in Canal B (draining Area 1) will increase
throughout the life of the peat mine until all the flow from the
15,000-acre area is routed through the lake to Canal B. The
increased flow in the canal will increase the risk of downstream
flooding as the storage capacity of the canal is reduced. Canal
B will have to be considerably deepened and maintained to ensure
rapid removal of water and to lessen -the risk of flooding.

For Scenario #2, all areas, annual flow during the 20-year
mining period will be less than 3019 above the pre-mining flow.
With the exception of Area 1, the flows will increase with
increased acreage in active mining, then hold relatively
constant until the mining area is gradually reclaimed and flows
decline. In all areas the flow in year 20 will be significantly
reduced from the during mining condition and should be close to
or below the pre-mining flow levels as a result of higher
evapotranspiration and lower flows from the areas reclaimed to
agriculture and forestry. In Area I (Scenario #2) annual flows
will remain closer to the pre-mining condition because of
controlled releases through and evaporation from the lake. Storm
peaks will be substantially reduced, assuming no lake or canal
over-topping.

Residential areas in Area 4 (Scenario #2) will experience
high surface runoff, counterbalancing the flow-reducing effect
of the bodies of water created as part of the reclamation plan
and resulting in annual flows similar to those of Areas 2 and 3.

Annual flows for Scenario #3 will be the same as Scenario
#1 for years 1 through 10. Upon cessation of pumping, canal dams
will be broken and all maintenance of-.' canals and dikes will end,
creating a swamp/lake area covering all mined and reclaimed
areas by year 20. The volume and distribution of runoff from
these areas will depend upon the changing nature of the outlets,
availability of water storage on the surface of mined areas and
the type and density of revegetation. Assuming that the water
levels remain high enough . to satisfy potential
evapotranspiration (PET) at all times, the water available for
runoff will be approximately equal to rainfall minus PET.

3.4.7 Nutrient Yields and Surface WatE!r Eutrophication

The peat mining, methanol production and agricultural
reclamation in the scenarios may have an adverse impact on water
quality. The natural vegetation yields less nitrogen and
phosphorus per unit area than other land uses, usually by a
large factor; therefore conversion to other uses will result in
loss of nutrients to downstream aquatic systems. The lagoons and
lakes into which runoff and effluents run or are pumped will
probably become unacceptably eutrophic. Unless these lagoons and

buffer wetland systems efficiently remove nutrients from the
water as it passes through, there will also be substantial
nutrient loading of the Pungo and Alligator Rivers and
consequent eutrophication.

3.4.8 Trace Element, Pesticide and Coliform Bacteria Yields

Peat mining and subsequent reclamation activities as
described in the scenarios are likely to significantly increase
trace metals, pesticides and coliform bacteria in runoff from
permitted areas. Impacts of such increases presently are not
fully known, but, should they occur, are likely to result from
the cumulative effects of a variety of trace metals, pesticides,
nutrients and other substances.

3.4.9 Groundwater

The alternative scenarios will have a negligible effect on
the recharge and yield of the major aquifers and on the
fresh/saltwater interface. However, the effects of direct
groundwater withdrawals for plant processing and the cumulative
effects of direct withdrawals and peat mining are not known. The
potential exists for saltwater intrusion into areas where peat
is mined close to and below sea level.

3.4.10 Land Use Conversions

The major land use change due to Scenario #2 will be the
loss of large tracts of natural, relatively undisturbed
wetlands. Approximately 41% (84,000 acres) of the wetlands
underlain by peat at least four feet in thickness in the state
will be lost under Scenario #2. The mining of 68,000 acres of
pocosins (undisturbed and disturbed) in Scenario #2 will
constitute a loss of 4.5% of the total remaining pocosins and
7.8% of the undisturbed pocosins in North Carolina. Since the
wetland system of the Albemarle-Pamlico Peninsula constitutes
the state's largest and least disturbed wetland complex, the
elimination of 84,000 acres from this system will be of
significance.

Agricultural land will increase from 9.6% to 28.2% of the
total acreage in Hyde, Tyrrell and Washington Counties by year
20 under Scenario #2.

3.4.11 Air Quality

Fugitive dust emissions during peat mining, transport and
storage will probably be a more serious concern than emissions
from methanol plants because of greater particulate emission
rates, the occurrence of peat harvesting in all areas (Scenaric
#2) and the possibility of emissions immediately adjacent to the
mining area boundary.

The cumulative impacts of multiple source air pollutants
due to expansion of peat mining and processing operations are
unknown.

3.4.12 Solid Waste

Leachates from gasification ashes and slags from the
methanol plants in the scenarios are not likely to exceed EPA
toxicity criteria, due to the relatively low concentrations of
most heavy metals in the source peat.

The high temperature and oxidizing environment of the
gasification stream is unlikely to produce significant amounts
of such substances as tars, oils, phenolics and polynuclear
aromatic hydrocarbons which are the hazardous by-products of
most concern in many synfuels and gasification facilities.

Large volumes of solid wastes will be generated during
conversion of peat to methanol in Scenario #2. Capacity of
potential disposal sites on the Albemarle-Pamlico Peninsula to
handle this volume is uncertain. Inapacts of onsite use of some
of this waste during reclamation to agriculture and forestry are
not known.

3.4.13 Fire

The frequency of small fires will increase if large-scale
peat mining (as de8cribed in Scenario #2) occurs, due to
increased accessibility of the mined areas to human activity.
The larger, less easily controlled fires will decrease in
number, since fewer large blocks of open, undisturbed land will
remain after mining.

3.4.14 Local Economics and Employment

Peat mining and processing as outlined in the alternative
scenarios will lead to increased employment of local workers,
migration of new workers and their families into the study 4rea,
stimulation of local businesses, dE!mand for new businesses and
public services, such as education, and increased employment in
the service sector.

Long-run fiscal problems may arise in cases where a local
government must provide expanded services and facilities but is
unable to tax the new facilities. This is a spillover problem
where new residents locate outside the political boundaries of
the local governments having the power to tax the facility.
Distributional aspects of tax revenues and services required may
create deficits in some cities and counties and surpluses in
others. Even if long-run benefits exceed costs, short-run fiscal
problems may arise where revenues generated lag cost incidence.
To the extent that peat mining adversely affects the
commercial fishing and recreation/tourism industries, the value
of these economic sectors will decline.
Assuming the smaller peat-to-methanol facility described in
Scenario #1 (Area 1) attracts the labor that is available
locally, additional employment required for expanded methanol
production in Scenario #2 will come primarily from migration.
Thus the migrant, new resident and new student impacts will be
larger both absolutely and proportionately under Scenario #2
than under Scenario #1, and fiscal effects noted above will be
magnified.
While an adequate supply of public services and facilities
will probably be available to meet the needs of migrants under
Scenario #1, it is unlikely that this would be the case under
Scenario #2. More public funds would be required to meet these
increased demands for services. This problem will be
particularly acute if construction for the methanol production
facilities in Scenario #2 is not staged.

The expansion of peat mining activity from the level of
Scenario #1 to that of Scenario #2 will attract other related
industries and enterprises that will act to magnify the economic
impacts of the peat mining itself.

Under Scenario #3, following the failure of the peat mining
industry, unemployment will be created proportional to the
increase in employment generated by operation of the peat mining
and processing facilities. Income will be lost by unemployed
mine workers and by workers and businesses serving the basic
mining industry. Fixed facilities (housing, businesses and
public facilities) will become unused unless other economic
activities replace demand lost with the mining facilities.
The extent of the fiscal impacts of Scenario #3 will depend
upon the extent to which local government has expanded the
services it provides. Excess capacity and high costs of
government may result if service construction programs were
accelerated. Other services, such as the number of school
teachers, could be reduced, but this would lead to higher
unemployment and related costs.

Since many services of local government can not be
proportionately adjusted downward once provided, and since many

are funded by long-term debt, the reduction in tax revenue will
be greater than the reduction in costs of government. If this
does occur, the costs of operating local government will rise
unless offset in some other manner. Property taxes will rise
accordingly.

3.5 Summary of Critical Cumulative Environmental and Economic
Impacts and Recommended Approaches

3.5.1 Estuarine Impacts
Large-scale conversion of peatlands to agriculture,
forestry and peat mining on the Albemarle-Pamlico Peninsula will
alter primary nursery areas in peripheral estuarine systems.
Changes in salinity regimes; surface water runoff rates;
nutrient loading; suspended solids; sedimentation; trace
element, pesticide and coliform bacteria levels; . and
interactions among these factors are believed to be the most
significant potential estuarine impacts from land conversion.

The recommended approach includes the initiation of an
integrated, multidisciplinary effort toward developing a
predictive numerical model for use by decision makers in
assessing the impacts of existing and proposed coastal land use
on the state's estuarine resources. Such a model could also be
used to set effluent limitations to meet water quality standards
for primary nursery areas, if such standards were to be
established by the state Environmental Management Commission.

3.5.2 Wildlife

A wildlife habitat simulation was used to analyze the
consequences of large-scale peat min.JLng on the Albemarle-Pamlico
Peninsula. A significant proportion of the currently existing
black bear and bobcat habitat will be lost if extensive mining
takes place.

Field validation of habitat suitability indices for
important species used in the simulation is required. In
addition, linking of the spatial and temporal aspects of the
wildlife habitat simulation model is necessary to enable land
managers to evaluate the impacts of alternative land. use
decisions on wildlife.

3.5.3 Upland Water Management
Extensive peat mining may increase annual runoff from the
mined areas by up to 30% above the pre-mining flow. Annual flows
may decrease or increase slightly from the pre-mining flow,
depending on the crops, as the mined areas are reclaimed to
agriculture and forestry.

Impacts of drainage systems and seasonal pumping on the
location of the fresh/saltwater interface in estuarine areas are
not known.

The cumulative impacts of groundwater withdrawals for peat
processing and drainage from mining sites are not well
understood; however, the potential exists for saltwater
intrusion into areas where peat is mined close to and below sea
level.

Further research is needed in the following areas:
hydrology of undisturbed peatlands; nutrient transformation in
canal and river networks; field measurement techniques and
modeling of surface runoff from actively mined sites; long-term
effectiveness of wetland buffers for filtration of nutrients,
trace elements and sediments and for control of fresh water flow
rate; effectiveness of storage lakes in reducing negative
estuarine impacts of land drainage; and effects of peat mining
on groundwater supplies and the location of the fresh/salt water
interface.

Data from the research recommended above will provide input
to an already existing hydrological model, thus aiding in the
estimation of the effects of alternative upland water management
strategies on surface runoff. The output from this model could
provide input to an estuarine model.

3.5.4 Hurricane Flooding

Approximately one-half to two-thirds of the
Albemarle-Pamlico Peninsula is subject to flood inundation
caused by wind tides having a 1% chance of being equalled or
exceeded in any one year.

Rains associated with hurricanes may accumulate in low
lying areas faster than the capacity of pumps to remove it. Thus
the potential also exists for freshwater damage to crop and
forest land, depending on the duration of the flooding.

The recommended approach is to develop a new series of maps
delineating flood susceptibility based on land elevations that
would exist if substantial peat deposits were removed from the
region. Sediments underlying the peat deposits should be
examined to determine their susceptibility to floodwater
infiltration.

3.5.5 Unique Natural Areas

Large-scale peat mining on the peninsula will be
accompanied by a loss of part or much of the state's largest and
least disturbed wetland complex, and a large proportion of the
area underlain by peat of depths greater than four feet. Some of
these areas contain prime Atlantic white cedar habitat.
Extensive mining will remove a significant proportion of these
unique areas and the biota they support.

A systematic attempt should be made to determine if the
peninsula contains areas that are unique in biological,
hydrological, geological, pedological, chemical or other-natural
aspects and worthy of consideration for preservation or
protection.

3.5.6 Air Quality

3.5.1 Solid Waste

The capacity of potential disposal sites on the Albemarle-
Pamlico Peninsula to handle the volume of non-hazardous waste
that would be created by extensive processing of peat is
uncertain. Additional research on site selection and evaluation
for solid waste disposal is needed.

Impacts of onsite use of some of this waste, for example,
on roadbeds or for agricultural land treatment, are not well
documented, and may pose environmental problems. Further
characterization of the properties of leachates of peat
combustion ashes is needed.

3.5.8 Local Economics

The development of two simulation models is recommended: 1)
a model to address the impact of potential peat mining
facilities on tax rates and revenues and 2) a model to examine
the overall fiscal impacts of peat mining on state and local
government.

3.6 Non-significant Impacts

Elements examined and found to be non-critical included
impacts on recreational hunting, agricultural production, forest
products (with the exception of Atlantic white cedar) and
occurrence of fire.

4. AFFECTED ENVIRONMENT

The environment affected by the alternative peat mining
development scenarios (section 5) extends beyond the three
counties (Hyde, Tyrrell and Washington) in which development was
assumed to occur. This description of the affected environment,
therefore, addresses the entire Albemarle-Pamlico Peninsula,
including Beaufort and Dare Counties, and the sounds (Albemarle
and Pamlico) that bound it on the north, east and south.
Groundwater and air resources, which extend beyond the original
three county study area, are also discussed.

4.1 Biophysical Environment

4.1.1 General Setting

The Albemarle-Pamlico Peninsula is a low lying, tidewater
region bordered by Albemarle Sound to the north, Pamlico Sound
and the Pamlico River Estuary to the south, Croatan and Pamlico
Sounds to the east and the Suffolk Scarp to the west. Elevations
in this area are generally less than 20 feet above mean sea
level, and much of the eastern part of the peninsula is less
than 5 feet in elevation (Heath, 1975). The area is
characterized by poorly integrated coastal streams, deep organic
soils, extensive swamps, marshes and evergreen wetlands, and a
low astronomical tidal range (Lukin and Mauger, 1983).

The peninsula covers 1,978 square miles (1,266,000 acres)
(McMullan, 1984) and includes the largest continuous area of
wetlands in North Carolina (Heath, 1975). Counties located on
the peninsula include all of Hyde, Tyrrell and Washington
Counties, the mainland part of Dare County, and part of Beaufort
County.

Approximately 37% of the five counties' total combined land
and water area is comprised by lakes, rivers, creeks and sounds.
These water bodies, and their intimate intermingling with the
land, have shaped the region's geography and its cultural and
economic development. The most critical environments in the
region occur at the margins between land and water: estuarine
marshes, primary nursery areas, shellfish waters and swamp
forests.

4. 1. 2 Hydrology

4. 1. 2. 1 Streams

Only two major streams on the peninsula region have their
sources west of the Coastal Plain, originating in the Piedmont.
The Roanoke River empties into Albemarle Sound just west of
Plymouth. The Tar River, which becomes the Pamlico River at
Washington, empties into Pamlico Sound. Other major streams in
the areas are the Pungo, Scuppernong and Alligator Rivers. These

are short coastal plain streams that become estuaries in their
lower reaches. Numerous short, slow flowing coastal tributaries
empty into these rivers (Lukin and Mauger, 1983).

Prior to the construction of canals in the area, overland
runoff was a major factor in the water budget. Although
long-term streamflow data are scarce, overland runoff may be
estimated as the difference between precipitation and other
water budget items (Heath, 1975):

Outputs Inputs

Precipitation 51.0 inches
Evapotranspiration 36.0 inches
Groundwater discharge 0.5 inches

------------
Subtotal 36.5 inches

Overland runoff 14.5 inches
(estimation by
difference)

Overflow runoff probably moved north from Lake Phelps to
the Scuppernong River and from Lake Mattamuskeet north to the
Alligator River prior to construction of an extensive system of
canals and ditches (see Figure 4A).

4.1.2.2 Lakes

The peninsula is the site of several lakes: Lake Phelps, on
the Washington-Tyrrell County line; Pungo Lake, on the
Washington-Hyde County line; and New (Alligator) Lake and Lake
Mattamuskeet in Hyde County (see Figure 2A). Lake Mattamuskeet
is the largest of these with a surface area of 66.7 square miles
(Coastal Zone Resources Corp., 1976). These lakes are very
shallow; average depths range from 2.5 to 5 feet. Lake
Mattamuskeet and Pungo Lake are now National Wildlife Refuges;
Lake Phelps is part of Pettigrew State Park (Lukin and Mauger,
1983).

All four lakes have been modified by drainage systems and
the levels of Phelps and Mattamuskeet are regulated. The lakes
are isolated from surface inflow and receive water only through
rainfall. They accumulate fine organic sediments from dust blown
in from the surrounding land and ash from occasional forest and
ground fires. No water quality problems in either lake have been
reported.

KEY
Natural.d
dl Ijo
Overland runoff
Overflow from ALIBEMARLE SOIJND
71
lakes

,eL

10 Miles

FiRure 4A: I)rainaize dIvIdes and probable Daths of overland runoff prior to artifinial drninagp
(adapted from Heath, 1975)

4. 1. 2. 3 Sounds

4.1.2.3.1 Albemarle Sound

Albemarle Sound covers an area of approximately 480 square
miles and contains some 233 billion cubic feet of water. The
sound is a drowned river valley estuary with an average depth of
less than 18 feet and a maximum depth of 30 feet. The central
portion of the sound from Edenton to the Alligator River
contains a broad, flat-bottomed trough with depths in excess of
18 feet. Seaward of the Alligator River, the depth of the sound
decreases. Textures of bottom sediments grade from predominantly
clays in the trough to fine sands along the flanks and the lower
portion of the sound (Pels, 1967).

Outflow from Albemarle Sound enters Pamlico Sound through
Croatan and Roanoke Sounds, where it discharges into the ocean
through Oregon, Hatteras and Ocracoke Inlets. The range of
semidiurnal astronomic tides throughout Albemarle Sound is less
than 0.5 feet due to the remote connection of the sound to the
ocean, combined with freshwater outflow. The periodic tide range
is somewhat greater in estuarine tributaries due to funneling
effects of decreasing dimensions in an upstream direction (Lukin
and Mauger, 1983).

Short-term, wind-driven currents dominate flow and water
levels in Albemarle Sound and the adjoining open water areas of
Croatan and Roanoke Sounds. The seasonal range of water levels
induced by wind-driven currents on Albemarle Sound is about 0.8
feet near Edenton at the mouth of the Chowan River (Daniel,
1977). Wind-induced current velocities ranging from 0.5 knots to
1.6 knots in Croatan and Roanoke Sounds have been measured
(Singer and Knowles, 1975, cited by Lukin and Mauger, 1983).

Net flow into Albemarle Sound is dominated by freshwater
inflow because the effects of winds blowing from various
directions tend to cancel each other out over time. Average
inflow to Albemarle Sound is about 17,000 cubic feet per second,
draining from a total area of about 18,359 square miles. The
peninsula accounts for only 4% of the drainage basin. The
average period required for water stored in Albemarle Sound to
be completely flushed and replaced by fresh water is about five
months (calculated from hydrologic data in Giese et al., 1979,
by Lukin and Mauger, 1983).

Periods of high freshwater inflow to Albemarle Sound
usually reflect the typical peak flow period of many North
Carolina streams, with maximum average freshwater inflow in
February and minimum freshwater inflow in October (Lukin and
Mauger, 1983).

Average surface salinities are lowest in March following
high freshwater inflow from January through March. Surface
salinities reach a maximum in December following low freshwater
inflow and high evaporation from June through September (Lukin
and Mauger, 1983).

Various water quality problems have occurred in the
Albemarle Sound system. Severe eutrophication has occurred in
the Chowan River, which empties into the sound. Red sore disease
has occurred periodically throughout Albemarle Sound. Early
signs of general eutrophication are occasionally detected in the
western portion of the sound; such signs include elevated
phytoplankton cell counts and species ratios, water
discoloration and elevated nutrient levels.

4.1.2.3.2 Pamlico Sound

Pamlico Sound covers an area of approximately 2,060 square
miles and contains 920 billion cubic feet of water. It is the
largest sound formed behind a barrier island strand on the
Atlantic coast of the United States (Giese et al., 1979, cited
by Lukin and Mauger, 1983). The sound has an average depth of 16
feet and contains a "y"-shaped basin with maximum depths of 26
feet at the confluence of the Neuse and Pamlico Rivers. A
broader basin with a maximum depth of 24 feet occurs in the
central portion of the sound. A central lagoon shoal separates
the two basins and extends across Pamlico Sound from Ocracoke
Inlet to Bluff Point (Lukin and Mauger, 1983).

Pamlico Sound is connected with the ocean through Oregon,
Hatteras and Ocracoke Inlets. This limited access, combined with
the broad expanse of the sound, results in astronomical or ocean
tides being significantly dampened. The mean periodic tide range
within Pamlico Sound is approximately 0.2 feet. Periodic tide'
range is considerably greater in the narrow river-estuaries
tributary to Pamlico Sound, due to the funneling effect of
decreasing dimensions in the upstream direction (Roelofs and
Bumpus, 1953 and Giese et al., 1979, cited by Lukin and Mauger,
1983). For example, the mean periodic: tide range at the mouth of
the Pamlico River is about 0.5 feet and increases to
approximately one foot at Washington. Wind-driven currents
dominate flow and water levels in the sound and adjoining
estuaries (Giese et al., 1979 and Singer and Knowles, 1975,
cited by Lukin and Mauger, 1983). The large surface area of
Pamlico Sound encourages wind setup over long fetches (Lukin and
Mauger, 1983).

Average annual inflow to Pamlico Sound is about 31,700
cubic feet per second, which drains from a total area of 28,820
square miles, less than 3% of which is on the peninsula.
Residence time of water in Pamlico Sound is about 11 months.
Maximum average freshwater inflow to Pamlico Sound occurs
between January and April, with the highest freshwater inflow in
February. Minimum net freshwater inflow does not occur in

September, October and November, as is the case for many North
Carolina streams, but in June, when evaporation rates are
greatest. Evaporative water loss resulting from the large
surface area and relatively low freshwater inflow rates are
significant factors in the annual gross water budget (Giese et
al., 1979, cited by Lukin and Mauger, 1983).

Surface salinity in Pamlico Sound tracks seasonal
variations of freshwater inflow, but short-term, wind-induced
currents may obscure seasonal salinity variations (Woods, 1967
and Giese et al., 1979, cited by Lukin and Mauger, 1983).
Average surface salinities are lowest in April, following peak
freshwater inflow. Surface salinities reach a maximum in
December after a period of low freshwater inflow in the fall.
Seasonal surface salinity differences of 4 to 6 parts per
thousand (ppt) are observed at the mouths of major estuaries,
while seasonal salinity fluctuations of 0 to 2 ppt are observed
in the vicinity of ocean inlets (Giese et al., 1979, cited by
Lukin and Mauger, 1983). Salinities in the sound rarely exceed
15 ppt except near inlets.

.Over one-third of the sediment reaching Pamlico Sound is
transported by the Neuse and Tar-Pamlico Rivers. Local shoreline
erosion is an even larger source of sediment. Erosion rates up
to 20 feet per year have been observed (Stephen B. Benton,
Office of Coastal Management, NRCD, personal communication).

Like Albemarle Sound, Pamlico Sound shows some signs of
incipient eutrophication, particularly in some of the tributary
estuaries, which receive a nutrient load that is part natural
and part man-induced. Agriculture and phosphate mining introduce
significant amounts of nutrients, particularly phosphate, into
the system.

4.1.2.4 Groundwater

Sand layers in Quarternary sediments serve as the primary
source of water supply in Dare County and are of importance to
shallow draw throughout the region, particularly in Hyde County
(Nelson, 1964). Sand and limestone layers in the Yorktown
Formation of Pliocene age are the principal source of water
supply in Hyde and Tyrrell Counties and are important for
Washington County as well. The Castle Hayne Formation of Middle
Eocene age (Jones and Sholar, 1981) is the primary source of
water supply in Washington County and the northwestern part of
Hyde County (Nelson, 1964).

Under the peninsula lie the cones of depression caused by-
two very large groundwater withdrawals: Texasgulf's phosphate
mines at Aurora, just south of the peninsula, and Union Camp at
Franklin, Virginia. Effects from Texasgulf's withdrawals from,
the Castle Hayne Aquifer have been detected as changes in the
potentiometric surfaces in much of the eastern peninsula. Union
Camp withdraws water from the Cretaceous Aquifer. No interaction
between these cones of depression has been detected. Clay and
silt layers act as aquitards, separating the aquifers. There is
no evidence that any portion of the study area serves to
recharge either the Castle Hayne or the Yorktown Aquifer (Bill
Jeter, Division of Environmental Management, NCRD, personal
communication).

4.1.2.5 Artificial Drainage

Drainage projects aimed at lowering the water table and
removing surface water in peatlands on the Albemarle-Pamlico
Peninsula have been undertaken to enhance agricultural and
lumbering operations since the late 1700s. The history of
drainage practices on the peninsula 'has been documented by Heath
(1975), Lilly (1981), Richardson (1981, 1983) and McMullan
(1984).

Since World War II, development of swamp lands for forestry
and agriculture in coastal North Carolina has continued. By the
1960s, paper companies owned most of the coastal swamp land not
in public ownership. Clark (1981) has estimated that
approximately 100,000 acres of wetlands have been cleared and
drained or recleared and redrained on the Albemarle-Pamlico
Peninsula within the past 15 years.

Drainage pattern alteration on the peninsula began in the
late eighteenth century, and a widespread system of canals,
ditches and associated roads had been developed in the area by
1970. Large-scale clearing and ditching of forest and evergreen
wetlands by the corporate farm industry since 1973 have resulted
in significant additions to this artificial drainage system
(Lukin and Mauger, 1983).

Main canals are spaced about one mile apart. The material
excavated from these canals is used as roadbed fill. Collector
ditches are then dug at right angles to the main canals.
Finally, smaller v-shaped field ditches are dug at right angles
to the collector ditches at intervals of 150 to 350 feet. In an
idealized situation, approximately 16 to 20 miles of field
ditches and 3 miles of collector ditches drain each square mile
.of land (Lukin and Mauger, 1983).

Studies of effects of development on regional hydrology and
runoff water quality are few. However, available data suggest
that peak runoff rates occur earlier and are three to four times
higher on developed than on undeveloped lands. Average water
table depths measured by Skaggs et al. (1980) were about 9
inches deeper on developed organic soil than on undeveloped
organic soil (Lukin and Mauger, 1983).

In eastern Hyde County the drainage system has apparently
allowed saltwater intrusion into agricultural lands, although
the area affected is relatively small. The intrusion is related
to wind tides and the lack of flow control structures on outfall
canals. Storm tides are a more significant source of flooding:
in 1954, Hurricane Hazel flooded about half of the study area
with saltwater.

The effect of freshwater flow from artificial drainage
canals into primary estuarine nursery areas has become an issue
of increasing concern in recent years. Freshwater intrusion into
primary nursery areas was recognized as the most critical
environmental problem in the coastal region by the Governor's
Coastal Water Management Task Force (1982).

4.1.3 Fishery Resources

4.1.3.1 Marine Fisheries

Pamlico Sound and its tributaries contain the most
important fisheries resource in North Carolina. The sound itself
is a major commercial fishing ground, and the primary nursery
areas around its fringes are essential to commercially important
fish and shellfish species. The same species, with a few
exceptions such as the menhaden (Brevoortia tyrannus), bay
anchovy (Anchoa mitchilli), and silver perch (Bairdiella
chrysur support both commercial and recreational fisheries in
the sound. These include: brown shrimp (Penaeus aztecus), white
shrimp (P. setiferus), pink shrimp (P. duorarum), blue crab
(Callinectes sa2idus), oyster (Crassostrea virginiqa), spot
(Leiostomus xanthurus), croaker (Micropogonias undulatus), red
drum (Sciaenops ocellatus), weakfish (Cynoscion. regalis),
spotted seatrout (Cynoscion nebulosus), bluefish (Pomatomus
saltatrix), striped mullet (Mugil cephalus), southern flounder
(Paralichthys lethostigma), and summer flounder (Paralichthys
1!1@atu@s (Birkhead et al., 1977; Copeland et al., 1983; Hester
and Copeland, 1975; and others).

4.1.3.2 Freshwater Fisheries

Freshwater areas on and around the peninsula support.
smaller commercial and recreational fisheries than does Pamlico
Sound, but these fisheries are nevertheless significant.
Recreational fishing overshadows commercial fishing for most.
species, but the white perch and eel fisheries are economically
important. Important freshwater species of the region include:
white perch (Morone americana), catfish (Ictalurus spp.),
bluegill (Lepomis macro@3-h-irus), other sunfish (Lepomis spp.),
largemouth bass (Micropterus salmoides), eel (Angu-lla,.
rostrata), and crappie (Pomoxis spp.)

4.1.3.3 Anadromous Fisheries

A variety of important anadromous species characterizes the
drainage systems of the study area. The major rivers (Chowan,
Roanoke) and large creeks have historically supported large runs
of these fish. Some anadromous fishes now spawn in artificial
drainage canals. Species present include: blueback herring
(Alosa aestivalis), alewife (Alosa pseudoharanqu ), striped bass
(Morone saxatilus), American shad (Alosa sapidissima), hickory
shad (Alosa mediocris), and Atlantic sturgeon (Acipenser
oxyrhynchus) (Hassler et al., 1981; Johnson et al., 1977, 1979;
Street, 1982; Street et al., 1975).

The striped bass populations in this region, and along the
entire Atlantic coast, appear to be declining, possibly in
response to water quality problems.

4.1.4 Soils and Farmland

Soils of the area can be divided into two main groups,
depending on their location. Those soils east of the Suffolk
Scarp are the youngest and most poorly drained. Broad, flat
interstream areas have combined with impermeable underlying
sediments to create conditions favorable for slow water runoff
and eventual accumulation of organic matter. Extensive
swamplands occur in this area. Soils west of the Suffolk Scarp
tend to be better drained because of higher elevations and have
better developed drainage patterns (Governor's Coastal Water
Management Task Force, 1982).

Soils are predominantly sandy with firm subsoils, but
clayey and silty textured soils are also commonly found. organic
soils (histosols) have formed in swampy areas where organic
matter accumulation has occurred. (Governor's Coastal Water
Management Task Force, 1982). Deep organic soils cover much of
the peninsula. In the three-county study area, over 100,000
acres are covered by organic soils deeper than four feet.

Agricultural statistics indicate that 206,730 'acres of
cropland were harvested on the peninsula in the 1979-80 season:
83,280 acres in Washington County, 77,100 acres in Hyde County,
45,440 acres in Tyrrell County, and 900 acres in Dare County
(Lukin and Mauger, 1983).

4.1.5 Forests

Between 1963 and 1973, commercial forest lands on the
northeastern Coastal Plain of North Carolina decreased by more
than 3%. More than half of this loss of forested areas was a
result of conversion to agricultural land, primarily in those
counties south of Albemarle Sound (Lukin and Mauger, 1983).

Forests on the peninsula cover 729,000 acres, about 70% of.
the total area. Most of the forested areas occur on deep organic
soils and fall into six classes in two major groups:

Upland Forests
Deciduous Forest Land: oak, hickory, tulip poplar
Evergreen Forest Land: peninsular upland pine forests,
broadleaf-evergreen dominated forest, managed pine
plantations
Mixed Forest Land

Forested Wetlands
Swamp Forest: gum-cypress swamps,, mixed hardwood
bottomland swamps, Atlantic white cedar swamps, some
pine-hardwood swamps, "high brush swamps"
Evergreen Wetland: pond pine and broadleaf.evergreens
(bays and wax myrtle), pocosins, shrub bogs, bay
forests, pond pine forests
Disrupted Grass and/or Shrub Wetland: some pond pines,
'grouped with forest lands because they were produced
by alteration of evergreen forests and will revert to
evergreen forests if no further disruptions occur
(Lukin and Mauger, 1983)

4.1.6 Mineral and Energy Resources

4.1.6.1 Phosphate

The most economically valuable mineral resource in the
North Carolina coastal region is phosphate, occurring as
carbonate fluorapatite in the Pungo River Formation of Middle
Miocene age. This formation underlieS much of the outer Coastal
Plain north of the Neuse River. Phosphate is mined in central
Beaufort County, on the south shore of the Pamlico River. It is
not mined on the Albemarle-Pamlico Peninsula because of the
depths at which the phosphate deposits lie in the subsurface.

4.1.6.2 oil and Gas

Oil and gas have been sought in 42 exploratory wells on the
peninsula in the past 37 years, but none has been found. Oil and
gas activity on the outer continental shelf 50 miles east of the
peninsula may eventually lead to pipeline construction, but no
such activity is currently planned.

,4.1.6.3 Peat

The only potentially valuable energy resource in the
coastal region is a generally fine grained, highly decomposed
black peat (Ingram and Otte 1981, 1982). Extensive peat deposits
occur in North Carolina, the largest of which are located on the
Albemarle- Pamlico Peninsula. The peninsula contains
approximately 278 million dry tons of peat over an area of about
582 square miles (373,000 acres). The peat deposits occur in
shallow depressions to a depth of 10 feet and in narrow former
stream channels to a depth of 16 feet (Ingram and Otte, 1982).

Peat deposits are associated primarily with the Alligator
River drainage system. Thick peat occurs along both shores.
Peat-filled tributaries extend eastward into Dare County,
southward into Hyde County and westward into Tyrrell County,
where the peats of the Southwest Fork of the river are very
extensive, spreading west and south in the vicinity of Lake
Phelps (see Figure 4B).

The peat is generally sapric and moderately to highly
decomposed. Ash content is generally low (6-10 percent average),
as is sulfur (less than 0.5%). Stumps and logs occur frequently,
especially in the thicker peat deposits (Ingram and Otte, 1982).

The peats of the peninsula yield approximately 10,000 Btu's
per pound (moisture free) and could provide almost 6 quadrillion
Btu's of energy value if mined completely and used efficiently.
This amount could meet the state's thermal needs for almost 4
years at 1980 consumption levels (calculated from Ingram and
Otte, 1982 and Harwood and McMullan, 1981, by Lukin and Mauger,
1983).

4.1.7 Wildlife

The Albemarle-Pamlico Peninsula contains rich and abundant
wildlife resources as a result of the high quality and diversity
of available habitat. The broad floodplains of the Roanoke,
Pamlico-Tar and Alligator Rivers transecting the area, the vast
estuarine marshes and the low flatlands that were historically
the floor of the Atlantic Ocean create a mixture of ecological
systems unsurpassed in richness, diversity and complexity
anywhere in the state.

4.1.8 Parks, Refuges and Natural Areas

Major portions of the peninsula are publicly owned and
managed (Figure 4C). There are national wildlife refuges at
Pungo Lake, Lake Mattamuskeet, and Swanquarter. In March, 1984,
120,000 acres of land in Dare and Tyrrell Counties were donated
to the federal government to create the Alligator River National
Wildlife Refuge. Lake Phelps is a state park. Gull Rock State
Gameland is managed to conserve wetlands and bear habitat. The
Air Force Bombing Range in Dare County, while not a refuge, is
managed to conserve natural habitat and is closed to hunting. A
large portion (27,000 acres) of the bombing range is pending
entry in the N. C. Natural Heritage Registry and will be managed
by the Air Force to preserve large examples of three types of
pocosin communities.

+
+

LO
OF fC/ y

NZ,

AM ......
J ON

ISOPACH MAP OF PAM
2 ff INCkness int"Wal.
mark Gainers of arlhe
Names of maps are

r
Figure 4B: isopach map of peat on the Albemarle-Pamlico Peninsula (from Ingram and 0

ALREMARtES

Ole z

Wash,ngt6nCo-ty
------ ----
B-f.a c-'y T- C-n,@

C',

N-
Lik, t

US 264

A, Mgt
El StaLe

Fede
,4,4t,CO R,tER
7

Clear

Half

Figure 4C: State and federal lands on the Albemarle-Pamlico Peninsula

The peninsula has recently been inventoried for potential
natural areas. Such areas were identified and described on the
basis of: 1) relative lack of disturbance, 2) quality of
botanical assemblage, and 3) size (McDonald and Ash, 1981;
Peacock and Lynch, 1982a and 1982b; Lynch and Peacock, 1982a and
1982b).

4.2 Socioeconomic Environment

4.2.1 Population

The region is sparsely populated, with a few small cities
and towns. In the three-county study area the population is
aggregated in areas of good farmland and along the shoreline in
towns originally settled as fishing ports. A long-term trend of
population loss in Hyde and Tyrrell Counties and very slow
growth in Washington County was apparently reversed in the past:
decade. Even so, the regional growth rate of +5.1% is only
one-third of the state growth rate of +15.5% for 1970-80. (See
Figure 4D for comparison of these counties with the rest of the
coastal region.)

4.2.2 Employment

Agriculture, forestry commercial fishing and shellfishing
and recreational industries have traditionally dominated.
economic activity, and therefore employment, on the peninsula.
Although such employment remains economically significant,
particularly in terms of income, the composition of the labor
force in the area is shifting toward employment in the
industrial and service sectors (see Table 4A). This shift has
been coupled with increased commuting to work in adjacent
counties.

4.2.3 Income

Median family and personal income fall below the state
medians in all three counties (Tables 4B and 4C).

4.2.4 Economic Sectors

Commercial fishing in Hyde, Tyrrell and Washington Counties
in 1980 produced fish and shellfish worth $4.5 million (Table
4D) and $49.4 million in the counties bordering on Pamlico
Sound. (Not all seafood landed in these counties was caught in
Pamlico Sound.) In the three counties, this compares to
agricultural products worth $42.3 million and estimated 1982
forestry output worth $3.9 million (Alex Dowdell, Div. Forest
Resources, NRCD, personal communication).

5,829 11,089
VA. (58.0%)
C, o
:21 ')Gates
4,368',._ 8,875
(4.40/.) '-@44.11%
/'Hertford 0?
C, 28@46
8ertie NI 486 (&1%)
io,
21,024 2,!558 (@1@3.6-6)
(2.4%) Is
'o Yrr I are
.oe-j, /1?25,948
It .j-@Q0-1%14@4,7863 13377
(4.9%) 114AP (5.3%
-,.--'40 266 k
Pitt Beaufo ly.9%) L 5 73
83 1 d 0 (5.4 %)
(1@,5
.?a
L)

71,043
>
ILenoir
,L59819 t \Craven 1 10,398
(@A%-@" @Panrllic (9.8%)
9)705
(0.8%)
1 40,952 Jones
(7.7%) Y-
Ouplin (9.4%) LI--- feT
i Onslow Ca(W

30,448 22,2-15 41,092
(15%) Of (22.4%) (30.0%)
Bladen Pander
% %@, %

Columbus New Hanover
51,037 103,471
(8.7%) 1--/
C, (24.7%)
j Brunswick
IrJ 35,7 7
(47.7%)

Figure 4D: Total population, 1980, and percentage change in total population,
1970-1980

Table 4A: Employment summary by industry groups by county,
1960, 1970

Hyde Tyrrell Washington
1960 1970 1960 1970 1960 1970

Total Employed 1,686 1,699 1,354 1,220 4,088 4,679

Agriculture/
Forestry/
Fisheries 44.7 26.0 27.7 18.4 16.9 9.8

Construction 5.3 10.0 6.7 11.7 .3.8 5.9

Manufacturing 10.3 17.4 20.0 19.9 17.2 42.4

Transportation/
Communication/
Utilities 3.3 4.5 3.1 1.9 2.2 2.2

Wholesale Trade/
Retail Trade 13.0 13.5 16.5 16.7 15.8 13.9

Services - 6.8 - 8.0 - 8.5

Education 5.1 10.1 7.0 10.3 3.1 5.8

Government 4.4 25.1 2.0 18.4 3.4 13.0

Source:
U.S. Census of Population, 1960 General Social and Economic
Characteristics, North Carolina Table 85, 1960. U.S.
Census of Population, 1970, General Social and Economic
Characteristics, Table 123.

Table 4B: Median family income by county, 1960,1970

1960 1970

Median Families Median Families
Family Below Family Below
Income Poverty Income Poverty
Line Line

Hyde $1,979 N.A. $4,430 33.5
Tyrrell 1,927 N.A. 4,307 37.9
Washington 3,495 N.A. 7,152 23.7

North Carolina $3,956 N.A. $7,770 16.5

Note:
N.A.=not available
Source:
Local Area Personal Income, South East Region, U.S.
Department of Commerce, Bureau of Economic Analysis

Table 4C: Per capita personal income by county, 1970, 1975, 1977

Per Capita Personal Income
1970 1975 1977

Hyde $2,204 $3,612 $3,901
Tyrrell 2,046 3,589 4,358
Washington 2,710 4,096 4,946

North Carolina $3,200 $4,940 $5,916

Source:
Local Area Personal Income, South East Region, U.S.
Department of Commerce, Bureau of Economic Analysis.

Table 4D: Commercial fishing vessel licenses, pounds landed
and dockside value by county 1975-1980*

Commercial
Vessel
Pounds Dockside Value Licenses
1975 1980 Change 1975 1980 Change 1975 1.980 Change
(000s) (000s) % (000s) (000s) % (000s) (000s)

Hyde 3,204 13,056 307.5 770 4,182 443.1 448 415 -7A
Tyrrell 766 976 27.4 143 228 59.4 143 113 -21.0
Wash- 604 532 -11.9 88 100 13.6 254 263 3.5
ington

NC 72,326 153,805 112.7 16,409 61,390 274.1 17,776 18,268 2.8

* The figures do not include menhaden landings

Source:
Division of Marine Fisheries, NRCD, "Annual Statistics on Fish Landings"

There is little current manufacturing in the three
counties: two small garment operations and numerous small.
agricultural processors and supplies. Large industrial paper and
textile operations are located in Beaufort and Martin Counties;
adjacent to the study area. There is no large scale chemical or
electrical facility in the region or any of the adjacent:
counties.

4.2.5 Transportation Infrastructure

Highway access on the peninsula is generally good east-west
and limited north-south. The north-s-Duth highways (NC 32, 45, 94
and 99) are utilized primarily by local traffic and are not
heavily traveled (Cribbins, 1983).

Water access is very good: the peninsula is bisected by the
Intracoastal Waterway and surrounded on three sides by water.
Barge terminals of varying quality exist in Belhaven, Columbia,
Edenton and Plymouth. Lack of shoreside loading equipment,
limited depth of approach channel or turning basin and
inadequate storage area are characteristic of some of these
facilities (Cribbins, 1983).

Rail access is available only at the western end of the
peninsula. Dare, Hyde and Tyrrell Counties have no rail service
(Cribbins, 1983).

No petroleum product pipelines exist in the region and
natural gas service is not available in Dare and Tyrrell
Counties (Cribbins, 1983).

4.3 Legal-institutional Environment
This section reviews the governmental setting in which the
proposed peat mining will take place, the major regulatory
controls available to mitigate any adverse environmental
consequences of mining and possible responses of the affected
local governments.

4.3.1 Local and County Government
Washington and Hyde Counties have commission-manager
governments. Tyrrell County is run directly by a board of
commissioners; the chief executive officer is the county
finance officer. Washington and Hyde maintain planning officers.'
All three counties participate in land use planning through the
state Coastal Area Management Act (CAMA). Each county has a
single unified school district.
The only incorporated towns on the peninsula are Plymouth,
Creswell, Roper and Columbia. Each has a mayor-council
government. Plymouth has its own planning department. Plymouth,
Roper and Creswell have zoning ordinances; the counties and
Columbia do not. There are no special taxation districts on the
peninsula.
In Washington County the county acts as a drainage district
to carry out drainage projects, but is organized under Article
3, Chapter 139 of the General Statutes of North Carolina, not
under Chapter 156, which governs drainage districts. Hyde County
contains Fairfield and Grassy Ridge drainage districts, both of
which have been active since 1976. In Tyrrell County the only
active drainage district is Gum Neck.

4.3.2 Major Regulatory Controls

4.3.2.1 State Regulatory Controls

Some exclusively state permits and some federal permits
administered by the state are applicable to peat mining. This
section discusses the former. Federal-state permits are
addressed in section 4.3.2.2.

4.3.2.1.1 Mining Act

The major state regulatory tool for the control of the
environmental impacts of peat mining is the mining Act: of 1971.
(G. S. 74-46 et seq.). This law requires a permit before surface
mining is undertaken, and in order to obtain a permit the
applicant must demonstrate that the mining will not violate ail:
and water quality standards, will not result in substantial.
deposits of sediment in stream beds or lakes, or landslides, and
will not have unduly adverse effects on fish and wildlife. A
reclamation plan is required; a bond must be kept in effect:
until reclamation is complete. The maximum amount of the bond
($50,000) is set according to a schedule established by the
Mining Commission. This is an extremely small per acre amount if:
the state must undertake substantial reclamation efforts or must:
support pumping or maintenance of drainage systems. Since the
maximum amount of reclamation bonds is no longer set by statute,,
the Mining Commission has authority to increase the amount of:
the bonds to make them more adequate on a per acre basis.

Reclamation plans for some of the potentially minable areas
may require that water be perpetually pumped from the reclaimed
land in order for the land to support farming or timbering
activities. A possible legal technique for enforcing this
requirement is through the mining permit and bond requirements..
The Mining Act provisions (G.S. 74-46 through G.S. 74-68), when
read as a whole, appear to comtemplate that reclamation will be
completed within a reasonable time after the conclusion of:
mining activities, and that when reclamation has been completed
in a satisfactory manner the bond will be released and no
further undertakings will be required of the holder of the
mining permit. That is, the Act appears to contemplate that.
reclamation activities will have a definite termination date..
Altho'ugh G.S. 74-53 requires reclamation to be completed within
two years of the termination of mining, it authorizes the
Department of Natural Resources and Community Development (NRCD)
to allow a longer time. If NRCD may allow a longer time, it is
arguable that when circumstances so require, NRCD may require a
longer time. This is supported by G.S. 74-49(12), which defines
11reclamation" as being the "reasonable rehabilitation of the
affected land for useful purposes". G.S. 74-54'provides that the
liability under the bond must be maintained until reclamation is
completed in accordance with the plan; thus it would appear that.
all or a portion of the bond could be continued in effect to
indemnify the state in the event it should have to continue the
pumping after failure or refusal of the permit holder to do so.

4.3.2.1.2 Capacity Use Designation

All of Washington County and portions of Hyde and Tyrrell
Counties have been designated capacity use areas pursuant to the
Water Use Act of 1967 (G. S. 143-215.11 et seq.), and the
remaining portions of the counties could be so designated
pursuant to this law. Within the designated areas, a permit from
the Environmental Management Commission is required for
withdrawal or utilization of water in excess of 100,000 gallons
per day. The Commission must also approve "any project involving
the excavation of any single area in excess of five acres to a
depth below the highest natural level of groundwater" (15
N.C.A.C. 2E .0205).

4.3.2.1.3 Areas of Environmental Concern (Coastal Area
Management Act)

The North Carolina Coastal Area Management Act (CAMA), in
listing potential areas of environmental concern, adopts as its
definition of "wetlands" in G.S. 113A-113(b)(1) the same
definition used in G.S. 113-230(a). G.S. 113-230(a) (part of the
dredge and fill permit law) adopts for its definition of
"coastal wetlands" any marsh as defined by G.S. 113-229(n)(3),
plus certain contiguous land. G.S. 113-229(n)(3), in turn,
defines "marshland" as any marsh subject to tidal flooding in
which is found at least one of ten named species of plants. Thus
a "wetland" as defined under CAMA is "any marsh subject to tidal
flooding in which is found at least one of ten named species of
plants".

Should any mining activity take place within an Area of
Environmental Concern designated pursuant to the Coastal Area
Management Act (G. S. 113-100 et seq.), a major development
permit would be required from the Coastal Resources Commission.

4.3.2.2 Federal Regulatory Controls

4.3.2.2.1 NPDES Permits

Any water discharges from canals draining mining sites or
other point sources require an NPDES Permit, administered by the
state, but mandated by the federal Clean Water Act (33 U.S.C.
Section 1251 et seq.). Water quality standards must be met for
the permit to be obtained. Also, under Section 401 of the Clean
Water Act, the state must certify to EPA that no effluent
standard, water quality limit or toxic pollutant standard will
be violated by the mining activity.

4.3.2.2.2 Clean Air Act

. The air quality in the study area counties meets or exceeds
that required by the national air quality standards, and,
therefore, the area is designated a Prevention of Significant
Deterioration (PSD) area. The state, through its state
implementation plan, administers and enforces the federal Clean
Air Act (42 U.S.C. section 7401 et seq.) and by means of that
plan must enforce the standards for PSD areas. These standards,
in summary, require that the air quality in PSD areas not exceed
certain stated increments for listed pollutants, including
particulate matter. The area is a class II PSD area, to whic'11
moderately stringent standards are applied, except for the Swal.'I
Quarter National Wildlife Refuge in Hyde County, which is a
class I area, to which the most stringent standards are applied.
Activities occurring outside a class I area must not cause a
violation of the class I standards within the area. Mining
activities would be regulated under the PSD planning and
permitting provisions if the activity emits or has the capacity
to emit 250 tons per year, or more, of a controlled pollutant,
such as particulates (40 C.F.R. section 52.21 et seq.). The most
likely control measures that would be applied are work practice
standards designed to control fugitive emissions.

4.3.2.2.3 404 Dredge and Fill Permits

If dredged or fill material is to be deposited into
navigable waters or associated wetlands as part of the mininq
activity, a permit must be obtained from the U. S. Army Corps of'
Engineers under Section 404 of the Clean Water Act (33 U.S.C.
Section 1344). The conditions of this permit must be such that
fishery areas and wildlife are not adversely affected. No permit.
is required for normal farming and forestry operations such as
plowing, seeding, cultivation and minor drainage or "for the,
purpose of construction or maintenance of farm roads or forest
roads, or temporary roads for moving mining equipment, where
such roads are constructed and maintained, in accordance with
best management practices" to assure that the flow and quality
of the water is unimpaired (33 U.S.C. section 1344(f)).

For purposes of issuing dred( ije and fill permits in the
naviagable waters of the United States pursuant to Section 404,
the Army Corps Engineers and EPA have adopted the same
definition of "wetlands." For the Corps of Engineers, the
definition appears at 33 C.F.R. section 323.2(c); for EPA, at 40
C.F.R. section 230.3(t). The definit:[on is: "The term 'wetlands'
means those areas that are inundated or saturated by surface or
ground water at a frequency and duration sufficient to support,
and that under normal circumstances do support, a prevalence of
vegetation typically, adapted for life in saturated soil
conditions. Wetlands generally include swamps, marshes, bogs and
similar areas."

If a Section 404 permit is required, the Corps of Engineers
must also prepare an environmental impact statement under the
National Environmental Policy Act (42 U.S.C. section 4321 et
seq.).

4.3.2.2.4 Endangered Species Act

The study area provides habitat for at least three animals
that have been listed as endangered species: the redcockaded
woodpecker, the bald eagle and the American alligator; another
endangered species, the eastern cougar, may inhabit the area (50
C.F.R. section 17.11). No critical habitats have been designated
for these species, but the cougar and woodpecker are listed as
endangered throughout their ranges and the eagle is endangered
in the lower 48 states. The case of Palila v. Department of Land
and Natural Resources, 471 F. Supp. 985 (D. Haw. 1979), aff'd
639 F.2d 495 (9th Cir. 1981), held that state action allowing
the deterioration of the habitat of an endangered species is a
"taking" within the meaning of the Endangered Species Act (16
U.S.C. section 1531 et seq.) and may be enjoined by a federal
court. In that case, the habitat destruction was taking place in
an area designated as critical habitat for the palila, an
endangered Hawaiian bird, by the U.S. Fish and Wildlife Service,
and, therefore, the case against the state was strong. Private
organizations might also rely on the Endangered Species Act to
block mining activities that are disruptive to critical habitat.

4.3.3 County Responses

A county may respond to large-scale mining activities by
requiring a local environmental impact statement; adopting a
land use ordinance requiring a county mining permit; and/or
pressing for state enabling legislation that would authorize the
levy of a severance tax (Brower et al., 1983).

4.3.3.1 Local Environmental Impact Statement

Local governments are authorized by G.S. 113A-8 to require
environmental impact statements for major development projects,
which are defined to include commercial and industrial projects
of more than two contiguous acres. A peat mine would appear to
fit this definition. An environmental impact statement might be
quite helpful to a county in making plans for dealing with the
social, economic and environmental impacts of large-scale
mining, but the statement is informational only and does not
empower the county to veto the project because the predicted
environmental consequences are severe, nor does it bind the mine
operator to any particular environmental standards. For the
requirement of a county environmental impact statement to be
effective, the county must employ a person capable of drafting

and administering the impact statE!ment ordinance and reviewing
the completed statement for adequacy.

4.3.3.2 County Mining Permit

Counties may respond to mining activities that are
regulated by the state under the Mining Act by enacting land use
regulations. County zoning regulations might be honored to SOME?
extent, but a county prohibition of mining would -- in the face
of a state permit -- clearly be preempted by state law. Brower
et al. (1983) indicate that the county would require a
reclamation bond in addition to the state bond. However, the
strong possibility of preemption exists here also. Although SOME?
effective land use regulation might be adopted at the county
level to deal with mining, it would have to be very carefully
tailored to avoid state preemption, and even then it would
probably invit.e litigation by the mining companies.

4.3.3.3 Severance Tax

Peat mining itself will not generate additional property,
taxes in affected counties, although counties in which peat.
processing plants are located will receive some property taxes4
Therefore, for the counties to realize any significant amount of
tax revenues from the mining operations, a severance tax would
be required. For a number of reasons outlined by Brower et al.
(1983), the ad valorem property tax on peat deposits is, as a
practical matter, worth nothing. The primary reason for this is
the great difficulty in appraising the deposits.

Severance taxes can take a number of forms, including a per
unit tax on each ton or other quantity of the product mined, or
a percentage of the sales price of the resource mined. A portion
of the tax could be allocated for reclamation efforts. Other
states with severance taxes could provide models for a North
Carolina tax. State legislation would be required before
counties could levy any sort of a severance tax. The tax could
also be made a state tax.

5. ALTERNATIVE PEAT MINING DEVELOPMENT SCENARIOS

5.1 Introductory Section

In the context of this project, a scenario is a set of
assumptions about the course of peat mining development over a
20-year period. In Scenario #1 (currently permitted acreage
mined as proposed), these assumptions are based as much as
possible on the stated plans of peat mining companies that held
mining permits or had applied for permits as of summer, 1983.
Where plans for specific aspects of the scenarios were not
available, attempts were made to make the most "reasonable"
assumptions possible. Comments on early drafts of the scenarios
by representatives of the peat mining industry and by state
agency personnel involved with permitting processes contributed
to the refinement of these assumptions.

Scenarios #2 and #3 are based entirely on assumption and
(except for the section of Scenario #3 between years I and 10
which corresponds to Scenario #1) do not represent the stated
plans of any peat mining industry or landowner in the study
area.

In all scenarios, national economic conditions are assumed
to warrant the development described.

Two mining areas have been delineated for Scenarios #1 and
#3 based on permits issued and permit applications submitted as
of summer, 1983, geographical location, and drainage
characteristics. These areas are shown in Figure 5B.

Four mining areas are outlined for Scenario #2 based on
drainage characteristics and geographical location (see Figure
5G). Areas 1 and 2 of this scenario are expansions of Areas 1
and 2 in Scenario #1. Areas 3 and 4 of Scenario #2 are areas for
which no mining permit applications have been submitted to date,
but in which substantial peat deposits lie.

The following pages outline each of the three scenarios,
stating assumptions made about each of the following aspects:

1) Permitted acreage
2) Land disturbance
3) Mining and processing technologies
4) Transportation
5) Water management
6) Air quality management
7) Solid waste management
8) Wildlife mitigation measures
9) Fire protection measures
10) Reclamation plans

5.2 Alternatives

5.2.1 No Change

This alternative assumes that neither peat mining nor any
other type of development occurs during the 20-year study period
in areas within the boundaries of the scenarios. No further
ditching occurs and the permit areas remain largely in their
present state. Agricultural and forestry operations currently
underway continue but do not expand; no conversions from one
land use-habitat type to another, other than normal succession,
occur.

Burned and otherwise disturbed acreage not under
cultivation or in pine plantations. in the permitted areas
undergo natural vegetational succession and eventually revert to
low or high pocosin.

5.2.2 Scenario #1: Currently Permitted Acreage

(Static: at years 1/10/20 and/or Cumulative: years 1-10
and 11-20)

Note: Peat Methanol Associates (PMA) documents refer only
to 15,012 acres assumed permitted for methanol
production in Area 1 and do not refer to
horticultural peat operations.

5.2.2.1 Permitted mining Activity

5.2.2.1.1 Permitted Acreage

year 1 10 20
Area 1 15,818

Area 2 7,142

Total 22,960

Assumptions:
No further acreage is permitted during the next 20 years
Permit renewals are granted for continuation of mining on
already permitted acreage
First Colony Farms' mining permit is transferred to PMA

Sources:
Mining Permits
Figure 5A

5.2.2.1.2 Location of Permitted Acreage

see Figure 5B

Figure 5A: Scenario #1-- Acreage disturbed

Year
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Total

Area 1
Permitted: 15,818 ac. 3,080 2,440 3,400 2,440 11,360 ac.
Mined: 11,360 ac.

Area 2
Permitted: 7,142 ac. 1,500 1,500 1,500 1,500 6,000 ac.
Mined: 6,000 ac.

Maximum
Acreage 8,520 8,840 17,360 ac.
Disturbed

24
Lake

Phelps
+
%C!D

New
U1 Lake .6.--.,

P C
of
Z:
ir

It N G 0 1 A 9

Figure 5B: Scenario #1-- Currently Permitted Acreage Key: Area 1 15,81
(Basemap - Isopach Map of Pamlimarle Peat - 2 ft Area 2 7,14
thickness interval - from Inpram and Otte. 1982)

5.2.2.2 Land Disturbance

5.2.2.2.1 Acreage Mined (cumulative)

by 10 by 20
Area 1 5,520 11,360

Area 2 3,000 6,000

Total 8,520 17,360

Assumptions:
Mining start dates and rates occur as indicated in Figure 5A
Disturbed acreages for Area 2 and for the horticultural
operations,in Area 1
Sources:
PMA, 1983d, Fig. 2-10 (blocks fully or partially mined or in
preparation at years 5, 10, 15 and 20)
Figure 5A

5.2.2.2.2 Average Acreage in Peat Mining Production at Any One
Time

1-10 11-20
Area 1 2,000 2,000

Area 2 1,500 1,500

Total 3,500 3,500

Assumption:
Average acreage in production for Area 2
Source:
PMA, 1983c, d

5.2.2.2.3 Maximum Acreage Disturbed (in Preparation or Being
Mined) at Any One Time
at 10 at 20
Area 1 2,880 2,560

Area 2 1,800 1,800

Total 4,680 4,360

Assumption:
Maximum acreage disturbed for Area .2
Source:
PMA, 19nc,d

5.2.2.2.4 Average Annual Rate of Land Disturbance

1-10 11-20
Area 1 552 584

Area 2 300 300

Assumptions:
Mining rates

5.2.2.2.5 Elevation of Mined Acreage

Land Elev. Expected Max. Average Depth Elev of Mined
(MSL) Mine Depth of mining Acreage (MSL)
Area 1 13-181 91 4-51 7-121

Area 2 5-101 91 4-51 if

Sources:
Elevations - see Figure 5C
Mining Permit Applications
WTF Mining Permit
PMA, 1983c

5.2.2.2.6 Undisturbed Permitted Acreage at Year 20

Area 1 4,458

Area 2 1,142 (includes a 410 acre conservation easement-
to remain unmined)

Total 5,600

Assumptions:
Mining of Area 1 acreage is expected to occur over a period
of 34 years
Mining of Area 2 permitted acreage is expected to occur over
a period of more than 20 years

A L 41 A

/0
W A S H 1" N G T Ni

TYRRELL
0 A R E

/0 ... ...

BEAUFORT,

%G too#

10 H Y D E

"off
-1.08
5

"Co

0 'o
j__. 2.0 50 Nq S
EXPLANATION
TOPOGRAPHiC CONTOUR-- Contour interval 5 feel. Five-fool contour not shown
when it would Mer.ge with the 10-foof contour of this scale. Datum is mean sea level

Figure 5C: CL!iieralized topographic map of the Albemarle-Pamlico Peninsula

(from Heath, 1975)

5.2.2.3 Mining and Processing Technologies

5.2.2.3.1 Mining Technologies in Use

Area 1
Milled peat production (15,012 acres permitted)
Bulldozer, truck, and front-end loader (98 acres permitted)
Scrape mining (similar to milled method) (708 acres
permitted)

Area 2
Milled peat production (7,142 acres permitted)

Sources:
Mining Permit Applications

5.2.2.3.2 Average Amount of Peat Mined Per Year at Years
10 and 20

Area 1 525,000 dry tons (875,000 tons at 40%
moisture)

Area 2 140,000 dry tons (235,000 tons at 40%
moisture)

Total 665,000 dry tons (1,110,000 tons at 40%
moisture)

Assumptions:
140 mining days per year (average)
Amount of peat mined is based on:
Area 1: 3,600 dry tons/day x (average) 140 mining
days-peat for methanol production
25,00 dry tons/year-horticultural peat
Area 2: 1,000 dry tons/day x (average) 140 mining days
Source:
PMA, 1983d, p.14 (harvesting projected to take place
142 days per year)

5.2.2.3.3 Processing Technologies in Use at Years 10 and 20

Area 1
Conversion to methanol (500,000 dry tons per year)
Export as horticultural peat (25,000 dry tons per year)

Area 2 -
Export to industry as peat for fuel (140,000 dry tons per
year)

Assumption:
Area 2: export of peat to off-peninsula industry for use
as fuel
Sources:
Mining Permit Applications

5.2.2.3.4 Products from Mined Peat: Type and Amount at Years 10
and 20

Area 1
methanol 60 million gals/year
horticultural peat 25,000 dry tons/year

Area 2
peat for industrial use (fuel) 140,000 dry tons/year

Assumptions:
Area 1: methanol plant annual output is equivalent to
approximately 310 days per year at full capacity requiring
an average of 1,600 dry tons peat per day to produce an
average of 200,000 gallons of methanol per day

Area 2: peat for industrial use is mi'ned/produced 140 days
per year
Sources:
PMA documents

5.2.2.4 Transportation

5.2.2.4.1 Type and Maximum Volume of Transportation to and on
Site (Construction and Operation)

Type Size Number/day
Area 1 heavy duty trucks up to 40 (construction)
36 tons 13 (operation)

Area 2 trucks up to 5 (operation)
36 tons
Assumptions:
Years 1-3: construction ongoing in Area 1
Years 4-20: no construction ongoing in Area 1
No construction required in Area 2
Operation excludes transportation of peat or peat products.
Refers primarily to transportation of slag and fly ash
(Area 1).
Number of trucks needed in Area 2
Source:
PMA, 1983j, p. 25

5.2.2.4.2 Type and Volume of Transportation on Site - Harvesting
(Years 1-20)

Type Volume
Area 1 tractor & carts 233 loads/day to methanol
(15 ton capacity) plant stoarge pile or
shipping area for
horticultural peat

Area 2 tractor and carts 63 loads/day to shipping
(15 ton capacity) area

Assumptions:
Assumes peat can be transported from mining site to
processing plant or shipping area 250 days/year
Transportation method and capacity in Area 2
Calculations:
Area 1: 875,000 tons of peat at 40% moisture per year/15
tons per cart/250 days per year
Area 2: 235,000 tons of peat at 40% moisture per year/15
tons per cart/250 days per year
Source:
PMA, 1983i, p. 22- peat to be transported from the mining
site to the plant stockpile an average of 251 days per year

5.2.2.4.3 Type, Volume, and Route of Transportation from Site
Products at Years 10 and 20

Number Type size Route

Area 1 27/day trucks 36-ton Rte 64 to
Plymouth, NC

Area 2 2/week barges 1,500-ton IWW
(south)

Assumptions:
Peat from Area 2 is transported via barge through the IWW to
a major industry off the peninsula (50 weeks/year)
Horticultural peat and methanol from Area 1 is transported
to barge and RR facilities in Plymouth, NC
Source:
PMA, 1983j, pp. 44 & 73

5.2.2.4.4 Maximum Distance (Miles) Peat Transported on Unpaved
Roads on Site

at 10 at 20

Area 1 2.5 4

Area 2 4 4

Assumptions:
Distances for Area 2
Source:
PMA, 1983d, Fig. 4-1, general phases of mining (used
phase II for at 10/phase V for at 20)

5.2.2.4.5 Distance Products Transported on Paved/Unpaved Roads
from Site (Miles) Years 1-10

paved unpaved total destination

Area 1 19 10 29 (one way) Plymouth,
NC

Area 2 0 0 0

Assumptions:
All peat products from Area 1 are transported to or through
Plymouth, NC and all peat from Area 2 is transported to
a major industry off the peninsula via barge on the IWW
(from a barge terminal adjacent to the mining site)
Road on northern edge of Area 1 mining site remains unpaved
Source:
PMA, 1983j

5.2.2.5 Water Management

5.2.2.5.1 Acreage of Sediment, Evaporation, and Other Temporary
Ponds and Acreage of Permanent Lakes

1-9 10-20

Area 1 2550 (temp-max 1450 (perm-max
depth V) depth 8')
Area 2 0 0

Assumptions:
All drainage water from Area 2 is discharged into IWW/no
holding ponds
Note:
Area 1: holding ponds located on 15,012 acre tract in
methanol production
Sources:
PMA, 1983c, d
PMA, 1983i, p. 19

5.2.2.5.2 Groundwater Withdrawn from the Quarternary Shell Hash
Unit for Processing at Years 10 and 20

Area 1 2.3 mgd

Area 2 none

Assumptions:
Withdrawals are made from the Quarternary Shell Hash Unit
(underlying Area 1 at depths of 40 to 130 feet)
Sources:
PMA, 1983i, p. 74 and personal communication R. Hornstein,
Koppers Company, Inc.

5.2.2.5.3 Maximum Water Withdrawn from the Surficial Aquifer
during Plant Site Preparation

Area 1 3 mgd (for a period of two years)

Area 2 0 mgd

Sources:
PMA Water Use Permit Applications and Permits

5.2.2.5.4 Water Balances for mining Sites

Condition Total Runoff Subsurface Surface Evapo-
mgy/2000 mgy/1500 Dr1ina2e Rrof5 trans-
acres acres (in /in (in /in pi5ati2n
(Area 1) (Area 2) (in /in

Pre-mining 1046 784 11.2 8.0 29.2
(disturbed)

Pre-mining 778 591 11.1 3.4 33.9
(shrub)

During mining 1336 1002 6.5 18.0

After mining 808 606 6.8 8.0 33.6
(agriculture
330' spaced
drainage ditches)

Note:
Data based on 15 year averages of computer simulations using
weather data from Elizabeth City weather station. Annual
average rainfall for the 15 years used is 48.41'.
Source:
R. Broadhead, Dept. Biol. and Agric. Eng., NCSU

5.2.2.5.5 mined and Reclaimed Acreage from Which Drainage
Water is Being Pumped during Mining (Cumulative)

0-5 5-10 10-15 15-20
Area 1 3,080 5,520 8,920 11,360

Area 2 1,500 3,000 4,500 6,000

Total 4,580 8,520 13,420 17,360

Assumptions:
All disturbed acreage requires pumping during mining (i.e.,
drainage water from all lands gravity drains to lowest
points on the mining sites and is pumped into lakes or
canals)
All reclaimed acreage requires pumping
Acreage figures do not include unmined land which may drain
into the low points depending on the location of the
unmined land relative to the sites being mined
Sources:
L. Otte, Geol. Dept., ECU
R. Broadhead, Dept. Biol. and Agric. Eng., NCSU

5.2.2.5.6.Maximum Changes in Surficial Groundwater at the
Mine Sites

Areas 1 and 2
In areas where peat is removed, groundwater levels will
decline by the depth of peat mined. If vegetation is
replanted, groundwater level will drop an additional foot.

Source:
R. Broadhead, Dept. Biol. and Agric. Eng., NCSU

Area 1
Projected maximum effects of mining operations on water
levels along the northern edge of the mining site are a
decline of about 3.5' in the Fine Sand Unit and 2.5' in the
Shell Hash Unit.

Source:
PMA, 1983k, p. 84

5.2.2.5.7 Drainage and Runoff Waters from All Mined and
Reclaimed Lands: Direction of Flow/Receiving
Body of Water

1-10 11-20
Area 1 All runoff to temp. lagoons All runoff to central
or central lake to Canal lake to Canal B to
B to Pungo River Pungo River
(Mean annual discharge (Mean annual discharge
from holding ponds: 8 cfs from lake: 35.3 cfs
Max. runoff: 59.6 cfs) Max. runoff: 151 cfs)

Area 2 Mine site to IWW Same as 1-10

Assumptions:
Drainage systems on all mined lands similar to agricultural
drainage systems in use throughout the coastal area of NC
Area 1: Water will drain from disturbed areas by gravity to
low points from which it will be pumped to lagoons or a
central lake
Area 2: Water will be discharged into IWW`
Sources:
PMA, 1983f, p. 6-74
WTF NPDES Permit
PMA, 1983i, p. 91

5.2.2.5.8 Quality of Runoff from Mining Sites (Areas 1 and 2)

Source Water Parameters (all units except pH in mg/l
Type (ppm) +/- approx. S.E.)

DO pH TSS CN SCN

1 Drainage 3 4.2 25 <0.005 2
(measured +/-0.6 +/-0.4 +/-8 +/-0.7
in existing
canals)

2 Drainage 4.3-8.5 100
(Mean effluent (200 max)
characteristics
projected from
harvesting)

3 Processing 7 6-9 - 0.002
Effluent (80% sat.
at 20 C)

4 Storm 6-9 50 -

5 Drainage - -
(11natural
peatlands")

6 Drainage
(peatlands
converted to
pasture)

Note:
Abbreviations may be found in Appendix 10.10
Sources:
I- PMA, 1983f, Appendix A
2,3,4- PMA, 1983f
5,6- Skaggs et al., 1980
7- NRCD unpublished data

5.2.2.5.8 (Continued)

Source Water Parameter
Type (mg/l (ppm) 4-/- approx. S.E.)
Ci- Fl- so 4: NH 3-N NO 2-N
1 Drainage 12 0.1 12 1.0 0.01
+/-2 +/-0.02 +/-2 +/-0.2

2 Drainage - 0.96

3 Process - 1.4 -

5 Drainage 2.2 - 0.11
+/-0.01

6 Drainage 9.2 0.36
+/-0.04

NO 3-N Kjd-N Tot Org-N Ortho-P Tot-P
1 Drainage 0.01 3.5 2 0.2 0.3
+/-0.4 +/-0.2 +/-0.04 +/-0.03

2 Drainage - 0.01 -

3 Process - - - - 0.5

5 Drainage 0.03 1.18 1.20 0.006
+/-0.01 +/-0.04 +/-0.03 +/-0.01

6 Drainage 0.24 1.68 1.92 2.36
+/-0.07 +/-0.04 +/-0.09 +/-0.21

Note:
Abbreviations may be found in Appendix 10.10
Sources:
1- PMA. 1983f, Appendix A
2,3,4- PMA, 1983f
5.6- Skaggs, et al., 1980
7- NRCD unpublished data

5.2.2.5.8 (Continued)

Source Water Parameter
Type (mg/1 (ppm) +/- approx. S.E.)
5 Day BOD As Sb Ca Cd Cu

1 Drainage 2.5 <0.02 <0.02 10 0.002 0.01
+/-4

2 Drainage 4 - - - 0.02
(max 6)

3 Process 6 0.003 - - 0.001 -

5 Drainage - - - 1.4 <0.01 0.012

6 Drainage - - 10.4 <0.01 0.009

Fe* Cr Mn Mg Pb** Hg
1 Drainage 5 0.005 0.03 3 0.02 0.001
+/-1.3 +/-1 +/-0.002

2 Drainage 4.9 - - "ambient"

3 Process <0.001 0.01 0.02 - <0.001 0.00021

5 Drainage 0.63 - 0.003 0.5 - -

6 Drainage 1.66 0.027 2.5 - -

7 ? - - - - <0.0002

Notes:
> criterion (1 & 2)
much variation, sometimes > criterion (0.03?)
Abbreviations may be found in Appendix 10.10
Sources:
1- PMA, 1983f, Appendix A
2,3,4- PMA, 1983f
5,6- Skaggs et al., 1980
7- NRCD unpublished data

5.2.2.5.8 (Continued)

Source Water Parameter
Type (mg1l (ppm) +/-- approx. S.E.)

Ni Se Ag Na Zn Co Be D.S.
1 Drainage <0.01 <0.001 <0.001 6 0.08 <0.01 - 250

3 Process 0.07 0.001 - - 0.09 <0-001 <0.005 4500

5 Drainage - - - 3.7 0.01 - - -

6 Drainage - - 5.1 0.02

Note:
Abbreviations may be found in Appendix 10.10
Sources:
1- PMA, 1983f, Appendix A
2,3,4- PMA, 1983f
5,6- Skaggs et.al., 1980.
7- NRCD unpublished data

5.2.2.5.9 Wastewater Treatment: Source/Rate/Route of Effluent
Discharge/Receiving Body of Water at Years 10 and 20
Source Average Route Receiving
Daily Discharge Water Body

Area 1 Methanol plant 870,000 gal/day Canal B Pungo R.

Area 2 none

Assumption:
No processing occurs in Area 2
Source:
PMA, 1983i

5.2.2.5.10 Flood Gates/Flood Control Measures

Area 1
No flood gates constructed because of elevation of
permitted land

Area 2
Flood gates constructed at all drainage outlets from mining
sites to permit site drainage but prevent entry of water
from IWW

Assumptions:
Flood gates constructed in Area 2
Sources:
WTF Mining Permit
R. Hornstein, Koppers Co., Inc.

5.2.2.5.11 Elevation of Dikes Around Mined Areas/Storage Ponds
and Lakes

at 10 at 20

Area 1 201 MSL 20' MSL around central lake
around temp ponds

Area 2 no dikes 8' MSL around eastern end
of mine
Sources:
PMA, 1983d
WTF Mining Permit

5.2.2.5.12 Probability of Hurricane Flooding in 100-year
Floodplain at Years 10 and 20

Area 1
Not susceptible to flood inundation caused by wind tides
having a 1% chance of being equalled or exceeded in any one
year

Area 2
Approximately half the area is susceptible to flood
inundation caused by wind tides having a 1% chance of being
equalled or exceeded in any one year (without protective
barriers)

Source:
Figure 5D

V A

01,#'0
,r,j '0 '0 )
f

Lott

lo'.11
a

If
-(@be
p Coot
<1 _6

35.
Poll 09 a I ..;I;
off

to 10 to 50 MIMS
a . d . I
19 0 10 20 NO 40 90 $14.0101111's

Figure 5D: Area subject to flood inundation caused
by wind tides having a 1% chance of being
equalled or exceeded in any one year
(from'Wilder, Robison and Lindskov, 1978)

5.2.2.5.13 Change in Groundwater Recharge Rate to the Castle
Hayne Aquifer Resulting from Land Clearing and Mining
Activities. Values are Average Changes in Recharge
Rates Over the Entire Acreage for Each Area.

1-10 11-20 over 20years

Area 1 -0.0005 in/yr -0.0002 in/yr -0.0007 in/yr
(-5.2%) (-7.2%)
-66gpd -230 gpd -830 gpd

Area 2 -0.0007 in/yr -0.0001 in/yr -0.0009 in/yr
(-7.6%) (-8.8%)
-400 gpd -60 gpd -460 gpd
Notes:
Rate at year 0 = 0.01 in/yr
Change in rate is noted in parentheses
Assumptions:
Assumes layers are isolated laterally (i.e., essentially a
vertical system)
Stratigraphy for all areas similar to that found for First
Colony Farms (Area 1)
Depth of mining operations for all areas similar to that
proposed by PMA (Area 1)
Source:
Foutz, 1983.

5.2.2.5.14 Salt water Encroachment in Shallow and Deep Aquifers

Areas 1 and 2
No significant lateral movement in the freshwater/saltwater
interface. Since there is already a wide diffused zone
ranging from salt to fresh water, the anticipated change in
head due to withdrawals (a few feet) is not expected to
significantly change the location of this diffused zone

Sources:
P. Nelson, Groundwater Section, DEM, NRCD
PMA, 1983k

5.2.2.5.15 Revegetation of Canal/Ditch Banks

Revegetation is completed following ditch maintenance and as
part of reclamation

Assumption:
All of the above

5.2.2.5.16 Erosion and Sediment Control Measures

Adequate mechanical barriers including but not limited to
diversions, settling ponds, earthen dikes, brush barriers,
silt check dams, silt retarding structures; rip rap pits or
ditches provided in the initial stages of any land disturbance
to prevent sediment from discharging onto any adjacent surface
areas or into any lake or natural watercourse in proximity to
the affected land.

Assumptions:
All of the above

5.2.2.5.17 Buffer Strips Adjacent to Estuaries/Lakes/Rivers at
Years 10 and 20

Area 1 2000' tree buffer between
site and Phelps Lake

Area 2 300' between site and IWW

Note: 20001 tree buffer in Area 1 is outside permitted area
Sources:
PMA, 1983f
WTF Mining Permit

5.2.2.6 Air Quality Management

5.2.2.6.1 Off-property Fugitive Dust Concentrations Resulting
from Mining and Processing operations at Years 10
and 20

With adequate buffer strips, mining in Areas 1 and 2 is not
anticipated to exceed air quality standards.

Notes:
NC Air Quality Standards
Area 1 (15,012 acre tract) 3
Annual Standard for Particulate - 75,ag/M 3
24-Hour Standard for Particulate - 150.,iAg/M
Area 1 (all other acreage) and Area 2 3
Annual Standard for Particulate (Class I) - 5'"g/M
24-Hour itandard for Particulate (Class I) -
10 _'kg/M
Annual S andard for Particulate (Class II) -
19 Ag/M
24-Hour itandard for Particulate (CLass II) -
37.wAgIM
Class I protected areas having air cleaner than the
National Ambient Standard (Swanquarter
National Wildlife Refuge is the only Class I
area on the Albemarle-Pamlico Peninsula)
Class II other areas having air cleaner than the
3 National Ambient Standard
.ZCg/M micrograms per cubic meter
Source:
M. Sewell, Air Quality Section, DEM, NRCD

5.2.2.6.2 Mitigation Measures for Fugitive Dust Emissions from
Transportation of Peat in Use at Years 10 and 20

Area 1
restricted speed limits
paving or watering of roadways
tree buffer strips

Area 2
restricted speed limits
tree buffer strips

Assumptions:
All of the above
Source:
PMA, 1983j, p. 78

5.2.2.7 Solid Waste Management

5.2.2.7.1 Amount of Non-hazardous Waste Generated (Years 1-20)
Area 1 53,000 tons/yr (851,000 ft 3/yr*)
(non-burnable material from methanol production
including 27,000 tons/year of slag and fly ash)
Area 2 negligible
Assumptions: 3
Assumes a bulk density of 0.062 tons/ft
No significant amount non-hazardous waste generated
in Area 2
Source:
PMA, 1983h, Fig. 1

5.2.2.7.2 Amount of Hazardous Waste Generated (Years 1-20)
Area 1 1,000 ft 3/yr (does not include catalysts
recycled)
8,100 gals/yr waste oils

Area 2 none

Assumption:
No hazardous wastes generated in Area 2 since no peat will
be processed on site
Source:
PMA, 1983h

5.2.2.8 Wildlife Mitigation Measures

5.2.2.8.1 Permitted Acreage Restored to Native Vegetation
(Buffer Strips)

see section 5.2.2.10.6

Assumption:
20% mined/reclaimed land required re-established to native
vegetation or low intensity managed forest for buffer strips
Source:
D. Owens, Office of Coastal Management, NRCD

5.2.2.8.2 Location of Native Vegetation Buffer Strips on
Permitted Areas at Years 10 and 20

see Figure 5E

Source:
PMA, 1983c, d

5.2.2.9 Fire Protection Measures

5.2.2.9.1 Source and Volume of Water for Fire Suppression

1-10 11-20

Area 1 Canals, lagoons- Central lake (5 blocks)
14 unharvested blocks (12,000 ac-ft)
in use as water storage
reservoirs

Area 2 Fire protection/waterfowl same as at 10
impoundment

Source:
PMA, 1983c, pp. 13, 37

5. 2.2.9.2 Water Control Structures for Areas Not Being Mined

Structures installed to prevent gravity drainage from lowering
water level lower than l' below ground level on lands not
being actively mined. These structures have capacity to retain
sufficient water to flood or saturate peat soil to or slightly
above ground level.

Assumptions:
All of the above
Sources:
PMA, 1983c, p. 13
WTF Mining Permit

Numbers indicate mining blocks

Lake
2 3

(Nat ral
4 5 6
Area) 0

7 8 9

"K
1 12

Wildlife
14
13 I.Corridor

16
18 Cr
19
0

20 21 22 Lake

Natural
23 24 25 M
W Area)
J

26 27 28
rT
,('300' buffer strip 20' buffer.strip
Assumptions:
1/2 mi. buffer along major bodies of water
1/2 mi. wildlife corridors between natural ar as
(corridor can be mined if equivalent area maintaine
in native vegetation, i. e., corridor is movable)
300' buffer strips running N-S alorig me side of major canals
20' buffer strips running E-W along one side of roads and smaller
canals
scale: 1"-2,000'
V 15

Fi.vure 5E: Schematic of tvpical wildlife buffer plan

5.2.2.10 Reclamation

5.2.2.10.1 Mined Acreage Legally Required to be Reclaimed
(Cumulative)

by 10 by 20
Area 1 2,020 7,980

Area 2 1,500 4,500

Total 3,500 12,480

Assumptions:
NRCD requirement that mined areas be reclaimed within 2
years of completion of mining is met
All legally reclaimable land reclaimed on schedule (refers
to sections 5.2.2.10.3-5.2.2.10.8)
Reclamation schedule for Area 2 and part of Area 1
Source:
PMA, 1983d, Fig. 2-10

5.2.2.10.2 Percentage of Total Reclaimed Land in Various Types
of Reclamation
Area 1 Area 2
by 10 by 20 by 10 and 20

Row crops with pumping 8 62 78

Row crops without pumping 0 0 0

Pine plantations 10 10 10

Restored native veg. 10 10 10

Open water 72 18 0

Grass replanted 0 0 2

Assumptions:
Native vegetation restored in buffer strips as shown in
Figure 5E
Pumping required in all reclaimed farmland
Reclamation activities - percentages

5.2.2.10.3 Mined Acreage in Row Crops with Pumping (Cumulative)

by 10 by 20
Area 1 162 4,930

Area 2 1,170 3,510

Total 1,332 8,440

Calculations:
Sections 5.2.2.10.3-5.2.2.10.8 calculated based.on % in
section 5.2.2.10.2 and acreages in section 5.2.2.10.1

5.2.2.10.4 Mined Acreage in Row Crops Without Pumping
(Cumulative)

by 10 by 20
Area 1 0 0

Area 2 0 0

Total 0 0

5.2.2.10.5 Mined Acreage in Pine Plantations (Including
Vegetative Buffer Strips) (Cumulative)

by 10 by 20
Area 1 202 798

Area 2 150 450

Total 352 1,248

5.2.2.10.6 Mined Acreage Restored to Native Vegetation
(Buffer Strips) (Cumulative)

by 10 by 20
Area 1 202 798

Area 2 150 450

Total 352 1,248

5.2.2.10.7 Mined Acreage in Open Water Reclamation
With/Without Marshes and Islands (Cumulative)

by 10 by 20
Area 1 1,454 1,454

Area 2 0 0

Total 1,454 1,454

5.2.2.10.8 Mined Areas Replanted to Grass (Cumulative)

by 10 by 20
Area 1 0 0

Area 2 30 90

Total 30 90

5.2.2.10.9 Unreclaimed Mined Acreage Not Yet Legally Required
to be Reclaimed (Cumulative)

by 10 by 20
Area 1 3,500 3,380

Area 2 1,500 1,500

Total 5,000 4,880

5.2.2.10.10 Unreclaimed Disturbed Acreage Legally
Required to be Reclaimed (Cumulative)

by 10 by 20
Area 1 0 0

Area 2 0 0

Total 0 0

Assumption:
All legally reclaimable land reclaimed on schedule

5.2.3 Scenario #2: Upper Boundary

(Static: at years 1/10/20 and/or Cumulative: years 1-10
and 11-20)

5.2.3.1 Permitted Mining Activity

5.2.3.1.1 Permitted Acreage

year 1 10 20
Area 1 30,000

Area 2 15,000

Area 3 26,000

Area 4 13,000

Total 84,000

Assumptions:
All of the above
Source:
Figure 5F

5.2.3.1.2 Location of Permitted Acreage

see Figure 5G

5.2.3.2 Land Disturbance

5.2.3.2.1 Acreage Mined (Cumulative)

by 10 by 20
Area 1 7,500 30,000

Area 2 3,750 15,000

Area 3 5,500 26,000

Area 4 3,400 13,000

Total 20,150 84,000

Assumptions:
Mining start dates and rates occur as indicated in
Scenario #2 chart of disturbed acreages
Source: Figure 5F

Figure 5F: Scenario #2-- Acreage disturbed

Year
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 116 17 18 19 20 Total

Area 1
Permitted: 30,000 ac. 3,000 4,500 9,000 13,500 30,000 ac.
Mined 30,000 ac.

Area 2
Permitted: 15,000 ac. 1,500 2,250 4,500 6,750 15,000 ac.
Mined: 15,000 ac.

Area 3
Permitted: 26,000 ac. 1,500 4,000 8,000 12,500 26,000 ac.
Mined: 26,000 ac.

Area 4
Permitted: 13,000 ac. 1,500 1,900 3,850 5,750 13,000 ac.
Mined: 13,000 ac.

Maximum
Acreage 20,150 63,850 84,000 ac.
Disturbed

Lake
Alf.,
Phelps
+

'V %

N
ew
Lake

X--
00

A M V SK & Z
U,N2t60 a ,

Scenario #2-- Upper Boundary
Figure 5G: Key:
fRncomnn - Tsopach map of Pamlimarle peat 2 ft
thickness interval from Ingram and Otte, 1982) Area 1 30,000 ac Area
Ev-LAJ@U 15,000 ac
Area 2 Area

5.2.3.2.2 Average Acreage in Peat Mining Production at Any
One Time

1-10 11-20
Area 1 3,750 11,250

Area 2 1,875 5,625

Area 3 2,750 10,250

Area 4 1,700 4,800

Total 10,075 31,925

Source:
Figure 5F

5.2.3.2.3 Maximum Acreage Disturbed (in Preparation or Being
Mined) at Any One Time

at 10 at 20

Area 1 4,500 13,500

Area 2 2,250 6,750

Area 3 4,000 12,500

Area 4 1,900 5,750

Total 12,650 38,500

Source:
Figure 5F

5.2.3.2.4 Average Annual Rate of Land Disturbance

1-5 6-10 11-15 16-20
Area 1 600 900 1,800 2,700

Area 2 300 450 900 1,350

Area 3 300 800 1,600 2,500

Area 4 300 380 770 1,150

Assumptions:
Mining rates
Source:
Figure 5F

5.2.3.2.5 Elevation of Mined Acreage

Land Elev. Maximum Average Minimum
(MSL) Mine Depth DE!pth of Elev of Mined
mining Acr-eage (MSL)
Area 1 13-18' 10, 4-5' 41

Area 2 5-10' 91 4-6' 11

Area 3 <5-151 81 4-61 31 below MSL

Area 4 51 or less 14' 4-8' 9' below MSL
or lower
Sources:
Maximum depth of peat deposits estimated from Ingram
and Otte, 1982
Elevations - see Figure 5C

5.2.3.2.6 Undisturbed Permitted Acreage at Year 20

Area 1 0

Area 2 0

Area 3 0

Area 4 0

Total 0

5.2.3.3 mining and Processing Technologies

5.2.3.3.1 Mining Technologies in Use

Area 1
Milled peat production (28,300 acres permitted)
Bulldozer, truck, and front-end loader (200 acres permitted)
Scrape mining (similar to milled method) (1,500 acres
permitted)

Area 2
Milled peat production (15,000 acres permitted)

Area 3
Milled peat production (26,000 acres permitted)

Area 4
Milled peat production (13,000 acres permitted)

Assumption:
Hydraulic mining not in use/feasible

5.2.3.3.2 Average Amount of Peat Mined (dry tons/yr)
at 10 at 20
Area 1 837,525 2,512,575

Area 2 367,500 1,102,500

Area 3 471,900 1,758,900

Area 4 432,000 1,219,000

Total 2,108,925 6,592,975

Calculations:
Area 1: Estimated peat contained within area boundaries
33.5 million dry tons
33.5 million tons/30,000 ac=1,116.7 tons/ac
yrs 1-10: 7,500 ac mined x 1,116.7 tons/ac/10
yrs=837,525
yrs 11-20: 22,500 ac mined x 1,116.7 tons/ac/10
yrs=2,512,575 tons/yr
Area 2: Estimated peat contained within area boundaries
14.7 million dry tons
14.7 million tons/15,000 ac=980 tons/ac
yrs 1-10: 3,750 ac mined x 980 tons/ac/10
yrs=367,500 tons/yr
yrs 11-20: 11,250 ac mined x 980 tons/ac/10
yrs=1,102,500 tons/yr

5.2.3.3.2 (Continued)
Area 3: Estimated peat contained within area boundaries
22.3 million dry tons
22.3 million tons/26,000 ac=858 tons/ac
yrs 1-10: 5,500 ac mined x 858 tons/ac/10
yrs=471,900 tons/yr
yrs 11-20: 20,500 ac mined x.858 tons/ac/10
yrs=1,758,900 tons/yr
Area 4: Estimated peat contained within area boundaries
16.5 million dry tons
16.5 million tons/13,000 ac=1,270 tons/ac
yrs 1-10: 3,400 ac mined x 1,270 tons/ac/10
yrs=432,00 tons/yr
yrs 11-20: 9,600 ac mined x 1,270 tons/ac/10
yrs=1,219,000 tons/yr

Note:
Tonnages by area roughly estimated based on data
provided by R. L. Ingram - square miles of peat
by depth by USGS quad map. Bulk density assumed
to be 180 tons/acre-foot.

5.2.3.3.3 Processing Technologies in Use

Method Dry Tons/Year
at 10 at 20
Area 1
Conversion to methanol 787,273 2,361,821
Export as horticultural peat 50,252 150,754

Area 2
Export to industry as peat 367,500 1,102,500
for use as fuel

Area 3
Conversion to methanol 471,900 1,758,900

Area 4
Export to industry as peat 432,000 1,219,000
for use as fuel

Calculations:
see section 5.2.3.3.2

5.2.3.3.4 Products from Mined Peat: Type and Amount

at 10 at 20
Area 1
methanol 94 million gal/yr 283 million gals/yr
horticultural 50,252 dry tons/yr 150,754 dry tons/yr
peat

Area 2
peat for industrial
use (fuel) 367,500 dry tons/yr 1,102,500 dry tons/yr

Area 3
methanol 57 million gals/yr 211 million gals/yr

Area 4
peat for industrial
use (fuel) 432,000 dry tons/yr 1,219,000 dry tons/yr

Assumption:
8,333 dry tons of peat produce 1 million gallons of
methanol (based on Scenario #1, section 5.2.2.3.4)

5.2.3.4 Transportation

5.2.3.4.1 Type and Maximum Volume of Transportation to and
on Site (Construction and Operation)

Type Size Number/day
Area 1 heavy duty up to 80 (construction)
trucks 36 tons 26 (operation) at year 10
65 (operation) at year 20

Area 2 trucks up to 10 (operation) at year 10
36 tons 30 (operation) at year 20
Area 3 heavy duty up to 75 (construction)
trucks 36 tons 25 (operation) at year 10
65 (operation) at year 20
Area 4 trucks up to 10 (operation) at year 10
36 tons 33 (operation) at year 20
Assumptions:
Areas 2 and 4: no construction required
Areas 1 and 3: construction ongoing years 1-10
Years 11-20: no construction ongoing
Operation excludes transportation of peat or peat products.
For Areas 1 and 3 refers primarily to transportation of
slag and fly ash

5.2.3.4.2 Type and Volume of Transportation on Site - Harvesting

1-5
Type Volume
Area 1 tractor & carts 233 loads/day to
(15-ton capacity) plant storage
pile

Area 2 same as above 98 loads/day to
shipping area

Area 3 same as above 126 loads/day to
plant storage
pile

Area 4 same as above 115 loads/day to
shipping area
Assumptions:
Assumes peat can be transported from mining site to
processing plant or shipping area 250 days/year
Years 6-20: switch to conveyers for transportation of
peat to plant storage piles or shipping areas (all Areas)

Source:
PMA, 1983i, p. 22 peat to be transported from the mining
site to the plant stockpile an average of 251 days per
year

5.2.3.4.3 Transportation from Site - Products at Years 10 and 20

Type Route
Area 1 pipelines to Plymouth, NC

Area 2 barges IWW (south)

Area 3 pipelines to Plymouth, NC

Area 4 barges IWW (south)

Assumptions:
Peat from Areas 2 + 4 is transported via barge through the
IWW to major industries off the peninsula
Methanol from Areas 1 + 3 is transported via pipeline to
barge and RR facilities in Plymouth, NC

5.2.3.4.4 Maximum Distance (Miles) Peat Transported on Unpaved
Roads on Site (Years 1-5)

Area 1 5

Area 2 8

Area 3 6

Area 4 8

Assumption:
Years 6-20: conveyers in use for transportation of peat in
all areas

5.2.3.4.5 maximum Distance Products Transported on Paved/Unpaved
Roads from Site (miles)

1-10
paved unpaved total destination

Area 1 0 0 0 Plymouth, NC

Area 2 0 0 0 off peninsula

Area 3 0 0 0 Plymouth, NC

Area 4 0 0 0 off peninsula

Assumptions:
All peat products from Areas 1 + 3 are transported by
pipeline to Plymouth, NC and all peat from Areas 2 + 4
is transported to industries off the peninsula via
barge on the IWW (from barge terminals adjacent to
the mining sites)

5.2.3.5 Water Management

5.2.3.5.1 Acreage of Sediment, Evaporation, and Other Temporary
Ponds and Acreage of Permanent Lakes

1-10 11-20
Area 1 5,000 (temp) 2,900 (perm)

Area 2 0 0

Area 3 0 0

Area 4 1,954 (perm) 4,280 (perm)

Assumptions:
All drainage water from Area 2 is discharged into IWW/
no holding ponds
Area 1: 2 x Scenario #1
Area 3: no holding ponds: sheet flow through wetlands
utilized
Area 4: reclamation is open water

.5.2.3.5.2 Groundwater Withdrawn from the Quarternary Shell Hash
Unit, Yorktown Formation, or Castle Hayne Aquifer
for Processing

at 10 at 20
Area 1 3.7 mgd 10.9 mgd

Area 2 none none

Area 3 2.2 mgd 8 mgd

Area 4 none none

Assumptions:
At year 10:
Area 1: methanol production 160% x Scenario #1 (Area 1)
Area 3: methanol production 951; x Scenario #1 (Area 1)
At year 20:
Area 1: methanol production 472% x Scenario #1 (Area 1)
Area 3: methanol production 351% x Scenario #1 (Area 1)

5.2.3.5.3 Maximum Water Withdrawn from the Surficial Aquifer
During Plant Site Preparation

Area 1 3 mgd (for a period of ten years)

Area 2 0 mgd

Area 3 3 mgd (for a period of ten years)

Area 4 0 mgd

Assumptions:
Methanol plants under construction or expansion during
years 1-10 in Areas I and 3

5.2.3.5.4 Water Balances for All Mining Sites

Condition Total Runoff Subsurface Surface Evapo-
mgy/2000 DrIinage Ru 2off2 trans-
acres (in /in (in /in pi5ati2n
(in /in

Pre-mining 1046 11.2 8.0 29.2
(disturbed)

Pre-mining 788 11.1 3.4 33.9
(shrub)

During mining 1336 6.5 18.0

After mining 808 6.8 8.0 33.6
(agriculture-
330' spaced
drainage ditches)

Note:
Data based on 15 year averages of computer simulations using
weather data from Elizabeth City weather station. Annual
average rainfall for the 15 years used was 48.4 inches.

Source:
R. Broadhead, Dept. Biol. and Agric. Eng., NCSU

5.2.3.5.5 Mined and Reclaimed Acreage from Which Drainage Water
is Being Pumped During mining (Cumulative)

0-5 5-10 10-15 15-20
Area 1 3,000 7,500 1.6,500 30,000

Area 2 1,500 3,750 8,250 15,000

Area 3 1,500 5,500 1.3,500 26,000

Area 4 1,500 1,900 3,850 5,750

Total 7,500 18,650 42,100 76,750

Assumptions:
All disturbed acreage requires pumping during mining (i.e.,
drainage water from all lands gravity drains to lowest
points on the mining sites and is pumped into lakes or
canals)
Acreage figures do not include unmined land which may drain
into the low points depending on its location relative to
.the sites being mined
Area 4 reclamation is primarily open water, so pumping is
not required after mining ends.
Area 1,2 + 3 reclamation is primarily agriculture, so
pumping is required after mining ends.

5.2.3.5.6 Maximum Changes in Surficial Groundwater Levels Due
to Mining Operations in the Immediate vicinity of
the Mine Site

All areas:
Groundwater levels will decline in the immediate vicinity of
the mine by the depth of peat mined. If vegetation is
replanted, groundwater level will drop an additional foot.

Source:
R. Broadhead, Dept. Biol. and Agric. Eng., NCSU

5.2.3.5.7 Drainage and Runoff Waters from All mined and
Reclaimed Lands: Direction of Flow/Receiving
Body of Water

1-10 11-20
Area 1 all runoff to temporary all runoff drains by gravity
lagoons to Canal B to to a point near the central
Pungo River lake (pumped into lake) from
which it is discharged into
Canal B to Pungo River

Area 2 mine site to IWW same as 1-10

Area 3 mine site through wetlands same as 1-10
to tributaries of the
Alligator River

Area 4 all runoff into same as 1-10
permanent lakes

Assumptions:
Drainage systems on all mined lands similar to agricultural
drainage systems in use throughout the coastal area of NC
Capacity of Canal B is increased to handle greater flows

5.2.3.5.8 Quality of Runoff from All Mining Sites
(Areas 1, 2, 3, and 4)

see section 5.2.2.5.8

5.2.3.5.9 Wastewater Treatment: Source/Rate/Route of Effluent
Discharge/Receiving Body of Water at Years 10 and 20

Source Average Daily Route Receiving Body
Discharge
(mgd)
at 10 at 20
Area 1 Methanol plant 1.4 4.1 Canal B Pungo R.

or other
canals
Area 2 none

Area 3 Methanol plant 0.8 3.1 Wetlands Alligator R.
tributaries
Area 4 none

Assumptions:
Same as section 5.2.3.5.2

5.2.3.5.10 Flood Gates/Flood Control Measures

Area I
No flood gates constructed beause of elevation

Areas 2, 3 and 4
Flood gates constructed at all drainage outlets from mining
sites to permit site drainage but prevent entry of water
from water bodies receiving drainage

5.2.3.5.11 Elevation of Dikes Around Mined Areas/Storage Ponds
and Lakes

at 10 at 20
Area 1 201 MSL 201 MSL
around temp ponds around central lake

Area 2 dikes and flood gates built at elevation of
100-yr storm

Area 3 same as Area 2

Area 4 same as Area 2

5.2.3.5.12 Probability of Hurricane Flooding in 50- and 100-year
Floodplains (at Years 10 and 20)
Area 1
Not susceptible to flood inundation caused by wind tides
having a 1% chance of being equalled or exceeded in any one
year

Area 2
Approximately 50% susceptible to flood inundation caused by
wind tides having a 1% chance of being equalled or exceeded
in any one year (without protective barriers)

Area 3
Approximately 75% susceptible to flood inundation caused by
wind tides having a 1% chance of being equalled or exceeded
in any one year (without protective barriers)

Area 4
100% susceptible to flood inundation caused by wind tides
having a 1% chance of being equalled or exceeded in any one
year (without protective barriers)

Source:
Figure 5D

5.2.3.5.13 Change in Groundwater Recharge Rate to the Castle
Hayne Aquifer Resulting from Land Clearing and
Mining Activities. Values are Average Changes in
Recharge Rates Over the Entire Acreage for Each
Area.

1-10 11-20 Over 20 yrs
Area 1 -0.0005 in/yr -0.0004 in/yr -0.0009 in/yr
(-4.8%) (-9.2%)
-1050 gpd -950 gpd -2000 gpd
Area 2 -0.0005 in/yr -0.0004 in/yr -0.0009 in/yr
(-4.8%) (-9.2%)
-530 gpd -470 gpd -1000 gpd
Area 3 -0.0005 in/yr -0.0004 in/yr -0.0009 in/yr
(-4.8%) (-9.2%)
-910 gpd -840 gpd -1750 gpd
Area 4 -0.0005 in/yr -0.0004 in/yr -0.0009 in/yr
(-4.8%) (-9.2%)
-950 gpd -870 gpd -1820 gpd
Notes:
Rate at year 0 = 0.01 in/yr
Change in rate is noted in parentheses
Assumptions:
Assumes layers are isolated laterally (i.e., essentially
a vertical system)
Stratigraphy for all areas similar to that found for
First Colony Farms (Scenario #I/Area 1)
Depth of mining operations for all areas similar
to that proposed by PMA (Scenario #l/Area 1)

Sources:
Foutz, 1983
Calculations by R. Broadhead, Dept. Biol. and Agric. Eng.,
NCSU

5.2.3.5.14 Salt Water Encroachment in Shallow and Deep Aquifers

Area 1
Impact laterally insignificant in Castle Hayne, Tertiary Sand
Aquifer (including the Yorktown Formation), and the Quarternary
Shell Hash Unit. Greatest effect will occur if water pumped
from the Castle Hayne Aquifer, in which case an upconing or
upwelling of brackish water may occur at production wells.
Localized effect causing at most an increase in chloride
concentrations of a few mg/l.

Area 2
No significant lateral movement in. the freshwater/saltwater
interface. (No pumping from deeper aquifers for processing
water or plant site dewatering.)

Area 3
Impact laterally insignificant in Castle Hayne, Tertiary Sand
Aquifer (including the Yorktown Formation), and the Quarternary
Shell Hash Unit. Castle Hayne Aquifer is brackish in this area.
Greatest effect will occur if water pumped from Yorktown or
Tertiary Sand Aquifers, in which case an upconing or upwelling
of brackish water may occur at production wells. Localized
effect causing at most an increase in chloride concentrations of
a few mg/l.

Area 4
No significant lateral movement in the freshwater/saltwater
interface. (No pumping from deeper aquifers for processing
water or plant site dewatering.)

Source:
B. Jeter, Groundwater Section, DEM, NRCD

5.2.3.5.15 Revegetation of Canal/Ditch Banks

Revegetation is completed following ditch maintenance and as part
of reclamation

5.2.3.5.16 Erosion and Sediment Control Measures

Adequate mechanical barriers including but not limited to
diversions, settling ponds, earthen dikes, brush barriers, silt
check dams, silt retarding structures, rip rap pits or ditches
are provided in the initial stages of any land disturbance to
prevent sediment from discharging onto any adjacent surface areas
or into any lake or natural watercourse in proximity to the
affected land.

5.2.3.5.17 Buffer Strips Adjacent to Estuaries/Lakes/Rivers at
Years 10 and 20

Area 1 2000' tree buffer between
site and Phelps Lake

1/2 mile between site and Alligator (New) Lake

Area 2 300' between site and IWW

Area 3 1/2 mile between site and Alligator (New) Lake

Area 4 1/2 mile between site and Alligator R.

300' between site and IWW

Note:
2000' tree buffer is Area 1 outside permitted area
Assumption:
1/2 mile buffer between mining sites and Alligator River
is required in mining permits

5.2.3.6 Air Quality Management

5.2.3.6.1 off-property Fugitive Dust Concentrations Resulting
from mining and Processing operations at
Years 10 and 20

Assuming adequate buffer strips and appropriate spacing of
methanol plants (as determined necessary by computer simulation),
mining should not cause air quality standards to be exceeded.

Note:
State air quality standards (Increments) 3
Annual Standard for Particulate (Class I) 5..z(g/M3
24-Hour Standard for Particulate (Class I) 10,ag/M3
Annual Standard for Particulate (Class II) 19,ug/M3
24-Hour Standard for Particulate (Class 11) 37 mg1M
Class I protected areas having air cleaner than the
National Ambient Standard (Swanquarter National
Wildlife Refuge is the only Class I area on
the Albemarle-Pamlico Peninsula)
Class II other areas having air cleaner than the National
3 Ambient Standard
'zig/M micrograms per cubic meter
Source:
M. Sewell, Air Quality Section, DEM, NRCD

5.2.3.6.2 Mitigation Measures for Fugitive Dust Emissions During
the 20-year Period for All Areas:

restricted speed limits
paving or watering of roadways
tree buffer strips

5.2.3.7 Solid Waste Management

5.2.3.7.1 Amount of Non-hazardous Waste Generated

1-10 11-20
Area 1 84,800 tons/yr 3 250,160 tons4yr
(1.4 million ft /yr) (4 million ft /yr)

Area 2 negligible same as 1-10
Area 3 50,350 tons/yr 3 186,000 tons4yr
(0.8 million ft /yr) (3 million ft /yr)

Area 4 negligible same as 1-10

Note:
Waste consists of non-burnable material from methanol
production approximately half of which is slag and
fly ash
Assumptions: 3
All figures in ft 3 based on an assumed bulk density
of 0.062 tons/ft
Same as section 5.2.3.5.2
No significant amount of non-hazardous waste generated
in Areas 2 and 4

5.2.3.7.2 Amount of Hazardous Waste Generated

1-10 3 11-20 3
Area 1 1,600 ft /yr 4,720 ft /yr

Area 2 none none
Area 3 950 ft 3/yr 3,510 ft 3/yr

Area 4 none none

Assumptions:
No hazardous wastes generated in Areas 2 + 4 since no peat
will be processed on site
Same as section 5.2.3.5.2
Excludes catalysts recycled and waste oils (amount unknown)

5.2.3.8 Wildlife Mitigation Measures

5.2.3.8.1 Permitted Acreage Restored to Native Vegetation
(Buffer Strips)

See section 5.2.3.10.6

Assumption:
20% mined/reclaimed land required re-established to native
vegetation or low intensity managed forest for buffer
strips

Source:
D. Owens, Office of Coastal Management, NRCD

5i2.3.8.2 Location of Native Vegetation Buffer Strips on
Permitted Areas at Years 10 and 20

see Figure 5E

5.2.3.9 Fire Protection Measures

5.2.3.9.1 Source and Volume of Water for Fire Suppression

1-10 11-20
Area 1 Canals, lagoons- Central lake (2900 ac)
28 unharvested blocks
in use as water storage
reservoirs

Area 2 Fire protection/waterfowl same as at 10
impoundment

Area 3 same as Area 1 same as Area 3 (1-10)

Area 4 Reclaimed lakes same as 1-10

5.2.3.9.2 Water Control Structures for Areas Not Being Mined
Structures installed to prevent gravity drainage from lowering
water level lower than l' below ground level on lands not
being actively mined. These structures have capacity to retain
sufficient water to flood or saturate peat soil to or slightly
above ground level.

5.2.3.10 Reclamation

5.2.3.10.1 Mined Acreage Legally Required to be Reclaimed
(Cumulative.)

by 10 by 20
Area 1 5,700 24,600

Area 2 2,850 12,300

Area 3 3,900 21,000

Area 4 2,640 10,700

Total 15,090 68,600

Assumptions:
NRCD requirement that mined areas be reclaimed within
2 years of completion of mining is met
All legally reclaimable land reclaimed on schedule
(refers to sections 5.2.3.10.3-5.2.3.10.8)
Source:
Figure 5F

5.2.3.10.2 Percentage of Reclaimed Land in Various Types of
Reclamation (Cumulative)

Area 1 Area 2 Area 3 Area 4
by 10 by 20 by 10+20 by 10+20 by 10 by 20

Row crops with 24 63 78 75 0 0
pumping

Row crops without 0 0 0 0 0 0
pumping

Pine plantations 10 10 10 10 10 18

Restored native veg. 10 10 10 10 10 18

Open water 51 12 0 0 74 40

Grass replanted 5 5 2 5 2 2

Residential areas 0 0 0 0 4 22

Assumptions:
Native vegetation restored in buffer strips as shown in
Figure 5E
Pumping in all reclaimed lands is required

5.2.3.10.3 Mined Acreage in Row Crops with Pumping (Cumulative)

by 10 by 20
Area 1 1,368 15,543

Area 2 2,223 9,594

Area 3 2,925 15,750

Area 4 0 0

Total 6,516 40,887

Calculations:
Sections 5.2.3.10.3-5.2.3.10.8 calculated based on % in
section 5.2.3.10.2 and acreages in section 5.2.3.10.1

5.2.3.10.4 Mined Acreage in Row Crops Without Pumping
(Cumulative)

by 10 by 20
Area 1 0 0

Area 2 0 0

Area 3 0 0

Area 4 0 0

Total 0 0

5.2.3.10.5 Mined Acreage in Pine Plantations (Including
Vegetative Buffer Strips) (Cumulative)

by 10 by 20
Area 1 570 2,460

Area 2 285 1,230

Area 3 390 2,100

Area 4 264 1,926

Total 1,509 7,716

5.2.3.10.6 Mined Acreage Restored to Native Vegetation
(Buffer Strips) (Cumulative)

by 10 by 20
Area 1 570 2,460

Area 2 285 1,230

Area 3 390 2,100

Area 4 264 1,926

Total 1,509 7,716

5. 2.3.10.7 Mined Acreage in Open Water Reclamation With/Without
Marshes and Islands (Including Canals) (Cumulative)

by 10 by 20
Area 1 2,907 2,907

Area 2 0 0

Area 3 0 0

Area 4 1,954 41,280

Total 4,861 7,187

5.2.3.10.8 Mined Areas Replanted to Grass (Cumulative)

by 10 by 20
Area 1 285 1,230

Area 2 57 246

Area 3 195 1,050

Area 4 53 :214

Total 590 2,740

100

5.2.3.10.9 Mined Acreage Reclaimed as Residential Areas
(Cumulative)

by 10 by 20

Area 1 0 0

Area 2 0 0

Area 3 0 0

Area 4 106 2,354

Total 106 2,354

5.2.3.10.10 Unreclaimed Mined Acreage Not Yet Legally Required
to be Reclaimed (Cumulative)

by 10 by 20

Area 1 1,800 5,400

Area 2 900 2,700

Area 3 1,600 5,000

Area 4 760 2,300

Total 5,060 15,400

Source:
Figure 5F

5.2.3.10.11 Unreclaimed Mined Acreage Legally Required to be
Reclaimed (Cumulative)

by 10 by 20

Area 1 0 0

Area 2 0 0

Area 3 0 0

Area 4 0 0

Total 0 0

Assumption:
All Legally reclaimable acreage reclaimed on schedule

101

5.2.4 Scenario #3: Industry Failure

(Static: at years 1/10/20 and/or Cumulative: years 1-10
and 11-20)

Note:
PMA documents refer only to 15,012 acres assumed permitted
for methanol production (Area 1) and not to horticultural
operations.

5.2.4.1 Permitted mining Activity

5.2.4.1.1 Permitted Acreage

year 1 10 20
Area 1 15,818

Area 2 7,142

Total 22,960

Assumptions:
No further acreage is permitted during the next 20 years.
Permit renewals are granted for continuation of mining
on already permitted acreage
First Colony Farms' mining permit is transferred to PMA
Sources:
Mining Permits

5.2.4.1.2 Location of Permitted Acreage

same as section 5.2.2 (see Figure 5B)

5.2.4.2 Land Disturbance

5.2.4.2.1 Acreage Mined (Cumulative)

by 10 by 20
Area 1 5520 5520

Area 2 3000 3000

Total 8520 8520

Assumptions:
Mining start dates and rates occur as indicated in Figure 5H
Disturbed acreages: Area 2 and Area 1 (horticultural
operations)
All mining operations fail at year 10
Source: Figure 5H

102

Figure 5H: Scenario #3-- Acreage disturbed

Year
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Total
Area I
Permitted: 15,818 ac. 3,080 2,440 0 0 5,520 ac.
Mined: 5,520 ac.

Area 2
Permitted: 7,142 ac. 1,500 1,500 0 0 3,000 ac.
Mined: 3,000 ac.

Maximum
Acreage 8,520 0 8,520 ac.
Disturbed

5.2.4.2.2 Average Acreage in Peat Mining Production at Any One
Time

1-10 11-20
Area 1 2000 Q1

Area 2 1500 Qf

Total 3500 0

Source:
Section 5.2.2.2.2

5.2.4.2.3 Maximum Acreage Disturbed (in Preparation or Being
Mined) at Any One Time.

at 10 at 20
Area 1 2880 0

Area 2 1800 0

Total 4680 0

Source:
Section 5.2.2.2.3

5.2.4.2.4 Average Annual Rate of Land Disturbance

1-10
Area 1 552

Area 2 300

Assumptions:
mining rates
Years 11-20: no mining

5.2.4.2.5 Elevation of Mined Acreage
Average minimum
Land Elev. Expected Max. Depth of Elev of Mined
(MSL) Mine Depth mining Acreage (MSL)
Area 1 13-181 91 4-51 7-121

Area 2 5-101 91 4-51 if

sources:
Elevations - see Figure 5C
Mining Permit Applications and Permits

104

5.2.4.2.6 Undisturbed Permitted Acreage at Years 10 and 20

Area 1 10,298

Area 2 4,142 (includes a 410 acre conservation easement-
to remain unmined)
Total 14,440

5.2.4.3 Mining and Processing Technologies

5.2.4.3.1 Mining Technologies in Use

Area 1
Milled peat production (15,012 acres permitted)
Bulldozer, truck, and front-end loader (98 acres permitted)
Scrape mining (similar to milled method) (708 acres
permitted)

Area 2
Milled peat production (7,142 acres permitted)

Sources:
Mining Permit Applications

5.2.4.3.2 Average Amount of Peat Mined Per Year (at Year 10)

Area 1 525,000 dry tons (875,000 tons at 40% moisture)

Area 2 140,000 dry tons (235,000 tons at 40% moisture)

Total 665,000 dry tons (1,110,000 tons at 40% moisture)

Assumptions:
140 mining days per year (average)
Amount of peat mined is based on:
Area 1- 3,600 dry tons/day x (average) 140 mining
days - peat for methanol production
25,000 dry tons/year - horticultural peat
Area 2- 1,000 dry tons/day x (average) 140 mining days
At Year 20: no mining ongoing

Source:
Section 5.2.2.3.2

105

5.2.4.3.3 Processing Technologies in Use at Year 10

Area .1
Conversion to methanol (500,000 dry tons per year)
Export as horticultural peat (25,000 dry tons per year)

Area 2
Export to industry as peat for fuel (140,000 dry tons
per year)

Assumption:
At 20: no processing ongoing
Sources:
Mining Permit Applications

5. 2.4.3.4 Products from Mined Peat: Type and Amount

at 10
Area 1
methanol 60 million gals/year
horticultural peat 25,000 dry tons/year

Area 2
peat for industrial use (fuel) 140,000 dry tons/year

Assumptions:
Area 1: methanol plant annual output equivalent to
approximately 310 days per year at full capacity
requiring an average of 1,600 dry tons peat per day
to produce an average of 200,000 gallons of methanol
per day
Area 2: peat for industrial use (fuel) is mined/produced
140 days per year
At Year 20: none

106

5.2.4.4 Transportation

5.2.4.4.1 Type and Maximum Volume of Transportation to and on
Site (Construction and Operation)

Type size Number/day
Area 1 heavy duty trucks up to 40 (construction)
36 tons 13 (operation)

Area 2 trucks up to 5 (operation)
36 tons
Assumptions:
Years 1-3: construction ongoing in Area 1
Years 4-20: no construction ongoing in Area 1
No construction required in Area 2
Years 11-20: no mining operation ongoing
operation traffic excludes transportation of peat or peat
products. Refers in Area 1 primarily to transportation
of slag and fly ash.
Source:
PMA, 1983j, p. 25 and Fig. 4-2

5.2.4.4.2 Type and Volume of Transportation on Site - Harvesting

1-10
Type Volume

Area 1 tractor & carts 233 loads/day to
(15-ton capacity) methanol plant
storage pile or
shipping area for
horticultural peat
Area 2 tractor and carts 63 loads/day to
(15-ton capacity) shipping area

Assumptions:
Assumes peat can be transported from mining site to
processing plant or shipping area 250 days/year
Years 11-20: no harvesting
Calculations (1-10):
Area 1: 875,000 tons of peat (at 40% moisture) per year/15
tons per cart/250 days per year
Area 2: 235,000 tons of peat (at 40% moisture) per year/15
tons per cart/ 250 days per year
Source:
PMA, 1983i, p. 22 states that peat can be transported from
the mining site to the plant stockpile approximately 251
days per year

107

5.2.4.4.3 Type, Volume, and Route of Transportation from Site
Products
at 10
Number Type Size Route

Area I 27/day trucks 36-ton Rte 64 to
Plymouth, NC

Area 2 2/week barges 1,500-ton IWW (south)

Assumptions:
Peat from Area 2 is transported via barge through the IWW
to a major industry off the peninsula (50 weeks per year)
Horticultural peat and methanol from Area 1 transported to
barge and RR facilities in Plymouth, NC
At year 20: no products being transported
Source:
PMA, 1983j, pp. 44 & 73

5.2.4.4.4 Maximum Distance (Miles) Peat Transported on Unpaved
Roads on Site
1-10
Area 1 2.5

Area 2 4

Assumptions:
Years 11-20: no peat being mined -or transported
Distances for Area 2
Source:
PMA, 1983d, Fig. 4-1

5.2.4.4.5 Distance Products Transported on Paved/Unpaved Roads
from Site (Miles)
1-10
paved unpaved total destination

Area 1 19 10 29 (one way) Plymouth, NC

Area 2 0 0 0

Assumptions:
All peat.products from Area 1 are transported to or through
Plymouth, NC and all peat from Area 2 is transported to a
major industry off the peninsula via barge on the IWW
(from a barge terminal adjacent to the mining site)
Area 1: assumes road north of site remains unpaved
Years 11-20: no products being transported
Sources:
PMA, 1983j

108

5.2.4.5 Water Management

5.2.4.5.1 Acreage of Sediment, Evaporation, and other Temporary
Ponds and Acreage of Permanent Lakes

1-9 10-20
Area 1 2550 (temporary) 1450 (permanent
(maximum depth V) (maximum depth 8')

Area 2 0 0

Assumptions:
All drainage water from Area 2 is discharged into IWW (no
holding ponds)
At year 10 all pumping ceases
Sources:
PMA, 1983d and 1983i, p. 91 (size of temp and perm ponds)

5.2.4.5.2 Groundwater Withdrawn from the Quarternary Shell Hash
Unit for Processing at Year 10

Area 1 2.3 mgd

Area 2 none

Assumptions:
Withdrawals made from the Quarternary Shell Hash Unit
(underlying Area 1 at depths of 40 to 130 feet)
At year 20: no withdrawals being made
Sources:
Section 5.2.2.5.2

5.2.4.5.3 Maximum Water Drained from the Surficial Aquifer
During Plant Site Preparation

Area 1 3 mgd (for a period of two years)

Area 2 0 mgd

Assumption:
No plant constructed in Area 2
Sources:
PMA Water Use Permit Applications and Permits

109

5.2.4.5.4 Water Balances for Mining Sites (Until Cessation of
Pumping)

Condition Total Runoff Subsurface Surface Evapo-
mgy/2000 mgy/1500 Dr i inage Rpof@ trans-
acres acres (in /in (in /in.) pi@ati n
(Area 1) (Area 2) (in /in
Pre-mining 1046 784 11.2 8.0 29.2
(disturbed)
.Pre-mining 788 591 11.1 3.4 33.9
(shrub)

During mining 1336 1002 6.5 18.0
After mining 808 606 6.8 8.0 33.6
(agriculture-
330' spaced
drainage ditches)

Notes:
Data based on 15 year averages of computer simulations using
weather data from Elizabeth City weather station.
Annual average rainfall for the 15 years used is 48.41'.
Source:
R. Broadhead, Dept. Biol. and Agric. Eng., NCSU

5.2.4.5.5 Mined and Reclaimed Acreage from Which Drainage Water
is Being Pumped During Mining (Cumulative)

0-5 5-10 10-15 15-20

Area 1 3080 5520 0 0

Area 2 1500 3000 0 0

Total 4580 8520 0 0

Assumptions:
All disturbed acreage requires pumping during mining
(i.e., drainage water from all lands gravity drains to
lowest points on the mining sites and is pumped into
lakes or canals)
Acreage figures do not include unmined land which may
drain into the low points depending on the location of
unmined lands relative to the sites being mined
All pumping ceases at year 10
Sources:
L. Otte, Geol. Dept., ECU
R. Broadhead, Dept. Biol. and Agric. Eng., NCSU

110

5.2.4.5.6 maximum Changes in Surficial Groundwater Levels at
the Mine Sites

Areas I and 2
Groundwater levels will decline in areas where peat is
removed by the depth of peat mined. If vegetation is
replanted, groundwater level will drop an additional foot.

Source: R. Broadhead, Dept. Biol. and Agric. Eng., NCSU

Area I
Projected maximum effects of mining operations on water
levels along the northern edge of the site are a decline of
about 3.5' in the Fine Sand Unit and 2.5' in the Shell Hash
Unit.

Note:
Surficial groundwater levels will return to pre-mining
conditions following failure of the industry and
cessation of pumping
Source:
PMA, 1983k, p. 84

5.2.4.5.7 Drainage and Runoff Waters from All Mined and
Reclaimed Lands: Direction of Flow/Receiving
Body of Water

1-10 after year 10

Area 1 all runoff to temp. lagoons all runoff to
or central lake to Canal B Canal B to Pungo
to Pungo River River
(mean annual discharge from
holding ponds: 8cfs/ max
runoff: 59.6 cfs)

Area 2 mine site to IWW same as 1-10

Assumptions:
Drainage systems on all mined lands similar to agricultural
drainage systems in use throughout the coastal area of NC

5.2.4.5.8 Quality of Runoff from All Mining Sites
(Areas 1 and 2)

see section 5.2.2.5.8

5.2.4.5.9 Wastewater Treatment: Source/Rate/Route of Effluent
Discharge/Receiving Body of Water at Year 10

Source Average Daily Route Receiving
Discharge Body
Area 1 Methanol plant 870,000 Canal B Pungo R.
gal/day
Area 2 none

Assumption:
No processing occurs on mining site in Area 2
At year 20: none
Source:
PMA, 1983i

5.2.4.5.10 Flood Gates/Flood Control Measures

Area 1
No flood gates constructed because of elevation

Area 2
Flood gates constructed at all drainage outlets from mining
sites to permit site drainage but prevent entry of water
from IWW'. Flood gates not operational after industry fails.

Source:
Section 5.2.2.5.10

5.2.4.5.11 Elevation of Dikes Around Mined Areas/Storage Ponds
and Lakes
at 10 at 20
Area 1 201 MSL 201 MSL

Area 2 no dikes no dikes

5.2.4.5.12 Probability of Hurricane Flooding in 100-year
Floodplain (at Years 10 and 20)

Area 1
Not susceptible to flood inundation caused by wind tides hav--
ing a 1% chance of being equalled or exceeded in any one year

Area 2
About 50% susceptible to flood inundation caused by wind tides
having a 1% chance of being equalled or exceeded in any one year
(without protective barriers)

Source:
Figure 5D

112

5.2.4.5.13 Change in Groundwater Recharge Rate to the Castle Hayne
Aquifer Resulting from Land Clearing and mining
Activities. Values are Average Changes in Recharge
Rates Over the Entire Acreage for Each Area

1-10 11-20

Area 1 -0.0005 in/yr 0
(-5.2%)
-600 gpd

Area 2 -0.0007 in/yr 0
(-7.6%)
-400 gpd

Notes:
Rate at year 0 = 0.01
Change in rate is noted in parentheses
Assumptions:
Assumes layers are-isolated laterally (i.e., essentially a
vertical system)
Stratigraphy for all areas similar to that found for First
Colony Farms (Area 1)
Depth of mining operations for all areas similar to that
proposed by PMA (Area 1)

Source:
Foutz, 1983.

5.2.4.5.14 Salt Water Encroachment in Shallow and Deep Aquifers

Areas 1 and 2
No significant lateral movement in the freshwater/saltwater
interface. Since there is already a wide diffused zone ranging
from salt to fresh water, the anticipated change in head due to
withdrawals (a few feet) is not expected to significantly change
the location of this diffused zone

Sources:
Perry Nelson, Groundwater Section, DEM, NRCD
PMA, 1983k

5.2.4.5.15 Revegetation of Canal/Ditch Banks

Revegetation is completed following ditch maintenance and as part
of reclamation through year 8

113

5.2.4.5.16 Erosion and Sediment Control Measures

Adequate mechanical barriers including but not limited to
diversions, settling ponds, earthen dikes, brush barriers,
silt check dams, silt retarding structures, rip rap pits or
ditches provided in the initial stages of any land disturbance
to prevent sediment from discharging onto any adjacent surface
areas or into any lake or natural watercourse in proximity to
the affected land. Following industry failure no structures
are maintained.

5.2.4.5.17 Buffer Strips Adjacent to Estuaries/Lakes/Rivers at
Years 10 and 20

Area 1 2000' tree buffer between
site and Phelps Lake

Area 2 300' between site and IWW

Note:
2000' tree buffer in Area 1 is outside permitted area
Sources:
PMA, 1983f
WTF Mining Permit

5.2.4.6 Air Quality Management

5.2.4.6.1 Maximum off-property Fugitive Dust Concentrations
Resulting from mining and Processing Operations

at Year 10: same as section 5.2.2.6.1

at Year 20: none

5.2.4.6.2 Mitigation Measures for Fugitive Dust Emissions from
Transportation of Peat in Use

1-10
Area 1
restricted speed limits
paving or watering of roadways
tree buffer strips

Area 2
restricted speed limits
tree buffer strips

Assumptions:
All of the above
Years 11-20: no mining

114

5.2.4.7 Solid Waste Management

5.2.4.7.1 Amount of Non-hazardous Waste Generated

1-10 3
Area 1 53,000 tons/yr (851,000 ft /yr*)
(non-burnable material from methanol production,
including 27,000 tons/yr of slag and fly ash)

Area 2 negligible
Assumptions: 3
* Assumes a bulk density of 0.062 tons/ft
No significant amount of non-hazardous waste generated in
Area 2
Years 11-20: none generated
Source:
PMA, 1983h, Fig. 1

5.2.4.7.2 Amount of Hazardous Waste Generated

1-103
Area 1 1,000 ft /yr (excluding catalysts recycled)
8,100 gals/yr waste oils

Area 2 none

Assumptions:
No hazardous wastes generated in Area 2 since no peat will
be processed on site
Years 11-20: none generated
Source:
PMA, 1983h

5.2.4.8.Wildlife Mitigation Measures

5.2.4.8.1 Permitted Acreage Restored to Native Vegetation
(Buffer Strips)

See section 5.2.4.10.6

Assumption:
20% mined/reclaimed land required re-established to
native vegetation or low intensity managed forest
for buffer strips
Source:
D. Owens, Office of Coastal Management, NRCD

115

5.2.4.8.2 Location of Native Vegetation Buffer Strips on
Permitted Areas at Year 10

see Figure 5E

5.2.4.9 Fire Protection Measures

5.2.4.9.1 Source and Volume of Water for Fire Suppression

1-10
Area 1 Canals, lagoons-
14 unharvested blocks
in use as water storage
reservoirs

Area 2 Fire protection/waterfowl
impoundment

Assumption:
Years 11-20: Areas will be floodE@d following cessation of
pumping
Source:
PMA, 1983c, pp. 13, 37

5.2.4.9.2 Water Control Structures for Areas Not Being Mined

Structures installed to prevent gravity drainage from lowering
water level lower than l' below ground level on lands not being
actively mined. These structures have capacity to retain sufficient
water to flood or saturate peat soil to or slightly above ground
level. Structures not functional after year 10.

Assumptions:
All of the above

ll 6

5.2.4.10 Reclamation

5.2.4.10.1 Mined Acreage Legally Required to be Reclaimed
(Cumulative)

by 10 by 20
Area 1 2,020 5,520

Area 2 1,500 3,000

Total 3,520 8,520

Assumptions:
NRCD requirement that mined areas be reclaimed within 2
years of completion of mining is met
Land mined during years 1-8 reclaimed on schedule (refers
to sections 5.2.4.10.3-5.2.4.10.8)
No land is reclaimed after year 8
Reclamation rate for Area 2
Land fully reclaimed (cumulative):

by 10 by 20
Area 1 2,020 2,020
Area 2 1,500 1,500
Source:
PMA, 1983d, Fig. 2-10

5.2.4.10.2 Percentage of Reclaimed Land in Various Types of
Reclamation by Year 10
Area 1 Area 2
Row crops with pumping 8 78

Row crops without pumping 0 0

Pine plantations 10 10

Restored native vegetation 10 10

Open water 72 0

Grass replanted 0 2

Assumptions:
Native vegetation restored in buffer strips as shown in Figure
5E
Pumping required for all reclaimed farmland
When pumping ceases, dikes around the central lake are broken,
Canal B is no longer maintained, and mined areas in Area 1
gradually fill up with water until, by year.20, all mined
acreage (5,520) has become open water. Area 2 also becomes
open water by year 20 (3,000 acres).

117

5.2.4.10.3 Mined Acreage in Row Crops with Pumping

by 10
Area 1 162

Area 2 1,170

Total 1,332

Calculations:
Sections 5.2.4.10.3-5.2.4.10.8 calculated based on
% in section 5.2.4.10.2 and acreages in section
5.2.4.10.1

5.2.4.10.4 Mined Acreage in Row Crops Without Pumping

by 10
Area 1 0

Area 2 0

Total 0

5.2.4.10.5 Mined Acreage in Pine Plantations (Including
Vegetative Buffer Strips)

by 10
Area 1 202

Area 2 150

Total 352

5.2.4.10.6 Mined Acreage Restored to Native Vegetation
(Buffer Strips)

by 10
Area 1 202

Area 2 150

Total 352

118

5.2.4.10.7 Mined Acreage in Open Water Reclamation With/Without
marshes and Islands (Including Canals)

by 10
Area 1 1,454

Area 2 0

Total 1,454

5.2.4.10.8 Mined Acreage Replanted to Grass

by 10
Area 1 0

Area 2 30

Total 30

5.2.4.10.9 Unreclaimed Disturbed Acreage Not Yet Legally
Required to be Reclaimed (Cumulative)

by 10 by 20
Area 1 3,500 0

Area 2 1,500 0

Total 5,000 0

Source:
Section 5.2.2.10.9

5.2.4.10.10 Unreclaimed Disturbed Acreage Legally Required to be
Reclaimed (Cumulative)

by 10 by 20
Area 1 0 3,500

Area 2 0 1,500

Total 0 5,000

Assumption:
All legally reclaimable land reclaimed on schedule only
through year 8

119

6. ENVIRONMENTAL AND ECONOMIC ASSESSMENT OF THE SCENARIOS

6.1 Resource Production/Consumption

6.1.1 Agriculture

6.1.1.1 Approach/Assumptions
Two approaches to estimating the value of agricultural
production under the alternative scenarios were taken: 1) the
value of mined land reclaimed to agriculture was estimated at.
years 10 and 20 (see section 6.1.1.1.1) and 2) the cumulative
value of total agricultural production on permitted sites
(reclaimed areas in row crops plus acreage already irk
agricultural production prior to mining and not yet mined) was
estimated for the periods years 1-10 and 1-20 (see section
6.1.1.1.2).
An important difference in the two approaches was that the
assumption was made in section 6.1.1.1.1 that no acreage was in
agricultural production at year 0, while in section 6.1.1.1.2
the assumption was made that part of the total permitted acreage
was in agricultural production at year 0 (see acreages by
habitat/land use type in Appendix 10.1).

6.1.1.1.1 Value of Mined Land Reclaimed to Row Crops at Years 10
and 20

1. Acreage in agricultural production (row crops) at years
10 and 20 for each scenario was based on sections
5.2.2.10.3, 5.2.3.10.3 and 5.2.4.10.3.

2. Crop mix was assumed to be traditional corn-soybeans
rotation on 50% of each area and corn-soybeans-wheat
rotation on the other 50%.

3. Budgets were based on standard budget for 1983
produced by Department of Economics and Business,
N. C. State University (see Appendix 10.2).

4. Run #1 - Yields assumed: 115 bushels (bu/ac) for corn,
3,5 bu for soybeans single cropped; 25 bu for soybeans
double cropped and 50 bu.for whE!at were estimated
based on yields reported in Soil. Survey of Washington
County (USDA, SCS, 1981). Prices assumed for Run #1:
Corn $2.26/bu, soybeans $5.85/bui and wheat $3.60/bu.

1120

5. Run #2 - Yields assumed: 115 bu for corn, 35 bu for
soybeans single cropped, 30 bu for soybeans double
cropped and 50 bu for wheat. Prices assumed for Run #2:
Corn $2.71/bu, soybeans $6.75/bu and wheat $4.00/bu.

6. Drainage cost was estimated at $10.00/acre/year.

6.1.1.1.2 Cumulative Value of Total Agricultural Production
on Permitted Sites During Years 1-10 and 1-20

1. Acreages in agricultural production in all permitted
areas at year 0 were based on habitat type/land use
data located in Appendix 10.1.

2. Crop mix, Run #1 and #2 assumptions and estimated
drainage costs were the same as in section 6.1.1.1.1.

3. Without the mining projects, agricultural production
was assumed to remain constant throughout the
20-year period.

4. Conversion rates from one habitat type/land use to
another were the same as those used in section
6.1.4 (see Appendix 10.4).

5. A Suitability Index (SI) was determined for each crop
by multiplying assumed yield (bu/ac) x price/bu x %
of cropland planted with that crop.

6. Annualized units (SI x acres of cropland) for each
crop for each year were computed.

7. Cumulative values for the periods years 1-10 and years 1-20
were calculated.

121

6. 1. 1. 1. 2 Data

Table 6.1.1A: Value of mined areas reclaimed to row crops with
pumped drainage at years 10 and 20 (Run #1)

Crop Reclaimed Total Gross Income Net Return
Acres in Bushels Per Year to Land and
Row Crops Per Year Mgt Per Year

Scenario #1 - Area 1

1. 162 acres reclaimed to row crops at year 10

Corn 81 9,315 $ 21,052 $ 3,818
Soybeans 40 1,400 8,190 2
Soybeans- 1,025
Wheat 41 2,050 13,376 2,271
Total $ 42,618 $ 6,091

2. 4,930 acres reclaimed to row crops at year a-
Corn 2,465 283,475 $ 640,654 $ 116,195
Soybeans 1,232 43,120 252,252 62
Soybeans- 30,825
Wheat 1,233 61,650 402,266 68,297
Total 1,295,172 $ 184,554

Scenario #1 - Area 2

1. 1,170 acres reclaimed to row crops at year 10
Corn 585 67,275 $ 152,042 $ 27,576
Soybeans 292 10,220 59,787 15
Soybeans- 7,325
Wheat 293 14,650 95,591 16,229
Total 307,420 $ 43,820

2. 3,510 acres reclaimed to row crops at year 20
Corn 1,755 201,825 456,125 $ 82,727
Soybeans 877 30,695 179,566 44
Soybeans- 21,950
Wheat 878 43,900 286,448 48,633
Total 922,139 $ 131,404

122

Table 6.1.1A (Continued)

Crop Reclaimed Total Gross Income Net Return to
Acres in Bushels Per Year Land and Mgt
Row Crops Per Year Per Year

Scenario #2 - Area 1

1. 1,368 acres reclaimed to row crops at year 10

Corn 684 78,660 $ 177,772 $ 32,242
Soybeans 342 11' 970 70,025 17
Soybeans- 8,550
Wheat 342 17,100 111,578 18,944
Total $ 359,375 $ 51,203

2. 15,543 acres reclaimed-to row crops at year 20

Corn 7,772 893,780 $ 2,019,943 $ 366,357
Soybeans 3,885 135,975 795,454 196
Soybeans- 97,150
Wheat 3,886 194,300 1,267,808 215,248
Total $ 4,083,205 $ 581,801

Scenario #2 - Area 2

1. 2,223 acres reclaimed to row crops at year 10

Corn 1,112 127,880 $ 289,009 $ 52,418
Soybeans 555 19,425 113,636 28
Soybeans- 13,900
Wheat 556 27,800 181,395 30,797
Total $ 584,040 $ 83,243

2. 9,594 acres reclaimed to row crops at year 20

Corn 4,797 551,655 $ 1,246,740 $ 226,121
Soybeans 2,398 83,930 490,991 121
Soybeans- 59,975
Wheat 2,399 119,950 782,674 132,882
Total $ 2,520,405 $ 359,124

123

Table 6.1.1A (Continued)

Crop Reclaimed Total Gross Income Net Return to
Acres in Bushels Per Year Land and Mgt
Row Crops Per Year Per Year

Scenario #2 - Area 3

1. 2,925 acres reclaimed to row crops at year 10

Corn 1,463 168,245 $ 380,234 68,963
Soybeans 731 25,585 149,672 37
Soybeans- 18,275
Wheat 731 36,550 238,489 40,491
Total $ 768,395 $ 109,491

2. 15,750 acres reclaimed to row crops at year 20

Corn 7,875 905,625 $ 2,046,713 $ 371,212
Soybeans 3,938 137,830 806,306 198
Soybeans- 98,425
Wheat 3,937 196,850 1,284,446 218,073
Total $ 4,137,465 $ 589,483

Scenario #2 - Area 4

No land in row crops at year 10 or 20.

Scenario #3 (both areas)

Same as Scenario #1 at year 10 in ArE!as 1 and 2.

12 4

Table 6.1.1B: Value of mined areas reclaimed to row crops with
pumped drainage at years 10 and 20 (Run #2)

Crop Reclaimed Total Gross Income Net Return to
Acres in Bushels Per Year Land and Mgt
Row Crops Per Year Per Year

Scenari'o #1 - Area 1

1. 162 acres reclaimed to row crops at year 10

Corn 81 9,315 $ 25,244 $ 8,010
Soybeans 40 1,400 9,450 1,262
Soybeans- 1,230
Wheat 41 2,050 16,503 5,397
Total $ 51,197 $ .14,669

2. 4,930 acres reclaimed to row crops at year 20

Corn 2,465 283,475 $ 768,217 $ 243,763
Soybeans 1,232 43,120 291,060 38,868
Soybeans- 36,990
Wheat 1,233 61,650 496,283 162,314
Total $ 1,555,560 $444,945

Scenario #1 - Area 2

1. 1,170 acres reclaimed to row crops at year 10

Corn 585 67,275 $ 182,315 $ 57,850
Soybeans 292 10,220 68,985 9,212
Soybeans- 8,790
Wheat 293 14,650 117,933 38,571
Total $ 369,233 $ 105,633

2. 3,510 acres reclaimed to row crops at year 20
Corn 1,755 201,825 $ 546,946 $ 173,551
Soybeans 877 30,695 207,191 27,668
Soybeans- 26,340
Wheat 878 43,900 353,395 115,581
Total $ 1,107,532 $316,800

125

Table 6.1.1B (Continued)

Crop Reclaimed Total Gross Income Net Return to
Acres in Bushels Per Year Land and Mgt:
Row Crops Per Year Per Year

Scenario #2 - Area 1

1. 1,368 acres reclaimed to row crops at year 10

Corn 684 78,660 $ 213,169 $ 67,641
Soybeans 342 11,970 80,798 10,790
Soybeans- 10,260
Wheat 342 17,100 137,655 45,021
Total $ 413,622 $ 123,452

2. 15,543 acres reclaimed to row crops at year 20

Corn 7,772 893,780 $ 2,422,144 $ 768,570
Soybeans 3,885 135,975 917,831 122,567
Soybeans- 116,580
Wheat 3,886 194,300 1,564,115 511,559
Total $ 4,904,090 $1,402,696

Scenario #2 - Area 2

1. 2,223 acres reclaimed to row crops at year 10

Corn 1,112 127,880 $ 346,555 $ 109,965
Soybeans 555 19,425 131,119 17,510
Soybeans- 16,680
Wheat 556 27,800 223,790 73,193
Total $ 701,464 $ 200,668

2. 9,594 acres reclaimed to row crops at year 20

Corn 4,797 551,655 $ 1,494,985 474,374
Soybeans 2,398 83,930 566,528 75,654
Soybeans- 71,970
Wheat 2,399 119,950 965,598 315,808
Total $ 3,027,111 $ 865,836

126

Table 6.1.1B (Continued)

Crop Reclaimed Total Gross Income Net Return to
Acres in Bushels Per Year Land and Mgt
Row Crops Per Year Per Year

Scenario #2 - Area 3

1. 2,925 acres reclaimed to row crops at year 10

Corn 1,463 168,245 $ 455,944 $ 144,676
Soybeans 731 25,585 172,699 23,062
Soybeans- 21,930
Wheat 731 36,550 294,228 96,230
Total $ 922,871 $ 263,968

2. 15,758 acres by 20 years

C6rn 7,875 905,625 $ 2,455,244 $ 778,756
Soybeans 3,938 137,830 930,353 124,239
Soybeans- 118,110
Wheat 3,937 196,850 1,584,643 518,273
Total $ 4,970,240 $1,421,268

Scenario #2 - Area 4

No land in row crops at year 10 or 20

Scenario #3 (both areas)

Same as Scenario #1 at year 10 in 20

127

Table 6.1.1C: Summary- Value of mined areas reclaimed to
agriculture with pumped drainage at years 10
and 20 (Run #1)

Reclaimed Gross Net Return to Net Income
Acres in Income Land and Mgt Minus
Row Crops Per Year Per Year Drainage Cost

Scenario #1 (both areas)

At year 10 1,332 $ 350,038 $ 49,911 $ 36,585
At year 20 8,440 2,217,211 315,958 231,597

Scenario #2 (all areas)

At year 10 6,516 $ 1,711,810 $ 243,937 $ 178,806
At year 20 40,887 10,741,075 1,530,408 1,121,789

Scenario #3 (both areas)

Same as Scenario #1 at year 10

Table 6.1.lD: Summary- Value of mined areas reclaimed to
agriculture with pumped drainage at years 10
and 20 (Run #2)

Reclaimed Gross Net Return to Net Income
Acres in Income Land and Mgt Minus
Row Crops Per Year Per Year Drainage Cost

Scenario #1 (both areas)

At year 10 1,332 $ 420,430 $ 120,302 $ 106,948
At year 20 8,440 2,663,092 761,745 677,191

Scenario #2 (all areas)

At year 10 6,516 $ 2,055,957 $ 588,088 $ 522,810
At year 20 40,887 12,901,441 3,689,800 3,280,232

Scenario #3 (both areas)

Same as Scenario #1 at year 10

128

Table 6.1.1E: Cumulative value of total acreage in row
crops with the mining projects (Run #1)

Crop Gross Income Net Return to
(Cumulative) Land & Mgmt
(Cum)
Scenario #1, Area 1

1. Years 1-10

Corn $ 3,010,000 $ 545,924
Soybeans 1,190,000 293
Soybeans- 850,000
Wheat 1,040,000 320,884
Total 6,090,000 867,101

2. Years 1-20

Corn 8,280,000 1,501,744
Soybeans 3,260,000 802
Soybeans- 2,340,000
Wheat 2,860,000 882,856
Total 16,740,000 2,385,402

Scenario #1, Area 2

1. Years 1-10

Corn 1,540,000 279,310
Soybeans 610,000 150
Soybeans- 430,000
Wheat 530,000 162,989
Total 3,110,000 442,449

2. Years 1-20

Corn 5,300,000 961,261
Soybeans 2,080,000 512
Soybeans- 1,500,000
Wheat 1,840,000 567,065
Total 10,720,000 1,528,838

129

Table 6.1.1E (Continued)

Crop Gross Income Net Return to
(Cumulative) Land & Mgmt
(cum)

Scenario #2, Area 1

1. Years 1-10

Corn 3,190,000 578,570
Soybeans 1,260,000 310
Soybeans- 900,000
Wheat 1,100,000 339,560
Total 6,450,000 918,440

2. Years 1-20

Corn 16,940,000 3,072,408
Soybeans 6,680,000 1,643
'Soybeans- 4,760,000
Wheat 5,860,000 1,803,064
Total 34,240,000 4,877,115

Scenario #2, Area 2

1. Years 1-10

Corn 2,020,000 366,367
Soybeans 800,000 197
Soybeans- 570,000
Wheat 700,000 215,621
Total 4,090,000 582,185

2. Years 1-20

Corn 10,740,000 1,947,914
Soybeans 4,240,000 1,043
Soybeans- 3,020,000
Wheat 3,720,000 1,144,317
Total 21,720,000 3,093,274

130

Table 6.1.1E (Continued)

Crop Gross Income Net Return to
(Cum) Land & Mgmt
(Cum)

Scenario #2, Area 3

1. Years 1-10

Corn 1,220,000 221,271
Soybeans 480,000 118
Soybeans- 340,000
Wheat 420,000 129,033
Total 2,460,000 350,422

2. Years 1-20

Corn 15,060,000 2,731,432
Soybeans 5,920,000 1,456
Soybeans- 4,240,000
Wheat 5,220,000 1,606,119
Total 30,440,000 4,339,007

Scenario #2, Area 4

1. Years 1-10

Corn 270,000 48,970
Soybeans 100,000 25
Soybeans 70,000
Wheat 90,000 27,165
Total 530,000 76,160

2. Years 1-20

Corn 480,000 87,058
Soybeans 200,000 49
Soybeans- 140,000
Wheat 160,000 50,934
Total 980,000 138,041

Scenario #3 (both areas)

Same as Scenario #1, Areas 1 and 2, years 1-10

131

Table 6.1.1F: Cumulative value of total acreage in row
crops without the mining projects (Run

Crop Gross Income Net Return to
(Cum) Land & Mgmt
(Cum)

Scenario #1, Area 1

1. Years 1-10

Corn 3,700,000 671,069
Soybeans 1,460,000 359
Soybeans- 1,040,000
Wheat 1,280,000 -393,890
Total 7,480,000 1,065,318

2. Years 1-20

Corn 7,400,000 1,342,138
Soybeans 2,920,000 718
Soybeans- 2,080,000
Wheat 2,560,000 787,779
Total 14,960,000 2,130,636

Scenario #1, Area 2

1. Years 1-10

Corn 1,390,000 252,104
Soybeans 550,000 135
Soybeans- 390,000
Wheat 480,000 1.47,709
Total 2,810,000 399,948

2. Years 1-20

Corn 2,780,000 504,209
Soybeans 1,100,000 270
Soybeans- 780,000
Wheat 960,000 295,417
Total 5,620,000 799,896

132

Table 6.1.1F (Continued)

Crop Gross Income Net Return to
(CUM) Land & Mgmt
(CUM)

scenario #2, Area 1

1. Years 1-10

Corn 3,510,000 636,609
Soybeans 1,380,000 340
Soybeans- 990,000
Wheat 1,220,000 375,214
Total 7,100,000 1,012,163

2. Years 1-20

Corn 7,020,000 1,273,217
Soybeans 2,760,000 679
Soybeans- 1,980,000
Wheat 2,440,000 750,428
Total 14,200,000 2,024,324

Scenario #2, Area 2

1. Years 1-10

Corn 1,560,000 282,937
Soybeans 610,000 150
Soybeans- 440,000
Wheat 540,000 166,384
Total 3,150,000 449,471

2. Years 1-20

Corn 3,120,000 565,874
Soybeans 1,220,000 300
Soybeans- 880,000
Wheat 1,080,000 332,769
Total 6,300,000 898,943

133

Table 6.1.1F (Continued)

Crop Gross Income Net Return to
(CUM) Land & Mgmt
(Cum)

Scenario #2, Area 3

No land in agricultural production years 1-20

Scenario #2, Area 4

1. Years 1-20

Corn 340,000 61,6661
Soybeans 130,000 32
Soybeans- 100,000
Wheat 120,000 37,352
Total 690,000 99,050

2. Years 1-20

Corn 680,000 123,332
Soybeans 260,000 64
Soybeans- 200,000
Wheat 240,000 74,703
Total 1,380,000 1,98,099

Scenario #3 (both areas)

Same as Scenario #1, Areas 1 and 2, years 1-10

134

Table 6.1.1G: Cumulative value of total acreage in row
crops with the mining projects (Run #2)

Crops Gross Income Net Return to
(Cumulative) Land & Mgmt
($) (cum)

Scenario #1, Area 1

1. Years 1-10

Corn 3,610,000 1,145,489
Soybeans 1,370,000 182,950
Soybeans- 1,170,000
Wheat 1,160,000 762,050
Total 7,310,000 2,090,489

2. Years 1-20

Corn 9,920,000 3,147,715
Soybeans 3,760,000 502,110
Soybeans- 3,220,000
Wheat 3,180,000 2,093,184
Total 20,080,000 5,743,009

Scenario #1, Area 2

1. Years 1-10

Corn 1,840,000 583,850
Soybeans 700,000 93,478
Soybeans- 600,000
Wheat 590,000 389,201
Total 3,730,000 1,066,529

2. Years 1-20

Corn 6,360,000 2,018,092
Soybeans 2,400,000 320,496
Soybeans- 2,060,000
Wheat 2,040,000 1,340,946
Total 12,860,000 3,679,534

135

Table 6.1.1G (Continued)

Crop Gross Income Net Return to
(Cum) Land & Mgmt
(Cum)

Scenario #2, Area 1

1. Years 1-10

Corn 3,820,000 1,21.2,124
Soybeans 1,450,000 193,633
Soybeans- 1,240,000
Wheat 1,230,000 807,838
Total 7,740,000 2,21.3,595

2. Years 1-20

Corn 20,300,000 6,441,393
Soybeans 7,700,000 1,028,258
Soybeans- 6,600,000
Wheat 6,520,000 4,291,027
Total 41,120,000 11,760,678

Scenario #2, Area 2

1. Years 1-10

Corn 2,420,000 767,890
Soybeans 920,000 122,@857
Soybeans- 790,000
Wheat 780,000 513,484
Total 4,910,000 1,404,231

2. Years 1-20

Corn 12,880,000 4,086,953
Soybeans 4,880,000 651,675
Soybeans- 4,180,000
Wheat 4,140,000 2,721,139
Total 26,080,000 7,459,767

136

Table 6.1.1G (Continued)

Crop Gross Income Net Return to
(cum) Land & Mgmt
(Cum)

Scenario #2, Area 3

1. Years 1-10

Corn 1,460,000 463,273
Soybeans 550,000 73,447
Soybeans- 470,000
Wheat 470,000 307,436
Total 2,950,000 844,156

2. Years 1-20

Corn 18,040,000 5,724,272
Soybeans 6,840,000 913,414
Soybeans- 5,860,000
Wheat 5,800,000 3,813,520
Total 36,540,000 10,451,206

Scenario #2, Area 4

1. Years 1-10

Corn 320,000 101,539
Soybeans 120,000 16,025
Soybeans- 100,000
Wheat 100,000 65,412
Total 640,000 182,976

2. Years 1-20

Corn 580,000 184,040
Soybeans 220,000 29,379
Soybeans- 180,000
Wheat 180,000 117,742
Total 1,160,000 331,161

Scenario #3 (both areas)

Same as Scenario #1, Areas 1 and 2, years 1-10

137

Table 6.1.1H: Cumulative value of total acreage in row
crops without the mining projects (Run #2)

Crop Gross Income Net Return to
(Cumulative) Land & Mgmt
(Cum)

Scenario #1, Area 1

l..Years 1-10

Corn 4,440,000 1,408,856
Soybeans 1,680,000 224,347
Soybeans- 1,440,000
Wheat 1,420,000 935,392
Total 8,980,000 2,568,595

2. Years 1-20

Corn 8,880,000 2,817,713
Soybeans 3,360,000 448,694
Soybeans- 2,880,000
Wheat 2,840,000 1,870,783
Total 17,960,000 5,137,190

Scenario #1, Area 2

1. Years 1-10

Corn 1,670,000 529,908
Soybeans 630,000 84,130
Soybeans- 540,000
Wheat 540,000 353,225
Total 3,380,000 967,263

2. Years 1-20

Corn 3,340,000 1,059,815
Soybeans 1,260,000 168,260
Soybeans- 1,080,000
Wheat 1,080,000 706,450
Total 6,760,000 1,934,525

138

Table 6.1.1H (Continued)

Crop Gross Income Net Return to
(Cum) Land & Mgmt
(Cum)

Scenario #2, Area 1

1. Years 1-10

Corn 4,210,000 1,335,875
Soybeans 1,600,000 213,664
Soybeans- 1,370,000
Wheat 1,350,000 889,603
Total 8,530,000 2,439,142

2. Years 1-20

Corn 8,420,000 2,671,750
Soybeans 3,200,000 427,328
Soybeans- 2,740,000
Wheat 2,700,000 1,779,206
Total 17,060,000 4,878,284

Scenario #2, Area 2

1. Years 1-10

Corn 1,870,000 593,370
Soybeans 710,000 94,813
Soybeans- 610,000
Wheat 600,000 395,743
Total 3,790,000 1,083,926

2. years 1-20

Corn 3,740,000 1,186,739
Soybeans 1,420,000 189,627
Soybeans- 1,220,000
Wheat 1,200,000 791,485
Total 7,580,000 2,167,851

139

Table 6.1.1H (Continued)

Crop Gross Income Net Return to
(Cum) Land & Mgmt
(Cum)

Scenario #2, Area 3

No land in agricultural production years 1-20

Scenario #2, Area 4

1. Years 1-10

Corn 410,000 1.30,097
Soybeans 150,000
Soybeans- 130,000
Wheat 130,000 :35,036
Total 820,000 2.35,164

2. Years 1-20

Corn 820,000 260,194
Soybeans 300,000 40,062
Soybeans- 260,000
Wheat 260,000 1-70,071
Total 1,640,000 470,327

Scenario #3 (both areas)

Same as Scenario #1, Areas 1 and 2, 1
years 1-10

140

Table 6.1.11: Summary- Cumulative value of total acreage
in row crops with the mining projects
(Run# 1)

Gross Income Net Return to Net Income
(Cumulative) Land & Mgmt Minus Drainage
(Cum) Cost (CUM)
Scenario #1
(both areas)

Years 1-10 9,200,000 1,309,550 959,900
Years 1-20 27,460,000 3,914,240 2,869,138

Scenario #2
(all areas)

Years 1-10 13,530,000 1,927,207 1,412,643
Years 1-20 87,380,000 12,447,437 9,123,971

Scenario #3
(both areas)

Years 1-10 same as Scenario #1, years 1-10

Table 6.1.1J: Summary- Cumulative value of total acreage
in row crops without the mining projects
(Run #1)

Gross Income Net Return to Net Income
(Cumulative) Land & Mgmt Minus Drainage
(Cum) Cost (CUM)
Scenario #1
(both areas)

Years 1-10 10,290,000 1,465,266 1,074,040
Years 1-20 20,580,000 2,930,532 2,148,080

Scenario #2
(all areas)

Years 1-10 10,940,000 1,560,684 1,143,981
Years 1-20 21,880,000 3,121,366 2,287,961

Scenario #3
(both areas)

Years 1-10 same as Scenario #1, years 1-10

141

Table 6.1.1K: Summary-- Cumulative impacts on row crop
agriculture years 1-20 with and without
the projects (Run #1) - Net income minus
drainage costs ($)

Years 1-10 Years 1-20

With Without With Without

Scenario #1 959,900 1,074,040 2,869,138 2,148,080

Scenario #2 1,412,643 1,143,981 9,123,971 2,287,961

Scenario #3 959,900 1,074,040 -

Table 6.1.1L: Summary-- Cumulative value of total acreage
in row crops with the mining projects
(Run #2)

Gross Income Net Return to Net Income
(Cumulative) Land & Mgmt Minus Drainage
(Cum) Cost (Cum)
Scenario #1
(both areas)

Years 1-10 11,040,000 3,157,018 2,314,094
Years 1-20 32,940,000 9,422,543 6,906,724

Scenario #2
(all areas)

Years 1-10 16,240,000 4,6441,958 3,404,754
Years 1-20 104,900,000 30,002,812 21,992,061

Scenario #3
(both areas)

Years 1-10 same as Scenario #1, years 1-10

142

Table 6.1.1M: Summary- Cumulative value of total acreage
in row crops without the mining projects
(Run #2)

Gross Income Net Return to Net Income
(Cumulative) Land & Mgmt Minus Drainage
(Cum) Cost (Cum)
Scenario #1
(both areas)

Years 1-10 12,360,000 3,535,858 2,591,784
Years 1-20 24,720,000 7,071,715 5,183,567

Scenario #2
(all areas)

Years 1-10 13,140,000 3,758,232 2,754,784
Years 1-20 26,280,000 7,516,462 5,509,567

Scenario #3
(both areas)

Years 1-10 same as Scenario #1, years 1-10

Table 6.1.1N: Summary- Cumulative impact on row crop
agriculture years 1-20 with and without
the projects (Run #2) Net income
minus drainage costs

Years 1-10 Years 1-20

With Without With Without

Scenario #1 2,314,094 2,591,784 6,906,724 5,183,567

Scenario #2 3,404,754 2,754,784 21,992,061 5,509,567

Scenario #3 2,314,094 2,591,784 - -

6.1.1.2.3 Summary and Conclusions

6.1.1.2.3.1 Net Annual Income from Mined Lands Reclaimed
to Agriculture

Using the assumptions for Run #1, the annual income at year
20 under Scenario #1 is estimated to be $231,597 on 8,440 acres
planted to corn, soybeans and wheat. Annual income under
Scenario #2 at year 20 is estimated to be @1,121,789 on 40,887

143

acres. Under Scenario #3, annual income at year 10 is $36,585 on
1,332 acres.
For Run #2, with the slightly higher prices and a higher
yield for soybeans double cropped, the annual. income at year 20
under Scenario #1 is estimated to be $677,191 for 8,440 acres
planted to corn, soybeans and wheat. Under Scenario #2, with the
same crop mix, annual income at year 20 is estimated to be!
$3,280,232 on 40,887 acres. Annual income under Scenario #3 at.
year 10 would be $106,948 on 1,332 acres.

6.1.1.2.3.2 Cumulative Value of Agricultural Lands Under the
Alternative Scenarios

Based on Run #1 assumptions, cumulative net income minus
drainage costs under Scenario #1 for the 20-year study period is;
approximately $2,869,000 with the projects and $2,148,000
without the projects. Under Scenario #2, cumulative net income
for the 20-year period is approximately $9,124,000 with the
projects and $2,288,000 without the projects. Estimated
cumulative net income under Scenario #3 during the period prior:
to industry failure and flooding of the permitted areas (years
1-10) is $960,000 with the projects and $1,074,000 without the
projects. The with-project loss in agricultural production
during years 1-10 under Scenarios #1 and #3 is due to the
conversion of agricultural land into mined acreage. Since
reclamation in Area 1 (Scenarios #1 and #3) involves the
creation of a 1454-acre lake during the first 10 years of:
mining, more agricultural land is lost to mining than is gained
via reclamation during this period. Thus the cumulative value of:
agricultural production under these two scenarios is lower with
the projects than wihout the projects for the first 10 years.
Based on Run #2 assumptions, cumulative net income minus
drainage costs for the 20-year period under Scenario #1 is
estimated at approximately $6,907,000 with the projects and
$5,184,000 without the projects. Under Scenario #2, cumulative
net income for the 20 years is about $21,992,000 with the
projects and $5,510,000 without the projects. Estimated
cumulative net income under Scenario #3 during years 1-10 is
approximately $2,314,000 with the projects and $2,592,000
without the project.
The mining projects will thus add between $2.9 and 6.1.)
million (Scenario #1) or between $9.1 and 22 million (Scenario
#2) to the local agricultural economy during the 20-year study
period. Under Scenario #3, the local agricultural economy will
lose between $114,000 and $278,000 during 10 years of mining.

144

6.1.2 Forest Products

6.1.2.1.Approach/Assumptions

Data were collected on the present forestry production
value of the areas covered by the scenarios prior to peat mining
activities. Information on forest products was scarce. No
information was obtained for Areas 2 and 4 (Scenario #2). Total
acreage of woodland by type was based on habitat type/land use
data in Appendix 10.1.

Assumptions made were:

1. The pocosin acreage in Area 1 of Scenario #1 was assumed to
have no present timber value (based on discussions with H.
Truesdell, First Colony Farms, and Sizemore and Sizemore,
a consulting firm that conducted a forest appraisal survey
on First Colony Farms in 1978).

2. The current total timber value for Areas I and 3 of
Scenario #2 was estimated at $1,500,000. Several Atlantic
white cedar and swamp hardwood forest stands of high value
are located in Area 3, but limited access reduces their
value considerably below their potential market value of
several million dollars (H. Truesdell, First Colony Farms,
personal communication).

3. All timber would be cut once a block was established for
peat mining. This would reduce harvest costs and maximize
returns.

4. Pine plantation value was based on a per acre value at year
20 (site index 40-60). The,value from years 0 to 20 is
based roughly on a yield of 35-40 (approximately 2 cords
per years) cords per acre for pulpwood at $15-25 per cord
value. These values assume a well-managed plantation
(fully stocked). The values are prorated and adjusted for
future worth at 6% inflation.

5. A large portion of this plantation land will act as a
buffer strip and would not be available for harvesting.
The amount of this land can not be determined at this time.

145

6.1.2.2 Data

Table 6.1.2A: Scenario #2 (Areas 1 and 3)-- Value of timber
harvested prior to peatt mining

Area Year Timber Value

1 10 0
1 20 0

3 10 233,000
3 20 1,500,000

Total value 1,500,000

Table 6.1.2B: Scenario #2-- Value of plantation pine if
harvested at year 20

Area Year Timber Value

1 10 0
1 20 1,291,500 - 2,460,000

2 10 0
2 20 645,750 - 1,2--:10,000

3 10 0
3 20 1,102,500 - 2,100,000

4 10 0
4 20 2,086,875 - 3,975,000

Total value 5,124,000 - 9,765,000

6.1.2.3 Conclusions

The present value of the timber (hardwood, cedar) contained
in Areas 1 and 3 of Scenario #2 is approximately $1,500,000. The
plantation pine in all four areas will have a $5 - 10 million
value at year 20 if 1) it is all harvested and 2) it has been
properly managed. The net result will be a gain in timber value
due to the activity of peat mining and reclamation in pine
plantations. However, Atlantic white cedar habitat will be
significantly reduced.

146

6.1.3 Fish

6.1.3.1 Approach/Assumptions

Major freshwater and estuarine recreational and commercial
fisheries occur in and around the Albemarle-Pamlico Peninsula.
However, available information is not extensive enough to fully
assess the impacts that may occur as a result of the alternative
scenarios (see section 7.1).

The literature for North Carolina and other coastal
estuarine areas of the United States were examined to determine
the results of studies related to the fisheries impacts of
altered freshwater flows. (Abstracts of literature reviewed may
be found in Appendix 10.3.) Altered salinities and water
quality in marine finfish and shellfish nursery grounds are
considered negative impacts by many biologists familiar with
such areas (Stegman, 1981). The major factors that alter
historic freshwater flow patterns and water quality are upstream
municipal and industrial development (including dams) and local
and upstream agricultural practices. These factors, as well as
exploitation, have degraded many fisheries (Rote and Roberts,
1981; Stegman, 1981; Armstrong and Ward, 1981; Spear, 1981).
The impacts on estuarine fisheries of large-scale agriculture,
forestry and peat mining activities that accelerate drainage and
otherwise modify normal movemets, quantities and quality of
surface waters are not fully understood and should be
investigated further.

6.1.3.2 Conclusions

6.1.3.2.1 Scenario #1

6.1.3.2.1.1 Area 1

The fisheries resources of Area 1 are limited to canals and
low order streams. Appreciable sport or commercial fisheries do
not exist in the immediate area covered by this scenario, and
the species are generally tolerant of low pH-humic waters which
may be subject to periodic drying. Drainage and lowered water
tables will restrict fish to canal and water storage areas.
Reduced flows of streams (all waters are to be stored in
temporary ponds) could eliminate fish from small streams during
much of the year. Migration and spawning of many species occurs
in late winter and spring. Accelerated removal of the waters at
this time will limit those activities.

Since lateral seepage is indicated as low in peat soils,
water levels of Pungo Lake and Lake Phelps may not be affected
by lowering of soil water levels some distance from the lakes.
However, alterations of surface drainage patterns to or from the

147

lakes may affect their levels and, consequently, their
fisheries.

No other significant effects on the fisheries of Lake
Phelps or Pungo Lake are anticipated unless there is increased
sedimentation due to wind blown material. An increase in
sedimentation could be a significant problem to Lake Phelps,
especially since the present levels of suspended residue in this
lake are extremely low.
Until water quality and configuration of the storage lakes;
are more clearly described, predictions of the fish complexes;
which may develop in the areas are not possible. If the water,
quality resembles that of Pungo Lake, the fisheries will be less
desirable than if the water quality resembles Lake Phelps.
Suspended organic matter (probably of peat origin), low pH,
low total hardness and shallow character (less than 3 ft) of'
Pungo Lake precludes a desirable sport fishery. Species present:
include yellow bulhead, channel catfish, longnose gar,
mosquitofish, and little else. The standing crop is probably
less than 40 pounds per acre.
Lake Phelps apparently is not afflicted with as many
factors limiting to fish and as a result the fish population is
considered more desirable.
No significant effects on anadromous species are expected.
Aquaculture potentials have not been adequately explored
and would depend on characteristics of soils, waters and species
cultured. Availability of pumping facilities and high quality
aquifer water suggest that a potential for this activity exists.

6. 1. 3. 2. 1. 2 Area 2

Studies of the fish and fisheries of Area 2 have not been
conducted, but they are probably similar to those of Area 1.
A difference is that some streams and canals are connected
to the Intracoastal Waterway (IWW) and may be periodically
invaded by estuarine forms including American eel and herring.
Drainage canals opening into the IWW may provide additional
spawning sites for herring, but will probably not significantl,
Y
increase the population of this species. American eel elvers
may also use the new environments, but their overall population
will probably not be increased.
Drainage of water from Area 2 to the IWW suggests that
impacts on Lake Mattamuskeet fisheries will be negligible.

148

Aquaculture potential is similar to that of Area 1, except
that brackish waters may also be available, depending on canal
depths in relation to the water level of the. IWW.

Waters drained to the IWW would result in increased
amplitudes of fresh water during times of high precipitation and
reduced fresh water during periods of low rainfall. Thus
salinities and flows of the IWW may be affected. Impacts of
those changes and the extent to which they may influence the
Pungo and Alligator Rivers and their fisheries are not'known.

6.1.3.2.2 Scenario #2

6.1.3.2.2.1 Area 1

Impacts on fisheries will be similar to those described in
section 6.1.3.2.1.1; however, the volume of drainage water
entering the Pungo River via Canal B will be much greater. The
effect of this increased runoff on the fisheries in receiving
waters is unknown.

6.1.3.2.2.2 Area 2

Impacts on fisheries will be similar to those described in
section 6.1.3.2.1.2.

6. 1. 3. 2. 2. 3 Area 3

Impacts will be similar to Area 2 except that waters would
move by sheet flow toward the IWW and the Alligator River.
Volumes and periodicities would be determined by velocities of
sheet flow, presumably greater than presently occur.

6.1.3.2.2.4 Area 4

The effects of increased amplitudes of fresh water to the
Alligator River and its associated fisheries can not be
determined until these fisheries are described.

The fisheries that are likely to develop in the lagoons
will probably be similar to those described for the water
storage areas in section 6.1.3.2.1.1.

149

6.1.3.2.3 Scenario #3

6. 1. 3. 2. 3. 1 Area 1

Failure of the industry and flooding of the mined areas
will result in fish populations other than those present in
streams and canals. Depending on the expanses and depths of the
flooded areas, the fish populations will be more or less similar
to those currently found in standing waters in the area (see
section 6.1.3.2.1.1). If the waters are of appreciable depth
and permanent in nature, the freshwater fisheries may be of
value as recreational resources and as limited commercial
fisheries.

6. 1. 3. 2. 3. 2 Area 2

Freshwater fisheries impacts will probably be similar to
those in Area 1 except that abandoned drainage canals may
continue to function and divert surface waters to the IWW. The
use of the canals by anadromous and catadromous (American eel)
species will depend on flows in the canals and the extent of
vegetative re-establishment.

150

6.1.4 Wildlife

6.1.4.1 Approach/Assumptions

Wildlife habitat impacts were evaluated (Appendix 10.4)
through a modified Habitat Evaluation Procedure (HEP) analysis
(U.S. Fish and Wildlife Service, 1980) which involved:

1. Inventorying existing habitat-land use types in each
project area

2. Selecting an array of "indicator species" representative of
various environmental conditions

3. Determining a Habitat Suitability Index (HSI) for each
species in each habitat-land use type

4. Selecting a regression that describes the change from one
type to another, under each scenario and the no change
alternative

5. Computing annualized habitat units (HSI x (type x acres))
for each species for each year during the project period
and summing the results as indicators of impacts during
the period

6. Computing average HSI's for each species for each area
pre- and post-project as static indicators of conditions
at those times

Validity of the process depends upon the degree to which
the array of species used reflects total "wildlife value" in the
area, the validity of the Habitat Suitability Indices (HSIs),
and the accuracy with which land use change regressions reflect
actual events -- all of which are subject to large error. It
does, however, provide a quantitative, reproducible measure of
impacts and its assumptions and mathematical functions are
declared and can be modified to accommodate differences in
opinion and to test sensitivity.

Indicator species and habitat suitability indices were
obtained from the North Carolina Wildlife Resources Commission
(D. Stewart, North Carolina Wildlife Resources Commission,
personal communication). Habitat types and acreages of each
habitat type were based on data in Appendix 10.1. Changes in
land use over time were based on the scenarios and, for the no
change alternative, on reasonable assumptions (e.g., rotation
rates on forested lands).

151

Assumptions made in the simulation were:

Without the project:

1. No timber is harvested from high or low pocosins

2. Agricultural land, residential development, roads and
rights-of-way, and other developed area habitat types
remain in current acreage

3. Disturbed areas revert to native vegetation in the same
proportions as currently exist, as an exponential
function over 5 years

4. Forested habitat types are harvested (converted to
disturbed land) at exponential rates corresponding
to the reciprocal of their rotation period:

Assumed Rotation Ages

Habitat Type Rotation Period
(years)

Evergreen forest 30
Mixed forest 60
Deciduous forest 60
White cedar swamp 80
Mixed swamp 80
Bay forest 100

5. All inactive unreclaimed mine reverts to water and marsh
habitat as a linear function over 5 years

With the project - all scenarios:

1. Habitat types are converted to peat mine in the same
proportions as they currently exist

2. Inactive mine that is reclaiME!d as native vegetation
reverts to each native vegetation habitat type in the
same proportion as it currently exists

152

6.1.4.2 Data

Table 6.1.4A: Scenario #1-- Total accrued annualized habitat
units at the end of the project period, with
and without the project

With without Difference % Change

Area 1 56,594 64,828 -8,234 -12.7

Area 2 26,604 31,259 -4,655 -14.9

Total 83,198 96,087 -12,889 -13.4

153

Table 6.1.4B: Scenario #1, Area I-- I@ccrued annualized habitat
units at end of project: period, with and
without the project, by species

Species With Without Difference Change

Black bear 5,975 9,470 -3,485 -36.8

Whitetail deer 8,201 8,586 - 385 - 4.5

Marsh rabbit 5,916 8,375 -2,459 -29.4

Muskrat 3,804 3,110 + 694 +22.3

Bobwhite 8,043 6,905 +1,138 +16.5

Mourning dove 6,776 4,707 +2,069 +44.0

Great horned owl 6,244 5,837 + 407 + 7.0

Pine warbler 2,173 4,313 -2,140 -49.6

Hairy woodpecker 2,333 4,515 -2,182 -48.3

Bobcat 7,129 9,009 -1,880 -20.9

Table 6.1.4C: Scenario #1, Area 2-- Accrued annualized habitat
units at end of project: period, with and
without the project, by species

Species With Without: Difference % Change

Black bear 2,771 4,188 -1,417 -33.8

Whitetail deer 3,730 4,004 - 274 - 6.8

Marsh rabbit 2,283 3,206 - 923 -28.8

Muskrat 1,334 988 + 346 +35.0

Bobwhite 3,767 3,244 + 543 +16.7

Mourning dove 3,423 2,474 + 949 +38.4

Great horned owl 2,932 3,061 - 129 - 4.2

Pine warbler 1,668 3,114 -1,446 -46.4

Hairy woodpecker 1,512 2,837 -1,325 -46.7

Bobcat 3,184 4,143 - 959 -23.1

154

Table 6.1.4D: Scenario #1-- Average Habitat Suitability Index,
4y species, for the beginning and end of the
project period, with and without the project

Species Beginning End of Period
of Period Without Project With Project
Area 1
Black bear 0.48 0.63 0.31

Whitetail deer 0.63 0.52 0.47

Marsh rabbit 0.42 0.56 0.32

Muskrat 0.20 0.20 0.29

Bobwhite 0.60 0.40 0.51

Mourning dove 0.48 0.25 0.48

Great horned owl 0.48 0.34 0.36

Pine warbler 0.16 0.30 0.15

Hairy woodpecker 0.19 0.31 0.13

Bobcat 0.57 0.57 0.37

Area 2
Black bear 0.52 0.61 0.30

Whitetail deer 0.62 0.55 0.48

Marsh rabbit 0.41 0.47 0.25

Muskrat 0.16 0.14 0.25

Bobwhite 0.56 0.43 0.57

Mourning dove 0.45 0.31 0.59

Great horned owl 0.48 0.41 0.38

Pine warbler 0.31 0.45 0.19

Hairy woodpecker 0.30 0.41 0.15

Bobcat 0.58 0.58 0.35

155

Table 6.1.4E: Scenario #2-- Total accrued annualized habitat
units at the end of the project.period, with
and without the project,

With Without Difference % Change

Area 1 103,534 125,601 -22,067 -17.6

Area 2 53,301 64,100 -10,799 -16.8

Area 3 95,196 117,228 -22,032 -18.8

Area 4 42,761 56,302 -13,-41 -24.1

Total 294,791 363,230 -68,439 -18.8

Table 6.1.4F: Scenario #2, Area 1-- Accrued annualized habitat
units at the end of thE? project period, with
and without the project, by species

Species With Without Difference % Change

Black bear 12,031 20,057 -8,026 -40.0

Whitetail deer 14,206 16,311 -2,105 -12.9

Marsh rabbit 11,632 17,304 -5,672 -32.8

Muskrat 6,818 4,709 +2,109 +44.8

Bobwhite 13,313 11,606 +1,707 +14.7
Mourning dove 11,118 6,489 +4,629 +71.3
Great horned owl 10,460 10,747 - 287 - 2.7

Pine warbler 5,554 9,752 -4,198 -43.0
Hairy woodpecker 5,481 10,254 -4,773 -46.5
Bobcat 12,920 18,371 -5,451 -29.7

156

Table 6.1.4G: Scenario #2, Area 2-- Accrued annualized habitat
units at end of project period, with and
without the project, by species

Species With Without Difference % Change

Black bear 6,276 9,948 - 3,672 -36.9

Whitetail deer 7,149 8,114 - 965 -11.9

marsh rabbit 5,449 8,355 - 2,906 -34.8

muskrat 2,832 2,162 + 670 +31.0

Bobwhite 6,775 5,694 + 1,081 +19.0

Mourning dove 5,962 3,391 + 2,571 +75.8

Great horned owl 5,394 5,714 - 320 - 5.6

Pine warbler 3,612 5,774 - 2,162 -37.4

Hairy woodpecker 3,356 5,750 - 2,394 -41.6

Bobcat 6,496 9,198 - 2,702 -29.4

Table 6.1.4H: Scenario #2, Area 3-- Accrued annualized habitat
units at end of project period, with and
without the project, by species

Species With Without Difference % Change

Black bear 12,385 19,482 - 7,097 - 36.4

Whitetail deer 12,640 15,416 - 2,776 - 18.0

marsh rabbit 10,118 14,546 - 4,428 - 30.4

Muskrat 4,600 2,643 + 1,957 + 74.0

Bobwhite 10,347 9,544 + 803 + 8.4

Mourning dove 8,646 4,389 + 4,257 + 97.0

Great horned owl 9,965 10,389 - 424 - 4.1

Pine warbler 7,078 11,352 - 4,274 - 37.6

Hairy woodpecker 7,456 12,148 - 4,692 - 38.6

Bobcat 11,961 17,318 - 5,357 - 30.9

157

Table 6.1.41: Scenario #2, Area 4-- Accrued annualized habitat
units at the end of the project period, with
and without the project, by species

Species With Without Difference % Change

Black bear 5,750 9,018 - 3,268 - 36.2

Whitetail deer 5,379 7,495 - 2,116 - 28.2

Marsh rabbit 5,977 7,361 - 1,384 - 18.8

Muskrat 3,067 1,711 + 1,-356 + 79.3

Bobwhite 3,472 4,883 - 1,411 - 28.9

Mourning dove 2,473 2,597 - 124 - 4.8

Great horned owl 4,580 5,323 - 743 - 14.0

Pine warbler 2,919 4,483 - 1,564 - 34.9

Hairy woodpecker 3,415 5,051 - 1,636 - 32.4

Bobcat 5,728 8,379 - 2,651 - 31.6

158

Table 6.1.4J: Scenario #2-- Average Habitat Suitability Index,
by species, for the beginning and end of the
project period, with and without the project

Species Beginning End of Period
of Period Without Project With Project

Area 1
Black bear 0.60 0.69 0.27

Whitetail deer 0.59 0.53 0.44

Marsh rabbit 0.51 0.59 0.27

Muskrat 0.16 0.16 0.33

Bobwhite 0.48 0.36 0.53

mourni,ng dove 0.32 0.19 0.57

Great horned owl 0.42 0.34 0.34

Pine warbler 0.25 0.34 0.16

Hairy woodpecker 0.28 0.36 0.12

Bobcat 0.61 0.61 0.31

Area 2
Black bear 0.63 0.67 0.27

Whitetail deer 0.56 0.54 0.47

Marsh rabbit 0.53 0.57 0.22

Muskrat 0.15 0.14 0.28

Bobwhite 0.42 0.37 0.59

mourning dove .0.27 0.21 0.64

Great horned owl 0.41 0.37 0.37

Pine warbler 0.36 0.39 0.17

Hairy woodpecker 0.36 0.39 0.12

Bobcat 0.61 0.61 0.31

159

Table 6.1.41 (continued)

Species Beginning End of Period
of Period Without Project With Project

Area 3
Black bear 0.76 0.76 0.27

Whitetail deer 0.59 0.59 13.47

Marsh rabbit 0.59 0.56 0.22

Muskrat 0.13 0.09 0.28

Bobwhite 0.32 0.36 0.59

Mourning dove 0.15 0.15 0.64

Great horned owl 0.46 0.38 0.37

Pine warbler 0.43 0.46 0.17

Hairy woodpecker 0.49 0.48 0.13

Bobcat 0.67 0.67 0.31

Area 4
Black bear 0.71 0.72 0.31

Whitetail deer 0.58 0.56 0.35

Marsh rabbit 0.59 0.58 0.53

Muskrat 0.17 0.12 0.36

Bobwhite 0.32 0.36 0.21

Mourning dove 0.18 0.17 0.20

Great horned owl 0.49 0.37 0.25

Pine warbler 0.34 0.37 0.22

Hairy woodpecker 0.43 0.41 0.20

Bobcat 0.65 0.64 0.30

160

Table 6.1.4K: Scenario #3-- Total accrued annualized habitat
units at the end of the project period, with
and without the project

With Without Difference % Change

Area 1 58,035 64,828 -6,793 -10.5

Area 2 26,878 31,259 -4,381 -14.0

Total 84,913 96,987 -11,174 -11.6

Table 6.1.4L: Scenario #3, Area 1-- Accrued annualized habitat
units at the end of the project period, with
and without the project, by species
Species With Without Difference % Change
Black bear 6,339 9,470 -3,131 -33.1

Whitetail deer 8,267 8,586 - 319 - 3.7

Marsh rabbit 7,017 8,375 -1,358 -16.2

Muskrat 4,911 3,110 +1,801 +57.9

Bobwhite 7,652 6,905 + 747 +10.8

Mourning dove 5,963 4,707 +1,256 +26.7
Great horned owl 6,210 5,837 + 373 + 6.4
Pine warbler 1,916 4,313 -2,397 -55.6
Hairy woodpecker 2,247 4,515 -2,268 -50.2

Bobcat 7,513 9,009 -1,496 -16.6

161

Table 6.1.4M: Scenario #3, Area 2-- Accrued annualized habitat
units at the end of the project period, with
and without the project, by species
Species With Without Difference % Change
Black bear 2,965 4,188 -1,153 -27.6
Whitetail deer 3,621 4,004 - 383 - 9.6
Marsh rabbit 3,026 3,206 - 180 - 5.6
Muskrat 2,028 988 +1,040 +105.3
Bobwhite 3,272 3,244 + 28 + 0.9
Mourning dove 2,646 2,474 + 172 + 7.0
Great horned owl 2,814 3,061 - 247 - 8.1
Pine warbler 1,608 3,114 -1,506 -48.4
Hairy woodpecker 1,526 2,837 -1,311 -46.2
Bobcat 3,373 4,143 - 770 -18.6

162

Table 6.1.4N: Scenario #3-- Average Habitat Suitability Index, by
species, for the beginning and end of the project
period, with and without the project

species Beginning End of Period
of Period Without Project With Project

Area 1
Black bear 0.48 0.63 0.39

Whitetail deer 0.63 0.52 0.49

marsh rabbit 0.42 0.56 0.53

Muskrat 0.20 0.20 0.46

Bobwhite 0.60 0.40 0.43

Mourning dove 0.48 0.25 0.31

Great horned owl 0.48 0.34 0.36

Pine warbler 0.16 0.30 0.10

Hairy woodpecker 0.19 0.31 0.12

Bobcat 0.57 0.57 0.45

Area 2
Black bear 0.52 0.61 0.40

Whitetail deer 0.62 0.55 0.45

Marsh rabbit 0.41 0.47 0.53

Muskrat 0.16 0.14 0.47

Bobwhite 0.56 0.43 0.37

Mourning dove 0.45 0.31 0.27

Great horned owl 0.48 0.41 0.34

Pine warbler 0.31 0.45 0.18

Hairy woodpecker 0.30 0.41 0.17

Bobcat 0.58 0.58 0.44

163

6.1.4.3 Conclusions

6.1.4.3.1 Scenario #1

With the mining projects, total accrued annualized habitat
units, summed over all species, will be 13% less in Area 1, 15%
less in Area 2, and 13% less in the entire project area than
without the projects (Table 6.1.4A). This summation confounds
gains and losses among the indicator species, equates all
species, and assumes comparability and linearity among all
components of the model. A more valuable interpretation may be
gained by examining impacts upon individual species.

Black bear, pine warbler and hairy woodpecker will be most
severely (adversely) affected by the mining projects. Overall
habitat suitability (Table 6.1.4D) will be reduced about 50%.
During the 20-year project period, habitat suitability with the
projects will be 50-60% of no-project conditions (accrued
annualized habitat units, Tables 6.1.4B and C). These species
are associated more with native vegetation (pocosin, swamp and
evergreen forest) than with the water and marsh, agriculture and
mined areas characteristic of during-project and post-project
conditions. The bear, a wilderness animal which cannot survive
in areas intensively modified by man, will have an overall
Habitat Suitability Index (HSI) of 0.2 following the 20-year
project period (Table 6.1.4D) and a habitat quality reduction of
63% (Area 1) and 51% (Area 2) during-project operation (Tables
6.1.4B and C).

With mining, marsh rabbit and bobcat will sustain
moderately negative impacts. Habitat suitability for both will
decrease about 35% in,, Area 1 and over 40% in Area 2 (Table
6.1.4D). The increase in water and marsh (HSI=0.7), suitable
habitat for marsh rabbits, will not offset the increase in
unsuitable agriculture and mining (HSI=<0.2). The bobcat is
associated with native vegetation (HSI=>0.5); habitat quality
will be reduced 21% (Area 1) and 23% (Area 2) (Tables 6.1.4B and
C) during the project period, and post-project habitat quality
will be reduced 35% (Area 1) and 40% (Area 2) from
without-project conditions.

With the projects, whitetail deer will experience a 10%
decrease in HSI in Area 1 and a 13% decrease in Area 2, compared
to no-project conditions (Table 6.1.4D), and a 4-7% decrease
during the projects (Tables 6.1.4B and C).

Muskrat, bobwhite, mourning dove and great horned owl will
all benefit from the projects. The muskrat will gain about 22%
(Area 1) and 35% (Area 2) during-project operation (Table 6.1.4B
and C), but will have an overall suitability of 0.25-0.29 at
project conclusion. The mourning dove will gain 44% (Area 1) and
38% (Area 2) during the projects (Tables 6.1.4B and C), and

164

post-project conditions will be 92% (Area 1) to almost 200%
(Area 2) better than no-project conditions (Table 6.1.4D).
Conditions for great horned owls will improve about 7% in Area 1
and decline 4% in Area 2 during-project operation (Table 6.1.4B
and C), and will be about the same, with or without the
projects, after the 20-year period (Table 6.1.4D).

6.1.4.3.2 Scenario #2

Total accrued annualized habitat units, with the mining
projects will be less than without the projects in each area,
summing over all species (Table 6.1.4E). The decline in total
habitat units will be 18% in Area 1, 17% in Area 2, 19% in Area
3 and 24% in Area 4. Overall, habitat quality (as measured by
the evaluation species cited) will decrease 19% from
without-project conditions.

Black bears will lose 60% or more in habitat suitability in
three of the four areas with the projects compared to no-project
conditions at the end of the period (Table 6.1.41). Loss of
accrued annualized habitat units will range from 36% (Areas 3
and 4) to 40% (Area 1) during the projects (Tables 6.1.4F-I) due
to conversion of land from native vegetation to agricultural
land in Areas 1, 2 and 3 and conversion to residential property
and water in Area 4. Whitetail deer will lose 38% in habitat
suitability in Area 4 with the project compared to no-project
conditions because of the residential land (HSI= 0.02) and
4280-acre water body (HSI=0.23) planned for reclamation. The
conversion to residential property and lake areas in Area 4 will
be accompanied by a substantial loss of habitat units (28%)
during-project operation (Table 6.1.4F). The habitat suitability
for deer in Areas 1, 2 and 3 will decline 20% or less (Table
6.1.4J). Habitat unit losses in Areas 1, 2 and 3 during-project
operation will be less than 20% (Tables 6.1.4G-I).

Land conversion with the projects will severely reduce the
habitat suitability for marsh rabbit, pine warbler, hairy
woodpecker and bobcat in Areas 1, 2 and 3 over the no-project
alternative (Table 6.1.4J). Habitat quality for marsh rabbit
will be reduced because of the loss of low pocosin vegetation
(HSI=0.54-0.66) and conversion to mined land (HSI=0.06) and
agriculture (HSI=0.18)--partially off-set by the increase in
water (HSI=0.7) in Area 4. The rabbit HSI for water was
originally intended for small-area water bodies such as canals,
and for marshy areas. The 4280-acre water body in Area 4 will
not be suitable habitat for marsh rabbits, but was assigned a
HSI of 0.7 in this analysis. Thus the impacts of the mining
project upon this species in Area 4 have been underestimated.
Habitat unit loss during-project operation will be about 30% in
Areas 1, 2, and 3, and 19% in Area 4 (Tables 6.1.4F-I).

165

original habitat conditions are only fair in all areas for
pine warbler and hairy woodpecker (HS'E=0.25-0.43 for warbler and
HSI=0.28-0.49 for woodpecker) (Table 6.1.4J). For both species,
habitat will become marginal under project conditions (HSI
generally less than 0.2) (Table 6.1.4J).

Bobcat habitat suitability will decrease about 30% during
the projects (Tables 6.1.4F-I), and resultant HSIs will be about
50% less than under no-project conditions (Table 6.1.4J).

Muskrat, bobwhite and mourning dove will experience
substantial increases in habitat suitability under project
conditions, with muskrat and mourning dove habitat more than
doubling in quality (Table 6.1.41). These species are associated
with agriculture and/or water, both of which increase in all
areas. Initial habitat suitability for muskrat is poor in all
areas (HSI=<0.2). Although habitat quality will be greatly
improved with the projects (HSI=about 0.3), it will still not be
high enough to consider any of the areas (in total) really
suitable for muskrat (Table 6.1.4J). Canals and water bodies
created by the projects will, however, provide excellent,
localized muskrat habitat.

Habitat quality for great horned owl will be relatively
unaffected by the projects (Tables 6.1.4F-I), except in Area 4
where conversion to residential property (HSI=0.3) and water
(HSI=0.15) will reduce overall quality by about 30% (Table
6.1.41).

6.1.4.3.3 Scenario #3

With the mining projects, total accrued annualized habitat
units, summed over all species, will be 11% less in Area 1 and
14% less in Area 2 than without the projects (Table 6.1.4K).
Overall, habitat quality will decrease about 12% (as measured by
the evaluation species used).
Pine warbler and hairy woodpecker will experience the
greatest loss in habitat suitability with the mining projects
compared to no-project conditions at the end of the period
(Table 6.1.4N). Loss of accrued annualized habitat units will
range from 46% to 56% during the projects (Tables 6.1.4L and M).
Currently, the area is not well suited for either species (pine
warbler HSI=0.16-0.31; hairy woodpecker HSI=0.19-0.30).

Black bear will lose 34-38% in habitat quality, compared to
without-project conditions (Table 6.1.4N), and accrued habitat
units will be 28-33% less than under without-project conditions
(Tables 6.1.4L and M). Bobcats will sustain less, but still
substantial, reduction in habitat quality under project

166

conditions--about 18% in accrued habitat units (Tables 6.1.41,
and M) and 20-30% in post-project conditions (Table 6.1.4N).

Whitetail deer, marsh rabbit and great horned owl will be
only slightly affected by project conditions; with-project HSIs
and accrued habitat units will be within +20% (and usually
within +10%) of without-project values (Table 6.1.4N).

Muskrat, bobwhite and mourning dove will all benefit from
the projects, with gains of more than 200% in the case of
mourning dove (Table 6.1.4N). These species are characteristic
of agricultural and aquatic environments, which expand as a
result of the mining projects.

6.1.4.3.4 Summary

Project impacts can be evaluated in terms of magnitude,
significance, and possible mitigation.

Pine warblers and hairy woodpeckers will sustain the
greatest overall habitat degradation under project conditions
(generally 50-60%). Both species are relatively common, widely
distributed and tolerant of human activity. No population of
either species will be jeopardized and mitigation is probably
unnecessary.

Black bears and bobcats will sustain proportionately less
loss (generally 20-40%). These species are much more narrowly
distributed, and the bear is particularly intolerant of
disturbance and human activity. HSIs used in this analysis were
based upon professional opinion; during- and post-project values
were dependent upon estimates of the effects of mitigation
measures (buffer strips, corridors, habitat type interspersion)
which have not yet been tested. The implications of potential
habitat loss and of errors in the HSIs used are therefore
substantial. If necessary, additional mitigation measures could
be required by modifying existing permits to reduce the acreage
disturbed or to require greater reforestation in the reclamation
plans. Legal authority for permit and reclamation plan
modification is granted by G. S. 74-51 (6th paragraph) and G. S.
74-57. Additional. strength is given to permit and plan
modifications to mitigate loss of wildlife resources by G. S.
74-51, which makes "unduly adverse effects on wildlife" a ground
for denying a permit for any mining operation.
Whitetail deer and the great horned owl will be only
slightly affected by the projects, except in Area 4 of Scenario
#2, where residential development and open water reclamation
will decrease available habitat.

167

The marsh rabbit is widely distributed through the lower
Coastal Plain and will be moderately,, though variably, impacted
by the projects. This species has not been intensively studied
in North Carolina, however, and rE@SUlts reported here may be
subject to considerable error.

Species benefitting from the projects -- muskrat, bobwhite,
and mourning dove are all common and widely distributed.

168

6.1.5 Recreation

6.1.5.1 Approach/Assumptions

1. The literature was analyzed for data on the present
recreational value of the areas included in the scenarios
prior to peat mining activities.

2. The acreage figures of peatland by land use category at
year zero (T=O) for Scenarios #1 and #2 are based on
habitat type/land use data in Appendix 10.1. These data
were used to calculate the actual recreation value at T=O.
Cropland was not given a hunting value since access to
the land was assumed to be restricted. (If this assumption
is not met, then recreational hunting values would not
change; however, game species would change significantly.)
3. The recreational value of pocosins prior to development was
based on Postel (1981).

4. The primary use of pocosin lands for recreation is for
hunting and fishing (Richardson, 1981). Under the moderate
assumptions of a $5.00 per trip hunting value, a 9% benefit
appreciation rate and a 7% interest rate, hunting benefits
yield a present worth of $36 per acre over a twenty-year
period (Postel, 1981). This does not take into account
the downstream benefits related to the role of pocosins in
estuarine water quality maintenance, which may control an
annual $500 million fishing industry. Other nonquantifiable
benefits include critical habitat maintenance, ecosystem
preservation and option value to future generations.

5. The loss in recreational value due to the conversion of
pocosin ecosystems as well as surrounding swamp forest,
cropland and marsh habitat was based on the acreage in a
somewhat natural state at T=O multiplied by $36 per acre,
minus the acreage of landscape converted to peat mining
at time T+1 times $36 per acre. This simplistic approach
does not take into account the opportunity costs of
development and was chosen since a marginal analysis of
these opportunity costs was not possible. The acres that
are calculated to be reclaimed at each calculation period
are added back into the value at $36 per acre. The data
representing an estimate of changes in recreational value
due to peat mining are shown in Table 6.1.6A.

169

6.1.5.2 Data

Table 6.1.5A-- Estimated changes in recreational value (primarily
hunting) based on a value of $36/acre over 213 yrs

Scenario Area Year Total Value Value Lost

1 1 0 $ 452,156 $ -
1 1 10 177,994 274,162
1 1 20 121,174 '330,982

1 2 0 222,486 -
1 2 10 73,513 148,973
1 2 20 40,872 181,614

Total loss for Scenario #1 (all areas) at year 20 512,596

2 1 0 $ 978,486 $ -
2 1 10 393,177 1585,309
2 1 20 98,477 1380,009

2 2 0 500,237 -
. 03,649
2 2 10 196,588 .3
2 2 20 49,238 450,999

2 3 0 952,832 -
2 3 10 353,926 598 , 906
2 3 20 84,065 368,767

2 4 0 462,124 -
2 4 10 168,431 :29 3 , 69 3
2 4 20 77,100 385,024

Total loss for Scenario #2 (all areas) at year 20 $2,584,799

Notes:
$ value of forest and native land assumed to be $36/acre
$ value/acre of pasture, cropland, mining area and open water
all assumed to be 0; thus, value of forest and native land
assumed to equal total value of all acreage in permitted area

6.1.5.3 Conclusions

An estimate of the loss in value over 20 years in terms of
hunting recreational value in Scenario #1 is roughly $512,600
(Table 6.1.5A). This assumes that cropland is not available to
hunters in the future and that a portion of the peat mine is not
yet reclaimed. In Scenario #2 the total loss of recreational
value in Areas 1, 2, 3 and 4 of Scenario #2 due to peat mining
is approximately $2.6 million when projected over the next 20
years (Table 6.1.5A). In both cases, the estimated losses in
recreational value are based on an assumed value of $5.00 per
hunting trip.

170

6.2 Water

6.2.1 Surface Water

6.2.1.1 Amount of Surface Water Runoff

6.2.1.1.1 Approach/Assumptions

6.2.1.1.1.1 Scenario #1

For the analysis of Scenario #1, Area I was considered to
consist of 45 333-acre blocks permitted for methanol production
and 800 acres permitted for horticultural peat production. The
pre-mining conditions were based on habitat type/land use data
in Appendix 10.1. The habitat type data and PMA's 'Peat
Harvesting Sequence' (PMA, 1983d, Fig. 2-10) were used to
determine the number of acres existing in each land use
condition in Table 6.2.1.1A at any one time. Pre-mining
disturbed land was equivalent to habitat type categories
(Appendix 10.1) 'agricultural land' and 'disturbed land
transitional/field ditched'. This category thus includes all
land ditched and recently cleared for agriculture including
burned and rejuvenated areas and pasture land. These areas were
all modeled as pasture sites with field ditches spaced 330 feet
apart. Pre-mining shrub encompassed high and low pocosin areas.
These areas were modeled assuming a standard ditched area as for
pasture with increased rooting depths and surface storage. For
the first ten years an extra 80 acres per year (1/4 block) were
considered cleared for mining in areas producing horticultural
peat (Area 1).

A block was considered to be in pre-mined condition until
the second year of bog preparation. (Bog preparation involves
digging an extra drainage ditch between the existing ditches,
breaking down and grinding up the vegetation and land forming
the block to encourage rapid surface drainage.) From the
beginning of the second year of bog preparation the block was
considered to be in the mined condition. increased runoff may be
expected with the removal of vegetation but not to the extent
modeled for the actively mined phase. The one year delay in
considering a block in the mined condition was an attempt to
account for this progressive change in expected runoff.

Reclaimed land not used for the lake in Area 1 was assumed
to be in 80% agriculture (row crop rotation with poor subsurface
drainage), 10% forestry and 10% native vegetation (see section
5.2.2.10). Reclaimed native vegetation was considered the same
as forestry in the analysis. If reclamation was scheduled to
begin before the end of the first quarter of a particular year,
a block was considered reclaimed for that entire year. If
reclamation was not scheduled to begin until after the first
quarter, the block was considered in the mined condition until
the following year. All land being mined for horticultural peat
was assumed recl-imed to agriculture and forestry in year 11.

171

At the completion of mining, the soil surface will be
fairly well compacted from the continuous passage of heavy
harvesting equipment. High surface runoff may be expected prior
to plowing and planting. Although it will take several seasons
of plant residue incorporation and fertilization to produce the
soil type assumed for after mining agriculture and forestry, the
most significant effect of reclamation will be the alteration of
evapotranspiration. These effects will begin immediately after
planting of the first crop. once a crop is planted,
transpiration will increase significantly over the during mining
condition, lowering the water table and reducing runoff.
Assuming quick reclamation is thus considered reasonable.

Average total annual flows from 20 years of simulation were
generated for each of the land surface conditions (Table
6.2.1.1A) using the models described in Gregory et al. (1984).
The slight differences from values reported in section 5.2.2.4
are due to improved records of rainfall data for the
simulations. Flows from pre-mining shrub areas are higher than
flows from post-mining agriculture because of the difference in
soil type. Although the shrub has a deeper root depth than the
row crops, in the post-mining mineral soil more water is
available to the plant for evapotranspiration, resulting in
deeper water tables and, thereforE!, less runoff. Flows were
weighted by their various areas throughout the study period to
determine an expected average annual. flow per unit area for all
20 years (Table 6.2.1.1A). The assumed acreage by land use
category for each scenario and area for the 20 year study period
may be found in Appendix 10.5. In year 10 the land used for the
large temporary lake was assumed to revert back to pasture
before being mined at a later date. The 20 year maximum and
minimum flows were also considered throughout the study period.
The resulting expected average, maximum and minimum annual flows
per unit area for Scenario #1, Area 1, for the 20 year study
period are plotted in Figure 6.2.1.1A. The plant discharge of
870,000 gallons per day (0.7 inches per year over the entire
Area 1) was added to the flow for all years after year 0. (The
horizontal lines in Figures 6.2.1.IA-F represent the no project
condition (i.e., the average annual flow at year 0).)

For Area 2 of Scenario #1, precise mining strategy was not
available. It was assumed for this analysis that 300 acres were
prepared for mining each year up to a maximum of 1,500 acres. An
extra 300 acres were included in the active mining condition. for
each year to simulate areas in bog preparation and areas mined
but not yet reclaimed. The land use areas were taken from data
on acreage by habitat type in Appendix 10.1 and each of the
non-forested areas was assumed to be depleted at a rate
proportional to the original habitat type acreage. The assumed
acreages of each land use thoughout the 20 year study period are
given in Appendix 10.5. As with Area 1, forested areas were

172

assumed to be replenished at a rate equal to 20 percent of the
reclaimed area. Differences in hydrology between forestry on the
reclaimed areas and on the original peat soil were found to be
small (less than 2%) and consequently the same annual flow
totals were used for both. The predicted average, maximum and
minimum total flows for Scenario #1, Area 2, for the 20 year
study period are shown in Figure 6.2.1.1B.

6.2.1.1.1.2 Scenario #2

For Scenario #2, all areas, the initial land use types were
taken from the habitat type data in Appendix 10.1. Each was
depleted at a rate proportional to the initial habitat type
acreage. Different mining rates were used from those reported in
section 5.2.3.2.4. In order for the required acreage to be mined
by year 10 and 20 as given in section 5.2.3.2.1 and assuming
that it takes 5 years to mine out a block, the acreage mined at
year ten must be in the active mining state by year 5.
Similarly, in order to finish mining an area by year 20, all
acreage must be reclaimed or in active mining state by year 15.
Thus the following average annual rates of land disturbance were
used in this analysis:

I - 5 6 - 10 11 - 15 16 - 20
Area 1 1500 1800 2700 0
Area 2 750 900 1350 0
Area 3 1100 1600 2500 0
Area 4 680 770 1150 0

Using the above rates and the given existing land use
types, the acreages for each year of operation were calculated
and are given in Appendix 10.5. Residential areas in Area 4 were
modeled as an active peat mine to simulate the high surface
runoff expected for a residential area. Accurate urban modeling
is not possible at this stage because of lack of information
about the nature of the residential areas and because the model
used in this analysis is not designed to handle urban areas. The
resulting predicted average, maximum and minimum annual flows
per unit area for Scenario #2, Areas 1, 2, 3 and 4, for the 20
year study period are shown in Figures 6.2.1.lC-F, respectively.

173

6.2.1.1.2 Data

Table 6.2.1.lA: Annual flow totals per unit area generated from
20 years of simulation. (Average annual
rainfall for the 20 years is 48.4 inches.)

Average 20 Year 20 Year
Land Use Annual Flow Maximum minimum
in/year in/year in/year

Lake 9.8 17.6 -4.6

Pre-mining
Disturbed 18.7 29.5 9.1

Pre-mining Shrub 14.5 27.4 4.3

Active Mine 24.1 32.2 12.8

Agriculture 14.3 25.8 3.4

Forestry 12.6 24.3 1.5

174

SCENARIO *1, AREA *1

20 YEAR AVGE 20 YEAR MAX

20 YEAR MIN ---------- NO PROJECT

35-

cn
W 30-

z 2S-

cn
in
20-:
----------

16-

0 2 4 6 8 10 12 14 16 18 20

YEAR OF OPERATION

Figure 6.2.1.1A: Scenario #1, Area 1-- Total annual flow (inches per year)

FOR SCENARIO *1, AREA #2

20 YEAR AVGE 20 YEAR MAX
40-
20 YEAR MIN NO PROJECT

cn
,w -
30
0

z 2s-

cn
cn
0 20-

------------------------------------

0 2 4 5 8 10 12 14 20

YEAR OF OPERATION

F i (yi i rp 4, 9 1 1 R qppnqri n iil Ar@n 9-- Tnt-il n n,iql fl r-wv.T ( in @li @ c .
Year)

SCENARIO *2, AREA *1

20 YEAR AVGE - 20 YEAR MAX
40-
20 YEAR MIN ----------- NO PROJECT

3s-

cn
LLJ

-----------------

z 2s-:
(n
cn -
0 20-

W -x ----------------------------------------------

0 2 4 6 8 10 12 14 16 18 20

YEAR OF OPERATION

Figure 6.2.1.1C: Scenario #2, Area 1-- Total annual flow (inches per year)

SCENARIO *2, AREA #2

20 YEAR AVGE 20 YEAR MAX
40
20 YEAR MIN ------------ NO PROJECT

cn
LLJ
m 30
U
z ------------------------------------

z 2S-

V)
V)
00 20-

-----------------------------------------------

0 2 4 6 8 10 12 14 16 18 21a

YEAR OF OPERATION

Figure 6.2.1.1D: Scenario #2, Area 2-- Total annual flow (inches per year)

SCENARIO 02, AREA 03

20 YEAR AVGE 20 YEAR MAX
40-
20 YEAR MIN ----------- NO PROJECT

3S-

Cn
W
30-
0 -

(n
0 20-
-j

is - -------------------------------------------------------------------------

10-

0 2 4 6 8 10 12 14 18 18 20
----------
---------------------------------------

YEAR OF OPERATION

Figure 6.2.1.1E: Scenario #2, Area 3-- Total annual flow (inches per year)

SCENARIO *2, AREA #4

20 YEAR AVGE 20 YEAR MAX
40-
20 YEAR MIN NO PROJECT

Cn
Ld
30-
U

25-

00
0 20-

- ---------------------------------------------------------------------------

0 2 4 8 8 10 12 14 18 20

YEAR OF OPERATION

Figure 6.2.1.1F: Scenario #2, Area 4-- Total annual flow (inches per year)

80-

70@-

cn
LL.
0
40-

30-
cr

0 20-
LL.
10-

0 2 4 6 8 18

TIME EOUALED OR EXCEEDED

LEGEND: AGRIC. MINING
PASTURE

F i,(-,ure 6,2. 1.. 1 G: Compar!,,on of peak f lows f rom a 320-acre block
under three different land uses

181

6.2.1.1.3 Conclusions

6.2.1.1.3.1 Scenario #1

For Scenario #1, Area 1, the average annual total flow will
not vary by more than about 5% from the pre-mined condition over
the first 20 years of operation (see Figure 6.2.1.1A). The
reasons for this small change include: 1) less than 25% of the
area will be in the mined condition at one time, 2) reduced
flows from the reclaimed area will off-set the increased flows
from the actively mined areas and 3) the effect of extra
evaporation from the lakes.

The slight steady decline in expected total annual water
loss from Area 1 will continue to the end of mining
(approximately year 35). At this point, the average annual flow
should stabilize at approximately 14 inches per year (21% less
than the pre-mining condition).

The abrupt increase in expected flow in years 9 and 10
corresponds to the abandonment of the large (8 blocks, 2560
acres) temporary lake and the sole use of the smaller (1450
acres) permanent lake. This transition need not be as abrupt as
depicted; maintaining the larger lake into year 13 would clearly
help reduce total annual flows.

In Area 2 of Scenario #1, the initial increase in total@
annual flows will be greater than for Area 1 because no lake is
proposed (see Figure 6.2.1.1B). Once the maximum disturbed area
has been reached, total flows will level off as the area of
reclaimed land slowly increases. Again, the average flow will
drop below pre-mining levels once all the mined areas have been
reclaimed.

In both areas, the major factor controlling the occurrence
of floods will be the capacity of the pumps removing water from
the canal system to the lakes (in Area 1) and the Intracoastal
Waterway (in Area 2). ESE (1983) predicted (using the SWMM III
model) only two breaches of the 1450-acre lake in Area I over 20
years of historical climate data from 1960 to 1979. However, if
water cannot be pumped into the deep storage available in the
lake at a high enough rate during high rainfall events, the
canals themselves may be breached, causing flooding. Because of
the low lying aspect of the mined land in relation to the
surrounding unmined areas, flooding should remain localized for
most events. The lowered elevations due to mining will increase
the capacity to store water on the surface, therefore, the
occurrence of downstream flooding should be reduced from the
before mining condition for all scenarios and areas with the
following exception. In Area 1, the volume of flow in Canal B
will slowly increase throughout the life of the peat mine until
all the flow from the 15,000-acre area will be routed through
the lake and discharged into Canal B. In year 35, this will

182

amount to about 14 inches per year, or an average annual flow
rate of 25 cubic feet per second (as compared to an average
annual flow rate of about 31 cubic feet per second from the
total area at present). Despite the overall drop in total flow,
the flows in Canal B during and after rainfall events will be
increased. The increased flow in Canal B will increase the risk
of downstream flooding as the storage capacity of the canal. is
reduced. Canal B will have to be considerably deepened and
maintained free from weeds and sediment to ensure rapid removal
of water and lessen the risk of flooding.

There are two possible organizational mechanisms for
performing the necessary deepening and maintenance of Canal B.
Responsibility for maintenance of the canal could be placed with
a local drainage district. Drainage districts in North Carolina
are usually directed by part time volunteers and have to depend
on sources of funds that are not always reliable. There is no
existing drainage district covering Canal B, so one would have
to be created.

The second option would be to place continuing
responsibility for canal maintenance with a state agency. The
work could be funded either out of general state revenues or out
of the proposed severance tax revenues discussed in section
4.3.3.3. The responsibile agency would have to obtain permission
from private landowners whose property is crossed by the canal
to enter their land to perform the maintenance.

There does not appear to be sufficient authority in the
Mining Act to require canal deepening and maintenance as part of
the reclamation plan.

6.2.1.1.3.2 Scenario #2

For all areas in Scenario #2 the annual flow will be less than
30% above the pre-mining flow for all 20 years of operation.
with the exception of Area 1, the flows will increase with
increased acreage in active mining, then hold relatively
constant until the size of the mining area starts to decline and
with it the flows. in all areas the flow in year 20 will be less
than or equal to the flow in year 0 as a result of higher
evapotranspiration and lower flows land reclaimed to agriculture
and forestry. Area I demonstrates the advantages of using a lake
for water management: the annual flows will remain closer to
the pre-mining situation. The jump in flows in year 8 in Area 1
is due to abandoning a large evaporation area for a smaller
permanent lake. Maintaining the larger temporary evaporation
area until year 15 will keep annual flows close to the
pre-mining levels. The second main advantage of a lake system is
the controlled release of flow. Storm peaks will be
substantially reduced, provided lake or canal over-topping does
not occur. In Area 4 the residential areas, with their high

183

surface runoff, will counterbalance the flow-reducing effect of
the lake and the annual flows will behave similarly to those in
Areas 2 and 3.

Figure 6.2.1.lG illustrates the differences in peak flows that
might be expected from a 320-acre block under three different
land use conditions. This flow duration curve is truncated at
10% to focus on the high flows. For flows equalled or exceeded
more than 10% of the time all three curves are similar. The
post-mining agriculture and pre-mining pasturo are also simil.:.ir
for flows greater than 5 cubic feet per second. The actively
mined site, however, exhibits a definite increase in frequency
of high flows. For example, a flow of 10 cubic feet per second
will be equalled or exceeded about 1.2% of the time for pasture
or agriculture, but will be equalled or exceeded about 2.25% of
the time for actively mined sites.

6.2.1.1.3.3 Scenario #3

For Scenario #3 the flows up to and including year 10 will
be the same as for Scenario #1. After year 10 it is assumed that
all pumping ceases, that canal dams are broken and all canal and
dike maintenance ceases, resulting in the creation (by year 20)
of a swamp/lake area covering all mined and reclaimed areas (see
sections 5.2.4.5 and 5.2.4.10). The volume and distribution of
the runoff from these areas will be dependent on the changing
nature of the outlets, how much water storage is available on
the surface of the mined areas and the type and density of
returning vegetation. Provided that the water levels remain high
enough to satisfy potential evapotranspiration at all times,
then the water available for runoff will be approximately equal
to rainfall minus potential evapotranspiration, or an average of
about 10 inches per year.

184

6.2.1.2 Nutrient Yields and Surface Water Eutrophication

6.2.1.2.1 Approach/Assumptions

A preliminary assessment was made of the environmental
consequences of peat harvesting and subsequent conversion of
some of the peat to methanol, specifically the effects upon
nutrients in runoff and adverse changes in water quality. The
approach to the problem and the assumptions made were:

1. Literature data on nutrient concentrations and yields
from various land uses in this area (natural vegetation,
cropland, pasture land, and peatland cleared for mining)
were assembled.

2. Land use data used are located in Appendix 10.6
(Table 10.6A).

3. It was assumed that: 1) planted forests, buffers and
natural revegetation have the same yields of nutrients
as natural vegetation, 2) the whole area was ditched
but in natural vegetation at year 0 and 3) open water
is a source for nutrients in proportion to its area
and the nutrient content of rainwater and a sink for
about half of its loading of total nitrogen (TN)
and total phosphorus (TP). Removal of nutrients from
water passing through wetlands or buffer zones was
not assessed for lack of data on hydrology.

4. The yields (lb/acre.yr) were multiplied by the areas
(acres) of each land useage (see Appendix 10.6) and
summed to calculate the total nutrient yield for each
scenario and each area at years 0, 10 and 20, except
Scenario #3 (years 0 and 10 only).

5. The total nutrient yields which drain into lagoons at
years 0 and 20 were summed and divided by the area of
each lagoon or lake to obtain the areal loading rate
(lb/acre.yr). These loading rates were compared to
rates reported to have resulted in eutrophic conditions.

6. The total nutrient loadings of estuaries contributed by
runoff from areas subjected to peat mining and subsequent
agricultural development were examined. It was assumed
that runoff and other waters having passed through lakes
or lagoons had half of the total nitrogen (TN) and total
phosphorus (TP) removed. Where runoff was to the IWW, it
was assumed that half of the load went to the Pungo River
and half to the Alligator River. Area 1 loading rates
attributable to the peat mining and associated operations
(including agricultural development) were obtained by
dividing by the area of each estuary. (Area was determined

185

by planimetry.) These loadings WE!re then compared to the
anticipated loading from the rest of the watershed and to
those which have created eutrophic conditions in similar
estuaries.

6. 2. 1. 2. 2 Data

Table 6.2.1.2A: Concentrations (mg/1) of nutrients in runoff
water from various land uses

Land Use Nutrient

NH4 NO3 Kjeld-N Total Ortho-P Total
N P

Natural vegetation,
planted forests,re-
generated vegeta-
tion (a,b) 0.15 0.06 1.11) 1.25* 0.02 0.06*

Cleared peatland
before, during,
after mining (b) 0.35 0.13 1.85 1.98* 0.05 0.17*

Drained cropland 0.91 1.00 2.92 3.73* - 0.14*
(a)

Drained pasture-
land (c) 0.37 0.21 1.67 1.88* 2.48*

Note:
Abbreviations may be found in Appendix 10.10
* Hypereutrophic (Wetzel, 1975)
Sources:
(a) Skaggs et al., 1980, mineral soil
(b) Gregory et al., 1984
(c) Kuenzler et al., 1977

186

Table 6.2.1.2.B: Areal yields (lb/acre.yr) of nutrients from
watersheds with various land uses

Land Use Nutrient
NH 4 NO 3 Kjeld-N Total Ortho-P Total
N P

Natural vegetation
(as defined in 0.7 0.2 5.2 5.4 0.06 0.26
Table 6.2.1.2A)

Cleared for
mining 1.9 0.7 10.0 10.8 0.27 0.93

Drained cropland 3.3 3.6 10.0 13.5 - 0.50

Drained pasture 1.2 0.6 5.4 6.1 - 8.5

Open water 2.3 2.6 5.3 8.0 0.46 0.59

Residential - - - 5.3 - 1.1

Notes:
Assumed runoff values:
1. Natural vegetation: 14.6 in/yr
(Mean of shrub (16.7 in/yr) and forest vegetation
(12.6 in/yr) runoff values from Table A,
section 5.2.1.1, Task 2, first draft (10/14/84))
2. Cleared for mining: 24.1 in/yr
(Based on active mine runoff value, Table A,
section 5.2.1.1, Task 2 first draft)
3. Drained cropland: 14.8 in/yr
(Based on page 17, Task 1 final draft (9/83): 6.8 inches
subsurface drainage + 8.0 inches surface runoff)
4. Drained pasture: 19.2 in/yr
(Based on page 17, Task 1 final draft; 11.2 inches
subsurface drainage + 8.0 inches surface runoff)
5. open water: rainwater concentrations (from Kuenzler
et al., 1977) x annual precipitation (48.4 in/yr,
from page 34, Task 2 final draft)
6. Residential: based on Reckhow et al., 1980
Concentrations from Table 6.2.1.2A
Abbreviations may be found in Appendix 10.10

187

Table 6.2.1.2C: Total annual yields of nutrients from peatlands
under the alternative scenarios

.Scenario Area Year Annual Yield (Tons/Yr)
NH 4-N NO 3-N Total N Total P

1 1 0 4.6 1.4 36 1.7
10 7.9 > 3.8 >46 >2.9
20 13.1 >10.5 >62 >3.3

1 2 0 2.1 0.6 16 0.7
10 4.1 2.6 23 1.7
20 6.7 6.0 31 1.8

2 1 0 8.6 2.5 67 3.2
10 13.8 > 7.9 > 79 > 5.2
20 32.8 >29.0 >135 >10.8

2 2 0 4.3 1.3 34 1.6
10 7.2 4.6 43 2.3
20 16.3 15.6 72 4.1

2 3 0 7.4 2.2 58 2.7
10 12.0 > 6.7 > 72 > 4.6
20 29.2 >25.9 >123 > 9.3

2 4 0 3.7 1.1 29 1.4
10 5.4 3.3 33 2.1
20 5.8 4.3 34 3.8

Notes:
Abbreviations may be found in Appendix 10.10
Scenario #3 same as Scenario #1 for Areas I and 2, years 0
and 10.
Total annual yields for scenarios cannot be directly compared
because total acreages for areas and scenarios are different

188

Table 6.2.1.2D: Nutrient loadings to lakes and lagoons

Scenario Area Year Water Water Nutrient Load
Body Area (lb/acre.yr)
(acres) TN TP

1,3 1 10 Temp Lake 1,455 36* 1.7*

1 1 20 Perm Lake 1,455 80* 4.4*

2 1 10 Lagoons 2,907 22* 2.2*

20 Lagoons 2,907 103* 8.6*

2 4 10 Lagoons 1,954 12.6 1.2

20 Lagoons 2,895 21* 2.8*

Procedure:
Divide annual TN or TP loading to lagoons (= total yield -
yield from forest) by lagoon or lake area.
Notes:
Abbreviations may be found in Appendix 10.10
Exceed Vollenweider's (1968) criteria of "dangerous" loading:
18 lb TN/acre.yr or 1.2 lb TP/acre.yr

189

Table 6.2.1.2E: Nutrient loadings to estuaries. Approximate
background loading if entire watershed WE!re
in natural vegetation and predicted loadings
at years 0, 10 and 20, with assumption of'
50% TN and TP removal by lagoons and canals.

Scenario Area Year Water Water Nutrient Loading
Body Area (lb/acre.yr)
(acres) Background Loading From
From Natural Project Area
Watershed Alone
TN TP TN TP

1 1+2 0 Pungo R. 12,000 19 :94 4.0 .20

10 Pungo R. 4.2 .26

20 Pungo R. 4.8 .26

1 2 0 Alligator R. 11,900 81 4.1 .74 .04

10 Alligator R. 1.07 .08

20 Alligator R. 1.47 .08

2 1+2 0 Pungo R. 12,000 19 .94 7.7 .37

10 Pungo R. 8.1. .34

20 Pungo R. 10.0 .70

2 2+3+4 0 Alligator R. 11,900 81 4.1 9.7 .46

10 Alligator R. 11.2 .66

20 Alligator R. 16.,8 1.79

Note:
Abbreviations may be found in Appendix 10.10

190

6.2.1.2.3 Conclusions

Nutrient concentrations vary considerably in runoff from
land in different uses (Table 6.2.1.2A). Compared to natural
vegetation, planted forests and revegetated areas, disturbance
by clearing for mining or for agriculture considerably increases
nutrient concentrations in runoff. For example, disturbance
considerably increases nutrient concentrations as follows:
1. NH 4 increased 1.7-6.1-fold by disturbance.
2. NO increased 2.2-fold by mining, 2.5-fold by pastures,
anA 17-fold by crops.

3. Total N (TN) increased 1.6-fold by mining, 1.5-fold by
pastures, and 3.0-fold by crops.

4. Total P (TP) increased 3.0-fold by mining, 44-fold by
pastures, and 2.3-fold by crops.

Furthermore, nutrient concentrations in all of these waters
are relatively high. The TP and TN levels in waters draining
from naturally vegetated areas (Table 6.2.1.2A) would, if
present in a lake, cause them to be classified as hypereutrophic
(Wetzel, 1975) (see Appendix 10.6); TP levels in waters from
disturbed tracts are high enough to classify them as eutrophic
to hypereutrophic even by the less rigorous water quality
criteria for North Carolina waters suggested by Weiss and
Kuenzler (1976).

The areal nutrient yields (lb/acre.year) from land in
different uses is a function of both the nutrient content of the
runoff and the amount of runoff (Table 6.2.1.2B). Lowest yields
generally came from areas in natural vegetation and highest
yields from areas used for mining or agriculture. The increased
yields of N from North Carolina peatlands under various changes
in land use are similar to the increases seen in other
watersheds used for these purposes (see figures from Reckhow, et
al., 1980 in Appendix 10.6). There is large variability in
export coefficients for the same land use (Appendix 10.6)
because measurements include tracts with different soils,
different slopes, different nutrient inputs (fertilizer, manure,
septic tank drainage) and different amounts of runoff. Data
gathered by Skaggs et al. (1980) and Gregory et al. (1984)
showed areal yield of P from non-organic cropland (0.55
kg/ha.yr) below the lower quartile of data gathered by Reckhow
et al. (1980) (Appendix 10.6) whereas yield from organic soil
(7.6 kg/ha.yr) was above Reckhow's upper quartile. The lower
yield estimate (0.55 kg/ha.yr) was used in calculations for this
report under the assumption that crops will be grown only on a

191

highly mineral soil remaining after mining has removed the peat.
The much higher yield of P from pasture on North Carolina peat
soils than were reported by Reckhow et al. (1980) are consistent
with the usually poor retention of P by peat. Nitrogen yields
from North Carolina cropland and pastures were closer to
Reckhow's medians (Appendix 10.6), although N yields from the
state's forest lands were near the top of his range.

Total annual yields (Table 6.2.1.2C) will increase in each
scenario and area from year-O to year 20. Comparison of' yields
between scenarios, however, must take into account the larger
total area considered in Scenario #2 than in Scenarios #1 and
#3. Total annual yields of NO 3 increase by the largest
percentage (always >4-fold). Increases in TN from disturbed
lands result mostly from increases in ammonium and nitrate
rather than from organic N; this is important because ammonium
and nitrate are readily available for algal growth. The yield of
TP also increases substantially, from 2- to 3.4-fold, depending
on the.area. This analysis does not include loading of P leached
from solid wastes of the methanol plant(s). Conversion of
525,000 tons of peat per year at 0.04% P would result in 210
tons of P in ash, slag and other forms, at least 20 times more
than the annual yields of any one area in any scenario (Table
6.2.1.2C). Therefore, if substantial amounts of phosphorus are
leached within the watershed from disposal in landfills or on
agricultral lands as a soil conditioner and thereby enter
surface waters, P-loading to lagoons will greatly increase over
the loadings calculated here.

Predicted nutrient loadings to lakes and lagoons (Table
6.2.1.2D) exceed Vollenweider's criteria of 18 lb N/acre.yr and
1.2 lb P/acre.yr at both years 0 and 20 in virtually all
scenarios. The criteria of Vollenweider are not strictly
applicable to North Carolina's surface waters, especially the
relatively dystrophic waters of the Outer Coastal Plain, but the
fact that calculated loadings are several to many times
Vollenweider's criteria suggests that severe problems are
likely. Eutrophic waters with dense algal growths may be
expected, but precise estimation cannot be made without detailed
information on algal densities which result from various
nutrient loadings in similar lagoons in this region of North
Carolina.

The Pungo and Alligator Rivers have nearly the same surface
areas (Table 6.2.1.2E), but the background nutrient loading
rates to the Alligator River are about four times higher because
its watershed is that much larger. Under natural conditions
these loads are probably well distributed spatially and the poor
light transmission by the dark and turbid waters prevents high
algal productivities. The Alligator River did not show abundant
phytoplankton ten years ago (Bowden and Hobbie, 1977). Recent
measurements of nutrient concentrations (PMA, 1982c) show that

192

the Pungo River is now rich in nutrients. Estuaries act as
nutrient traps, especially for P, often being substantially
richer in total P than any of their source waters. This is
clearly seen in the high P concentrations and algal abundances
during summer in the middle reaches of the Pamlico River
(Kuenzler et al., 1979), the source of salt water for the Pungo
River. Background P loadings of 0.94 and 4.1 lb/acre.yr for the
Pungo and Alligator Rivers, respectively, are at or above the
Vollenweider criterion, but they are at least an order of
magnitude less than present loadings of the Pamlico and Chowan
Rivers because these latter rivers have considerably larger
watersheds. Both Weiss and Kuenzler (1976) and Craig et al.
(1977) suggest that Coastal Plain systems of the Southeast may
function without noxious algal blooms even with P loadings
several fold higher than the Vollenweider criteria. This
suggestion is borne out by conditions in the Pamlico River;
productivity of the phytoplankton is high but noxious algal
blooms have not occurred in the brackish portions. Dispersion of
P-rich water from downstream and regeneration of P from the
sediments or the estuarine fauna constitute additional loadings
not included in this analysis.

The emphasis here has been on phosphorus, in large part
because this element is more often limiting in lakes. The data
in Table 6.2.1.2E show TN:TP ratios usually about 20:1 by
weight; such ratios are close to the proper ratio for algae.
Furthermore, any N loads resulting from the mining and
subsequent land development will be in addition to loads which
are at or far above the Vollenweider criterion of 18 lb
N/acre.yr.

Because of their large areas relative to the developed
areas in the scenarios, activities associated with and following
mining will not deliver to the Pungo and Alligator Rivers
nutrient loads which are large compared to the "background"
loads (Table 6.2.1.2E). As stated above, leaching of nutrients
from ash, slag or other solid wastes from a potential methanol
plant has not been evaluated and could increase loadings several
fold over the values shown for the mining projects alone. The
areas proposed for mining, however, are only a portion of each
estuary's watershed, 40% and 12% for the Pungo and Alligator
Rivers, respectively. Additional extensive land development, for
agriculture or other purposes, will impose additional nutrient
loads on the estuaries, especially if lagoons or wetland buffer
strips are not used to strip nutrients from land runoff.

It appears that the Alligator River is more at risk because
of its greater natural load and the anticipated greater load due
to development for any particular scenario. If half of the
Alligator River watershed undergoes development which yields P
at the average rate of the mined areas, the anticipated load
would reach about 7 lb P/acre.yr. The work of Jaworski (1981)

193

suggests that in estuaries with N:P ratios of 7.2:1 (by weight)
excessive eutrophication may result. if P loadings exceed 9
lb/acre.yr. Thus the whole Alligator River may be at risk with
less than complete development of the watershed; periodic
nutrient pulses to the fresher, poorly mixed headwater areas
could result in eutrophic conditions with still less
development. The fresher waters are considered to be at more
risk because certain blue-green algae can form surface blooms in
these areas in summer.

In view of 1) present water quality of the Pungo and
Alligator Rivers; 2) their background loadings from the
watershed and by dispersion upstream; 3) the additional loading
from existing agriculture and other land development not
included in this analysis; and 4) the intensive agricultural
development now being planned on the eastern shore of the
Alligator River, additional loadings such as have been
calculated from these scenarios are a threat to future water
quality. Since mixing is not uniform, excessive loadings of P
(and maybe N) to the upper portions of these estuaries will
almost certainly result and eutrophic conditions may be
expected. However, there are no accepted criteria specifically
for estuarine waters of North Carolina or the Southeast and
"dangerous" loadings may not be the same as suggested by
Jaworski for other estuaries.

Lee and Jones (1979) extended the Vollenweider P-loading
relationship to estuarine waters and found that data from the
Potomac Estuary fell into the eutrophic sector of the diagram,
as expected. The principle behind this relationship is the same
for estuaries as for freshwater lakes where it was developed,
but larger amounts of P may be assimilated in estuaries without
resulting management problems. Although there are considerable
uncertainties in the data and the assumptions of this analysis,
recent appearance of severe algal blooms in the slightly
brackish portions of the Chowan River and the Neuse River
suggests that the upper reaches of other North Carolina
estuaries are in danger if nutrient loadings are not carefully
controlled.

6.2.1.2.3.1 Summary

Examination of the data on nutrient yields from North
Carolina peatlands under various kinds of land use suggest that
mining of the peat, production of methanol and placing the land
in agricultural production may have an adverse impact on water
quality. The natural vegetation yields less N and P per unit
area than other land uses, usually by a large factor; therefore,
conversion to other uses results in loss of nutrients to
downstream aquatic systems. The lagoons and lakes into which
runoff and plant effluents may run or be pumped probably will

194

become unacceptably eutrophic. Unless these lagoons and buffer
wetland systems efficiently remove nutrients from the water as
it passes through, there will also be substantial nutrient
loading of the Pungo River and the Alligator River and
consequent eutrophication.

This assessment cannot be made more accurately with the
present data base and time resources, but the indications are
that serious water quality degradation may result from the
changes in land use and from associated industrial development
in this region.'

6.2.1.2.3.2 Regulatory Implications and options for Controlling
Nutrient Loading

To the extent that these nutrients are entering "waters of
the United States" from canals and ditches, i.e., point sources,
they can be controlled through the NPDES permit. Any nutrients
entering waters from general runoff, i.e., non-point sources,
are not subject to any control mechanism; however, the state 208
plan urges that best management practices be used to control
this type of runoff.

Another possibility is for the Environmental Management
Commission to classify the affected waters as nutrient sensitive
under G.S. 143-214.1. once waters have been so classified,
however, the enforcement mechanism by which standards are
imposed to meet the classification is uncertain. In some cases,
the state is able to use a special order under G.S. 143-215.2,
but agricultural and forestry activities are expressly exempted
from the reach of special orders. Another enforcement approach
is to attempt to equate the nutrient sensitive classification
with water quality limited waters under 33 U.S.C. section 1312,
thereby authorizing the imposition of more stringent effluent
limitations through the NPDES process than would be imposed
under the 33 U.S.C. section 1311 effluent standards. This still
does not deal with the problem of non-point sources, however.

A third possible legal source for controlling nutrients is
the mining permit itself. Among the grounds for denying a permit
under G.S. 74-51 are that the operation will have unduly adverse
effects on freshwater, estuarine or marine fisheries, or that
the operation will violate water quality standards promulgated
by NRCD. If the excessive nutrient levels would trigger either
of these provisions, the permit conditions should reflect
controls to reduce the nutrients to acceptable levels. The use
of the mining permit to control nutrients has the advantage of
imposing enforceable controls on non-point sources.

195

6.2.1.3 Trace Element, Pesticide and Coliform Bacteria Yields

6.2.1.3.1 Approach/Assumptions

The approach followed that employed in section 6.2.1.2 Ten
elements were selected for study based on occurrence in peat and
environmental concern (dictated largely by relative toxicity):

Arsenic (As) Mercury (Hg)
Cadmium (Cd) Manganese (Mn)
Chromium (Cr) Nickel (Ni)
Copper (Cu) Selenium (Se)
Lead (Pb) Zinc (Zn)

A review of the available literature indicated the
following:

1. For As, Cd, Cr, Ni and Se only "less than detectable"
data are available.

2. No data are available for the ten elements (excluding
largely "less than detectable" data for Hg) for the
land use category "actively mined".

3. Data suitable for predicting changes due to land use
changes (i.e., from undeveloped peatlands to croplands
or pasture lands) are available only for Cu, Mn and Zn
(Skaggs et al. 1980).

Therefore, yields for Cu, Mn and Zn were calculated
following the assumptions and procedures used in section
6.2.1.2. Since no data pertaining to yields associated with
either active mining or residential development were found, it
was assumed that yields from these two sources are equivalent to
yields from shallow organic croplands according to Skaggs et al.
(1980). In addition, yields from open water were assumed
equivalent to yields from naturally vegetated areas. The use of
the relatively low yields reflects the assumption that open
water areas will serve as a partial sink for metals from
surrounding peat mines and croplands. The following yields from
Skaggs et al. (1980) were used:

Source Yields (lb/acre.yr)
Cu Mn Zn

Deep organic, naturally-
vegetated peat 0.062 0.018 0.071
Deep organic pasture 0.027 0.089 0.071
Shallow organic croplands 0.125 0.107 0.259

196

Land use data used are located in Appendix 10.6 (Table
10.6A).

Yields from the effluent of a peat-to-methanol conversion
plant were calculated based on data from PMA's NPDES application
(PMA, 1983f). The assumption was made that the flow rate and
element concentrations given in this document (0.866 mgd) are
equivalent to those associated with the processing of 500,000
dry tons of peat per year, as stated in Scenario #1, Area 1.
Effluent yields for other areas and/or scenarios were prorated
according to estimates of peat processed for methanol given in
the scenarios (see sections 5.2.2.3.3, 5.2.3.3.3 and 5.2.4.3.3).

6.2.1.3.2 Data

Table 6.2.1.3A: Total annual yields of three trace elements
in drainage waters from peatlands under
alternative scenarios

Scenario Area Year Annual Yield (lb/yr)
CU Mn Zn

1 1 0 981 285 1123
10 1212 611 1811
20 1504 1024 2685

1 2 0 443 129 507
10 609 368 1007
20 755 581 1449

2 1 0 1860 540 2130
10 2050 842 2726
20 3136 2491 6067

2 2 0 930 270 1065
10 1125 552 1652
20 1696 1382 3376

2 3 0 1612 468 1846
10 1890 885 2697
20 2883 2389 5747

2 4 0 806 234 923
10 859 315 1086
20 1092 663 1798

Notes:
Scenario #3: same as Scenario #1, Areas 1 and 2, at years 0
and 10.
Assumed runoff values: same as for Table 6.2.1.2B

197

Table 6.2.1.3B: Total annual yields of selected trace
elements from wastewater effluent
discharged by methanol plants in the
scenarios (lb/yr)

Scenario Area Year Element
Se As Cd Mn Ni Zn

1 & 3 1 0 0 0 0 0 0 0
2.6 7.9 2.6 52.7 184.3 237
20* 2.6 7.9 2.6 52.7 184.3 237

2 1 0 0 0 0 0 0 0
10 4.2 12.6 4.2 82.9 290.2 373.3
20 12.6 37.5 12.6 248.9 871 1120.1

2 3 0 0 0 0 0 0 0
10 2.4 7.5 2.4 49.8 174 223.8
20 9.3 28 9.3 185.4 648.3 833.5

Notes:
*Scenario #1 only
For other areas in all scenarios no processing of peat on site

Table 6.2.1.3C: Average fecal and total coliform bacteria
concentrations measured in drainage water
from the organic soil sites (no./100ml)

Shallow Organic Deep Organic
Crop Natural Pasture Natural
Fecal Total Fecal Total Fecal Total Fecal Total

1976* 28 1665 29 441 730 2672 18 132
1977 207 1091 9 139 1242 2665 5 71
1978 193 2054 28 313 1181 2231 17 117

Note:
*Only monitored for last six months of the year. The averages
are not weighted averages, but are means of all values
obtained, regardless of flow rate.
Source:
Skaggs et al., 1980

198

6.2.1.3.3 Conclusions

6.2.1.3.3.1 Trace Elements

Generally, increases in Cu, Mn and Zn appear to reflect
conversion of peatlands to croplands, which is not surprising
given the yield data provided by Skaggs et al. (1980) and
recalling the equivalence of actively mined areas and croplands.
Trace elements, particularly those that occur predominantly as
divalent cations (e.g., Cd, Hg, Ni, Pb) will probably display
trends similar to those suggested here for Cu and Zn.

Among the trace element components of methanol plant
effluent (Table 6.2.1.3B), the significant quantities of Ni
anticipated may merit particular scrutiny. Unfortunately, no
data concerning organic constituents of such plant effluent are
available; such data are necessary to fully assess potential
impacts of the effluent.

The potential impacts of trace element yields have not yet
been considered due to severe data limitations and current time
constraints.

6.2.1.3.3.2 Pesticides

There are far less data available concerning yields of
pesticides in the region than exist even for trace elements.
However, runoff containing pesticides from peatlands converted
to croplands could have impacts on receiving systems. Yields
have been estimated, to our knowledge, only for Alachlor, the
most widely used herbicide in the region. According to Skaggs et
al. (1980), less than 1% of the amount applied will enter
surface waters, based on field experiments. Using an average
application rate of 3 lbs/ac (3.4 kg/ha) suggested by Dr. John
W. Van Duyn (state entomologist, Plymouth, NC), the following
yields can be estimated:

Low Medium High

(0.1%) (0.5%) (1.0%)

0.0030 lb/ac.yr 0.0151 lb/ac.yr 0.0303 lb/ac.yr

At this point, this is as far as the analysis can go, since we
have no estimates of the proportion of peatlands expected to be
converted to croplands that will be treated with Alachlor. It
should be noted that Skaggs et al. (1980) observed
concentrations of Alachlor in drainage waters on two occasions
that were within the 95% confidence interval of the LD 50 for
bluegill (2.33-4.5 4Ag/ml (Johnson and Finley, 1980).

199

other pesticides currently in use in the area and the crops
on which they are used may be found in Appendix 10.7. Yield
estimates provided by Willis and McDonald (1982) may be useful
for predicting inputs of some of these pesticides where
application areas and rates can be predicted.

6.2.1.3.3.3 Coliform Bacteria

Again, data are quite sparse and appear inadequate for
making yield predictions. However, the following concentration
data from Skaggs et al. (1980) clearly indicate the potential
for large increases in inputs of coliform bacteria from
peatlands converted to croplands and, particularly, to pasture.
The potential impacts of such inputs have not yet been assessed.

6. 2. 1. 3. 3. 4 Summary

The limited data available suggest that peat mining
activity and subsequent land use changes will significantly
increase effluxes of trace metals, pesticides and coliform
bacteria. At this time, little information exists to address the
critical question of the impacts of such increases in drainage
waters on biota of the receiving estuarine systems. Determining
.the potential for impacts is a critical research need. In
addressing these issues, the approach should be similar to that
employed for assessing impacts of complex effluents. If impacts
do occur, they are not likely to be the result of a single
material, such as mercury or Alachlor, but rather the result of
the cumulative effects of a variety of trace metals, pesticides
and other substances.

200

6.2.2 Groundwater

6.2.2.1 Approach/Assumptions

Prior to mining, the estimated recharge rate to the Castle
Hayne Aquifer is between approximately 0.01 and 0.02 inches per
year in the vicinity of Area 1 in Scenario #1 (Foutz,
1983). Confining clay layers over the Yorktown, Pungo River and
Castle Hayne Aquifers are responsible for this very low recharge
rate. These confining layers t1pically possess hydraulic
conductivities of less than 2xlO_ feet per day. It is assumed
that similar recharge rates exist for much of the study area
because of these same confining layers. Figure 6.2.2A
illustrates two approximate hydrogeologic profiles within the
vicinity of Area 1 of Scenario #1 as reported by two independent
researchers (PMA, 1983k; Foutz, 1983).

6.2.2.2 Conclusions

As detailed in the alternative scenarios (see sections
5.2.2.5.13, 5.2.3.5.13 and 5.2.4.5.13) the reduction in recharge
rate to the Castle Hayne Aquifer with the removal of peat was
determined to be less than 10%. The study area does not appear
to be a major recharge area for the primary aquifers and the
potential effects of peat mining on the recharge and on the
aquifer yield are considered to be negligible.

Foutz (1983) found that, with the removal of peat, the
overall downward gradient was maintained, although reduced from
the before mining levels, in the vicinity of the PMA peat mine.
However, this result may not be applicable to other areas in the
region. Leggette, Brashears and Graham, Inc. (LBG, 1983)
predicted, using a three-dimensional ground water model, a flow
of up to 0.6 mgd being released from the shell hash and fine
sand units into the surface water system. This flow results from
a predicted gradient reversal between the fine sand and shell
hash units resulting in an upward rather than downward gradient.
This result differs from Foutz (1983), reported above. The LBG
finding of upwelling is dependent upon the assumption that the
confining clay layers above and below the fine sand unit are
continuous. In the boring analysis performed by Foutz, these
layers were not continuous. The upwelling prediction is also
dependent upon the conductivities of the fine sand and shell
hash units being high enough to maintain an adequate supply of
water to those layers. LBG reported conductivities of these
layers several orders of magnitude higher than those measured by
Foutz. Based on Foutz's data, the upwelling in the PMA harvest
area would be overestimated by LBG and the underlying aquifers
should adjust to a new equilibrium fairly quickly after mining,
preventing any continuous upwelling effect. The LBG conclusion
represents a worst case situation in which heads in the
surrounding aquifers do not adjust to the changing conditions.

201

Figure 6.2.2A: Generalized hydrogeologic units in Scenario #1, Area 1.
Average thicknesses for each layer (in ft.) as reported by
PMA (1983K) and Foutz (1983). Not to scale.

PMA FOUTZ
F
8 PEAT 8.5 PEAT
3 UPPER C 0.5 TRA=r-

SANDY LOAM TO
FINE SAND
25 24 sic" SANDY CLAY
UNIT
LOAM

2 LOWER CLAY UNIT

SANDY LOAM
TO SANDY CLAY
LOAM WITH SHELLS
102 SHELL HASH UNIT 16 @,S >

4J
4-1 LH
%_1 @ 20 YORKTOWN CLAY
U) U)
--YORKTOWN CLAY- U3
Q)

60 YORKTOWN
4 4J FORMATION,
w 190 YORKTOWN a)
cm 40
co M
FORMATION @4
30 PUNGO CLAY

_-PUNG0 -CLAY 206 PUNGO RIVER
FORMATION

20 PUNGO RIVER 10 -CASTLE HAYNE CLAY--
FORMATION

_U5.jLL!jAYNE CLAY- 300-400 CASTLE HAYNE
UPPER
CASTLE HAYNE

SiCL - Silty Clay Loam Lenses
202

The potential for saltwater intrusion is of concern due to
the proximity of the study area to the coast. According to Heath
(1975) the fresh/saltwater interface is moving to the west.
Within the Upper Castle Hayne Unit the rate of lateral movement
is estimated to range from about 5 feet per year to about 15
feet per year for a change in gradient of one foot per mile
(PMA, 1983k). Declines in the hydraulic head in the Upper Castle
Hayne Unit project by PMA as a result of peat harvesting will
result in negligible impact on the rate of interface movement.
In addition, the methanol plant in Scenario #1, Area 1 will
withdraw up to 3 million gallons of water per day (mgd) from the
surficial aquifers for plant site dewatering during plant
construction (approximately 2 years) and a maximum of 2.3 mgd
from high-yielding aquifers for plant processing water during
normal operation. The effects of these direct withdrawals on the
fresh/saltwater interface are unknown.

A second hazard relating to salt water is the potential of
upconing. Heath (1975) estimated the depth to the
fresh/saltwater interface at between 400 and 600 feet. Because
of the higher specific gravity of salt water and provided that
the rate of movement of the fresh/saltwater interface is low,
then, to maintain hydrostatic equilibrium, about 40 feet of
fresh water is required below sea level for each foot of fresh
water above sea level. This is known as the Ghyben-Herzberg
principle. However, because of the variabilities in the
formation layers in this area, this simple relationship will not
be sufficient to determine the depth to the saltwater interface
or its potential intrusion into the freshwater aquifers.
Theoretically, a one foot decline in the pressure head in the
Upper Castle Hayne Aquifer could raise the fresh/saltwater
interface 40 feet. The Castle Hayne Aquifer in Areas 3 and 4 of
Scenario #2 is known to be brackish and any pumping from deep
aquifers in those areas may cause an upconing of brackish water
sufficient to pollute production and local wells.

The probability of these problems occurring increases with
proximity to the shoreline and with decreasing ground elevation.
Special care should be taken in areas where mining will reduce
the ground surface close to or below sea level (Scenario #1 and
#3, Area 2 and Scenario #2, Areas 2, 3 and 4). The salt content
of the Intracoastal Waterway and Alligator River mouth varies
between 1 and 4 parts per thousand (J. Reed, Dept. of Zoology,,
NCSU, personal communication). Fresh water is generally
considered to have a salt content of less than 0.36 parts per
thousand. Thus any encroachment of these waters into local fresh
water wells would cause contamination.

LBG (1983) analyzed the effects of expected alterations in.
hydraulic heads of various formations with peat mining. These
analyses indicate that peat mining will have a negligible effect
on the recharge and yield of the major aquifers and on the
saltwater interface. However, analysis is lacking on the effects

203

of direct groundwater withdrawals for plant: processing. The
exact magnitude of the effects of plant process water
withdrawals of about 2.3 mgd (Scenario #1, Area 1) and the
cumulative effects of direct withdrawals and peat mining are
unknown. The analysis should also be expanded to the other areas
in the study and the potential for saltwater intrusion should be
studied more seriously, especially in areas where mining close
to and below sea level is being considered.

To the extent that saltwater upconing becomes a problem,
controls on pumping and drainage could be imposed in those areas
through mining permit conditions.

204

6.2.3 Hurricane Flooding

Maps of the 100-year floodplain for the counties in the
study area are being prepared for the National Flood Insurance
Administration, but were not available at the time this report
was written.

205

6.3 Land Use Conversions

6.3.1 Approach/Assumptions

Wetland development in North Carolina has been concentrated
on tracts of land underlain by mineral soils, peaty mineral
soils and shallow, high-ash peats. In all of the state's
wetlands that contain peat deposits, most disturbance, including
ditching, draining and clearing for either agriculture or
silviculture, stops where the peat attains a thickness of about
four feet. Once this thickness is reached, the degree of
difficulty in preparing the land increases significantly.
outlined below are the steps typically taken to prepare a site
for farming:

1. Cut out the marketable timber.

2. Dig field ditches to drain the surface and shallow
subsurface water.

3. Bulldoze the remaining vegetation and root mat into
windrows.

4. Bulldoze the excessive peat into the windrows.

5. If the remaining peat contains abundant "fossil" wood, pull
the wood out and add it to the windrows.

6. Burn the windrows.

7. Deep plow the remaining peat into the underlying mineral
soils.

8. Grade the ground surface to attain the proper slope for
surface and shallow subsurface drainage.

9. Fertilize and plant.

Numerous problems are encountered in developing peat
deposits as peat thickness increases. These problems can occur
at any point during site preparation, as illustrated in the
following examples:

1. Virgin timber was removed from most of the peatlands many
years ago. The second growth that now covers a large
portion of the deep peats in Hyde, Tyrrell and Washington
Counties is relatively young, and is thus less attractive
for commercial use.

206

2. The peat associated with the Alligator River predominantly
fills tributary valleys of the river system. The thicker
peats are concentrated in the channel areas of the
valleys. Surface and subsurface waters, unless cut off
by canals, still flow toward these ancestral channels.
These areas, therefore, are naturally wetter than the
shallow peats around the periphery of the deposits, and
are thus more difficult to drain.

3. It is difficult to run heavy machinery designed for
clearing and farming operations over the thick peats,
especially after the supportive root mat is removed.

4. The thicker peats contain greater amounts of large wood
fragments, including large stumps and logs, making the
peat more difficult to prepare for use.

5. The thicker peats are typically low in ash (mostly less
than 10% and commonly less than 5% ash at dry weight)
and are thus nutrient poor.

6. Even with field ditching and evapotranspiration, the water
table in the thicker peats remains close to ground surface,
and very rarely drops into the underlying mineral soils
during the growing season. The underlying mineral soils,
therefore, remain out of reach of most plants.

Numerous small scale attempts, and one major attempt within
the boundaries of Area 1, Scenario #1, have been made to utilize
the thicker peats, but all attempts have thus far failed. By
virture of their inaccessibility, these peatlands have remained
undisturbed. Peat mining may, however, eliminate practically all
the major obstacles that have thus far prevented development of
deep peatlands.

207

6. 3. 2 Data

Table 6.3A: Scenario #1, Areas 1 and 2-- Land use/land cover,
pre- and post-mining (% of total acreage)

Land use Area 1 Area 2
Pre Post Pre Post
Yr 0 Yr 20 Yr 0 Yr 20

Agriculture/
Silviculture 18 72 15 88

Severely
disturbed 56 0 16 0

Undisturbed/
Minimally 24 10* 69 10*
disturbed

Open water 2 18 0 0

Pasture 0 0 0 2

*Restored native vegetation

Table 6.3B: Scenario #2, Areas 1, 2, 3 and 4-- Land use/land cover,
pre- and post-mining (% of total acreage)

Land use Area 1 Area 2 Area 3 Area 4
Pre Post Pre Post Pre Post Pre Post
Yr 0 Yr 20 Yr 0 Yr 20 Yr 0 Yr 20 Yr 0 Yr 20

Agriculture/
Silviculture 9 73 8 88 0 85 2 18

Severely
disturbed 34 0 3 0 3 0 6 0

Undisturbed/
Minimally
disturbed 57 10* 89 10* 97 10* 92 181k
Open water 0 12 0 0 0 0 0 40
Pasture 0 5 0 2 0 5 0 2

Residential 0 0 0 0 0 0 0 22

*Restored native vegetation

208

6.3.3 Conclusions

6.3.3.1 Scenario #1

6.3.3.1.1 Area 1

The peat mines described encompass 15,818 acres. Currently
76% of this tract is severely disturbed or is in human use
(Table 6.3A). Only 24% can be considered in a natural to
near-natural state. Reclamation as outlined in section 5.2.2.10
will include using 72% of the area for agricultural purposes and
18% as an open water lake. Only 10% will return to a native
system.

6.3.3.1.2 Area 2

The peat mine covers 7,142 acres. Currently 31% of this
tract is severely disturbed or is in human use, whereas 69% can
still be considered in a natural state, or has undergone only
minimal disturbance (Table 6.3A). Reclamation as outlined in
section 5.2.2.10 will convert this tract almost exclusively to
agriculture and pasture (90%). Native vegetation will be
regenerated on only 10% of the tract.

6.3.3.2 Scenario #2

6.3.3.2.1 Area 1

The total area covers 30,000 acres. In its present state,
43% of this land is in agriculture, is planned for agriculture,
or is severely disturbed by human activity (Table 6.3B). The
undisturbed 57% is dominated by pocosin wetlands (low
pocosin=44%, high pocosin=13%). Reclamation for this tract as
outlined in section 5.2.3.10 is 78% in pasture, row crops and
pine plantation. An open water lake will cover 12% of the tract.
Only 10% will be returned to native vegetation.

6.3.3.2.2 Area 2

Of the 15,000 acres in this tract, only 11% is severely
disturbed (Table 6.3B). The 89% that is either undisturbed or
minimally disturbed is covered with evergreen forest (8%), mixed
swamp forest (3%), high pocosin (18%), low pocosin (48%) and
partly disturbed land (12%). The reclamation plan outlined in
section 5.2.3.10 will convert 90% of the land to pasture, row
crops and pine; 10% will return to native vegetation.

209

6.3.3.2.3 Area 3

The 26,000 acres in this area are currently 97% undisturbed
(Table 6.3B). Only 3% is considered transitional, containing
field ditches. The undisturbed portion is dominated by high
pocosin (60%). The remaining land is covered with MiXE?d swamp
forest (21%) and low pocosin (16%). Post-mining use outlined in
section 5.2.3.10 will convert 90% of this land to pasture, pine
plantation and row crops, with 10% returning to native
vegetation.

6.3.3.2.4 Area 4

This area contains 13,000 acres, of which 92% is relatively
undisturbed (Table 6.3B). Only 8% has been either cleared for
farming or field ditched. of the undisturbed land, 5% has been
partially ditched. The remaining 88% contains 1% white cedar
forest. Area 4 is elevationally lower than the other three areas
in Scenario #2. Significant drainage problems could develop if
the mined land were reclaimed in row crops. Reclamation assumed
for Area 4, however, includes 40% open water, 22% residential or
recreational use, 20% pasture and pine plantation and 18%
restored native vegetation.

6.3.3.3 Summary

The major overall change in land use due to the scenarios
will be the loss of large tracts of natural, relatively
undisturbed wetlands. The subsequent post-mining maintenance of
this land for agricultural purposes will prevent the land from
reverting to a natural system.

Hyde, Tyrrell and Washington Count ies contain a total of
876,160 acres of land, of which 205,820 (23.5%) was in active
agriculture in 1981 (Lukin and Mauger, 1983). The maximum amount
of peat mining, as proposed in Scenario #2 (84,000 acres),
constitutes 9.6% of the land in the three county area. If the
post-mining reclamation plans outlined in Scenario #2 (see
section 5.2.3.10.3) are followed, an additional 40,900 acres of
crop land will be developed, bringing the total agricultural
land to 28.2% of the total land area in the three counties.

Approximately 84,000 acres of peat in Scenario #2 exists in
deposits at least four feet thick; the entire state contains
about 200,000 acres of wetlands underlain by peat of these
thicknesses. The excavation of these 84,000 acres will eliminate
41% - of this type of wetland environment. The dominant
undisturbed land cover for the total 84,000 acres in Scenario #2
is pocosins (54,000 acres or 65%). If the disturbed pocosin land
is included (13,780 additional acres), pocosins cover 68,080
acres (81%) of the total mining area in Scenario #2. Richardson,

210

et al. (1981) state that North Carolina originally contained
2.24 million acres of pocosins, of which, by 1979, only 695,000
acres were still undisturbed and 808,000 acres were in
transition. The 68,080 acres of total pocosin land in Scenario
#2 constitute 4.5% of the total remaining pocosins in the state;
the 54,300 acres of undisturbed pocosins include 7.8% of the
state's undisturbed pocosins. Superficially, this amount does
not sound like a significant portion of the total pocosin
ecosystem in North Carolina. The pocosins of the
Albemarle-Pamlico Peninsula, however, and in fact, the total
wetland system of the peninsula, constitute the largest and
least disturbed wetland complex in the state. The elimination of
84,000 acres from the core of this system will not only destroy
this portion of the wetlands, but will also aid, indirectly, in
the conversion of many tens of thousands of additional acres of
wetland around the periphery of the wetland complex.

6.3.3.3.1 Legal Aspects of Residential Development

Legal controls exist at the federal, state and local levels
to mitigate environmental harm from large-scale residential
development as proposed in Area 4, Scenario #2. If the area
affected is within the Section 404 permit jurisdiction, a dredge
and fill permit must be obtained from the Corps of Engineers
before any dredging or filling is done in waters of the United
States. Land-disturbing activity would be subject to the three
standards imposed by G.S. 113A-57 for the control of erosion and
sedimentation, and the counties could adopt local sedimentation
control programs pursuant to G.S. 113A-60, under which permits
for land-disturbing activities could be required. The counties
could also regulate development through the adoption of
subdivision and zoning ordinances pursuant to Chapter 153A of
the General Statutes.

6.3.3.3.2 Legal Aspects of Wet Reclamation and Newly
Created Drainage Canals

The following paragraphs outline the laws and regulations
that would affect bodies of water, such as isolated lagoons or
canals with outlets to rivers or estuaries, created during peat
mining.

Excess *water from mined areas may in some cases be disposed
of in isolated storage ponds dredged from land owned by the
mining operator and having no outlet to a sound, river or
tributary of a sound or river.

If the isolated ponds are dredged in areas subject to the
Corps of Engineers' Section 404 permit jurisdiction, that is, if
they are located on "wetlands" within the meaning of Section 404
of the Clean Water Act, then a dredge and fill permit would have

211

to be obtained f rom the Corps, with an accompanying
Environmental Impact Statement. Whether or not the ponds are
located on "wetlands," the permit and reclamation provisions of
the North Carolina Mining Act of 1971, G.S. 74-46 through G.S.
74-68, are sufficiently broad to cover the dredging of the ponds
in conjunction with surface mining, and their construction could
be regulated pursuant to those provisions.

The beds and banks of the ponds (whether isolated or having
an outlet) would remain in private ownership and would be
subject to local ad valorem taxation. However, it is difficult
to appraise land lying under water, and it is therefore likely
that the ponds would be given a nominal. value for tax purposes.

Isolated storage ponds created on "wetlands" within the
meaning of Section 404 would remain a part of the wetlands and
would continue to be subject to Section 404 dredge and fill
permit jurisdiction and Section 402 NPDES jurisdiction after
they are filled. Ponds created on land that does not fall within
the Section 404 definition of "wetlands" would not be "waters of
the United States" under either 33 U.S.C. section 1326(7) or the
expansion of that term in 40 C.F.R. section 122.2 because they
are artificially created and have no outlets into other waters.
As a result, the ponds, once created, would be subject to
neither Section 402 nor Section 404 permit jurisdiction under
the Clean Water Act. Even though they are not created on
wetlands, are artificial, and have no outlets to other waters,
the ponds would still come within the broad definition of
11waters" in G.S. 143-213(20) and could, therefore, be subject to
North Carolina water quality standards and other regulatory
controls.

In other cases, excess water from mined areas may be
disposed of via canals dredged from land owned by the mining
operator opening into a sound or river or tributary of a sound
or, river (including canals receiving waters from storage ponds
with controlled outlets). Canals created in this manner would be
subject to Section 404 jurisdiction, and a Corps of Engineers'
dredge and fill permit would be required for their creation.
Also, a North Carolina dredge and fill permit would be required
pursuant to G.S. 113-229.

The beds and banks of the carkals would remain in private
ownership and would be subject to local ad valorem taxation,
with the same difficulty regarding appraisal mentioned above.

The canals, once created (and probably ponds connected by
an outlet to such canals), would appear to come within the
definition of "waters of the United States" as given in 40
C.F.R. section 122.2, especially in view of the fact that the
courts have given the term an expansive definition (see Leslie.
Salt Co. v. Froehlke, 578 F.2d. 742 (9th Cir. 1978) and U.S. V.
Earth Sciences, Inc., 599 F.2d. 368 (10th Cir. 1979)).

212

Therefore, both Section 402 and Section 404 permit restrictions
would apply to the canals.

213

6.4 Air quality

6.4.1 Approach/Assumptions

The air quality impacts of peat. mining and utilization are
possible to predict only on a site specific basis. Model
predictions require quantitative information on the flux of
emitted pollutants from each source, the location of each
source, the location of all sensitive receiving areas with
respect to the sources, comprehensive meteorological data for
the region and an appropriate mathematical dispersion model. In
addition, the height above ground at which the pollutants are
emitted and any ameliorating conditions must be factored into
the model calculations. The cost and complexity of both data
gathering and computation limit air quality model development to
immediate cases of concern; long range, cumulative air quality
impacts are rarely undertaken because of the additional costs
and the uncertainty that exists in source location. To date, an
air quality impact assessment has only been performed for the
PMA methanol production site that roughly corresponds to the
methanol production site in Scenario #1, Area 1. Predicted
impacts of both fugitive dust emissions during mining and
pollutant emissions from methanol conversion are reported in PSD
permit applications of PMA to the Division of Environmental
Management (PMA, 1981). Because these two source types are
assumed to be the same as the scaled up peat mining development
of Scenario #2, the PMA document could provide the basis for
development of air quality impact models involving the
integrated impact of the large-scale peat mining postulated in
Scenario #2.

Although it was not possible to build a quantitative
integrated model of air quality impacts of peat mining on the
scale of Scenario #2 (or even Scenario #1) without specific
siting location and scheduling, a review of the data was
conducted. Additional information on the following aspects of
air quality are included in Appendix 10.8: applicable air
quality standards; an expanded discussion of pollutant sources
and emissions; critical receptors; models and predictions; and
monitoring requirements.

214

6. 4. 2 Data

Table 6.4A: Scenario #1, Area 1-- Fugitive dust emissions from
peat mining, transport and field pile storage of
peat for methanol production

Source Annual release tons/yr

Harvesting 159

On-site transport 188 (66 tons/yr/round trip
vehicle mile)

Field storage piles 34

Note:
Assumes 1900 acres are actively being mijed each year with
total harvested peat equal to 90.6 x 10 tons at 40%
moisture per year.
Source:
PMA, 1983a

Table 6.4B: Scenario #1, Area 1-- Criteria pollutant emissions
from the methanol plant processing about 1,600 (dry)
tons of peat per day

minimum Minimum
Emission Emission
Potential Plant-Wide Levels Requiring
Pollutant Air Emissions Requiring BACT
(tons/yr) PSD Review Review
(tons/yr)

Particulates 120.4 100 25
Sulfur Oxides (SO 685.9 100 40
Nitrogen Oxides (KO 560.0 100 40
Carbon Monoxide (COI 1032.6 100 100
Hydrocarbons (HC) 95.0 100 40
Ozone 98.8

Source:
PMA, 1981

215

Table 6.4C: Scenario #1, Area 1-- Non-criteria pollutant emissions
from a methanol plant prOCE?SSing about 1,600 (dry)
tons of peat per year

Potential. Plant- Minimum Emission
Wide Air Emissions Levels Requiring
Pollutant Emissions PSD Review
(tons/yr) (tons/yr)

Hydrogen Sulfide (H S) 1.0 10
Carbonyl Sulfide (C8S) 36. 10
Fluorides (HF) 0. 3
Mercury (Hg) 0.065 0.1
Beryllium (Be) 0. 0.0004

Source:
PMA, 1981

Table 6.4D: Scenario #1, Area 1-- Fugitive particulat analysis,
maximum off-property concentrations (A4g/M
from peat for methanol project

Worst Case Mining Location
Class II- Annual Class 11- 24 Hour

Predicted Predicted
Activity Activity
Activity Concentration Concentration

Harvesting 4.16 6.65
Athey Loader 0.004 0.009

Storage Piles

a) Wind Erosion 6.01 8.84

b) Load In/Load Out Neg. Neg.

c) Pile Maintenance Neg. Neg.
Roadways 5.19 6.52

Plant Contribution 3.05 11.57

Baseline Background 40 40

Total Predicted 58.4 73.58

NC Air Quality Standard 75 150

216

Table 6.4E: Scenario #1, Area 1-- Fugitive particulat analysis,
maximum off-property concentrations (Aig/M from
peat for methanol project

Worst Case Mining Location
Class I - Annual Class I - 24 Hour

Predicted Predicted
Activity Activity
Activity Concentration Concentration

Harvesting 0.03 0.082

Athey Loader Neg. Neg.

Storage Piles

Wind Erosion 0.0092 0.090

Load In/Load Out Neg. Neg.

Pile Maintenance Neg. Neg.

Roadways 0.012 0.097

Plant Contribution 0.086 2.14

Baseline Background 40 40

Total Predicted 40.13 42.40

NC Air Quality Stand. 75 150

217

Table 6.4F: Scenario #1, Area 1-- Modeling results: Maximum
off-property predicted concentrations* from PE!at
for methanol project

Averaging New Mine Baseline Total
Pollutant Period Site Plant Background Predicted

Particu- Annual 3.24 0.12 40 4:3.36
lates 24-Hour 12.40 7.34 40 59.7

so2 Annual 0.98 - 20 20.98
24-Hour 6.42 - 20 26.42
3-Hour 26.41 - 20 46.41

CO 8-Hour 80.12 - 1,000 1, 080.12
1-Hour 230.05 - 1,000 1,230.05
NO2 Annual 0.67 - 20 20.67
Cos 1-Hour 9.67 - 0 9.67

Pollutant Averaging Class II N.C. Air
Period Increment Quality Standard

Particulates Annual 19
24-Hour 37 150

so2 Annual 20 80
24-Hour 91 365
3-Hour 512 1,300

Co 8-Hour - 10,000
1-Hour - 40,000
NO2 Annual - 60

Cos 1-Hour - -

*All minimum concentrati on and stagdards expressed in
micrograms per cubic meter (A(g1M ).
Subject to revision pending final permit approval.
Adapted from: PMA, 1981

218

6.4.3 Conclusions

6.4.3.1 Particulate Emissions During Peat Harvesting and
Transport

During the mining and transport of peat, fugitive dust
emissions will result from wind erosion of dried surface peat,
from peat transport and from peat storage piles. Estimates of
these sources have been made by PMA (1983a) and should prove
similar for other areas of the region. Table 6.4A lists the
estimated source term emissions of fugitive peat dust from these
activities. Uncertainties in these emission estimates are very
large and there are reasons to suspect that some of them may be
biased on the low side (see Appendix 10.8). Direct field
measurement of realistic emission rates is urgently needed.

Tilling during peat harvesting and transportation traffic
will contribute about equally to predicted fugitive dust
emissions, with emissions from field storage piles about
five-fold lower.

6.4.3.2 Process Plant Emissions

Methanol production is assumed to be the main point source
of air pollutant emissions. Tables 6.4B and 6.4C are based on
PMA'S analysis (PMA, 1981) and list predicted emissions from the
methanol plant in Area 1 of Scenario #1. Subsequent methanol
plants could have different emission rates depending on control
technologies employed. Nevertheless, the PMA estimates seem
reasonable. Because point source emissions such as these are
more easily monitored than the dispersed sources of peat
harvesting and because control technologies can be more readily
evaluated, regulation of emissions to limit air quality impacts
can be carried out more effectively and with better assurance
that control has been achieved.

6.4.3.3 Fires

Uncontrolled forest and peatland fires are a potential, if
unpredictable, source of particulates to the air. Vandenberg and
Knoerr (1983) measured particulate deposition in the Lake Phelps
vicinity that was approximately ten-fold higher than normal
during a period of extensive forest and peatland fires in the
same region. If fire management efforts are abandoned during
years 8-20 of Scenario #3, an increased probability of
uncontrolled fires could degrade air quality, especially in the
very short term before flooding of mined areas reduces the fire
hazard significantly. Otherwise air quality impacts of Scenario
#3 will be similar to those of Scenario #1 during years 1-8 and
negligible thereafter.

219

6.4.3.4 Effects on Air Quality

Worst case estimates of offsil:e air quality degradation
from mining activities for methanol production in Scenario #1,
Area I are based*on PMA's analysis and shown in Tables 6.4D and
6.4E. Maximum off-property predicted concentrations from a
single methanol conversion plant serving a 15,000-acre mining
tract (i.e. Scenario #1, Area 1) are shown in Table 6.4F.

A single peat-to-methanol plant in Area 1 of Scenario #1 or
plants in Areas 3 and 4 of Scenario #2 will not violate North
Carolina Air Quality Standards at either Class I or Class II
receptor sites under the assumptions used in the PMA model. The
distance and direction of Area 2 from the Swanquarter NWR Class
I area might preclude such a plant location, but no onsite
conversion of peat to methanol is postulated for Area 2 in
either Scenario #1 or #2.

An eight-fold increase in methanol production (and SO 2
emissions) as assumed for Scenario #2, Areas 1 and 3, will
probably not violate North Carolina Air Quality Standards in
Class II areas if the plants are not closely spaced near
property boundaries. so emissions will increase from 686
tons/year to 5488 tons@year (Texasgulf's facility upwind (in
terms of the dominant wind vector) at Aurora produces 21,000
tons/year; Weyerhaeuser's facility at Plymouth emits 18,000
tons/year).

Fugitive dust emissions during peat mining, transport and
storage are probably a more serious concern than emissions from
methanol plants. This is a consequence of the greater
particulate emission rates, peat harvesting in all four areas in
Scenario #2, and the possibility of emissions immediately
adjacent to the mining area boundary.

Estimates of fugitive dust emission impact on air quality
are shown in Tables 6.4D and E for a mining operation as
considered in Area I of Scenario #1. Although no North Carolina
State Air Quality Standards are exceeded in these predictions,
state standards could be exceeded in Class II areas if the
source emission estimates are seriously underestimated (Appendix
10.8) or if harvesting operations are conducted immediately
adjacent to property boundaries.

The Swanquarter National Wildlife Refuge (NWR) Class I area
is perhaps less likely to suffer transgressions of particulate
air quality standards, but more consideration must be given in
Scenario #1 to the impact of the nearby Area 2 peat mining
region which lies upwind of dominant wind vector during the fall
and to Areas 3 and 4 in Scenario #2, which also lie upwind
during this season.

220

6.4.3.5 Amelioration of Impacts through Emission Control

Point sources of pollutant emissions can be more readily
controlled than dispersed emissions from in peat mining and
transport. Known and effective technological methods to control
point source emissions exist, and their effectiveness can be
evaluated readily through specific source monitoring. Many
pollutant emission reduction technologies have been planned for
PMA's methanol plant and accepted as adequate by NRCD and could
be augmented as necessary by further emission controls. These
methods could be applied to other methanol plants such as those
described in Scenario #2.

Controls to limit fugitive dust emissions during peat
harvesting and transport are less well tested and more difficult
to monitor for effectiveness. Rogers, Golden and Halpern, Inc.
(RGH, 1982) suggest four approaches to mitigate fugitive dust
emissions during milled peat harvesting operations: 1) planting
vegetative windbreaks on the prevailing wind side of the peat
drying fields and/or between the fields; 2) harvesting peatlands
in narrow strips perpendicular to the prevailing winds; 3)
roughening the land surface by making a series of ridges in the
fields which trap windblown particles and reduce the wind speed
across the fields; and 4) wetting the fields to form a crust on
the soil resistant to wind erosion.

A similar set of recommendations has been made by
Vandenberg and Knoerr (1983). As yet, neither the effectiveness
of such measures nor their direct and indirect costs are known.
Such information should be obtained on test plots utilizing
local site specific monitoring. Control technologies for dust
emissions from roads and storage piles (e.g. wetting and
screens) should be evaluated.

6.4.3.6 Effect of Peat Mining in Restricting Future Industrial
Growth

As new sources of air pollution are added to a region, the
increments of allowable air quality degradation from subsequent
sources will be reduced. If allowable increments have been
exhausted by prior commitments, additional industrial
development would be precluded if such development further
degraded air quality.

Vigorous debate has arisen over the potential impact of
extensive peat mining and processing in precluding subsequent
industrial development. Rogers, Golden, and Halpern, Inc. (RGH,
1982) believe that the Class I Area of Swanquarter NWR would
seriously limit industrial development, including peat mining
and processing. Representatives of PMA, NRCD and the NC
Department of Commerce have argued that site selection and
application of control technologies could allow development near

221

the Class I Area. Both contentions are speculative until
specific siting and source emission parameters are modeled. To
summarize, the state must ensure through the FISD permit process
that the allowable increments for pollutants are not exceeded by
peat mining, transportation or processing activities. The
extensive modeling and planning process that is part of the PSD
permit process should, however, enable the state to monitor the
expected emissions and to require their control through the
permit process.

222

6.5 Solid waste

6.5.1 Approach/Assumptions

Solid wastes will be generated during peat mining
development as a by-product of onsite conversion of peat to
secondary products. mining itself will generate no solid wastes.
In the scenarios evaluated, methanol is the only secondary
product of onsite conversion. The basis for assessing solid
waste impacts is found almost entirely in the Solid Waste
Management Plan prepared by PMA (1983).

According to this report, non-hazardous and probably
non-hazardous wastes will be generated at the rate of 0.101
tons/ton (dry weight) of peat mined. These wastes include
gasifier slag, pelletized gasifier fly dust, clarifier filter
cake solids, bottom and fly ash from the boilers, spent
catalysts, refuse, dessicants, spent water treatment resins,
gypsum from sulfur dioxide recovery, dirt, combined sludge
wastage from water treatment and peat solids. Slag, fly dust,
ash clarifier solids, gypsum and sludge are the main components.
All will be disposed of offsite in sanitary landfills.

Hazardous wastes to be disposed of in secure offsite
landfills will be produced at a rate of 0.0019 cubic feet/ton
(dry weight) of peat mined. organic bottom sludges from product
storage and bulk plant stock storage have not as yet been
characterized more specifically. In addition, potentially
hazardous by-product oils, produced at a rate of 0.014
gallons/ton (dry weight) of mined peat, will be disposed of by
combustion in the plant boiler.

At these rates of production, wastes will be produced in
the amounts shown in Tables 6.5A and B. Because all solid waste
is to be directed offsite, outputs from all areas have been
pooled.

223

6. 5. 2 Data

Table 6.5A: Non-hazardous wastes from peat to methanol
conversion

Scen- Years 1-10 Years 11-20 20-Year
ario Cumulative
Total
#1 53,000 tons/yr 53,000 tons/yr 1.06xlO6 tons
(851,000 ft 3/yr) (851,000 ft 3/yr') (17xlO6 ft3

#2 135,000 tons/yr 436,000 tons/yr 5.7xio6 tons
(2.17xlO6 ft3/yr) (7.OxlO 6ft 3/yr) (92xlO6 ft3)

#3 53,000 tons/yr 0 0.53xio6 tons
(851,000 ft3/yr) 0 (8.5xlO6 ft3

Note: 3
All figures in ft are baied on an assumption of a bulk
density of 0.062 tons/ft

Table 6.5B: Hazardous wastes from peat to methanol conversion

Scen- Years 1-10 Years 11-20 20-Year
ario Cumulative
Total
#1 1,000 ft 3/yr 1,000 ft 3/yr 20,000 ft 3
#2 2,350 ft 3/yr 8,230 ft 3/yr 108,000 ft 3
#3 1,000 ft 3/yr 0 10,000 ft 3

224

6.5.3 Conclusions

6.5.3.1 Potential Toxicity of Wastes

Non-hazardous or potentially non-hazardous solid wastes
will tot present a toxicological threat. They are similar, in
part, to coal combustion ashes but will generally contain lower
heavy metal concentrations. Leachates of some ashes and slags
produced after test gasification of peat did not exceed EPA
toxicity criteria for all heavy metals analyzed. However, the
finer sized ashes which would be collected in cyclones and
electrostatic precipitators were probably not collected in the
test gasification. Such particles are known to contain higher
concentrations of many elements (including most heavy metals)
than slags and coarser ashes, and the elements are generally
more readily leachable because they are concentrated on the
particle surfaces. Nevertheless, given the relatively low
concentrations of most heavy metals in the source peat,
leachates from gasification ashes and slags would not be likely
to exceed EPA toxicity criteria. However, both the leachability
of real process ashes under realistic conditions and the
specific charcteristics of proposed landfill sites will need to
be evaluated.

Wastewater sludge cannot be well characterized as yet, but
includes activated sludge from treatment of organic plant
wastewater and alum and lime precipitates from inorganic
wastewater. Unless particular toxic compounds from plant
operations enter the organic wastewater stream, these wastes are
probably correctly categorized as."probably non-hazardous."

Hazardous wastes have not been characterized, but if proper
disposal methods are utilized they can probably be handled at
secure offsite disposal sites. As pointed out by PMA, the high
temperature and oxidizing environment of the gasification stream
is unlikely to produce significant amounts of such substances as
tars, oils, phenolics and polynuclear aromatic hydrocarbons
which are the hazardous by-products of most concern in many
synfuels and gasification facilities. No official toxic waste
disposal site operates in North Carolina, a limitation to
offsite hazardous waste plans.

6.5.3.2 Volume of Solid Waste

The ash content of peat is sufficient that very large
volumes of solid wastes will be generated during conversion to
methanol. Even if the wastes are not hazardous, disposal offsite
of the large volumes produced may prove difficult. Low
topographic relief and porous sandy soils limit site
availability for sanitary landfills in the Coastal Plain. Given
the negative value and large bulk of solid waste material to be
disposed of, long distance hauling is unlikely, and local

225

landfills must be used. The 851,000 cubic feet per year of
non-hazardous waste predicted in Scenario #1 probably
approximates the sanitary landfill utilization currently
committed in the Albemarle-Pamlico Peninsula area. The solid
waste volumes anticipated in Scenario #2 would exceed the
Scenario #1 volumes by a factor of nearly ten during years
11-20.

Washington County has considered expansion of the capacity
of its landfill to allow for the accommodation of wastes that
could potentially be generated by a methanol plant such as that
described in Scenario #1, Area 1 (J. DiSarno, Washington County
manager, personal communication). The landfill is on land leased
from a private owner and is operated by an independent
contractor pursuant to a county franchise. Thus, the plans and
desires of both the landowner and the landfill operator must be
taken into account, in addition to the county's needs.

PMA has proposed that much of the non-hazardous waste could
be used onsite during reclamation to agriculture and forestry.
Ashes and sludges would have some value as soil conditioners,
but such use of these materials could affect water quality of
runoff and drainage, especially since the relatively low pH of
local soils and drainage waters is likely to greatly increase
the solubility of many trace elements and metals.

Should the industry fail at year 10 as postulated by
Scenario #3, no substantial differences should occur as a result
of uncompleted reclamation, disposal, or treatment.

226

6.6 Fire

6.6.1 Approach/Assumptions

Fire data were obtained from the North Carolina Forest
Service office in Fairfield, North Carolina. Data were for Hyde,
Tyrrell and Washington Counties for the years 1970 through 1983.
This information was used to calculate the frequency of various
sized fires and the sources of the fires. Fires from earlier
dates were not used. Relatively large scale changes in land use
and land cover in these counties have taken place over the past
20 years. The fire data from before this time would not
accurately reflect fires controlled by present land use/land
cover.

6.6.2 Data

Table 6.6A: Cause of fire (Hyde, Tyrrell and Washington Counties)

Peat Thickness - in feet
% of
Cause of Fire 0 1 2 3 4 5 6 7 Total Total

Miscellaneous 1 - - - 1 - - - 2 2

Railroad 1 - - - - - - - 1 1

Machine use 4 2 - - 1 2 - - 10 11

Incendiary 10 - - - - - - - 10 11

Debris burn 27 6 - 3 - 1 - 1 38 44

Smoking - 1 - - - - - - 1 1

Lightning 16 5 - 3 - 2 - - 26 30

Total = 59 14 0 6 2 5 0 2

% of Total 67 16 0 7 2 6 0 2

Total Number of Fires 88

Notes:
Peat thickness was obtained by plotting the Forest Service fire
location data on the peat thickness map for the three county
area.
Data are based on where the fires started, not necessarily on
what types of land were ultimately burned.

227

Table 6.6B: Size of fire (Hyde, Tyrrell and Washington Counties)

Peat Thickness - in feet
Size of Fire % of
(acres) 0 1 2 3 4 5 6 7 Total Total

5,000 + - 2 - - - - - - 2 2

1,000-4,999 3 2 - - 1 3 - - 9 10

300-999 3 - - - - - - - 3 3

100-299 9 2 - 1 - - - 2 14 16

10-99 37 6 - 4 1 2 - - 50 58

0.26-9 5 2 - 1 - - - - 8 9

0.25 2 - - - - - - - 2 2

Total 59. 14 0 6 2 5 0 2

% of Total 67 16 0 7 2 6 0 2

Total Numbers of Fires = 88

Note:
Data are based on where the fires started, not necessarily on
what types of land were ultimately burned.

6.6.3 Conclusions

1. 67% of the fires started on non-peat soil.

2. 83% of the fires started on either non-peat soil or on peat
only one foot thick.

3. 17% of the fires started on peat three feet or greater in
thickness.

4. 69% of the fires were less than 100 acres in size.

5. 85% of the fires were less than 300 acres in size.

6. 15% of the fires were larger than 300 acres in size.

7. 70% of the fires were started by people.

228

8. 30% of the fires were caused by lightning strikes.

9. 44% of the fires were started by debris burns that went out
of control.

10. 66% of the fires were caused by some form of clearing,
farming, or logging operation.

Fires were concentrated in the non-peat and shallow peat
soils because human activity is concentrated there. Most of the
peats with greater than 4-foot thicknesses either have no roads
into them or have only small canal maintenance roads with
limited access. Most of the fires were small because they were
either easy to get to, easy to extinguish, and/or they started
in areas that were already partially to completely cleared.

Most of the large fires (greater than 1,000 acres) burned
into undeveloped areas, thus hindering control, since these
areas do not have good fire breaks (roads, large canals, open
fields).

.If peat mining does occur, no matter which scenario is
followed, numerous tracts of land, each up to several thousand
acres in size, will be in various stages of site preparation at
one time. Two major factors will control each tract's
susceptibility to fire: 1) the extent to which the vegetation
has been removed and 2) the intensity of field ditching.

If a tract is field ditched, standing surface water will be
removed more rapidly and the ground surface will stay dry for
longer periods of time. If such a tract has not been cleared of
its natural vegetative cover, the associated leaf litter, dead
wood and other surficial debris will also dry, providing a
quick-burning fuel source. A fire that starts in such an
environment will be hard to control. Under such conditions, the
frequency and size of fires may increase.

If a tract is subjected to intense drainage operations and
is also cleared so that the underlying peat soil is exposed for
drying, the fire situation should be different. With the
vegetative cover eliminated, the source of a quick-burning fuel
will also be gone. As the peat dries and is worked by machinery,
it is possible that small fires may occur more frequently. Peat,
even when sun-dried, still contains a significant amount of
water; hence it is more likely to smolder and remain confined to
a small area than to burn with open flames and spread rapidly.
The frequency of fires may increase under these conditions,
because of the increased human activity, but the size of the
fires should stay relatively small.

229

If large tracts of peat are mined and the underlying
mineral soils exposed and planted in either row crop or pine
plantation:

1. The number of fires per unit time will increase, since
these newly exposed areas will be increasingly utilized
by man - the major cause of fire.

2. A greater number of.small, more easily controlled fires
will occur.

3. The larger, less easily controlled fires will decrease
in number, since fewer large blocks of open, undisturbed
land will remain.

To the extent that deliberately set fires are a substantial
risk, they can be controlled through the open-burning
restrictions imposed by G.S. 113-60.23. All three of the study
area counties are classified as high-hazard counties, which
means that before any fire is set within 500 feet of a woodland,
a permit for the fire must be obtained from NRCD.

230

6.7 Local Economics and Employment

6.7.1 Approach/Assumptions

Available information and data on long- and short-run
economic and fiscal and cumulative impacts of the scenarios were
collected, relying heavily on data provided by PMA (1983g). (A
description of each type of impact and means for analyzing them
may be found in Appendix 10.9.) In cases where data were not
available, reasonable assumptions were made.

Assumptions made for Scenarios #1 and #3, Area 1 were:

1. The methanol plant will employ 312 persons once it is fully
operational.

2. During plant construction (2.5-3 years) 1,452 different
workers will be employed.

3. Workers will commute up to 1.25 hours driving time to the
plant and mining sites.

4. Approximately 84% of the operation and construction workers
will be local (within commuting distance).

5. Approximately 16% of the workers will migrate into
Washington and Chowan Counties.

6. Family size for operation workers will average 3.4 people,
including 100 children.

7. The number of new residents per 100 construction workers
will average 228, including 79 children (many workers do
not bring their families with them).

Assumptions made for Scenario #2, Areas 1 and 3:
1. Capacity-employment ratio for the expanded methanol plants
is equal to the ratio assumed in Scenario #1.

The status of population, employment, income and the
availability of public services in the study area under the no
change alternative (present condition) has been documented by
PMA (1983g) and is briefly described in section 4.2.

231

6.7.2 Data

Table 6.7A: Scenario #1, Area 1-- Long-run direct impacts of
525,000 (dry) ton methanol plant

Item 10-County Area

Total employment 312
Local 262
Migrants 50
New residents 1701

New school students 50-100
Increase in retail sales $500,000 2

Notes:
1. Assumes family size of 3.4 (3.4 x 50 = 170)
2. Assumes retail sales of $2,900 per year per person
Source: PMA, 1983g

Table 6.7B: Scenario #1, Area I--- Long-run direct plus indirect
impacts of 525,000 (dry) ton methanol plant

Item 10-County Area

Mine employment 312
New services employment 172 1

Total new employment 484
Migrants 77 2
New residents 262 3
New students 77 4

Notes:
1. The employment multiplier (1.55) includes base employment
(1.0) and new services employment (0.55). Thus new
services employment equals 172 (31-2 x (1.55 - 1.00)).
2. The PMA study concluded that 16% of the operating labor would
not be available locally and would migrat6 into the area
(50/312 = .16). If the same ratio is used here, the estimate
of migrants is 77. However, more service industry workers
than construction workers would probably be available locally.
3. Assumes family size of 3.4 (3.4 x 77 =262)
4. Assumes 100 students per 100 operations workers

232

Table 6.7C: Scenario #1, Area 1- Short-run impacts of 525,000-
(dry) ton methanol plant

Item 10-County Area
Total Peak
Employment
Total employment 1,452 1,169
Local 1,054 832
Migrants 398 337
New residents NA1 768 2
Children NA1 266 3

Notes:
1. Not available
2. From PMA, 1983g (p. 45)-- 228 residents per 100 workers
3. PMA, 1983g (pp. 45, 46) - 79 children per 100 workers
Source:
PMA, 1983g

Table 6.7D: Scenario #2, Areas 1 & 3-- Long-run direct plus
indirect impacts of methanol plants processing
4.1 million (dry) tons of peat

Item 10-County Area
Mine employment 2,4491
New services employment 1,3472

Total new employment 3,796
Migrants 3,3893
New residents 11,5234

5
New students 3,389

Notes:
1. Scenario #2 assumes an expansion of plant capacity to 4.1
million tons, an increase of 7.85. If the capacity-
employment ratio remains constant, basic employment
in Scenario #2 will be 2,449. ((7.85)312 =2,449).
2. Assumes an employment multiplier of 1.55
3. In Table 6.7B, new employment of 484 leads to immigration of
77, with 407 available locally. Assuming the smaller
facility employees are those available locally, the larger
facilities must rely solely on migrants. Thus Scenario #2
would lead to immigration of 3,389 workers (3,796 - 407)
4. Assumes family size of 3.4
5. Assumes 100 children per 100 workers.

233

Table 6.7E: Scenarios #1 and #2, Areas 1, 2 and 4-- Estimated
employment for horticultural peat and peat for fuel*

Employment:
Scenario Area Operation Capacity (dry) At Years
10 20

#1 1 Horticultural 25,000 tons/yr 6 6
#1 2 Peat for fuel 140,000 tons/yr 33 33

Total Scenario #1 39 39

#2 1 Horticultural 50,000 tons/yr 12 36
(at 10)
151,000 tons/yr
(at 20)
#2 2 Peat for fuel 368,000 tons/yr 86 258
(at 10)
1.1 million tons/
yr (at 20)
#2 4 Peat for fuel 432,000 tons/yr 101 281
(at 10)
1.2 million tons/
yr (at 20)
Total Scenario #2 199 575

Notes:
Estimates of employment in peat for fuel operations are based
on PMA estimates of 117 harvesting employees per 500,000 (dry)
tons/year. Assumption was made that employees per ton
harvested is constant.
Estimates of employment in horticultural operations based on
personal communication from Haul Reddick, Peat Fuels, Inc.

Assumes no construction or processing on site, except bagging
of horticultural peat.

234

6.7.3 Conclusions

6.7.3.1 Peat for Methanol

6.7.3.1.1 Scenario #1, Area 1

6.7.3.1.1.1 Long-run Impacts

6.7.3.1.1.1.1 Economic Impacts

Of the 312 employees expected to be employed at the
methanol plant (Area 1, Scenario #1) when it becomes fully
operational, approximately 50 will be non-local. Assuming a
family size of 3.4, a total of 170 people will thus migrate into
the study area. Of these, 50-100 will be children. Also,
assuming each generates an average sales volume of $2,900 per
year (retail sales volume per capita in Washington and Chowan
Counties, 1980), these new residents will stimulate local
businesses by $500,000 per year (Table 6.7A). It should be noted
that use of $2,900 per person per year (PMA, 1983g) assumes
families will contribute, on average, $9,860 per year to retail
sales. This may be high considering the current wage levels in
the area (see Table 4C) and wage levels expected for migrating
workers.

In addition, the migration described above will lead to
indirect effects, because the $500,000 that new families will
spend will generate demand for new businesses, services and
jobs. Assuming an employment multiplier of 1.55, the increase in
basic employment of 312 would lead to an increase of 172 jobs in
the service sector, giving total direct plus indirect employment
of 484 persons in the long run from constructing and operating
the methanol plant. Assuming the same proportion of workers
would be migrating as was estimated for direct employment
(50/312=0.16), the number of migrants needed to fill these
service sector positions is estimated to be 77. However, this is
likely an overestimate of immigration, because service
industries are more apt to increase the labor participation rate
in the locality and also to have less stringent skill
requirements than does basic employment at the mining facility.
The number of new residents employed indirectly resulting from
the methanol plant is therefore estimated to be 262. The number
of new students is estimated to be 77 (Table 6.7B).

6.7.3.1.1.1.2 Fiscal Impacts

Net revenues to local governments may exceed the costs of
services and facilities demanded by new residents. on the other
hand, two types of developmental problems may confront local
governments in the impacted area. First, long-run fiscal
problems may arise in cases where a local government must
provide expanded services and facilities but is unable to tax

235

the new plant. This is a spillover problem where new rE!Sidents
locate outside the political boundaries of the local gOVE!rnments
that have the power to tax the plant. Second, even if long-run
benefits were to exceed costs, front-end or short-run fiscal
problems may arise where revenues generated lag cost incidence.
For example, local government may need to increase the local
school budget immediately upon arrival of new residents, whereas
tax revenues generated by those residents or from the plant
itself will be lagged several years beyond that time. A
short-run cash flow problem will thus arise.

Fiscal impacts will vary by county and city in the
10-county area surrounding the plant. Taxes of several
categories will be contributed by the peat mining facilitiy:
business property taxes; unemployment taxes; intangible property
taxes; inventory taxes; corporate franchise taxes; sales and use
taxes; and income taxes on wages and proprietary incomes.
However, the distribution of these local and state revenues to
individuals and counties will vary greatly ' For example,
Washington County will receive the bulk of the property taxes,
estimated at $900,000 per year (PMA, 1983g). Municipalities and
other counties may receive little. Many of the tax categories
are paid directly to the state. How and to what extent they are
distributed to impacted counties and municipalities will
partially determine whether net fiscal impacts are positive or
negative.

Demands placed on local governments by new residents will
vary in similar fashion. Chowan and Washington Counties will
receive most of the influx of new residents. Yet, Washington
County will likely receive the largest share of revenue
generated by the facility. Chowan County, and particularly the
City of Edenton where many new residents will probably reside,
will receive much less.

The increased number of students may require an additional
school, especially if the influx of students is concentrated in
only two areas, Washington and Chowan Counties. Further, even if
facilities are adequate, several new teachers will likely need
to be hired, and each new pupil will need to be supported. In
1980-81, school expenditures per pupil across the state averaged
$1,-944.31, including salaries, while in the 10-county impact
area, the average expenditure per pupil was $2,103.96 (North
Carolina Board of Education, 1982). Based upon these averages,
the cost side of the fiscal impact of 50-100 new students is in
the order of $105,198- $210,396. of course, not all of these
funds must be generated locally through increased taxes since
the source of school funds in North Carolina in 1980-81 averaged
63% state, 19% federal and 18% local. Nevertheless, the local
fiscal impact may be a problem because of the lag before
receiving the state and federal portions of the money. The
distribution of these impacts will also vary between areas.

236

Finally, new residents immigrating from other areas may be
accustomed to a higher level of services than currently exists
in the study area so that, in the long run, costs may be
incurred to raise the level of services.

Unequal distribution may lead to increased taxes in some
areas while at the same time providing surpluses in others.
Cities may not fare well fiscally, because they can be expected
to bear a large proportion of the demand for new services and
facilities, yet receive little property tax revenue because the
mine lies outside of their taxing jurisdiction. A more detailed
statement concerning school costs and the levels and
distribution of other fiscal impacts requires more data than
were available for this study. To provide additional assistance
to the affected counties, the severance tax discussed in section
4.3.3.3 could be made a state severance tax with some of the
funds being returned to the counties where the mining is
conducted and to cities and counties in the area as impacted
area aid funds, the distribution being made on the basis of
demonstrated need.

There is also a concern that the peat mining facility may
adversely affect the commercial fishery and recreation/tourism
industries. As noted in section 4.2.4, the catch from commercial
fishing in Hyde, Tyrrell and Washington Counties was valued at
$4.5 million in 1980. In 1982, travel and tourism expenditures
were estimated at $11,032,000 in Hyde County, $138,000 in
Tyrrell County, and $748,000 in Washington County (M. Dodd,
Travel and Tourism Division, North Carolina Department of
Commerce, personal communication).

To the extent that peat mining damages the fishery and
reduces commercial catch or the attractiveness of the area for
recreation and tourism, these economic values will decline.
Whether, or the extent to which this may occur, however, is
difficult to estimate without further research.

6.7.3.1.1.2 Short-run Impacts

6.7.3.1.1.2.1 Economic Impacts

Short-run impacts of the methanol plant may be great,
because the number of construction workers will exceed permanent
employment after the plant becomes operational. The number of
employees will peak during the middle of the construction
period, while tax revenues will peak after the plant becomes
operational.

237

During the peak construction period, the total number of
new residents is estimated at 768, including 266 children (Table
6.7C).

6.7.3.1.1.2.2 Fiscal Impacts

Property taxes will be assessed the facility based upon
percent of construction completed on January 1 of each year.
Yet, the impact of population increase will be more immediate.
For example, upon the arrival of a new worker with a family, new
school students will be sent to class if it is during the school
year. The taxing jurisdiction, however, will not receive the tax
revenues until perhaps one to two years later, depending on the
rate at which construction proceeds. For those tax or aid
categories where the state or federal government returns a
portion of revenue collected to the local area or otherwise
shares revenue, the lag may be even greater. Often, the
distribution of these funds is based upon census population, and
any adjustments require waiting for another census. Although
school aid is based upon the current year's enrollment,
short-run increases in population are often missed by these
formulas and produce the revenue lag described.

In the short run, sufficient excess public service capacity
probably exists in the area. Thus large, new expenditures for
many public services would not appear to be likely. However,
operating budgets for some services will increase while capital
expenditures may need to be speeded up for others. School
budgets will need to be larger even though facilities may be
adequate. Improvement and expansion of sewer and solid waste
disposal facilities may require added funds in some localities
(PMA, 1983g).

As with the long-run impact, the distribution of costs and
benefits will vary with some areas experiencing revenue
shortfalls and others experiencing surpluses.

6.7.3.1.2. Scenario #2, Areas 1 and 3

6.7.3.1.2.1 Long-run Impacts

6.7.3.1.2.1.1 Economic Impacts

The larger-scale methanol plants in this scenario were
assumed to have the same capacity-employment ratio as the plant
in Scenario #1. Thus, since Scenario #2 output is 7.85 times
(4,120,721 dry tons/525,000 dry tons = 7.85) larger, basic mine
employment is also assumed to be 7.85 times larger, or 2,449
persons (Table 6.7D).

Assuming the sinaller facility attracts the labor that is

238

Assuming the smaller facility attracts the labor that is
available locally, additional employment for larger facilities
must come from immigration. Thus the migrant, new residents and
new student impacts will be larger both absolutely and
proportionately under Scenario #2 than under Scenario #1. The
direct plus indirect employment impact is estimated at 3,796
compared to 484 under Scenario #1. Immigrants increase from 77
to 3,389. Although data are not available, income effects will
likely dwarf the impact of Scenario #1 because of the large
increase in employment that will provide income to mine workers
and service industry personnel.

6.7.3.1.2.1.2 Fiscal Impacts

Although no quantitative information is available regarding
the fiscal impacts upon the 10-county area under Scenario #2,
potential for the same types of problems exists as for Scenario
#1. These fiscal impacts may be expected to be magnified in
Scenario #2. For example, the distribution of local governmental
costs and revenues will likely be unequal. New residents will
probably live outside of areas able to tax the facilities,
leading to long-run fiscal surpluses in some counties and/or
cities and fiscal deficits in others. The magnitude of each will
greatly exceed those of Scenario #1 because of the very large
increase in immigration. Since some of the sources of tax
revenue are paid to the state, the level of deficit or surplus
will depend upon whether and to what extent tax revenues are
distributed to impacted counties. Under Scenario #2, the role of
state severance taxes could take on increased importance because
of the magnitude and possibly more widespread nature of the
fiscal impacts.

While an adequate supply of public services and facilites
will probably be available to meet the needs of migrants under
Scenario #1, it is unlikely that this will be the case under
Scenario #2. Table 6.7D shows the large increase in overall
population that will be generated, and few cities or counties
could provide needed services and facilites for migrants without
expanding those capabilities. overall, there will be a need to
invest more public funds to meet these demands. However, the
level of demand in a specific county or city will depend upon
the location decisions of the new residents and, once again,
points out the distributional aspects of the issue. Even with
large population increases and increased public investment in
services and facilities, local governments receiving a large
proportion of the tax revenues may still have surpluses.

On the other hand, the potential for large fiscal deficits
is greater under Scenario #2. For example, using school
expenditures data presented earlier, if average expenditure per
pupil equalled the 1980-81 average in the study area, the
increased enrollment of 3,389 students will require increased
school expenditures of $7,130,000. Of this, about 20% must be

239

raised locally. New residents will likely concentrate the demand
for additional school services in relatively few areas. If those
areas are not receiving a large share of the tax revenues
generated, deficits may result.

6.7.3.1.2.2 Short-run Impacts

6.7.3.1.2.2.1 Economic Impacts
If methanol production capacity is expanded by a factor of
7 or 8, the short-run impact will depend upon how the expansion
is accomplished. If the plants are built or expanded in stages,
the short-run impact noted for Scenario #1 may merely continue
for a longer period of time. In this case, construction workers
will finish one stage before moving on to another. Depending
upon the number of stages, this may result in a "short-run
impact" of 10-15 years duration if each stage were to take 2.5-3
years, as for Scenario #1. If plant capacity expansion is not
staged, the short-run impact may be large, because the number of
construction workers is so great. Since no information is
available on how larger plants would be constructed, few
quantitative comments can be made on the short-run impacts of
Scenario #2.

6.7.3.1.2.2.2 Fiscal Impacts

If expansion of plant capacity is staged and does not
require more construction workers than did Scenario #1, the
short-run fiscal impact will resemble that of Scenario #1, as
noted in Table 6.7C. If it is not staged, the potential
short-run fiscal impact will be greater, because the influx of
new residents will be greater. In this case, public service and
facility capacity will likely be exceeded, and short-run.impacts
will be greater, just as was the case in the long-run.
The distribution of costs and revenues among alternative
local governments will again be important.

6.7.3.1.2.2.3 Cumulative Impacts
The expansion of peat mining activity from the level
indicated in Scenario #1 to that of Scenario #2 will attract
other related industries and enterprises that will magnify the
impacts of the mining activity itself. In addition, the
potential for related industries locating in the area will be
greater than in Scenario #1, because of the greater methanol
output and the larger number of people immigrating into the
area. In this case, employment and income multipliers will be
greater, as will fiscal impacts.

240

6.7.3.1.3 Scenario #3, Area 1

The socioeconomic impact of industry failure upon cities
and counties will depend upon the level of development that had
occurred (i. e., the level of employment and income that had
been generated) and the extent of excess capacity built by local
government (schools, waste disposal, etc.). Unemployment will be
created proportional to the increase in employment generated by
operation of the peat mining facility. Income will be lost by
unemployed mine workers (direct effect) and by workers and
businesses serving the basic mining industry (indirect effect).
Fixed facilities constructed will be unused unless other
economic activities replace demand lost with the mining
facility. This includes housing, businesses and public
facilities. Social impacts will be similar to effects in other
areas in recent years, where workers are unemployed and family
conditions suffer.

The extent of the fiscal impact will depend upon the extent
to which local government has expanded the services it provides.
Excess capacity and high costs of government may result if
service construction programs have been accelerated. Other
services, such as the number of school teachers, can be reduced,
but this will lead to higher unemployment and related costs. Tax
revenues will fall, but costs of operating local government will
also decrease. Since many services of local government cannot be
proportionally adjusted downward once provided (e. g., a
wastewater treatment plant or school), and since many are funded
by long-term debt, the reduction in tax revenues will be greater
than the reduction in costs of local government. If this does
occur, the costs of operating local government will rise unless
offset in some other manner. Property taxes will rise
accordingly.

6.7.3.2 Peat for Fuel and Horticultural Peat

The fiscal impacts noted earlier in section 6.7.3.1 will be
magnified to the extent new migrants are employed for harvesting
and processing horticultural peat and peat for fuel. The earlier
discussion of these impacts is applicable here. Insufficient
information is available to estimate short-run and long-run
economic impacts of horticultural peat and peat for fuel
operations, as was done for the peat for methanol facility.
However, direct employment is estimated as shown in Table 6.7E
for Scenario #1 (Areas 1, 2) and Scenario #2 (Areas 1, 2, 4) at
years 10 and 20. These numbers are equivalent to long-run
impacts because of the time frame they cover.

For Scenario #1, Areas 1 and 2, total base employment is
estimated at 39 for each of the years. Assuming an employment
multiplier of 1.55 as before, new services employment may be
expected to increase by 22 (0.55 x 39) for a total direct plus
indirect employment impact of 61 (22 + 39). If 16% migrate.into

241

the area, 10 new migrant workers will arrive and, assuming a
family size of 3.4, will increase population in the study area
by 34. The number of new students will increase by about ten. At
$2,900 average retail sales per person, retail sales will
increase by about $98,000 per year.

Using the same procedures for Scenario #2, Areas 1, 2 and
4, new services employment at year 10 is estimated to be 110
(199 x 0.55) for a total direct plus indirect employment
increase of 309. If 16% of the workers (50) migrate into the
area and family size is 3.4, population will increase by 170,
and the number of students will increase by about 50. Retail
sales will increase by $493,000. At year 20 the increases are:
direct employment, 575; direct plus new services employment,
892; migration of workers, 143; population, 487; students, 143;
and retail sales, $1,400,000.

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7. EVALUATION PROCESS

7.1 Estuarine Impacts

7.1.1 Statement of the Problem

7.1.1.1 Introductory Section

Large-scale peat mining and related land conversion
activities (reclamation) as described in the upper boundary
scenario (#2) (see section 5.2.3) have the potential to
substantially alter primary nursery areas if mining takes place
adjacent to estuaries. While this project has considered the
cumulative impacts of three alternative peat mining development
scenarios, the effects of other forms of land conversion of
peatlands (e.g., to agriculture and forestry) on estuarine
systems are similar in many respects. For this reason, the
following discussion is focussed on the impacts on estuarine
systems peripheral to the Albemarle-Pamlico Peninsula of land
conversion activities in general. Changes in salinity regimes,
nutrient loading, suspended solids, sedimentation, trace
element, pesticide and coliform bacteria levels, and
interactions among these factors are believed to be the most
significant potential estuarine impacts from land conversions.
The processes by which these impacts are effected and the
interrelationships among them are poorly understood. Decision
makers are therefore required to act without an adequate data
base and with considerable risk.

7.1.1.2 Land Conversions

Drainage pattern alteration on the Albemarle-Pamlico
Peninsula for agricultural and silvicultural purposes is
discussed in section 4.1.2.5. According to McMullan (1984),
approximately 12.4% of the peninsula's land area had been
cleared prior to the 1940s. By 1963, 1974 and 1981, 18.5%, 26.2%
and 29.6%, respectively, of the land area had been cleared.
Large-scale peat mining and related reclamation activities would
obviously continue and accelerate this process of land
conversion on the peninsula (see section 6.3).

7.1.1.3 Salinity

Although overall salinities in Pamlico Sound would probably
not be significantly affected by runoff from large-scale land
conversion on the Albemarle-Pamlico Peninsula since it
contributes only about 6-8% of the total freshwater inflow, a
more dramatic effect may occur in the smaller streams and bays
linking the peninsula and Pamlico Sound. Many of these small
tidal creeks have been identified by the North Carolina Division
of Marine Fisheries as "primary nursery areas", the most
productive and sensitive of the state's nursery grounds for
economically important species of fish and shellfish. These

243

primary nursery areas are characterized by soft mud sediments,
proximity to regularly or irregularly flooded marshes, and
salinities ranging from 5 to 15 parts per thousand (ppt) (Pate
and Jones, 1981).
Studies conducted by Pate and Jones (1981) of primary
nursery areas receiving heavy, moderate and no upland drainage
through man-made canals indicated that salinities at the
unaltered sites were more stable during periods of high runoff
than those recorded at two sites receiving drainage waters
through ditches. Their research raised the possibility that
production of brown shrimp and other commercially important fish
may be adversely affected by freshwater "pulsing" via drainage
canals into primary nursery areas during and following storm
events.

7.1.1.4 Nutrient Loading

All North Carolina estuaries can support enhanced algal
growth in response to accelerated nutrient (both nitrogen and
phosphorus) loading (Stanley and Hobbie, 1977; Kuenzler et al.,
1979, 1982; Paerl, 1982, 1983; Paerl et al., 1984). The worst
manifestations of growth enhancement are blooms of blue-green
algae which are restricted to freshwater or oligohaline (less
than 2 ppt salinity) habitats. Nutrient loadings projected for
.the upper boundary scenario (#2) (see section 6.2.1.2) appear to
be sufficient to support blooms in these upper estuarine waters.
If so, salinity would limit the areal extent of blue-green algal
bloom conditions. The offshore extent of such conditions is
currently unknown.
Virtually nothing is known about marine bloom 1'anz@log" taxa
which could develop in higher salinity (in excess of 2-5 ppt)
estuarine waters (Paerl et al., 1984).
Recent research has illustrated the negative impacts of
blue-green algal biomass on herbivorous consumers (zooplankton).
Assimilation and trophic transfer of such biomass are greatly
reduced in comparison to non-blue-green algal food sources
(Fulton. and Paerl, in prep). In the event of documented bloom
potentials and events, food chain alterations may therefore be
expected in receiving estuarine waters. This research is of
long-term relevance with respect to E?Conomic (fisheries) impacts
in the Albemarle-Pamlico Sound systems.

7.1.1.5 Physical Stratification Impacts on Water Quality
Current research efforts into the causes and proliferation
of nuisance blue-green algal blooms in the Chowan and Neuse
River systems have strongly linked vertical stratification
characteristics to bloom potentials. The chief reason for this
direct relationship is the habitat preferences of nuisance taxa.

244

All nuisance blue-green algal taxa, including Microcystis,
Anabaena and Aphanizomenon, have the ability to become buoyant
during stagnant periods when the water column is vertically
stratified (either due to thermal or salinity stratification).
Buoyancy is a response which, from an ecological standpoint,
greatly favors the growth of blue-green taxa over more desirable
(non-buoyant) algal groups, such as diatoms, green algae and
flagellates. During stratified periods blue-green algae can
float to the surface, thereby capturing optimal amounts of
sunlight for photosynthetic production and net growth, while
shading underlying algae.

It is not presently known whether such stratification
potentials exist, and, if so, what their duration and
seasonality are.

7.1.1.6 Suspended Solids and Sedimentation

Because the peninsula has very little relief, erosion is
not a significant problem. Development of peatlands causes a
slight increase in sediment loads in drainage waters,
particularly during land clearing, buried wood removal and field
shaping. Thus, disturbance caused by peat mining may be expected
to increase sediment loads in drainage canals unless settling
ponds or other measures to remove suspended sediment from
drainage waters are utilized. Once initial development
activities are completed, erosion and turbidity during normal
agricultural production are not likely to cause water quality
problems (Skaggs et al., 1980).

The normal hydrology of North Carolina estuaries causes
them to function as sediment and nutrient traps. Increasing
salinity down the estuary neutralizes the electrical charges on
colloidal organic and clay particles, resulting in flocculation
and sedimentation. The sediments are usually soft, organic-rich
muds which constitute a huge sink for oxygen in the overlying
water. Most of the sediment is mineral matter, silts and clays
from the Piedmont as well as from local areas of the Coastal
Plain. The remainder is organic matter, some relatively
resistant material of terrestrial origin and some more labile
material originating from phytoplankton (Matson et al., 1983).
Microbial activity in the sediments and chemical transformations
release ammonium and phosphate to the bottom water, some of
which moves upstream, thus recycling the nutrients to the
phytoplankton and resulting in high levels of productivity
(Stanley and Hobbie, 1977; Kuenzler et al., 1979; Kuenzler et
al., 1982; Paerl, 1982, 1983). High levels of summertime
production which occur in the middle reaches of Pamlico River
(Kuenzler et al., 1979) have not been considered noxious.
Similar or higher productivities in fresher parts of the Chowan
and Neuse Rivers, however, have included blooms of blue-green
algae which are not only noxious but may also adversely affect

245

fisheries (Stanley and Hobbie, 1977; Kuenzler et al., 1982;
Paerl, 1982, 1983; Copeland et al., 1983).
As a result of soil disturbance and diversions and
alterations of surface and subsurface runoff during land
conversion activities, changes in the humic and fulvIc acid
content of receiving waters may occur. Humic and fulvic acids
impact both the transparency and chemical characteristics (pH,
metal availability) of receiving waters (Paerl, 1982, 1983).
Both characteristics are known to affect algal production
potentials. Transparency alterations can regulate
photosynthesis, and hence primary production, in subsurface
depths of the water column. Metals such as iron, manganese,
copper and zinc are required for growth among both desirable and
nuisance algal species. These metals are strongly chelated or
chemically bound by humic and (particularly) fulvic acids.
Differential metal binding therefore affects metal availability,
which in turn can affect algal growth potentials.

7.1.1.7 Trace Metals
Concern regarding the possible effects of peat mining on
the release of trace metals was triggered by reports by ESE
(1983), a consultant for PMA, of elevated mercury
concentrations (above state and federal standards) in canals
draining naturally vegetated peatlands. More recent monitoring
by the state Department of Natural Resources and Community
Development has generally failed to find mercury concentrations
above the EPA recommended criteria (0.2 parts per billion
(ppb)). (The current state standard for mercury is 0.05 ppb,
however, a standard revision to 0.02 ppb is presently under
consideration.) The bulk of available mercury data, however,
reflects pre-mining rather than during- or post-mining
conditions. Studies from Finland (Simola and Lodenius, 1982) and
Minnesota (Clausen et al., 1980) have reported increased mercury
fluxes into receiving systems, apparently as a consequence of
peatland drainage.
Other metals which have higher standards than mercury may
be deleterious to nursery areas. For example, lead
concentrations in excess of the state standard (which is 30 ppb
VS. 0.05 ppb for mercury) have been reported by PMA (1983f). In
terms of toxicity to fish larvae, there is very little
difference between waterborne lead and mercury. The difference
in standards reflects concern for the health of humans, not
fish, and is due to the greater ability of mercury to biomagnify
in food chains.
Skaggs et al. (1980) suggested that peatland disturbances
associated with agriculture will significantly increase fluxes
into receiving systems of three metals which the researchers
measured: copper, manganese and zinc (cadmium concentrations

246

were below detection limits). It is likely that other elements,
particularly those that exist largely as divalent cations, will
demonstrate similar trends. The cumulative impacts of excessive
amounts of these trace metals, as well as interactions among
trace metals and other substances, deserve further study.

7.1.1.8 Pesticides

Potentially of greater concern than trace metals is the
increased influx of pesticides likely to occur with extensive
conversion of undeveloped lands on the peninsula to row crop
agriculture.

Skaggs et al. (1980) reported concentrations of the
herbicide Alachlor within the 95% confidence interval of the
LD for bluegill (Johnson and Finley, 1980) in field
20
di ches draining peatlands. No data are available for other
pesticides, including numerous insecticides used in the region
that are far more toxic to aquatic organisms than Alachlor is.
Data were not collected from main drainage canals " and
concentrations in water reaching the estuaries would be expected
to be considerably lower than concentrations in field ditches.
However, the potential for pesticides to reach and impact
estuarine nursery areas merits consideration.

7.1.1.9 Coliform Bacteria

Research by Skaggs et al. (1980) indicated that the average
number of fecal and total coliform bacteria in drainage waters
from developed shallow and deep organic soils was considerably
higher than from similar undeveloped areas. These coliforms came
from lands under cultivation as well as in pasture, although
bacterial concentrations from the latter were higher. Increases
in bacteria may be due to a generally lower acidity in drainage
waters from developed lands because of liming.
One potential problem with development of organic soils
adjacent to estuaries for pastures or row crop agriculture is
the introduction of fecal organisms via drainage waters into
shellfishing waters. While non-fecal coliform bacteria are not
harmful, they are used as indicators of human pathogens.

247

7.1.2 Data and Information Available

Solution to the problem requires an understanding of
estuarine physical, chemical and biological processes, how they
impact upon estuarine organisms and how these processes are
affected by upland activities. such "understandings" are usually
portrayed through a model.

7.1.2.1 General Approaches to System Representation

The past decade has seen the development of a great range
of models of three general types: 1) empirical, regression
models, 2) loading vs. trophic state models and 3) numerical
models.

Empirical, regression models have been developed for
temperate lakes which show a strong relationship between a
limiting nutrient (usually phosphorus) and algal chlorophyll
levels (e.g., Dillon and Rigler, 1974). Such models have the
appeal of simplicity and, sometimes, high correlations with
field conditions, but have not performed reliably in dystrophic
fresh waters or estuaries. Lauria and O'Melia (1980) suggested
that in the Pamlico Estuary phosphorus is limiting in winter and
nitrogen in summer. They developed two steady-state, one
dimensional (seasonal) models to predict water quality in the
estuary under different nutrient loadings. Thus factors
controlling trophic status may vary temporally as well as
spatially and a single empirical, regression model may not be
adequate to predict conditions over a complete annual cycle.

Extension of empirical, regression models produced models
relating trophic state to phosphorus loading rate, water depth,
water detention time and other variables (Vollenweider, 1968,
1975; Dillon, 1975; Larsen and Mercier, 1975). These models have
proved useful for many lakes, especially since the ultimate
stress (nutrient loading from land runoff) is one of the
independent variables. Furthermore, trophic state is preferable
to chlorophyll-a content because it may be defined in other
terms which are important for a particular water body. This
approach has apparently been used by Lee and Jones (1979). They
expressed strong support for the Organization for Economic
Cooperation and Development (OECD) approach (Seyb and Randolph,
1977; Rast and Lee, 1978), extending the use of the nutrient
load/eutrophication relationships to estuarine waters. Lee and
Jones (1979) inserted data from the Potomac River Estuary into a
Vollenweider-type plot, a step which had.not been done before.
They argued that the low cost and generality of this approach
make it useful for estuaries as well as lakes.

A large number of numerical, simulation or dynamic models
describing aquatic systems has been developed within the past
fifteen years (Chen and Orlob, 1972; Kelly, 1972; O'Connor et

248

al., 1973; Johnson, 1974; Johanson et al., 1976; Harleman et
al., 1977; Vernberg et al., 1977, 1978; Kelly and Spofford,
1977; Kremer and Nixon, 1978; Roesch et al., 1979; Ambrose et
al., 1980; Neale et al., 1981; Burns et al., 1981; Clark and
Feigner, 1982; and many others). Most of these models include
hydrodynamic, water quality and biological components. They
encompass a range of model types including one, two and three
dimensions, laterally and depth-averaged, and a variety of water
quality parameters, including salinity, temperature, phosphorus,
nitrogen, DO, BOD, turbidity and toxics.

7.1.2.2 Prior Modeling Work in North Carolina

Several water quality models have been developed for North
Carolina waters. As mentioned in section 7.1.2.1, Lauria and
O'Melia (1980) developed a model for predicting water quality in
the Pamlico Estuary under different nutrient loadings. Amein and
Galler (1979) generated a water quality management model for the
lower Chowan River, which consisted of a flow dynamics module
and a water quality module. The flow dynamics module was based
on the finite difference representation of the equations for the
conservation of mass and momentum for water flow in estuaries.
Variables included water stage, wind direction and wind speed.
The water quality module included DO, BOD, nitrite plus nitrate
nitrogen, ammonia nitrogen, organic nitrogen and algal biomass.
The module utilized computations on photosynthesis and nutrient
uptake by algae. It was a time-dependent or unsteady flow model
which also predicted nutrient concentrations and algal
abundance. However, neither the Lauria and O'Melia nor the Amein
and Galler model has been used by the state Division of
Environmental Management (DEM) to date because of the large
volume of data (currently unavailable) needed to fit all the
parameters.

In response to recurrence of nuisance surface blooms of
blue-green algae in the lower Chowan River, DEM has adopted a
management strategy based on a phosphorus loading/chlorophyll-a
model. The model was developed by Chapra and Tarapchak (1976,
cited by DEM, 1982) based on the phosphorus
concentration/loading relationship and phosphorus/chlorophyll-a
relationship developed by Dillon and Rigler (1974, cited by DEM,
1982). This simple model takes into account the effect of
variations in annual discharge on average total phosphorus
concentrations, but cannot predict the effects of seasonal
variability in flushing rates and/or short-term fluctuations in
phosphorus concentrations on phytoplankton biomass
(chlorophyll-a). Neither does the model account for the many
physical factors that cause the massive surface blooms and peak
chlorophyll-a levels. It is hoped that the model will provide a
good indication of how the river responds to increases or
reductions in phosphorus loading over several years (DEM, 1982).

249

A simplified approach to predicting the "suitability" of an
area to support a given wildlife species has been developed by
the U. S. Fish and Wildlife Service (1980). Their Habitat
Evaluation Procedures (HEP) relate-environmental conditions to
life requisites for indicator organisms, and may be employed in
space, time or both. Many of the details contained in more
sophisticated approaches are by-passed or consolidated in HEP
(e.g., bottom type may serve as proxy for food), and the models
are difficult to validate (they allege to measure "quality" or
"suitability", but efficient validators of quality and
suitability are evasive). Even with its limitations, the
strengths and practicability of the HEP approach have been
recognized and it is becoming widely applied. For example, the
HEP approach has been used in terrestrial (Lancia et al., 1982;
Noffsinger et al., 1983; Lancia et al., 1984) and estuarine
environments in North Carolina (Adams et al., 1982; Adams and
Overton, 1983).

1 A fini'te element numerical hydrodynamic model was developed
by Wei (1983) at NCSU, and has been used in several projects in
North Carolina. The model has been linked to simple habitat
suitability models to predict impacts of salinity introductions
into Currituck Sound (Adams and Overton, 1983) and channel
modifications in the White Oak Estuary (Adams et al., 1982).
Adaptations of this model and other existing models should
provide the foundation of the modeling efforts discussed in
section 7.1.3.

7.1.2.3 Other Relevant Studies

Kremer and Nixon (1978) developed a mechanistic numerical
model of a temperate estuary (Narragansett Bay, Rhode Island).
Their model used known forcing functions to predict'temperature,
solar radiation, tidal circulation, exchange with an adjacent
sound and river flow, and empirically derived growth
relationships to predict phytopliankton-zooplankton-nutrient
dynamics in the estuary.

Kremer and Nixon (1978) used temperature as the variable
controlling the absolute maximum growth rate of phytoplankton
(Eppley, 1972). Nutrient limitation of phytoplankton growth was
calculated from the concentrations of phosphate, silicate and
inorganic nitrogen relative to the half-saturation coefficient
for these nutrients. The third factor affecting growth was
light. Annual changes in intensity and day length, cloudiness
and water transparency were incorporated. Computations linked
the phytoplankton growth model to the physical forcing functions
in the estuary. These factors and their relationships to
phytoplankton productivity are not fundamentally different from
those of North Carolina estuaries, and a similar model would
likely be satisfactory.

250

The zooplankton community of North Carolina estuaries may
be simulated by the zooplankton model of Kremer and Nixon
(1978). This model includes such controlling variables as
temperature, food availability, filtering rate, reproduction,
respiration, egestion, predation and cannibalism in order to
compute the productivities of several kinds of planktonic
animals.

The roles of the benthos in the Narragansett Bay model were
two: 1) phytoplankton grazing (filtration by bivalves) and 2)
nutrient regeneration. Few data were available on the dynamics
of estuarine benthic communities and, as a result, a program to
measure feeding, respiration and nutrient regeneration rates in
situ was initiated. For purposes of the model, a daily clearing
rate for the bivalve population was determined from pumping rate
and duration projections as a function of temperature. Nutrient
regeneration with temperature was based on in situ flux
measurements made in the bay (Kremer and Nixon, 1978).

The effects of adult fish and higher trophic levels were
not included in the model of Narragansett Bay because the
authors believed it unlikely that this predation exerts
significant influences on the planktonic system and because
omitting this level simplified model development.

The U.S. Army Corps of Engineers (Edinger and Buchak, 1981;
Buchak and Edinger, 1982) has developed a two-dimensional
numerical estuarine model laterally averaged in space. The model
currently includes circulation, salinity and temperature. Water
quality constituents such as dissolved oxygen and nitrogen will
eventually be included. Water quality models will then be linked
to a vertically averaged model. The Corps plans to develop a
three-dimensional estuarine model within the next several years.
The objective of the entire study is to develop methods for
evaluating the impact of changes in circulation on the water
quality of estuarine systems.

7.1.2.4 Data Sources

The type of data currently available and needed in
developing a simulation model is reviewed below. Although
extensive data exist, the data base is currently insufficient to
address many of the problems discussed in section 7.1.1. For
example, the current question on the distribution of the
vertical salinity profile during freshwater pulsing and the
possibility of stratification cannot be answered with biweekly
data at one location in the absence of runoff data or pre-event
conditions. The system is too complex to be described by spatial
or temporal averages.

251

7.1.2.4 .1 Hydrodynamic/Water Quality Datta

Baseline data needed for the development of a hydrodynamic
model include a bathymetric survey, current measurements, tidal
elevation changes and wind speed and direction. Because of the
time dependent nature of the model, values of all the parameters
are required at some initial time (to be used as initial
conditions). At designated boundaries, time varying values of
the parameters are required (to be Used as boundary conditions).
For initial model development, the data could be compiled from
existing sources (i.e., from the bulk of literature that
describes previous estuarine studies in North Carolina).
However? for model refinement and verification, additional field
data would be required. The specific form of the data needed can
best be described as the model is developed and simulation
requirements are defined.

Some of the water quality data needed may be available from
DEM, which conducts two water quality monitoring programs. In
the Ambient Water Monitoring Program 300 sites statewide
(approximately 25 in the study area) are monitored monthly for
temperature, dissolved oxygen, PH, alkalinity, specific
conductance, biological oxygen demand (BOD5) and fecal coliform
and quarterly for turbidity, chemical oxygen demand (COD),
arsenic, mercury and general metals. The Basic Water monitoring
Program samples monthly for temperature, DO, pH, alkalinity,
conductivity, secchi disc, salinity, turbidity, BOD5, COD, fecal
coliform, total nitrogen, NO and NO 3" total Kjeldahl
nitrogen, PO and total p9osphorus and quarterly for
cadmium, totaf chromium, cobalt, copper, iron, lead, magnesium,
mercury, zinc and arsenic at 37 sites,.including one each in
Albemarle Sound and Pamlico Sound (DEM, undated).

7.1.2.4.2 Biological Data

Sampling for phytoplankton biomass and species composition
in the study area is conducted by the'Biological Monitoring
Group of the Water Quality Section of DEM.'Sampling stations are
located in the Chowan, Alligator, Pungo and Pamlico Rivers and
Albemarle Sound. Sampling schedules vary, but nutrient data and
chlorophyll-a measurements are taken whenever phytoplankton is
sampled.
Very little is known about zooplankton in estuaries.
However, sampling for zooplankton is currently underway in the
Neuse River Estuary.

252

The state Division of marine Fisheries (DMF) has been
conducting a monthly survey of fish (March through November) in
nursery areas since 1974. Data on temperature, salinity (surface
and bottom) and juvenile catch data are taken. Depth, sediment
type, % carbon, nitrogen, and organic matter in the sediment and
sediment size have also been recorded for each station. These
primary nursery area stations are not located in the same places
as DEM's sampling stations, however, the two agencies are
considering joint sampling efforts for the future.

As part of an effort to evaluate and update its programs
for coastal water quality DEM has been compiling scientific
information on water quality impacts on key species in estuarine
nursery areas. In addition to reviewing published reports, DEM
is also conducting an analysis of five years of catch data
collected in primary nursery areas by DMF. The analysis of the
DMF catch data focuses on brown, white and pink shrimp; blue
crab; croaker; menhaden; southern flounder and spot. The
relationship between juvenile catch and bottom salinity is the
analysis of primary interest, however, several other factors
including water temperature and some bottom sediment
characteristics are also being examined. The literature review
and data analysis may enable DEM to specify a salinity threshold
above and below which a particular species is not likely to
occur. The information will be integrated to develop possible
water quality criteria for primary nursery areas and water
quality regulations may be proposed.

7.1.3 Recommended Approach

7.1.3.1 General Approach

A substantial body of research, conducted over the past 10
to 15 years, has improved our understanding of the behavior of
estuarine systems and the land-based activities that affect
these systems, yet a sufficient informational framework for
decision making remains elusive. It can be concluded, however,
that 1) estuarine systems and their relationships to land
influences are extremely complex, 2) site specific research must
be undertaken to determine which factors are most important in a
particular environment, 3) data and information on components of
the system must fit into an overall system framework, and 4) the
requisite effort will require large expenditures of resources
over a long period of time (at least a decade). At least three
approaches to the problem are possible.

The first assumes that we now have an understanding of the
system sufficient to support development of a comprehensive,
large-scale simulation. Proponents of this approach argue that
some parts of the system may be poorly understood, but that
sensitivity analyses can be used to identify the most important

253

sources of uncertainty, which can then be addressed by future
research.

The second approach presupposes that. sufficient information :is
available to begin developing parts of the overall system, but
that data and information gaps will preclude completion.. under
this approach, model-building would proceed on parts of the
system until stopped by data and information limitations.
.Research efforts would then be initiated to correct these
deficiencies, while the modeling effort shifted to another
sector. The "model" would thus serve to identify data ( 'laps as
well as to integrate available data and information into the
whole.

The third approach is based on the belief that existing
knowledge is so deficient that research efforts must be 'Limited
to studies of small areas of the system. Under this approach
individual research projects would continue to be supported, but
no effort to integrate results into a larger concept would be
attempted until a later date.

The research team favors the second alternative. It permits
individual research efforts to continue, 'funded from a variety
of sources, yet encourages efforts toward beginning to
understand the larger system. If the state should pursue this
alternative, the team recommends limiting the initial geographic
extent and the number of water quality parameters and biological
components of the modeling effort and maximizing the amount of
field calibration and validation. As experience and expertise
increase, the effort may be expanded in scope and complexity.
Regardless of the approach adopted, the data and information
required can be organized into three subsystems: 1) the land
use-hydrologic subsystem that generates inputs into the estuary
(from the Upland Water Management simulation, section 7.3); 2)
an estuarine physical-chemical System; and 3) an estuarine
biological system.

7.1.3.2 Physical-Chemical Aspects

The hydrodynamic component derive*s from the three
dimensional equations of motion which describe the conservation
of fluid mass and momentum. Variables in the equations are the
three components of velocity, pressure and water elevation.
These equations fully depict the hydrodynamics of the system.
Forcing functions are provided by specifying boundary and
initial conditions. Factors such as winds, tides, currents
bottom topography and bottom materials are included in initial
and/or boundary conditions. Therefore, the basis for the model
is somewhat independent of the simulation criteria. However, the
mathematical model and the numerical technique chosen to solve
these equations will depend in part on the form of the input

254

provided by the Upland Water Management model (section 7.3) and
the output required by the biological component (section
7.1.3.3). These interfaces must be compatible. For example, if
spatial resolution in the vertical dimension is necessary, a
depth-averaged form of the equations above and a boundary
integral ma-thod of solution would be inappropriate.

The water quality component should be developed for the
specific parameters under consideration (i.e., salinity,
nitrogen, phosphorus, suspended solids). For example, the
balance equations could be written in three dimensions for
salinity distribution and solved for each time step. The water
quality component would interface with the hydrodynamic
component by using the solutions from the hydrodynamic component
as input to the water quality component. The temporal and
spatial resolution provided will be determined in part from the
requirements of the biological model and these requirements, in
turn, might influence the development of both the hydrodynamic
model and the numerical solution technique chosen.

Parameters to be considered include:

1. Physical characteristics of receiving waters
a. Surface flow rates, volumes, vertical and stratification
characteristics of receiving estuaries.
b. Turbidity, light penetration characteristics.
c. Yearly temperature fluctuations of entire water column.

2. Chemical characteristics of receiving waters
a. Seasonal and spatial (vertical) distribution of salinity,
major nutrients (including NH 4, N031 P04)1 pH
in riverine
and receiving estuarine habitats.
b. Total nitrogen (Kjeldahl) and total phosphorus
determinations on seasonal and spatial bases.
c. Alkalinity (dissolved inorganic carbon) on a seasonal
basis in rivers and oligohaline estuarine habitats.

7.1.3.3 Biological Aspects of an Estuarine Model

The estuarine biological model component relates simulated
physical-chemical conditions to phytoplankton, zooplankton,
benthos and higher consumers. It may be based on environmental
limiting factors affecting indicator organisms or nutrient
cycling, food chains and energy flow, or more complicated
relationships, and may consider short-term or long-term
conditions. The estuarine biological model is the least
understood component of the overall modeling efffort and will
require a considerable investment before meaningful results can
be expected.

255

Parameters to be considered include:

2. Chemical characteristics of receiving waters
a. Seasonal and spatial (vertical) distribution of salinity,
major nutrients (including NH 4, NOV P04)1 pH
in riverine
and receiving estuarine habitats.
b. Total nitrogen (Kjeldahl) and total phosphorus
determinations on seasonal and spatial bases.
c. Alkalinity (dissolved inorganic carbon) on a seasonal
basis in rivers and oligohaline estuarine habitats.

7.1.3.3 Biological Aspects of an Estuarine Model

The estuarine biological model component relates simulated
physical-chemical conditions to phytoplankton, zooplankton,
benthos and higher consumers. It may be based on environmental
limiting factors affecting indicator organisms or nutrient
cycling,. food chains and energy flow, or more complicated
relationships, and may consider short-term or long-term
conditions. The estuarine biological model is the least
understood component of the overall modeling efffort and.will
require a considerable investment before meaningful results can
be expected.

Parameters to be considered include:

1. Biological characteristics of receiving waters
a. Particulate chlorophyll-a concentrations on a seasonal
and spatial (vertical distribution) basis in riverine
and estuarine habitats.
b. Algal community composition (as major groups -
Cyanophyceae, Chlorophyceae, Dinophydeae, etc.) on a
seasonal and spatial basis.
c. Zooplankton community composition and biomass (again
as major groups of cladocerans, copepods, insect larvae,
rotifers, microzooplankton and icthyoplankton) on a
seasonal basis, using integrated (over depth) water
column samples in major rivers and estuarine
environments.

2. Biophysical processes
a. Seasonal growth limitation effects of nutrients on
phytoplankton.

256

b. Seasonal primary productivity at selected water column
locations, as indicative of actual growth potentials of
phytoplankton under natural (ambient) conditions.
c. Relationships between salinity, water flow, water column
stratification and the potential for algal growth
(blooms) (seasonal).
d. Relationships between salinity, water flow and dissolved
oxygen in the water column (seasonal)
e. Nutrient exchange between the sedimen@s and water column
on a seasonal basis. Relationship of nutrient inputs
and outputs to overall nutrient availability for
phytoplankton growth.
f. Current food chains utilizing particulate matter
generated in and entering the estuary, including major
rates of food utilization, preferred food types and
preferred herbivorous grazers sustaining commercially
and recreationally important finfish and shellfish
species. Current rates of food transfer (fluxes)
along identifiable links in the estuarine food chain.
(The choices of desirable phytoplankton food sources
and herbivore grazers depends on the desired finfish
or shellfish resources.)
g. Interactions of estuarine salinity gradients with
qualitative and quantitative aspects of primary and
secondary productivity.
h. Hydrological and nutrient loading "mass balance"
budgets to predict the impacts of altered freshwater
nutrient loading on quantitative and qualitative
characteristics of estuarine primary productivitiy.
In other words, the relationship of nutrient loading
to both the amounts and types of algal production
desired.

7.1.3.4 Application

An estuarine model could be used as a means of
understanding the system and identifying significant data gaps.
In addition, such a model would allow decision makers to assess
the impacts of existing and proposed coastal land use on the
state's estuarine resources.

7.1.3.4.1 Regulatory Implications

An estuarine model could also be used as the basis for
setting effluent limitations to meet water quality standards for
primary nursery areas, should such standards be established by
the Environmental Management Commission.

257

7.1.3.4.2 Legal Aspects of the Control of Freshwater Drainage
into Primary Nursery Areas

The assumption has been made here that a major portion of
the fresh water drained from the mining activities will enter
"Waters of the United States" (rivers, sounds, estuaries) via
either man-made or improved canals and ditches.

The discharge of fresh water into the brackish waters of
the primary nursery areas probably cannot be controlled through
the NPDES permit process in the same direct way that BOD or TSS,
for example, are controlled. This is because fresh water is not
included in the definition of "pollutant" in 33 U.S.C. section
1362(6) (Clean Water Act), and the primary basis for control
under an NPDES permit is to limit the discharge of "Pollutants,"
as defined. Nor do any of the effluent limitations promulgated
by EPA for various categories of point sources include fresh
water among the standards.

In order for the NPDES permit system to be used to control
fresh water discharges, the Environmental Management Commission
must create a classification for the nursery areas with
accompanying water quality standards that specify a required
range of salinity. The statutory basis for classifying waters of
the state and applying standards to the classifications is G.S.
143-214.1. Of special interest for present purposes are G.S.
143-214.1(d) (3), which requires the Environmental Management
Commission to consider the extent to which the waters are being
used for "fish and wildlife and their culture," and G.S.
143-214.1(d)(4), which requires the Commission, in adopting new
classifications or standards, to consider the use and value of
the waters for the "propagation of fish and wildlife."
Statutory definitions that support a classification of the
nursery areas are -G.S. 143-213(20), which includes swamps,
sounds, tidal estuaries and bays within the definition of
"waters", and G.S. 143-213(19), which defines "water pollution"
broadly as being the "man-made or man-induced alteration of the
chemical, physical, biological, or radiological integrity of the
waters of the State, including, but specifically not limited to,
alterations resulting from the concentration or increase of
natural pollutants caused by man-related activities."

once the classification and standards have been adopted,
the standard must be submitted to EPA for approval pursuant to
33 U.S.C. section 1313(c). Once EPA has approved the standards,
then any NPDES permit issued that would affect the classified
waters -- whether issued by EPA or the state -- must, pursuant
to 40 C.F.R. section 122.44(d)(1), contain conditions that are
designed to protect those standards.

258

A second possible approach, independent of the NPDES
permit, but still relying on a classification and standards,
would be to require a state permit for the discharge pursuant to
G.S. 143-215.1(a)(6). In this regard, the definition of "waste"
in G.S. 143-213(18)b appears to be comprehensive enough to
include fresh water drained from mining activities; the water in
this case is a "waste substance ... resulting from ... the
development of any natural resource."

A -third possible approach, which could be used in
conjunction with the adoption of a classification and standards
or without the adoption of a classification, would be to require
a permit for the discharge of fresh water into the nursery areas
pursuant to G.S. 143-215.1(a)(10). This provision was adopted to
enable the state to assume authority over the discharge of
pollutants into aquac*ulture projects pursQant to 33 U.S.C.
section 1328(c). The language of G.S. 143-215.1(a)(10), however,
appears to be broader than necessary to implement the federal
statutory requirement. The state statute is phrased in terms of
a broad prohibition against the discharge of pollutants into one
of the described areas, whereas the federal statute gives
authority to EPA to allow the discharge of specific pollutants
into aquaculture projects under certain conditions. The breadth
of language in the state statute may allow it to be used in this
situation, but before it may be used the state must show that
the primary nursery areas that are of concern are "defined
.managed area(s) of the State's waters for the maintenance or
production of harvestable freshwater, estuarine, or marine
plants or animals."

A fourth possibility, once a classification and standards
have been adopted, would be to condition the mining permit on
the taking of actions necessary to protect the salinity or other
water quality standards for the nursery areas. This may be done
pursuant to G.S. 74-51(3), which provides that the permit may be
denied if the activity would violate surface water quality
standards, and G.S. 74-49(13), which requires the reclamation
plan to include a plan for compliance with state water pollution
laws.

A fifth possibility would be a special order issued
pursuant to G.S. 113-230 to control activities in coastal
wetlands for the protection of marine fisheries. The use of this
approach would require the Secretary of Natural Resources and
Community Developmet to make use of the expanded.definition of
"coastal wetlands" allowed by G.S. 113-230(a) to include not
only "marshes," as defined in G.S. 113-229(n)(3), but also "such
contiguous land as the Secretary reasonably deems necessary to
affect by any such order in carrying out the purposes of this
section."

259

7.2 Wildlife

7.2.1 Statement of the Problem

Natural resource development on the Albemarle-Pamlico
Peninsula inevitably involves conversion of one habitat-land use
type to another and concommitant faunal changes. In the
scenarios evaluated, the most significant conversions were from
pocosin vegetation to mining to agriculture, and the most
significant adverse wildlife impacts were upon black bear and
bobcat. The bear, in particular, is intolerant of human
disturbance and requires large areas of suitable habitat. The
coastal plain population is under considerable stress. Under the
most extreme conditions evaluated (Scenario #2, Area 1) (see
section 6.1.4.3.2), bear habitat quality in the impacted area
would be reduced by 40%; under the most favorable conditions
(Scenario #3, Area 2) (see section 6.1.4.3.3), habitat quality
would be reduced by 28%. Bobcat habitat quality, under the same
circumstances, would be reduced by 30% and 19%.

The validity of these conclusions rests on two unproven
assumptions. First, habitat quality indices used in modeling
impacts were derived from a consensus of wildlife biologists
familiar with the area and were intended to measure the
"goodness" of each habitat-land use type from the standpoint of
each species considered. No field data were used in developing
these models, nor was there any attempt to validate the results.
Secondly, indices applied to post-project conditions assumed
certain degrees of effectiveness for buffer strips and other
mitigation measures, none of which has been field tested.
Thus, the results represent state-of-the-art efforts within
the time and funding constraints imposed by the project, but
their reliability is yet to be tested.

7.2.2.Data and Information Available

7.2.2.1 Habitat Quality Modeling
The procedure dsed in predicting wildlife habitat impacts
was developed by the U.S. Fish and Wildlife Service, and is
termed Habitat Evaluation Procedures (HEP) (U.S. Fish and
Wildlife Service, 1980). It consists of 1) inventorying the land
use-habitat types on the study area, 2) selecting evaluation
species, 3) determining a Habitat Suitability Index (HSI) for
each habitat type for each species, 4) estimating the rate of
change from one type to another, 5) accruing habitat quality
units for each species over the project period, and 6)
evaluating results in terms of impacts on individual evaluation
species and on "wildlife" as a whole as represented by the sum
of indicator species (or guilds). Models for numerous species
have been developed by the Fish and Wildlife Service.

260

HEP are usually used in the form described above,
emphasizing temporal changes at the expense of spatial
considerations. Another approach, developed at N. C. State
University (Adams et al., 1982b), applies HEP principles in a
spatial context, but is unable to efficiently consider changes
in continuous time (although before- and after-project
conditions can be evaluated). No means for considering both
spatial and temporal aspects of habitat conversion currenty
exist, although both are important in evaluating impacts on
wildlife.

In a temporal context, HEP have been used in North Carolina
to evaluate effects of the Falls Reservoir (Hair, 1978) and
Prulean Farms' Section 404 permit application (Noffsinger et
al., 1983). In a spatial context, they have been employed to
assess proposals to introduce salt water into Currituck Sound
(Adams and Overton, 1983) and to assess efforts to improve
circulation in the White Oak River Estuary (Adams et al.,
1982a). In these examples, no effort was made to validate
results beyond findings of "reasonableness" and acceptance by
peers.

The concept of validation is itself hazy, and more efforts
toward validation by field data are needed. Although HSIs are
alleged to measure "suitability" or "quality", these terms are
difficult to define and more difficult to measure. Lancia et al.
(1982) attempted to validate a bobcat model (with reasonably
good results) and various songbird models (with mixed results).
Other researchers (Whelan et al., 1979) had similar experiences.
Common, specialized species with small home ranges are more
easily modeled; rare, generalized, and far ranging species are
more difficult. Frequency and intensity of use appear to be
better validation criteria than population density. Limiting
factors other than habitat quality (e.g. predation, social
interactions, accessibility, demographic and behavioral factors)
frequently confound field validation attempts.
Despite these weaknesses, the HEP approach appears to
possess the potential for evolving into a useful and credible
tool for assessing land conversion impacts. At the present
time, it has no competition. Efforts must therefore be expended
toward improving this system as it may be applied to land
conversions on the Albemarle-Pamlico Peninsula.

7.2.2.2 mitigation

During- and post-project HSIs used in this study considered
mitigation efforts currently included in mining permits and
those proposed in draft form (as of March, 1984) within the
North Carolina Wildlife Resources Commission. The latter
describes a Regional Peat Mining Reclamation Plan containing

261

"interconnecting wildlife habitat corridors" linking state and
federal land and proposed Natural Areas, "buffer strips" along
natural water bodies, and "buffer strips and filter strips" as
part of individual mine site reclamation plans. While
specifications (length, width, separation, vegetation,
management) are suggested in the draft and must be part of any
implementing documents, no data exist by which one could assess
animals' reactions to these mitigative efforts or evaluate
trade-offs between dedication of land to wildlife mitigation and
other more economically rewarding uses.

A second approach to mitigation emphasizes modifications of
customary land management practices to lessen adverse impacts
upon wildlife without changing basic land use patterns. Somewhat
analogous to Best Management Practices (BMPs) developed in
response to Section 208 of PL 92-500, these measures could
include minimum ditch and canal bank disturbance (reducing
erosion and sedimentation and destruction of muskrat food
plants), minimal channel maintenance (lessening impact upon fish
and other aquatic biota), encouraging woody vegetation along
canal banks (reducing erosion, shading out aquatic weeds),
minimum tillage (leaving unharvested grain exposed over the
winter, reducing erosion), and many others. The efficacy of this
approach, in contrast to mitigaton based more on land
dedication, is untested.

In reality, a combination of habitat preservation, BMPs and
monitoring efforts may be the most likely approach.

7.2.3 Recommended Approach

7.2.3.1 Habitat Quality modeling

Two efforts are required. The first would validate HSIs for
selected species (particularly black bear and bobcat) using
field data from the study area. The second would link spatial
and temporal aspects of the modeling concept in a form usable
for "real-time" decision making.

While the procedure for field validation and improvement of
models is relatively straightforward, many more validations need
to be completed to document and/or improve the accuracy of the
HSIs. Wide ranging and rare species have been particularly
evasive, and require extensive study areas and considerable time.
and expense. In this instance, the validation project should:

1. Consider black bear and bobcat.

2. Develop species-babitat models incorporating spatial con-
siderations, based on literature and consensus of area
biologists.

262

3. Predict habitat quality for each species over a large
study area (several thousand acres) on the peninsula.

4. Correlate habitat quality, as determined by the models,
with animal presence, use intensity, use frequency, or
other validator.

5. Revise original models to improve correlations.

6. Test revised models in another, similar, area.

Techniques and procedures are reasonably well known,and
proven; fiscal, personnel, and materiel recluirements should be
readily estimated; and definitive results shoqld be attained.

The second element, linkage of spatial and temporal
considerations, is much less certain. Conceptually, one should
be able to iterate a spatial model through time, apply it to a
computer-generated habitat map of the study area, inject types
and locations of management decisions, and perform all
operations on an easily accessible micro-computer. Such a system
would permit a land manager to evaluate alternative land use
decisions prior to execution, assessing their wildlife impact
before commitments were made on the ground.

In approaching this element, the following steps would be
taken:

1. Enter a land inventory into a computer and obtain graphic
output on the monitor.

2. Load a program containing species-habitat models for
species of interest.

3. Indicate a decision (time,space) to modify part of the
study area.

4. Obtain a computer-generated map of the revised land use
distribution.

5. Obtain an analysis of the impact of the decision upon
species of interest.

6. Advance time by any desired increment, and repeat the
procedure.

7. Continue the process through a reasonable time span,
and obtain an analysis of accrued impacts.

263

8. Repeat the process until the implications
of the decisions are known and the results
satisfactory.

Development of this procedure will require a considerable,
but difficult to quantify, investment. One is never sure of the
cost of developing a computer program until it has been
developed. Nevertheless, the evolution of decision oriented
models for wildlife habitat impact assessment is moving in this
direction, and the process will not be complete until spatial
and temporal considerations can be evaluated in real time.

7.2.3.2 Mitigation

Two approaches may be employed. The first would use
observations of existing situations, similar but not necessarily
identical to recommended mitigation, as indications of results
to be expected. The second would employ a designed array of
potential mitigation measures.

Distributed throughout the peninsula are numerous examples
of potential mitigation measures, created over time through
random and/or fortuitous land use decisions. Buffer strips of
various dimensions and character do exist along some fields;
relict stands of natural vegetation, of varying area, have
survived agricultural development here and there; linkages and
corridors among escape cover and refuges can be found; and
examples of diverse agricultural practices impacting upon
wildlife species occur. observations of wildlife use (hence
habitat "goodness") under these varying conditions could provide
quidance, with no development cost in time or money, for those
stipulating mitigation as part of permit conditions. Under this
approach, the following steps would be taken:

1. Determine the array (dimensions, age, vegetation,
management practices, etc.) of potential mitigation
measures of interest.

2. Select a preliminary set of examples through analysis
of historic aerial photos.

3. Confirm suitability through ground surveys.

4. Determine abundance and use intensity by species of
interest in each site.

5. Relate use intensity to site characteristics; opti-
mize for species of concern.

6. Use results as bases for specifying permit conditions.

264

7. Monitor results and adjust specifications accordingly.

This approach could be implemented immediately, before
permits are issued, at no development cost. Results could be
available within a short time, probably before significant
mining development occurs, and in time to amend outstanding
permits with minimal trauma-. There would be no opportunity to
design a well-balanced, precise experiment, however. Some
conditions would be under-represented or missing, while others
would be over-represented. Replications and experimental
intervals between examples would thus be unequal and erratic,
and statistical analyses may be more complicated and less
powerful than in the following alternative.
Conditions attached to mining permits provide a vehicle
for: 1) designing an experiment in alternative mitigation and
implementing it as part of the mining-reclamation operation, or
2) entering into a cooperative agreement with a permittee under
which a long-term mitigation program could be conducted and
evaluated. Under this approach, the following steps would be
taken:

1. Design a balanced array of mitigation alternatives,
including land dedication and management practices,
that would provide a spectrum of conditions signif-
icant to the species concerned (particularly bear
and bobcat).
2. Include specifications for the array as part of permit
conditions or under a cooperative agreement with a
permittee.

3. Implement the mitigation plan.
4. Evaluate resulting conditions in terms of animal use or
other validator.

5. Determine the optimum mitigation plan, based on results
from above.

6. Amend existing permits, condition future permits,
accordingly.

This approach has the advantage of better experimental
design and simpler and more powerful statistical analysis. It
incurs significant development costs, in both time and money,
however.

265

7.2.3.3 Application

The recommendations outlined above will. provide a firm
factual basis for addressing the most critical. wildlife habit-at
problems associated with peat mining or other land use
conversions on the peninsula. Results can be implemented through
permit conditions (mining; Section 10, Section 404; CAMA; etc.),
BMPs and general educational programs.

266

7.3 Upland Water Management

7.3.1 Hydrology of Existing Natural Conditions

7.3.1.1 Statement of the Problem

Large sections of the areas potentially available for peat
mining on the Albemarle-Pamlico Peninsula are covered in natural
pocosin vegetation (see Appendix 10.1). The rate and variability
of the runoff from these areas are not well known, either from
ditched (1.5 mi. blocks) or unditched areas. A specific problem
is the lack of detailed understanding of the magnitude and
behavior of bank storage flow, the release of water from the
banks immediately adjacent to a canal or ditch following an
infiltration event. Potential runoff from agricultural land can
be estimated, but a better understanding of the existing
conditions is needed for accurate assessment of the
environmental impacts of mining or otherwise altering natural
pocosin areas.

7.3.1.2 Data and Information Available

Pocosin areas are characterized by a 'thick porous mat of
roots and decaying vegetation overlying the peat. This mat
restricts evaporation from the peat and is also responsible for
rapid interflow of rainfall. Because of the large pores in the
mat, it is rarely saturated. During rainfall it absorbs water
rapidly. This water then infiltrates the underlying peat at a
much slower rate or, if the peat is saturated to the surface,
flows through the porous mat, fairly rapidly, to the nearest
available outlet. Badr (1978) determined hydraulic
conductivities of this layer at about 26 ft/hr or higher. Runoff
da a exist from a previous study of a ditched pocosin area (1/2
mi block) (Skaggs et al., 1980). Water table depths at the
center of the same block are also available for about three
years.

Another distinctive feature of the pocosin areas is the
magnitude of the effect of the bank storage. Any water that may
be released into a ditch or canal from the adjacent banks will
tend to be a fairly significant percentage of the total water
lost from a field by subsurface flow following a rainfall event.
This is because of the very low hydraulic conductivity
(approximately 0.008 in/hr) of the peat which, in general, keeps
the subsurface drainage very low but also allows the bank
storage zone to "fill up" more than would occur in a mineral
soil. This is also complicated by flow through the porous mat
which tends to "extend the bank storage effects" farther back
from the ditches than would normally be expected.

267

7.3.1.3 Recommended Approach

Various modeling techniques need to be investigated in
relation to this problem, which previously has been looked at on
a per unit area basis. Water balances at a point have been
performed by Purisinsit (1982) using the DRAINMOD computer
model. Solutions to the water balance and water flow equations
need to be found over an area. A two-dimensional, finite element
solution technique would achieve this. The hydrology of the root
mat should be examined closely. A technique for routing flow
through the root mat and over the ground surface would be
desirable. Also, improved, simpler methods of routing flows
through the canal systems to the outlets need to be developed
for determining the impact of field scale changes on runoff
reaching estuaries.

In addition to the modeling approach, a number of field
experiments are required to improve data for the models as well
as to gather information to improve our knowledge and
understanding of the hydrologic processes in these areas: 1) the
characteristics of the root mat need to be analyzed; 2) improved
descriptions of the root mat's depth, conductivity and effect on
infiltration to the peat layer underneath are required
(infiltrometer experiments are suggested, with the rings
extending to the peat layer beneath the root mat); 3) average
rooting depths of the vegetation should be determined as
valuable inputs to the modeling effort; and 4) additional
measurements from large unditched natural areas are also needed.

7.3.2 Nutrient Transformation in Canal and River Networks

7.3.2.1 Statement of the Problem

Good data exist on the nutrient and sediment losses from a
mined or agricultural area at the field edge (Skaggs et al.,
1980). However, it is necessary to know what transformations
take place within canal or river networks draining into
estuaries. This would enable more accurate predictions to be
made of the effects of field level operations on the ultimate
receiving waters.

7.3.2.2 Data and Information Available!

Some data have been collected by Gregory et al. (1984) and
PMA (1982c, 1983f).

268

7.3.2.3 Recommended Approach

A monitoring network along several existing canals being
fed from a number of different land use types would be required.
Continuous sampling for nutrients, sediment and possibly metals,
herbicides and pesticides following rainfall events of varying
magnitudes as well as under base flow conditions, would help
answer many of these questions. This question is being
investigated to a limited extent by Gilliam et al. (1983).

Data obtained in these studies would provide input to the
hydrodynamic/water quality component of the estuarine model
discussed in section 7.1.

7.3.3 Improved Field Data and Modeling for Actively Mined Areas

7.3.3.1 Statement of the Problem

Development of better field runoff measuring techniques is
needed. Existing flow measuring techniques (weirs with stage
level recorders) are prone to problems (e.g., clogging,
submergence). The need for improved field data for both model
input and model testing is particularly great for the actively
mined and pocosin areas. The present modeling work for these
habitat-land use types is based on many assumptions which should
be verified or updated.

7.3.3.2 Data and Information Available

Flows from areas under active mining appear to be much
higher than flows from unmined fields. The primary reasons are:
1) increased compaction from heavy machinery; 2) improved
surface drainage from land forming and extra ditches; 3) the
removal of vegetation, reducing transpiration; and 4) the
harvesting of the dry surface layer which 'otherwise functions as
a "storage reservoir" for subsequent rainfall. Current modeling
predicts that during mining the average annual flow from a field
will increase by about 35% over the pre-mining condition. All of
this increase is in the surface runoff component which is
predicted to increase by up to 130% over the pre-mining surface
runoff from disturbed (pasture) lands and by a higher percentage
from natural pocosin areas.

Field data collected by ESE (1983) and Gregory et al.
(1984) illustrate increases in total volume, flow duration and
flow peaks from the sites opened for mining over the pre-mining
sites. However, data from all of the largest storms were lost
due to weir submergence or clogging with debris or silt.

269

7.3.3.3 Recommended Approach

One or more actively mined field sites should be monitored
to record all of the water leaving them. one possible method
would require the use of some form of unrestricted outlet from
the site with a control structure through which all water
leaving the site would be forced to pass. Another approach would
be to isolate and pump all of the water leaving the site. An
effective series of debris and sediment traps would be required
upstream of the control structure in the canal or field ditch to
prevent clogging and erroneous results.

A detailed soil property analysis of the surface layer of
an actively mined site should be made. Infiltration properties
of the peat vary with wetting and drying in a more exaggerated
manner than is the case for mineral soils. The hydrologic
properties of the layer of peat exposed and allowed to dry
change during the drying process. Knowledge of the nature and
rate of these changes would greatly assist in modeling efforts.
The modeling allows "average" conditions to-be approximated by
simulating a situation over many years of climatological data.
Thus by comparing the long-term average runoff before, during
and after mining, realistic conclusions may be drawn regarding
the expected hydrologic effects of peat mining. Single event
analysis is more difficult to set tip accurately enough to get
reliable results.

Data from these efforts would provide input to the
estuarine model (see section 7.1).

7.3.4 Wet Reclamation and Perpetual Pumping

7.3.4.1 Statement of the Problem

Proposed reclamation plans include or are likely to include
lakes for flow regulation or areas of "wet reclamation". Many of
these areas will require pumping. Models should be developed
that are capable of handling areas with outlets controlled by
weir structures or pumps.

7.3.4.2 Data and Information Available

ESE (1983), using the SWMM III model, incorporated the
storage lake proposed by PMA into the system modeled. Both
available lake storage and the buffering effect of the lake were
considered. The outlet from the lake was controlled by a weir
with a maximum discharge and a minimum depth below which there
was zero flow. The flood routing model used by Gregory et al.
(1984) has the capability of modeling a controlled outlet
situation. This feature, however, has not been tested on the
extremely small slopes existing on the peatlands.

270

7.3.4.3 Recommended Approach

Modifications to existing models may be used to analyze the
hydrologic effects of pumped outlets on flow rates from mined or
reclaimed areas. The modifications would be required in the
flood routing sections of the models. Inputs to these sections
would come from estimated water losses from fields either on a
per unit area basis or on an areawide basis as, for example,
from a two-dimensional, finite element model of the soil and
water system.

For wet reclamation or lake areas, a short time period
water balance could be used. If inputs to the lake, outlet
relationships as a function of lake depth, and the lake area are
known, a water balance can be determined on, for example, an
hourly basis. This would give the expected outflow from the lake
area over time. The variation in flow rates, as well as total
flows on a monthly or annual basis, could be determined.

Again, data from these studies would provide input to an
estuarine model (see section 7.1), enhancing evaluation of the
effectiveness of storage lakes in reducing negative estuarine
impacts of land drainage.

7.3.5 Wetland Filter Areas for Overland Treatment of Runoff

7.3.5.1 statement of the Problem

The use of wetland buffer areas has been proposed as a
method for the treatment of agricultural drainage water
(Governor's Coastal Water Management Task Force, 1982). The
effectiveness of lagoons and wetland filter areas for removing
nutrients and sediments and reducing fresh water pulsing from
reclaimed agricultural areas must be determined.

7.3.5.2 Data and Information Available

Work in other states (Florida, Minnesota, Maryland and
Massachusetts), primarily on municipal wastewater treatment, is
not very applicable to North Carolina conditions. Previous
research projects in North Carolina (Kuenzler et al., 1980;
Brinson et al., 1981) on nutrient removal and cycling in swamp
ecosystems were conducted on different soil systems and under
different conditions than exist on the Albemarle-Pamlico
Peninsula. A number of farms in eastern North Carolina are using
forested wetlands as treatment areas for agricultural drainage
water. This technique is highly recommended, especially for
areas close to the estuarine receiving waters. Wetland filters
are also an option for mined areas reclaimed to agriculture. At
this time, no established criteria exist for determining the
size of buffer areas, although the Governor's Coastal Water
Management Task Force (1982) has recommended broad guidelines
for the use of filter areas for pumped drainage pending the

271

development of precise design criteria. Further research is
needed on the actual effectiveness of wetland buffers for
treatment of overland runoff. Gilliam et al. (1983) are
currently investigating the hydrologic and nutrient removal
characteristics of two wetland buffer areas. These two areas are
on soil types and in locations considered typical of peatlands
reclaimed to agriculture. Preliminary results from this project
are exected in July, 1984.

7.3.5.3 Recommended Approach

The number of locations investigated in the Gilliam et al.
(1983) project should be increased to include a greater variety
of soil and vegetation types. This project should be expanded to
examine vegetative changes in buffer areas over time and the
effectiveness of buffer areas for the treatment of drainage
water. The relationships between different management practices
in drainage areas (e.g., crop rotations, fertilizer
applications) and the required buffer area specifications should
be investigated. Filtration capabilities of wetland buffers for
other compounds including pesticides and metals (if used) should
also be studied.

Ongoing and proposed studies outlined in this section would
provide input to an estuarine model (see section 7.1),
ultimately enabling resource managers to evaluate the effects on
estuaries of the use of wetland buffer areas for filtration of
drainage waters.

7.3.6 Effects of Peat Mining on Groundwater and Saltwater
Intrusion

7.3.6.1 Statement of the Problem

The effects of drainage systems, peat harvesting and
surface water pumping on the location of the fresh/saltwater
interface in very low lying areas and areas adjacent to
estuaries is not well understood. Specifically this issue should
be investigated in areas where mining could extend close to or
below sea level.
If groundwater pumping is to be required for construction
dewatering or for plant process water, the effect on the
aquifers should be investigated more thoroughly. Particular
concerns include effects of groundwater withdrawals on local
wells and the potential for saltwater intrusion into aquifers.

272

7.3.6.2 Data and Information Available

Theoretically, for every foot of fresh water above sea
level, 40 feet of fresh water is stored below sea level (if
steady state conditions are attained). Therefore, any action
that results in lowering the fresh water table by even a small
amount could be amplified by a factor as high as 40 in its
effect on the groundwater storage. However, the fresh/saltwater
interface is not distinct on the Albemarle-Pamlico Peninsula.
The estuarine water varies in salinity up to almost fresh in the
river mouths (Alligator, Pungo). In addition, the different
hydraulic conductivities of the various geologic layers tend to
obscure the exact location of the interface.
The peninsula is not considered an area of significant
groundwater recharge, based on work by Foutz (1983). He
determined the recharge rate to be less than 0.04 in/year. Foutz
did not, however, consider the lowering of the piezometric head
in the deep aquifers by operations such as phosphate mining in
the region. While such operations would clearly increase the
recharge to the groundwater, the magnitude of the effects would
probably be small. This could be investigated in the modeling
approach suggested below.

Recent groundwater studies by Heath (1975), LBG (1983) and
Foutz (1983), as well as ongoing studies by the U.S. Geological
Survey, have been inconsistent in their estimates of aquifer
depths and properties, specifically, aquifer transmissivities. A
number of studies have been performed, including those mentioned
above, on which improved modeling investigations of the effects
of peat mining operations on the fresh/saltwater interface could
be based (Henry, 1964; Collins, 1971; Shamir and Dugan, 1971).

7.3.6.3 Recommended Approach
The development of a comprehensive three dimensional,
finite element model is proposed. All available data from
pumping and drill logs should be accumulated for the
Albemarle-Pamlico area. Extra drilling should be planned to fill
in any gaps in the data to adequately describe the geologic
profile as well as to resolve any contradictions in the
available data. The model should be flexible enough to address
both small areas of development (less than 10,000 acres) and the
peninsula as a whole.

The U.S. Geological Survey (U.S.G.S.), in addition to
conducting a monitoring program, is in the process of
calibrating a groundwater model to known well data on a regional
scale. There appears to be a good potential for the U.S.G.S.
work to answer many of the regional groundwater questions raised
by this project.

273

7.4 Hurricane Flooding

7.4.1 Statement of the Problem/Data and Information Available

The low relief terrain along the North Carolina coast and
surrounding the state's major estuaries is subject to periodic
inundation by high water associated with onshore wind tides.
onshore winds associated with hurricanes can drive massive
quantities of saline waters into the estuaries, up coastal
rivers and over adjacent low-lying lands. Similar flooding can
occur if floodwaters feeding into the estuaries from upstream
drainage systems are met by onshore winds and are prevented from
draining into the open ocean. The following statements regarding
the effects of such flooding are based on Wilder, Robison and
Lindskov's 1978 study of the water resources of northeastern
North Carolina (Wilder et al., 1978), with only minimal
modification to include peat mining as a possible land use.

The possibility of flooding is an important consideration
in planning land use on the Albemarle-Pamlico Peninsula. As the
low-lying areas are cleared and drained for agriculture, or if
peat is removed, further lowering the ground surface, the
likelihood of major economic losses caused by wind-driven
floodwaters increases. Freshwater flooding would cause immediate
damage to crops and to other land uses, and delays in drainage
would impede recovery. wind tides associated with hurricanes or
other major onshore storms are likely to transport salt water
that will destroy growing crops and may create an undesirable
soil environment for long periods of time after floodwaters have
receded. Under natural conditions the deleterious effects of
inundation by saline waters are minimized because the high fresh
water table impedes the percolation of these floodwaters into
the soil zone. Man-made drainage systems, however, can directly
or indirectly effectively lower this water table. As a result,
during storms floodwaters may infiltrate the enlarged
unsaturated zone (where evaporation and ion-exchange processes
can concentrate the salts in the soil zones) in larger portions
of the land.

In addition, removing peat from large tracts of land will
create extensive depressional landscapes. These depressional
features may hold floodwaters for long periods of time,
depending on pump capacity. Concentrations of salts in soils can
be removed by leaching with fresh water and surficial treatment
with lime and gypsum, but the loss of the use of the land for
agriculturefor one or more years is possible.

Prediction of the frequency with which a given location is
likely to be flooded with water from the estuaries or sounds is
inexact because of the almost infinite number of possible
combinations of wind direction and velocity, shoreline
configuration and fetch, as well as the effects of vegetation
and man-made structures in impeding free advancement of a wave.
Some idea of the severity of the problem can be obtained from
Figure 7.4A, on which are delineated approximate boundaries of

274

wind-tide floods likely to be equalled or exceeded 50% and 1% of
the years. By "exceeded" is meant that inundation of an area at
least as great as that shown is likely every other year on the
average at the 50% probability, and once every hundred years on
the average at 1% probability. These are average frequencies
over long periods of time, and no specific interval between two
consecutive events is implied. A flood with a 1% chance of
occurring in any year will cover a large part of the study area.
However, all of the area with an equal chance of being flooded
at a given frequency will seldom, if ever, be flooded by the
same storm. For example, strong southerly winds may cause
inundation along the northern shorelines of a body of water,
while actually lowering water levels along the southern
shorelines.

It is important also to qualify the accuracy of Figure
7.4A. The boundary outlining the area inundated by a flood with
a 1% chance of exceedance was transferred directly from
flood-prone area maps available from the U.S. Geological Survey.
The lines on the maps are general and are not as detailed as
those appearing on the large-scale flood-prone maps. More
accurate data are available from the Geological Survey and from
floodplain information studies completed by the U. S. Army Corps
of Engineers. The flood with a 50% chance of exceedance was
sketched on the large-scale flood-prone area maps using a flood
stage from 2.5 to 3.5 feet below the flood outlined as having a
1% chance of exceedance. These maps are based only on wave
heights and land elevation, with no consideration of the damping
effect of dense vegetation or man-made structures, and thus the
maps tend to overestimate the extent of inundation.
The National Flood Insurance Administration is currently
working on a series of detailed elevation maps for a large
portion of the North Carolina Coastal Plain. These maps will
include flood boundary lines for numerous intensities of storms.

7.4.2 Recommended Approach
To determine the extent of this problem, the following
steps should be taken:

1. Develop a new series of detailed large scale flood-prone
area maps, based on new land elevations, as determined by
the amount of peat that potentially could be removed from
peat deposits in the region.
2. If the hypothetical removal of peat from a given deposit
increases the susceptibility to flooding, the underlying
sediments should be examined to determine their potential
for floodwater infiltration.

275

3. If certain areas are found to be underlain with highly porous
and permeable sediments that would allow rapid infiltration,
this factor would have to be taken into consideration, either
in the decision to allow mining in the area, or in the
proposed post-mining reclamation plans.

276

0 C.
:A \

164

to 0:
41
J)
\-1 its
to

it
A, /

Vote bole 0
coot
Not/0'es
<1
00,
to

Z Ott 16
W-J

20 30 MIL9S M 0 to 30 NIL

.0 a #0 20 50 *0 50 dIL0109TINS 10 10 40 50 NIL
Figure 7.4A: Area subject to flood inundation caused by wind tides having A, 50% chance of
equalled or exceeded in any one year; B, 1% chance of being equalled or exceed
it Fii/ ."I

in any one year
(from Wilder, Robison and Lindskov, 197

7.5 Natural Area Inventory

7.5.1 Statement of the Problem/Data and Information Available

The North Carolina Coastal Plain contains about one million
acres of wetland. Over the years many aspects of this eCOSYStem
have been studied by the scientific community, yet no
comprehensive picture of a single wetland has ever been
developed. Little is truly known of the biotic and abiotic
components of these wetlands. In addition, the processes that
brought about their origin and development and which now control
their maintenance are poorly understood. Where and how the
wetlands fit into the overall natural scheme of the Coastal
Plain is not known (Richardson, 1981; Ash et al., 1983).

Many of the large wetland tracts in the state, including
the Green Swamp, Holly Shelter, Angola Bay, Hofmann Forest,
Croatan National Forest, Alligator River National Wildlife
Refuge and the Dismal Swamp are either partially or entirely
under state, federal or private conservational ownership. These
areas are at least partially protected, and are generally
readily available for scientific research. The series of wetland
tracts associated with the Alligator River drainage basin in
Dare, Hyde, Tyrrell and Washington Counties is the largest and
most unique, in terms of its origin and complex nature, in the
state. This system, because of its overall size and remoteness,
has been relatively inaccessible for research and, consequently,
is the least understood of the North Carolina wetlands.

Despite the March, 1984, gift of 120,000 acres in Dare and
Tyrrell Counties to the federal government to create the
Alligator River National Wildlife Refuge, much of the land in
the Alligator River drainage basin is still in private ownership
and has been exploited to a much greater extent than the other
large wetlands in the state. In a Sense, it is the exploitation,
and especially the recent development of. extensive drainage
systems and clearing of the land, that has opened the area for
research. In the past ten years, this four-county area has been
the focus of several large-scale overview studies, including
Heath's 1975 work on the hydrology of the region; Daniel's 1978
work on the land use, land Cover and drainage of the area;
Ingram and Otte's 1982 report on the peat deposits located in
the drainage basin; a series of county natural area reports by
McDonald and Ash (1981) for Tyrrell County, Peacock and Lynch
(1982a) for Dare County, and Lynch and Peacock (1982a and 1982b)
for Hyde and Washington Counties; and Lukin and Mauger's 1983
environmental geologic atlas of the four-county area, which
includes maps of the soils, drainage systems, land use and land
cover, based on previous studies and on analyses of aerial
photographs.
The development of this region has been proceeding at such
a rapid pace that the scientific community rarely has the time
or funding to achieve an understanding of the natural
significance of an area before it has been substantially

278

altered. Many questions concerning these wetlands should be
answered before they are irreparably disturbed. The majority of
the wetlands associated with the Alligator River drainage basin
has already been altered to varying degrees. Most, if not all,
of the forested tracts have been cut at least once. Large
portions have been ditched and are being drained in an attempt
to prepare the land for agriculture, silviculture or peat
mining. Roads and drainage canals cross the paths of natural
surface and subsurface water flow and have effectively altered
the water regime in numerous areas.

Large portions of the Alligator River drainage basin now
support either second growth swamp forest or shrub-dominated
pocosin systems. No attempt has ever been made to reconstruct
the original vegetational systems to determine how the wetlands
have responded to alterations by man. It is not known how the
present swamp forests resemble the original forests. If any last
vestiges of virgin forests do exist, they have not been located.
The pocosins are either primary natural systems or secondary
systems that developed on cut-over land. No study, however, has
attempted to differentiate the two. No comprehensive survey has
been undertaken to determine the presence, location or size of
populations of threatened or endangered plant or animal species,
unique habitats, communities or disjunct systems.

The Alligator River drainage basin covers hundreds of
square miles of land. This system contains tracts of wetland, up
to tens of thousands of acres in size, that respond to different
environmental factors. The physical, chemical and biological
parameters of these tracts are poorly understood. It is not
known how attempts at draining, clearing and developing portions
of a single tract will influence the dynamics of the remaining
undisturbed portions. The boundaries of these tracts are not
even accurately delineated.

7.5.2 Recommended Approach

Before an area such as the Alligator River drainage basin
is developed so extensively that it can no longer be considered
natural, an attempt should be made to determine if the basin
contains areas that are in some way unique, in terms of
biological, hydrological, geological, pedological, chemical or
other natural aspects of the system.

A tremendous amount of work would be required to develop a
comprehensive understanding of the natural qualities of the
Alligator River drainage system and, in particular, the regions
that are prime candidates for development. Thus far, essentially
all research has been restricted to areas of easy access,
meaning areas that have already undergone some degree of
disturbance. The areas that are least disturbed and, thus, least
accessible, have been ignored. These undisturbed areas, however,
are the locatio,is in which discovery of natural features worthy
of preservation is most likely.

279

A broad data base, including maps and several series of top
quality, recent aerial photographs that cover the entire
four-county region, is available. PL comprehensive survey should
be undertaken using these maps and photographs to locate areas
of possible interest. Once these areas are differentiated, they
must be analyzed first hand to determine their overall
significance. The following steps should be taken:

1. A team of multidisciplined field scientists with a good
working knowledge of ecology, botany, zoology, pedoiogy,
hydrology and basic geology, and capable of getting
into theseareas, must be assembled.

2. A standardized field inventory and classification system
must be adopted. This would assure that all work is
comprehensive, such that no natural process or feature
is overlooked, and that all work is comparable.

3. A standardized set of criteria for determining the
significance of each area investigated must be
established. These criteria could then be used to
determine the best of what is found.

4. A priority rating system must be developed, including
significance priority, protection priority and
management priorities, in order that sites deemed of
some importance can be fitted not only into the
natural realm, but also into the human realm.

The large size and natural quality of the Alligator River
drainage basin almost guarantees that sites worthy of
preservation will be found. It is possible that all of these
sites will be on land that is either already preserved or on
land, such as peat mining buffer strips, that would be somehow
legally protected. It is probable, however, that numerous sites
will be found on land slated for PE!at mining, timber production
or agriculture. In such cases, the private landowners,
representatives of the scientific community, local, state and
federal agencies, and conservation groups will have to negotiate
the ultimate use of these lands.

280

7.6 Air Quality

7.6.1 Statement of the Problem/Data and Information Available

Expansion of peat mining and processing from the scale of
Scenario #1 (see sections 5.2.2 and 6.4) to that of Scenario #2
(see sections 5.2.3 and 6.4) has @the potential to increase
associated air pollutant emissions by about a factor of eight.
This could lead to transgressions of air quality standards that
are not jeopardized by the lower scale of development of
Scenario #1. The pollutants of greatest concern are particulates
and SO 2'
The initial PMA analysis of air quality impacts of a
peat-to-methanol plant processing approximately 500,000 dry tons
of peat annually (equivalent to the methanol production assumed
in Scenario #1,' Area 1) indicated that there should be no
significant air quality degradation with such an operation (RGH,
1982). However, the potential impact of an eight-fold or greater
expansion (as described in Scenario #2, Areas 1 and 3) has not
been evaluated, largely because of the site specific
requirements of any air quality modeling efforts. Such complex
and expensive modeling is not required by state permitting
procedures nor is it in an operator's self interest, given the
hypothetical nature of such models not tied to specifically
planned developments. Yet without such modeling it is very
difficult to project the air quality impacts of large-scale peat
mining and conversion. Model validation is also currently
lacking.

7.6.2 Recommended Approach

Figure 7.6A shows isopleths of incremental additions to
particulate concentrations (annual averages) in air resulting
from a peat-to-methanol conversion plant processing 500,000 dry
tons of peat per year (Scenario #1, Area 1). The data were
provided by Koppers Company and were used in PMA's air quality
permit application. Fugitive dust emissions from peat mining,
transportation and away from plant storage are not included in
these predictions. Contours for so 2 are similar but about
half the predicted particulate concentrations. In Figure 7.6B,
the incremental particulate concentrations are estimated for an
eight-fold increase in methanol production. The assumption was
made that each of four facilities would emit twice the
particulates of the Scenario #1 plant and that the four plants
were widely spaced as shown. For comparison, the allowable PSD
(Prevention of Significant Deteriorition) increment for
particulates in Class II areas is 19,ag/M .
This cursory analysis suggests that an eight-fold expansion
of peat-to-methanol conversion plants would keep added
particulate increments (and so2 increments) within
permissible levels. The short term (e .g., 24-hour) average added
increments is not, so easily estimated and might approach

281

permissible limits. It would be of value to model air quality
impacts at this level of time resolution if long-term peat
mining impacts are to be assessed. However, because of the
sequential incremental development of peat processing plants and.
the individual separate permitting process for each, no single!
plant would transgress air quality standards because each has art
individually applied PSD increment within a higher absolute air
quality standard. If, however, peat mining in the region is
considered to be a single air pollutant: source (or the
developments of a single owner/operator are so considered), then
allowable increments should not be applied to each single
facility as it comes on line (i.e., a bubble approach is
required). This would require that state regulatory agencies
change the way they evaluate the air quality impacts of'
.facilities that develop sequentially.
More important from an air quality perspective is the
problem of mining itself as a source of particulates. The air
quality model calculations from mining operations on the scale
of Scenario #1 do not predict transgressions of particulate
standards at offsite -locations. However, the emission rates on
which the model calculations are based are highly uncertain and
possibly unrealistically low. There is an urgent need to
determine fugitive dust emission rates under the actual.
conditions proposed for milled peat mining as well as the impact
of any control and amelioration methods. The studies required to
better define these emission rates need not wait for actual
mining to begin. The state Division of Environmental
Management's (DEM) permitting process might require such studies
of the already permitted mining companies without waiting for
post hoc monitoring results after commencement of mining. Test:
plots on First Colony Farms (PMA) permitted property have
already been of use in evaluating the impacts of mining on water
quality. An analogous test system. to evaluate dust emission
rates and mitigative measures would seem to be feasible, at a
reasonable cost, borne by one or more of the already permitted
mining companies.
Because air quality permits are renewable yearly, such
requirements could be readily incorporated in the near future.
DEM's Air Quality Section seems cognizant of these problems and
is encouraging a local monitoring network to evaluate fugitive
dust emissions.
Because of the low height (as contrasted with a processing
plant smoke stack) at which fugitive dust emissions will occur,
their impact is likely to be very local and limited to areas
immediately adjacent to mined lands. As a result, the
contributions to air quality degradation of individual mining
operations will be largely indePE!ndent and non-additive. The
need for multiple source modeling which exists for stack
emission point sources is probably absent.

282

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14
0
Lake
4J
ca
-Phe pj-

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&

Lake
00

J@h..
re

-A

Lake Mattamuskeet

Figure 7-6A: Isopleths of annual average particulate concentrations (ug/m3) Area I
predicted to be added by peat-to-methanol conversion at a plant
the size of that postulated in Scenario #1. Area 2

-7-
IN

:/'W70"iL

@Z
AMN
Lake
4q
helps Cal

-j
VWAFL
L

N-e
--ake
00
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ye,

Lake Mattamuskeet

a 30,000 acres
Figure 7.6Bdsoplethr, of annual Overalle particulate concentrations Are
.,-.-1jn4nA fn tip nolded by rinat.-tri-methAnol facilities of the ff-En
1%-non arres
tlic: tilze of ScenorloV2. Four plonts, each twice the size of the Area 3 26,000 acres
L!ccnPrIo#l plant are postulated to exist at the %Adcly spoced
G'IL(,B chovn. Area 4 13.000 acres

7.7 Solid Wastes

7.7.1 Statement of the Problem/Data and Information Available

Peat on the Albemarle-Pamlico Peninsula contains on a dry
weight basis approximately 6-10% ash. If oxidized completely, as
in direct combustion or in conversion to methanol, peat produces
very large quantities of ash or slag residues requiring
disposal. Peat thus shares many properties with coal in terms of
the volume and composition of its combustion wastes. The output
from a methanol plant producing 60 million gallons of methanol
per year has been estimated at approximately one million cubic
feet of non-hazardous waste per year (PMA, 1983h). Greatly
expanded peat to methanol conversion as described in Scenario #2
(see section 5.2.3) would produce up to seven million cubic feet
of non-hazardous solid waste per year. Such volumes, if disposed
of offsite as planned, would require great expansion of existing
solid waste disposal capabilities on the peninsula.
In order to accommodate the solid wastes generated by a
plant producing 60 million gallons of methanol annually in
Washington County, the county's sanitary landfill would need to
be expanded. Because the landfill is currently located on leased
property and operated by an independent operator, the capacity
for expansion on the larger scale of Scenario #2 is not certain
and must be determined.

Preliminary tests of ash produced during pilot scale!
simulations of peat-to-methanol conversion have shown them to be
rightly characterized as non-hazardous. However, these tests did
not collect the smallest ash particles which are likely to
contain the highest concentrations of some toxic trace elements.
As a consequence, leachates from ash by-products have not been
accurately characterized, with a probable underestimate of
leachable toxic metal concentrations. In addition, most of the
leachate tests were performed at pH levels higher than would be
expected in percolating groundwater or local surface waters in
which disposed ash is likely to be in contact. As a consequencel,
predicted leachable metal concentrations were further
underestimated. Finally, the leachability of phosphorus from
simulated ash was not determined.

The question of leachability is important because leached
metals (or other elements) could enter groundwaters flowing from
the disposal site. In addition, surface water contamination
could result if onsite ash disposal by land application (as a
soil amendment) or as roadfill is utilized as an alternative
disposal approach. Leachable phosphorus in appreciable
quantities would add to nutrient loads in runoff, increasing the
potential for eutrophication of receiving waters. However, based
on evidence derived from coal ashes, the ash contribution to
phosphorus concentrations in runoff is not likely to be large.

285

7.7.2 Recommended Approach

There are thus two potential problems in solid waste
disposal which will need solution beEore large scale utilization
of peat in combustion processes can occur: 1) further
characterization of the properties of leachates of real peat
combustion ashes and 2) selection and evaluation of disposal
sites.

Further characterizations of joeat combustion ashes should.
include analysis of the very finest -ash particles which were not,
collected in PMA's study (1983h) but which will be collected.
(e.g.,, by electrostatic precipitators) in an operational
peat-to-methanol plant. These fine ashes are likely to contain
higher concentrations of many trace elements and toxic metals in
a more soluble form than those sampled by PMA (1983h).
Phosphorus in leachates of these ashes should be measured.
Leaching studies should be conducted at the low pH (3.5 to 5)
occurring naturally in surface drainage and perhaps with the
associated high concentrations of humic and fulvic acids which
can readily complex many trace metals and increase their
leachability from ashes. Leachability under anoxic, low redox
potential conditions characteristic of groundwaters contacting
landfills would also be useful.

These tests could be performed before actual operation of a
peat-to-methanol conversion plant 'began. Once such a plant has
begun operating, real ash and other solid waste could then be
evaluated, providing information needed to assess larger scale
peat mining for methanol production as hypothesized in Scenario
#2.

if direct combustion of peat for thermal/electric!
generation is planned as another end use of mined peat, separate
evaluation of resultant ashes and other solid wastes will be
required, as the ashes produced will likely differ somewhat front
those resulting from the peat-to-methanol conversion process.

Most of these solid waste characterization studies could be
carried out as part of the normal pre-operational permitting
process, without the need for special research programs. They
require, however, an understanding of the chemical environments;
(e.g., low pH and redox potential and high dissolved organic:
content) of probable disposal sites in eastern North Carolina.
Such characterization studies could be incorporated in future
permitting requirements.

Site selection and evaluation for solid waste disposal.
should be given more consideration by both the operatinq
companies and the state regulatory agendies. The ash materials
resulting from peat combustion differ greatly from the usual.
materials disposed of in municipal sanitary landfills. methods
of disposal applied to the latter will not be appropriate for
peat ashes. Coal ash disposal methods would provide a better
model. The potential for groundwater and surface water:

286

contamination by trace elements leaching from buried ashes can
not be evaluated until the ash leachates have been better
characterized, as previously discussed.

The limited vertical topographic relief of the Coastal
Plain, in association with the highly porous sandy soils and
shallow water tables, limits the availability of good landfill
sites. This may create problems if ash leachates are
significantly more hazardous than initially predicted. Certainly
the disposal sites selected should be well characterized in
terms of their appropriateness for this class of solid waste.
Utilization of the Washington County landfill could prove
complicated if leachate problems develop as the liable party
responsible for remedial action is not clearly defined. Is it
the waste producer, Washington County, the private property
owner of the site or the private waste disposal contractor?

Disposal of non-hazardous wastes onsite would clarify this
responsibility issue. The use of solid waste for agricultural
land treatment or roadfill as an alternative to offsite disposal
should be encouraged, along with the necessary studies of the
safety and feasibility of such an approach. This could readily
be incorporated as a requirement in the normal state
pre-operational permitting process.

Moreover, onsite disposal would obviate the problem of the
large volumes of solid waste. It is unlikely that the Washington
County landfill or other municipal landfills in the region have
the capacity to accept the seven million cubic feet per year of
waste that is estimated for the methanol production rate by year
20 described in Scenario #2 (see section 5.2.3.7).

287

7.8 Local Economics

7.8.1 Statement of the Problem

The analysis of the socioeconomic impacts of the scenarios
(section 6.7) must be considered a 'preliminary estimate because
it is based on 1) secondary data currently available for the
area or 2) data developed in studies of mining in other parts of
the country.
In addition, it was not possible within the time and
resource limitations of this project to examine possible
economic losses in the recreation, tourism and commercial and
sport fishing sectors of the economy due to peat mining. In the
section on estuarine impacts, approaches for estimatinq
hydrodynamic and biological impacts are described. if:
harvestable finfish and shellfish stocks and flows are found to
be impacted by peat mining, net economic returns of the
commercial fishing sector may be affected. Economic returns
generated by sports fishermen may also be affected if the
probability of catch affects their expenditures. Recreation and
tourism may be impacted for similar reasons and, in addition,
are tied to the overall level of environmental quality in the
region. Research is also needed on the economic impact of!
wildlife habitat changes on activities such as hunting and bird
watching.
Another concern is the potential adverse fiscal effect of'
peat mining upon some county and city governments in the area
surrounding the peat mining facility. Two basic concerns are:
1) that the benefits of peat mining will not be distributed to
city and county governments in proportion to the costs incurred
(the distribution issue) and 2) that revenues accruing to local
governments from peat mining will lag cost incidence, thus
leading to short-run cash flow problems (the revenue-lag issue).
The demand for governmental services (e.g., water supply,
wastewater disposal, solid waste disposal and education)
generated by the immigration of individuals and families into
the area to work at the peat mining facility (or to serve people
who do) may result in governmental deficits that lead to
increased tax rates or reduced quality of services for current
residents.

The distribution issue arises because new residents may
move into areas that do not benefit from tax revenues generated
by the mining facility. The reve-nue-lag issue arises because
governmental costs incurred while providing additional services
to the increased number of residents must typically be incurred
one or more years in advance of' the receipt of local tax
revenues or state aid designed to pay those costs.. Research
information is needed for city and county governments concerning
(1) revenues that will be generated and (2) expenditures that
will be incurred as a result of the peat mining activity.

288

7.8.2 Data and Information Available

PMA (1983g) has analyzed the socioeconomic impacts of a
peat-to-methanol plant processing approximately 500,000 (dry)
tons of peat per year.

Information in sufficient quantity is not currently
available to model the cost and revenue impacts of peat mining
at different scales on city and county governments. PMA (1983g)
assessed in a general way the adequacy of services and the
availability of excess capacity to serve larger populations in
affected areas. However, cost estimates for services were not
developed. Further, a more detailed analysis is required to
estimate the fiscal impact upon all affected individual cities
and individual counties. This level of detail is essential since
each such level of government must tax residents to obtain
revenues for operation. Any revenue shortfalls or lags will thus
adversely affect current residents. Modeling of these impacts is
possible, however, using data that can be obtained from state,
city, county and industry sources.

Research concerning the potential impacts upon the
recreation, tourism and commercial and sport fisheries sectors.
can utilize existing data as a base case, but will be dependent
upon physical and biological impact information from
hydrodynamic and hydrological modeling efforts (see sections 7.1
and 7.3) and from impact studies of participation in rereation,
tourism and sport fishing. most of the data required are not
currently available.

7.8.3 Recommended Approach

Research required for a more complete analysis of the
socioeconomic impacts of peat mining would include: 1) an
independent evaluation of the socioeconomic data upon which
PMA's (1983g) analyses of impacts were based; 2) an analysis of
the economic feasibility of the peat-to-methanol conversion
process; 3) generation of more detailed data for horticultural
peat and peat for fuel operations; 4) a more detailed analysis
of the effects of plant scale; and 5) the studies of impacts
upon recreation, tourism and sport fisheries that are dependent
upon responses of users to changes in the fishery and
environmental quality. As noted earlier, these impacts are
related to the physical and biological changes that occur but
are dependent upon how users preceive these changes, how they
adjust their expenditures on those activities accordingly or
what they are willing to pay to maintain the "without project"
level of environmental quality and fishery populations.

289

An estimate of the fiscal impact of peat mining upon
city and county governments is also needed. (Estimates of the
overall economic impacts would require a much more comprehensive
model of the regional economy than would be provided by the
fiscal impacts analysis proposed here.)

Two simulation models are necessary. One would simulate the
taxes paid by the peat mining facility (for example, corporate
property, sales and income taxes, and the unemployment tax).
This model would allow for assessing the impact of changes in
these tax rates and for simulating alternative plant production
levels that enter the equation determining local tax revenues.
The model would also be capable of simulating the impact of new,
taxes that might be considered to help generate local funds
needed to serve new residents (e.g., severance taxes on peat.
mined or a tax on the final products of the plant). The focus of
the model would be on the impact of various tax laws on the peat.
mining facility.

The second simulation model would examine the overall.
fiscal impact of peat mining upon various levels of state and
local government in the study area. Revenues to these levels of
government will be a function of their tax rates, their share of'
state revenues determined by state aid formulas and the manner
in which they are impacted by the peat mining facilities'
activities (for example, the increase in their tax base,
population, new students, etc.). This revenue information would
be used as input in the analysis of the net benefits (revenues
less service costs) resulting from peat mining activities. A key,
element in this portion of the analysis would be the need for,
new or expanded services. The focus of this model would thus be
each city and county government in the effected area. The model.
would also allow for estimating the level of tax revenues paid
by employees (e.g., income, sales, property and excise taxes).
Throughout the analysis, assumptions must be made for
certain parameters, for example, the distribution of new
residents attracted by the facility. The models would allow for
easy sensitivity analysis of these factors to estimate the
impact of alternative scenarios.

290

8. LIST OF PREPARERS

David A. Adams, Project Coordinator, CEIP Cumulative Impacts of
Peat Mining Project, and Associate Professor, Division of
University Studies and Department of Forestry, North Carolina
State University, Raleigh (Wildlife, estuarine impacts).

Richard G. Broadhead, Research Assistant, Department of
Biological and Agricultural Engineering, North Carolina State
University, Raleigh (Surface water hydrology).

William A. Campbell, Professor, Institute of Government,
University of North Carolina at Chapel Hill (Law and
government).

Leon E. Danielson, Associate Professor and Extension Economist,
Department of Economics and Business, North Carolina State
University, Raleigh (Natural resource economics).

Richard T. DiGiulio, Assistant Professor, School of Forestry and
Environmental Studies, Duke University, Durham (Environmental
toxicology).

David W. Evans, Analytical Chemist, Duke University Marine
Laboratory, Beaufort (Environmental chemistry).

Judith A. Gale, Editor/Staff, CEIP Cumulative Impacts of Peat
Mining Project, Department of Forestry, North Carolina State
University, Raleigh (Coastal resources management and ecology).

Melvin Huish, Professor, Department of Zoology, and Leader,
North Carolina Cooperative Fisheries Unit, North Carolina State
University, Raleigh (Fisheries biology).

Edward J. Kuenzler, Professor, Department of Environmental
Sciences and Engineering, University of North Carolina at Chapel
Hill (Estuarine productivity and water quality).

Lee J., Otte, Assistant Professor, Department of Geology, East
Carolina University, Greenville (Wetland ecology, peat
resources).

Margery F. Overton, Assistant Professor, Department of Civil
Engineering, North Carolina State University, Raleigh (Numerical
modeling of estuarine hydrodynamics).

Hans W. Paerl, Associate Professor, Institute of Marine Sciences
of the University of North Carolina at Chapel Hill, Morehead
City (Marine and freshwater biology, limnology).

Joseph A. Phillips, Professor and Assistant Director,
Agricultural Extension Service, North Carolina State University,
Raleigh (Soils, agricultural economics).

291

Curtis J. Richardson, Associate Professor, School of Forestry
and Environmental Studies, Duke University, Durham (Resource
ecology, wetland ecology with emphasis, on water quality).
R. Wayne Skaggs, Professor, Department of Biological and
Agricultural Engineering, North Carolina State University,
Raleigh (Hydrology of soils with shallow water tables).

James F. Smith, Coordinator, Coastal Energy Impact Program,
Office of Coastal Management, North Carolina Department of
Natural Resources and Community Development, Raleigh (Peat
mining, coastal zone management, mathE!matical ecology).

292

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10. APPENDICES

10.1 Habitat Type/Land Use Data
(based on Lukin and Mauger, 1983)

Table 10.1A: Scenarios #1 and #3-- Approximate acreages of
peatland by habitat type/land use category
at year 0

Area 1 Area 2
Land Use Category Acres % Acres %

Residential development 0 0 0 0

Roads and rights-of-way 0 0 0 0

Other developed areas 0 0 0 0

Agricultural land 2,848* 18 1,071 15

Deciduous forest 0 0 0 0

Evergreen forest 0 0 929 12.5

Mixed forest 0 0 0 0

White cedar swamp 0 0 0 0

Mixed swamp forest 0 0 71 1

Disturbed land:
a)Transitional/field ditched 8,700 54 1,071 15
b)Ditched pocosin, not
otherwise disturbed 0 0 1,857 26

High pocosin 633 4 1,214 17

Low pocosin 3,005 20 929 12.5

Bay forest 0 0 0 0

Water (incl. canals), marsh 316 2 0 0

Active peat mine 0 0 0 0

Inactive peat mine 316 2 0 0

Total Acres 15,818 7,142

* Not currently in production, but soon to be put into
agricultural production (S. Barnes, First Colony Farms, personal.
communication, 1983).

308

Table 10.1B: Scenario #2-- Approximate acreages of peatland by
land use category at year 0

Area 1 Area 2 Area 3 Area 4
Land Use Category Acres % Acres % Acres % Acres %

Residential development 0 0 0 0 0 0 0 0

Roads and rights-of-way 0 0 0 0 0 0 0 0

Other developed areas 0 0 0 0 0 0 0 0

Agricultural land* 2,700 9 1,200 8 0 0 260 2

Deciduous forest 0 0 0 0 0 0 0 0

Evergreen forest 0 0 1,200 8 0 0 0 0

Mixed forest 0 0 0 0 0 0 0 0

White cedar swamp 0 0 0 0 0 0 130 1

Mixed swamp forest 0 0 450 3 5,460 21 3,640 28

Disturbed land:
a)Transitional
field ditched 9,600 32 300 2 780 3 650 5
b)Ditched pocosin,
not otherwise
disturbed 0 0 1,800 12 0 0 650 5

High pocosin 3,900 13 2,700 18 15,600 60 2,990 23
Low pocosin 13,200 44 7,200 48 41160 16 3,640 28

Bay forest 0 0 0 0 0 0 910 7

Water (incl.
canals)/marsh 300 1 150 1 0 0 130 1

Active peat mine 0 0 0 0 0 0 0 0

Inactive peat mine 300 1 0 0 0 0 0 0

Total Acres 30,000 15,000 260,000 13,000
Difference between acres in agricultural production in Scenarios
#1 and #2 (Areas 1 and 2) is due to the fact that acreage outside
the 4-foot peat thickness contour included in Scenario #1 (Areas 1
and 2) was not necessarily included in Scenario #2 (Areas 1 and
2).

309

WHEAT/SOYBNS.0 BUDGET 74-1
1/83
WHEAT ANn SOYBEANS, DOUHLE-r-ROPPEO: Estimated revenue. operating qKponses, ennual ownership
costs and not revemuo per acre

Category Units Price Quantity Value Your Value

F4-oduct ion,:
itheat au. S 3,60 50.000 S180.00
Soybean su. 5.85 25.000 146.25
Total Receipts $326.25

Operating Inputs:
Lime applied Tons $26.00 0.333 S 8.66
Seed 'wheat Bu. 8.00 1.500 12.00
5-15-30, bulk Cwt. 9.33 4.000. 37.32
Dry fertilizer spreading a Acre 5.50 2.000 11.00
33.5% Amonlum nitrate, bulk CW11. 10.50 1.791 18.81
Post-emerge herbicide Acre 2.59 1.000 2.59
Soybean seed Su. 10.50 0.800 8.40
Soybean-Inoculant Bu. 1.85 0.800 1.48
Pro-emerge bherbicide Acre 17.02 1.000 17.02
Nomatlcld* b Acre 34.05 1.000 34.05
Insecticide. b Acre 3.47 1.000 3.47
Insecticide- applied by plane Acre 4.50 1.000 4.50

Tractor fuel and lube cost Acre 6.69
Tractor repair cost Acre. 2.59
Machinery fuel and lube cost Acre 6.36
Mach'nery repair cost Acre 9.57
Total -perating cost S184.91

Returns to land. labor, capital,
machinery, overhead, and management $141.34

Capital cost:
Annual operating capital S 0.14 S 55.143 S 7,72
Tractor Investment 0.14 39.026 5.46
Machinery Investment 0.14 189.571 26.54
Total Interest charge S 39.72

Returns to land, labor, machinery,
overhead, and management $101.62

Ownership cost: (Deprociatlow, taxes. Insurance)
Tractor 001. S 4.42
Machinery 001. 29.18
Total ownership cost $ 33.60

Returns to land, labor, overhead, and
management S 68.02

Labor cost-
Machinery labor W . S 4.25 2.972 S 12.63
Total labor cost 12.63

Returns to land, overhead, and
management S 55.39

Prepared by R. E. Jarrett, E. J. Dunphy, Crop Science Extension Soecialls #i. in! D. F. Neu-nan, Ex-enslon
Economist.
aincrease n1trocisn application by 20 pounds in Coastal Plain.
bAn i-secticija and nematIcide I not I I ke I y I)e , ee lm@,! i 1 fne

311

OVEAT AND SOISCANS, DOVOL I-C40PO13, sstimatod 01*.onus. Oroorefing Costs fad lict 010.44vo
,a, Ac,*.
L I fit JAN FES WAR APR MAI' JUL AUG w
PROOJC?11@11 "webor w Units
I "%*a- 0.0 0.0 0.0 0.0 0.0 53.0 0.0 0.0 0.0
2 soyhes"s 0.0 C . C 0.0 0.0 0.0 0.0 0.0 0.0 0.0
OCT Nov DEC PRICE WE I UNIT CODE ITEM CODE TO C"
koob*r a# Units
I Wheat 0.0 0.0 0.0 3.60 a. C1 2.00 64.00 2.00 0.4
2 sovile4"s 0.0 25.00 0.0 5.05 0. C 2.0@ $6.00 2.00 0.0
JAN -to MAN APR 14A T JUN JUL AUG sa;
Ogereti-g Imouls Rato/11"IT
I time. Apollo# 0.0 0.0 0.0 0.0 0.0 @.C 0.0 0.0 0.0
4 load on**# 0.0 0.0 0.0 0.0 0.0 @.a 0.0 0.0 0.*
5 5-15-30. setit 0.0 0.0 0.0 0_7 0.0 1: . Z0.0 0.0 0.0
I Dry 0, : 0, 11 -30 0.0 0.0 0.0 0.0 0.0 0.0 0.0
1 33., a .79 0.0 0.0 0.0 0.3 0.0 0.0 0.*
a Post E-O'Se Herb 0.0 1.00 0.0 0.0 0.0 3.0 0.0 0.0 0.0
9 Soybean loud 0.0 0.0 0.0 0.0 0.0 0.0 0.60 0.0 0.0
10 SoIrbooft laocwl 0.9 0.0 0.0 0 0 0.0 *.a 0.40 0.0 0.0
It Pro-jeorge Herb 0.0 0.0 0.0 0:0 0.0 0.0 1.00 0.0 0.0
12 monsticife 0.0 0.0 0.0 0 0 0 0 0 0
13 I.SeCTIC149 0.0 0.0 0.0 0:00 ON 0:0 0,10 OU0. 0:0
14 Insecticide Allot 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.00 0.0
OCT, Now DEC P.M I WE I GoT U41T CODE ITEM CODE To C111
O;Oroti-g Inputs mote/Umit
Lim. 4,011*4 0.33 0.0 0.0 26.00 0.0 3.03 229.00 0.0
4 is*: Wheat 1.50 0.0 0.0 4.00 0.0 2.50 174.00 3.00 0.0
5 S-I'-30. Built 2.00 0.0 0.0 9.)3 0.0 16.00 209.00 3.00 0.0
6 Dry Fort Sor*od 1.00 0.0 0.0 5.50 0.0 7.00 230.00 3.00 0.0
7 33.' 101 0.0 0.0 0.0 10.50 0.0 16.00 225.00 .1.00 0.0
a Post :merge 4606 0.0 0.0 0.0 2.59 0.0 7.00 236.00 3.00 0.0
I $*wood* sago 0.0 0.0 0.0 10.50 0.0 171.00 5.00 0.0
10 Sov*eo- 1.0401 0.0 0.0 0.0 1.65 0.0 Z.00 275.00 3.00 0.0
11 Pro-tworge Herb. 0.0 0.0 0.0 17.02 0.0 1.00 256.00 ).So 0.0
It 10004ticide 0.0 0.0 0.0 34.05 0.0 7.00 266.00 3.00 0.8
13. $msettl:140 0.0 0.0 0.*
If fa%.C- 0.0 3.47 0.0 7.00 240.00 3.00 0.0
0.0 0.0 4.50 O.D 7.00 269.00 3.00 0.0
Monthly swommory ot nocelpto and topit*$*$
"114mv #M4tj1.' JAR, or CIS *A* APR "T Jun J UL AUG SEP OLT Now DEC TOTAL
Tevet mocelpts, AGOw G.'* 0.0 0.0 0.0 0.0 16*.66 0.0 0 0 .0 146.29 0.0 126.25
?**a$ 1&VOAs*O. Agen, 0.0 29.00 0.0 0.4 0.0 7.40 67.55 ):9, X601. 9.09 0.0 194.9t
44111tvi'"S to Load. Lobar. Capital. Mitefitiory, Ov*rhooo. Risk. *ad "&*4q&amxt 141.34
ANOUAL CAPITAL 001. 0.0 21.92 0.0 0.0 0.0 3.04 22.63 1.91 0.0. 5.62 0.0 0.0 55.14
Labor Monte
0.0
MACHIMIRT LASOR He 0.0 0.32 0.0 0.0 0.4 0. 00.0 0.0 0.59 0.48 0.0 7.97
mockinory Flood and variable costs Per Near TOTAL
MACHINE con 01PR INSUR TAX TOTAL FIRED REPAIR FUEL L US VARIAGLI INV 011IM"It
,rector (5) 52.44 0.25 0.13 3.19 1.87 4.19 0.63 6.69 3.9& 1.00
PIC%up True% 17 2.42 0.10 0.05 2.58 t . 30 3.44 0 12 5.26 1.80 1.00
TP vCft 16 4.7) 0.24 0.15 5.11 S. 30 3.04 0.46 0.79 4. 1& 1.00
Groin Console SO 20 34.60 1.96 1.16 37.74 7. 25 6.67 1.00 14.93 34.61 0.25
Tmodoe Disc 39 3.67 0.23 0.14 4.25 1.01 0.0 0.0 1.01 4.05 0.17
$OCT. Korea. as 0.49 0.03 0.02 0.53 0.12 0.0 0.0 0.12 0.90 0.17
Grain Drill so 7.40 0.44 0.20 8.12 1.91 2.0 0.0 1.91 7.71 0.22
SlItever Td 1104A to 0.69 0.03 0.02 0.70 0. 61' 0.0 0.0 0.67 0.5? 0. 1 a,
Coro Plo.tor/ATT 6.11 0.36 0.23 6.70 a. 241 0.0 0.0 4.20 6.36 0.32
ftrover Tic 116 71 0.65. 0.03 0.02 0.70 0.61, 0.0 0.0 0.67 0.37 0.32
Roll Culti.ator 63 5.06 0.10 0.tl 3.35 0.331 0.0 0.0 0.35 3.20 0.22
Soro*ttp To 110 71 0.611 0.03 0.02 0.70 1.44 0.0 0.0 1.80 0.37 0.22
ITEM Times LA1100k MAC"INS FUCL-OIL-LVW@ FIX90 COSTS
80. MAT6 W1111 HOURS HOURS 41PA&A PER ACINS 1111111 ",111s
Sprayer To ItI524- 9.70 Orell 1.00 0.190 0.164 31 1.49
Tend% I* Fee 0.10 0.120 0.100 0.22
1.:4
Toodom also 5.30 Jun 1.06 0.204 0.162, 1 7.11
SOOT "*"*a Is Jun* 1.00 0.0 0.109 0.01
Grillm C408166 211`_ Jun 1.00 0.303 0.293 3.77
True* to JIM 0.23 0.300 0.294 2.20. 2.31
Coe* Ptestior 2.46 JUL 1.00 0.595 0.329 3.78 6
loroyor TO 110"@ 71 JUL 1.00 0.0 0.325 0.22 0:..
sell CVITI.otdf@,. S. JUL 1.00 0.262 0.217 1.67 3.12
Stealer TO 1111 ?2, JUL t.00 0.0 0.217 0.40 0.29
to JUL 0.10 O.Izo 0.100 13.80 O.S?
T#-Aoo Disc 2.3V OCT 1.00 0.204 0.169 1.41 2.72
$act we,,** 49, OCT 1.00 0.0 0.169 0.5Z 0.11
i;,ralft Drill 5.90 OCT 1.00 0.264 0.218 2.02 5.17
Pickup T,.cm 11 OCT 0.10 0. 120 0.100 :.93 0.44
Gee$. Cousins so 20 Nov t.00 0.301 0.213 3.77 10.29
truck to toy 0.15 0.1so 0.150 1.112 -1.39
TOTAu 2.972 3-4 4 25.61 65.56

VHtAT 414D SOYSIANS. VOUSLE-CROPPED: Ittect of 'er,109 4-04 Of Production 01 has*
and soybeans a. -*I to lend. o.er"ood a.d
(-Ifft -%sot 91;C6 At 13.60 00, 606hal old lo.boe- 014C. a'
ll.&$ per bushol)

Rat* ot prodmiatieft Rate of Production of ."*S,
ot soybean* Total cost for sees I -
11 40 Ov. 10-b.. 50 D..
ZO $270.86 S -9.66 1 .6.14 1 62.14
25 .270,66 19.39 55.!o
)0 84,6A 1-1.44

312

CORN. I I 5@'DGZr 70-1
'/83

CORN (COASTAL -nz @;v! revenue, ooerat I nq expen-Fe-, costs
-t-@,enue per scre

Category I-% Pr;ce '-uart I ty Va. J@'

Production:
Corn a
S 2.26 115.000 S2
Total Receipts

Operating Inputs:
Lima applied S26.00 C.333 1 i@'45
SOW corn 1.26 16. 0111c@
0-0-60, bulk c6t. 8.75 2000 7, 5,0
Dry fertilizer soreacinc 5. 5G. !.coo
30S nitrogen solution 7.16 4.,57C
Pro-emorge herbicide
Post-emergo herbiciae 12.
Insecticide and nematicide A,:-e 0
Liquid nitrogen, custom apof;ed Acre 5.25 2.00 "O."j-
Tractor fuel and lube cost kcre C.64
Tra&or repair cost Acre 2.12
Machinery fuel and lube cost Acre 4.06
Machinery repair oost Acre 6.72
Total operating cost $150.05

Returns to land, labor, capital,
machinery. overhead, and ffenacement S109.85

Capital cost:
Annual operating capital S 0.14 $ 64.641 S 9.04
Tractor Investment 0.14 31.890 4'e'c
Machinery Investment 0.14 123.338 17.2-1
Total interest charge Z0.77

Returns to land, labor, mach;rerv,
overhead, and management S

Ownership cost: (Depreciation, taxes,
Insurance)
Tractor Doi. S 3.@'
Machinery Doi. 19.03
Total ownw-shlp cost S 22. 1-54

Returns to land, labor, overhead, and
management S 56.44

Labor cost:
Machinery labor
S 4.25 2.188 S f". K
Total labor cost 2.188 1

Returns to land, overhead, -n,@
management

Prepared by J. R. Andersc@r-, --ir s I on Speci a I I st anL' D,
aBased on $2.55 orice, 2.1% 2.5% orice dlsccvn't i-o-
over 75.5%.
bNitrogen level is

313

coos. 12
CORM (COASTAL Aft[ASI: &&Ifoasted as ... us. Operating E.00-sox. Annual 0.00rahop Costs See age A9.1.0*0
For ACro.

L INS JAN fee MAa APR WAY JUN JUL A us S a I,
PRODUCTION Number Of Units
I Care 0.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 115.00,
OCT NOV DEC PRICE WE ! GAT UNIT coal ITEM coot TIO C"
Number at Unit&
I COP& 0.0 0.0 0'0 2.26 0.0 2.00 62.00 2.00 0.0
JAN Fee WAR APR MA JUN JUL Aloe SEP
00*rstlag loomts RAT*/U.11
I Lima. Applied 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.10 0.0
3 flood Car. 0.0 0.0 0.0 16.00 .0.0 0.0 0.0 0.0 0.0
4 0-0-60. Sets 0.0 0.0 2.00 0.0 0.0 O.C 0.0 0.0 0.0
I Ory Fort Spread 0.0 0.0 1.00 0.0 0.0 0.0 0.0 0.0 0.0
4 309 US? Solut 0.0 0.0 0.0 2.7% 1.97 0.3 0.0 0.0 0.0
? Cell ADS LIS Rog 0.0 0.0 0.0 1.00 1.00 0.0 0.0 0.0 0.0
a pro-1.0'a Herb 0.0 6.0 0.0 1.00 0.0 0.0 0.0 0.0 0.0
9 post 1**r0mkerb 0.0 0.0 0.0 C.0 1.00 0.0 0.0 0.0 0.0
to lasoct a asset 0.0 0.0 0.0 1.00 0.0 0.0 10.0 0.0 0.0
OCT Nov DEC PRICE lot I 614T UNIT coot ITEM CODE To a
overatial Inputs Naf*/UftIt
2 Liao. A091110411 0.33 0.0 0.0 26.00 0.0 3.00 229.60 3.00 0.0
I Small Cars 0.0 0.0 0.0 1.26 0.0 12.00 171.00 5.00 0.0
4 0-0-60. sulk 0.0 0.0 0.0 8.79 0.0 16.00 204.00 3.00 0.4
I Dry Fort Spread 0.0 0.0 0.0 1.50 0.0 7.0* 230.00 1.00 0.0
6 301 414 $*out 0.0 0.0 0.0 7.16 0.0 16.00 226.00 3.00 0.0
I Cut Apo L14 Olt 8.0 0.0 0.0 5.25 0.0 7.00 23?.00 3.00 0.0
6 pro-Clsere War& 0.0 0.0 0.0 14.48 C.0 7.00 234.00 3.00 0.0
I Pegg [more* Herb 0.0 0.0 0.0 12.07 0.0 7.00 216.00 3.00 0.0
I* lasgat a Mae&? 0.0 0.0 0.10 9.20 0.0 7.00 250.00 3.00 6.0

Neetitly summary of Receipt# and twoosses
CATIOMI UNIT Jan ?1111 SlAn APR MAY JUN JUL AUG SEP OCT 001 DEC TOTAL
Uget 404010*0 Acre 0.0 0.0 0.0 0.0 0.0 0.0 0.0 - 0.0 Aq.,10 0.0 0.0 0.0 299.90
Total Into***$ Acre 0.0 0.0 26.94 71.53 .31.07 0.0 0.0 0.0 8.6.7 12.21 0.0 0.4 150.05
1111011fores. to Load, Labor. Ceallifel. nesslaerl, Overhead. 111!sk. $ad 1184020meat 109.69
ANNUAL CAPITAL 001. 0.0 0.0 13.29 29.61 10.36 0.0 0.0 0.0 0.0 11.19 0.0 0.0 $*.&a

Labor Requirowoots by meAth
11111ACNIOCAT LA4OR Me 0.6 0.6 0.33 0.36 0.0 0.0 0.0 0.0 0.90 0.51 0.0 0.0 1.19

Mockl4ory Fired *ad Variable Costs Fee "out YOTAL
MACM101 coal DCPQ lnsun TAX TOTAL FIXED REPAIR FUEL LUS VARIABLE INT maPTINE
Tractor 44) 4 1.33 0.19 0.10 2.62 I.S4 3.67 0.55 9.76 3.24 1.00
Treetop (#1 9 4.90 0.3# 0.20 5.12 3.02 $.1111 1.02 10.80 6.35 1.00
Pleksig Track 17 2.42 0.10 0.06 2.94 1.30 3.44 0.92 5.26 1.60 1.00
Truck Is 4.73 0.24 0.15 $.If 9.30 3.04 0.46 8.79 4.14 1.00
Coralsess cooblao 21 39.04 2.01 1.17 34.21 T.'jS 1.24 0.79 13.41 35.11 0.32
Teades also at 7.60 O.dS 0.28 0.21 1"92 0.0 0.0 t.92 7.79 0.10
olpoor-eed#or 33 2.S4 0.17 0.11 !1.12 0"72 0.0 0.0 O.?z 2.99 0.10
Care Pf W/Now $Roper 46 6.99 0.41 0.26 7.59 4.81 0.0 0.0 4.81 7.14 0.20
$Iran was Is 1.11 0.06 0.04 1.22 0"40 0.0 0.0 0.40 1.15 0.33
Iyals TIMES LAIION MACHINE FUEL-OiL-LUG. FIXCO COSTS
OPERATION NO. OAT9 OVER HOURS HOURS REPAIR PER ACRE PER ACRE

Tenses Oltle 9.41 OCT 1.00 0.117 0.091 1.35 2.74
seek Was 4.93 OCT 1.00 0.396 O_sz? 2.21 2.86
Tangos of$* 9.41 SAN 1.00 0.117 0.097 1.35 2.76
11111pper-solloldor 9.33 111111111 1.00 0.213 0.176 2.23 3.29
Core Pi W/Relp Sasser 4.46 APR 1.00 O.Z4Z 0.200 2.23 4.23
plesep Treat 17 APR 0.10 0.120 0.100 0.53 0.44
Coroolsowe Casiblow 21 sap 1.00 0.362 0.316 4.27 23,35
Treat IS sap 0.10 0,600 O.soo 4 40 4.62
TOTAL 2.187 1.813 'F.LT 44.37

CORE (COASTAL PtA$N--"*@ILLOUG AREAS); Collett of varying rates of Production $Ad
procoo 00 wat to food. overhead and management
Rate of preduatfoR Total cost for ogle I - fee Oar bushels
1 1111.621 $2.26 1 32.71
as be. $204.01 S -62.41 1-27.21 1 8.70
Its 6". 212.76 - 3.46 4 7.,14 )8.59
140 be. 222.11 12.49 94.09 51.09
#base# sees to percent moisture coatoot at harvest, :.5 porcoof price discount
for sea& P#reoftt moisture Star 19.9. *we Prices of 12.05, 12.55 and 1).05

314

W-HEAT!SOYBNS.0 9UDGET 74-1
1/83
WHEAT AND SOYBEANS. DOUR@Lf -CROPPED: Estlwated revenue, ooorating expenses. annual ownership
costs and not revenuo per acre

Cateno-y Units Price Quantity Value Your Value

Production:
'01heat su. $ 4.00 50.000 SISO.00 200.00
Soybean au. 6.75 30.000 1 146.25 202.5
Total Receipts S326.25 402 - 5

Operating Inputs:
Llme applied Tons $26.00 0.333 $ 8.66
Seed wheat su. 8.00 1.500 12.00
5-15-30, bulk 9.33 4.000 37.32
Dry fertilizer spreading a Acr 5.=O 2.000 11.00
33.5% Amonlum nitrate. bulk 10.50 1.791 18.61
Post-emerge herbicide Acre 2.59 1.000 2.59
Soybean seed SU. 10.50 0.8D0 8.40.
Soybean Inoculant Bu. 1.85 0.13W 1.48
Pre-amerge bherbicide Acre 17.02 I.DDO 17.02
Nematlclde b Acre 34.05 I.DD0 34.05
Insecticide b Acre 3.47 1.000 3.47
Insecticide applied by piano Acre 4.50 1.000 4.50

Tractor fuel and lube cost Acre 6.69
Tractor repair cost Acre 2.59
Machinery fuel and lube cost Acre 6.36
Mach'nery repair cost Acre 9.57
Total peratIng cost $184.91

Returns to land. labor, capital,
machinery, overhead, and management S217.59

Capital cost:
Annual operating capital S 0.14 S 55.143 S 7.72
Tractor Investment 0.14 39.026 5.46
Machinery investment. 0.14 189.571 26.54
Total Interest charge S 39.72

Returns to land, labor, Machinery,
overhead, and management s177.87

Ownership cost: (Depreciation, taxow@.Insurvnce)
Tractor Doi. S 4.42
Machinery DOI. 29.18
Total ownership cost S 33.60

Returns to land, labor, overhead, and
management S144.27

Labor cost-
Mach7mery labor Hr. S 4.25 2.972 S 12.63
Total labor cost S 12.63

Returns to land, -,)verhead, and
manage-ment s131.65

Prepared ty F. jarrett, E. J. Dunphy, CroD Science :-xTension SDeclal!sts, nnj ). F. Neuman, @x-t@,nsion

@;:@Ilcat)on oy 20 oounds In Coast:! :'lair.
will not likelv -)e in t')e
A

315

SOYBE AW, 7 3 -
)/83
S 0 YP f, AL .4, Ax:)nnsFos, o-an+*rs- C01-TS M-,@! no@ acre

a Un I *S Oue r - i Vn u t- 'our Yz 'ue

Pr U Ct i L n
.zoY-)e--!n Bu. S 5.85 3 5. @2-%. 5
Tota! Racelp-,,s

OperaTing InDUI'-cl
Soybean seec au. 1 C. 5 J
S 8.4
0-10-20, Cwt. 11.55 3. ;"n,'' 19..65
Dry fertlii:q.- -n:@-eadiig i.,
Acre 5.50 03 5.50
Lima appilec Tons 26.00 -4 -
8.66
soybeAn Inoc-*a@' 9U.
Pro-emerae ne-t!: -,e Acre
02
Post-emeroe '@erni:;-e Acre !4.-6
Nematicide -aterial Acre
Insectic1cle Acre
Insecticide appliee by air Acre 4.5@)

Tractor fuel and lube cost Acre 6.49
Tractor repair cost Acre 2.95
Machinery fuel and lube cost Acre 3.71
Machimery'repeir cnst Acre 6.84
Total operatlnq cost S137.48

Returns to land, labor, caDital,
machinery, overnea:% and management S E7.217

Capital :ost:
Annual wera@;ng :zpital S 0.14 S 60.3!7 S 8.44
Tractor Inves-mgnt 0.14 44.271 6.2C
Machinery lnves-@en- 0.14 128.707 18.02
Total Interest cmarp S 32.66

Returns to land, laDor, macNinery,
overhead, and management S 54.61

Ownership cost: (Deoreclation, taxes, Insurance)
Tractor Doi. S 5.011
Machinery Doi. 19.78
Total ownership cost S 24.79

Returns to land, laoor, overhead. and
management S -^.32

Labor cost:
Machiqerv tanor Hr. S 4.25 S
Total labor cos, S

Returns to lijr@, @@verneall, and
menagemenT

Preparea try E. Crop S@Iamce Extension Ano

aAn i nsect i c I -ic- in@- --a-Ta-r 1:@; ie. are not I I ke ly to oe nee;',(wn

316

WHEAT!SOYBNS.0 9UDGET 74-1
1/83
WHEAT AND SOYBEANS, DOUR LE -CROPPED: Estimated revenue. operating expenses. annual ownership
costs and not revenue per acre

cateno-Y Units Price Quantity Value Your Value

Production:
Wheat Bu. $ 4.00 50.000 S180.00 200.00
Soybean su. 6.75 30.000 1 146.25 202.5
Total Receipts $326.25 A02--U

Operating Inputs:
Llme applied Tons S26.00 0.333 $ 8.66
Seed wheat su. 8.00 1.500 12.00
5-15-30, bulk Cwt- 9.33 4.000 37.32
Dry fortll)zer spreading a Acr 5.r.0 2.000 11.00
33.5% Amonlum nitrate, bulk 10.50 1.791 18.dl
Post-emerge herbicide Acre 2.59 1.000 2.59
Soybean seed au. 10.50 0.800 8.40.
Soybean Inoculant Bu. 1.85 0.800 1.48
Pre-amerge bherbicide Acre 17.02 1.000 17.02
Nematicide b Acre 34.05 I.Ow 54.05
Insecticide b Acre 3.47 1.000 3.47
Insecticide applied by plane Acre 4.50 1.000 4.50

Tractor fuel and lube cost Acre 6.69
Tractor repair cost Acre 2.59
Machinery fuel and lube cost Acre 6.36
MachInery repair cost Acre 9.57
Total peratIng cost 1184.91

Returns to land, labor, capital,
mach I nery, overhead, and managewient S217.59

Capital cost:
Annual operating capital 1' S 0.14 S 55,143 S .7.72
Tractor Investment 0.14 39.026 5.46
Machinery Investment. 0,14 189.571 26.54
Total Interest charge S 39.72

Returns to land, labor, mach I nery,
overhead, and management $177.87

Ownership cost: (DWeelation. tamm,'-Ansurance)
Tractor DOI. S 4.42
Machinery Doi. 29.18
Total ownership cost S 33.60

Returns to land, labor, overhead, and
management S144.27

Labor cost-
Mach"nary labor Hr. $ 4.25 2.972 S 12.63
Total labor cc*t $ 12,63

Returns to land, nverhead, and
M,nagernent s131.65

Prepared* ty 71_ 7. jarrett, E. J. Dunphy, CrOD Science Ex-r;msion S",clal!sts, inj F. Neuman, @x-Ension
Econ-)Tlc.t.
-_@:@llca!'Ion Dy 20 oounds In Coasta
.111 not llxeIV in t-,e

315

SOYBE -NNS 73-
1/83
-:t nq Aq:3irnses @mntirs- 1; cosrs an@! rto@ re@,-*@,--,- ,,orr acre
0 Y 14 @. A .4,

a Un 1 #5 73 Ouer - I-, "in u@- ',:)L:r vt 'ue

Pr =4 L c-t L@n
a '- Y -'Ie Bu. 5.85 3t. @0:1 @5
Tota! Rftcelp's

Oper3flng
Soybean seso au. S! C. 5@)
S 8.4
0-10-20, zu:,@ Cwt. 1,.55 3. @'O 19 .65
Dry tert I I i zs@- :@z-ead i ng Acrs 5.50 1 . 'C"' 5.50
Ume appilec Tons 26.00 :".3113 8.6A
SoybeAn Inoc-'a- Bu. 1.65 G.En-'. !.45
Pre-emerqe ne-t@: ie Acre !7.-"2
Post-emerae 'iern;::1e Acre 14.-5
Nematicide -4TS,-10' Acre
Insectic'Ide Acre
Insecticide applied by air a Acre 4. C;

Tractor fuel and lube cost Acre 6.49
Tractor repair cost Acre 2.95
Machinery fuel and lube cost Acre 3.71
Machinery'repair cost Acre 6.84
Total operatinq cost 1137.4@

Returns to land, labor, capital,
machinery, overnea:l, and management S E7.217

Capital :ost:
Annual wera@;nz sapital S 0.14 S 60.3!7 S 8.44
Tractor Inves-nent 0.14 44.271 6.2C
Machinery Inves-nen' 0.14 128.7107 18.02
Total Interest cnarge S 32.66

Returns to land, labor, mac0iinery,
overhead. and management S 34.61

Ownership cost: (Depreciation, taxes, Insurance)
Tractor (301. S 5.0,
Machinery Doi. 19.78
Total ownership cost 1 24.79

Returns to lana, laoor, overhead. and
management

Labor ccst:
Machiiary tanor Hr. S 4.25 9.
Total labor --os'

Returns to tani, :@varneald, And
menacemesnT

Preparea try E. Crop 'Sc-lence Extension

aAn I nsect i 1:ip in z --ama'r I i ce. r e- not I I ke I y tr,' rx- neec' eo :.@l

316

O.Re-A-10 Cos"' 0.0 140, *a-**.* Per Acre.

JAN rfs MAN APIII "at JI.Q UIL 4UG 310,
-QODJC,11)k Number of J11fli
3.0 0.0 0.0 0.1) a..) 0.4 0.0 0.0 0.0

OCT Nov DEC PR ICE WE IG.T UNIT CODE I ?IN C')OI -P Cm
MWelter at U. I to
sovase. 0.0 35.00 0.0 5.69 0.0 2.00 lla.-Io 2.03 0.0

JAN PCs mAR pQ .44, UK JUL SIP
@Oors-lnj 4214/u.11
2sovagan Seed 0.0 0.0 2.0 0.0 0.63 0.0 0.0 0.0 0.0
3seed Tres'04.1 0.0 0.0 0.0 G..1 CAD 0.0 0.0 0.0 0.0
40-10-20. Balk 0.0 0.0 0.0 3. 0.0 o. a 0.0 0.0 0.0
5Dry per, spread 0.0 0.0 0.0 1.0- 3.0 0.0 0.0 0.0 0.0
6Liao. &&*fled 0.0 0.0 0.0 0.0 3.0 0.0 0.0 0.0 0.0
7P"-E.Org Herb 0.0 0.0 0.0 0.0 1.00 0.0 - 0.0 101 . 0 0.0
aPost Emerge Nor@ 0.0 0.0 0.0 0.0 0.1 1.00 0.0 0.0 0.0
9N6849-cide 0.0 0.0 0.15 0.0 1.00 0.0 0.0 0.0 0.0
to 1094mricide ----- 0.0 0.0 0.0 0.0 0.0 0.0 C.0 1.00 0.0
I t..goellelgo AV 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.00 0.0

OCT Poor DEC PRICE WE I Gody JNIT Coot ITEM CODE To coo
opere-1.2 '-pays as-9/10.11
2savvese Seed 0.0 0.0 3.0 10.50 0.3 2.00 177.06 3.00 0.0
3Seed Treatment 0.0 0.0 0.3 1.05 0.0 Z.00 262.00 3.00 0.0
41-3-20. awl% 0.* 0.0 0.0 6.53 O.C 16.00 202.00 5.00 0.0
IOrr Fort Spread 0.0 0.0 0.0 5.10 3.0 7.00 Z30.30 3.00 0.0
6Lima. Applied 0.0 0.33 0.0 !6.00 .0 5.00 229.CO 3.00 0.0
7P`,o.(adrq Worb 0.0 0.0 0.0 17.02 0.0 1.00 2id.00 5.00 0.0
IPCs, :.*ego Nero 0.0 0.0 0.0 14.76 0.0 1.00 25G.00 3.00 0.0
9noeo?lcldo 0.0 0.0 0.0 34.05 0.0 7.00 206.00 3.00 0.0
10 1006491clas, ----- 0.0 0.0 0.0 3.47 0.0 7.00 240.00 3.00 0.0
I II.Secticide 40 0.0 0.0 0.0 4.50 0.0 7.00 269.** 3.00 0.0

Mentrily Sumvierv we Itocelpts said favatoi*es
CAfjGOQV- UNIT JAM r I& ItAx APO 041 JUN JUL &fse sip OCT Nov DEC TOTAL
Tees$ PlOsaWs, acrar 0.4- 6.0, O.S. 0.0 0.0 0.0 0.0 . 0.0 *.6 0.0 204.75 0.0 204.75
Tovat 1.060996 Acre 0.0 0.0 0.0 21.6% 64.04 17.70 0.0 7.97 0.0 0.0 14.60 0.0 137.49
Alorural ft Laos. Leber. C&*4tai. slecol-ary. Overhead. Risk. ape Management 67.20

4%mUa@. CAPITAL Doi. 0.0 0.0 0.0 16.72 34.22 7.39 0.0 1.19 0.0 0.0 0.5 0.0 60.31

Lobar 0144.110-9-12 by MORI'"
MACRIN91111 LABOR air 0.0 0.0 &.0 0.116 0.44 ').is 0.0 0.0 0.0 0.0 0.62 0.0 2.30

Nechiftery F1.64 end variant* Costs 00, Now, TOTAL
dAC-INI coot DIP% I '@SUN TAX TOTAL FtxfO REPAIR FUEL L UO VANIARLI I fit nNITING
Tracts, lot 6 j.?z 0.30 'j. 1 1 4.!6 :.46 4.72 0.71 7.89 5.12 1.00
pickup Truck 17 2.42 0.10 0.06. 2.58 1.10 3.44 0.92 5.26 1.80 1.00
True% is 4.73 *.Z& 0.11 5.11 5.30 3..14 0.49 0.79 4.14 1.00
Coralsese Coooloo. 21, 33.0& 2.01 1.17 38.21 7.30 1.24 0.79 15.41 39.11 0.37
random 9164 !19 3.2v 0.23 0. Is J.25 V.01 0.0 0.0 1.01 A. 05 0.17
C-11801 allwe 32 2.19 0.13 0.09 2.40 0.29 8.0 0.0 0.23 2.29 0.21
Sect. "arrow 42 or. so. o. 0 JF- 0.02 0.33 0.12 0.0` 0.4 0.12 0.56 0.11
4 Coro 1150496FAIT da 4.tl 0,. J& 0.23 'is, 76 4.29 0.0 0.6 4.29 6.38 0.11
- ID'ever 116 VIGGO-, To 0.69 VI.Or 0. In 0:70 0.67 or. 0. 6.0 @.Or 0.31 0.32
Mail cologgeearl, 0;11 3.35 0.3t 0.9 0.3%. 3.20 0.23'
$&rotor 10 Ile it, 110, 0609 or. U 0.07 4.7v Q.*T q.01- 0.0 G.Gr 0.97 0.21

TIMES LAtew, MACI4106 FU*L-QJL-kU*.' 9111110 COSTS
OPERaT I Our NO. OATf. Gain MOIJIM "OUR$ alpkt* FM AM P" ACRE

ratio@* Oise 6.3t APW 1.00 0.2" 0.169 3.13
Calsof slow 6.32 ApIr . 1.00 0. 214'r 0.210 3.14
random Oiled: 6.39 MAT 1.00 0.204. 0.169 1.63L 3.13
See, Narrow 49 mar 1.00 0.0 0.169 0.01 0.17
care posel4wisTr 4.48 Its 1 1.00 G.)92 0.32) 4.21 7.9f
Sorsior 78 1?04& 70 may 1.00 0.0 0.325 0.22 0.41
Truck is way 0.10 0.120 0.100. *. @IF 01.92
Ica.@ !rue% 17 FIAT 0.10 0.120 0.100 0.93 3.44
14011 C.191.01of 6.63 JUN 1.00 0.262 0.21? 1.96 3.69
spro'er To Ile 6 71 JUN 1.00 0.0 Q.217 0.14 0.28
"yc% I I 'U. 0.10 0.122 0.00 0.58 3.92
:9.1111.9 11 Nov 1.00 O.M 0.3 19 4.27 23.1%
truck is Nov 0.20 '@. .140 0,200 1.76 .a.)
'OTAL 2. 290 7.659 20.00 48.95

S@15(.qs jtfeCt 04 varying rates of production erg 311cpq -at -6-9 e ..f.
overhead &'a

40-. .' Orod.Ctta. C'e
:-7_ S8.95 %!.v sb.,5
$204. 70 -60.911 5 .58.d-l 1-55.95
204. 70 -.1.45 J.@l 31.53
204.70 14.05 .1.55 9 i.

317

Reports relating the effects of altered freshwater flows on estuarine fisheries

Nature of influence Brief abstract

Estuarine management. At present no estuary of our nation is being properly managed, and none has
Darnell, R. M. 1981. an adequate management structure. Tools of estuarine management include
zoning, permitting authority, and lease/purchase.
The best goal in estuarine management is the predisturbance state, and to
achieve this goal both general and site-specific knowledge are required.
Reduced freshwater flows. For several years Region 2 (US FWS) has identified the problem of reduced
Stegman, J. L. 1981. freshwater inflow to Texas estuaries as the number one regional environ-
mental problem.

Striped bass declines Striped bass populations in the San Francisco Bay estuary have declined 60
and reduced freshwater to 80 percent. A major factor responsible for the reductions has been
flows. reductions in freshwater inflow. In Chesapeake Bay, as well as the east
Rote, J. R. and K. coast estuaries, stocks of striped bass have declined so dramatically that
Roberts. 1981. Congress has approved and authorized funding of special studies to deter-
mine the cause. Banning the commercial harvest of shad is being considered
in Chesapeake Bay, since the catch has declined more than 80 percent since
1970 (i.e. from 5,150,000 to 994,000 pounds).
About 3 billion pounds of recent annual U.S. commercial fish landings 60
to 70 percent of the most valuable commercial species of the Atlantic and
Gulf Coast - occupy estuaries during all or part of their life cycles.
Oyster beds are now being lost from intrusion of oyster predators and
parasites upstream in the bay. With additional freshwater diversion this
problem could become a major affliction.

Nature of influence Brief abstract

Salinity variations. Spatial and temporal salinity variations constitute the most signifi-
Robinson, A. E., Jr. 1981. cant physical parameter influencing the circulation dynamics of the
estuary and the types of aquatic species which reside in it.

Alterations of freshwater While the exact mechanisms producing reductions of commercial harvests
inflows. are being debated, salinity levels and nutrient influxes are consid-
Armstrong, N. E. and G. ered to be the most important variables.
H. Ward, Jr. 1981.

Adverse impacts of Florida Bay has developed into a hypersaline area. It has essentially
altered freshwater flows. ceased to function as an estuary. There has been a catastrophic
Spear, M. 1981. reduction in nursery habitat for estuarine finfish and shellfish due
to altered flows of freshwater and reduction of overland flow from 8
months to 4 months. Discharges of fresh water from canals into
estuaries are often confined to short time periods and the sudden
LO surges result in fish and shellfish mortalities in estuaries.
The catch per shrimp boat has decreased from 44,000 pounds in 1945 to
less than 5,000 pounds in 1972. The production per acre of oysters
has decreased from 500 pounds in 1945 to about 75 pounds in 1972.
The changes are attributed to drainage and saltwater intrusion.

High salinity and white High salinity has an adverse effect on white shrimp and oysters.
shrimp and oysters. Hypersalinity caused by low freshwater inflows resulted in decline to
Parker, R. H. 1955. white shrimp and oysters. Mission-Aransas and Nueces, Tex.

Reduced flows. Reduced flows and/or additional effluents would result in negative
Cooper, D. C. and B. J. impacts to estuarine productivity. Trinity-San Jaanto, Texas.
Copeland. 1973.

Freshwater inflow is There is a need for balanced salinity regimes as well as sufficient
important to Texas nutrients and sediments to maintain a sound habit--t for shri-p.
shrimp industry.
Rayburn, R. 1981.

Nature of influence Brief abstract

Optimum salinity for Optimum salinity for oyster was in the 10-15 ppt range. oyster larvae
oysters. were killed below 10 ppt and oyster drill doesn't tolerate less than
Breithaupt, R. L. and 15 ppt.
R. J. Dugas. 1979.

Oyster as indicator of The authors considered oyster a good indicator species for the deter-
optimum salinity range. mination of the optimum salinity range for Louisiana estuarine fish-
Lindall, W. M. et al. eries in general.
1972.

Shrimp production as Local shrimp production is related to the ratio of marshwater inter-
related to ratio of face to area of water. La.
marshwater interface
to area of water.
Faller, K. M. 1979.

Marsh-salinity corre- Annual production of brown shrimp was correlated with the acreage
lated with brown shrimp of marsh having waters above 10 ppt. salinity. La.
production.
Barrett, B. B. and M.
S. Gillespie. 1973.

Shrimp and blue crab Low summer salinities are not suitable for brown and white shrimp but
production as related are ideal for blue crabs. Sabine-Neches estuary, TX.
to low summer
salinities.
White, C. J. et al.
1969.

Altered temporal flows Correlation-regression analysis indicated that offshore shrimp catches
affect shrimp harvests. (brown, white and pink) are positively correlated with spring (April-
Browder, J. A. and D. June) inflow and negatively correlated with winter (January-March) and
Moore. 1981. summer (July-August) inflows. Laguna Madre, Texas.

Nature of influence Brief abstract

Increased flow of fresh- Increased oyster and shrimp.production was associated with increased
water and nutrient input. freshwater inflows. La.
Viosca, P. 1938, Gunter,
G., 1950, Dugas, R. J.,
1977.

Detritus. Significance of river-derived particulate organic matter to estuarine
Livingston, R. J. 1981. biota remains in doubt. Fla.

Low flows in wet season Extremely dry, wet seasons are accompanied by increased abundance of
affects abundances. common and scarce forms. Abundances in such a season affects abun-
Fraser, T. H. 1981. dance in the following dry season.

Freshwater discharge Freshwater discharges by the St. Lucie Canal, Florida, had significant
and creel results. short-term effects on catch rates-of nine important estuarine species
Van Os, E., et al. 1981. and caused their habits to be less predictable.

Salinity and estuarine Normal oligohaline fauna was replaced by freshwater fauna during
fauna. flood conditions when salinity fell under about 0.5 ppt.
Hoese, H. D. 1981. Atchafalaya Bay, LA.

Freshwater inputs related Did not conclude there was a clear relationship between freshwater
to catch of commercial flows and yields (except that shrimp catch may be negatively related
species. to freshwater flows.
Nixon, S. W. 1981.

Altered timing of Reduction in catches of brown and white shrimp were associated with
freshwater flows and reduced inflow surge delayed until mid May due to operation of a dam;
reduced catches of shrimp. Sabine Lake, LA.
White, C. J. and W. S.
Perret. 1973.

Standing stocks and Summary of many numerous Gulf States studies indicate highest marine
freshwater estuaries. standing stocks are in or near estuaries which receive freshwater
Browder, J. A. and D. inputs.
Moore. 1981.

Nature of influence Brief abstract

Increased wet season and Negative impacts were noted due to seasonal alterations of freshwater
decreased dry season fresh- inflows.
water inputs in Florida.
Browder, J. 1977.

Increased freshwater flows Stratification caused low dissolved oxygen in canals during period of
caused stratification. high discharge. Benthic life was negatively affected and pelagic
Van de Kreeke 1979, Yokel, fishes were excluded from the area. Lack of mixing in dead-end canals
1979, and Hicks 1979. tended to trap and concentrate organic materials including pathogenic
bacteria. Fla.

River flow rates control Annual abundance indices increase directly with river flow rates.
survival of major species. (striped bass, chinook, salmon, American shad, longfin smelt).
Herrgesell, P. L. et al. Sacramento-San Joaquin Estuary.
1981.

Additional inflow at Preliminary results indicated that additional inflow at the
appropriate time appropriate time will increase numbers of fry and juvenile salmon
increased survival. using the Sacramento-San Joaquin Estuary.
Kjelson, M. A. et al.
1981.

Rainfall rates and Wetter years favored populations of young migratory fishes and
estuarine fish and crustacea; larger predator fishes tended to be more abundant
crustacea. during dry years than during wet years.
Johnson, D. R. et
al. 1981.

High concentrations Estuarine receiving waters are commonly threatened by pollution and
of nutrients at time the impacts are often most pronounced at times of low flow in warm
of low flow. weather.
Correll, D. L. 1981.

Nature of influence Brief abstract

Declining zooplankton Flood waters reduced estuarine zooplankton by 2/3 and sharply reduced
populations due to salinities of San Antonio Bay. Implication that larval stages of
freshwater intrusion. economically important species were adversely affected by the natural
Matthews, G. A. 1981. phenomenon.

Reduced estuarine Estuarine zooplankton were flushed out by freshwaters and replaced by
zooplankton and major freshwater species. Following the freshwater incursion Acartia
freshwater incursions. tonsa were successful at salinities of I to 3 ppt.. This was attrib-
Kalke, R. D. uted to the influx of nutrients, food and a decrease of higher
salinity predators. Nueces-Corpus Christi and Copano-Aransas Bay
systems, TX.

Increased benthos follow- Fresh water, due to flooding, in Corpus Christi Bay, TX., may have
ing flood waters. introduced nutrient materials thus increasing faunal densities which
Flint, R. W. and S. C. may be a link to shrimp populations which derive much of their
Rabalais. 1981. nutrition from benthos.

4-
Detritus and river Detritus is a principle element in the food web of estuarine eco-
flow. systems.
Copeland, B. J. 1966.

Nutritional particulate Highest concentrations, of the biochemical components analy@ed,
matter And entrapment occurred in the entrapment zone at salinities of-4 to 6 ppt. San
zone. Francisco Bay-Estuary.
Barclay, W. R. and A. W.
Knight. 1981.

Sediment -- assets or Sediments are assets relative to delta building and associated
liability. estuarine wetlands, but are liabilities to maintaining navigation.
van Beek, J. L. and K.
Meyer-Arendt. 1981.

Nature of influence Brief abstract

Retention of freshwater Holding freshwater will decrease total water going to bay (evapotrans-
on land advantageous for piration), increase ratio of delayed runoff to immediate runoff, reduce
management of estuary. peak flows, increase base flows, raise dry-season water table, reduce
Simpson, B. 1979. forest fires, prevent saltwater intrusion, increase irrigation water
supplies and increase the productivity of wetlands. Fla. ..

Forestry practices and Forestry operations led to increased amplitudes and decreased duration
periods of high runoff of runoff events, causing more abrupt than normal changes in salinity
from swamps. and nutrients in the vicinity. Increased water color, decreased dis-
Livingston, R. J. and solved oxygen, decreased pH coincided with periods upper bays were
J. L. Duncan. 1979. heavily utilized as nursery grounds by fish and invertebrates resulting
in significant reduction of white shrimp. Regrowth of covering
vegetation had ameliorating effect. Fla.

Climatic variables and Recruitment of striped bass is determined by the end of the larval
production of striped stage and their position in the estuary. Where spawning takes place
bass. and zooplankton abundance are important factors regulating this pro-
Mihursky, J. A. et cess. These factors are in turn influenced by several climatic
al. 1981. variables.

Several authors have related internal ecosystems characteristic(s)
to the behavior of extrinsic variables (Menzel et al. 1966, Aleem
1972). Copeland (1966) found that fishery yields in some Texas bays
increase in years of above average river flow. Menzel et al. (1966)
showed similar trends for oyster stocks in Apalachicola Bay, Florida.
Heinle et al. (1975) concluded that colder than normal winters
enhance zooplankton and juvenile fish recruitment in the Patuxent
River, Maryland. Sutcliffe et al. (1976) and Sutcliffe et al. (1977)
demonstrated significant correlations between catches of 17 species
of commercial marine fish and shellfish and sea temperatures in the
Gulf of Maine.

Nature of influence Brief abstract

Altered freshwater flows. Unaltered areas had significantly higher production of brown shrimp
Jones, R. A. and T. M. as well as other commercially important species. Rapidly pulsating
Sholaft. 1981. events occurred in the altered sites.

Ditching systems and Ditching systems are designed to efficiently remove surface waters
rates of freshwater from cultivated fields, thus increasing peak runoff rates and alters
discharge. the ability of the inland areas and associated vegetation to act as a
Pate, P. P., Jr. and natural regulator of surface runoff. The results are an increase in
R. Jones. 1981. the rate of runoff during and following storms and an unstable
salinity pattern responding quickly and dramatically to rainfall.
Unaltered shrimp nursery areas were much more stable than were
altered areas during the same rain periods. Extensive drainage into
a nursery area reduces its value by reducing average salinities and
making it more sensitive to the effects of rainfall within the drain-
age basin.
Relative productivity of estuarine organisms was down each year in
the nursery area with extensive drainage. The most serious effects
of drainage into nursery areas appears to be the degree of alteration
and the danger that alteration will be severe enough to create an
unsuitable habitat during periods of normal rainfall. N. C.

Bibliography

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Armstrong, N. E. and G. H. Ward,Jr. Alterations of freshwater inflows.
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Barclay, W. R. and A. W. Knight. 1981. The Nutritional Significance of
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Barrett, B. B. and M. C. Gillespie. 1973. Primary factors which
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Browder, J. 1977. The estuary viewed as a dynamic system. Seaman, W.,
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Browder, J. A. and D. Moore. 1981. A new approach to determining the
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Cooper, D. C. and B. J. Copeland. 1973. Responses of continuous-series
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Darnell, R. M. 1981. Strategies for the Management of Estuaries. Cross,
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Dugas, R. J. Oyster distribution and density on the productive portion
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Faller, K. H. 1979. Shoreline as a ccntroling factor in commercial
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Gunter, G. 1950. The relationship of the Bonnet Carre Spillway to
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Heinle, D. R. and D. A. Flemer. 1975. Carbon requirements of a popula-
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Herrgesell, P. L. et al. 1981. River flow rates control survival of
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of a fish-crustacean community in Texas Galveston Bay System. Cross, R.,
and D. Williams, Eds. Proc. of Nat. Sym. on Freshwater Inflow to
Estuaries. FWS/OBS-81/04. Vol. II, p. 335-349.

Jones, R. W. and T. M. Sholar. 1981. The effects of freshwater
discharge on estuarine nursery areas of Pamlico Sound. Completion
Rept. Project CEIP 79-11. 59 p.

Kjelson, M. A. et al. 1981. Influences of freshwater inflow on
Chinook salmon (Oncorhynchus Tshawytscha) in the Sacramento-San
Joaquin Estuary. Cross, R., and D. Williams, Eds. Proc. of Nat. Sym.
on Freshwater Inflow to Estuaries. FWS/OBS-81/04. Vol. II, p. 88-108.

328

Lindall, W. M. et al. 1972. Louisiana coastal zone: analyses of
resources and resource development in connection with estuarine ecology.
Sections 10 and 13, Fishery resources and their needs. Report of the
commercial fishery work unit of the National Marine Fisheries Service
to the U. S. Army Corps of Engineers (Contract #14-17-002-430); 1972;
320 p. Located at: NMFS, Southeast Regional Office, 9450 Koger Blvd.,
St. Petersburg, FL 33702.

Livingston, R. J. 1981. River-derived input of detritus into the
Apalachicola Estuary. Cross, R., and D. Williams, Eds. Proc. of Nat.
Sym. on Freshwater Inflow to Estuaries FWS/OBS-81/04. Vol. 1, p.
320-332.

Livingston, R. J. and J. L. Duncan. Climatological control of a north
Florida coastal system and impact due to upland forestry management.
Livingston, R. J., ed. Ecological processes in coastal and marine
systems. New York: Plenum Press; 1979: 339-381.

Matthews, G. A. 1981. The effects of floods on the zooplankton
assemblage of San Antonio Bay Texas during 1972 and 1973. Cross, R.,
and D. Williams, Eds. Proc. of Nat. Sym. on Freshwater Inflow to
Estuaries FWS/OBS-81/04. Vol. 1, p. 509-525.

Menzel, R. W. et al. 1966. Oyster abundance in Apalachicola Bay,
Florida, in relation to biotic associations influenced by salinity
and other factors. Gulf Res. Rep. 2(2):73-96.

More, W. R. A contribution to the biology of the blue crab (Callinectes
sapidus Rathbun) in Texas, with a description of the fishery. Tex. Parks
Wildl. Dept. 1969. Tech. Ser. 1.

Nixon, S. W. 1981. Freshwater Inputs and Estuarine Productivity.
Cross, R., and D. Williams, Eds., Proc. of Nat. Sym. on Freshwater
Inflow to Estuaries FWS/OBS-81/04. Vol. 1, p. 31-57.

Parker, R. H. 1955. Changes in the invertebrate fauna, apparently
attributable to salinity changes, in the bays of central Texas. J.
Paleont. 29:193-211.

Pate, P. P., Jr. and R. Jones. 1981. Effects of upland drainage on
estuarine nursery areas of Pamlico Sound, N. C. Cross, R., and D.
Williams, Eds. Proc. of Nat. Sym. on Freshwater Inflow to Estuaries.
FWS/OBS-81/04. Vol. II, p. 402-418.

Rayburn, R. 1981. Texas shrimp fisheries and freshwater inflow. Cross,
R., and D. Williams, Eds. Proc. of Nat. Sym. on Freshwater Inflow to
Estuaries FWS/OBS-81/04. Vol. 1, p. 431-435.

Robinson, A. E., Jr. 1981. Chesapeake Bay Low Freshwater Inflow Study.
Cross, R., and D. Williams, Eds. Proc. of Nat. Sym. on Freshwater
Inflow to Estuaries FWS/OBS-81/04. Vol. 1, p. 114-127.

329

Rote, J. R. and K. Roberts. 1981. Role of the National Marine Fisheries
Service in the Protection of Freshwater Inflow Estuaries. Cross, R., and
D. Williams, Eds. Proc. of Nat. Sym. on Freshwater Inflow to Estuaries
FWS/OBS-81/04. Vol. 1, p. 18-22.

Simpson, B. Appendix F-Engineering. The Naples Bay study. 1979. 27
p. Available from Collier County Conservancy, P. 0. Box 2136, Naples,
FL 33939.

Spear, M. 1981. Freshwater Inflows and Fish and Wildlife Service
Operations. Cross, R., and D. Williams, Eds. Proc. of Nat. Sym. on
Freshwater Inflow to Estuaries FWS/OBS-81/04. Vol. 1, p. 23-30.

Stegman, J. L. 1981. Welcoming Address. Cross, R., and D. Williams,
Eds. Proc. of Nat. Sym. on Freshwater Inflow to Estuaries FWS/OBS-81/04.,
Vol. 1, p. 3-4.

Sutcliffe, W. H. et al. 1976. Coastal circulation and physical oceano-
graphy of the Scotian Shelf and the Gulf' of Maine. J. Fish. Res. Board
Can. 33:98-115.

Sutcliffe, W. H. et al. 1977. Correlations of fish catch and environ-
mental factors in the Gulf of Maine. J. Fish. Res. Board Can. 34:19-30.

van Beek, J. L. and K. Meyer-Arendt. 1981. Sediment -- assets or
liability. Cross, R., and D. Williams, Eds. Proc. of Nat. Sym. on
Freshwater Inflow to Estuaries. FWS/OBS-81/04. Vol. II, p. 197-215.

van de Kreeke, J. Appendix C-Hydrography. The Naples Bay study 1979;
43 p. Available from Collier County Conservancy, P. 0. Box.2-136,
Naples, FL 33939.

Van Os, E., et al. 1981. The Effects of Freshwater Discharges on
Sportfishing CatchRates in the St. Lucie Estuary, Martin County,
Florida. Cross, R., and D. Williams, Ed.s. Proc. of Nat. Sym. on
Freshwater Inflow to Estuaries FWS/OBS-81/04. Vol. 1, p. 269-281.

Viosca, P., Jr. Effect of the Bonnet Carre Spillway on fisheries.
Louisiana Conservation Review 6:51-53; 1938.

White, C. J. and W. S. Perret. Short term effects of the Toledo Bend
Project on Sabine Lake, Louisiana. Mitchell, A. L., ed. Proceedings,
27th Annual Conference, S. E. Assoc. Gair,.e Fish Comm.; 1973 October
14-17. Hot Springs, AR: 1974; 710-721.

Yokel, B. Appendix E-Biology. The Naples Bay study 1979; 54 p.
Available from Collier County Conservancy, P. 0. Box 2136, Naples, FL
33939.

330

10.4 Appendix for Section 6.1.4: Wildlife

331

Wildlife Habitat Simulation

Introduction

A wildlife habitat quality prediction model forecasts future
habitat conditions (given a set of present conditions and a management
scheme) so that impacts of proposed management pllans may be evaluated.

In 1973, the U. S. Fish and Wildlife Service began developing
uniform Habitat Evaluation Procedures (HEP) to assist this process.
HEP use simple mathematical functions wich describe habitat guality
for particular species, ascribe a guality value to each habitat type
in the project area, and sum the quantities (area x value) to obtain
an index of habitat quality for a qiven species on the total area
(Adams et al., 1982).

The model presented here uses the HEP concept to predict habitat
qualitY for the three scenaris and four areas considered. The model
uses a computer program which operates on an Apple II microcomputer ,
prompts the user for data input permits input file editing, provides
hard copy printouts of inputs and outputs on request, computes land
use-habitat type inventories for the end of the project period with
and without the project, by major user), accrues annualized habitat
quality units (by species, with and without the project, by major-
user), and provides an index of overall wildlife habat impact.
Specifically:

1. It requires the following input:

a. Project duration (20 years in our case).

b. Land inventory, for each area consider-
ered (up to 4 areas) by land use-habit-
at type (up to 16 types are permitted)

c. Indicator species (up to 14 species
are permitted).

d. A Habitat Suitability Index ( HSI) for
each species for each land use-habitat
type.

e. A conversion rate for each land use
habitat type to every other type,
based on "PRO", the proportion of the
area or absolute area affected,
"BEG" and "END", the begommomg and end
of the period over which the
change occurs, and "REG", the form
of the regression.

332

2. It computes annual land use-habitat type conversions
as "changes" from one type to another. In accordance with the
following user-specified functions.

a. A linear function:

change = (area of type at beginning of
the project period x percent of
area affected) / period over
which change occurs

b. An exponential function:

change = (area of type at beginning of
computational year x percent
of area affected) / period
over which change occurs

c. A time-phased function (5-year
increments):

change = (area at end of increment -
area at beginning of increment)
/ 5

d. A fixed increment function:

change = the user-specified increment

e. A sinusoidal function:

change = an annual increment along a partial
sine wave encompassing the percent
of area affected, over the period
in which the change occurs, based
on the area of the type at beginning
of the project period

For each year, the program computes "change" from each
type to every other types, subtracts the "change" from the former, adds
it to the latter, computes a new inventory for the beginning of the
next year, and accumulates annualized habitat quality units for each
species in each habitat.

3. It provides the following outputs:

a. All input data.

b. Habitat conditions (acreage of each
type) at the of the project
period, with and without the project
for each major user.

333

c. Accrued annualized habitat quality
units for each species, with and
without the project, for each major
user's land.

d. Total accrued annualized habitat
quality units for the project area.
with and without the project, and an
index of project impact.

e. Average HSI for each species is each
area, at the beginning and
end of the project.

FUNCTIONS

Functional Entries

Type Pro. BEG., END Req.

Linear Percent of initial Period over L
area affected which change occurs

Esponential Percent of annual Period over E
inventory affected which change occurs

Sinusoidal Percent of initial Period over S
area affected which change occurs

Fixed Area lost per year Period over F
which change occurs

Time-phased Any number > 0 Any number T
(Enter accrued area lost at year indicated)
334

Variables

PR = project period
PER = period over which change occurs.
A = initial area (acres)
AC = area at beginning of given year (annual inventory)
I = land use-habitat type losing area
NUM = land use-habitat type gaining area
P = "Pro." from entry data
Y = "Yr." from entry data
YR = year being computed
Z = area concerned
T5 = accrued area lost by year 5
TIO = accrued area lost by year 10
T15 = accrued area lost by year 15
T20 = accrued area lost by year 20

Equations (solved annually over the period in which change
occurs)

Linear (L) Change = (A(I, Z) * (P(I<NUM) / 100)) / PER
PER

Exponential (E) Change = (AC(I) * (P(I,NUM) / 100)) /
PER

Sinusoidal (S) S1 = (COS(3.1416 * (YR I/ PER)))
+ 1
S2 = (COS(3.1416 * ((YR-I) / PER)))
+ 1
DI = (P( I, NUM) / 100 * (A( I,Z) / 2)
CI = SI * DI
C2 = S2 * DI
Change = C2 - Cl

Fixed (F) Change = P(I, NUM)

335

Time-phased (T) If YR <= PR / 4 then
Change = T5(I,NUM) / (PR * .25)

If YR > PR / 4 and YR <= PR / 2 then
Change = (TlO (I,NUM) - T5 (I,NUM))
/ (PR.* .25)

If YR > PR / 2 and YR <= PR / 1.3333
then
Change = (T15(I,NUM) - TIO(I,NUM))
(PR * .25)

If YR > PR / 1.3333 and YR <= PR then
Change = (T20(I,NUM) - T15(I,NUM) /
(PR * .25)

Inputs to and outputs from the simulation are given on the
following pages.

336

HABITAT TYPES WITHIN PROJECT AREA EVALUATION SPECIES

1 RESIDENTIAL DEVELOPMENT 1 BLACK BEAR
2 ROADS AND RIGHTS-OF-WAY 2 WHITETAIL DEER
3 OTHER DEVELOPED AREAS 3 MARSH RABBIT
4 AGRICULTURAL LAND 4 MUSKRAT
5 DECIDUOUS FOREST 5 BOBWHITE
6 EVERGREEN FOREST 6 MOURNING DOVE
7 MlXED FOREST 7 GREAT HORNED OWL
8 WHITE CEDAR SWAMP 8 PINE WARBLER
9 MIXED SWAMP 9 HAIRY WOODPECKER
10 DISTURBED LAND 10 BOBCAT
11 HIGH POCOSIN
12 LOW POCOSIN
13 BAY FOREST
14 WATER AND MARSH
15 ACTIVE PEAT MINE
16 INACTIVE PEAT MINE

HABITAT SUITBILITY INDICES FOR HABITAT SUITABILITY INDICES FOR
BLACK BEAR IN; WHITETAIL DEER IN:

TYPE HSI TYPE HSI

RESIDENTIAL DEVELOPMENT 0 RESIDENTIAL DEVELOPMENT .02
ROADS AND RIGHTS-0F-WAY .03 ROADS AND RIGHTS-OF-WAY .22 OTHER DEVELOPED AREAS .03 OTHER DEVELOPED AREAS .08
AGRICULTURAL LAND .24 AGRICULTURAL LAND .53 DECIDUOUS FOREST .72 DECIDUOUS FOREST .85 1
EVERGREEN FOREST .4 EVERGREEN FOREST .47 MIXED FOREST .62 MIXED FOREST .77 WHITE CEDAR SWAMP .6 WHITE CEDAR SWAMP .38
MIXED SWAMP .77 MIXED SWAMP .58
DISTURBED LAND .47 DISTURBED LAND .78
HIGH POCOSIN .78 HIGH POCOSIN .6
L0W POCOSIN .73 LOW POCOSIN .52 WATER AND MARSH .23 WATER AND MARSH .23 .07 ACTIVE PEAT MINE .1 TV- INACTIVE PEAT MINE .13 INACTIVE PEAT MINE .28

337

HABITAT SUITABILITY INDICES FOR HABITAT SUITABILITY INDICES FOR
MARSH RABBIT IN: MUSKRAT IN:

TYPE HSI TYPE HSI

RESIDENTIAL DEVELOPMENT .02 RESIDENTIAL DEVELOPMENT .05
ROADS AND RIGHTS-OF-WAY .2 ROADS AND RIGHTS-OF-WAY .13
OTHER DEVELOPED AREAS .06 OTHER DEVELOPED AREAS .12
AGRICULTURAL LAND .18 AGRICULTURAL LAND .38
DECIDUOUS FOREST .32 DECIDUOUS FOREST .12
EVERGREEN FOREST .24 EVERGREEN FOREST .03
.24 MIXED FOREST .05
MIXED FOREST .42
WHITE CEDAR SWAMP .7 WHITE CEDAR SWAMP .08
MIXED SWAMP .27
MIXED SWAMP
DISTURBED LAND .4 DISTURBED LAND .15
HIGH POCOSIN .54 HIGH POCOSIN .08
LOW POCOSIN .66 LOW POCOSIN .13
BAY FOREST .5 BAY FOREST .05
WATER AND MARSH .7 WATER AND MARSH .9
ACTIVE PEAT MINE .06 ACTIVE PEAT MINE .05
INACTIVE PEAT MINE .22 INACTIVE PEAT MINE .12

HABITAT SUITABILITY INDICES FOR HABITAT SUITABILITY INDICES FOR
BOBWHITE IN: MOURNING DOVE IN:

TYPE HSI TYPE HSI

RESIDENTIAL DEVELOPMENT .11 RESIDENTI0NAL DEVELOPMENT .3
ROADS AND RIGHTS-OF-WAY .37 ROAD AND RIGHTS-OF-WAY .43
OTHER DEVELOPED AREAS .18 OTHER DEVELOPED AREAS .28
AGRICULTURAL LAND .75 AGRICULTURAL LAND .85
DECIDUOUS FOREST .36 DECIDUOUS FOREST .16
EVERGREEN FOREST .43 EVERGREEN FOREST .48
MIXED FOREST .39 MIXED FOREST .38
WHITE, CEDAR SWAMP .1 WHITE CEDAR SWAMP .12
MIXED SWAMP .15 MIXED SWAMP .12
DISTURBED LAND .7 DISTURBED LAND .53
HIGH POCOSIN .36 HIGH POCOSIN .15
LOW POCOSIN .32 LOW POCOSIN .12
SAY FOREST .21 BAY FOREST .1
WATER AND MARSH .12 WATER AND MARSH .03
ACTIVE PEAT MINE .07 ACTIVE PEAT MINE .07
INACTIVE PEAT MINE .28 INACTIVE PEAT MINE .26

338

HABITAT SUITABILITY INDICES FOR HABITAT SUITABILITY INDICES FOR
GREAT HORNED OWL IN: PINE WARBLER IN:

TYPE HSI TYPE HSI

RESIDENTIAL DEVELOPMENT .03 RESIDENTIAL DEVELOPMENT .05
ROADS AND RIGHTS-OF-WAY .23 ROADS AND RIGHTS-OF-WAY .08
OTHER DEVELOPED AREAS .07 OTHER DEVELOPED AREAS .08
AGRICULTURAL LAND .4 AGRICULTURAL LAND .08
DECIDUOUS FOREST .8 DECIDUOUS FOREST .2
EVERGREEN FOREST .55 EVERGREEN FOREST .96
MIXED FOREST .82 MIXED FOREST .64
WHITE CEDAR SWAMP .33 WHITE CEDAR SWAMP .33
MIXED SWAMP .77 MIXED SWAMP .34
DISTURBED LAND .58 DISTURBED LAND .1
HIGH POCOSIN .38 HIGH POCOSIN .5
LOW POCOSIN .33 LOW POCOSIN .34
BAY FOREST .45 BAY FOREST .26
WATER AND MARSH .15 WATER AND MARSH 0
ACTIVE PEAT MINE .05 ACTIVE PEAT MINE 0
INACTIVE PEAT MINE .23 INACTIVE PEAT MINE .06

HABITAT SUITABILITY INDICES FOR HABITAT SUITABILITY INDICES FOR
HAIRY WOODPECKER IN: BOBCAT IN:

TYPE HSI TYPE HSI

RESIDENTIAL DEVELOPMENT .13 RESIDENTIAL DEVELOPMENT .02
ROADS AND RIGHTS-OF-WAY .06 ROADS AND RIGHTS-OF-WAY .15
OTHER DEVELOPED AREAS .1 OTHER DEVELOPED AREAS .05
AGRICULTURAL LAND .04 AGRICULTURAL LAND .28
DECIDUOUS FOREST .8 DECIDUOUS FOREST .68
EVERGREEN FOREST .66 EVERGREEN FOREST .53
MIXED FOREST .84 MIXED FOREST .75
WHITE CEDAR SWAMP .5 WHITE CEDAR SWAMP .53
MIXED SWAMP .56 MIXED SWAMP .7
DISTURBED LAND .16 DISTURBED LAND .65
HIGH POCOSIN .52 HIGH POCOSIN .67
LOW POCOSIN .36 LOW POCOSIN .65
BAY FOREST .42 BAY FOREST .62
WATER AND MARSH 0 WATER AND MARSH .25
ACTIVE PEAT MINE 0 ACTIVE PEAT MINE .03
INACTIVE PEAT MINE .06 INACTIVE PEAT MINE .22

339

RATE OF HABITAT CONVERSION IN RATE OF HABITAT CONVERSION IN
AREA 1,SCENARIO #1 AREA 1,SCENARIO #1,
WITHOUT THE PROJECT. WITHOUT THE PROJECT

FROM DISTURBED LAND TO- FROM INACTIVE PEAT MINE TO:

TYPE PRO BEG END R TYPE PRO BEG END E

HIGH POCOSIN 3.5 1 20 E RESIDENTIAL DEVELOPMENT 0 0 0
LOW POCOSIN 16.5 1 20 E ROADS AND RIGHTS-OF-WAY 0 0 0
BAY FOREST 0 13 0 OTHER DEVELOPED AREAS 0 0 0
WATER AND MARSH 0 0 0 AGRICULTURAL LAND 0 0 0
ACTIVE PEAT MINE 0 0 0 DECIDUOUS FOREST 0 0 0
INACTIVE PEAT MINE 0 0 0 EVERGREEN FOREST 0 0 0
PESIDENTIAL DEVELOPMENT 0 0 0 MIXED FOREST 0 0 0
ROADS AND RIGHTS-OF-WAY 0 0 0 WHITE CEDAR SWAMP 0 0 0
OTHER DEVELOPED AREAS 0 0 0 MIXED SWAMP 0 0 0
AGRICULTURAL LAND 0 0 0 DISTURBED LAND 0 0 0
DECIDUOUS FOREST 0 0 0 HIGH POCOSIN 0 0 0
EVERGREEN FOREST 0 0 0 LOW POCOSIN 0 0 0
MIXED FOREST 0 0 0 BAY FOREST 0 0 0
WHITE CEDAR SWAMP 0 0 0 WATER AND MARSH 100 5 20 T
MIXED SWAMP 0 0 0 BY YEAR
5 = 0 10 = 316 15 = 316 20 = 31
ACTIVE PEAT MINE 0 0 0

HABITAT CONDITIONS, SCENARI0 #1
AT THE END OF THE PROJECT PERIOD.
AREA 1 WITHOUT THE PROJECT.

TYPE ACRES

RESIDENTIAL DEVELOPMENT 0
ROADS AND RIGHTS-OF-WAY 0
OTHER DEVELOPED AREAS 0
AGRICULTURAL LAND 2843
DECIDUOUS FOREST 0
EVERGREEN FOREST 0
MIXED FOREST 0
WHITE CEDAR SWAMP 0
MIXED SWAMP 0
DISTURBED LAND 100
HIGH POCOSIN 2138
LOW POCOSIN 10100
BAY FOREST 0
WATER AND MARSH 632
ACTIVE PEAT MINE 0
INACTIVE PEAT MINE 0

TOTAL 15819

340

ACCRUED AN@IUALIZED HF2461TAT UNITS ACCRUED ANNU"LI:ED HABITAT UNITS
AT THE 'EtIri Or: THF7 PROJECT PERIOD. AT THE END OF THE PROJECT PERIOD.
AREA I , ;,f-- E"NARI 0 4 1 , AREA SCENARIO #1 ,
W!THOUT THE PROJECT. WITHOUT THE PR'OJECT. (CONT7NUED)

T(PE SPEC. TYPE SPEC. TOT.
1 2 3 4 5 7 8 9 10

1 0 0 0 0 1 0 0 0 0 0 0
2 0 0 0 13 cl 2 0 0 11 0 0 0
0 0 0 0 0 .3 0 0 0 0 0 0
4 664 1509 512 1082 2136 4 2 42 1 112@1 228 114 797
5 0 0 0 0 cl C, 1) 0 cl 0 0
0 0 cl 0 0 0 0 0 0 0 0
7 0 0 0 0 0 7 0 0 0 0 0 0
8 cl 0 0 0 0 a 0 0 0 0 0 0
9 0 0 0 0 0 9 0 0 0 0 0 0
10 808 1256 688 258 1204 10 ?12 998 1-2 275 ills 7682
1113 1001 148 668 It 272 7
!1 144 05 9@7 964 1243 S45A
1-;, 'S97 12 1052 281?2 2?80 3155 56516 3645c
8 , 4557 5784 1 139 2204
13 0 0 0 0 0 13 0 0 0 0 cl 0
14 120 120 365 4 6? C-3 14 16 78 0 0 1 So 1361
15 0 0 0 0 0 15 0 0 0 0 0 0
16 14 3 1 2`4 13 '31 16 2 9 25 7 7 24 206

7 9470 8586 8375 71,110 .6905 T 41-07 5837 4313 4515 9000 6482E

RATE f-,P H@iE174;T i--ONK)ERSION IN RATE @F
Cl-i-,IERSICIN IN
p- E: :,@ F. 41
AREA 3 C Et @H R 1
WITH THE PROJFC.T.' WITH THE PROJE,--T.

FROM AGRICULTURAL LAND TO: PROM DISTURBED LAND TO:

TYPE PRO BEG END R TYPE PRO BEG END P

DECIDUOUS FOREST 0 0 0 HIGH POCOSIN 0 1 0
21,1ERGREEN FOREST 0 0 0 LOW POCOSIN 0 1 1)
MIXED FOREST 0 0 0 6AY FOREST 0 0 0
i.%IHITE CEDAR SWAMP 0 0 0 WATER AND MARSH 0 11 0
t!I'm,ED SWAMP 0 1) C! ACTIVE PEAT MINE 313 1 20 F
Z'ISTUReED LAND 0 0 0 INACTIkIE PEAT MINE 0 0 cl
HIGH POCOSIN 0 0 9 RESIDE!,ITIAL DEVELOPMENT 0 0 0
LOW POCOSIN 0 0 cl POADS AND RIGHTS-OF-1,-jAY 0 0 1)
EAY FOREST 0 0 0 OTHEP DEVELOPED AREAS 13 0 0
WATER AND MARSH ,-'I cl cl @@GPICULTURAL LAND 0 0 cl
41-.TIVE PEAT MINIE 102 1 20 F DECIDUOUS FOREST 0 0 0
lt,,I,-CTIk,'E PEAT MINE cl 0 0 EVERGREEN) FOREST 0 0 0
RESIDEHTIAL DEVELOPMENT 0 0 0 MIXED FOPEST 0 0 0
ROADS "HD PIGHTS-OF-WA'( 0 0 F@ WHITE I.-;E[,AR S1,dAmP 13 0 cl
OTHER DEI)ELOPED AREAS 0 0 0 HI""ED 31,441P 0 0 0

341

PATE OF HABITAT CONk.)EPSION IN RA,rs OF HABITAT' CONVERSION IN
AREA I,SCEllf"@RIO 141 - AREA 14,.,
WITH THE PROJECT. WITH THE PROjECT,

FROM HIGH POCOSIN TO: FROM LOW POCOSIN TO:

TYPE PRO BEG END R TYPE PRO BEG END F

LOW POCOSIN a 0 0 SAY FOREST 0 0 0
SAY FOREST 0 0 0 WATER AND MARSH 13 0 a
WATER AND MARSH 0 0 0 ACI'It)E PEAT MINE igs I -@ 0
ACTIQE PEAT MINE 21 3 1 () F INACTI'-)E PEAT MINE 11 0 0
INACTIt)E PEAT MINE 0 0 0 PESIDEINTIAL DEVELOPMENT 0 0 0
RESIDENTIAL DEVELOPMENT 0 0 0 ROo:iDS AND RIGHTS-OF-WAY 0 cl 11
ROADS AND RIGHTS-OF-WAY 0 0 0 OTHER DEVELOPED AREAS 0 cl
OTHER DEVELOPED AREAS 0 0 cl AGRICULTURAL LAI-41.- ct
AGRICULTURAL LAND 0 0 0 DECIDUOUS FOREST 0 0
DECIDUOUS FOREST 0 0 0 EVERGREEN FOREST 0 (1
EVERGREEN FOREST 0 0 0 MIXED FOREST cl 0, 0
MI':<ED FOREST 0 0 0 WHITE CEDAR SWAMP 0 0 0
WHITE CEDAR SWAMP 0 0 0 MIXED SWAMP a 0 0
MIXED SWAMP 0 0 0 DISTUPSED LAND 0 0 0
DISTURBED LAND 0 0 0 HIGH POCOSIN 0 0 0

PATE OF HABIT4-7 CONIt.'ERSION IN RATE OF H,@F--ITAT '--C-NVERSI;---N IN
AREA I -SCENHF-101 -41 - (-4 R EA 1 , S C Ei 4,-m. F 1 Q
WITH THE PROJECT. WITH THE PROJECT.

FROM WATER AND MARSH TO: FROM ACTIVE PEAT MINE TO:

TYPE PRO BEG EN D R TYPE PRO 9EG END R

ACTIk.'E PEAT fill-JE 11 1 :10 F INACTI')E PEAT IIIHE 100 2 ZO T
INACT IVE PEAT MINE 0 0 0 E-'Y EA P
RESIDENTIAL De,ELOPMENT 0 0 0 5 2840 10 = q-6!30 15 = 8520
ROADS f*lD RIGHTS-OF-WAY 0 0 13 PESIDEl,',JTIHL DEVELOPMENT 0 0 0
OTHER DEUELOPED AREAS 0 0 0 ROADS AND RIGHTS-OF-WAY 0 0 1)
AGRICULTURAL LAND 0 0 0 OTHER DEVELOPED -@REPZ,3 0 cl 0
DECIDUOUS FOREST 0 0 0 AGRICULTURAL Lt-41---
EVERGPEE14 FOREST 0 cl cl DECIDLI@70-c, Fi--,F.'E::'r c@ cl
HIIXED FOREST cl 0 0 EVERGREEN FOR-"-'Z-'7 C; 0 zi
WHITE CEDAR SWAMP 0 0 0 MIXED FOREST 0 0 1)
MIXED 'SWAMP 0 0 0 WHITE CEDi-4R Z-WAMP 0 0 0
DIS7'@RSED LAND 0 0 0 MIXED SWAMP 0 0 1)
HIGH POCOSIN 13 0 0 DISTURSED LAND ct 13 1)
LOW POCOSIN 0 1) HIGH POCOSIN 1) 0 0
SAY FOREST 0 0 0 LOW POCOSIH cl 0 1)
BAY FOREST 0 13 13
IJATER t41,10- HARSH 0 0

342

RATE OP -@@RIT@@T f-.f-jtllJERSIOtj IN HABITAT
AREA 41,
AT THE END OF THE PpojECT PERIOD.
WITH THE PROITECT. AREA I WITH THE PPOJECT.
FROM INACTIVE PEAT MINE TO: TYPE ACRES
TYPE PRO @'EG END R @RESIDENTIAL DEVELOPMENT 0
ROADS AND RIGHTS-OF-WAY 0
RESIDENTIAL DEVELOPMENT 0 0 0 OTHER DEVELOPED AREAS 0
ROADS AND PIGHTS-OF-Wi@@Y 0 0 0 AGRICULTURAL LAND 5756
OTHER DEVELOPED AREAS 0 0 0 DECIDUOUS FOREST 1)
AGRICULTURAL LAND 7 0 5 -WO T EVERGREEN FOREST 799
BY (EAR MIXED FOPE-ST 0
5 = 0 10 @ 102 15 = 2555 20 = 47@48 WHITE CEDAR SWAMP FI
DECIDUOUS FOREST 0 0 0 MIXED SlIJAMP 0
EVERGREEN FOREST 70 5 -20 T DISTURBED LAND 214 4 cl
BY YEAR HIGH POCOSIN 312'
5 = 0 10 @ 202 15 = 500 20 = 798 LOW POCOSIN 1504
111'.'EC, FOREST 0 0 0 SAY FOREST 0
b,1H I TE CEDAR SWAMP 0 0 0 WATER AND MARSH 154?
t 1 I'-'ED WAMP 0 0 0 ACTIUE PEAT MINE 568
DISTURBED LAND ri 1) 0 INACTIVE PEAT MINE 2e?l
HIGH POCOSIN 70 5 20 T
BY YEAR
5 = 0 10 = 35 15 = 87 20 TOTAL 15818
LOW POCOSIH 70 5 20 T
YEAR
5 = 0 1 C, = 1 -67 15 = 413 20 = 6 5
FOPEST 0 0 0
,.-JATER AND MARSH -70 3 20 7
SY 'f'EAP
5 = q.9F, 10 = 1817 15 = 181@ 20 = 1817
ACTIVE PEAT MINE 11 i 20 F

ACCRUED @4NNUALIZE@, H@EITH@T UNITS ACCRUED Af%)r'-4UALI-=D HABITAT UNITS
AT THE EHD OF THE PROJECT PERIOD. AT THE Ef,@c, -jF THE PPOJECT PERIOD.
AREA 1, , -1 #., , A RE A I . 3C R' f-, @! 1 .
1,,-J I T HTHE PF'(-ITE,-7. ',,.) I T H THE Pg@GjZCT. (CONTINUED)
T i'PF SPEC. TYPE SPEI-7. TC7
1 2 3 - 4 - =, 6 7 8 10
1 0 0 C, 0 0 0
0 cl 0 0 0 C,
0 0 0 0
0 ri 0 cl cl
4 -ec-4 I .--: S 7 5 7 2 12 i 0 2 e -27 G 6 127 3 255 '27 cl, Q I I I
5 0 0 0 ID 5 ID 0 1) 0 0 13
lis 13? 71 ? 142 1 283 jQ5 IF6 1
7 0 0 0 0 0 0 0
cl
1 0 0 ci 0 0 cl cl
0 0 0 0 0 ri 0 0 cl 0 0
113 2544 3952 21 C"5 81 12 37 8 9 10 2809 3140 541 86.6 2519 2 4 1 ;-G,
11 345 266 Z, --l. 9 3' 5 159 6 16e. 221 23 0 2?7 202-'
12 1544 1100 1S96 --,75 677 12 254 6198 71'P 71-61 1-2,75 S 7 9EO
I -:: 0 0 ri 0 0 1 ]@ 0 0 C, C, 0 0
14 288 288 1 12 'P t5l 14 38 188 0 0 314 3274
15 40 57 S4 -".8 4: @n
u 15 40 26 0 0 i 7 4
.='O 6 -13 18 l!" 6 2 SS 6 152 153 5 0 4725
7 5?75 8201 5916 3804 8043 T it',776 6244 2172 2-233 2- ? 565@@4

343

PATE OF L44S RATE OF H4;1-@T CONVERSION IN
.TT4T CONQEPSION IN
AREA 2 10 # I AREA 2 , 7: P T 1) #1
WITHOUT THE PROJECT. WITHOUT THE

FROM EVERGREEN FOREST TO: FROM MIXED SIAIAMP TO:
TYPE PRO BEG ENID R TYPE PRO BEG Et-,Ii) R
MIXED FOREST 0 0 0 DISTURBED LAND 1 .251 80 E
WHITE CEDAR SWAMP 0 0 0 HIGH FOCOSIN 0 13 0
MIXED SWA11P 0 13 ri LOW POCOSIm 0 0 0
DISTURBED LAND 3.3 1. 30 E SAY FOREST 0 1) 1)
HIGH POCOSIN 0 0 0 WATIER AND rop,.I;,SH 13 0 0
LOW POCOSIN 0 0 0 ACTIVE PEAT MINE 0 0 0
BAY FOREST 0 0 0 INACTIVE PEAT MINE 0 cl 0
IAATSP AND MARSH 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 0
ACTIVE PEAT MINE 0 0 0 ROADS AND RIGHTS-OF-WAY 0 li I
INACTIVE PEAT MINE 0 0 0 OTHER DEVELOPED APE(--,S 0 0 0
RESIDENTIAL DEVELOPMENT 0 0 0 AGR! .CULTURAL Li44D 0 0 0
ROADS -ND RIGHTS-OF-1.,)AY 0 0 0 DECIDUOUS FOREST 1) ri 0
OTHER DEVELOPED AREAS 0 0 0 EVERGREEN FORES7 a 0 0
."GRICULTUPAL LAND 0 0 0 MI'XED FOREST 0 1) 0
DECIDUOUS FOREST 0 a 0 WH17E CEDAR SlA4MP 0 0 0

RATE OF H@4e.!T,-T CONVERSION lN HABITAT CGNDITIC!t@S,@CEr@ F:-. @il
. _: - - -1
@@IPEvwi 2 #1 AT THE END OF THE @";.IDJEC-71 PERIOC.
k%1ITHOUT T!@E PROJECT. AREA 2 WITHOUT 7HE PRO,77-C-7.

FROM DISTURBED LAND TO: -7Y F E ACFE3
TYPE PRO BEG END R R'ESIDEt-ITIA-L DEVELOPMENT
POADS 4411) PIGHTS-OF-l-,lAY 0
H113H '10COSIN -7.7 1 -2 0 E OTHER DEVELOPEC @'RE.@-= ci
LOW POCOSIN 5.9 1 13 C "GRICULTUPt@,L L.-:41D 10 7 i
Z
BAY FOPEST 0 0 0 DECIDUOUS FOREST
WATER AND MARSH 1) t3 13 EVERGPEEN FOREST
ACTIVE PEAT MINE 0 i 0 FOREST
lNACTIk.)E PEAT MINE 0 0 1) WHITE CED"R S;";-'t,!P
PESIDENTIAL DEQELOPMENT 0 0 1) MIX'ED SWAMP
ROADS At-,ID PIGHTS-OF--WAY 0 0 1) DIS7UP2,ED L@'NC- .45
OTHER DEVELOPED AREAS 13 C. 10 HIGH POCOSIH
t-,GPICULTURAL L@'ND 0 0 0 L014 FOCCSIN
DECIDUOUS FOREST 0 0 0 SAY FOREST
Et,.!ERGPEEH FOREST 5. 9 1 -@o E I.-JATEP. A@ID tli@,PSH
..ED FOREST
0 cl P@-Cl IUE F@EA7 ril',,IE ct
WHITE CEDAR SWAMP 0 0 cl INA-'- TIVE PEAT MINE 0
MIXED SWAMP .4 i 20. E
TC,7AL

344

ACCRUED ANNUALIZED HABITAT UNITS ACCRUED ANNUALIZED HABITAT UNITS
AT THE END OF THE PROJECT PERIOD. AT THE END OF THE @'ROJECT PERIOD.
AREA 2 ' SCENAR 10 # I AREA 2- , SCENAP 10
WITHOUT THE PROJECT. WITHOUT THE PROJECT. (CONTINUED)

TYPE SPEC. TYPE SPEC. TOT.
1 2 3 4 5 6 -1 8 10

1 0 0 0 0 0 1 0 0 0 0 0 0
2 0 0 0 0 0 2 0 0 0 0 0 0
3 0 0 0 0 0 3 0 0 0 0 0 0
4 2 5 7 5 .41 a 193 40 -r 803 4 ?10 428 86 43 Soo 3995
5 13 0 0 0 0 5 0 0 0 0 0 0
6 509 59S 305 38 547 6 611 700 12222 840 .674 6045
7 0 0 0 0 cl 7 0 0 0 0 0 0
8 0 0 0 0 0 8 0 0 0 0 0 0
9 85 64 77 30 17 9 13 85 37 62 77 547
10 355 552 302 113 529 10 401 438 76 121 491 3379
11 1737 1336 1203 178 802 11 334 846 1114 1158 1492 1020f
12 1245 S87 1125 -222 546 12 205 563 5,00 814 110.9 7094
13 0 0 0 0 0 13 0 0 0 0 0 0
14 13 0 0 13 0 14 0 cl 1) .0 0 0
15 0 0 0 0 0 15 0 0 0 0 0 0
16 0 0 0 0 0 11:1 0 0 0 0 ID 0

T 4188 4004 3206 968 3244 T 24,4 2061 3114 2837 4143 3125@

RATE OF HABITAT CONVERSION IN RATE OF HAE'ITI-@T CONVERSION IN
AREA 2. =CENAPIO 4t. AREA _2 , S 0 01
WITH THE PROJECT. WITH THE PROJECT.

FROM AGRICULTURAL LAND TO; FROM EVERGREEN FOREST TO:

TYPE PRO BEG END R TYPE PRO BEG END R

DECIDUOUS FOREST 13 11 rl MIXED FOPEST 0 0 f-i
EYEERGREEN FOREST 0 0 0 10HITE CEDAR -SWAr'lP 0 0 cl
MIXED FOREST 0 0 0 MIXED SWAMP 0 0 0
WHITE CEDAR SWAMP 0 0 0 DISTURBED LAND 0 1 0
MI '-'ED SWAMP 0 0 0 HIGH POCOSIN 0 0 0
[,I.'-;TURF:EC, LAND 0 ri 0 LOW POCOSIN 0 0 0
HIGH POCOSIN 0 0 0 BAY FOREST 0 13 0
LOW POCOSIN 0 11 0 WATER AND MARSH 0 u 0
BA*f FORES*T 0 0 0 ACTIVE PEAT MINE q_ 0 1 211 F
WATER AND MARSH cl 0 0 INACTIVE PEAT MINE 0 0 0
ACTIVE PEAT tlINE 45 1 @13 F RESIDENTIAL DEVELOPMENT 0 0 0
INACTIVE PEAT MINE 0 0 0 ROADS AND RIGHTS-OF-1-dAY 0 0 0
RESIDENTIAL DEVELOPMENT 0 0 0 OTHER DEVELOPED AREAS 0 0 0
ROADS AND RIGHTS-OF-WAY 0 0 0 AGRICULTURAL LAND 0 1) 0
OTHER DEI)ELOPED AREf:@.S 0 0 1) DECIDUOUS FOREST 0 0 0

345

RATE OF W48TT4T @'-:O.NtIERSION IN RATE DF H"617AT C0114k)ERSION IN
AREA 2. -SCENAPIO #1: AREA 3--=Nr@,R10 1*1
WITH THE PROJECT. WITH THE PRO.ECT.
FROM MIXED SWAMP TO: FROM DISTURBED LAND TO:

IYPE PRO BEG END R TYPE PRO BEG END R

DISTIJP13ED LAND 0 1 0 HIGH POCOSIN 0 1 0
HIGH POCOSIN 0 0 0 LOW POCOSIN 0 1 0
LOW POCOSIN 0 0 0 BAY FOREST 0 1) 0
BAY FOREST 9 a a WATER AND MARSH 0 13 13
WATER AND MARSH 0 0 0 ACTIVE PEAT MINE 123 1 12 0 F
ACTI',)E PEAT Ml@)E 3 1 20 INACTIVE PEAT MINE cl 0 0
INACTIVE PEAT MINE 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 01
RESIDENTIAL DEVELOPMENT 0 0 0 ROADS AND RIGHTS-OF-WAY 0 0 0
ROADS AND RIGHTS-OF-WAY 0 0 0 OTHER DEVELOPED AREAS 0 0 f0
OTHER DEVELOPED AREAS 0 0 0 AGRICULTURAL LAND C, Q 0
AGRICULTURAL LAND a 0 0 DECIDUOUS FOREST 0 0 0
DECIDUOUS FOREST 0 0 0 EVERGREEN FOREST 1 0
EVERGREEN FOREST 0 0 0 MIXIED FOREST 0 0
MIXED FOREST 0 0 0 WHITE CEDAR SWAMP 0 1) n
WHITE CEDAR SWAMP 0 0 0 111'.,.ED SWAMP 0 i 0

RATE OF HAE-IT44T CONVERSION lN RATE OF HAB17AT C,---Nk,-'ER3l0N lN
AREA 2 - SC 2' 14; 10 # i , AREA 2 , SC2NI-'R@- @,
WITH THE PROJECT. WITH 7HE PROjEC7.

FROM HIGH POCOSIN TO: FROM LOW POCOSIN TO:

TYPE PRO BEG END R TYPE PRO BE@3 END .9

LOW POCOSIN cl 0 0 BAY FOREST 0 ID 0
BAY FOREST a 0 0 WATER AND MARSH 0 0 9
WATER AND MARSH 0 9 0 ACTI',;E PEAT MINE 1 20 F
ACTIVE PEAT MINE 51 1 F INACTIVE PEAT MINE 13 0 ii
INACTIVE PEAT MINE 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 13
RESIDENTIAL DEUELOPMENT 0 0 0 ROADS AND RIGHTS-OF-14AY 0 0 0
ROADS AND RIGHTS-OF-WAY 0 0 0 OTHER DEVELOPED AREAS 0 0 0
OTHER DEVELOPED AREAS ii 0 a AGRICULTURAL LAND 0
AGRICULTURAL LAND 0 0 0 DECIDUOUS FOREST C.
DECIDUOUS FOREST 0 0 C, EVERGREEN FOREST 0 0 0
EVERGREEN FOREST 13 0 0 MIXED FOREST 0 0 0
MIXED FOREST 0 0 0 IAHITE CEDAR SWAMP 0 0 0
WHITE CEDAR SWAMP 0 0 0 MIXED SWAMP 0 0 0
MIXED SWAMP 0 0 0 DISTURBED LAND 0 0 0
DISTURBED LAND 0 0 0 HIGH POCOSIN 0 0 0

346

RATE OF 1-4AB17,@.T CONIVERSION IN RATE OF HABITAT CONVERSION IN
H'REA 2 z-'C2tlAPIO #1. AREA 2 , #!,
WITH THE PROJECT. WITH THE @POJECT.

FROM ACTIVE PEAT MINE TO: FROM INACTIVE PEAT MINE TO;

TYPE PRO BEG END R TYPE PRO BEG END R

lNf-'CTI,.,lE RESIDENTIAL DEVELOPMENT 0 0 0
1 4 PEAT MINE 300 2 20 F
;;E'SIDENTIAL DEVELOPMENT 0 0 0 ROP-DS AND RIGHTS-OF-WAY 0 0 0
ROADS AND RIGHTS-OF-I,,IAY 0 1) 0 OTHER DEVELOPED AREAS 0 0 0
OTHER DEI)ELOPED AREAS 13 0 1) "GRICULTURAL LAND 240 20 F
,@@GRICULTURAL LAND 0 0 0 DECIDUOUS FOREST 0 0 0
DECIDUOUS FOREST 0 0 0 EVERGREEN FOREST 30 6 20 F
EVERGREEN FOREST 0 0 0 MIX'ED FOREST 0 0 0
WHITE CEDAR SWAMP
r,11EYED FOREST 0 0 0 0 0 0
1.,iHITE CEDAR SWAMP 0 0 0 MIXED SWAMP 1 6 20 F
mi'le.,ED SWAHP 0 0 0 DISTURBED LAND 0 0 0
DISTURBED LAND 0 0 0 HIGH POCOSIN 16.46 20 F
HIGH POCOSIrl 0 0 0 LOW POCOSIN 12.66 20 F
LOW POCOSIN ID 0 0 BAY FOREST 0 0 0
&-)*@' FOREST ci 0 0 WATER AND MARSH 0 3 0
IJATEP 4@JD MARSH 1) 0 0 -'CT!k@E PEAT MINE 0 1 0

H1,8 I TAT COND I T I ONS, CEt,-; P T @',CCPUED INNUt@tL7ZED HHBITAT UIHIT-3
"T THE END OF THE PROJECT PERIOD. AT THE END OF THE PROJECT PERIOD.
2 WITH THE PROJECT. AREA 2 . 3 1: EN " P 10 141
REA
1,11TH THE PROJECT.
-;'!'FE ACRES
TYPE SPEC.
RESIDENTIAL DEVELOKIENT 0 1 2 4 5
POADES "HD RIGHTS-OF-144@,( 0
OTHER DEI)ELOPED AREAS 0 1 0 0 0 0 0
,GPICULTURAL LAND
- 1) 0 0 0 0
DECIDUOUS FOREST 3 cl 0 0 0 0
EVERGREEN FOREST 57,1@ 4 489 1080 367 7,75 115271
HIXED FOREST cl 5 0 0 11 0 0
10HITE CEDAR SWi:;,MP 0 6 2 le. 0 168 '7.1 301
t!IXED c-,l,,JAHP 0 0 0 0 0
DI ST LIP 0 0
- - BE'D LA@!D 4 0 0 0
HIGH POCOcIN 440 57, -3 5 2 i@ -2 -
POCOslIt--l @1138 10 76/ 115,5 655 245 1 146
BAY FOREST ri 1 1 606 466 420 62 280
AND ZlAR'SH cl 12 4:7:4 @3 0 9 S? -3 -7-@ 1
,@@CTIVE PEAT MINE 300 13 0 0 1) 0 0
!!,IHCTII,,'E FEAT MINE 12LIO 14 0 1) cl 0 11
15 21 -,o 11S 15 21
TOTAL 71-12 16 13' 294 231 126 --?4

3 0 2:SS 13 24 S-671

347

ACCRUED ANNUALIZED HABITAT UNITS RATE OF HABITAT CONVERSION IN
AT THE E!@[D 'IF THE PROJECT PERIOD. AREA I SCENARIO 42.
AREA 2 . SCENAP 10 #1, WITHOUT THE PROJECT.
WITH THE PROJECT. (CONTINUED)
TYPE SPEC. TOT. FROM DISTURBED LAND TO:
i 7 1? 10 TYOE PRO BEG END R

1 0 0 0 0 0 0 HIGH POCOSIN 4.6 1 20 E
2 0 0 0 0 0 0 LOW POCOSIN 15.41 220 E
:3 0 0 0 0 0 0 BAY FOREST 1) 0 1)
4 1733 815 1-63 82 5,71 7604 I-OATER AND MARSH 0 0 0
5 0 0 0 0 0 0 ACTIVE PEAT MINE 0 0 0
6 3 3.6 385 672 462 371 3323 INACTIVE PEAT MIHE 0 0 ID
7 0 0 .0 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 0
a 0 0 0 0 0 0 ROADS AND RIGHTS-OF-4JAY 0 0 0
9 5 35 15 25 32 226 OTHER DEVELOPED AREAS 0 0 0
10 867 941? 164 262 1064 7315 A3RICULTUPAL LAND 0 0 0
11 117 295 ass 404 521 3558 DECIDUOUS FOREST 0 0 0
12 -f 1 1916 202 214 387 247lb EVERGREEN FOREST 0 0 0
13 0 0 0 0 a 0 MIXED FOREST 0 0 0
14 0 0 0 0 0 0 WHITE CEDAR SWAMP 0 0 0
15 21 15 0 0 .? 150 MIXED SWAMP 0 0 0
16 273 242 63 63 2 *lm' 1 1953

T 3423 2932 1663 1512 3184 2660-4

RATE OF HASIT4T CONVERSION IN HABITAT CONDITIONS.;C-E@@"F-10
AREA I.-SCEHAPI'D #2, A-r THE END OF THE FROJSCT PSPIOD.
WITHOUT THE PROJECT. "REA I WITHOUT THE PROJECT.

FROM INACTIVE PEAT MINE TO: TYPE "CRES
I

TYPE PRO BEG END P RESIDENTIAL DEI)ELOPMENT 0
ROADS ANb RIGHTS-OF-4AY 0
RESIDENTIAL DEVELOPMENT 0 0 0 o'rHER DEVELOPED AREAS 0
ROADS -4ND RIGHTS-OF-44AY 0 0 0 A13RICULTURAL LAND
OTHER DEVELOPED AREAS 0 0 0 DECIDUOUS FOREST 13
HGFICULTURAL LAND 0 0 0 EVERGREEN FOREST 0
DECIDUOUS FOREST 0 a 0 MIXED FOREST 0
EVERGREEN FOREST 0 0 0 WHITE CEDAR SWAMP 0
MIXED FOREST 0 0 MPKED SWAMP 0
6-lHITE CEDAR SWAMP r! 0 Dl STURSED L,@ND III
MIXED SWAMP 0 0 0 HIGH POCOS!!l 60SZ
DISTURBED LAND 0 a 0 LOW POCOSIN Z050.7
HIGH POCOSIN 0 0 0 eAY FOREST 0
Low POCOSIH 0 a 0 Wi4TER AND MARSH 600
BAY FOREST 0 0 0 .,.t:Tlk,)E PEAT MINE "I
WATER AND MARSH 100 5 20 T INACTIVE PEAT MINE 0
BY YEAR
5 = 0 10 = SOO 15 30d 20 300 70TAL Soooo
ACTIVE PEAT MINE 0 a 0

348

ACCRUED ANNUALIZED HABITAT UNITS ACCRUED ANNUALIZED HABI TAT UNITS
AT THE E7t--j[., CIF 714E PROJECT PERIOD. AT THE ";= THE PROJECT PERIOD.
AREA I SCEN-',PIO 02. AREA I SCENARIO W2,
WITHOUT THE PROJECT. WITHOUT THE PROJECT. (CONTINUED)

TYPE SPEC. TYPE SPEC. TOT.
7
2 a 4 5 It. a 9 10

0 0 0 0 0 0
0 cl 0 0
0 1) 1) cl 0 0 cl 0 0
0 rl cl 0 0 0 0
4 6 4 G_' 1421 486 10 2`6 2 0 225 4 229'5 1060 216 108 756 10.071
5 1) 0 0 0 cl 5 0 0 ci 0 0 0
6 0 0 0 cl cl 6 0 0 0 0 0 0
7
0 0 0 0 0 . 0 0 0. 0 0 0
o 0 0 0 0 8 0 0 0 0 0 0
0 0 0 0 cl 3@ 0 0 0 0 9 0
10 892 1285 759 2C351 IS29 10 1006 ii0l 190 304 1234 3483
11 4424 31403 31363 454 2042 11 851 7,155 28316 2949 3800 25975
12 1 39,@.5 5,,? 4 8 1 262t, 2487 1222 12 2_2 ? .6 3 6504 6887 12435 79583
13 0 0 0 0 0 13 0 0 0 a 0 0
14 114 114 347 446 59 14 15 74 cl 0 124 1292
15 0 0 0 0 13 15 0 13 13 0 0 0
16 14 7"? 23 113 2 ? 16 27 24 6 13 195

T 20057 16211 1_17'@04 4710? T 6489 10747 9752 10254 18371 125601

R.ATE CF HAE?!T,@T Tt-1 PATE '3F @HEJT,@T CONVERSION IN
AREA I _CE!-,@ 'F: ',:; ti - ' A REA I , _=@ 1 G tt
WITH THE PROJECT. WITH THE.FPOJECT.

FROM AGRICULTURAL LAND TO: FROM DISTUPBED LAND TO:

TYPE PRO BEG END R TYPE PRO .9EG END P

DECIDUOUS FOREST 0 0 Q HIGH POCO'llN 0 1 cl
ZVERGREEH FOREST ij 0 0 LOW POCOSIN ci 1 0
H I' ':ED FOREST 0 1) G BAY FOREST 0 ID 0
IdHITE CEDAR SWAMP 0 0 0 WATER AND MARSH 0 cl 0
MIXED SWAMP 0 cl 01 @CTIVE PEAT MINE 4 8, 0 t 20 F
DISTURBED LAND 0 0 0 INACTIVE PEAT MINE 1) 0 0
HIGH POCOSIN 0 0 0 RESIDEt-)TIAL DEVELOPMENT. 0 13 0
LOW POCOSIt-4 0 0 0 ROADS AND RIGHTS-OF-lmIAY C. ct 0
BAY FOREST 0 ri 0 OTHER DEVELOPED AREAS cl 0 0
1@@IATER AND HARSH 0 0 0 AGRICULTURAL LAND 0 0 0
,@I-T I I IE 20 F CECIDUOUS FOREST 0 0 0
I e PEAT MINE 135 1 -
1NACTIVE PEAT MINE fli 0 0 EVERGREEN FOREST 1-j 0 0
RE51DENTIAL DEI)ELOPMENT 0 0 0 MIXED FOREST 0 0 0
ROADS AND RIGHTS-OF-WAY ri - WHITE CEDAR SWAMP 0 0 cl
C MI';l.ED SWAMP 0 0 0
OTHER DEVELOPED :4REP-@S 0 ij 0

349

RATE OF HABITAT CONVERSION IN RATE OF H-@4el--AT CCNVEPSION IN
AREA I SCENARIO 4REA I
WITH THE PROJECT. WITH THE PROJECT.

FROM HIGH POCOSIN TO: FROM LOW POCOSIN TO:

TYPE PRO BEG END R TYPE PRO BEG END R

LOW POCOSIN 0 0 0 BAY FOREST 0 0 0
SAY FOREST 0 0 0 blATER AND MARSH 0 0 a
WATER AND MARCH 0 0 0 ACTIVE PEAT MINE 660 1 20 F.
ACTIVE PEAT MINE 195 1 20 F INACTIVE PEAT MINE 0 0 0
INACTIVE PEAT MINE 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 0
RESIDENTIAL DEVELOPMENT 0 0 0 ROADS AND RIGHTS-OF-WAY 0 0 0
ROADS AND RIGHTS-OF-4,)AY 0 0 0 OTHER DEVELOPED AREAS 0 0 0
OTHER DEVELOPED AREAS 0 0 0 AGRICULTURAL LAND 0 0 cl
AGRICULTURAL LAND 0 0 0 DECIDUOUS FOREST C, 0 C.
DECIDUOUS FOREST 0 0 0 EVERGREEN FOREST 0 0 co
EVERGREEN FOREST 0 0 0 MIXED FOREST 0 0 0
MIXED FOREST 0 0 0 WHITE CEDAR SWAMP 0 0 0
WHITE CEDAR SWAMP 0 0 0 MIXED SWAMP 0 0 0
MIXED S@WAMP 0 0 0 DISTURBED LAND !1 0 0
DISTURBED LAND 0 0 0 HIGH POCOSIN 0 0 0

RATE OF HABITAT CONYERSION IN RATE OF HABI74T CCINVERSION IN
AREA I SCENARIO #-" ' AREA I SCENi-4F-10 Is-.,
WITH THE PROJECT. IAITH THE PROJECT.

FROM WATER AND MARSH TO: FROM ACTIVE PEAT MINE TO:

TYPE PRO BEG 9ND R 7"'PE PRO BEG END R

ACTIVE PEAT MINE 15 1 20 F INACTIVE PEAT MINE IT002 20 F
INACTIVE PEAT MINE 0 0 0 PESIDENTIAL DEVELOPrIFNT 0 1)
RESIDENTIAL DEVELOPMENT 0 0 0 ROADS AND RIGHTS-OF-Ws@',Y 0 0 0
ROADS AND RIGHTS-OF-4,,)AY 0 0 0 OTHER DEVELOPED AREAS 0 11
OTHER DEVELOPED AREAS 0 0 0 #@tGRICULTURAL LAND 12 0
AGRICULTURAL LAND 0 0 ri DECIDUOUS FOREST 1-1 0 cl
DECIDUOUS FOREST 0 0 0 EVERGREEN FOREST ri 0 0
EVERGREEN FOREST C, 1) 0 ML/lED FOREST 12 ri
MIXED FOREST 0 0 a IJHI@E CEDAP 0 Q
WHITE CEDAR SWAMP 0 0 0 MIXED SWAMP 0 0 0
MIXED SWAMP 0 0 0 Co'STURSED LAND 1) 1) 0
DISTURBED LAND 0 0 0 HIGH POCOSIN 13 0 0
HIGH POCOSIN 0 0 0 LOW POCOSIN 0 0 0
LOW POCOSIN 0 0 0 9-@AY FOREST 0 0 0
SAY FOREST 0 0 0 t-dATER AND MARSH 0 0 0

350

RATE OF H9617AT CONVERSION IN HABITAT CONDITIONS.SCEt-,IARIO #2,
AREA i,SCENAPI,--l #--,, AT THE END OF THE PROJECT PERIOD.
WITH THE PROJECT. AREA I WITH THE PROJECT.

FROM INACTIVE PEAT MINE TO: TYPE ACRES

TYPE PRO BEG END R RESIDENTIAL DEVELOPMENT 0
ROADS AND RIGHTS-OF-WAY 0
RESIDENTIAL DEVELOPMENT 0 0 0 OTHER DEVELOPED AREAS 0
ROADS AND RIGHTS-OF-WAY 0 0 0 AGRICULTURAL LAND 16773
OTHER DEVELOPED AREAS 0 0 0 DECIDUOUS FOREST 0
AGRICULTURAL LAND 56 5 20 T EVERGREEN FOREST 2460
BY YEAR MIXED FOREST 0
5 = 0 10 = 1653 15 = 9213 20 = 16773 WHITE CEDAR SWAMP 0
DECIDUOUS FOREST 0 0 0 MIXED SWAMP 0
EVERGREEN FOREST 8.2 5 20 T DISTURBED LAND 0
BY YEAR HIGH POCOSIN 561
5 = 0 10 = 570 15 = 1515 20 = 2460 LOW POCOSIN 1899
MIXED FOREST 0 0 0 BAY FOREST 0
WHITE CEDAR SWAMP 0 0 0 WATER AND MARSH 2907
MIXED SWAMP 0 0 0 ACTIVE PEAT MINE 1500
DISTURBED LAND 0 0 0 INACTIVE PEAT MINE 3900
HIGH POCOSIN 1.9 5 20 T
BY YEAR TOTAL 30000
5 = 0 10 = 130 15 = 345.520 = 561.1
LOW POCOSIN 6.3 5 20 T
BY YEAR
5 = 0 10 = 440 15 = 1169.520 1698.?
BAY FOREST 0 0 0
WATER AND MARSH 5. - 5 20 T
BY YEAR
5 = 0 10 = 2907 IS = 2907 20 = 2907
ACTIt)E PEAT MINE 15 1 20 F

ACCRUED ANNUALIZED HABITAT UNITS ACCRUED ANNUAL-'ED HABITAT UNITS
,@L.T THE EFID OF THE DROJECT PERIOD. AT THE END OF THE PROJECT PERIOD.
IARI Cl
AREA AREA I , @K0 #Z-
WITH THE PROJECT. WITH THE PROJECT. (CONTINUED)

,YPE SPEC. TYPE SPEC. TOT.
1 2 :3 4 5 6 7 8 9 10

0 0 0 0 0 1 0 0 0 0 0 0
2 0 0 0 0 cl 2 0 0 0 0 0 0
0 0 0 0 0 3 0 0 C. 0 0 0
1564 2453 1172 2476 488,6 4 5528 2606 521 261 1,;24 242,01
5 0 0 0 0 u 5 0 0 0 0 0 0
983 6 4 4
56 418 214 21 27 90 855 58S 4i .2 4229
0 0 7 0 0 0 0 0
0 13 0 0 1) 0 cl 0 13
9 cl 0 0 0 li 9 0 0 0 0 0 0
10 2143 S32? 1824 684 3192
10 2417 2645 456 7,30 29-64 20363
11 1603 123S 1110 164 740 11 308 781 1028 1069 IS77 '9414
12 5079 S618 4592 5-04 2226 12 835 2296 2365 2505 4522 -28942
1@ 0 0 0 0 0 13 0 0 0 0 0 0
14 467 467 1422 1829 244 14 61 305 0 0 508 5304
15 105 151) 90 75 105 15 105 75 0 0 45 750
16 714 !537 1208 65? 1537 16 14274 1263 329 329 11-7108 1ID211

T 12021 14206 1111.5'32 A-81-9 13213 T 11118 10460 5554 5481 12920 1025S-

351

RATE OF L448!T--T CONVERSION IN PATE OF HABITAT CONVERSION IN
AREA 2 SCENARIO #2, AREA 2 SCEN,@.Rjo
WITHOUT THE PROJECT.
WITHOUT THE PROJECT.
FROM EVERGREEN FOREST TO: FROM MEXED SWAMP TO:
TYPE PRO BEG D40 R TYPE PRO BEG END R
MIXED FOREST 0 1 0
)ISTUPbED LAND 3.751 so E
WHITE CEDAR SWAMP 0 0 0 HIGH POCOSIN 0 13 0
MIXED SWAMP 0 0 0 LOW POCOSIN 0 0 0
DISTURBED LAND 2.0,71 30 E SAY FOREST 0 0 0
HIGH POCOSIN 0 0 0 WATER AND MARSH 0 a I?
LOW POCOSIN 0 0 0 ACTIVE PEAT MINE cl 0 co
BAY FOREST 0 0 0 XNACTIVE PEAT MINE 0 0 0
WATER AND MARSH 0 0 li RESIDENTIAL DEVELOPMENT 0 0 0
ACTIVE PEAT MINE 0 0 0 FROADS AND RIGHTS-OF-WAY 0 0 0
INACTIVE PEAT MINE 0 0 0 OTHER DEVELOPED AREAS 1) 0
RESIDENTIAL DEVELOPMENT 0 0 0 64GRICULTURAL LAND 0 0 0
ROADS AND RIGHTS-OF-44AY 0 0 0 DECIDUOUS FOREST 0 0 0
OTHER DEVELOPED AREAS 0 0 0 E-@,IEPGREEN FOREST 0 0 0
AGRICULTURAL LAND 0 0 0 Ml,-@,ED FOREST 0 0 0
DECIDUOUS FOREST 0 0 )a WHITE CEDAR SWAMP 0 0 0

PATE OF HABITAT CCI-IVERSION IN HABITAT
AREA Z, . 10 42'. 94T THE END OF THE I@FOJECT PERIOD.
WITHOUT THE PROJECT. 4REA 2 WITHOUT THE.PROjECT.

FROM DISTURBED LAND TO: T'YPE ACRES

TYPE PRO BEG END R RESIDENTIAL DEVELOPME'lT ID
ROADS AND P.IGHTS-OF-4,vlAY 0
HIGH POCOSIN 4.7 1 20 s OTHER C-Et@ELOPED AREAS cl
LOW POCOSIN 12.51 20 E AGRICULTURAL 1-AND 1200
BAY FOREST ri 0 0 DECIDUOUS FOREST
WATER AND MARSH 0 0 0 El.'ERGPEEN @=OFEc-T 90 1
P-ICTIVE PEAT MINE 0 1 0 MIXED FOREST
INACTIVE PEAT MINE 0 0 0 1.0HITE CEDAR SWAMP
RESIDENTIAL DEVELOPMENT 0 0 0 "lIXED SWAMP 2 7
ROADS AND RIGHTS-OF-WAY 0 0 0 DISTURBED LAND 2' 14
OTHER DEVELOPED AREAS 0 0 0 HIGH POCOS!!'-l I. @-' 4 5
AGRICULTURAL LAND 0 0 ri LOW POCOSIN 8914
DECIDUOUS FOREST 0 0 0 BAY FOFEST 0
EVERGREEN FOREST 2.1 1 20 E WATER AND tlARSH lEo
MIXED FOREST 0 0 0 ACTIVE PEAT MINE 0
WHITE CEDAR SWAMP 0 0 0 ;NACTIVE PEAT MINE 0
MIXED SWAMP .8 1 20 E
TOTAL 15000

352

ACCRUED HH617AT UNITS ACCRUE7i @@H']L,'LIZED HASITAT UNITS
,-@T THE END DF THE cR'OJECT PERIOD. AT THE END CiF THE PIPOJECT PERIOD.
AREA 2,SCEt4_iPIO #22' AREA S!CF!424;-'IQ #2
.,,lITHOL'T THE PROJECT. WITHOUT THE PROJECT. (CONTINUED)

TYPE SPEC. TYPE SPEC. TOT.
1 2 3 4 5 6 8 9 10

1 0 0 0 0 0 1 0 0 a 0 ID 0
2 0 0 1-1 cl cl 2 0 0 13 0 0 0
3 13 13 1-1 0 0 3 cl 0 0 0 cl 0
4 2S8 636 216 456 900 4 1020 480 96 48 336 4476
5 0 cl 0 13 0 5 0 0 0 0 0 0
6 4--4 5113 260 -13 467 6 521 5?7, 1042 716 5"75 5154
- 0 0 0 ct 7 1) 0 0 0 0 0
e 0 0 0 0 0 0 13 1) 0 0
'84 214 2 5S 101) 55 44 '2 8 4 125 207 258 1 19 3 0
io Z1. 8 432 *227 414 10 ?, 13 343 59 1715 2`8 4 2644
11 246? 1 1710 253 1140 11 475 1203 1583 1046 2121 14499
12 '1610 4288 5570 1097 2'700 12 1013 2785 286? 3038 5485 35106
13 0 0 0 0 13 0 0 0 0 0 0
I le
14 -35 S5 105 135 is 14 5 23 0 0 392
1.5 ID 0 0 0 0 15 0 0 0 0 0 0
1 It.0 1) fj 0 0 1.6 0 0 0 0 0 a

T ?948 311-4 '3355 2162 569-4 T 3351 5714 57-4 5750 01?S 64100

FATE It-4 RATE :-",:: H@F,T-.t:@@ CONQERSION IN
APE@4 2 AREA 2 :42,
,11TH @HE ZPlOJEC7. IJITH THE PROJECT.

FROM A'__,PIC'l_lLTUPAL L@4t,]D TO: FROM E'.)ERGREEtl FOREST TO:

7iPE P F, 0 SEG Ei,jD P Tf F E PRO BEG END R

FORESIT 9 0 0 MI@ED FOREST
E'i'=_RGPE=_H FOREST cl 0 I'D 1,,JHITE CEDHP SWAMP cl 13 0
MIXED FOREST cl 0 0 M.IXED SWF41-IR 0 0 0
WHITE 1-7H-DAR @EWAMP _1 cl 13 Dl'-TURBED LAND 0 1 cl
t'l F".ED SWAMP 0 0 H113H ROCOSIN cl 0 0
C.-I :_:.Tl_'F*BED LAND 0 0 cl LOW POCOSIN 0 G C,
HIGH P0CO.-_-.'IN 0 SA'r 7OR'E_T 0 ID cl
Fo@@CiSlt,l t". cl W,,TER AN@ MARSH 1) 0 1-,
EA'i' PC-iPEST 0 1? C. ACTlk@'E PEf@iT M11,1E 16 1 20 F
WATER i4ll) MARSH 0 ri cl 1NACTI',E PEAT MINE cl 0 a
CTII,'E PEAT VIINE .60 1 F RESIDENTIAL DEVELOPMENT 0 0 0
IHACTIVE FEi-@T MINE r! 0 0 ROADS AND RIGHTS-OF-IA'Y 0 0 0
RESIDEtITIAL DEVELOFME@lT 0 1? 0 OTHER DEQELOPED AREAS 0 11
ROADS AND RIGHTS-OF-1.,Jf@@r' 0 0 11 @@GRICULTIJRAL LAND 0 0 i:!
OTHER DEVELOPED AREAS 13 I'D 0 DECIDUOUS FOREST 1) 0 0

353

RATE OF L44e!'ri;T S"MYERSION IN RATE OF HAEIT@4T CONVERSION IN
C -4
AREA 2. SCENARIO 42. AREA 2 SCEN@"P.10 42,
WITH THE PROJECT. WITH THE PROJECT.

FROM MIXED SWAMP TO: FRCM DISTURBED LAND TO-

TYPE PRO BEG END*R TYPE PRO BEG END R

DISTURBED LAND 0 1 0 HIGH POCOSIN 13 1 0
HIGH POCOSIN 0 0 0 LOW POCOSIN 0 11 13
LOW POCOSIN 0 0 0 BAY FOREST .0 0
BAY FOREST 13 0 1) WATER AND MARSH 4j Q 0
WATER AND MARSH 0 0 0 ACTIVE PEAT MINE 1105 1 2-10 F
ACTIVE PEAT MINE 22.51 20 F INACTIVE PEAT MINE ri 0 0
INACTIVE PEAT MINE 0 0 0 RESIDENTIAL DEVELOPMENT 0 1) 0
RESIDENTIAL DEVELOPMENT 0 0 0 PQ@4DS AND PIGHTS-OF-44AY 0 0 ID
ROADS AND RIGHTS-OF-4AIAY 0 0 0 OTHER DEVELOPED AREAS 13 0 0
OTHER DEVELOPED AREAS 0 0 0 AGRICULTURAL LAND 4) 0 0
AGRICULTURAL LAND 0 0 0 DECIDUOUS FOREST 0 0 1)
DECIDUOUS FOREST 0 0 0 EVERGREEN FOREST Q 1 0
EVERGREEN FOREST 0 0 0 MIXED FOREST 11 0 0
MIXED
FOREST 0 0 0 WHIrE CEDAR SWAMP 0 0 0
WHITE CEDAR SWAMP 0 0 0 M I SWAMP 0 1 a

PATE OF HA6l'r,:4T CCHVERSION IN PtW7-E OF H"817-T CONVERSION IN
@,REA 2 , SCE!%:o;R,-' #@-. A P, E: A -- ,
14ITH THE PROJECT. WITH THE @'JEC7.

-@W POCOSIN TO:
F-POM HIGH POCOSIN TO: FPC-M LC

TYPE PRO BEG END P TYPE PRO EEG END R

LOW POCOSIN fi 0 0 BAY FOREST 1) 0 1-3
BAY FOREST 0 0 0 bdATER AND MARSH cl 13 13
1.@ATER AND MARSH 0 a 0 ACTIVE PEAT MINE ri F
ACTIQE PEAT MINE 135 1 21 0 F: I@IACTII)E PEAT MINE 1) 0 C,
!Ni4CTIVE PEAT MIHE 0 0 0 RESIDENTIAL DEI)ELOPMENT 0 0 0
RES I DENT IAL DEVELOPMENT 0 0 13 ROADS AND PIGHTS-OF-W2Y A C!
p,---,F4DS AND RIGHTS-OF-I,,IA'( 0 0 0 OTHER DEVELOPED APE@-S 0 ll
OTHER DEVELOPED AREAS 0 0 0 AGRICUL71jRiaL L--ND
.,4GPICULTURAL LAND 0 0 ri DECIDUOUS FOREST
DECIDUOUS FOREST 0 0 0 E@)ERGREE-14 FOREST 0 11
EVERGREEN FOREST 0 0 0 MIXED FOREST 13 0 0
MI',@ED FOREST 0 Q 13 WH17E CEC-AP SWAMP 0 0 1)
b3HITE CEDAR SWAMP 0 11; 0 MI*X.IED SWAMP 0 0 113
MIXED SWAMP 0 cl DISTURBED LA14D ri ri 0
DISTURBED LAND 0 0 0 HIGH POCOSIN 0

35 4

RATE 05 HABITAT CCNl.TRSIOt,j IN PATE OF HAeTT"iT CONVERSION IN
AREA 2 SC0:HPIO 42', AREA 2 , ;-C-EHAPl:-j #7
WITH THE PRuJECT. WITH THE PROJECT.

FROM WATER AND MARSH TO: FROM ACTIVE PEAT MINE TO:

TYPE PRO BEG END R TYPE PRO BEG END R

ACTIVE PEAT MINE 7.5 1 213 F INACTIVE PEAT MINE 750 2 20 F
INACTIVE PEAT MINE 0 0 0 RESIDENTIAL DEVELOFMENT 0 0 0
RESIDENTIAL DEVELOPMENT 0 0 0 ROADS AND RIGHTS-OF-WAY 0 0 0
POim@DS AND RIGHTS-OF-WA'-( 0 0 0 OTHER DEt)ELOPED AREAS ri 0 0
OTHER DEVELOPED AREAS 1) 0 0 HGRICULTURAL LAND 0 0 0
AGRICULTURAL LANE cl cl 0 DECIDUOUS FOREST cl 0 0
DECIDUOUS FOREST 0 0 0 El,jEPGREEN FOREST 0 0 cl
EVERGREEN FOREST cl 0 cl MIXED FOREST 0 0 0
MIXED FOREST 0 0 0 WHITE CEDAR SWAMP 0 0 0
WHITE CEDAR SWAMP 0 0 0 MI';<ED SWAMP 0 0 0
111'KED SWAMP 0 0 0 DISTURBED LAND 0 cl 0
DISTURBED LAND 1) 1) 0 HIGH POCOSIN 0 0 0
HIGH POCOSIN 0 0 0 LOW POCOSIN 0 0 0
LOW POCOSIN 0 0 0 BAY FOREST 0 0 0
BAY FOREST 0 0 0 WATER AND MARSH 0 0 0

PATE OF HHEITAT CONVERSION IN
AREA 2 , 42, HA B I TAT C ON D I T: ON S CEI I -- P 0 #27 .
WITH THE PROJECT. AT THE END OF THE PROJECT PERIOD.
AREA 2 WITH THE PPO,',ECT.
PPOM Il!HCTIl.lE REH7 MINE TO: TYPE ACRES
TYPE P PO BEG END R RESIDENTIAL DEVELOPMENT 0
RESIDENTIAL DEVELOPMENT 0 ci 0 ROADS AND R!GHTS-OF-(,,-A'Y 0
ROADS AND RIGHTS-OF-WAY 0 13 ri OTHER DEVELOPED AREAS ri
OTHER DEUELOPED AREAS ri 13 cl AGRICULTURAL LAND 1718 4 c
@4GRICULTURAL LAND 6-t, 5 220 T DECIDUOUS FOREST 0
E`( r'EH'P EVERGREEN FOREST i @ 2 0
5 = 0 10 = 2280 15 6060 9S40 MIXED FOREST ci
DECIDUOUS FOREST 0 0 0 WHITE CEDAR SWAtlP 0
EVERGREEN FOREST 3.2 5 20 T MEXED SWAMP 54
BY YEAR DISTURBED LAND 0
HIGH POCOSIN .32.
5 = Q 10 = 2@'5 15 1-5 ..520 1222" 0 L04J POCOSIti 856
t-,l I X E DFOREST I'D cl BAY F 0 RE ST 0
WHITE CEDAR !EWAMP ij 0 W-'TEP AND MARSH I
MIXED @WAMP .4 5 20 T ACTIVE PEAT MINE 750
By YEAR INACTIVE RE,4T MIHE 11@10
5 = 0 10 = 12.4 15 22.,;, 20 = 53.5 -
DISTURBED LHND 0 0 0
HIGH POCOSIN 2.1 5 ---,0 T TOT A L 15000
BY (EAR
5 = cl 10 74.2 15 197.720 = 3 --- 0 . 'P
LOW POCOSIN 5.7 5 2 0 T
BY "EHR
5 = 0 113 11:8.215 52-6.720 = 255.6
BAY FOREST 0 ri 0
;,.)ATER -41D HARSH 0 5 0
i.@CTIIJE PEAT HINE 0 0

355

ACCRUED ANNUALI, ED HABITAT UNITS HCCRIJED ANNUALI2ED HABITAT UNITS
AT THE END 171F THE PROJECT PERIOD. AT THE X
I _ND OF 7HE @@POjECT PERIOD.
AREA 2 . SCENAR.'O #2, @PEA 2 . SCENAPIO #2.
WITH THE PROJECT. 'W I TH THE PROJECT. kCONTINUED)

TYPE SPEC. TYPE SPEC. T CIT
t 2 3 4 5 .6 7 8 9 10

1 0 0 0 0 0 1 0 1) 0 0 il 1)
2 0 0 0 0 0 Z, 1) 13 0 13 1) 0
i) 13
a 0 1) ri 0 0 2 0 0 0
4 991 -1189 744 1570 3098 4 351 i t652 S 3 0 i O's 1157 154rj::
5 1) 13 1) 0 13 5 0 0 0 13 1?
6 400' 477 244 30 43-@ 6 4G7 5se 975 670 5 S S
7 0 0 0
8 0 0 1) 0 13 ri 0
9 179 135 163 63 35 9 28 1 79 50
10 469* 728 399 150 698 10 5:29 5 7 0 100 60
ti to9l 339 ?55 t12 504 1.1 21.0 53! 727 ?__ 640
12 2723 1939 2462 485 1103 12 448 1231 12 0 3 1.343 2424 15515
13 0 0 0 0 1) 13 0 0 0 0 C,
14 16 116 50 .64 ? 14 2 11 '1 0 1
15 53 75 45 38 5 3 i S 51 2. .0 3 5
16 34e 749 5S8 321 74'@' 10 0 @, 5 -S 1 !5 i 60, 16", 3:_::8 4 97 3:'

T 6276 7140 5449 2 8 3 2 6775 T '5 9 6 2, T 3 361 Z, ,:, 3 1@ 6 5 S, 3 0

RATE OF Ht@i-BITAT CONQERSION lN RATE -_iF CONt"ERSION IN
AREA 3. SCENI-iP"i 42, AREi, 3
WITHOUT THE PROJECT. WITHOUT THE PROJECT.

FROM MIXED SWAMP FRCM DISTUPBEiD L@f,-* 7.0
TYPE PRO BEG END F 7YPE P P 1:1 SE G END R

DISTURBED LAND Zol::5 i "' 0 E HIGH POCOSIN I Z .41 2 .0 E
HIGH POCOSIN 0 0 a LOW POCOSIH 3.3 1 -: @, =
LOW POCOSIN 0 13 ri SAY FOREST 13 0 43
EAY FOREST 11 0 13 1,,)ATER AND MARSH 0 0 1)
WATER AND MARSH G 0 0 ACTII)E P5@T r-jT1,j= a 0
ACTIVE PEAT MINE ru 11 a INAC-Ik.lE PEAT M!'JE 01 0 !D
INACTIVE PEAT MINE 0 0 0 REE I DENT! 'L C-El 'ELOPMENT 0 _1 0
RESIDENTIAL DEVELOPMENT 0 0 0 F,.&@41)-, @,ND RIGHTS-OF-I@JAY 0
ROADS AND RIGHTS-l_)F-(,W( 0 ri @l OTHEP DEk.)ELOREI,
OTHER DE')ELOPED AREAS 0 0 ri AGRI CULTUR#@-.L LHND cl ri ri
AGRICULTURAL LAND 0 0 0 DECIDUOUS FOREST 13 C,
DECIDUOUS FOREST 0 0 0 0JERGREEN FOREST 0 1
EVERGREEN FOREST 13 0 0 MIXED FORES7 0
MIXED FOREST 0 0 0 WHITE CEDi-4.R SLI(-4MP 13 'D ID
WHITE CEDAR SWAMP 0 0 0 MIXED SWAMP 4.3 1

356

HABITAT CONDITIONS, SCENARTO 4@,
-1 ACCRUED ANNUALIZED HABITAT UNITS
AT THE END OF THE PROJECT PERIOD. AT THE END OF THE PROJECT PERIOD.
AREA 3 WITHOUT THE PROJECT. AREA 3, SCENARIO #2',
TYPE ACRES WITHOUT THE PROJECT.
TYPE SPEC;
RESIDENTIAL DEVELOPMENT 0 1 2 -2 4 5
ROADS AND RIGHTS-OF-WAY 0
OTHER DEVELOPED AREAS 0 1 0 0 0 0
AGRICULTURAL LAND 0 171 0 ri 0 0 0
DECIDUOUS FOREST 0 3 0 0 0 0 0
EVERGREEN FOREST 0 4 0 0 cl 0 0
MIXED FOREST 0 5 0 0 0 0 0
WHITE CEDAR SWAMP 0
el 0 0 cl 0 0
MIXED SWAMP 163 7 0 0 0 0 0
DISTURBED LAND 533 9 0 0 0 0
HIGH POCOSIN 1?979 -96 59,9 722 2779 155
LOW POCOSIN 5325 10 824 1280 701 263 1227
BAY FOREST 0 11 142?5 10'P'P6 98?7 1466 6598
WATER AND MARSH cl 12 2567 2541 3225 635 1563
ACTIVE PEAT MINE 0 13 0 0 0 0 0
INACTIVE PEAT MINE 0 14 0 0 0 0 0
15 0 0 0 0 0
TOTAL 26000 16 0 0 0 0 0

T 1@,432 15410 14546 2643 9544

ACCRUED APINUOLIZED HFwiB17AT LINIT-1 RATE OF HABITAT CONVERSION IN
AT THE END OF THE PROJECT PERIOD. AREA .3 M@ lf@ T
AREA Z@ - -::CEtJ-'P!C' i*--, WITH THE PROJECT.
14ITHOUT THE PROjECT. (CONTINUED)
TYPE SPEC. TOT. FROM Ml.*@@'ED SWAMP TO:
6 10 TYPE PRO BEG END R
1 0 0 0 J3 1) 0 DISTURBED LAND 0 1 0
2 0 0 0 cl 0 HIGH POCOSIN 0 0 0
:3 0 0 0 0 13 0 LOW POCOSIN 0 Ill
4 0 0 cl 0 0 SAY FOREST 0 0
5 0 0 0 0 Fi 0 WATER AND MARSH 0 0 0
0 13 .0 0 0 ACTIIIE PEAT MINE 7 1 20 F
0 0 cl INACTIVE PEAT MINE 0 Q 01
0 0 cl 0 0 RESIDENTIAL DEVELOPMENT 0 0 0
9 124 - 351 5 7 9 72- 5 126 ROADS AND RIGHTS-OF-WAY 0 0 0
10 1? 2 9 jol-, 175 2-181 1140 7 8 13 11 OTHER DEVELOPED AREAS 0 0 0
11 2 7 f4 6964 9' z,4 '?530 12-179 82940
- - HGRICULTURAL L,@41D 0 0 0
12 586 1 .6 12 1@61 1759 2.1-76 Z, 0 --l 2 5 DECIDUOUS FOREST 0 11 Fj
13 0 0 0 13 1) cl Et)ERGREEN FOREST 0 0 0
14 0 cl ol Q 0 MIXED FOREST 0 0 0
15 0 11 0 ID 0 13 WHITE CEDAR SL.4@4MP 0 0 0
16 0 0 0 0 0

T 4289 10289 11352 12148 17318 1172) 8

357

RATE OF HARITAT CCHVERSION IN FATE OF H"Fl--;,T @Ctlt 'ERSION !rl
AREA 3 , :-CEN-P 1 *2. A R E,, -S . 3 CEN fw4 R T j it.-I ,
WITH THE PROjECT. H -1 H E p R 0 -,. so T .

FROM DISTURBED LAND TO: FROM HIGH POCOSIN TO:

TYPE PRO BEG END R TYPE FPO e E (3 END R

HIGH POCOSIN 0 1 0 LOW POCOSIN 0 0 13
LOW POCOSIN 11 1 0 SAY FOREST 13 a 0
SAY FOREST 0 0 0 WATEER AND MARSH 1) 13 a
WATSR AND MARSH 0 0 0 ACTIVE PEAT MINE 7 13 0 i 20 F
ACTIVE PEAT MINE 39 1 20 F INvACTP,,lE PEAT MINE 1 0
INACTIQE PEAT MINE 0 0 0 RESIDENTIAL DEVELOPMENT 0 1-1 Q
RESIDENTIAL DEVELOPMENT 0 0 0 ROADS AND RIGHTS-OF-1.4""y' 0 0 'i
ROADS AND RIGHTS-OF-WAY 0 0 0 OTHER DEVELOPED AREAS cl cl
OTHER DEVELOPED AREAS 0 0 0 AGRICULTURAL LAND 0 0
AGRICULTURAL LAND 0 0 0 DEC.;DUOUS FOREST 10 C. 6
DECIDUOUS FOREST 0 0 a EVERGREEN FOREST 0 1) 0
El,'ERGREEN FOREST 0 1 0 MI,.'ED FOREST 0 1) 0
MIXED FOREST 0 0 0 WHITE CEDAR SWAMP 0 1 0
I.-JHITE CEDAR SWAMP Ll 0 a 0 0 0
MIXED SWAMP 0 0 DISTUREPED LAND 0 0

PAT-71' OF --CriVEPSION lN RATE OF L4r-ETT
AREA. AP&
WITH THE PROJEC7. WITH THE PRO,-'ECT.

FROM LOW POCOSIN 70: FRCM ACTIVE P_=.-;T MINE TO.-

TYPE PRO BEG END R T'-@ P E PRO SES END R

SAY FOREST 0 0 0 INACTIVE PEA7 !@IIINE IS 0 1) Z 2 li
-)ELOFMENT 1) Fj
1-.JATEP AND MARSH 1) ri 13 R'ESIDENTIAL DV
ACTIVE PEAT MINE 208 1 20 F PC-IDS c' 1). 1)
!N#;4CTP-)E PEAT MINE 0 13 13 OTHER DEVELOPED 1) 1) i-I
RESIDENTIAL DEI)ELOPt-,IENT 0 cl 0) AGRICLILTURr-iL L111D 1-, 0 0
POADS AND RIGHT@--l)F-l.jAt' ri 13 --ECIS-UOUS FOPE`T ct II
REEST
OTHER DEYELOPED 4REAS c: 0 ri El.)ERGPEEN FOF u 0
"GRICULTUPAL LAND 0 cl 0 HIXED FOREST
DECIDUOUS FOREST 0 13 0 WHI'7*E CEDP@4P
EVERGREEN FOREST 0 a 0 --j
',!I' ED FOREST 0 0 0 0 0 0
1s.lHITE CEDAR SWIAMP 0 cl 0 H113H POCOSI'l i) J-j 1)
M I. @ED SWAMP 0 0 L01,' POCOSIN, 13
0 0 0 FOREST .1
C-ISTUPSED Li4ND
HIGH POCOSIN 0 0 .0 "ND MARSH 0

358

0 fj U)
f2-

w C. 0 Ol a) C.
C@ 0 a.
0 Ix co C. Ol
L) `0 C:) V @T (1) r@ "0
- @l C) C) C) - 17@ 0 IT C. m a, 01 (,A vj
0 Ix Z
w Z, w lr@ll) 10")
LL
7

TOj
Lj.j LIJ F- W L) r.,) r, In 0, c@
Lj -@ z ca uj Q C@ C- N C, --r If) -r
0 W w 0-) a-
w -1 z -1 T Ix fo
LIL 0 Ll- IL W (I Q,
Ol w oow w -1) In (171 cli
= W OL -i 1 110 CL z .0 .., (" r@ C@
0 :E w (1) z w r,I C:. .7) -T '4C. C' 11 1 r) rl)
w :;@ @- C@ 11 x z
w 3: w -i w w cri @ a LLJ
Cj L. Ll Ix OK (r) z w 2: 0 rrj
C.1 0 - Cl _j 0 0 1 z 11
-i LY -) 'I U- LL ILI) M CL j
Ln
.1 ul w w <1 x z C, Pj r.j (A
C.) Z Z Ix q0ow0ow
_; W (n a
w CL @-ZIA@-Dwow2w0owzCI-W LLI LU
z a 0 J 0 W LL 0 (0 111 0 0 11: 4 . T tl@
"T LU fn w D D Q@ ky LL Cl 0 LLJ LLI Lu C.) "0 f,-
0 ix u C, 0 a w a D M LL M :@ D a:
W L) (Y @- 'I T W '4C. P I
w 0 q x a- w X (.i w F-
'I F- Lk@ WOF-ow-:,-y :x 2 2 3.@- @- a X a_
0 'T a I.) Z @- I
X @j I <1 F-

OD ID C, 10
'40 1711 @- It
IN

z C. 11 CD
W Pj c. 0 (14 C-1
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z m C. 1=1 C, I[-) C) III to C, C. in cri r
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w w :E uj -i w w 11 :3 11 C.) if O-j -
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0 a- - C, -1 000 C. F- j D 0@ 0 .11 C- (I. C,
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Cl- uj IX w 1:1 z <1 P@ 0 .7, C-. 0 -Z, F.) C.
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tj- a: z Z -1 c) -i m 0 u I L'If LL- cl., m C. Q@ -) ly CX 11 , . T C, C,
M w D q D CL '1 .1 CL 11- .1 C, 1: 0 w ul w f"ll 1- 0
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PATE OF @404BIT"'T CONVERSION IN Po;@,TE j--,F HA2:@-T CCINVERSION 'N
AREA 4, :-'CT-NAP!O 42-, FEA 4, m2,
WITHOUT THE PRO,:iECT. WITHOUT THE PROJECT.

FROM WHITE CEDAR SWAMP TO: FROM MIXED SWAMP TO:

TYPE PRO BEG END P (PE PRO BEG END R

MI'-,,'ED SWAMP 0 0 0 DISTURBED LAND 25 4 so E
DISTURBED LAND 1 2251 80 E HIGH POCOSIN Of 0 Ij
HIGH POCOSIN 6 o 0 LOW POCOSIN 0 0 0
LOW POCOSIN 0 0 0 2AY FOPEST 1) 0 0
SAY FOREST 0 0 0 WATER AND MARSH 0 0 0
14ATER AND MARSH 0 0 0 ACTIVE PEAT MINE 0 1 0
ACTIVE PEAT MINE 0 0 0 INACTIVE PEAT MINE 0 0 0
INACTIVE PEAT MINE 0 0 RESIDENTIAL DEVELOPMENT 0 0 0
RESIDENTIAL DEVELOPMENT 0 ri 0 ROADS AND RIGHTS-OF-44AY 0 0 0
ROADS AND RIGHTS-OF-44AY 0 0 0 OTHER DEVELOPED t:4REAS cl 0 0
OTHER DEVELOPED AREAS 0 0 0 #L@GPICULTUR44L LAND 0 0 fj
AGRICULTURAL 13 cl 13 DECIDUOUS FOREST 0 0 a
DECIDUOUS FOREST 0 0 0 El.'ERGREEN FOREST 0 0 0
EVERGREEN FOREST 0 0 11VIED, FOREST cl 0 cl
MIXED FOREST 0 0 WHIiE CEDAR SWAMP cl r, cl

RATE CF H SIT4iT IN P,47E -:F CC-NIJERSION IN
AREA 4- 42, AR EA 4, :*21
WITHOUT THE PROJECT. 'Aj [ THOUT 7HE PF;Ol-=.

FROM DIS71JRBED LAND 70. FROM BAY FOREST 70:

TYFE T' PE PRO SEG E N'l: P
PRO EEG END P

HIGH POCOSIN 5.3 -20 E Wi,.TER AND- I-IARSH 0 0
LOW POCOSIN 16.4 1 70 = .,i',7:1.'E PEAT MINE cl 0 01
SAY FOREST I 1 20 E ItIACTII)E PEAT MINE (3) 0 0
10ATER "D MARSH 0 0 RESIDENTIAL DEVE: OPMENT 0 cl 0
0 1 ri ROADS AND RIGHTS-OF-W-'i 0
ACTIVE PEAT MINE 1 0 0
IN-C'71UE PEAT MINE cl 0 co 07HEP DEYELOPED 1) cl
RESIDENTIAL DEVELOPMENT 0 0 0 @GPICULTUP"!- L,@44D 10
R.IGHTS-OF-WAY 0 0 0 DEC-1-DUOUS Frlp.E:@! !j 0
OTHER DEVELOPED AREAS 0 0 0 EQERGREEN FOREST 0 0
L@'ND 13 0 0 FOREST 0 0 13
DECIDUOUS FOREST 0 li 0 WHITE CEDAR SWAMP 0 13 1)
ElljEPGREEN FDr-.'.E-TT 0 1 0 i,l,:."ED SWAMP 1 0 li
MIXED FOREST 0 0 ij DKS'rUR2ED LA!-lD 01) E
2, 0 E
WHITE CEI`t@R SWAMP .2 1 HfGH POCOSIN 0 1)
MIXED !SWAMP 6.4 1 2, 0 E LOW POCIDS11N 0 0 0

360

HABITAT CONDITION-E
AT THE END OF THE :)POJECT PERIOD. ACCRUED ANNUAL17ED HABITAT UNITS
AREA 4 WITHOUT THE PROIJECT. AT
A THE END OF T@F PROJECT PERIOD.
AREA 4, SCEN,4PIO 42,
TYPE ACRES WITHOUT THE PROJECT.
RESIDENTIAL DEVELOPMENT cl TYPE SPEC.
ROADS AND RIGHTS-OF-WAY 0 1 2 3 4 5
OTHER DEVELOPED AREAS 0
AGRICULTURAL LAND 1 0 0 0 0 0
2.60 cl
DECIDUOUS FOREST ri -
EVERGREEN FOREST 0 3 ri 0 0 0 0
MIXED FOREST 0 4 6 2 136 47 99 1515
WHITE CEDAR Si...jAmp 165 5 0 0 0 0 0
1-11/f,'ED SWAMP 185, 6 0 0 0 0 0
DISTURBED LAND 7 0 0 0 0 0
HIGH POCOSI@-j 8 ?4 5 -P 65 12 1.6
LOW POCOSIvi U9418 ? 50- 382 46 1 178 99
6005
EAY FOREST 495 0 25@ 1331 -29 273 127.6
Wo@;TER AND MARSH 130 11 3267 2513 2262 335 1508
ACTIVE PEAT 0 12 37t:3 2 t1i 4 5 3357 6@61 1628
IHACTIVE PEAT MINE ri 13 489 @--qs S 4 35 147
14 30 so 91 117 16
TOTAL I-e-000 15 o 0 0 0 0
16 0 0 0 0 0

T @.@O 18 74-Pf 77 1 1711 4SS?

ACCRUED ANNUALIZED Hi@BIT@@'T UNITS
AT THE :--!iC- OF THE -,F.,O.JE,--T PEFIi'-DD. RATE OF HA617A7 CCNVERSION IN
.7,
AREA 4. #@. AREA 41
klITHOLIT THE PROJECT. 'CONTINUED) WITH THE PROJECT.
TYPE SPEC. TOT. FRCM AGRICULTURAL LAND TO:

TYPE PRO BEG END R
1 0 0 0
1, DECIDUOUS FOREST 0 0 0
j cl 0 0 0 0
0 0 0 0 cl 13 EVERGREEN FOREST 0 0 0
4 121 104 21 MIXED FOREST cl 0 0
0 0 loJHITE CEDAR SWAMP 13 0 0
cl 9 0 0 1111*XED SWAMP 0 0
0 cl 0 cl 0 cl
DISTURBED LAND 0 0 0
0 0 1) 0 0 li
- 51 4-- - -. .-,4 = - -
HIGH POCOSIN n rl
71, 50 7 2Z-4 4ol LOW PclcOSI;l 0 Ij Q
10 1057 1 2Y2 I I '.:-i 5 S 14:3 DAY FOREST 0 0 cl
11 6 2 15512 2094 17 S 2b,06 i @:- I v.lATER AND MARSH 0 11 11
12 .610 167? 1 1. So 8 - 1 0 21 lo, ACTIVE PEAT MINE 13 1 ZO F
i 2 70 314 181 2 ?3' 423 2708 2 ItJAZTlUE PEAT MINE 0 3 I'l
14 4 20 1 0 l's -31 :3 RESIDENTIAL DEVELOPMENT 0 0 0
15 u 0 0 0 0 0 ROADS AND RIGHTS-OF-WAY 0 0 ri
16 0 0 cl 0 1) 0 "ITHEP DEYELOPED A@EAS 0 0 0

T 255717 5323 4483 5051 8379 56302-

361

PATS OF 14ASTTAT CONVERSIOM IN RATE OF IN
,;RFA 4, -SCEINAPIO ;Q. AREA 4. =CT.N@"RIO 42,
141TH THE PROJECT. WITH THE PROJECT.

FROM WHITE CEDAR SWAMP TO: FROM MIXED SWAMP TO:

TYPE PRO BEG END R TYPE PRO BEG END R

MIXED SWAMP 0 0 0 DISTURBED LAND 0 1 0
DISTURBED LAND 0 1 0 HIGH POCOSIN 0 ri 13
HIGH POCOSIN 0 0 13 LOW F10COSIN 0 0 0
LOW POCOSIN 0 0 0 BAY FOREST 0 0 0
SAY FOREST 0 0 a WATER AND MARSH 0 0 0
WATER AND MARSH 0 0 0 ACTIt,'E PEt:,7 MINE 182 1 20 F
ACTIVE PEAT MINE 6.5 1 213 F INAC71VE PEAT MINE 0 0 0
INACTIVE PEAT MINE 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 0
RESIDENTIAL DEVELOPMENT 0 0 0 ROADS AND PIGHTS-OF-WAY 0 ri 0
ROADS AND RIGHTS-OF-14AY 0 0 0 OTHER DEVELOPED AREAS a 0 0
OTHER DEVELOPED AREAS 0 0 0 AGRICULTURAL LA.1--lD 13 0 0
r4GRICULTURAL LAND 0 0 0 DECIDUOUS FOPEST 0 0 a
DECIDUOUS FOREST 0 .0 0 EVERGREE14 FOREST 0 0 13
EVERGREEN FOREST 0 0 0 tlI>,E!) FOREST 13 0 0
MIXED FOREST 0 0 0 CEDAR SWAMP cl 0 0

RATE OF '.-4AEl"rA'r CONVERSION IN RATE OF H--'F,17-T lN
AREA 4. -ECE"i"'PIO 42. AREA 4. t;--.
WITH THE =ROjECT. WITH THE PPC-JECT.

FROM DISTURBED Lj-4ND TO: FROM HIGH POCOSIN TIC:

TYPE PRO BEG END R TYPE PRO BEG END R

HIGH POCOSIN 0 1 0 LOW POCOSI&H
LOW POCOSIN 0 0
SA'@ FOREST
BAY FOREST 0 1 0 L-JATER AND MARSH 1)
14ATER AND MARSH 0 0 0 @CTII,IE PEAT MIHE 14,,Z.51 20
ACTIVE PEAT MINE 65 1 '20 F INACTIVE PEI-T 0 0 Q
INACTIVE PEAT MINE Q 0 PESl:)E!-JT",4L --l-EYELOPMENT 0 1-1 1-1
RESIDENTIAL DEVELOPMENT 0 0 F.0-D'S kND 0
R&4DS AND RIGHTS-OF-WAY Q 0 ri OTi@ER DEI)ELOPED rt C,
OTHER DEVELOPED AREMS 0 0 0 AGRI:1-ILTURAL LANC, 13
i;,GRICULTURAL LAND 0 0 0 DECIDUOUS FOREST 1)
DECIDUOUS FOREST 0 0 0 El.:ERSPEEN FOREST 0 0 ri
E:,)E;GREEN FOREST 0 1 0 FOREST 13 1)
MIXED FOREST 0 0 0 WHITE CEDAR StJ-"MP 1.1 0
WHITE CEDAR SWAMP ri 1 0 MIll<ED sl;j@;mp fj j 0
MIXED SWAMP 0 i 0 DISTUP13ED LAND 0 ID 1)

362

co r-T :K pi c, 1, c, -v -ij-D Tl @kl x v a o i q -n x 1::. -- rp -n
C. - rn r-, -1 c) m Z Q x - M G) -4 o rTI Cil, 1, m
11) CO X X [11 C) n 2: 1- (1) 0 --1 m -A Gi co X - X rn (-):U:E I -D 1 -4 -< 0
x -4 m -A m T - - m li, -- C-1 @ :K T- T, rri III :K
-n 71 C 0 M Z) 0 0 0 M k.6 0 -1 cr-, mooon X01-1 -4 1: -Ili -n
C) 0 -0 lu '11 c M - M -4 f. C, -0 IT m c C M-M Jo r-
T (-l 0 U) -J-- kl -11 (11 0 r- C) 1, C m -n o w @Lj o -n 111 0 r- 0 1, Z @: 1 10 0
m c) m Z: m -D FYI -A m m -D m C-) m 1@- m C) III C -A M Z -A m -U Z M
M m 0.@11."-Mzwcco m V (.0
I, m 7@ m -0 D .-A lu M (A D M "0 m @ -0 D -A --i T
T -C, 11 1 F 'D r m -i m w -11 M D r M r m -A Z 0
-1 C) C-i (- 0 - 1, C. z D -loor-0- D 1, T (-)
e(. 773 T -0 w 0 -1 :z m Z o) ,n -0 -u G') 0 -1 z M 0
fnmr-ma:rn - ;@j Fil C, Z mmrmmm -'r.
1@ 01 U) :11, C-1 --i C :K z CI OwDa-Acazm
-i z (.) m - m :z Li -1 --f z 0) M - M z
cl D Ir-Z D - v D I r- Z
0 0 0 m Z C) ;u 0 0 m
rn -n -u fil m 71 T 0
m (n E m
11 z 1> z
0 CO
-u
C) 0 Cl C@ C. 0 C, D C) Ln C) Q V. C@ C', C, 0 L.) C. C, C,
CO

C. C. C. ID C, a- C. CD C. L') En C@ (1- C) 0 cr, 0 C) 0 0 0 1-) C. Cl cu
LO m m
a', G)
W
D CD C. 1=1 L, W m L, 1=1 CD C) C, 0 C@ C-1 LD L, L') C) r.) C) C, III
z z

-n

F- Un F- :E 0 Z M ri JP 0 _0 T -n r -T Q :K m o D cl ;u @4) Z
-- -Z -A 0 M
:c m G) -4 b rfi 0 - - - X M M 0
i Z Ln M t-j Xi :I- :r, to 1, C. -1 m -A u-) o) X :@ x m 0 x :r D 0) -4 0
m x -4 m -A r7i -u - - m CD - r) in a: -A III MM--mo-r,.-m
T-"T cvmc7oQoTov-A
ID -D T 10 -Tj c c M - -A J- C. C, -010 C C: M-M
le T (7) L-) rJU u-. (-) -11 m o r- cl D z C :L -71 n o a) to r-) ii mo-r, v i :!,- D
Z in 0 0 M E M C. M c -A m Z -A m -A m o o m E m o m c -i m z -A rFl --o z
01 0 0 D V m Z 0 C C 0 - :c wot:7DOXZWCCv- mv
(0) :K D- III _0 m 1; -0 -A C -Dki I -(o XT-M m m D -0 D -4 -n
r- -o 7b Lc. -n -n D r- -n r m -,' M ;9 7 - r- 13 M fj) 'il -n D r :0 r m -4 7 -< 0
7.n @u z J> -A 0 0 r- 0 -0 X
11 -40OF-Ci- 11 -v 0
Z co 'IV 7-n T i7j " -4 ITI 'a C. Z (),) ;0;0 Torl-lam m m
CO Q E: m m r- m:r m M M .n I.. o E mmrmxm -0 Y)
T 1" (f) u, 1, C, --i @- :1 T. (7, -, --i D w w D v -A,7: -7
75- -1 -4 Z U) M- - -1 -1 0 a --i -i z 0 m ;:,.
Q 0. 1 1 r- Z 1, 1 r- -7
IT 0 ct m ;o o o fn- 0
m -n -0 Z m -n -6
m U) Z- m
@13
-A
'n C@ C. C@ C, 0 C. 'D :-, (" T1 a- 0 (D 0 Co 0 0 C. C) 0 CD 0 clr- C@ -0
Ln 711 z 0 ;u
11 0 0
C, C. C, C. 0 0 (1- C. Cl .7. C, C) 'D f, ED 0 - (D ID cl C. 0 C. 0 C) @- 0 CD w
m rn
0 a)
m L, C) C) CD 0 CA 0 C) C-1 @, 11 L@ to C, m
0 -7 Cl z
0 0

-n

RATE OF HAeITA7 ',-.f-,t,,VERSION IN HABITAT CONDITIONS.
..REA 4, AT THE END OF THE F:R6TECT PERIOD.
WITH THE PROJECT. AREA 4 WITH THE PROJS@T.
FROM IINACTIVE PEAT MINE TO: TYPE AGRES
TYPE PRO BEG ENO R RES,111SNTIAL DEt,)ELOPMENT -:"-: 5 4
ROADS AND RIGHTS-OF-WAY 0
PESIDENTIAL DEI)ELOPMENT IS 5 '20 T OTHER DEI)ELOPED AREAS 13
SY (SAR @,GRICJJLTURAL LAND 214
5 = 0 10 - 106 13 331 20 2354 DECIDUOUS FOREST 0
ROADS AND RIGHTS-OF-WAY 0 0 0 Ek)ERGREEN FOREST i 11 2 6
OTHER DEVELOPED AREAS 0 0 0 MIXED FOREST 0
F:40RICULTURAL LAND 1.7 5 T WHITE! CEDAR SWo;l-MP Z 2
BY YEAR MIXED SIAAMP @,20
5 10 = 53 15 69 20 214 DISTUPeED L@HD
DEC I DIJOUS FOREST 1) a 0 HIGH POCOSIN 50?
Et)ERGREEEN FOREST 15 5 20 T LOW FOCOSIN
BY YEAR SAY F -3 R E ST
5 = 0 10 = 2:@4 15 430 , 20 = 1?26 WATER AND MARSH 42so
MIXED FOREST 0 b o r4CTIVE PEAT M!NE
!...JHITE CEDAR EWAMP 5 - 20 T INACI'!',E PEAT MINE
BY "EAR
5 = 0 10 = 3 15 4.9 .20 = 2 2' TOTAL
MIXED SWAMP 4.8 5 '2 0 T
BY YEAR
5 = 0 10 = 95 1'- 138.420 -@20
DISTUP2ED, LAND
C. 1) 0
HIGH POCOSIN 3. 9 5 20 T
S-@'r' '(Ei@@,.R
5 = 0 io 69.8 15 113.1-20 = 509
LOW POCOSIN 4.a 5 'Z 0 T
EY
5
5 = ID 10 S5 15 13e.420 = 61-0
Ef_lf' FORES-1 I . 7- !5 7:- 0 7

5 = 0 10 21.2 15 34.6 2e = 1'5
10ATER 41C, MARSH :,13 5 20 T
BY EAR
5 C, 10 = I@F34 5 Z187 0
-C"!'Ik)E PE_^T MIHE 0

364

ACCRUED AHNUALIZED H--4BITAT UHITS ACCRUED ANNUAL17ED HABITAT UNITS
AT THE END OF THE PROJECT PERIOD. AT THE END OF THE PROJECT PERIOD.
AREA 4, `-CEH@@FIQ #7-. AREA 4. SCENARIO # -@'
WITH THE PROJECT. WITH THE PROJECT. (CONTINUED)

TYPE SPEC. TYPE SPEC. TOT.
1 2 3 4 5 6 7 8 9 10

1 0 9 Q 23 51 1 139 14
^_o 9 338
2 0 13 11 0 cl 2 0 0 cl 1) 13 0
3 cl cl cl 0 0 3 0 0 0 0 0 0
4 -15 515, 32 .71 140 4 152 ?4 15 7 52 694
5 Cl cl 0 0 0 5 0 0 0 0 0 0
6 185 2'17 ill 14 199 t@ 2242 254 444 305 245 2196
0 11 0 0 0 7 0 0 0 0 0 0
40 25 28 5 8 8 22 22 34 36 227
1446 1089 1314 507 2.132 ? 225 1446 6SS 1052 1314 ;314
10 250 451 -2 4 432 1. 0 327 358 .62 99 401 2760
It 12 0 3 ?25 .233 123 555 11 S136 -t 802 1 C133 7065
1 -1 - - 60 1 1' '@@25 620 638 67.6 1221 7812
1- 1 --1- 1 lp.7-6 1239 244
13 32':' 268 235 23 99 13 47 211 122 1?7 291 1821
14 400 400 1217 1565 209 14 52 261 0 0 435 453?
15 46 65 39 -3 3 46 15 46 33 0 0 20 325
16 -3 9 6 8 5 3 61-1 @ It" 6 8 5 3 16 792 '701 183 183 671 566-55'

T 5750 53-9 5977 3067 2472 T 2473 4580 2919 3415 5728 4276

RATE 0;: HA617-T C-j-jt,jUEF;.SION IN PA77- OF H@@e,rAT --NVERS I ON I N
APEA 1 . !A;; 1,j 0 -', AREA !.`SCEI-4-@PIO 14-Ll
WITHOUT THE PROJECT. l.,JITHOUT THE PROjECT.
FROM DISTURBED LAND TO - FROM INACTIVE PEAT MINE TO:
TYPE PRO BEG END R! TYPE PRO BEG END R'
HIGH FOCOSIN :3.5 1 20 E RESIDENTIAL DEt)ELOPMENT 0 0 0
LOW POCOSIN 16.51 20 E ROADS AND RIGHTS-OF-WAY 0 0 0
BAY FOREST 13 0 0 OTHER DEVELOPED AREAS 0 0 0
WATER AND Mi:@P'@H .3 0 0 AGRICULTURAL -AND cl 0 0
"CTIk.'E PEAT flIHE 0 rl 0 DECIDUOUS FOREST 0 0 0
INACTI-E PE@T MINE 13 1) cl Ek)ERGREEN FOREST 1) ID 11
PESIDEHTI,-@L DEIJELOPMPIT 0 r. Ml"'El- FORE-::- 1) c
WHITE CEE.-'F,'
r,O'DS :,14D RIGHTS-OF-Wl'y 0 cl cl
OTHER DEVELOPED ARE."S 0 cl ID MIXED SwHrllp 1) 0
14GPICULTURAL L.4ND cl 0 0 DISTURBED LAND 0 0 0
E-ECIbUOUS FOREST 0 0 0 HIGH POCOSIN 0 cl 0
EI)ERGREEN FORE.-IT cl 0 cl LOW POCOSIN 0 0
MIXED FOREST 0 0 ct BAY FOREST 11 0 0
WHITE CEDAR EWAMP 0 0 0 lAATEP AND MARSH 100 5 20 T
MIXED SWAMP 0 0 0 BY YEAR
5 = 0 10 = 31.6 15 .316 20 = 316
ACTIVE PEAT MINE 0 0 0

365

HABITAT CONDITICNS.SCENARIO #3, ACCRUED 4,INIJAL,-@ED HASITAT UNITS
AT THE END OF THE PROJECT PERIOD. AT THE END OF THE PROJECT PERIOD.
"REM I WITHOUT THE PROJECT. AREA I.SCENAPIG
W17HOUT THE PROJE@@-
TYPE ACRES
Tl.(FS SPEC.
RESIDENTIAL DEVELOPMENT 0 1 .3 4 !5
ROADS AND RIGHTS-OF-WAY 0
OTHER DEVELOPED AREAS 1) 1 0 0 0 0 0
AGRICULTURAL LAND 2a4a 71 0 0 13 1.1
DECIDUOUS FOREST 0 3 0 0 1) 0 01
EVERGREEN FOREST 0 4 6.34 i 50;4 1313 10821
MIXED FOREST 0 5 0 0 0 0 13
WHITE CEDAR SWAMP 0 0 0 0
Ml',,,'ED SWAMP 0 0 0 13
DISTURBED LAND 100 S 0 0 13 0
HIGH POCOSIN 2138 .? 1) 0 1) 13 0
LOW POCOSIN 10100 10 803 1 2_1 5 -A 1688 25.13 1204
BAY FOREST 0 11 1447 1113 1001 148 6^8
WATER AND MARSH 632 !2 .6 *39 7 4557 5784 1!39 _23 0 4
ACTIVE PEAT MINE 0 13 13 0 0 0 1)
IVIAC71 46@ -
IVE PEAT MINE 0 14 20 120 365 7
i If . 0. Fj 0
TOTAL 15818 16 14 3 1 74 i 3; 31

T ?4-10 S-586 :3,3'75 3 110 6'@ 13 5

ACCRUED ANNUALIZED HABITAT UNITS RATE OF Ht-4e!-47 --ONVERSION 1N
END OF THE PROJECT PER!OD. r.I -L,-
AT THE REA ! 42,
-REA 1-:CENARIO #21 W17H 7HE PROJECT.
GJITHOUT THE PROJECT. (CONTINUED)
7'(PE SPEC. FROIA AGPIC_UL71J'Rr@@L LAND TO:
6 7 8 0 10 TYPE PRO SEG END R

i 0 0 n 0 0 10 DECIDUOUS FORES7 13 0 1)
0 0 0 0 13 =_:,'ER:GREEN FOREST 0 1) 0
0 13 0 0 tl!@-zD FOREST 0 0 1)
4 2421 1139 228 114 797 !0623 'AH I Swt41P 0 0
5 0 0 0 0 0 0 MIXED SWAMP 0 C, 0
6 0 0 0 0 0 cl DISTURSED LHND .3 0 1--
0 0 HIGH POCOSIN
0 cl 0 0 0 LIDW POCOSIN't 0 0
0 0 0 0 0 10 SAY* FOREET ri 0
11 912 ?98 172 275 ills "r 0, Sa 1,44TER AND MARSH 0 1) cl
li '927 9.64 124S S494 HCTIVE PEAT MINE 1 0 Z 1 10 F
'2 1NACTIVE PEAT IMINE 0 -
1 1052 Z .3 1? 2 '2 9 S 0 73 155 5696 30,456 I'l 13,
I S 11-11 0 0 0 0 0 RESIDENTIAL DEI)ELOPMENT 0 1) 0
14 t6 73 0 0 12.10 1. 13 6 1 RCADS AND RIGHTS-OF-1.dA'Y 0 u
15 0 0 0 0 0 1) 07HSR DEI)ELOF"ED AREAS 0 0
16 24 206
1 29 25

4707 5837 4313 4515 9009 44R',B

366

PATE OF HABITAT C!'NVERSION IN RATE OF HABITAT '-,-'NkjERS ION IN
AREA 1 SCENAR.10 *:., AREA I '-3CEr--lARIO i*3,
WITH THE PROJECT. WITH THE PROJECT.

FROM DISTURBED LAND TO: FROM HIGH POCOSIN TO:

TYPE PRO BEG END R TYPE PRO BEG END R

HIGH POCOSIN 0 1 0 LOW POCOSIN 0 0 0
LOW POCOSIN 0 1 0 BAY FOREST 0 0 0
BAY FOREST 0 0 0 WATER AND MARSH 0 13 0
WATER AND MARSH cl 0 0 ACTIVE PEAT MINE 23 1 10 p
ACTIVE PEAT MINE 313 1 10 F INACTIVE PEAT MINE 0 0 0
INACTIVE PEAT MINE 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 0
RESIDENTIAL DEVELOPMENT 0 0 0 ROADS AND RIGHTS-OF-WAY 0 0 0
ROADS AND RIGHTS-OF-WAY 0 0 0 OTHER DEVELOPED AREAS rf 0 0
OTHER DEVELOPED AREAS 0 0 0 AGRICULTURAL LAND 0 0 0
i-kGRICULTURAL LAND 0 0 0 DECIDUOUS FOREST 0 0 0
DECIDUOUS FOREST 0 0 0 EVERGREEN FOREST 0 0 0
EVERGREEN FOREST 0 0 0 MIXED FOREST 0 ri 0
MIXED FOREST 0 0 0 WHITE CEDAR SWAMP 0 0 0
WHITE CEDAR SWAMP 0 0 0 tllXED SWAMP 0 11 0
MIXED SWAMP 0 0 0 DISTURBED LAND 0 0 0

RATE OF HABIT4@i7 1--l--,NQERSION IN RATE OF HABITAT CONVERSION IN
ARE" I -*D:Zj@@.F,10 #3, AREA 1 -ECENf@iPIO
W17H THE PROJECT. WITH THE F-R.OJECT.

FROM LOW FOCOSIN TO: FROM 14ATER AND MARSH TO:

T*I'*F'E PRO BEG END R TYPE FRO 6 E GEl--lD P

BAY FOREST 0 0 0 ACTIVE PEAT MINE 11 1 iO F
WATER AND MARSH TNACTIVE PEAT MINE 0 cl. 0
ACTIVE '@,&;T HINE 108 i 10 F RE3,1DENT! PA- DEVELOPMENT 0 0 0
lt-,4@1--TIVE P&@T HINE cl 0 0 ROADS AND RIGHTS-OF-k-,lAY 0 cl 0
RESIDENTIAL DEVELOPMENT 0 0 0 OTHER DEVELOPED AREAS 0 0 0
ROADS AND RIGHTS-CIF-WAY.0 0 0 AGRICULTURAL LAND 0 0 0
OTHER DEVELOPED AREAS 0 cl 0 DECIDUOUS FOREST 0 0 0
AGRICULTURAL LAHD 0 0 EVERGREEN FOREST 1) cl 0
DECIDUOUS FOREST 0 0 ri MEED FOREST C, 0 0
EVERGREEN FOREST 0 0 0 1.,JIH@TE CEDAR SWAMP 0 0 0
Ml'q ED FOREST 0 0 ri MIXED SWAMP 0 cl 0
WHITE CEDAR St,-jAmP cl ri cl DISTURBED LAND C, 1) ci
@,j I: ED SWAMP 0 0 HIGH POCI'=-'!N 0 0 0
1 "
DISTURBED LAND 0 0 0 LCIJ POCOSIN ri 0 ri
HIGH POCOSIN 0 0 Q BAY FOREST 0 0 0

367

RATE OF HAeITA7 CONVERSION IN PATE QF @4ASTTA-@' 1:10liVERSION IN
AREA 1 .:3C-a4APIO 03. AREA I SCENAF-.';D W-3,
WITH THE PROJECT. W'117H THE PROJEC7.

FROM ACTIVE PEAT MINE TO- FROM INACTIVE PEAT MINE TO:

TYPE PRO BEG END R T'VPE PRO BEG END R

INACTIVE PEAT MINE 568 2 11 F RESIDENTIAL DEVELOPMENT 0 0 0
RESIDD-ITIAL DEVELOPMENT 0 0 0 ROADS P*ID RIGHTS-1-IF-1.@JAY 0 11 0
n040S AND RIGHTS-OF-WA( 0 0 0 07HER De)ELOPED AREAS 0 0 0
OTHER DEt.,IELOPED AREAS 13 0 0 AGRICULTURAL -;,;iND .3 5 2 0 T
AGRICULTURAL LAND 0 0 a BY YEAR
DECIDUOUS FOREST 0 0 0 5 = 13 10 = 162 15 =_O 20 = D
EVERGREEN FOREST 0 0 0 DECIDUOUS FORES7
MIXED FOREST 0 0 0 EVER13REEN FOREST 4 5 20
WHITE CEDAR SWAMP 0 0 0 By ylz-"@R
MIXED SWAMP 0 0 0 5 = 13 10 2 15 =-O Z
DISTURBED LAND 0 0 0 MIXED FOREST ij 0
HIGH POCOSIN ri 0 0 WHITE CEDAR SWAMP 0 0 0
LOW POCOSIN 0 a 0 M IX E D SWAMP 0 0 0
BAY FOREST a 0 0 DISTURBED LAND 0 10 0
WATER AND MARSH 0 0 0 HIGH POCOSIN 2 T 20 T
BY YEA R
5 = 1) 10 = 35 15 = 13 20 = 0
LOW POCOSIN 4 5 20 T

5 0 10 = 167 15 = 0 27 cl = C,
e,A,,f, froPEST ri 1@ 0
AND MARSH 10 C, 5 20 T
ply YEAR
5 = -) 10 = 1454 = 5:386 20 = 588.
ACTIVE PEAT MINE il 10 F

HABITAT COND17, I Of-IS SCENARI 0 ACCRUED ANNUALIZED Hs@tSITAT UNIT'S
AT THE END OF THE PPDjECT wERTOC. AT THE T!C' -Y= -PF0-.'E---T
AREA I WITH THE PROJECT. @4REA I c2i i",@
WITH 7L@E PF'OjE,--7.
TYPE ACRES
TYPE SPEC.
RESIDENTIAL DEVELOPMENT ri 1 2 5
ROADS AND R!GHTS-':)F-lAJAY 1)
OTHER DEUELOPED AREAS 0 0 0 0*
cl cl cl
AGRICULTURAL LAND 1828 i" I
DECIDUOUS FOREST 0 13 11 0 0
EVERGREEN FOREST 4 5'- 4
MI'e.E,D FOREST 0 5 0 0 0 0 1)
WHITE CEDAR SWAMP 0 6 2 0 24 1 2
NEX"ED SWAMP 0 7 0 ID 1)
DISTURBED LAND 5570 8 11 0 0 0 0
HIGH POCOSIN 403 ? 0 0 0 0 0
LOW POCOSIN 1925 10 2949 4580 2510 'P41 43@@2
SAY FOREST 0 i 6 2 2;. 7 8 250
WATER AND MARSH 6092 1.61 S 1149 14@8 Z, S 7 ri 7
ACTIVE PEAT MINE 0 1- 0 1) 0 13 0
INACTIVE PEAT MINE 0 14 .6 78 .67S *2 0 6 4 2654 254
i5 23 -@@a 47 14 20
TOTAL 1 @6 1514 417 2 iZ s 1 417

6329 *.3 -017 41? 1

368

ACCRUED ANNUALIZEr- HABITAT UNITS RATE OF Lio@48ITAT C.01+.'ERSION IN
AT THE =',JD -jr' TL4E PROJECT PERIOD. AREA 2 SCENARIO W-3,
AREA I SCEHAPIO #7S., WITHOUT THE FROJE,-;l
WITH THE PROJECT. (CONTINUED)
FROM EVERGREEN FOREST TO:
TYPE SPEC. TOT.
6 8 9 10 TYPE PRO BEG END R

1 0 0 0 0 0 MIXED FOREST 0 0 0
2 0 0 0 fi 1-1 0 WHITE CEDAR SWAMP 0 0 0
3 cl 0 0 0 0 0 MI,-,ED SWAMP 0 0 0
4 1783 839 1 t- 2 :34 5 817 7S26 DISTURBED LAND 3.3 1 30 E
5 ID o cl 0 0 0 HIGH POCOSIN 0 0 0
24 28 48 23 27 240 LOW POCOSII',I 0 0 0
7 0 0 0 0 0 0 BAY FOREST 0 0 0
0 cl 0 0 0 0 WATER AND MARSH 0 0 0
0 ri 0 0 0 0 ACTIVE PEAT MINE 0 0 0
10 :3 3 225 363? -627 1004 4078 28046 INACTIVE PEAT MINE 0 0 0
11 -170 1 7-tl 2'82 241 311 2123 RESIDENTIAL DEVELOPMENT 0 0 0
12 265 729 751 79.6 1436 -7 1 3 ROADS AND RIGHTS-OF-WAY 0 ri 0
13 0 0 0 0 0 0 OTHER DEVELOPED AREAS fj 0 0
14 28 442 0 0 737 7 6 6 AGRICULTURAL LAND 0 0 0
15 Z, 0 14 0 0 9 142 DECIDUOUS FOREST 0 0 0
I@ S'ED7 *3 4'-: 139 SIP 328- 2770

T 5 6 3 621 iD 1916 2247 7513 5-9035

RATE OF HAE:I@AT CONk.'EPSION IN RATE OF HABITAT CONVERSION IN
AREA -2 -1 C E'r I A R 1 '0 4 -', , AREA 2 SCENAFIO #3,
WITHOUT THE PROJECT. WITHOUT THE PROJEU.

FROM MIXED SWAMP TO: FROM DISTURBED LAND TO-

TYPE PRO BEG END R TYP E PRO BEG ENID R

DISTURBED LAND 1.251 80 E HIGH POCOSIN 7.7 1 Z, 0 E
HIGH POCOSIN 0 0 1) LOW POCOSIN 5.9 1 2 0 E:
LOl,--J POCOSIIN 0 0 0 BAY FOREST 0 0 0
BAY F10FEST 0 0 0 WATER AND MARSH 0 1) 1-1
WATER AND NIARSH 0 0 0 ACTIVE PEAT MINE 0 1 0
... CTIVE PEAT MIHE 0 0 0 INACTIVE FSAT MINE 01 ri 0
INACTIVE PEAT MINE 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 cl
RESIDENTIr@-L DEVELOPMENT 0 0 0 ROADS AND RIGHTS-OF-WA',( 0 0 0
ROADS AND RIGHTS-OF-WAY 0 ri 0 OTHER DEVELOPED AREAS 0 0 0
OTHER DEVELOPED 0 cl AGRICULTURAL LAND 0 0 0
AGRICULTURAL LAND 0 1) 13 DECIDUOUS FOREST 0 0 cl
DECIDUOUS FOREST 0 cl 0 EVERGREEN FOREST 5.1y 1 20 E
E','ERGREEN FOREST 0 13 0 tAIXED FOREST 0 0 0
MIXED FOREST 0 cl 0 WHITE CEDAR SWAMP 0 0 0
WHITE CEDAR SWAMP 0 0 0 !,1IXEE) SWAMP .4 1 20 E

369

FACCRUED ANNUALI:E-D PA21T-*T UN173
YAB I TAT COND I T I ONS -li@,P 10 4'
AT THE END OF THE PROJECT PERIOD. AT THE F-Hr., =0!),;Ef--T PERKOD.
AREA 2 WITHOUT THE PPOJZCT. P.AREA 2 SCalp:,.RIC 43.
WITHOUT THE PROjECT.
TYPE ACRES
TYPE SPEC.
RESIDENTIAL DEI)ELOPMENT 0 Z, 3 4 5
ROADS AND RIGHTS-OF-61AY 0
OTHER DEVELOPED AREAS 13 1 cl 0 3 ID 0
o--GRICULTUPAL LA1,1D 1071 2 0 0 cl 13 9
r@'ECIDUOUS FOREST 0 :3 1) 0 0 3
E"ERGREEN FOREST 1147 4 563 19 'S 407 @=-!j
,1-11'::.ED FOREST 0 5 0 ID
WHITE CEDAR SWAMP 0 6 '509 598 305 S Z' 547
MI-E-D SWAMP 7 0 ri 3
DISTURBED LAND Z 4 c5 8 0 0 0 0
HIGH POCOSIN 25E5 64 - 30 -7
LOW POCOSIN 1 9719 10 355 "2 302 113 529
EAY FOREST 0 1 11.73,17 1 '336 1 Zo 3 !-;a 802
1AATER AND MARSH 0 122 122 4 5 SS-4 1 1 2=1 @Z46
ACT IVE PEAT M114E 0 13 () 0 0 0 1)
IN,@4CTIVE PEAT MINE 1 14 0 cl 0 Ll 0
15 .)
I 1-j 0 IJ
TOT@',L 7142 16 1) 0 0 0 cl

T @; I S 4OFj4 :3 20 @i ':@'9 S :22 4

ZSD 'H@BITAT UNITS
-.,CCRUED r-NNUALI@
PAT=- CF wi.4eTrAT lN
,-iT THE E,',J[, -tF TWE RROJECT PERIOD.
4 Z
A P EA 2 . : @ @- @"R ! i--, , , . .PEA 0
W17HOUT THE PROjECT. (CONTINUED)
TYPE SPEC. TOT. =P011 AC-F.I@--UL7-'R@L LAMO, TO:
6 1 S. TYPE PRC S, E G END
0 1) G 0 DECIDUOUS FOREST Q 0
Z, 0 0 0 0 0
3 0 0 0 0 0 0 EVERGREEIN FOPEZ-7 1)
XED 0 0
4 51!0 42-8 6 43 300 :S ? 9.1 M 1, FOREST
5 0 13 o 0 0 L,-JHITE C=D'R Sl,-;' !F 0 L
MI,."]:-,C,
611 77 0 0 1222 340 6-14 6045
DISTUPEED L4.!--lD
0 0 L) 0
HIGH POCOSIN 0 Ll 1-
la S 5 '2 7 02 547, LOW POCOE.Tt,j
ij -101 4 -:: 8 -,i 12, i SAY FORES7 0 13 C.
91 S37,?
'xiHTER "NE, MARSH 0
11 S 'S 4 84-6 1ia i:5a 1492 1 C, 12 0 0
1 Z 205 5-@ S T-130 i 4 iris OP 4 CTP@E PEAT M INE 45 1 13
1'.'E -4T .'11HE 0 0
1:3 0 0 NACI PE.'
14 0 0 0. 0 0 ri PESIDaITIAL DEVELOPME!-iT 0 C.
15 0 0 0 0 0 0 ROADS *)D j ;j 0
10' 0 0 0 0 0 0 OTHER DEVELU-PED @@PEAS 13 cl j

T 2474 2061 S114 2837 d143 :31*25?

370

RATE OF @-J@'@BITAT CONVERSION IN RATE OF HABT7P@7 CONVERSION IN
AREA Z , SCENARIO tt.3, AREA 2. SCENARIO #3,
WITH THE WITH THE PROJECT.

FROM EVERGREEN FOREST TO: FROM MIXED SWAMP TO:

T'rPE PRO BEG END R TYPE PRO BEG END F

MIXED FOREST 0 0 0 DISTURBED LAND 0 1 0
WHITE CEDAR SWAMP 0 0 0 HIGH POCOSIN 0 0 0
r-II@'ED SWAMP 0 0 0 LOW POCOSIN 0 0 0
DISTURBED LAND 0 1 0 BAY FOREST 0 0 0
HIGH POCOSIN 0 0 0 WATER AND MARSH 0 0 0
LOW POCOSIN 0 0 0 A.CTIVE PEAT MINE 3 1 10 F
BAY FOREST 0 0 0 INACTIVE PEAT MINE 0 0 0
WATER AND rlARSH 0 0 0 RESIDENTIAL DEVELOPMENT 0 0 cl
HCTI()E PEAT MINE :3 1/ 1 10 F ROADS AND RIGHTS-OF-lAAY 0 0 0
TNACTIVE PEf2@T MINE 0 0 0 OTHER DEVELOPED AREAS 0 0 0
RESIDENTIAL DEVELOPMENT 0 0 0 AGRICULTURAL LAND 0 0 0
ROADS AND RIGHTS-OF-l,,)AY 0 0 0 DECIDUOUS FOREST 0 0 0
OTHER DEVELOPED AREAS 0 0 0 EVERGREEN FOREST 0 0 0
GRICULTURAL LAND ri 0 0 MIXED FOREST 13 0 0
DECIDUOUS FOREST 1) 0 0 ',-JHITE CEDAR SWAMP 0 0 0

RATE OF HHBIT,@4T CONVEP
PAT@' OF H,@,81T-4T --3HVERSION IN .SIO!ll IN
AREA -1, #3 AREA 2,
WITH THE PROJECT. WITH THE PROjEr-T.

FPOM DISTURBED LAND TO: FROM HIGH POCOSIN TO:

TYPE PRO BEG END R TYPE PRO EEG END R

HIGH POCOSIN 0 1 0 LOW POCOSIN 0 0 0
LOW POCOSIN I 1-j BAY FOREST cl 0 0
BA'f FORE37 ID 0 a WATER AND MARSH 0 0 9
@@JATEP @AND "APSH cl 0 CTIVE PEAT MINE 51 1 101
"r.TPlE PEAT MINE 123 1 10 F INACTIVE PEAT M.INE 0 0 0
1NACT11,1E PEAT MIHE 0 0 0 PESIDE@-ITIAL DEVELOPMENT 0 0 0
PE'-z 1 DE@,J-l IAL DEVELOPMENT 0 cl 0 ROADS AND PIGHTS-QF-t-,li@iY & cl C.
ROADS AND RIGHTS-OF-1.,Ji@4( 0 cl cl OTHER. DEYELCIFEE., AREAS 0 cl 11
IDTHEP DEVELOPED ARE-iS Q 0 ri @@--,RICULTUPFm@L LAND 0 C, 0
,'IGPICULTUPAL LAND 1) 0 1-. DECIDUOUS FOREST 0 'j cl
DE,-7DU)D'-"S FOFEST !,j 0 0 El@'EPGREFIIJ FOREST 0 0 0
E"!EPGREEN FOPE@-T 0 1 0 FOREST cl 0 13
MIAED FOREST Q 1) 0 ]WHITE CED(@R SWAMP 0 0 cl
WHITE CEDAR SWAMP 01 0 0 MIXED SW41P 0 1.) 0
MIX*ED SWAMP 0 1 0 DISTURBED LAND 0 0 0

371

RATE OF HAeITAT CONVERSION !N RATE -DF PA817AT C@ONt)ERSIC'N IN
A-REA 2. SC-ENAPIO 1*3. AREA SCE@!@'.P!o #s,
WITH THE PROJECT. WITH THE PROJECT.

FROM LOW POCOSIN TO: FPCM ACTIQE PEAT MINE TO:

TYPE PRO BEG END P TYPE PRO EEG END F

SAY FOREST 0 0 0 lN$A'r_71VE PEAT MINE @_@O 0 2 11 F
4ND MARSH 1) Q 0 REEIDENTIiAL DEVELOPMENT 13 0 ri
ACTIVE PEAT MINE 39 1 1 li F RO-"DS AND RIGHTS-OF-WAY-0 0 0
PEAT MINE 0 a 0 OTHER DEUELOPED AREAS 9 0 0
RESIDENTIAL DEVELOPMelT 0 0 0 GPICUL7UPAL LAND 0 0 0
ROADS @-*ID RIGHTS-OF-WAY-0 0 0 DECIDUOUS FOREST 0 0 cl
OTHER DEVELOPED AREolliS 0 0 0 EVERGREEN FOPETT 0 0 13
AGRICULTURAL LAND 0 0 MIXED FORE@@T 1". ri 0
DECIDUOUS FOREST ri 13 0 WHITE CEDAR SWAMP 0 0 0
e)ERGREEN FOREST 0 0 0 rll@'ED SWAMP 0 0
Ml'.,.'ED FOREST 0 0 0 DIS7UPSED LAND 1) 0
1-.-;HIlTE CEDAR S14AMP 0 0 0 HIGH POCOSIN cl 0 0
MIXED SWAMP 0 0 0 LOW POCOSIN 0 0
DISTURBED LAND 0 0 04 eAY 50REST
HIGH POCOSIN 0 0 0 1..jATE-R AND MAPSH 0

RATE OF CClNL.!ERSI(-jN IN 'riASITAT CCM-6111710NS
i..4REA 2 - AT 7HE EHD OF THE @:ROJE= PERIOD.
WITH 7HE PROJECT. HREA@ _': WITH 7HE

FROM INACTIUE PEAT MINE TO: TYPE ICRES

TYPE PRO eEG END P ='E'S@IDENTIAL DEI.)ELOPMENT ci

RESIDENTIAL DEVELOPMENT 0 0 0 OTHER DEVELOPED HPEHS
ROADS AND RIGHTS-OF-WAY 0 0 0 ACRl --.!JL71JPAL ILANC@
OTHER DEVELOPED AREAS 0 0 0 DECIDUOUS zCFE3`
AGPICULTURAL LAViD 4 5 20 T EVERGREEN FOREST
BY YEAR fll' ED FOREST iI
5 = ID 10 = 1*200 LE 0 2 0 = 0 t..JH171z- CEC-@--R
DEC! DUOUS FOREST 0 13 E:-') @IJAMP
13 Z@
EVERGREEN FOREST 5 11 .2 0 T DISTUPeED LAND
e`( '(Et@,P H113H POCOSIN --j"
0 10 = 150 15 0 .2 0 0 01A
M I "--,ED F 0 R'E S T 0
1.0HITE ;-'E[.,;R SWAMP 0 0 !3 W,@-TER r;fJD r,!ARSH 3
MIXED SWAMP 1 5 Z- 0 T 13
*_Y YE@'P. 7@1ACTIk.)E PEAT NIIlE 0
5 = ,, 1 Q = 5 1. 5 = 0 20 = ,
D 1 STURBED LAND 0 0 Q TOTAL '17142
HIGH POCOSIN 6 5 22 0 T
BY '(EAR
5 = 0 10 = 32 i 3 = 0 '2 0 = 13
LOW POCOSIN 3 5 220 T
E;Y '.1 EPAR
5 = 13 10 = 63 15. = 0 '2 0
SAY FOREST 0 0 1)
WATER o@,ND MARSH 100 11 7-0 T
SlY YEAR
S = 0 10 = 0 15 = sooo 20 = sooo
AC7. *@"E PSA7 MINE 0 1 0

372

ACCRUED ANNUALIZED HABITAT UNITS ACCRUED ArlNIji2iLI7-ED HABITAT UNITS
AT THE ETID OF 7HE PPOJEf--;T PERIOD. AT THE EHD OF THE rPnJECT PERIOD.
AREA 2 CE !AP., iD # i@, SC@I'tAF
-!. - AREA 2 , , - - -'. T 0 #3.
WITH THE PROJECT. 'CONTINUED) WITH THE PROJECT.

TYPE SPEC. TOT. TYPE SPEC.
6 7 8 10 1 2 3 4 5

1 0 0 0 0 0 0 ri 0 0 0
Z, 0 13 0 0 0 2 0 0 0 0 0
s 0 0 Fj 0 13 0 3 0 ID 0 0 0
-4 86? 1409 82 41 28 6 8 1 4 245 542 10-4 368 -67
5 0 0 0 5 0 0 0 0 0
8 4se 352 2-3155 260 312 159 zo 286
0 0 0 0 0 0 0
8 0 0 ci 0 cl 0 ID cl .0 0
? 6 2., E: 1-7 24 242 38 28 34 1 7
10 1047 1145 197 S16 12e4 S927 10 922 1442 -75'0 2 ?6 1-3e@2
11 1 '-':� 6 S19 420 436 5 6 2 3,3 4 4 11 655 504 453 67 3012
1 --' 77 212 218 231 418 '26 7 3 12 4 6'7- 334 42*@ 84 Z06
1:3 0 0 0 0 0 0 13 0 0 0 0 0
14 36 1130 ID 0 @Ao 3132 14 2 7 276 8140 1080 144
15 11 8 0 0 5 75 15 11 1@ 9 8 1
1,:. 1516 1 !3 81 36 316 1. 2 2 1116 16 79 168 132 72 168

T 2646 -7914 1608 1526 32- S 26-879 T 2P 5 3621 S'0 2 6 2023 3272

373

10.5 Appendix for Section 6.2.1.1: Amount of Surface
Water Runoff

374

Scenario #1, Area 1. Acreape t3v land use catepories
for the 20 year stuay. oeriod.

.. .... . ..... . ... . ....... ....... ...... .. . ......... ... . ..... .... . ... .....
OPEN PRE-MINING PEAT RECLAIMED
YEAR WATER DISTURBED SHRUB MINE AGRIC FOREST

.. .......... .
0 330 114160 4000 330 0 0
1 L-660 8400 4000 750 0 0
2 2660 6990 4000 2160 0 0
3 C2,660 6900 3670 E580 0 0
4 2660 6820 3340 3000 0 0
5 2660 6400 3340 3410 0 0
6 3000 5990 3340 3330 170 0
7 3160 5570 3340 35BLA 170 0
a 3500 5490 3340 3330 170 0
9 4000 4740 3000 3750 P70 70
10 1670 73PO 2670 3500 530 130
11 1670 6990 2670 2660 1470 370
12 1670 6320 2340 3000 2000 500
J-2 1670 5990 2340 2330 ;--1800 700
14 1670 5660 2000 2660 3060
15 1670 5320 1670 2660 3600 900
16 1670 4660 1670 2660 4130 10,30
17 1670 4660 1340 2330 4660 1170
18 1670 4660 670 3000 4660 1170
19 !670 4660 340 2330 5460 1,370
20 1670 4660 0 2000 5990 1500

. ... .......... . . ..... . .... ...... . ......... ........ ... .. .... .... . .......

Note: OPEN WATER includes the teriloorary lagoon, permanent lake
and an estimate of the canal surface area.

375

-rable 10. 5B: Scenario #1, Area 2: Acreage by land use categories
for the 20 year study perlod.

. ........ .. . .. .. . . ....... . . . ..... .... .. ......... ... .... ...... . . ......... . . ........ . ........ .. .... ....

PRE-MINING PEAT' RECLAIMED
YEAR DISTURBED SHRUB MINE AGRIC FOREST

............ . . . . ..... .... . ... - - -----------

0 2140 4000 0 0 1000
1 2050 3830 300 0 960
2 1960 3660 600 0 920
3 1870 3490 900 0 881zf
4 1780 3320 1200 0 840
5 1690 3150 1500 0 800
6 1600 2980 1800 0 760
7 1510 P-810 1800 300 720
8 1420 2640 1800 600 680
9 1330 2470 1800 720 820
10 1249 2300 1800 960 840
11 1150 2130 1800 1200 86QI
12 1060 1960 1800 1440 860
13 970 1790 1800 1680 900
14 880 1620 1800 1920 920
15 790 1450 1800 2160 940
16 700 1280 1800 2400 960
17 610 1110 1800 2640 980
18 520 940 1800 2880 1000
19 430 770 1800 3120 1020
20 340 600 1800 3360 1040

. ............. ....... . ........... . .......

376

Table10.5C: Scenario #2, Area 1: Acreage by land use categories
for the 20 year study period.

. ......... . . ......

OPEN PRE-MINING PEAT RECLAIMED
YEAR WATER DISTURBED SHRUB MINE AGRIC FOREST

0 300 12300 17100 300 0 0
1 5000 7250 16250 1500 0 LA
2 5000 6600 15400 3000 0 0
3 5000 5950 14550 4500 0 0
4 5000 5300 13700 6000 0 0
5 5000 4650 12850 7500 0 0
6 6500 4120 11380 8000 0 0
7 8000 3590 9910 8500 0 0
8 8000 3060 8440 9000 1500 0
9 3000 7530 6970 9500 2400 .600
10 3000 7000 5500 10000 3600 900
11 3000 5600 4400 10500 5200 1300
12 3000 4200 3300 11000 6800 1700
13 3000 2800 2200 11500 840LA 2100
14 3000 1400 1100 12000 10000 2500
15 3000 0 0 12500 11600 2900
16 3000 0 0 10000 13600 3400
17 3000 0 0 7500 15600 3900
18 3000 0 0 5000 17600 4400
19 3000 0 0 2500 19600 4900.
20 3000 0 0 0 21600 5400

377

Table(0.51): Scenario #2, Area 2- Acreage by land use categories
for the 20 year study period.

...... ....

OPEN PRE-MINING PEAT RECLAIMED
YEAR WATER DISTURBED SHRUB MINE AGRIC FOREST

. . ........ . ......
0 150 1500 11700 0 0 1650
1 150 1425 11110 750 0 1565
2 150 1350 10520 1500 0 1480
3 150 1275 9930 2250 0 1395
4 150 1200 9340 3000 0 1310
5 150 l125 8750 3750 0 1225
6 150 1025 7960 4000 750 1115
7 150 925 7170 4250 1500 1005
a 150 825 6360 4500 1800 1345
9 150 725 5590 4750 2400 1385
10 150 625 4800 5000 3000 1425
11 150 500 3840 5220 3800 1490
12 150 375 2680 5440 4600 1555
13 150 250 1920 5660 54LAO 1620
14 150 125 960 5880 6200 1685
15 0 0 0 6100 7000 1750
16 0 0 0 4880 7970 2000
17 0 0 0 3660 8940 2250
18 0 0 0 2440 9930 2480
19 0 0 0 1220 10900 2730
20 0 0 0 0 11880 2970

378

e 10. 5 E @S c e n a r :rp Ac-r-eace oy lal"d use categories
t7te 20 year- stucy oerioa.

.... ......
tj EN E - M I N G PEAT RECLAIMED
MINE A G R 1 C FOREST
YE P.I WAI E R 7 C_ T L, R B E_ D SH RUB

0 Q@ '780 1'37E-'-O 0 0 5460
0 750 i 8920 1100 0 5230
0 7 *,:-:'0 18080 2200 0 5000
0 630 17240 3300 0 4770
0 660 i6400 4400 0 4540
5 0 6'.30 i5560 5500 0 4310
k 0 580 4-4350 6000 1100 3970
7 0 530 13140 6500 2200 3630
8 0 480 1.19"30 7000 2640 3950
0 430 .07,::'0 7500 3520 3830
10, 0 .-".Bo 9510 80010 4400 3710
0 300 7610 8900 5680 3510
- 5710 9800 61360
0 2 @-" Q7) 3310
0 140 ;;Slo 10700 S240 3110
0 60 11.3 10 11600 9520 21310
1 '77) 0 0 0 i 2500. 10800 2700
0 ol 0 10000 .12600 3200
0 0 0 7500 14SIZIO 3700
DO 16800 4200
B 0 0 0 50V
0 0 0 2500 18800 470LA
20 0 0 0 0 20800 5200

379

Ta pi e 10. 5F: Scertaric, Area 4 A-reatoe O'y' jA ri Cl Q. L@ CLRI@; 0 CC; 3. e s
trie E-NI vear stuc.v

OPEN PRE-MILNING 7'R L C A D
YEAR WATER D S T U R B E D Sri R,,'-., B Mll I NE .. -f r- .- - - --
i- Ri-

0 130 91-10. 7280 0 0 oo
130 860 6. 9 0 e., 6 B 0 0 44130
2 130 810 65'LO 1360 0 4 18. CA
3 1 1-1-5 0 7E@,O E, 1. 4 0 2:, 0 4 0 0 r:) 0
4 3 V., 10 55 7 F, 0 2 7 @_-_'O 0
5 130 El El: 0 5 3 El, 0 3400. 0 -.3 /13 0
6 8.10 610 A- 9: 4 CA 34`3 0 0 " 150
7 122,0 560 ZI-500 3580 0 3140
8 1700 510 4 0 E, 0 "35 E, 7 0 60 ".3000
9 2i8o 460 1_31 S 2 0 3760 iso 2850
0 ;R5E.10 4@, 0 131 i 80 38150(140) 190 27 10
ii 2790 330 2 15 .3 0 4 8 3 0 i 3-',-% 0 2 "', 0 5 7 0
.@2 30*70 250 :,,BBQI 4610(520) 2140 C440.
13 3280 170 123 0 9 9 0 (7 10') --,o
:,.4 32 4': @ Q) 90 580 "i370(900.) 420
15 3700 0 0 t750(10,90) 360 21 0 a 0
'00 4 4 0) ",600
6 4010 0 0 4 6 2
A ---450(1790) 3 21 0 120
17 4-320 0 IZ
18 4640 0 0 0 ( 2 14 Qi 260 3 E, 4 0
. 150 (2490), C2.4 0 4 i F-0
qq 4960 0 0 1
20 5280 LA 0 0 2 3, 0 4 6 3 0

Nurilbev'S Irs Dare-ritrieses reoreserit t,,-ie resicleritia.1 ar'eas.

380

10.6 Appendix for Section 6.2.1.2: Nutrient Yieilds and Surface
Water Eutrophication

Table 10.6A: Land use acreages used in calculations for sections
6.2.1.2 and 6.2.1.3

Scen- Area Year Naturally- Crop land Pasture Open Resi-
ario vegetated & Actively Land Water
dential
Mined

1 1 0 15818 0 0 0 0
10 10702 3662 0 1454 0
20 6054 8310 0 1454 0

1 2 0 7142 0 0 0 0
10 4420 2670 30 0 0
20 2042 5010 90 0 0

2 1 0 30000 0 0 0 0
10 23640 3168 285 2907 0
20 4875 20943 1230 2952 0

2 2 0 15000 0 0 0 0
10 11820 3123 57 0 0
20 2460 12294 246 0 0

2 3 0 26000 0 0 0 0
10 21280 4525 195 0 0
20 4200 20750 1050 0 0

4
2 4 0 13000 0 0 0 0
10 10127 760 53 1954 106
20 3852 2300 214 4280 21354

Notes:
Naturally-vegetated includes reforested, buffers
Scenario #3 = Scenario #1 at years 0 and 10

381

TAqtE F0. 6 B: General Ranges of Primary Productivity of Phyloplanklon and Related Characteristics
of takes of Different Trophic CalegiWes"

blean
11,11milry Light
11'soduc- Phyto. 11,11)10. lixtindion Total Total
lirlIV6 P10161,14"I plankton Chlorophyll Cactu- Organic 1101orgulde
flog C in -I Density Biomass s Dominant ticills Cadjon Total F Total N Solids
Tropleit Type day - 1) (Callm-11111KCM-2) (mgm-2) 1`11)ICIP10111tion Non-11 1118gl-1) Wa 1 '9 (OK 1 1) (Ing I - 1)

Uloa-1111glAW111111k. <50 < I <50 0.01-0.5 0.0.3-0.8 < 1-5 < 2-15
Oligotillpille 50-300 20-100 0.3-3 ChlysophytVat., 005-1.0 < 1-3

011go-enesolrophic 1-3 D11111phyllt.1c. 5-10 M-W 10-200
00
MOMOIF01111iC gm-low 160-.1w 2-15 0.1-2.0 < 1-3
hieso-eittiophic 10-34) SOO- 1 !00 A
E111follisk. > HNIO > 3(9) * 10-500 11acilhorloplivecar, I]A-4.0 5-30
Cyalloployceble.
>10 30->.5000 rAxi-> ISMO 4#X)-6(MMXI

Dystlopilic < .50-500 <50-200 0.1-10 1.0-4.0 3-30 <1-10 < 1-519) 5-2(k)

*hWilified from Likens 11975). after inatoy saidwis and sources.
"no-feirdox 14) approxituately ilea plinlawy pf"411101rity. 5111@h as weasured loy the IIC methoil.

Oletzel, 1975)

PHOSPHORUS EXPORT (KG/tIA/YR)

GQ
? ?

> FOREST

0 cu w @-aw
0 :j w 0
H JaA ;j
0 m
0 ROW CROPS
H
m w En 0
aq m rt
0 cn rA

rD 0
0 Fh NONROW CROPS
(D Fl H
rt 0

0
@d
0 PAST
U.) F" H i
00 "0 OA 0 r.
Lo OD (D rj)
rt
(D (D
MIXED AGRICULTURAL
0 co 0

;uw 0
rt 1.4 m
FA URBAN

(a OQ

ca w rt
rtm 0 Ln
m
C)
0 ? ? ?

OD
0 %D FEEDLOT
H OD MANURE STORAGE
ct0 0
t3l c:

Ln
,@q 0
@ROW @CR 0 P @S@@

FEE'TTOOTRAGE
U
='=M=AN =RE

10 n rtm
0

41,50 38.47
25- 79.6 30.85 80001 7979.9
Cr.

20- 4000-

X CC
>- CL
X w
CC
3000.

0 w
10 Uj
w 2000- U-
z
Q.) 0 cm
z C=
W V)

5- 1000-

Figure 10.6B: Box plots of nitrogen export coefficients from various
U

land uses (from Reckhow, Beaulac and Simpson, 1980)

x marks areal. yields determined by Skaggs et al., 1980
and Gregory et al., 1984, for peatland systems in
North Carolina

384

10.7 Appendix for Section 6.2.1.3: Trace Element, Pesticide
and Coliform Bacteria Yields
I

385

Other pesticides currently in use in the area (Dr. J. W. Van Duyn, personal

communication), and the crops on which they are used, include the following:

Herbicides

Corn and soybean, pre-emergent:

Alachlor (Lasso) - high organic soils

Atrazine - used with Alachlor in low organic soils

Linuron (no-till soybeans)

Soybean, post-emergent;

Bentazon (Basagran)

Acifluoron (Blazer)

Fuselaid

Corn, post-emergent:

2,4 D

Dicamba

Ametryn

Linuron

Small grains:

2,4 D or Dicamba (at time of N-application @ April)

Paraquat (no till)

386

Insecticides

Corn (1 application at planting) of either:

Carbofuran

Chlorpyrifos

Phorate

Turbufos

Soybean, mainly:

Phorate

Late-planted soybeans typically are treated

in August with either:

Carbaryl

Methomyl

Fenvalerate

Permethrin

Small grains (typically on @ 10% treated, mainly for army worms):

Carbaryl

Methomyl

Malathion

Toxaphene (being-phased out)

387

Air Quality Assessment

Introduction

The air quality impacts of peat mining and utilization are impossible

to predict except on a site specific basis. Model predictions require

quantitative information on the flux of emitted pollutants from each

source, the location of each source, the location of all sensitive

receiving areas with respect to the sources, comprehensive meteorological

data for the region and an appropriate mathematical dispersion model. In

addition, the height above ground at which the pollutants are emitted and

any ameliorating conditions must be factored into the model calculations.

The cost and complexity of both data gathering and computation limit air

quality model development to immediate cases of concern; long range,

cumulative air quality impacts are rarely undertaken because of the

additional costs and the uncertainty that exists in source location. To

date, an air quality impact assessment has only been performed for that

part of the Scenario,l peat mining area operated by Peat Methanol.

Associates. Predicted impacts of both fugitive dust emissions during

mining and pollutant emissions from methanol conversion are reported in PSD

permit applications of PMA to the NC Division of Environmental Management.

Because these two source types are assumed to be the same that would exist

in the scaled up peat mining development of Scenario 2, this could provide

the basis for development of air quality impact models involving the

integrated impact of the largescale peat mining postulated in Scenario 2.

None of the companies currently considering peat mining in the region

has developed such an integrated impact model. This is understandable

since they are not, as individuals, knowledgeable about the specific plans

of other companies and the NC State permitting process deals with PSD

permit applications on an individual, sequential and incremental basis
389

rather than planning for and partitioning allowable pollutant increments on

the basis of anticipated cumulative integrated impacts.
An attempt to take an integrated view has been made in a study
conducted by the firm of Rogers, Golden and Halpern, issued as CEIP Report
No. 14 "Design of a planning program to help mitigate energy facility air
quality impacts in the Washington County-, North Carolina, area." This

report has been criticized for the additive scaleup assumptions used in

extrapolating impacts resulting from peat mining and conversion on 15,000
acres of land to those resulting from development eight times as large.
Additional criticism has been directed at the failure to consider options
for amelioration of impact that are possible through pollutant source

spacing options and pollution control technologies.

390

Air Suality standards

Relevant air quality standards have been discussed recently in CEIP

Report No. 14 which specifically focused on peat mining impacts in the

Pamlico /Albemarle sound area. State and Federal regulations set upper

limits on permissible concentrations of specific pollutants as both annual

averages and short-term maximum permissible concentrations. The regulated
pollutants are carbon monoxide (Co), hydrocarbons, nitrogen dioxide (NO 2),
sulfur dioxide (SO 2 lead, photochemical oxidants (ozone) and

particulates. Table I lists the primary and secondary standards. Primary

standards are intended to protect public health; secondary standards are

intended to protect public welfare. The standards differ among different

class areas, two of which exist in the peat mining area. Class II areas

are those thought to tolerate some degradation of air quality that

accompanies normal, well-managed growth. Class I areas are more sensitive

and cannot tolerate further air quality deterioration. . These are often

park and wilderness areas. The Swanquarter National Wildlife Refuge in

Hyde County is such a Class I area in the peat mining region and it

requires special consideration in assessing air quality impacts. All other

areas are Class II.

In addition, regulations designed to Itprevent significant

deterioration" (PSD) are intended to limit increases above existing
baselines in concentrations of two pollutants JSO 2 and total suspended

particulates. These are listed in Table 2. These are.intended to provide

protection to areas with air that is currently cleaner than the ambient air

quality standards by limiting additional increments of pollutants.

Particulates from fu6itive emissions during peat mining are exempt from PSD

increment limitations.

391

Table 10.8A: National Ambient Air Quality Standards

Finally it is required that Visibility (which is primarily a. function
of particulate.concentrations) should not lie reduced in Cl ass I areas.

Pollutant Primary SecSndary
Pg/m (ppm) IIg/m (ppm)

CO
80 hr Max 10,000 (9) same
1-hr Max 40,000 (35) same

Hydrocarbons
3-hr Max 160 (0.24) same
(6-9 a.m.)

N02
Annual Arithmethic Mean 100 (0.5) same
24-hr Max 250 (1.25)

Photochemical Oxidants (ozone)
1-hr Max 235 (0.12) same

Particulates
Annual Geometric Mean 75 60
24-hr Max 150 150
so 2Annual Arithmetic Mean 80 (0.03) --
24-hr Max 365 (0.14) --
3-hr Max 1300 (0.5)

Lead
3-mo Max 1.5 same

392

Table 10.813: Maximum Allowable increases under
prevention of significant
deterioration (PSD) regulations

Pollutant Micrograms per
cubic meter

.CLASS I

Particulate Matter
Annual Geometric Mean 5
24-hr Maximum 10

Sulfur Dioxide
Annual Arithmetic Mean 2
24-hr Maximum 5
3-hr Maximum 25

CLASS II

Particulate Matter
Annual Arithmetic Mean 19
24-hr Maximum 37

Sulfur Dioxide
Annual Arithmetic'Mean 20
24-hr Maximum 91
3-hr Maximum 512

393

Uncertainties in Estimates of Fugitive Dist Emissions

There are large uncertainties that must be:
associated with these estimates. In part this results from the empirical.
nature of the source emission models. Most of these were derived from coal.

storage models which may not be appropriate to peat. In particular, dried
peat will likely have a much lower bulk density than coal and thus be more
easily resuspended by wind and held in suspension-more easily.

In addition, although some conservative assumptions have been included
in the PMA analysis/ there are several assumptions that tend to minimize
estimates of fugitive dust emissions. First, it is assumed that the fields

will be tilled 16 times each year in order to remove 16 inches of peat for
dryingIat one inch increments. However, PMA's Draft Environmental and
Occupational Health Monitoring Plan Outline states that the milled peat
harvesting process removed only as much as 7% of the peat moisture with

each turn to a depth of 4 inches. To reduce moisture from 81% to 40% would

require a minimum of about 6 turns or 24 per year to mine 16 inches depth.

There will be a separate milling process associated with each turning which

could resuspend additional peat.

Second, fugitive dust emissions are assumed to occur only during

tilling (i.e. turning). However milled, dried peat will lie on the surface

'in what is described as a "thin fluffed layer" that should be easy to

resuspend by wind erosion. This may be as important a source of fugitive

dust emissions as tilling.

Third, field storage piles (I mile by 70 feet by 10 'feet high) are

assumed to behave as coal storage piles in terms of dust emissions. As

mentioned earlier this may not be the case. Also, a seeming impossibility

exists in the emission model equation used by PMA. Wind erosion from

394

storage piles is calculated to be proportional to the average peat pile

turnover in days (33 days in PMA's case). If the piles are never turned

over (i.e. utilized) the turnover time is infinite and the emission rate

is, therefore, also infinite. This cannot be true. In addition model

calculations made by PMA assume an 80% reduction in emissions due to wind

speed control using screens. There is no adequate justification for the

choice of this reduction factor. Such screens would need to be taller than

the 10 foot height of the piles to be effective and would probably need to

be on both longitudinal sides of the storage pile to be effective. If wind

screens are not used or are not as effective as assumed above, dust

emissions from storage piles would be substantially increased.

Last, the dust emissions resulting from truck traffic will vary with

the average round trip distance travelled along unsurfaced roads between

field storage piles and plant storage. PMA has used an average round trip

distance of about 3 miles to calculate inputs for subsequent dispersion

modeling. However, the choice of initial and worst case harvesting

locations are all clustered around the methanol plant peat storage sites.

If the whole 15,000 acre PMA site and other sites of Scenarios 1 and 2 are

to be considered, round trip transport to either a methanol processing

facility or transshipment points for offsite use will certainly be greater

with consequently greater fugitive dust-emissions.

It is worth noting that CEIP Report 14 cites a paper by Ertugrul and

Sober (1979) that fugitive dust emissions during peat harvesting could be

as high as 10 percent of the total peat harvested. This is equivalent to

96,000 tons per year based on the 1900 acre/yr mined under the assumptions

of PMA in Table 5.4A,Although this. seems unrealistically high and the

assumptions leading to the 10% figure are not immediately available, it

395

points to the same two conclusions previously reached: First, there are
serious uncertainties in our estimates and our ability to estimate fugitive
dust emissions during peat harvesting and second, existing estimates by PKA
be too low. There is an obvious need to refine these estimates if the
emission inputs used in air quality dispersion models are to be of any use.

Critical receptors

Two critical receptor types exist in regard to air quality impacts.

First is the offsite boundary of the peat mining and processing facility,

where air quality deterioration would first impact the general public.

There are an infinite number of possible receptor points along the!

peripheral boundary of any peat mining operation. As harvesting-operations

shift throughout any permitted mining area, different points along the:

periphery become the most sensitive receptor s. This complicates most

modeling efforts. Worst case analyses can probably set upper limits on

impacts.

Second is the Class I area of the Swanquarter National Wildlife

Refuge, which is a more sensitive receptor. Given the distance from the
PMA (-27 km),,and most other proposed mining areasI it could probably be
modeled as a single point receptor for each proposed mining area which

could, in turn, be approximated as individual point sources. An exception

might be Area II of our Scenarios which lies nearest to Swanquarter NWR and

which lies approximately NNW of Swanquarter, the direction from which the

dominant wind blows during the September to November season. More detailed

modeling of this source/receptor pair might: be necessitated as a result.

396

In addition)the Mattamuskeet and Pungo Lake National Wildlife Refuges,

although not Class I Areas, should perhaps be considered special receptors.

The impact of peat derived particulates on visibility at -Pettigrew State

Park (Phelps Lake) should also be considered for special treatment.

397

Monitoring Requirements

CEIP Report No. 14 has considered extensively the needs and purposes
of air quality monitoring in relation to peat mining and use in the area.
Their evaluation and generally sensible recommendations will be quoted
verbatim in what follows.

Need for Monitoring

Air quality monitoring is an essential. component of an air quality
maintenance/air pollution control program. Monitoring provides the inf ormation
needed to judge compliance with air quality- standards and chart trends or
changes in air quality. In order for an air quality monitoring network to provide
the required data, the design of the network must take into consideration factors
such as existing pollution levels, meteorology, topography, population, and source
distribution.

The purpose of this chapter is to present several basic concepts and
requirements to be considered in upgrading the existing monitoring system to
track more closely the air quality impacts of peat mining and various end uses in
eastern North Carolina. Suggestions on the future placement of air quality
monitors will be offered. These monitors will augment the existing State
network to keep closer surveillance on emissions from peat mining, transpor-
tation, and combustion, as well as conversion to peat methanol. In addition to
regional surveillance, the use of specially designed intensive monitoring pro-
grams will be suggested to improve knowledge of particulate emissions charac-
teristic of various peat mining, transportation, handling and storage activities.

Operation of the State monitoring network is the responsibility of the
Division of Environmental Management (DEM). The Division operates twelve
monitors that sample the air continuously as well as seventy-two manual
monitors that sample the air for a 24-hour period once every six days. In the
vicinity of the study area, there are only three DEM air quality monitoring
stiltions: Plymouth (50 29 NO 2 and particulates); Washington (particulates); and
Elizabeth City (particulates)."
1. The existing State network is clearly inadequate to document air
quality and trends in the study region, yet the air quality impacts of peat mining
must be monitored in order to protect the area's natural resources and to ensure
C .4. -

398

A new monitoring
system must be designed to complement the existing system. Eff ective resource
management and the design of an eff ective monitoring system require a
knowledge of the overall physical and ecological systems in the region where
peat mining is now or will be occurring. Planners need to know about the
components of the natural system, their natural variability, and vulnerabiEry to
disruptions caused by peat mining and reclamation, and the critical threshold
levels beyond which a problem is created. Knowledge of a.U these elements is
difficult to obtain, as the area in which peat mining is ongoing or contemplated
is an isolated one, about which little has been documented,

Any new monitoring system to be constructed must serve the f ollowing
purposes, at a minimum:

0 Ricord compliance of peat mining and development activities with
existing environmental standards;

0 Provide information for general protection of the Class I area
(Swanquarter Wildlife Refuge), as well as the sensitive areas of Lake
Phelps and Pungo Lake;

0 Provide information to determine the need for changes in environ-
mental standards, permit conditions, or mitigation design; and

o Provide information to more accurately quantify emissions from
peat-related activities to make possible more accurate prediction of
the effects of future development.

Monitoring of Regional Background and Trends

Good definition of regional air quality will require installation of at leas t
two air quality monitoring stations.@.

399

One station should be located within the boundaries of the Class I area and
the other should be located just downwind (to the east or northeast) of the active
and proposed mining areas between Pungo Lake and Lake Phelps. The ourpose of
the Swanquarter monitor would be to determine current ambient air quality.
Since the Swanquarter National Wildlife Refuge has been designated by the
Federal government as a Class I area, the level of ambient particulates cannot
be increased more than 5 micrograms per cubic meter as an annual geometric
mean or 10 micrograms per cubic meter as a 24-hour average over the baseline.
Similar, highly restrictive limitations apply to 50 2 There
has not been any air quality monitoring within the Refuge, so accurate
determination of the "baseline level" of ambient particulates or any of the other
criteria pollutants is impossible. If the air quality of the Refuge is to be
protected in the face of projected regional development, sampling must be
initiated to establish the baseline air quality. However, such a monitor would
not likely be capable of providing increment tracking information or dispersion
modeling for increment consumption in that monitors are unable to differentiate
between impacts from those sources consuming increment and variations in
impacts from existing baseline sources.

The overall purpose of the second monitoring station is to quantify air
quality in the heart of the region near Lake Phelps and Pungo Lake.

LAKE PHELPS is a sensitive area that may be adversely affected by peat
operations. Lake Phelps borders the area where First Colony Farms and others
are now or wul soon be mining peat.

400

The sensitivity of this area tends to support the location of a monitoring station
near Lake Phelps, at a location downwind from peat mining operations.

PUNGO LAKE, a 12,350-acre National Wildlife Refuget is another sensitive
natural area within Washington County that the County feels should be preserved
in the future for scientific, ecological, educational, and recreational purposes.
The lake has been designated as a wildlife refuge because of its importance as a
wildlife habitat, its representation of a protected pocosin ecosystem, and its
!Uu3-tration of geologic and geomorphic processes. Its proximity to present and
proposed peat mining areas supports the placement of monitoring devices in the
vicinity.

Data collected by this second monitoring station will serve three useful
purposes. First, when winds are blowing from the peat mining areas and fuel
conversion plant toward the monitors, this station will record the general air
quality impact of the aggregate of these activities. Second, when winds are
from other directions, this station will be used to determine the true background
pollutant levels for the study region. These background values may well be
substantially different from the EPA values heretofore assumed. The third use
of data from this station will be to monitor the trends in air quality caused by
expansion or an increase in the number of nearby sources. In this manner,
modeling need not be relied upon exclusively to keep track of increment.

In addition to augmentation of -the existing State network for purposes of
documenting overall regional air quality, implementation of special purpose
0
particulate monitoring systems should also be considered. The primary purpose
of such systems would be to determine fugitive emissions and their associated
impacts. Reliable fugitive emissions factors simply do not exist for many peat-

401

related activities. Studies should be designed to determine emission factors as
functions of wind speed, moisture (precipitation, evaporation, and relative
humidity),. and activity (vehicles per day or tons of material handled) for the
following:

0 Peat mining,
0 Peat transportation, and
0 Peat handling and storage.

The emission factors developed for these activities must include mass emission
by particle size to be successfully used in dispersion modeling

Since the operation of monitoring programs entails some considerable
expense, the responsibility for their implementation and maintenance should be
shared. by the applicants for peat mining and other peat-related licenses. The
Department of Environmental Management anticipates that a monitoring
network will eventually need to be established, and that a significant portion of
the monitoring will likely have to be performed by the mining operators. The
Division's approach to monitoring peat mining impacts is to allow, limited initial
mining to proceed while affording the opportunity to evaluate the mining
impacts. From these evaluations, operational conditions and monitoring
requirements can be applied to future permits or renewals. Currently, Air
Quality Permits issued to peat mining operations are only issued for one year.

Compliance monitoring can also be required under the State's Mining Act
of 1971. Although the phrases "unduly adverse" and "significantly adverse" are
used in the Mining Act in reference to effects on wildlifej fisheries, and
publicly-owned parks, forests, and recreation areas, there are no concrete
standards attached to these phrases. Revision of the Mining Act may be needed
to quantify these standards, thus allowing lack of monitoring to be cited as a
reason for denying mining permits.

For the purpose of studying PSD increment consumption by sources that
could potentially locate in the region, it will be necessary to determine the
amount of increment remaining at*various receptor locations in both the Class I
and Class II portions of the study region. This will require compilation of a
special source data base (inventory) of emission changes both inside the region
and at sources outside the region but having a significant effect upon the region.

402

Model Validation/Calibration

Accuracy of dispersion model predictions 13 generally considered to be
within a factor or two of the actual concentration. Modeling accuracy lessens as
source-receptor distance increases or as influence of topographical features that
violate model assumptions (such as nearby significant bodies of water) become
important. Both of these problems leading to accuracy degradation are present
when ISC is used for predictions in the Class I area. The most restrict ive Class I
so 2 PSD increment is less than 2 percent of the corresponding NAAQS. This
almost infinitesimally small concentration increment is extremely difficult to
predict accurately. It is almost beyond the current state of the art. In addition
to the factor of two uncertainty generated simply by modeling theory and
assumptions, other sources of possible inaccuracy are present. A modeling
analysis can be no more accurate than the input source emissions data. Sources
not included in the inventory that are actually present, sources that are included
but are actually defunct, and errors in emissions or stack data may seriously
degrade the modeling.

For all the above reasons, a validation of modeling results for the Class I
area is considered an absolute necessity. A validation program using quality
assured monitored data and emission information from the sources now affecting
the Class I area should be developed. Calibration of ISC for.the study region
may be possible if the validation results are disappointing.'

403

10.9 Appendix for Section 6.7: Local Economics and Employment.

404

SOCIO-ECONOMIC IMPACT ANALYSIS

Large-scale developments have the potential to greatly affect a region's

people, communities and governmental-institutions. For developments that are

resource based, and for developments that occur in sparsely populated agricul-

tural areas, the potential for important impacts is especially great. Peat

mining in North Carolina possesses both these attributes. The socioeconomic

analysis in this report is designed to: (1) establish a general framework

for analysis of the social and economic impacts of peat mining in North Carolina

and (2) estimate those impacts to the extent possible given the time constraints

placed on thi,s study and the general lack of available data necessary for a full

understanding of peat mining impacts. This Appendix expands somewhat on the

procedures in the basic report but does not present again those results pro-

vided in Section 5.8.

It is useful to separate economic impacts into two components: (1) private

sector impacts and (2) public sector impacts.

Private Sector Impacts

Through production of output that is demanded locally and/or nationally,

peat mining will create jobs and provide income through salaries paid to

workers and through increased demand for materials from input and service

supplying businesses. These are often called the direct effects of an expan-

sion of an industrial sector.

In addition, these direct effects lead to additional income-generating

effects: (1) through wage earners spending of money received from their

employment at the new or expanded industry and (2) through direct suppliers

purchasing additional materials and hiring labor in order to provide the

inputs and materials to the peat mining industry. These are often called

indirect effects. More specifically, the trickle-down cumulative impact of

wage earners spending their money is often called the consumer indirect.
405

effect, while the trickle-down cumulative impact of purchases of inputs is

called a producer indirect effect. In cases where wage earners spend a large

proportion of their earnings locally, and where input purchases are made

locally rather than from producers located great distances from the -site of

the new industry, the indirect income and employment impacts can be 'Substantial.

It is important to understand that the economic impacts of peat miniig on the

private sector is not limited to their payments of wages to employees nor to

purchases of supplies to construct and operatE- the peat mining facility

Direct employment and income effects are normally estimated from studies

relating the value of the output of the new industry to its projected employ-

ment and wages paid, and to projected expenditures for construction or opera-

ting materials. Indirect employment and income eff ects are typically estimated

using input-output models that provide output employment and income multipliers

by which peat mining output levels can be multiplied to obtain the desired

"trickle-down" consumer and producer indirect effects. Alternative output

levels can be developed from phasing of plant capacity schedules or plans

and scenarios of multiple industry possibilities.

Public Sector Impacts

Economic growth and development affects the fiscal affairs of local

government by providing revenue and by causing government to incur additional
expenses. On the revenue side, the process of constructing and operating the

peat mining facility will provide revenues for, the operation of state and

local government. Currently included in North Carolina are, for example,
business and personal property tax, sales tax, utility franchise tax, intangible
personal property.tax, motor fuel tax, corporate and personal income taxes,
unemployment taxes and inventory taxes. Some of these taxes go to the state
and others are paid to counties and cities. The amount of these funds avail-

able locally depends upon how taxes are administered locally and upon how the

406

state shares with local government the taxes it collects. An additional factor

is whether a severance charge is assessed and, if so, how it is distributed.
In addition, new residents in the area will be assessed sales taxes on pur-
chases and property taxes on homes and personal property. Taken in sum, this
revenue is available to pay or help pay for the public service and facilities
costs local government incurs as a result of the development of the peat mining
industry and the new residents it attracts.

The fiscal cost impacts of growth and development upon the public sector
are understood or acknowledged to a lesser degree than are the private sector
income and employment impacts, because of the less obvious (on the surface)
tie between the arrival of new workers and families and the demand for public
services and facilities they create. However, these costs and benefits are
just as real and must be estimated to fully understand the total impact of the
peat mining industry on coastal North Carolina residents.

Public service and facilities costs depend largely upon the influx of new
residents (workers and families) resulting from the construction and operation
of the peat mining facility. This, in turn, depends upon the level of d,irect
and indirect employment generated by the facility, the level of unemployment
and skills available within the area, the labor force participation rate, the
extent to which workers currently employed and living elsewhere commute to the
peat mining facility rather than relocate their residence, and family composi-
tion of the new residents (size of family, number of children, whether both
spouses work, etc.). Community service impact models can be constructed at
various levels of detail to estimate these impacts.
In the public sector, the issue is not whether the peat mining facility
provides revenue to or generates costs for local government. It is clear that
both costs and revenues will be generated. Rather, the issue-concerns the net

balance, that is, whether or not the public costs generated by the peat mining

407

activity are offset by revenues generated. Both short-run and long-run time

frames must be analyzed. Further, it is essential to know the cumulative

effects of the development since multiple developments may occur in which case

the impact of the sum of all activities may exceed the sum of the individual

parts.

408

Long-run Impactsl

Long-run impacts are those that have occurred after the economy has had a

chance to fully adjust to the new activity and which are expected to be long

lasting. Two types of impacts are considered: economic impacts and fiscal

impacts.

Economic Impacts

Stimulation of the economies of Tyrrell, Hyde, Washington and surround-

ing counties is assumed to occur because of rising demand for the final products

of the peat mining industry. Increased demand for these exportable goods leads

to direct and indirect employment and income increases in those counties and,
perhaps, in other counties as well.2

The estimates presented in Section 5.8 are based upon a number of assump-

tions and upon data that may or may not reflect what might result in reality if

the plant were to be constructed. Although this is the nature of any study of

such a type because of the highly speculative and uncertain nature of key pieces

of data, the roughness of the estimates should not be underestimated. Many of

PMA's assumed coefficient levels were used for the direct plus indirect impact

without verification. Also, the 1.55 income multiplier derived in a coal mining

study but used here may not be accurate for peat mining. Without the benefit of

time for an in-depth study and analysis, these assumptions are the best available.

Nevertheless, it can be said that the PMA study ignores the indirect effect of

constructing the peat mining facility and, thus, underestimates the long-run

employment, population and income effects of the facility.

IThis report has benefited greatly from the work of Stinson, et al. [1982].
2A]though the foc-is of the scenarios is upon Tyrrell, Hyde and Washington
Counties, the economic impact will extend far beyond those counties. PMA
assumes workers will commute 1 hour 15 minutes to work on the project, thus
affecting 12 counties. The PMA Socioeconomic Analysis uses a study area of 10
counties and, since this section is heavily dependent upon their data, the
same is used here.

409

It might also be worthwhile to note that the information available in 'the

PMA study does not lend itself to providing the type of income estimate normally

derived from an input-output model. That is, the income estimate from PMA is

the retail sales volume generated by the spending of new workers and their

families, whereas an input-output model uses the value of output from the new

industry. In the latter case, changes in output level (assumed to bE! generated

by increased demand for its products) works through the sectoral interdepend-

encies in the model to provide estimates of changes in total area income

including indirect employment and income from the industries providing services

and supplies to the mining activity.

Fiscal Impacts

Net revenues going to local governments as a result of

peat mining may exceed the costs of services and facilities demanded by new

residents. On the other hand, three types of developmental problems might con-

front local governments in the impacted area. First, long-run fiscal problems

may arise in cases where a local government must provide expanded services and

facilities but is unable to tax the new facility. This is a spillover problem

where new residents locate outside the political boundaries of the local govern-

ments that have the power to tax the facility. Thus, costs of facilities and

services to meet demands of residents are incurred without receipt of offsetting

tax revenue. Second, even if long-run benefits were to exceed costs, there may

arise front-end or short-run fiscal problems where revenues generated lag cost.

incidence. For example, local government may need to increase the school budget

immediately upon arrival of new residents, whereas tax re venues generated by

those residents or from the peat mining facility itself will be lagged 1, 2 of,

more years beyond that time. A short-run cash flow problem will thus arise.

Third, the cumulative impacts of peat mining must be studied. To some extent,

the scenarios address different levels of development and, thus, go beyond
410

estimation of the impacts of a small-scale test facility. However, if develop-
ments beyond current expectations were to be attracted, impacts will likely
increase geometrically rather than arithmetically. For example, fiscal costs
could increase geometrically as excess capacity in the school systems is exhausted,
as full employment is reached, or as the road system becomes overloaded. Many
of these costs may not arise with a small facility. The report of the Peat
Mining Task Force [19831 indicates that success initially could lead to a
three- to eight-fold expansion of plant capacity. If such is a possibility, an
in-depth study of the cumulative impacts is required.
Fiscal impacts will vary by county and city in the 10-county area. Taxes
of several categories will be contributed directly or indirectly by the peat
mining facility: business property taxes; unemployment taxes; intangible
property taxes; inventory taxes; corporate franchise taxes; sales and use taxes;

and income taxes on wages and proprietory income. However, the distribution of
these local and state revenues to individuals and counties will vary greatly.
For example, Washington County will receive the bulk of the property taxes,
estimated by PMA to be $900,000 per year. Municipalities and other counties
may receive little. Many of the tax categories are paid directly to the state.
How and to what extent they are distributed to impacted counties and municipali-
ties will partially determine whether the net fiscal impacts are positive or

negative.

The demands placed on various local governments by new residents will vary
in similar fashion. It is estimated by PMA that Chowan and Washington Counties
will receive most of the influx of new residents. Yet, Washington County will
likely receive the largest share of revenue generated by the facility. Chowan
County, and particulacly the City of Edenton where many new residents will
probably reside, will receive much less. Other examples could probably be

411

identified with further study. Thus, while a major issue is simply whether

long-term benefits of peat mining exceeds its costs, the distribution of those

costs and benefits is of equal importance to the citizens of the cities and

counties throughout the impacted area.

The PMA study generally cites an adequacy of public facilities and ser-

vices available to meet the demands of the new residents. This con-

clusion deserves a review for two reasons. First, the underestimate of total

employment generated by the peat mining facility suggests that the demand

placed upon public faciliti es and services is also underestimated. In some

cases, the excess capacity may be exhausted requiring new public investments.

For example, the increased number of students may require an additional school,

especially if the influx of students is concentrated in only two areas, Washing-

ton and Chowan Counties. Further, even if facilities are adequate, several new

teachers will likely need to be hired, and each new pupil will need to be

supported.

The fiscal impacts of peat mining require an in-depth analysis of the

amount and distribution of costs and revenues between counties and cities

throughout the impacted area. Unequal distribution may lead to increased taxes

in some areas while at the same time providing great surpluses in others.

Cities especially may not fare well fiscally, because they can be expected to

.bear a large proportion of the demand for new services and facilities, yet

receive little property tax revenue because the mine will lie outside of their

taxing jurisdiction. However, full understanding of the potential for these

problems requires an in-depth analysis of state aid formulas and city and county

assessment policies and expenditure patterns.

412

Short-run Impacts

Short-run impacts are more difficult to estimate than long-run impacts,

because a year-by-year schedule of costs and benefits must be estimated rather

than selecting a single year in the future as is the case for long-run impacts.

However, the year-by-year assessment is essential, because tax revenue

generally lags the demand for services and facilities, and cash flow problems
for local government may result. For a large-scale facility such as planned,
the short-run impacts can be significant, because the number of construction
workers greatly exceeds permanent employment after the plant becomes opera-
tional. Thus, the number of employees peaks during the middle of the construc-
tion period, while tax revenues peak after the plant becomes operational.
As with the long-run economic impact, it is desirable to estimate both
direct and indirect eaployment and income effects of facility construction.
However, two key differences in the short-run and long-run impacts are (1) the
short-run impacts must be calculated on a yearly basis and (2) the short-run
employment and income multipliers are less than the long-run multipliers,
because input supply and consumer service industries will not develop due to
the short-term nature of the demand for their services. It would not pay to

invest in service facility construction if the number of workers would be

greatly reduced in 2.5 to 3 years or less.

Data are not readily available to estimate the short-run multipliers

necessary for estimating service employment and income to add to the direct

impact of construction workers. However, the proportional underestimate of

the total economic effect is likely somewhat less than was the case for the

long-run impact analysis.

413

Because of the large number of tax categories and because estimates of

direct plus indirect employment are unavailable, it is impossible to project

whether or not a short-run fiscal problem in certain areas may exist. However,

conclusions reached by PMA that sufficient excess capacity exists in the area

to eliminate the need for large, new expenditures for many public services

appear reasonable in most cases. However, operating budgets for some services.

will increase while capital expenditures may need to be speeded up for others.

School budgets will need to be larger even though facilities may be adequate.

Improvement and expansion of sewer and solid waste disposal facilities may
require added funds in some localities based on data in PMA's study.

As with the long-run impact, the distribution of costs and benefits will

be important. Some areas will experience revenue shortfalls, while others will

experience surpluses.

Estimation of demands for services requires an input-output or community

service impact model to determine the interrelationships between industries

and areas and the appropriate multipliers.

Summary

In summary, the socioeconomic impacts estimated for this study, while
they are the best that could be developed given the time available, should be

used with care. In all cases, they should be considered preliminary estimates

because (1) they are based on secondary data currently available for the area or

(2) they are data developed in studies of mining in other areas of the country.
Nevertheless, it has been demonstrated that peat mining will have substantial

social and economic i mpacts on a large portion of northeastern North Ca rol i na,
especially because of potential inequalities in the distribution of benefits and

costs to different local areas. Further, the framework required for a more in-

depth analysis, one that would provide the data needed, has been demonstrated.

414

References

Stinson, Thomas F., Lloyd D. Bender and Stanley W. Voelker, Northern
Great Plains Coal Mining: Regional Impacts, Agriculture Information Bulletin
No. 452, Economic Development Division, Economic Research Service, U. S. Depart-
ment of Agriculture, Washington, D. C., July 1982. 1
Peat Mining Task Force, Peat Mining Task Force Report, North Carolina
Department of Natural Resources and Community Development, January 1983.
Peat Methanol Associates, Socioeconomic Analysis, May 1983.

415

10.10 Abbreviations Used in the Report

Table 10.10A Abbreviations used in the report

ac acre
ac-ft acre-foot
Ag silver
AP American Peat Company
As arsenic
BACT bacteria
Be beryllium
BMP Best Management Proctice
BOD biochemical oxygen demand
BOD5 biochemical oxygen demand fuve day
BTu British Thermal unit
bu bushel
Ca calcium
CAMA North Carolina Coastal Area Management Act
Cd cadmium
C.F.R. Code of Federal Regulations
cfs cubic feet per second

Cl chloride
cm centimeter

CN cyanate
Co cobalt
Co carbon monoxide
COD chemical oxygen demand
Cos carbonyl sulfide
Cr chromium
Cu copper
DEM Division of Environmental Management
DMF Division of Marine Fisheries
DO dissolved oxygen
DS total dissolved solids
ECU East Carolina University
Elev. elevation
EPA U. S. Environmental Protection Agency
ESE Environmental Science and Engineering
evapotr. evapotranspiration
Fe iron

Fl fluoride
ft3 cubic feet
gal gallon
gpd gallons per day
G.S. General Statutes
ha hectare
HEP Habitat Evaluation Procedure
Hg mercury
hr hour
HSI Habitat Suitability Index
HS hydrogen sulfide

4-16

in inch
IWW Intracoastal Waterway
kg kilogram
Kjeld-N Kjeldahl nitrogen (total nitrogen)
1 liter
LD 50 lethal dose (50% mortality)

LQ Land Quality Section, Division of Land
3 Resources, NRCD
M cubic meter
max maximum
Mg magnesium
mg milligram
mg/l milligrams per liter
mgd million gallons per day
Mgt/mgmt management
mgy million gallons per year
mi mile
mi2 square mile
ml milliliter
Mn manganese
MSL mean sea level
-4tg microgram
N nitrogen
Na sodium
NC North Carolina
NCSU North Carolina State University
Neg negligible
NH3 ammonia
NH4 ammonium

Ni nickel
NNE north-northeast
No./100 ml number per 100 milliliters
NO2 nitrite
NO3 nitrate

NPDES National Pollutant Discharge Elimination System
NRCD North Carolina Department of Natural Resources
and Community Development
NWR National Wildlife Refuge
Ortho-P orthophosphate
P phosphorus
Pb lead
perm permanent
PF Peat Fuels, Inc.
pH a measure of acidity
PMA Peat Methanol Associates
PNA drimary nursery area
PO4 phosphate

ppb parts per billion

417

PPM parts per million
PSD Prevention of Significant Deterioration
R river
RR railroad
Rte route
Sat saturation
Sb antimony
SCN thiocyanate
Se selenium
S.E. standard error
so2 sulfur dioxide
so 4= sulfate

so sulfur oxides
x

SSE south-southeast
SSW south-southwest
T time
temp temporary
TN total nitrogen
tons/yr tons per year
Tot. Org. N total organic nitrogen
TP total phosphorus
TPY tons per year
TSS total suspended solids
UNC University of North Carolina
U.S.C. United States Code
U.S.G.S. U. S. Geological Survey
WTF Whitetail Farms
yr year
Zn zinc

418

CEIP PUBLICATIONS

1. Hauser, E. W. , P. D. Cribbins, P. T. Tschetter. arid R. D. Latta. Coastal Energy
Transportation Needs to Support Major Energy Projects in North Carolina's Coastal Zone.
CEIP Report #1. September 1981. $10.

2. P. D. Cribbins. A Study of OCS Onshore Support Bases and Coal Export Terminals. CEIP
Report #2. September 1981. $10. (NTIS # PB82-202912)
3. Tschetter, P. T. , M. Fisch, and R. D. Latta. An Assessment of Potential [mpacts of
Energy-Related Transportation Developments on North Carolina's Coastal Zone. CEIP
Report #3. July 1981. $10. (NTIS # PB83-203042)

4. Cribbins, P. S. An Analysis of State and Federal Policies Affecting Major Energy
Projects in North Carolina's Coastal Zone. CEIP Report #4. September 1981, $10.
(NTIS PB82-202920)

5. Brower, David, W. D. McElyea, D. R. Godschalk, and N. D. Lofaro. Outer Continental
Shelf Development and the North Carolina Coast: A Guide for Local Planners. CEIP
Report #5. August 1981. $10. (NTIS # PB82-196304)

6. Rogers, Golden and Halpern, Inc., and Engineers for Energy and the Environment., Inc.
Mitigating the Impacts of Energy Facilities: A Local Air Quality Program for the
Wilmington, N. C. Area. CEIP Report #6. September 1981. $10. (NTIS # PB82-197872)

7. Richardson, C. J. (editor). Pocosin Wetlands: an Integrated Analysis of Coastal Plain
Freshwater Bogs in North Carolina. Stroudsburg (Pa): Hutchinson Ross. 1981. 364 pp.
$25. Available from School of Forestry, Duke University, Durham, N. C. 27709. (This
proceedings volume is for a conference partially funded by N. C. CEIP.)

8. McDonald, C. B. and A. N. Ash. Natural Areas Inventory of Tyrrell County, North
Carolina. CEIP Report #8. October 1981. $10. (NTIS # PB83-209072)

9. Fussell, J. 0. , III, and E. J. Wilson. Natural Areas Inventory of Carteret County,
North Carolina. CEIP Report #9. June 1983. $10.

10. Nyfong, T. D. Natural Areas Inventory of Brunswick County, North Carolina. CEIP
Report #10. October 1981. $10. (NTIS # PB83-234039)

11. Leonard, S. W. , and R. J. Davis. Natural Areas Inventory for Pender County, North
Carolina. CEIP Report #11. October 1981. $10. (NTIS # PB83-209106)

12. Cribbins, Paul D. , and R. Daniel Latta. Coastal Energy Transportation Study;
Alternative Technologies for Transporting and Handling Export Coal.. CEIP Report #12.
January'1982. $10. (NTIS # PB83-203067)

13. Creveling, Kenneth. Beach Communities and Oil Spills: Environmental and Economic
Consequences for Brunswick County, N. C. CEIP Report #13. May 1982. $10@ (NTIS
PB83-209064)

14. Rogers, Golden and Halpern, Inc., and Engineers for Energy and the Environment. The
Design of a Planning Program to Help Mitigate Energy Facility-Related Air Quality
Impacts in the Washington County North Carolina Area. CEIP Report # 14. September
1982. $10. (NTIS # PB83-234021)

15. McDonald C. B. , A. N. Ash, and John Fussell. Natural Areas Inventory of Craven County,
North Carolina. CEIP Report #15. December 1981. $10. (NTIS # PB83-234021)

16. Frost, Cecil C. Natural Areas Inventory of Gates County, North Carolina. CEIP Report
#16. April 1982. $10. (NTIS # PB83-209098)

17. Stone, John R. , Michael T. Stanley, and Paul T. Tschetter. Coastal Energy
Transportation Study: Impacts of Increased Rail Traffic on Communities in Eastern
North Carolina. CEIP Report # 17. August 1982. $10. (NTIS # PB83-203075)

18. Kazarian, Jacqueline S. Newport River Estuary Dye Study: An Analysis of Water
Movement. CEIP Report # 18. March 1983. $10.00. (NTIS # PB84-222397)

19. Pate, Preston P., and Robert Jones. Effects of Upland Drainage on Estuarine Nursery
Areas of Pamlico Sound, North Carolina. CEIP Report #19. December 1981. $1.00. (UNC,
Sea Grant Working Paper 81-10). (NTIS # PB83-168096)

20. Carraway, R. J., and L. J. Priddy. Mapping of Submerged Grass Beds in Core arid Bogue
Sounds, Carteret County, North Carolina, by Conventional Aerial Photography. CEIP
Report #20. November 1983. $10. 8/84

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22. Epperly, Sheryan P. The North Carolina Division of Marine Fisheries Computerized
Biological Monitoring Database: System Description and User's Manual. CEIP Report
#22. May 1984. Available as photocopy for reproduction charge.

23. Epperly, Sheryan,P. Fishes of the Pamlico-Albemarle Peninsula, N.C.: Area Utilization
and Potential Impacts. CEIP Report #23. Jointly published as Division of Marine
Fisheries Special Scientific Report #23. July 1984. $10.
1
24. Stoll, Evans, Woods & As"qiotes. Railroad Induced Vibrations, New Bern, North
Carolina, August, 10 & 11, 11983. CEIP Report #24. March 1983. $1.00. (NTIS # PB83-
233221)

25. Wang Engineering Co., Inc. Analysis of the Impact of Coal Trains Moving Through
Morehead City, North Carolina. CEIP Report #25. October 1982. $10. (NTIS # PB83-
200865)

26. Anderson & Associates, Inc. Coal Train Movements Through the City of Wilmington, North
Carolina. CEIP Report #26. October 1982. $10. (NTIS # PB83-200857)

27. Peacock, S. Lance and J. Merrill Lynch. Natural Areas Inventory of Mainland Dare
County, North Carolina. CEIP Report #27. November 1982. $10. (NTIS # PB83-208736)

28. Lynch, J. Merrill and S. Lance Peacock. Natural Areas Inventory of Hyde County, North
Carolina. CEIP Report #28. October 1982. $10.
MIS # PB83-208728)

29. Peacock, S. Lance and J. Merrill Lynch. Natural Areas Inventory of Pamlico County,
North Carolina, CEIP Report #29. November 1982. $10. (NTIS # PB83-209114)

30. Lynch, J. Merrill and S. Lance Peacock. Natural Areas Inventory of Washington County,
North Carolina. CEIP Report #30. October 1982. $10. (NTIS # PB83-209080)

31. Muga, Bruce J. Review and Evaluation of Oil Spill Models for Application to North
Carolina Waters. CEIP Report #31. August 1982. $10. (NTIS # PB83-209056)

32. Lukin, C. G., and L. L. Mauger. Environmental Geologic Atlas of the North Carolina
Coastal Zone.- Dare, Hyde, Tyrrell, and Washington Counties. CEIP Report #32.
November 1983. $10.

33. Sorrell, F. Yates and Richard R. Johnson. Oil and Gas Pipelines in Coastal North
Carolina: Impacts and Routing Considerations. CEIP Report #33. December 1982. $10.
MIS # PB83-233973)

34. Roberts and Eichler Associates, Inc. Area Development Plan for Radio Island. CEIP
Report #34. June 1982. $10. (NTIS # PB83-200873)

35. Cribbins, Paul D. Coastal Energy Transportation Study: The Potential for Wide-Beam,
Shallow-Draft Ships to Serve Coal and Other Bulk Commodity Terminals along the Cape
Fear River. CEIP Report #35. August 1982. $10. (NTIS # PB83-203380)

36. DNRCD Peat Mining Task Force. Peat Mining and Natural Resources. CEIP Report #36.
March 1983. $10. (NTIS # PB83-172049)

37. Vandenberg, J. J. , and K. R. Knoerr. The Deposit of Airborne Materials in the Lake
Phelps, N.C. , Region. CEIP Report #37. March 1983. $10. (NTIS # PB83-234054)

38. Wyman, C. D. , D. J. Brower, and R. M. Kessler. Oil and Gas Leasing of North Carolina's
Submerged Lands. CEIP Report #38. March 1984. $10.

39. N.C. Division of Environmental Management. Water Quality Monitoring in the
Pamlico/Albemarle Peninsula. CEIP Report #39. March 1984.
40. Gale, Judith A. , and David A. Adams (eds -) - Cumulative Impacts of Peat Mining. Final
Project Report. CEIP Report #40. August 1984. $20.
41. Gregory, J. D., R. W. Skaggs, R. G. Broadhead, R. H. Culbreath, J. R. Bailey, and T.
Foutz. Hydrologic and Water Quality Impacts of Peat Mining in the Coastal Zone of North
Carolina. CEIP Report #41. Jointly published as N.C. Water Resources Research
Institute Report #214. September 1983. $8 (available from WRRI) -

8/84

DATE DUE

GAYLORDINo. 2333 TI@MTED IN U S A

3 6668 14106 1921