[Federal Register Volume 59, Number 227 (Monday, November 28, 1994)]
[Unknown Section]
[Page ]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 94-28456]


[Federal Register: November 28, 1994]


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ENVIRONMENTAL PROTECTION AGENCY

40 CFR Parts 51 and 52

[AH-FRL-5107-1; Docket No. A-92-65]


Requirements for Preparation, Adoption, and Submittal of 
Implementation Plans

AGENCY: Environmental Protection Agency (EPA).

ACTION: Notice of proposed rulemaking.

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SUMMARY: EPA is issuing this proposal to augment the final rule that 
was published on July 20, 1993. Today's notice proposes to make several 
additions and changes as supplement C to the ``Guideline on Air Quality 
Models (Revised)''. Supplement C does the following: incorporates 
improved algorithms for treatment of area sources and dry deposition in 
the Industrial Source Complex (ISC2) model, adopts a solar radiation/
delta-T (SRDT) method for estimating atmospheric stability categories, 
adopts a new screening approach for assessing annual NO2 impacts, 
and adds SLAB and HGSYSTEM as alternative models. The Guideline sets 
forth air quality models and guidance for estimating the air quality 
impacts of sources and for specifying emission limits for them. The 
purpose of the proposed changes is to enhance the guidance in response 
to a substantial number of public comments urging the Agency to do so. 
For the purposes of this document, EPA is soliciting public comments 
only on the four proposed changes associated with supplement C and will 
not respond to any comments that are outside the scope of this 
document. This limiting of EPA's responses to comments within the scope 
of this document allows the Agency to focus on the issues, data, and 
information relevant to this rulemaking.

DATES: The period for comment on these proposed changes closes January 
12, 1995.

ADDRESSES: Comments: Written comments should be submitted (in duplicate 
if possible) to: Air Docket (6102), Room M-1500, Waterside Mall, 
Attention: Docket A-92-65, U.S. Environmental Protection Agency, 401 M 
Street, S.W., Washington, D.C. 20460.
    Copies of supplement C (draft) to the ``Guideline on Air Quality 
Models (Revised)'' may be obtained by writing or calling Joseph A. 
Tikvart, Source Receptor Analysis Branch, MD-14, U.S. Environmental 
Protection Agency, Research Triangle Park, NC 27711, phone (919) 541-
5561. Supplement C (draft) is also available to registered users of the 
Support Center for Regulatory Air Models Bulletin Board System (SCRAM 
BBS) by downloading the appropriate file. To register or access this 
electronic bulletin board, users with a personal computer should dial 
(919) 541-5742.
    Docket: Copies of reports referenced herein (unless otherwise 
noted) and public comments made on this Notice of Proposed Rulemaking 
(NPR) are maintained in Docket A-92-65. The docket is available for 
public inspection and copying between 8:00 a.m. and 4:00 p.m., Monday 
through Friday, at the address above.

FOR FURTHER INFORMATION CONTACT: Joseph A. Tikvart, Chief, Source 
Receptor Analysis Branch, Office of Air Quality Planning and Standards, 
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711; 
telephone (919) 541-5561 or C. Thomas Coulter, telephone (919) 541-
0832.

SUPPLEMENTARY INFORMATION:

Background\1\

    The purpose of the Guideline\2\ is to promote consistency in the 
use of modeling within the air management process. The Guideline 
provides model users with a common basis for estimating pollution 
concentrations, assessing control strategies and specifying emission 
limits; these activities are regulated at 40 CFR 51.46, 51.63, 51.112, 
51.117, 51.150, 51,160, 51.166, and 51.21. The Guideline was originally 
published in April 1978. It was incorporated by reference in the 
regulations for the Prevention of Significant Deterioration of Air 
Quality in June 1978 (43 FR 26380). The Guideline was subsequently 
revised in 1986 (51 FR 32176), and later updated with the addition of 
supplement A in 1987 (53 FR 393). The last such revision was supplement 
B, issued on July 20, 1993 (58 FR 38816). The revisions in supplement B 
included techniques and guidance for situations where specific 
procedures had not previously been available, and also improved several 
previously adopted techniques.
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    \1\In reviewing this preamble, note the distinction between the 
terms ``supplement'' and ``appendix''. Supplements A, B and C 
contain the replacement pages to effect Guideline revisions; 
appendix A to the Guideline is the repository for preferred models, 
while appendix B is the repository for alternate models justified 
for use on a case-by-case basis.
    \2\``Guideline on Air Quality Models (Revised)'' (1986) [EPA-
450/2-78-027R], with supplement A (1987) and supplement B (1993), 
hereinafter, the ``Guideline''. The Guideline is published as 
appendix W of 40 CFR Part 51. The text of appendix W will be 
appropriately modified to effect the revisions proposed for 
supplement C.
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    During the public comment period for supplement B, EPA received 
requests to consider several additional new modeling techniques and 
suggestions for enhanced technical guidance.\3\ However, because there 
was not sufficient time for the public to review the new techniques and 
technical guidance before promulgation of supplement B, the new models 
and enhanced technical guidance could not be included in the supplement 
B rulemaking. Thus, in this subsequent regulatory proposal, EPA is 
proposing to revise the Guideline and is seeking public comment on the 
four items described below. Once promulgated, these four items will be 
included in supplement C to the Guideline. A copy of supplement C 
(draft) is available for public review (Docket Item III-B-1).
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    \3\The official public hearing for EPA's proposal to adopt 
supplement B was the Fifth Conference on Air Quality Modeling, March 
1991 (56 FR 7694). Full transcripts filed in Docket No. A-88-04; IV-
F-1 (see ADDRESSES). See also ``Summary of Public Comments and EPA 
Responses on the Fifth Conference on Air Quality Modeling: March 
1991'', February 1993. (Docket No. A-88-04; V-C-1)
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Proposed Action

    Appendix W of 40 CFR part 51 will be appropriately amended to 
effect the following revisions, proposed as supplement C to the 
Guideline. EPA solicits comment on each of the following revisions.

1. Enhancements\4\ to the Industrial Source Complex Model (ISC2)
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    \4\For clarification, these enhancements are discussed 
separately. EPA intends to integrate these enhancements into one 
model for actual use.
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A. Area Source Algorithm
    Today's action proposes to replace the area source algorithm in the 
Industrial Source Complex model (ISC2) with a new one based on a double 
integration of the Gaussian plume kernel for area sources.
    (1) Short-term algorithm: ISCST2. A previous EPA study\5\ indicated 
that the currently implemented ISCST2 area source algorithm, based on a 
finite line segment approximation, estimates concentration 
distributions with limited accuracy, especially for receptors located 
close to the area source. An independent but later evaluation confirmed 
these findings.6,7 These studies suggested that the integrated 
line source algorithm for modeling impacts from area sources provides a 
better treatment of near-source geometry than that currently 
recommended in ISCST2, and a reasonable far-field behavior. Based on 
these performance evaluations and limited field data, the integrated 
line source algorithm is a candidate to substitute for the current 
ISCST2 area source algorithm. Responding to public comments received at 
the time supplement B was proposed, steps were taken to develop and 
test this algorithm. In the new algorithm,\8\ the ground-level 
concentration at a receptor downwind of all or a portion of the area 
source is given by a double integral in the upwind and crosswind 
directions. The integral in the lateral direction is solved 
analytically. The integral in the longitudinal direction (i.e., the 
summation of the contributions from the line sources in the upwind 
direction) is approximated with a Romberg integration technique.\9\ The 
new algorithm, essentially equivalent to PAL\10\ and the convergent 
mode of the FDM\11\ integrated line source algorithm, has been shown to 
perform very well in terms of efficiency and of the reasonableness of 
the results.\12\
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    \5\Environmental Protection Agency, 1989. Review and Evaluation 
of Area Source Dispersion Algorithms for Emission Sources at 
Superfund Sites. EPA Publication No. EPA-450/4-89-020. U.S. 
Environmental Protection Agency, Research Triangle Park, NC. (NTIS 
No. PB 90-142753)
    \6\American Petroleum Institute, 1992. Evaluation of Area and 
Volume Source Dispersion Models for Petroleum and Chemical Industry 
Facilities, Phase I (Final Report). API Publication No. 4539. 
(Docket No. A-92-65; II-A-1)
    \7\American Petroleum Institute, 1992. Area and Volume Source 
Air Quality Model Performance Evaluation, Phase II (Final Report). 
API Publication No. 4540. (Docket No. A-92-65; II-A-2)
    \8\``User Instructions for a New Area Source Algorithm'' (August 
1993), uploaded to the SCRAM BBS. (Docket No. A-92-65; II-A-3)
    \9\W.B., B. Flannery, S. Teukolsky, and W. Vetterling, 1986. 
Numerical Recipes. Cambridge University Press, New York; 797 pp.
    \10\Petersen, W.B., 1978. User's Guide for PAL--A Gaussian-Plume 
Algorithm for Point, Area, and Line Sources. EPA Publication No. 
EPA-600/4-78-013. U.S. Environmental Protection Agency, Research 
Triangle Park, NC. (NTIS No. PB 281306)
    \11\Environmental Protection Agency, 1991. User's Guide for the 
Fugitive Dust Model (FDM) (Revised). EPA Publication No. EPA-910/9-
88-202R. U.S. Environmental Protection Agency, Region X. (NTIS No. 
PB 90-502410)
    \12\Environmental Protection Agency, 1992. Comparison of a 
Revised Area Source Algorithm for the Industrial Source Complex 
Short Term Model and Wind Tunnel Data. EPA Publication No. EPA-454/
R-92-014. U.S. Environmental Protection Agency, Research Triangle 
Park, NC. (NTIS No. PB 93-226751)
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    Existing field studies of impacts within and nearby area sources 
being scarce and limited in scope, EPA compared model predictions to 
measured results using a wind tunnel simulation at the Fluid Modeling 
Facility, Atmospheric Research and Exposure Assessment Laboratory.\13\ 
Both qualitative physical and quantitative statistical analyses were 
performed. The analysis results\12\ show that the new algorithm 
predicts the concentration distribution with relatively good accuracy 
(i.e.,  \10%), especially for the ground-level 
receptors located near the downwind edge of the area source, a 
situation of concern to regulatory modeling applications. For receptors 
near ground level and within or near the area  source, the 
normalized modeled concentrations generally matched the wind tunnel 
measured concentrations to within  20%. EPA considers this 
to be an acceptable correspondence.
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    \13\Snyder, W.H., 1991. DATA REPORT: Wind Tunnel Simulation of 
Dispersion from Superfund Area Sources. Part: Neutral Flow. (Docket 
No. A-92-65; II-a-4)
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    To examine the sensitivity of the design concentrations across a 
range of source characteristics, scenarios considering source size, 
elevation, and downwind distance were simulated.\14\ For each scenario, 
the high-second high (HSH) 1-hour, 3-hour, 24-hour averages and high 
annual averages were determined using a full year of meteorological 
data; both rural and urban mode dispersion options were used. 
Generally, the concentration ratio\15\ averaged 1.2 (1-
hour) to 1.0 (annual). However, for receptors located 
within and nearby the area source, the ratio averaged 2 (1-
hour) to 3 (annual). Thus, for receptors inside the area 
source, the ratio is higher than for receptors outside the source, 
where the effect is a function of averaging time and proximity to the 
source in question.
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    \14\Environmental Protection Agency, 1992. Sensitivity Analysis 
of a Revised Area Source Algorithm for the Industrial Source Complex 
Short Term Model. EPA Publication No. EPA-454/R-92-015. U.S. 
Environmental Protection Agency, Research Triangle Park, NC. (NTIS 
No. PB 93-226769)
    \15\RATIO = XNEW/XOLD
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    The proposed algorithm is equivalent to that in PAL and FDM and is 
more efficient than either of these algorithms. Based on comparisons 
with wind tunnel data, the proposed algorithm provides a more realistic 
characterization of the magnitude of impacts at receptors located 
within and nearby the area than that currently in ISC2, and gives 
comparable results to the FDM convergent algorithm when modeled based 
on the same assumptions for release height, mixing height, and 
dispersion parameters. Furthermore, these findings confirm that the 
currently used area source algorithm in ISC2 is an approximation that 
routinely under-estimates (and underrepresents) the actual ambient 
impact, especially for receptor locations within and near an area 
source.
    (2) Long-term algorithm: ISCLT2. The studies previously cited in 
footnotes 5, 6, and 7 have also indicated the deficiencies of the 
virtual point source algorithm used in ISCLT2. While it is 
computationally efficient, the virtual point source algorithm used in 
the original ISCLT2 yields estimates of limited accuracy for receptors 
located near the edges and corners of the area, a problem also seen 
with the original ISCST2. The algorithm cannot predict the area source 
impact for receptors located inside the source itself, and does not 
adequately handle effects of complex source-receptor geometry.
    Thus, a new area source algorithm for the ISCLT2, based on the 
numerical integration algorithm described above, was developed and 
evaluated.\16\ Detailed performance tests, statistical analyses and 
sensitivity analyses were completed to assure the reliability and 
reasonableness of the modeling results. Using idealized meteorological 
conditions, the new algorithm yields very good comparison results when 
compared with the newly developed ISCST2 area source algorithm. For 
realistic meteorological data, the differences between ground level 
concentration values simulated with the new ISCLT2 algorithm and with 
the new ISCST2 counterpart are within about 10% for a typical source. 
The differences between the long-term and short-term algorithms using 
actual meteorological data are because ISCLT2 uses a meteorological 
frequency distribution to represent the meteorological conditions, and 
does not contain precise hour-to-hour information on specific 
combinations of wind speed, wind direction, stability class and mixing 
height that typically control the design values for the short-term 
model. Furthermore, sensitivity analyses show that the current ISCLT2 
area source algorithm, based on the virtual source approach, routinely 
underestimates (and underrepresents) the actual maximum concentration 
impacts by a factor of 2 to 4, especially when the receptors are 
located inside or near the source.
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    \16\Environmental Protection Agency, 1992. Development and 
Evaluation of a Revised Area Source Algorithm for the Industrial 
Source Complex Long Term Model. EPA Publication No. EPA-454/R-92-
016. U.S. Environmental Protection Agency, Research Triangle Park, 
NC. (NTIS No. PB 93-226777)
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B. Dry Deposition Algorithm
    Deposition phenomena can be conceptualized in a two by two matrix, 
with a wet/dry dichotomy on one side and a particle/gas dichotomy on 
the other. Each of the four cells can then be further subdivided into 
simple and complex terrain components. Today's action proposes to 
replace the plume depletion and dry deposition algorithm\17\ in the 
Industrial Source Complex model (ISC2) with a new algorithm that 
estimates the amount of material depleted from the plume as a 
combination of processes involving atmospheric turbulence and 
gravitational settling. This proposal embodies the simple terrain 
component of one cell in the conceptual matrix: dry deposition applied 
to particles. It is proposed that the new algorithm be implemented to 
treat dry deposition in rolling terrain, which is not possible in the 
current versions of ISC2. Future efforts may be directed at better 
characterizing gaseous and wet deposition in simple and complex.
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    \17\``User Instructions for the Draft Deposition Models DEPST 
and DEPLT'' (March 1994) have been uploaded to the SCRAM BBS. 
(Docket No. A-92-65; II-A-5).
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    The dry deposition algorithm currently used in ISC2 is applicable 
to large particles (i.e., those with diameters greater than 
20m) for which deposition is dominated by 
gravitational settling. In 1993, EPA initiated a study to evaluate the 
performance of alternative deposition algorithms. A review of the 
technical literature identified four core algorithms and six variants 
suitable for testing, producing a field of ten algorithm candidates. 
Estimates based on these algorithms were compared with observations 
from several data bases. Objective statistical procedures\18\ were used 
to measure model performance. The main feature of this approach is to 
compute normalized statistical measures of the fractional bias between 
observed and predicted values.
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    \18\Environmental Protection Agency, 1992. Protocol for 
Determining the Best Performing Model. EPA Publication No. EPA-454/
R-92-025. U.S. Environmental Protection Agency, Research Triangle 
Park, NC. (NTIS No. PB 93-226082)
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    Based on the evaluation,\19\ the performance among the three top-
ranked dry deposition algorithms was statistically indistinguishable. 
The three top-ranked models were UAM 2, CARB 3 and ADOM 1. The UAM 2 
and CARB 3 algorithms represent a hybrid variant of their respective 
core algorithms with an added Leaf Area Index (LAI)\20\ adjustment. 
ADOM 1, currently employed in the Acid Deposition and Oxidant Model, is 
a core algorithm (does not include a LAI adjustment). The results of 
the evaluation suggest that the reflection coefficient method used in 
ISC2 does not perform well for particle sizes less than 20m in 
diameter.
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    \19\Environmental Protection Agency, 1994. Development and 
Testing of a Dry Deposition Algorithm (Revised). EPA Publication No. 
EPA-454/R-94-015. U.S. Environmental Protection Agency, Research 
Triangle Park, NC. (NTIS No. PB 94-183100)

    Note: This report replaces one previously completed because an 
error was discovered after the earlier report was issued. The 
following memorandum details the nature of the error and documents 
the validity of the newer report.
    Memorandum from Jawad S. Touma et al. to Joseph A. Tikvart: 
Comments on the report ``Development and Testing of a Dry Deposition 
Algorithm (Revised)'', 6 May 1994 (3pp. w/5 attachments) (Dockets 
No. A-92-65; II-E-1)
    \20\The LAI is a ration of leaf surface area divided by ground 
surface area and can be estimated from land use type and season.
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    The technical applicability of a LAI adjustment, as implemented for 
particle deposition velocity, has not been extensively studied. Thus, 
the robustness of using a LAI in routine model applications is 
uncertain. Excluding algorithms with LAI adjustments, the ADOM 1 scheme 
produces the best composite fractional bias measure (CPM) and was 
significantly better than other models tested at the 95% confidence 
level. ADOM 1 slightly underestimates observed deposition velocities, a 
trait that is shared by all the algorithm candidates. Considering all 
of these factors, ADOM 1 is recommended for estimating dry deposition 
velocity in the ISC2 model.
    The ADOM 1 dry deposition algorithm has been tested within the 
framework of the ISC2 model and comparisons of deposition estimates 
using the old and new deposition algorithms have been made for a range 
of source types and particulate emission scenarios. Similar comparisons 
have been made of particulate concentration estimates as affected by 
the old and new deposition algorithms. A report\21\ documenting these 
analyses and assessing the potential consequences of replacing the 
current deposition algorithm in ISC2 with the proposed algorithm has 
been prepared.
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    \21\Environmental Protection Agency, 1994. Comparison of ISC2 
Deposition Estimates Based on Current and Proposed Deposition 
Algorithms. EPA Publication No. EPA-454/R-94-018. U.S. Environmental 
Protection Agency, Research Triangle Park, NC.
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    The results of the comparative analyses of the proposed dry 
deposition algorithm vary with release type, particle size, and 
averaging period. Consequently, care should be exercised in 
interpreting the generalizations that follow regarding deposition and 
concentration estimates.
    The effects on the actual deposition predicted by ADOM 1 were 
examined. For surface releases, the new algorithm gives higher annual 
and 24-hour deposition estimates for all particle sizes. For 1-hour and 
3-hour estimates for surface releases the results were mixed. For 
elevated releases, deposition estimates given by the new algorithm are 
higher for 0.1m and 1m particles, lower for 10 and 
20m particles, and higher for 80m and 100m 
particles. The results for elevated releases of 50m particles 
depend on release height.
    The effects on ambient concentrations predicted by ISC2 were also 
examined. For both surface and elevated releases of small and 
intermediate particle sizes (i.e., 0.1, 1.0, 10 and 20m), the 
differences in concentration estimates between the old and new 
algorithms are less than 10 percent. These differences are considered 
insignificant. Results for the large particle sizes (i.e., 50, 80, and 
100m) depend on release height. For surface releases, the 
concentration estimates using the new algorithm are diminished. For 
elevated releases, concentration estimates using the new algorithm are 
increased.
    EPA is also soliciting public comment on whether it would be 
appropriate to require the proposed dry deposition algorithm to be used 
for all ISC2 analyses involving particulate matter in any of the 
programs for which Guideline usage is required under 40 CFR parts 51 
and 52 (see Summary). Heretofore, use of the deposition algorithm has 
been optional, depending on the relevance of particle deposition to a 
particular application. However, with the more accurate deposition 
algorithm proposed herein, its use may result in the systematic 
prediction of more accurate ambient concentrations. Therefore, EPA is 
soliciting comment on whether it would be appropriate to revise 
Guideline section 8.2.7 (Gravitational Settling and Deposition) to 
require use of the deposition algorithm, and if so, whether the 
implementation guidance provided in the User's Instructions\17\ is 
sufficient.

2. Enhancements to On-site Stability Classification

    EPA is proposing to revise the on-site stability classification 
with the adoption of a new technique, adapted from Bowen et al.\22\ and 
herein referred to as the solar radiation/delta-T (SRDT) method. This 
method uses total solar radiation during daytime and temperature 
difference, delta-T (T), at night and is a replacement for the 
one originally proposed (56 FR 5900). As proposed in supplement C, the 
hierarchy of stability classification schemes in the Guideline will be 
changed to reflect a preference for SRDT-derived stability categories. 
Operation of the method is fully described in section 6.4.4.2 of ``On-
Site Meteorological Program Guidance for Regulatory Modeling 
Applications'' (EPA-450/4-87-013), hereafter, ``on-site guidance''.
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    \22\Bowen, B.M., J.M. Dewart, and A. I. Chen, 1983. Stability 
Class Determination: A Comparison for One Site. Proceedings, Sixth 
Symposium on Turbulence and Diffusion, American Meteorological 
Society, Boston, MA; pp. 211-214. (Docket No. A-92-65; II-A-6)
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    The new method has been completely reconfigured in terms of its 
classification criteria, in response to the public comments provided at 
the Fifth Conference on Air Quality Modeling (March 1991) regarding the 
original proposal. The comments (Docket A-88-04, Category IV-D; see 
footnote #4) were generally favorable to the concept of a SRDT method 
for determining stability category. However, there were some 
substantial criticisms of specific SRDT components. Most significant 
were comments on:
    (1) Accuracy of measurements associated with a 2-10m T;
    (2) Limitations on temperature measurements made at 2m;
    (3) Use of a 10-60m T in lieu of one measured from 2-10m;
    (4) Lack of evaluation data bases;
    (5) Use of net radiation measurements in lieu of solar radiation; 
and
    (6) Merits of  measurements for stability determination.
    Regarding the use of net radiation, it is not apparent that there 
is sufficient experience with routine use of such measurements to 
justify requiring their use, whereas there has been extensive 
experience with T systems. Regarding the use of  
measurements, experience has been that, unless such systems are tuned 
for site-specific regimes, the -based methods do not represent 
Pasquill-Gifford (P-G) stability classification well. Evaluation 
results,\23\ based on on-site measurements from three widely separated 
locations, indicate that the SRDT method seems to be less sensitive to 
local measurement configurations and is expected to be geographically 
robust. Furthermore, the new SRDT method has been configured so that 
the system accuracy will not be limiting. Thus, the method will be less 
sensitive to random temperature differences. The claim (commenter IV-D-
27 in Docket Item V-C-1; see footnote #3) that accurate measurement of 
the 2m temperature may be adversely affected by surface conditions 
under the tower has merit in certain circumstances. The new SRDT method 
does not mandate that the location of the lower temperature sensor be 
at 2m. EPA believes that proper siting of temperature probes in 
accordance with Chapter 3 of the on-site guidance, coupled with sound 
judgment, should obviate any such problem. Use of a 10-60m T, 
an interval specified in the meteorological monitoring protocol used by 
the Nuclear Regulatory Commission, is accommodated by the new SRDT 
method. Finally, substantial effort was made in acquiring suitable on-
site data bases with which to evaluate the new SRDT method; the new 
SRDT method has been more extensively evaluated.
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    \23\Environmental Protection Agency, 1993. An Evaluation of a 
Solar Radiation/Delta-T (SRDT) Method for Estimating Pasquill-
Gifford (P-G) Stability Categories. EPA Publication No. EPA-454/R-
93-055. U.S. Environmental Protection Agency, Research Triangle 
Park, NC. (NTIS No. PB 94-113958)
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    To make the stability classification comparisons for the SRDT 
evaluation, a surrogate for the preferred Turner classification 
scheme\24\ was devised. This surrogate method utilized ``off-site'' 
National Weather Service (NWS) observations in lieu of those otherwise 
made ``on-site''. To ensure the integrity of this surrogate method, it 
was necessary that candidate sites be sufficiently near a 
representative NWS station from which cloud cover and ceiling height 
observations could be obtained. Of ten on-site data bases considered 
for supporting the evaluation, three were ultimately selected because 
they had the requisite attributes. The data bases thus selected were: 
Kincaid, IL (21 weeks in 1980), Longview, WA (CY 1991), and a site near 
Bloomington, IN (7/91-7/92). Proximity of these sites to NWS stations 
ranged from 17 to 45 miles.
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    \24\This method requires on-site measurements of wind speed 
coupled with observations of cloud cover and ceiling height. Turner, 
D.B., 1964. A Diffusion Model for an Urban Area. Journal of Applied 
Meteorology, 3(1): 83-91.
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    For theoretical reasons, as well as for consistency with the 
approach originally proposed, the SRDT method was initially evaluated 
using T data from 2-10m; such data were available for all 
three sites. At two of the sites, T data from 10-50m were also 
available. These data were of interest in trying to accommodate 
T measurements from alternative height intervals.
    As substantial site-to-site variability was seen in initial 
analyses using the 2-10m T data, it was decided to pool the 
data from all three sites and then determine optimum SRDT ``cutpoints'' 
(i.e., meteorological criteria for discriminating stability category). 
Thus, optimum cutpoints were derived in an empirical, iterative fashion 
from a data base of 19,540 valid hours. Use of these optimum cutpoints 
resulted in a SRDT system that estimated the same P-G stability as the 
preferred Turner scheme for 62% of the hours; the categories were 
within one class for 89% of the hours. A randomization procedure in 
which the composite data were split into two complementary sets was 
done to ascertain robustness (insensitivity to random variations in the 
data) of the method. The optimum cutpoints from the composite data were 
then applied to the three sites individually to document site-specific 
residuals.
    For the two sites with 10-50m T data, the SRDT system 
using the optimum (for pooled data) cutpoints was applied in the same 
way as with the 2-10m T data, with reasonably accurate and 
consistent results. Stability categories were duplicated by the SRDT 
method at least 56% of the hours, and were within one class for about 
90% of the hours. Overall, the analyses show that the SRDT system works 
adequately for either T interval: the system does not appear 
to be unduly sensitive to the actual T height interval. Based 
on these analyses, EPA does not feel it should be overly prescriptive 
regarding the use of particular T intervals. Rather, in 
guidance for implementation of the method, actual placement of 
temperature probes is related to fundamental site-specific phenomena, 
e.g., surface roughness. While the method was evaluated using only 2-
10m and 10-50m T data, it is considered to be robust enough to 
accommodate other T height intervals as well, so long as 
section 6.4.4.2 of the on-site guidance cited above is followed.
    Finally, consequence analyses were performed using a Gaussian 
dispersion model (i.e., ISC2) to document the effect of the SRDT method 
on design concentration ratios.\25\ These analyses were performed for 
the 2-10m T comparisons at all three sites and for the 10-50m 
T comparisons at two sites. For all such analyses, scenarios 
included single 35m, 100m and 200m stacks and 180 receptors configured 
radially in 5 concentric rings. Averaging times included 1-hour, 3-
hour, 24-hour, and period. Modeled concentrations of interest were the 
high, and high 2nd high value. Using stability categories derived from 
the 2-10m T data for the three sites, the concentration ratios 
averaged 1.06-1.24 across three source types, four averaging times and 
two concentration types. Likewise, using those categories derived from 
the 10-50m T data, the same concentration ratios also averaged 
1.06-1.24.
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    \25\RATIO=XSRDT/XTurner
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    In the supplement B revisions to the Guideline, EPA referenced 
``On-Site Meteorological Program Guidance for Regulatory Modeling 
Applications'' in section 9.3.3. This document continues to serve as 
the primary source of supplementary technical guidance on the 
collection and use of on-site meteorological data. EPA is proposing an 
addendum\26\ to accommodate the technical details of the SRDT system. 
Once finalized, the hierarchy of stability classification schemes in 
that document will also be changed to reflect the preference for those 
derived via SRDT. The use of other techniques prior to a year following 
promulgation will be exempt from this provision, after which they will 
not be considered the primary method for estimating stability. Finally, 
the module designed to implement the SRDT system in Version 1.3 of the 
Meteorological Processor for Regulatory Models (MPRM), EPA-600/3-88-
043, will be activated and configured with the optimum cutpoints 
derived in the evaluation.
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    \26\ADDENDUM: On-Site Meteorological Program Guidance for 
Regulatory Modeling Applications. Draft for Public Comment 
(September 1993). (Docket No. A-92-65; II-A-7)
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3. Screening Approaches for Assessing Annual NO2 Impact

    EPA is proposing a revision to simplify the screening approaches 
for assessing annual NO2 concentration impact in Guideline section 
6.2.3.
    These revisions respond to public comments contending that the 
initial screening level (which assumed total conversion of NO to 
NO2) was overly conservative, and that the ozone limiting approach 
described in the second and third screening levels was sometimes 
inapplicable or impracticable. Thus, a second level screening approach 
that embodies use of an empirically derived NO2/NOX ratio is 
proposed. This method replaces the multi-tiered ozone limiting method 
now recommended in the Guideline. As described in Chu and Meyer 
(1991),\27\ the new approach reflects a review of 10 years of ambient 
NO2 and NOX concentration data collected at a variety of 
monitoring sites throughout the United States.
---------------------------------------------------------------------------

    \27\Chu, S.-H. and E.L. Meyer, 1991. Use of Ambient Ratios to 
Estimate Impact of NOX Sources on Annual NO2 
Concentrations. Proceedings, 84th Annual Meeting & Exhibition of the 
Air & Waste Management Association, Vancouver, B.C.; 16-21 June 1991 
(16pp.). (Docket No. A-92-65; II-A-8)
---------------------------------------------------------------------------

    The underlying basis for the ambient ratio method (ARM) is that, 
for a well mixed plume, the photochemical conversion of NO to NO2 
is essentially controlled by the characteristics of the ambient air. 
This, in turn, is reflected in the annual NO2/NOX ratio 
monitored downwind. Since the photochemistry involved in converting NO 
to NO2 is implicitly accounted for by the annual NO2/NOX 
ratio monitored downwind, no long-term complex photochemical 
calculation is needed. Thus, it makes the modeling exercise much 
simpler, yet still provides results consistent with available plume 
observational studies.
    The method is conservative since, in many cases, maximum estimated 
ground level NOX concentration may occur prior to thorough mixing 
of the plume. A second, less important, source of conservatism is that 
the existing NO2 and NOX data may overestimate the actual 
NO2 and NOX concentrations due to interference of PAN and 
nitric acid in the measurement. However, since the same amount is added 
to both the numerator and denominator of the NO2NOX ratio, it 
only makes the conversion ratio slightly more conservative. As shown by 
Chu and Meyer (1991), the ARM, while likely to be conservative, is 
somewhat less so than existing screening methods (such as the total 
conversion and the ozone limiting method) for estimating annual 
NO2 concentrations and PSD NO2 increments for NOX 
sources. Serving as a second level screening method, ARM has the 
quality of simplicity, is easy to apply and is likely to be somewhat 
conservative. It relies only on the standard regulatory Gaussian models 
and data from nationwide NOX monitoring networks. EPA has 
therefore selected this method to propose as a revision to the 
Guideline in supplement C.

4. Modeling Techniques for Toxic Air Pollutants

    In response to a request made by the American Petroleum Institute 
(see footnote 3), two new models for treating toxic air pollutant 
releases are being proposed for addition to appendix B of the 
Guideline. These models, SLAB and HGSYSTEM, will then accompany 
DEGADIS, another appendix B model for treating dense gas releases for 
use on a case-by-case basis. (See footnote 2.)

Administrative Requirements

A. Executive Order 12866

    Under Executive Order (E.O.) 12866 [58 FR 51735 (October 4, 1993)], 
the Agency must determine whether the regulatory action is 
``significant'' and therefore subject to review by the Office of 
Management and Budget (OMB) and the requirements of the Executive 
Order. The Order defines ``significant regulatory action'' as one that 
is likely to result in a rule that may:

    (1) Have an annual effect on the economy of $100 million or more 
or adversely affect in a material way the economy, a sector of the 
economy, productivity, competition, jobs, the environment, public 
health or safety, or State, local, or tribal governments or 
communities;
    (2) Create a serious inconsistency or otherwise interfere with 
an action taken or planned by another agency;
    (3) Materially alter the budgetary impact of entitlements, 
grants, user fees, or loan programs of the rights and obligations of 
recipients thereof; or
    (4) Raise novel legal or policy issues arising out of legal 
mandates, the President's priorities, or the principles set forth in 
the Order.

    It has been determined that this rule is not a ``significant 
regulatory action'' under the terms of E.O. 12866 and is therefore not 
subject to OMB review.

B. Paperwork Reduction Act

    This final rule does not contain any information collection 
requirements subject to review by OMB under the Paperwork Reduction Act 
of 1980, 44 U.S.C. 3501 et seq.

C. Regulatory Flexibility Act

    The Regulatory Flexibility Act (5 U.S.C. 601 et seq.) requires EPA 
to consider potential impacts of regulations on small ``entities''. The 
action here proposed is a supplement to the notice of final rulemaking 
that was published on July 20, 1993 (58 FR 38816). As described earlier 
in this preamble, the revisions here proposed as supplement C to the 
Guideline encompass the use of new model algorithms and techniques for 
using those models. This rule merely updates existing technical 
requirements for air quality modeling analyses mandated by various 
Clean Air Act programs (e.g., prevention of significant deterioration, 
new source review, SIP revisions) and imposes no new regulatory 
burdens. As such, there will be no additional impact on small entities 
regarding reporting, recordkeeping, compliance requirements, as stated 
in the notice of final rulemaking (op. cit.). Furthermore, this 
proposed rule does not duplicate, overlap, or conflict with other 
federal rules. Thus, pursuant to the provisions of 5 U.S.C. 605(b), EPA 
hereby certifies that the attached proposed rule will not have a 
significant impact on a substantial number of such entities.

List of Subjects

40 CFR Part 51

    Administrative practice and procedure, Air pollution control, 
Intergovernmental relations, Reporting and recordkeeping requirements, 
Ozone, Sulfur oxides, Nitrogen dioxide, Lead, Particulate matter, 
Hydrocarbons, Carbon monoxide.

40 CFR Part 52

    Air pollution control, Ozone, Sulfur oxides, Nitrogen dioxide, 
Lead.

    Authority: This notice of proposed rulemaking is issued under 
the authority granted by sections 110(a)(2), 165(e), 172(a) & (c), 
173, 301(a)(1) and 320 of the 1990 Clean Air Act Amendments, 42 
U.S.C. 7410(a)(2), 7475(e), 7502(a) & (c), 7503, 7601(a)(1) and 
7620, respectively.

    Dated: November 7, 1994.
Carol M. Browner,
Administrator.
    Parts 51 and 52, Chapter I, Title 40 of the Code of Federal 
Regulations are amended as follows:

PART 51--REQUIREMENTS FOR PREPARATION, ADOPTION, AND SUBMITTAL OF 
IMPLEMENTATION PLANS

    1. The authority citation for part 51 continues to read as follows:

    Authority: 42 U.S.C. 7410(a)(2), 7475(e), 7502(a) and (b), 7503, 
7601(a)(1) and 7620.


Sec. 51.112  [Amended]

    2. In Sec. 51.112, paragraphs (a)(1) and (a)(2) are amended by 
revising ``and supplement B (1993)'' to read ``, supplement B (1993) 
and supplement C (1994)''.


Sec. 51.160  [Amended]

    3. In Sec. 51.160, paragraphs (f)(1) and (f)(2) are amended by 
revising ``and supplement B (1993)'' to read ``, supplement B (1993) 
and supplement C (1994)''.


Sec. 51.166  [Amended]

    4. In Sec. 51.166, paragraph (l)(1) and (l)(2) are amended by 
revising ``and supplement B (1993)'' to read ``, supplement B (1993) 
and supplement C (1994)''.
    5. Appendix W to Part 51, section 4.2.2, is amended by revising 
footnote 1 in Table 4-1 to read as follows:

Appendix W to Part 51--Guideline on Air Quality Models (Revised)

* * * * *
    4.2.2  * * *
    Table 4-1. * * *

------------------------------------------------------------------------
                                                         Land           
                                                         Use    Model\1\
------------------------------------------------------------------------
                                  *****                                 
\1\The models as listed in this table reflect the applications for which
  they were originally intended. Several of these models have been      
  adapted to contain options which allow them to be interchanged. For   
  example, ISCST2 could be substituted for ISCLT2. Similarly, for a     
  point source application, ISCST2 with urban option can be substituted 
  for RAM. Where a substitution is convenient to the user and equivalent
  estimates are assured, it may be made.                                

* * * * *

Appendix W  [Amended]

    6. Appendix W to Part 51, section 6.2.3, is revised to read as 
follows:
* * * * *

6.2.3  Models for Nitrogen Dioxide (Annual Average)

    a. A tiered screening approach is recommended to obtain annual 
average estimates of NO2 from point sources for New Source 
Review analysis, including PSD, and for SIP planning purposes. This 
multi-tiered approach is conceptually shown in Figure 6-1 below:
Figure 6-1--Multi-tiered Screening Approach for Estimating Annual 
NO2 Concentrations From Point Sources

BILLING CODE 6560-50-M

TP28NO94.000


BILLING CODE 6560-50-C

    b. For Tier 1 (the initial screen), use an appropriate Gaussian 
model from appendix A to estimate the maximum annual average 
concentration and assume a total conversion of NO to NO2. If 
the concentration exceeds the NAAQS and/or PSD increments for 
NO2, proceed to the 2nd level screen.
    c. For Tier 2 (2nd level) screening analysis, multiply the Tier 
1 estimate(s) by an empirically derived NO2/NOX value of 
0.75 (annual national default).\36\ An annual NO2/NOX 
ratio differing from 0.75 may be used if it can be shown that such a 
ratio is based on data likely to be representative of the 
location(s) where maximum annual impact from the individual source 
under review occurs. In the case where several sources contribute to 
consumption of a PSD increment, a locally derived annual NO2/
NOX ratio should also be shown to be representative of the 
location where the maximum collective impact from the new plus 
existing sources occurs.
    d. In urban areas, a proportional model may be used as a 
preliminary assessment to evaluate control strategies to meet the 
NAAQS for multiple minor sources, i.e. minor point, area and mobile 
sources of NOX; concentrations resulting from major point 
sources should be estimated separately as discussed above, then 
added to the impact of the minor sources. An acceptable screening 
technique for urban complexes is to assume that all NOX is 
emitted in the form of NO2 and to use a model from appendix A 
for nonreactive pollutants to estimate NO2 concentrations. A 
more accurate estimate can be obtained by: (1) calculating the 
annual average concentrations of NOX with an urban model, and 
(2) converting these estimates to NO2 concentrations using an 
empirically derived annual NO2/NOX ratio. A value of 0.75 
is recommended for this ratio. However, a spatially averaged annual 
NO2/NOX ratio may be determined from an existing air 
quality monitoring network and used in lieu of the 0.75 value if it 
is determined to be representative of prevailing ratios in the urban 
area by the reviewing agency. To ensure use of appropriate locally 
derived annual NO2/NOX ratios, monitoring data under 
consideration should be limited to those collected at monitors 
meeting siting criteria defined in 40 CFR 58, appendix D as 
representative of ``neighborhood'', ``urban'', or ``regional'' 
scales. Furthermore, the highest annual spatially averaged NO2/
NOX ratio from the most recent 3 years of complete data should 
be used to foster conservatism in estimated impacts.

    e. To demonstrate compliance with NO2 PSD increments in 
urban areas, emissions from major and minor sources should be 
included in the modeling analysis. Point and area source emissions 
should be modeled as discussed above. If mobile source emissions do 
not contribute to localized areas of high ambient NO2 
concentrations, they should be modeled as area sources. When modeled 
as area sources, mobile source emissions should be assumed uniform 
over the entire highway link and allocated to each area source grid 
square based on the portion of highway link within each grid square. 
If localized areas of high concentrations are likely, then mobile 
sources should be modeled as line sources with the preferred model 
ISCLT2.

    f. More refined techniques to handle special circumstances may 
be considered on a case-by-case basis and agreement with the 
reviewing authority should be obtained. Such techniques should 
consider individual quantities of NO and NO2 emissions, 
atmospheric transport and dispersion, and atmospheric transformation 
of NO to NO2. Where they are available, site-specific data on 
the conversion of NO to NO2 may be used. Photochemical 
dispersion models, if used for other pollutants in the area, may 
also be applied to the NOX problem.

* * * * *
    7. Appendix W to Part 51, section 9.3.3.2, is revised to read as 
follows:

* * * * *

    9.3.3.2  Recommendations--Site-specific Data Collection.

    a. The document ``On-Site Meteorological Program Guidance for 
Regulatory Modeling Applications''\66\ provides recommendations on 
the collection and use of on-site meteorological data. 
Recommendations on characteristics, siting, and exposure of 
meteorological instruments and on data recording, processing, 
completeness requirements, reporting, and archiving are also 
included. This publication should be used as a supplement to the 
limited guidance on these subjects now found in the ``Ambient 
Monitoring Guidelines for Prevention of Significant 
Deterioration''.\63\ Detailed information on quality assurance is 
provided in the ``Quality Assurance Handbook for Air Pollution 
Measurement Systems: Volume IV''.\67\ As a minimum, site-specific 
measurements of ambient air temperature, transport wind speed and 
direction, and the parameters to determine Pasquill-Gifford (P-G) 
stability categories should be available in meteorological data sets 
to be used in modeling. Care should be taken to ensure that 
meteorological instruments are located to provide representative 
characterization of pollutant transport between sources and 
receptors of interest. The Regional Office will determine the 
appropriateness of the measurement locations.

    b. All site-specific data should be reduced to hourly averages. 
Table 9-3 lists the wind related parameters and the averaging time 
requirements.

    c. Solar Radiation Measurements. Total solar radiation should be 
measured with a reliable pyranometer, sited and operated in 
accordance with established on-site meteorological guidance.\66\

    d. Temperature Measurements. Temperature measurements should be 
made at standard shelter height (2m) in accordance with established 
on-site meteorological guidance.\66\

    e. Temperature Difference Measurements. Temperature difference 
() measurements for use in estimating P-G 
stability categories using the SRDT methodology (see Stability 
Categories) should be obtained using two matched thermometers or a 
reliable thermocouple system to achieve adequate accuracy.

    f. Siting, probe placement, and operation of T systems 
should be based on guidance found in Chapter 3 of reference 66, and 
such guidance should be followed when obtaining vertical temperature 
gradient data for use in plume rise estimates or in determining the 
critical dividing streamline height.
    g. Wind Measurements. The wind speed for determining plume rise 
using the methods of Briggs56,57 should be measured at stack 
top. For refined modeling applications in simple terrain situations, 
if a source has a stack below 100m, select the stack top height as 
the wind measurement height for characterization of plume dilution 
and transport. In some cases, collection of stack top wind speed may 
be impractical. For sources with stacks extending above 100m, a 100m 
tower is suggested unless the stack top is significantly above 100m 
(i.e., 200m). In cases with stack tops 200m, 
the Regional Office should determine the appropriate measurement 
height on a case-by-case basis. Remote sensing may be a feasible 
alternative.
    h. For refined modeling applications in complex terrain, 
multiple level (typically three or more) measurements of wind speed 
and direction, temperature and turbulence (wind fluctuation 
statistics) are required. Such measurements should be obtained up to 
the representative plume height(s) of interest (i.e., the plume 
height(s) under those conditions important to the determination of 
the design concentration). The representative plume height(s) of 
interest should be determined using an appropriate complex terrain 
screening procedure (e.g., CTSCREEN) and should be documented in the 
monitoring/modeling protocol. The necessary meteorological 
measurements should be obtained from an appropriately sited 
meteorological tower augmented by SODAR if the representative plume 
height(s) of interest exceed 100m. The meteorological tower need not 
exceed the lesser of the representative plume height of interest 
(the highest plume height if there is more than one plume height of 
interest) or 100m.

    i. Specifications for wind measuring instruments and systems are 
contained in the ``On-Site Meteorological Program Guidance for 
Regulatory Modeling Applications''.\66\
    j. Stability Categories. The (P-G) stability categories, as 
originally defined, couple near-surface measurements of wind speed 
with subjectively determined insolation assessments based on hourly 
cloud cover and ceiling height observations. The wind speed 
measurements are made at or near 10m. The insolation rate is 
typically assessed using observations of cloud cover and ceiling 
height based on criteria outlined by Turner.\50\ In the absence of 
site specific observations of cloud cover and ceiling height, it is 
recommended that the P-G stability category be estimated using the 
solar radiation/delta-T (SRDT) method described in section 6.4.4.2 
of reference 66. This method requires measurements of total solar 
radiation during the daytime and temperature difference () 
at night (see Temperature Difference Measurements), coupled with 
average wind speed at 10m above ground level. This technique is 
modified slightly from that published by Bowen et al. (1983),\136\ 
has been evaluated with three on-site data bases,\137\ and allows 
practical and reasonable implementation of the preferred Turner 
method.\55\
    k. Two methods of stability classification which use wind 
fluctuation statistics, the  and 
 methods, are also described in detail in 
reference 66 (note applicable tables in Chapter 6). As a primary 
method, these two techniques may only be used for processing data 
collected within 1 year following the promulgation date of 
Supplement C, and then only when data are unavailable to implement 
either the preferred Turner method\55\ or the SRDT method. After 
promulgation of Supplement C, these turbulence methods should only 
be used to provide back-up stability category estimates for missing 
hours in the record according to an established data substitution 
protocolg and after valid data retrieval requirements have been 
met.
---------------------------------------------------------------------------

    \2\Such protocols are usually part of the approved monitoring 
program plan. Data substitution guidance is provided in section 5.3 
of reference 66.
---------------------------------------------------------------------------

    l. In the case of the  method it should be 
noted that wind meander may occasionally bias the determination of 
 and thus lead to an erroneous determination of 
the P-G stability category. To minimize wind direction meander 
contributions,  may be determined for each of four 
15-minute periods in an hour. However, 360 samples are needed during 
each 15-minute period. If the  method is being 
used for stability determinations in these situations, take the 
square root of one-quarter of the sum of the squares of the four 15 
minute 's, as illustrated in the footnote to Table 
9-3. While this approach is an acceptable alternative for 
determining stability, as qualified above, 's 
calculated in this manner are not likely to be suitable for input to 
models that are designed to accept on-site hourly 's based 
on 60-minute periods, e.g., CTDMPLUS. For additional information on 
stability classification using wind fluctuation statistics, see 
references 68-72.
    m. In summary, when on-site data are being used, P-G stability 
categories should be determined by (1) Turner's method\55\ using 
site specific data which include cloud cover, ceiling height and 
surface (10m) wind speeds, or (2) the radiation-based 
technique (SRDT) described in reference 66.

    n. The following techniques may only be applied to on-site data 
bases collected within 1 year following the promulgation date of 
Supplement C, and then only when data are unavailable to implement 
the preferred Turner\55\ or SRDT method; or to provide back-up 
stability category estimates for missing hours in the record 
according to an established data substitution protocolg and 
after valid data retrieval requirements have been met (choice is 
based on data availability and site suitability):

(1)  from site-specific measurements in accordance 
with guidance;\66\

(2)  from site-specific measurements in accordance 
with guidance;\66\

(3) Turner's method\55\ using site-specific wind speed with cloud 
cover and ceiling height from a nearby NWS site.

    o. Meteorological Data Processors. The following meteorological 
preprocessors are recommended by EPA: RAMMET, PCRAMMET, STAR, 
PCSTAR, MPRM,\135\ and METPRO.\24\ RAMMET is the recommended 
meteorological preprocessor for use in applications employing hourly 
NWS data. The RAMMET format is the standard data input format used 
in sequential Gaussian models recommended by EPA. PCRAMMET\138\ is 
the PC equivalent of the mainframe version (RAMMET). STAR is the 
recommended preprocessor for use in applications employing joint 
frequency distributions (wind direction and wind speed by stability 
class) based on NWS data. PCSTAR is the PC equivalent of the 
mainframe version (STAR). MPRM is the recommended preprocessor for 
use in applications employing on-site meteorological data. The 
latest version (MPRM 1.3) has been configured to implement the SRDT 
method for estimating P-G stability categories. MPRM is a general 
purpose meteorological data preprocessor which supports regulatory 
models requiring RAMMET formatted data and STAR formatted data. In 
addition to on-site data, MPRM provides equivalent processing of NWS 
data. METPRO is the required meteorological data preprocessor for 
use with CTDMPLUS. All of the above mentioned data preprocessors are 
available for downloading from the SCRAM BBS.\19\

* * * * *

    8. Appendix W to Part 51, section 12.0, is amended by:

    a. Redesignating footnote g and h as footnotes h and i;

    b. Revising references 36 and 90; and

    c. Adding references 136 through 138.

    The revisions and additions read as follows:

* * * * *

    12.0 * * *

* * * * *
36. Chu, S.-H. and E. L.Meyer, 1991. Use of Ambient Ratios to 
Estimate Impact of NOx Sources on Annual NO2 
Concentrations. Proceedings, 84th Annual Meeting & Exhibition of the 
Air & Waste Management Association, Vancouver, B.C.; 16-21 June 
1991. (16pp.) (Docket No. A-92-65, II-A-7)
* * * * *
90. Environmental Research and Technology, 1987. User's Guide to the 
Rough Terrain Diffusion Model (RTDM), Rev. 3.20. ERT document No. 
PD535-585. Environmental Research and Technology, Inc., Concord, MA. 
(NTIS No. PB 88-171467)
* * * * *
136. Bowen, B.M., J.M. Dewart and A.I. Chen, 1983. Stability Class 
Determination: A Comparison for One Site. Proceedings, Sixth 
Symposium on Turbulence and Diffusion. American Meteorological 
Society, Boston, MA; pp. 211-214. (Docket No. A-92-65, II-A-5)
137. Environmental Protection Agency, 1993. An Evaluation of a Solar 
Radiation/Delta-T (SRDT) Method for Estimating Pasquill-Gifford (P-
G) Stability Categories. EPA Publication No. EPA-454/R-93-055. U.S. 
Environmental Protection Agency, Research Triangle Park, NC. (NTIS 
No. PB 94-113958)
138. Environmental Protection Agency, 1993. PCRAMMET User's Guide. 
EPA Publication No. EPA-454/B-93-009. U.S. Environmental Protection 
Agency, Research Triangle Park, NC.
* * * * *

Appendix W  [Amended]

    9. Appendix W to Part 51, section 13.0, is amended by redesignating 
footnote i as footnote j.

Appendix W [Amended]

    10. Appendix W to Part 51, Appendix A, is amended by:
    a. Revising section A.5.d;
    b. Revising section A.5.m;
    c. Adding four references in alphabetical order in section A.5.n; 
and
    d. Adding a reference at the end of section A.REF.
    The revisions and additions read as follows:

Appendix A to Appendix W of Part 51--Summaries of Alternative Air 
Quality Models

* * * * *
    A. 5  * * *

d. Type of Model

    ISC2 is a Gaussian plume model. It has been revised to perform a 
double integration of the Gaussian plume kernel for area sources.
* * * * *

m. Physical Removal

    Dry deposition effects for particles are treated using a 
resistance formulation in which the deposition velocity is the sum 
of the resistances to pollutant transfer within the surface layer of 
the atmosphere, plus a gravitational settling term (EPA, 1994), 
based on the modified surface depletion scheme of Horst (1983).

n. Evaluation Studies

* * * * *
    Environmental Protection Agency, 1992. Comparison of a Revised 
Area Source Algorithm for the Industrial Source Complex Short Term 
Model and Wind Tunnel Data. EPA Publication No. EPA-454/R-92-014. 
U.S. Environmental Protection Agency, Research Triangle Park, NC. 
(NTIS No. PB 93-226751)
    Environmental Protection Agency, 1992. Sensitivity Analysis of a 
Revised Area Source Algorithm for the Industrial Source Complex 
Short Term Model. EPA Publication No. EPA-454/R-92-015. U.S. 
Environmental Protection Agency, Research Triangle Park, NC. (NTIS 
No. PB 93-226769)
    Environmental Protection Agency, 1992. Development and 
Evaluation of a Revised Area Source Algorithm for the Industrial 
Source Complex Long Term Model. EPA Publication No. EPA-454/R-92-
016. U.S. Environmental Protection Agency, Research Triangle Park, 
NC. (NTIS No. PB 93-226777)
    Environmental Protection Agency, 1994. Development and Testing 
of a Dry Deposition Algorithm (Revised). EPA Publication No. EPA-
454/R-94-015. U.S. Environmental Protection Agency, Research 
Triangle Park, NC.
* * * * *
A. Ref Rerences
* * * * *
    Horst, T. W., 1983. A Correction to the Gaussian Source-
depletion Model. In Precipitation Scavenging, Dry Deposition and 
Resuspension. H. R. Pruppacher, R. G. Semonin, and W. G. N. Slinn, 
eds., Elseview, NY.

    11. Appendix W to Part 51, Appendix B, is amended by:
    a. Adding two entries to the Table of Contents in numerical order; 
and
    b. Adding sections B.32 and B.33 immediately following section 
B.31.
    The additions read as follows:

Appendix B to Appendix W of Part 51--Summaries of Alternative Air 
Quality Models

Table of Contents

* * * * *
B.32  HGSYSTEM
B.33  SLAB
* * * * *

B.32 HGSYSTEM: Dispersion Models for Ideal Gases and Hydrogen Fluoride

References

    Witlox, H.W.M., 1991. HGSYSTEM: dispersion models for ideal 
gases and hydrogen fluoride, tutorial and quick-reference guide. 
Report TNER.91.007. Thornton Research Centre, Shell Research, 
Chester, England. [EGG 1067-1150] (NTIS No. DE 93-000952)

Availability

    The PC-DOS version of the HGSYSTEM software (HGSYSTEM: Version 
NOV90, Programs for modeling the dispersion of ideal gas and 
hydrogen fluoride releases. [EGG 1067-1153]), executable programs 
and source code, can be installed from ten 5\1/4\'' diskettes. These 
diskettes and all documentation are available as a package from 
Energy, Science & Technology Center: (615) 576-1301.

Technical Contacts

Doug N. Blewitt, Amoco Corporation, Environmental Affairs & Safety 
Department, Mail Code 4901, 200 East Randolph Drive, Chicago, IL 
60601, (312) 856-4099
Howard J. Feldman, American Petroleum Institute, 1220 L Street, 
Northwest, Washington, D.C. 20005, (202) 682-8340

Abstract

    HGSYSTEM is a software package consisting of mathematical models 
for simulating one or more of the consecutive phases between 
spillage and far-field dispersion of a non-reactive ideal gas or 
hydrogen fluoride (HF). The individual models can be described as 
follows: (1) HFSPILL calculates the time-dependent spill rate of HF 
liquid or HF vapor from a pressurized vessel; (2) EVAP calculates 
the spreading and evaporation of a boiling liquid pool on water or 
non-boiling liquid pool on land; (3) HFPLUME calculates the 
depressurization to ambient pressure, the jet release and the near-
field dispersion from a pressurized release of HF; (4) PLUME 
calculates the depressurization to ambient pressure, the jet release 
and the near-field dispersion from a pressurized release of non-
reactive, ideal gases; (5) HEGADAS calculates the steady-state or 
time-dependent ground-level heavy-gas dispersion resulting from 
either a ground-level pool or a source in a vertical plane; and (6) 
PGPLUME simulates passive-gas dispersion downwind of a transition 
point based on a simple Pasquill/Gifford similarity model. The 
models assume flat, unobstructed terrain. HGSYSTEM can be used to 
model steady-state, finite-duration and time-dependent releases. The 
models can be run in either the interactive or batch mode.

a. Recommendations for Regulatory Use

    HGSYSTEM can be used as a refined model to estimate short-term 
ambient concentrations. For toxic chemical releases (non-reactive 
chemicals or hydrogen fluoride; 1-hour or less averaging times) the 
expected area of exposure to concentrations above specified 
threshold values can be determined. For flammable non-reactive gases 
it can be used to determine the area in which the cloud may ignite.

b. Input Requirements

    1. HFSPILL input data: reservoir data (temperature, pressure, 
volume, HF mass, mass-fraction water), pipe-exit diameter and 
ambient pressure.
    2. EVAP input data: spill rate, liquid properties, and 
evaporation rate (boiling pool) or ambient data (non-boiling pool).
    3. HFPLUME and PLUME input data: reservoir characteristics, 
pollutant parameters, pipe/release data, ambient conditions, surface 
roughness and stability class.
    4. HEGADAS input data: ambient conditions, pollutant parameters, 
pool data or data at transition point, surface roughness, stability 
class and averaging time.
    5. PGPLUME input data: link data provided by HFPLUME and the 
averaging time.

c. Output

    1. The HGSYSTEM models contain three post-processor programs 
which can be used to extract modeling results for graphical display 
by external software packages. GET2COL can be used to extract data 
from the model output files. HSPOST can be used to develop 
isopleths, extract any 2 parameters for plotting and correct for 
finite release duration. HTPOST can be used to produce time history 
plots.
    2. HFSPILL output data: reservoir mass, spill rate, and other 
reservoir variables as a function of time. For HF liquid, HFSPILL 
generates link data to HFPLUME for the initial phase of choked 
liquid flow (flashing jet), and link data to EVAP for the subsequent 
phase of unchoked liquid flow (evaporating liquid pool).
    3. EVAP output data: pool dimensions, pool evaporation rate, 
pool mass and other pool variables for steady state conditions or as 
a function of time. EVAP generates link data to the dispersion model 
HEGADAS (pool dimensions and pool evaporation rate).
    4. HFPLUME and PLUME output data: plume variables 
(concentration, width, centroid height, temperature, velocity, etc.) 
as a function of downwind distance.
    5. HEGADAS output data: concentration variables and temperature 
as a function of downwind distance and (for transient case) time.
    6. PGPLUME output data: concentration as a function of downwind 
distance, cross-wind distance and height.

d. Type of Model

    HGSYSTEM is made up of four types of dispersion models. HFPLUME 
and PLUME simulate the near-field dispersion and PGPLUME simulates 
the passive-gas dispersion downwind of a transition point. HEGADAS 
simulates the ground-level heavy-gas dispersion.

e. Pollutant Types

    HGSYSTEM may be used to model non-reactive chemicals or hydrogen 
fluoride.

f. Source-Receptor Relationships

    HGSYSTEM estimates the expected area of exposure to 
concentrations above user-specified threshold values. By imposing 
conservation of mass, momentum and energy the concentration, 
density, speed and temperature are evaluated as a function of 
downwind distance.

g. Plume Behavior

    1. HFPLUME and PLUME: (1) are steady-state models assuming a 
top-hat profile with cross-section averaged plume variables; and (2) 
the momentum equation is taken into account for horizontal ambient 
shear, gravity, ground collision, gravity-slumping pressure forces 
and ground-surface drag.
    2. HEGADAS: assumes the heavy cloud to move with the ambient 
wind speed, and adopts a power-law fit of the ambient wind speed for 
the velocity profile.
    3. PGPLUME: simulates the passive-gas dispersion downwind of a 
transition point from HFPLUME or PLUME for steady-state and finite 
duration releases.

h. Horizontal Winds

    A power law fit of the ambient wind speed is used.

i. Vertical Wind Speed

    Not treated.

j. Horizontal Dispersion

    1. HFPLUME and PLUME: Plume dilution is caused by air 
entrainment resulting from high plume speeds, trailing vortices in 
wake of falling plume (before touchdown), ambient turbulence and 
density stratification. Plume dispersion is assumed to be steady and 
momentum-dominated, and effects of downwind diffusion and wind 
meander (averaging time) are not taken into account.
    2. HEGADAS: This model adopts a concentration similarity profile 
expressed in terms of an unknown center-line ground-level 
concentration and unknown vertical/cross-wind dispersion parameters. 
These quantities are determined from a number of basic equations 
describing gas-mass conservation, air entrainment (empirical law 
describing vertical top-entrainment in terms of global Richardson 
number), cross-wind gravity spreading (initial gravity spreading 
followed by gravity-current collapse) and cross-wind diffusion 
(Briggs formula).
    3. PGPLUME: It assumes a Gaussian concentration profile in which 
the cross-wind and vertical dispersion coefficients are determined 
by empirical expressions. All unknown parameters in this profile are 
determined by imposing appropriate matching criteria at the 
transition point.

k. Vertical Dispersion

    See description above.

l. Chemical Transformation

    Not treated.

m. Physical Removal

    Not treated.

n. Evaluation Studies

    1. PLUME has been validated against field data for releases of 
liquified propane, and wind tunnel data for buoyant and vertically-
released dense plumes. HFPLUME and PLUME have been validated against 
field data for releases of HF (Goldfish experiments) and propane 
releases. In addition, the plume rise algorithms have been tested 
against Hoot, Meroney, and Peterka, Ooms and Petersen databases. 
HEGADAS has been validated against steady and transient releases of 
liquid propane and LNG over water (Maplin Sands field data), steady 
and finite-duration pressurized releases of HF (Goldfish 
experiments; linked with HFPLUME), instantaneous release of Freon 
(Thorney Island field data; linked with the box model HEGABOX) and 
wind tunnel data for steady, isothermal dispersion.
    2. The validation studies are contained in the following 
references:
    McFarlane, K., Prothero, A., Puttock, J.S., Roberts, P.T. and 
Witlox, H.W.M., 1990. Development and validation of atmospheric 
dispersion models for ideal gases and hydrogen fluoride, Part I: 
Technical Reference Manual. Report TNER.90.015. Thornton Research 
Centre, Shell Research, Chester, England. [EGG 1067-1151] (NTIS No. 
DE 93-000953)
    Witlox, H.W.M., McFarlane, K., Rees, F.J., and Puttock, J.S., 
1990. Development and validation of atmospheric dispersion models 
for ideal gases and hydrogen fluoride, Part II: HGSYSTEM Program 
User's Manual. Report TNER.90.016. Thornton Research Centre, Shell 
Research, Chester, England. [EGG 1067-1152] (NTIS No. DE 93-000954)

B.33  SLAB

Reference

    Ermak, D.L., 1990. User's Manual for SLAB: An Atmospheric 
Dispersion Model for Denser-than-Air Releases (UCRL-MA-105607), 
Lawrence Livermore National Laboratory.

Availability

    1. The computer code is available on the Support Center for 
Regulatory Air Models Bulletin Board System (Upload/Download Area; 
see page B-1), and can also be obtained from:

Energy Science and Technology Center, P.O. Box 1020, Oak Ridge, TN 
37830, (615) 576-2606

    2. The User's Manual (NTIS No. DE 91-008443) can be obtained 
from:

Computer Products, National Technical Information Service, U.S. 
Department of Commerce, Springfield, VA 22161, (703) 487-4650

Abstract

    The SLAB model is a computer model, PC-based, that simulates the 
atmospheric dispersion of denser-than-air releases. The types of 
releases treated by the model include a ground-level evaporating 
pool, an elevated horizontal jet, a stack or elevated vertical jet 
and an instantaneous volume source. All sources except the 
evaporating pool may be characterized as aerosols. Only one type of 
release can be processed in any individual simulation. Also, the 
model simulates only one set of meteorological conditions; therefore 
direct application of the model over time periods longer than one or 
two hours is not recommended.

a. Recommendations for Use

    The SLAB model should be used as a refined model to estimate 
spatial and temporal distribution of short-term ambient 
concentration (e.g., 1-hour or less averaging times) and the 
expected area of exposure to concentrations above specified 
threshold values for toxic chemical releases where the release is 
suspected to be denser than the ambient air.

b. Input Requirements

    1. The SLAB model is executed in the batch mode. Data are input 
directly from an external input file. There are 29 input parameters 
required to run each simulation. These parameters are divided into 5 
categories by the user's guide: source type, source properties, 
spill properties, field properties, and meteorological parameters. 
The model is not designed to accept real-time meteorological data or 
convert units of input values. Chemical property data are not 
available within the model and must be input by the user. Some 
chemical and physical property data are available in the user's 
guide.
    2. Source type is chosen as one of the following: evaporating 
pool release, horizontal jet release, vertical jet or stack release, 
or instantaneous or short duration evaporating pool release.
    3. Source property data requirements are physical and chemical 
properties (molecular weight, vapor heat capacity at constant 
pressure; boiling point; latent heat of vaporization; liquid heat 
capacity; liquid density; saturation pressure constants), and 
initial liquid mass fraction in the release.
    4. Spill properties include: source temperature, emission rate, 
source dimensions, instantaneous source mass, release duration, and 
elevation above ground level.
    5. Required field properties are: desired concentration 
averaging time, maximum downwind distance (to stop the calculation), 
and four separate heights at which the concentration calculations 
are to be made.
    6. Meteorological parameter requirements are: ambient 
measurement height, ambient wind speed at designated ambient 
measurement height, ambient temperature, surface roughness, relative 
humidity, atmospheric stability class, and inverse Monin-Obukhov 
length (optional, only used as an input parameter when stability 
class is unknown).

c. Output

    No graphical output is generated by the current version of this 
program. The output print file is automatically saved and must be 
sent to the appropriate printer by the user after program execution. 
Printed output includes in tabular form:
    1. Listing of model input data;
    2. Instantaneous spatially-averaged cloud parameters--time, 
downwind distance, magnitude of peak concentration, cloud dimensions 
(including length for puff-type simulations), volume (or mole) and 
mass fractions, downwind velocity, vapor mass fraction, density, 
temperature, cloud velocity, vapor fraction, water content, gravity 
flow velocities, and entrainment velocities;
    3. Time-averaged cloud parameters--parameters which may be used 
externally to calculate time-averaged concentrations at any location 
within the simulation domain (tabulated as functions of downwind 
distance);
    4. Time-averaged concentration values at plume centerline and at 
five off-centerline distances (off-centerline distances are 
multiples of the effective cloud half-width, which varies as a 
function of downwind distance) at four user-specified heights and at 
the height of the plume centerline.

d. Type of Model

    As described by Ermak (1989), transport and dispersion are 
calculated by solving the conservation equations for mass, species, 
energy, and momentum, with the cloud being modeled as either a 
steady-state plume, a transient puff, or a combination of both, 
depending on the duration of the release. In the steady-state plume 
mode, the crosswind-averaged conservation equations are solved and 
all variables depend only on the downwind distance. In the transient 
puff mode, the volume-averaged conservation equations are solved, 
and all variables depend only on the downwind travel time of the 
puff center of mass. Time is related to downwind distance by the 
height-averaged ambient wind speed. The basic conservation equations 
are solved via a numerical integration scheme in space and time.

e. Pollutant Types

    Pollutants are assumed to be non-reactive and non-depositing 
dense gases or liquid-vapor mixtures (aerosols). Surface heat 
transfer and water vapor flux are also included in the model.

f. Source-Receptor Relationships

    1. Only one source can be modeled at a time.
    2. There is no limitation to the number of receptors; the 
downwind receptor distances are internally calculated by the model. 
The SLAB calculation is carried out up to the user-specified maximum 
downwind distance.
    3. The model contains submodels for the source characterization 
of evaporating pools, elevated vertical or horizontal jets, and 
instantaneous volume sources.

g. Plume Behavior

    Plume trajectory and dispersion is based on crosswind-averaged 
mass, species, energy, and momentum balance equations. Surrounding 
terrain is assumed to be flat and of uniform surface roughness. No 
obstacle or building effects are taken into account.

h. Horizontal Winds

    A power law approximation of the logarithmic velocity profile 
which accounts for stability and surface roughness is used.

i. Vertical Wind Speed

    Not treated.

j. Vertical Dispersion

    The crosswind dispersion parameters are calculated from formulas 
reported by Morgan et al. (1983), which are based on experimental 
data from several sources. The formulas account for entrainment due 
to atmospheric turbulence, surface friction, thermal convection due 
to ground heating, differential motion between the air and the 
cloud, and damping due to stable density stratification within the 
cloud.

k. Horizontal Dispersion

    The horizontal dispersion parameters are calculated from 
formulas similar to those described for vertical dispersion, also 
from the work of Morgan, et al. (1983).

l. Chemical Transformation

    The thermodynamics of the mixing of the dense gas or aerosol 
with ambient air (including water vapor) are treated. The 
relationship between the vapor and liquid fractions within the cloud 
is treated using the local thermodynamic equilibrium approximation. 
Reactions of released chemicals with water or ambient air are not 
treated.

m. Physical Removal

    Not treated.

n. Evaluation Studies

    Blewitt, D. N., J. F. Yohn, and D. L. Ermak, 1987. An Evaluation 
of SLAB and DEGADIS Heavy Gas Dispersion Models Using the HF Spill 
Test Data, Proceedings, AIChE International Conference on Vapor 
Cloud Modeling, Boston, MA, November, pp. 56-80.
    Ermak, D. L., S.T. Chan, D. L. Morgan, and L. K. Morris, 1982. A 
Comparison of Dense Gas Dispersion Model Simulations with Burro 
Series LNG Spill Test Results, J. Haz. Matls., 6: 129-160.
    Zapert, J. G., R. J. Londergan, and H. Thistle, 1991. Evaluation 
of Dense Gas Simulation Models. EPA Publication No. EPA-450/4-90-
018. U.S. Environmental Protection Agency, Research Triangle Park, 
NC.

PART 52--APPROVAL AND PROMULGATION OF IMPLEMENTATION PLANS

    1. The authority citation for Part 52 continues to read as follows:

    Authority: 42 U.S.C. 7401-7671q.


Sec. 52.21  [Amended]

    2. In Sec. 52.21, paragraphs (l)(1) and (l)(2) are amended by 
revising ``and supplement B (1993)'' to read ``, supplement B (1993) 
and supplement C (1994)''.

[FR Doc. 94-28456 Filed 11-25-94; 8:45 am]
BILLING CODE 6560-50-P