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


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                                    The Role of Acid Rain in Atmospheric Deposition


                                         Report for year ending December 31, 1990
                                                    CZM contract CM-263
                                                    Ref. FSU #1368-619-37



                                                    Principal Investigator:
                                                     John W. Winchester
                                                    Dept. of Oceanography
                                                    Florida State University
                                                    Tallahassee, FL 32306
                                                      Tel. 904-644-6700



                       A study conducted to assess the potential importance of atmospheric nitrate deposition
               for a north Florida estuary. Funds were provided by the Florida Department of Environmental
               Regulation, Office of Coastal Management, made available through the National Oceanic and
               Atmospheric Administration under the Coastal Zone Management Act of 1972, as amended.


                                                     Acknowledgements
                       I am indebted to Curtis Watkins for suggesting that we undertake the assessment, to Ji-
               Meng Fu and Jin-You Liang for participating as collaborators in conducting the study, to J..B.
               Martin and Linda Geiger for providing U.S. Geological Survey surface water data, and to William
              -Burnett, Peter Cable, Jeffrey Chanton, William Landing, and Paul LaRock for helpful discussions.



                                                      Table of Contents


                       The report is in three parts, in the form of papers for publication:

               Paper   1. Atmospheric Deposition of Nitrate and Its Transport to the Apalachicola Bay Estuary
                       in Florida, by John W. Winchester and Ji-Meng Fu

                       Paper presented at the Florida Acidic Deposition Conference, Tampa, October 22, 1990.
                       Submitted for publication in proceedings of the conference, edited by Curtis Watkins, and
                       in the journal Water, Air, and Soil Pollution. Portions were also described in an invited
                       seminar talk by John'W. Winchester at the University of Maryland, November 20, 1990.

               Paper 2. Acid Deposition Relationships in Florida and Southeastern U.S.A., by Jin-You Liang and
                       John W. Winchester


               Paper 3. Comparison of Acid Deposition and Surface Transport in Three Watersheds of North
                       Florida, by Ji-Meng Fu and John W. Winchester
















                                                       Executive Summary







                       A comparison of fluxes of ten dissolved constituents of rain water and river water has been
                carried out for the watershed of the Apalachicola River in order to estimate the magnitude of
                nitrate contribution from the atmosphere to surface water that may flow to the Apalachicola Bay
                estuary. The comparison is based on statistical analysis of both atmospheric and river water
                monitoring data: weekly rain water chemical data from the National Acid Deposition Program
                (NADP) for five sites within the watershed area, from 1978-84 until late 1989, and less frequent
                river water chemical data from the U.S. Geological Survey for one site at Chattahoochee, Florida,
                from 1965 until late 1989.


                        As descriptive statistics, the means and standard errors of the fluxes from the atmosphere
                and in the river flow were determined. As a measure of correlations between different ionic
                concentrations in the rain and river water data sets, factor analysis was used to account for data
                variance by a sum of principal components according to a linear mixing model. By comparing
                the compositions and magnitudes of these components, judgments could be made concerning
                the importance of atmospheric deposition as a source of nitrate in the watershed as well as of
                chemical transformations and possible loss of nitrate during its residence in the watershed and
                transport to the estuary.


                        Although surface sources of nitrogen and extent of loss to the atmosphere by
                clenitrification have not yet been quantitatively determined, atmospheric deposition to the
                watershed appears to be sufficient to account for essentially all the dissolved nitrate and
                ammonium and total organic nitrogen flow in the river. However, after deposition most of the
                nitrate may be transformed to other chemical forms during the flow, except possibly under high
                flow conditions mainly in winter. But either nitrate or the other forms could, with high efficiency,
                reach the estuary and be available for its marine biological processes.












                        The general uniformity of yearly average nitrate and sulfate deposition fluxes from acid
                air pollution over southeastern U.S.A. obscures possibly important differences on a smaller
                geographic scale and on seasonal or shorter time scales. A statistical analysis of weekly NADP
                wet chemical data from 18 sites over most of an eight state region has been carried out.
                Groupings of sites are identified that indicate uniformity over a state-wide scale, but not larger,
                in correlations based on short term variability in acid air pollution deposition fluxes. Thus, groups
                of sites within this geographic scale could serve as predictors of deposition on a shorter time
                scale than is possible based on long term averages of deposition data. For deposition to the
                watershed of the Apalachicola River, both meteorological conditions and transport from pollution
                sources appear to control deposition fluxes of nitrate and sulfate acid air pollutants.






                        Comparison of sulfate, different forms of nitrogen, and other chemical compositions
                between atmospheric deposition and surface transport has been made for the Apalachicola,
                Sopchoppy, and Ochlockonee Rivers in north Florida by mass balance and multivariate statistical
                methods. The results show that the chemical compositions of all rivers, in general, can be
                represented as a mixture of three groups of dissolved constituents. One, containing nitrogen and
                sulfate, resembles the composition of rain water; another, containing calcium, resembles ground
                water; and a third, containing chloride and sodium, resembles sea salt. Total mass flow of
                nitrogen in all three rivers agrees well with the average atmospheric deposition to their
                watersheds, suggesting that the atmosphere is the major source of nitrogen to their watersheds.
                However, for Cl-, Na+, Mg2+, Ca   2+ , K+, P04 3-, the calculated atmospheric contribution is much less'
                than their river fluxes, implying that surface processes, including urban, agricultural, and industrial
                releases and weathering of soil, are dominant. The three rivers differ considerably in types of
                watersheds. The finding that atmospheric nitrogen deposition fluxes agree well with transport of
                nitrogen by river flow and that river nitrate is largely correlated with non-seasalt sulfate implies
                that on the average the watersheds are in a quasi steady state and that additional surface
                sources or sinks are relatively small. Moreover, the high relative river flow of organic nitrogen,
                which is not present in rain water, suggests that it may be a watershed transformation product
                of atmospheric inorganic nitrogen.










                                   Atmospheric Deposition of Nitrate and Its Transport

                                        to tie Apalachicola Bay Estuary in Florida


                                             John W. Winchester and Ji-Meng Fu
                                       Dept. of Oceanography, Florida State University
                                                    Tallahassee, FL 32306



                                                            Abstract
                       A comparison of fluxes of ten dissolved constituents of rain water and river water
                   has been carried out for the watershed of the Apalachicola River in order to estimate
                   the magnitude of nitrate contribution from the atmosphere to surface water that may
                   flow to the Apalachicola Bay estuary. The comparison is based on statistical analysis
                   of both atmospheric and river water monitoring data: weekly rain water chemical data
                   from the National Acid Deposition Program (NADP) for five sites within the watershed
                   area, from 1978-84 until late 1989, and less frequent river water chemical data from
                   the U.S. Geological Survey for one site at Chattahoochee, Florida, from 1965 until late
                   1989.
                       As descriptive statistics, the means and standard errors of the fluxes from the
                   atmosphere and in the river flow were determined.          As a measure of correlations
                   between different ionic c.incentrations in the rain and river water data sets, factor
                   analysis was used to account for data variance by a sum of principal components
                   according to a linear mixing model. By comparing the compositions and magnitudes
                   of these components, judgments could be made concerning the importance of
                   atmospheric deposition as a source of nitrate in the watershed as well as of chemical
                   transformations and possible loss of nitrate during its residence in the watershed and
                   transport to the estuary.
                       Although surface sources of nitrogen and extent of loss to the atmosphere by
                   denitrification have not yet been quantitatively determined, atmospheric deposition to
                   the watershed appears to be sufficient to account for essentially all the dissolved nitrate
                   and ammonium and total organic nitrogen flow in the river. However, after deposition
                   most of the nitrate may be transformed to other chemical forms during the flow, except
                   possibly under high flow conditions mainly in winter. But.either nitrate or the other
                   forms could, with high efficiency, reach the estuary and be available for its marine
                   biological processes,


                                                         1. Introduction

                       We have selected the estuarine system o' Apalachicola Bay in north Florida and its
               watershed for a case study to address the question raised by the Environmental Defense Fund
               [Fisher et al., 1988]:   Can nitrate input to an estuary, to a significant degree, be due to
               atmospheric deposition, wet or dry, of acid air pollution? The EDF report has been considered
               seriously by the U.S. Environmental Protection Agency, and studies have been undertaken
               along the Atlantic coast to assess this possibility.         Some of the findings have been
               summarized for NAPAP [Waddell, 19891 in its SOS/T Report No. 10. On page A-31 it is
               stated:

                       Ecosystem N cycles are exceptionally complex and dynamic. Simple input-
                       output relationships, therefore, may be grossly misleading.             It is also
                       exceptionally difficult to determine all potential N losses (especially gaseous











                                                               2

                       ones) from the most important natural ecosystems.         Information on specific
                       impacts of elevated deposition inputs of N is just beginning to accumulate.
                       Ecosystem fates and effects of such inputs, as well as the demarcation between
                       beneficial and harmful impacts, will vary substantially across ecosystems and
                       sites, and over time.     Conclusions from studies are highly dependent on
                       experimental conditions. Also, most studies have focused on short-term acute
                       effects rather than longer-term chronic impacts and have not included spatial
                       heterogeneity in the experimental design.

                       This cursory review of some calculations of N mass balances has reinforced the
                       EDF hypothesis that atmospherically derived N is likely a major contributor to
                       surface water quality in estuaries and near-coastal waters. EPA (1989) reports
                       that at least 13% of total N loading to the Bay is atmospheric deposition.
                       Though details of thk@ EDF study can be criticized, the main conclusion is valid.
                       However, results from the Chesapeake Bay may not necessarily represent other
                       areas. Except for wet deposition over the land, the other estimated contributions
                       of N are difficult to assess and are highly uncertain.

                       Information suggests that a watershed has a rather high capacity to retain or
                       denitrify N entering it. Furthermore, the variability in the ratio of stream basin
                       yield to total deposition suggests that this capacity is highly variable among
                       watersheds and/or that the relative importance of N sources differs greatly
                       between watersheds.

                       In our study emphasis has been placed on evaluating existing data for an initial
               assessment and estimation of atmospheric deposition of nitrate to the Flint, Chattahoochee,
               and Apalachicola River watersheds and transformation or loss of nitrate in the watershed that
               may have occurred during transport toward the estuary.           An important objective of this
               assessment is to identify major uncertainties that may be reduced by a measurement program.
               The design of a meaningful field or laboratory measurement program should be based if
               possible on an examination of available atmospheric and surface water monitoring data.
               Fortunately, a considerable amount of such data has been obtained for our evaluation. This
               includes weekly rain water onernical data from the National Acid Deposition Program (NADP)
               for five sites that have operat,:d for 5-11 years within or near the watershed area, from 1978-
               1984 until late 1989.    It also includes a more lengthy record of less frequent river water
               chemical data from the U.S. Geological Survey for one site at Chattahoochee, Florida, from
               1965 until late 1989, that represent flow from the Flint and Chattahoochee Rivers, that drain
               90% of the watershed, into the Apalachicola River that empties into Apalachicola Bay. These
               data sets, each consisting of 140-400 or more samples that have been analyzed for ten or
               more chemical concentrations, are large enough for statistical analysis and precise
               comparisons that may reveal important deposition and watershed processes and lead to a
               provisional answer to the question posed by the EDF.


                                       2. Comparisons based on descriptive statistics

               a. Geographic uniformity of nitrate wet deposition fluxes to the surface

                       Table 1 summarizes NADP nitrate concentrations in rainwater at 30 monitoring stations
               in 8 southeastern states in weekly samples collected over 5 to 11 years up to 1989. From
               the reported millimeters of precipitation each week we       1have calculated the average wet
               deposition flux of nitrate over the years of record in kg ha- yr 1. These average fluxes range











                                                                 3

                over a factor of 3 from 4.23 in south Florida to 11.56 in western North Carolina (see map
                accompanying Table 1). Four sites that lie within or near the Apalachicola River watershed
                (Alabama b, Georgia c and a, and Florida f) have a much narrower range, from 5.90 to 7.49,
                and differences between these long term averages        are not statistically significant at the 95%
                confidence level (twice the standard error for each site). It should be noted that the number
                of samples analyzed at each site ranges from 142        to 371; any fewer samples would lead to
                a less precise result.    Week-to-week variability in concentrations and deposition fluxes of
                nitrate and other ions is very great at any site,       so that long-term monitoring with many
                samples collected is necessary to calculate a meaningful average deposition rate.

                       It should be remembered that dry deposition may contribute an additional flux of nitrate
                to the surface, according to estimates made by FCG, the Florida Electric Power Coordinating
                Group  [1987, p. 10-41 who state:

                       Estimates of total deposition were made by adding wet deposition observed from
                       the monitoring network to dry depositions calculated using ambient air data and
                       assumed deposition velocities.... Due to uncertainties in deposition velocities,
                       dry deposition of sultur is known with much less certainty than wet deposition.
                       . . . About one-half to two-thirds of total nitrogen deposition occurs as dry
                       deposition. Similar to results for sulfur, the majority of nitrogen dry deposition
                       appears to occur inthe form of acid precursors (i.e., N02).

                Therefore, the total atmospheric nitrate flux to the surface may be at least double that due to
                wet deposition alone, in spite of uncertainties in dry deposition estimates by our national and
                state programs.    Nevertheless, estimates of nitrate deposition from the atmosphere to the
                Apalachicola River watershed or estuary using these existing data can be useful.                 Any
                improvement by additional atmospheric measurements would require an effort greater than that
                made by NADP or FCG. The need for such improvement is probably less urgent than the
                need to resolve greater uncertainties con.-erning the transformation, retention, or loss of nitrate
                in the watershed during its transport toward the estuary.

                b. Comparison of atmospheric deposition fluxes with river flow of dissolved ions

                       Table 2 presents a comparison of the fluxes of 10 dissolved species in Apalachicola
                River water as it flows past the Chattahoochee monitoring site with the wet deposition fluxes
                calculated for the watershed area from data taken at 5 NADP sites situated in the vicinity of
                the watershed and at its northern extremity. The fluxes suggest two general groups: The first
                six ions - Cl-, Na', K', Ca2,, Mg2+, and PO,   3- - have atmospheric wet deposition fluxes much
                less than the measured river water flows, and even double the            'rain water fluxes as an
                estimate of total wet+dry deposition are also less. Thus, atmospheric deposition is not enough
                to account for the river flows, and additional surface sources must also be present.
                       The next three species measured in river water - S04         2- , NO,-, and NH4+1 - show a
                different relationship with atmospheric fluxes. For these the atmospheric inputs are at least
                equal to or are greater than river water flows, suggesting that the atmosphere may be their
                principal source. Org N (a mixture of organic nitrogen compounds in unfiltered water samples)
                is also included, and its river flow exceeds that of N03- and NH4       + combined. It should be
                noted that Org N is not routinely monitored in atmospheric samples, since it not a pollutant
                from carbonaceous fuel combustion and should occur at much lower concentrations than, for
                example, nitrate.    It should be kept in mind that organic nitrogen could be a chemical
                conversion product of a precursor, e.g. nitrate, after deposition to the watershed, so that its
                river flux could ultimately to be in part the result of an atmospheric source.











                                                                4


                       The possibility of a substantial atmospheric source for these four species may better
               be judged after by comparing fluxes on a molar rather than weight basis as shown in Table
               3. Addition of dry deposition would lead to a total deposition at least double the atmospheric
               wet-only fluxes listed, and the last column lists twice the 5-site wet deposition averages for
               comparison with river fluxes. For sulfate the average, median, and geometric mean are all
               close to, or slightly greater than, the river sulfate flux. This close agreement suggests that
               additional watershed sources or sinks may be relatively small, so that sulfate could be due
               mainly to atmospheric deposition with little interaction with the watershed during surface
               transport. If indeed surface sources, e.g. by weathering, or sinks, e.g. by ion exchange, are
               relatively small, then sulfate may be a conservative tracer of atmospheric input from acid
               deposition to the watershed.

                       The river flow of N03- is considerably less than (roughly 1/3 of) twice the    atmospheric
               wet deposition, suggesting that, if the atmosphere is the principal source of N031 roughly 2/3
               has been transformed, lost, or retained by the watershed. For NH4+ the discrepancy is much
               greater, indicating that over 90% of NH4' is transformed, lost, or retained. For Org N we lack
               chemical concentrations measured in rain water, but these are believed (cf. the above cited
               statement by FCG [1987, p. 10-4]) to be much less than for nitrate. In contrast, on a molar
               basis the river fluxes of Org N are larger than those of nitrate and ammonium ion combined,
               and the total river flux of these three forms of dissolved nitrogen are 60-75% of the average,
               median, or geometric mean of twice the wet deposition from the atmosphere.

                       The material balance is not complete, however, until other surface sources of nitrogen
               compounds and losses back to the atmosphere are estimated. Not only agricultural, industrial,
               and urban sources, but the evolution of N20 and N2 should be considered. It should be noted
               that a likely range of N20 from managed agricultural systems is 0.2 to 6 kg N20-N ha-1 yr-1
               [Goodroad  6et al., 1984], a range that translates into (0.07-2.1)xlO9 moles N20-N per year for
               the 5.Ox1O ha of the watershed draining the Flint-Chattahoochee-Apalachicola River system.
               This range is the same general order of magnitude as the nitrogen transport data of Table 3,
               suggesting that N20 loss to the atmosphere could be an important part of the nitrogen budget
               of the watershed.

                       Atmospheric deposition of nitrate appears to be more than enough to account for
               dissolved nitrogen in the river, but transformation of nitrate to other forms, e.g. Org N, as well
               as some retention by the watershed or loss by return to the atmosphere through denitrification
               must occur during watershed or river transport. If surface sources are small enough relative
               to atmospheric, the transport efficiency of nitrogen-containing nutrients to the estuary after
               atmospheric deposition of nitrate could be quite high, although the chemical link between
               nitrate and organic nitrogen compounds in the river must still be demonstrated explicitly.

                       The last line of Table 2 is included to compare river water flow with       rainfall to  the
               watershed measured at 5 NADP sites. The river flow is for one year studied by Mattraw           and
               Elder [1984], whereas the rainfall is calculated for the measured rate at each NAIDP            site
               multiplied by the total watershed area. For two of the sites rainfall was measured for the
               year of river measurements, whereas for the other three sites the average rainfall is given for
               the indicated time interval.   It appears that average river flow is 2 to 3-fold lower than      the
               estimated rainfall input, indicating a substantial loss of water by evaporation or transpiration.
               However, soluble ions such as S04      2- should not be similarly lost, nor should N03- without
               additional chemical reaction in the watershed.











                               3. Comparisons based on absolute principal component analysis

                a. Absolute principal component analysis

                        In the foregoing approach based on material balance, long term average atmospheric
                and river monitoring data were compared. As an alternative, we now examine short term
                variability by multivariate statistical analysis of measured chemical concentrations. In absolute
                principal component analysis the correlations between the concentrations in the large number
                of samples within each data set are the basis for identifying groupings of elements that
                represent components. These may include, for example, acid rain or sea salt, and be present
                in different proportions in the different samples. The analysis attempts to account for the
                observed chemical concentration data as the sum of a small number of these components,
                assuming each has a fixed composition and the samples differ only in the mixing ratios of the
                components. The procedure followed here is carried out using a desktop microcomputer and
                commercial software; it is well known and has been described, for example, by Li and
                Winchester [1990].       Similar procedures have been used in two recent studies of acid
                deposition data [Hooper and Peters, 19809; Eder, 1989], but no such study of surface water
                data is known to us at present.

                b. Prin cipal components present in acid rain
                        Table 4 presents two examples of the factor analysis of NAbP rain water concentration
                data sets from sites, indicated in Table 1, in Florida and North Carolina that are near the
                watershed. This analysis indicates that, on average, 93% and 79%, respectively, of the
                variance can be explained as mainly due to the mixing in different proportions of three or two
                components that may have different origins, The oroportions may be caused by exposure of
                the air mass to different source areas to differing degrees before rain deposits its constituents
                to the surface.     Both the.factor loadings (correlation coefficients between measured ion
                concentrations and factor scores) and the factor compositions (concentrations of ions assigned
                to each factor) are shown in Table 4.           A high loading indicates that most of an ion is
                assigned to a factor, whereas the actual concentration of an ion in a factor, though perhaps
                small, can be compared to other ions and provide clues about the physical interpretation and
                origin of an atmospheric component.

                        At Quincy, Florida, most variance (factor 1) is explained by a factor with high loadings
                of Cl-, Na+, Mg2+, and Ca   2+; the ion concentrations calculated for factor 1 show a composition
                close to that of seasalt, except for a 50% enrichment of S04        2, . But most S04  2- together with
                NO.- are present in factor 2 in a proportion close to that expected for acid rain, with NH4+
                only 8.5% of that needed to neutralize sulfuric and nitric acids, indicating a strongly acidic
                                            2,                                                                         2-
                component, and even Ca. together with NH4+ balance only 19% of the equivalents of S04
                and NO,-. In addition, factor 3 also contains S04      2' and NO,-, together with NH4+ Sufficient to
                neutralize 63% (68% with Ca        2+) of the strong acidity, indicating a less acidic pollution
                component. These factors at the near coastal Florida site are interpreted to represent
                (1) seasalt aerosol that has   taken up additional pollution S02 before rainfall scavenging, such
                        as by sulfuric acid displacement of chloride,
                (2) sulfuric and nitric acid air pollution from tall stack fuel combustion sources, with little
                        ammonia from its surface sources on land, such as may be due to polluted air mass
                        transport over the sea surface before rainout, and
                (3) more neutralized acid rain such as by a longer residence time over terrestrial sources of
                        ammonia before rainout.
                It is important to realize that most of the sulfuric and nitric acids present in rain at Quincy,
                Florida, are not neutralized by ammonia. The relative importance of the three components











                                                                 6

                may be related, sample-by-sample, to air flow trajectories, although this comparison was not
                attempted in the present analysis.

                       At Coweeta, North Carolina, only two factors were found to explain a significant amount
                of variance. The most is factor 1 with composition expected for acid air pollution, indicated
                by high concentrations of S04  2- and NO,', with additional NH4+ sufficient to neutralize 22% of
                sulfuric and nitric acids. Factor 2 resembles seasalt in composition but also contains smaller
                concentrations of SO  42- and NO,   ., although with relatively less NH4+ than in factor 1.      As
                expected from its geographic location, seasalt concentration is lower than in coastal Florida,
                but the acid rain pollutant concentrations are higher and quite uniform in relative proportions
                so that only one factor is needed to describe them.
                       We should take special note of the chemical equivalent ratio N03_/xS04        2- at the two
                sites, 0.52, 0.32, and 0.39 in the three acid pollution factors just discussed, or about 0.4
                overall. These will be compared with the results of principal component analysis of surface
                water data.

                c. Principal components present in surface water

                       Apalachicola River water has been sampled by the U.S. Geological Survey since the
                1960's at a site below the Jim Woodruff dam at Chattahoochee near the confluence of the
                Chattahoochee and Flint Rivers. Over 200 samples (indicated in the note to Table 2) were
                collected several times each year, though less frequently during the 1980's, and analyzed for
                dissolved ions and for tota 'I organic nitrogen using procedures summarized by Maftraw and
                Elder [1984). The results of three different factor analyses of this data set are shown in Table
                5. The first shows that factors 1, 2, and 3 are defined by combinations of ions, but that Org
                N, NH4+1 and P04   3- are each relegated almost completely to their own factors. The second
                analysis, without the last two ions, confirms this result for Org N, indicating that the concentra-
                tion of this important constituent varies independently of the major dissolved ions. The third
                analysis, without Org N, was then carried out in order to include about 50% more samples
                that did not include Org N data for a more precise definition of the first three factors over the
                25 years of record, and its results are similar.

                       The compositions of the three factors, that explain 84% of data variance, form patterns
                that we recognize to represent plausible components in a linear mixing model of river water:
                       o One (factor 2) is rich in Ca  2' and the separate measurement of hardness and may
                be considered as ground water, i.e. meteoric water that has been exposed to limestone. NO
                is virtually absent, although S04  2- and other ions are present in small concentrations.
                       o Another (factor-1) contains most of the S04    2' and a substantial fraction of the NO,
                but the ratio NO 3' /XSO42" is lower than in the acid rain components in Table 4 by a factor of
                almost 10. It is important that NO,' is sufficiently well correlated with   So 42, to be assioned
                to this factor, suggesting that both ions are the result of atmospheric inputs. But if S04     2- is
                a relatively conservative tracer of acid rain in the surface water, its corresponding NO, has
                been depleted nearly 10-fold. Thus, if it is the result of acid rain, the component is a very
                aged rain that has lost NO,- by chemical transformation or removal from the aquatic system.
                       o  A third (factor 3) contains  So 2' and smaller concentrations of other ions, including
                significant NO,' and a ratio NO,'/xSO   2' about equal to the acid rain components in Table 4.
                                                    2 4
                Thus, NO,' is correlated with SO    4 -and assigned to this factor, suggesting an atmospheric
                deposition source and not depleted below the expected level. Compared to the other river
                water components, it may represent rather freshly fallen rain, such as in heavy storms, without
                sufficient time in the watershed for its NO.'  to be transformed or lost.











                                                                 7


                                  4. Comparisons based on patterns of temporal variability

               a. Temporal variations in acid precipitation

                       At any of the NADP sites the amount of rainfall and the concentrations and depositions
               of the measured ions in rainwater vary over a wide range, and the standard deviation about
               the mean (range of 68% of the observations) is typically as large as the mean itself.
               Consequently, a very large number of samples is required to calculate a precise average.
               The extreme variability is illustrated in Figs. 1-5 for the 5-year record at the Florida Quincy site
               at which rain was sampled during 60% of the weeks. In Fig. 1, that includes weeks without
               rain, the weekly rainfall ranged from a few to well over 100 mm, without discernable seasonal
               pattern or significant change in trend over the 5 years. Fig. 2 shows that the concentration
               of factor 1 (mainly sea salt) ranges over more than a factor of 10 in relative factor score units,
               without apparent regularity.

                       Since concentration of any component is the result of both dilution and the supply of
               the trace constituent itself, the deposition (concentration x precipitation amount) is plotted in
               Figs. 3, 4, and 5 for factors 1, 2, and 3, respectively. These also show a wide ran            .ge of
               variability, with sporadic peaKs a few times each year but without obvious seasonal or longer
               term pattern. It may be that some of these episodes of peak deposition can be linked to
               weather conditions, and we have initiated a metEorological investigation of these conditions.
               But until a means has been developed to forecast acid deposition from weather data, a long
               term monitoring program, such as NADP, is needed to estimate average deposition at a
               specific location. Such data can also be used to resolve and define the compositions of
               principal components as we have seen.

               b. Temporal variations in river water composition

                       The variability over 25 years of monitoring the Apalachicola River is illustrated in Figs.
               6-12. Fig. 6 shows that water flow rate in the river exhibits a pronounced seasonal pattern,
               with highest flow during the winter months early each year, quite unlike rainfall patterns such
               as in Fig. 1. We believe that river flow is closely linked to seasonal variation of the growth
               of plants in the watershed, with much less loss of water by evapotranspiration to the
               atmosphere during winter. Fig. 1 also shows that seasonal winter maxima in water flow have
               declined in amplitude since 1980, perhaps the effect of increased withdrawal of water for
               human use in the 3-state region during recent years.

                       Figs. 7-9 show variaiion in concentration of the three principal components, in relative
               factor score units, i.e. (1) aged rain, (2) ground water, and (3) fresh rain, with compositions
               given in Table 5.      All three components exhibit considerable variation in concentration,
               especially for fresh rain (factor 3) compared to aged rain (factor 1), with intermediate variation
               for ground water (factor 2). Since about 1980 it appears that the concentrations of all three
               components have been gradually rising as a longer term trend. If real, this trend could be the
               result of an interplay of several effects, such as the relative inputs to the river flow from wet
               and dry deposition and how each of these may be affected by withdrawal of water for human
               use in the 3-state region.

                       By close scrutiny of Figs. 6-9 we can compare the timings of peaks in flow and
               concentrations of the three components. Water flow peaks in the winter months early each
               calendar year. Aged rain concentrations peak in the fall months late each calendar year at
               times tending to coincide with minima in water tiow. Ground water concentrations show deep











                                                             8

               minima during peak winter flow and broad maxima in midsummer when water flow is generally
               low. (A scatter diagraro of river flow vs. ground water component concentration (not shown)
               shows a significant negative correlation, whereas no overall correlation of other factor
               concentrations with river flow is found.) Fresh rain concentration maxima tend to occur early
               each year near times of peak river flow, although with exceptions, and minima usually occur
               in midsummer when flow rat2 is low. The aged rain concentration peaks thus tend to precede
               fresh rain peaks, but with exceptions. In general, the scrutiny reveals these correspondences
               in timing of concentration and river flow peaks that are consistent with the recognition of
               principal components as representing ground water, aged rain, and fresh rain. Figs. 10-12
               show temporal variations of the fluxes of three components, i.e. concentrations x flow rate.
               All show high winter maxima, the result of much more prominent maxima in winter flow rates
               than the peaks in concentrations.


                                                       5. Discussion

                      Some additional comparisons may contribute to our understanding of the relationship
               between atmospheric deposition and surface water composition. First, if factor 2 represents
               ground water, we may attempt to estimate the volume of such ground water in the river.
               Table 6 presents the average concentrations of Ca  2+ and hardness in well water of northwest
               Florida counties in comparison with the corresponding concentrations in factor 2. Factor 2
               concentrations are expressed per unit of river water and are about 27% and 23% of the well
               water averages for Ca 2+ and hardness respectively. Therefore we may reason that about 25%
               of the river flow is due to ground water, a result that agrees closely with a field study by
               Maftraw and Elder [1984] and in approximate agreement with estimates of global ground water
               flow to rivers [World Resources Institute, 1990).

                      A further comparison of river flow with the study by Mattraw and Elder [1984] indicates
               general agreement. Table 7 shows that their flow for a one-year study period is identical to
               the median of USGS measurements for that year and within one standard error of the
               average. The one-year study also reported flow of total nitrogen (the sum of all dissolved
               inorganic and the organic nitrogen in unfiltered water).        This is again close to the
               corresponding sum of USGS data. This satisfactory comparison supports the validity of the
               USGS measurements and our interpretation of them.

                      The results of this study indicate the great value of long records of atmospheric and
               surface water monitoring data and the information that can be extracted from them by
               application of multivariate statistical methods.   The present conclusions are, of course,
               tentative, since not all available data have yet been fully analyzed. Nevertheless, it appears
               that we are converging onto a means of estimating the extent of nitrate loss or retention by
               a watershed before transport to an estuary, a challenge that is considered by other experts
               to be of central importance.    For the immediate future, further study of existing data is
               mandatory, so as to design future measurement programs that will reduce uncertainties in our
               understanding. These programs could include laboratory experimentation to test the validity
               of mechanisms suggested by field measurement data, for example mechanisms for N03
               .transformation, loss, or retention during watershed flow and how these may differ from direct
               precipitation to a flood plain. Additional field surveys may also be desirable, for example to
               demonstrate differences between river components that are suggested by the statistical
               analysis.











                                                              9

                      Acknowledgements. We are indebted to       Curtis Watkins for suggesting that we assess
               the potential importance of atmospheric nitrate deposition for a north Florida estuary, to J.B.
               Martin and Linda Geiger for providing U.S. Geological Survey surface water data, and to
               William Burnett, Peter Cable, Jeffrey Chanton, Paul LaRock, and Jinyou Liang for helpful
               discussions. Funds for this project were provided by the Florida Department of Environmental
               Regulation, Office of Coastal Management using funds made available through the National
               Oceanic and Atmospheric Administration under the Coastal Zone Management Act of 1972,
               as amended.



                                                         References
               Eder B.K. [1989]. A principal component analysis of S04     2- precipitation concentrations over
                      the eastern United States. Atmos. Environ. 23, 2739-2750.

               Fisher D.J., Ceraso J., Mathew T., and Oppenheimer M. [1988]. Polluted Coastal Waters:
                      The Role of Acid Rain. Environmental Defense Fund, New York, 102 pp.

               Florida Electric Power Coordinating Group [1987]. Florida Acid Deposition Study Five-Year
                      Data Summary. Environmental Science and Engineering, Inc. ESE No. 85-186-0106-
                      2110, October 1987.

               Goodroad L.L., Keeney D.R., and Peterson L.A. [1984].           Nitrous oxide emissions from
                      agricultural soils in Wisconsin. J. Environ. Quality 13, 557-561.

               Hooper R.P. and Peters N.E. [1989). Use of multivariate analysis for determining sources of
                      solutes found in wet atmospheric deposition in the United States.          Environ. Sci.
                      Technol. 23, 1263-1268.

               Li S.M. and Winchester J.W. [1990). Haze and other aerosol components in late winter Arctic
                      Alaska, 1986. J. Geophys. Res. 95, 1797-1810.

               Mattraw Jr. H.C. and Elder J.F. [1984]. Nutrient and Detritus Transport in the Apalachicola
                      River, Florida. U.S. Geological Survey Water-Supply Paper 2196-C, Apalachicola River
                      Quality Assessment. Alexandria, VA, viii+62 pp.

               Waddell T.E. [1989]. State of the Science Assessment: Watershed and Estuarine Nitrogen
                      Transport and Effects.     Appendix A of NAPAP State of Science and State of
                      Technology SOS/T Report No. 10, Watershed and Lake Processes Affecting Chronic
                      Surface Water Acid-Base Chemistry, December 1.989, pp. i to vi + A-1 to A-40.

               World  Resources Institute [1990].    World Resources 1990-91.       Chapter 10, Freshwater.
                      Oxford University Press.














                                                                                                                      NADP/NTN MONITORING NETWORK

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                                                                             Locations or acLiVe sites in the NADP/NTN nCt%York as of 10 Noveinber, 1989
                                                                                                                                                                                              h










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                   Table   1. NADP/NTN wet precipitation concentration and deposition summary for eight
                             southeastern states: Florida, Georgia, Alabama, Mississippi, Louisiana, South
                             Carolina, North Carolina, Tennessee

                             A. Rainwater weekly sampling summary

                   Site      Location                            Count             Dates Sampled                        Valid Samples
                                                                                                               Number      % of weeks
                                      Florida
                   Fl-c      Everglades                          Dade              800617-890808                   253                 53
                   FLe       Verna Well Field                    Sarasota          830825-890808                   177                 57
                   FLd       Kennedy Space Ctr                   Brevard           830802-890808                   198                 63
                   FLa       Bradford Forest                     Bradford          781010-890725                   350                 62
                   FLf       Quincy                              Gadsden           840313-890808                   168                 60
                                      Georgia
                   GAb       Bellville                           Evans             830426-890815                   214                 65
                   GAc       Tifton                              Tift              831004-890808                   199                 65
                   GAa       Georgia Stn                         Pike              781003-890815                   371                 65
                                      Alabama
                   ALb       Sand Mtn                            DeKalb            841002-890808                   142                 56
                   ALa       Black Belt Substn                   Dallas            830831-890815                   206                 56
                                      MiSSiSSijDPi
                   MSa       Meridian                            Lauderdale        800415-890808                   347                 71
                   MSd       Newton                              Newton            861111-890808                      ---                --
                   MSc       Coffeeville                         Yalobusha         840717-890815                   155                 58
                   MSb       Clinton                             Hinds             840710-890815                   163                 61
                                      Louisiana
                   I-Ac      Southeast Res Ctr                   Washington        830118-890808                   242                 71
                   I-Aa      Iberia Res Stn                      Iberia            821116-890808                   244                 70
                   I-Ab      Hill Farm Res     Stn               Claiborne         821116-880126                   159                 59
                                      South Carolina
                   SCb       Santee N Wildlife Ref               Clarendon         841016-890808                   141                 56
                   SCa       Clemson                             Pickens           790327-860617                   270                 72
                                      North Carolina
                   NCa       Lewiston                            Bertie            781031-890815                   437                 78
                   NCd       Clinton Crops Res Stn               Sampson           781024-890815                   396                 70
                   NCe       Finley Farm                         Wake              781003-890815                   393                 69
                   NCi       Jordan Creek                        Scotland          831018-890801                   196                 65
                   NCc       Piedmont Res       Stn              Rowan             781114-890808                   402                 72
                   NCj       Clingman's Peak                     Yancey            851126-890808                      96               50
                   NCb       Coweeta                             Macon             780705-890808                   418                 72
                                      Tennessee
                   TNb       GtSmokyMts N Pk-Elkmont             Sevier            800812-890801                   281                 60
                   TNa       Walker Branch Watershed             Anderson          800311-890815                   372                 76
                   TNc       Giles County                        Giles             841002-890808                   151                 60
                   TNd       Hatchie N Wildlife Ref              Haywood           841002-890808                   143                 57









                        B. Nitrate and sulfate concentration and deposition averages
                                + standard error (68% confidence interval)
                 Site           N03- conc.               N03- wet dep.            N03'/SO4   2-
                 L D.           mg L-1                   kg ha-1 yr-1             wt. ratio

                 FLc            0.643+.037              4.23+0.36                 0.577+.025
                 FLe            0.988+.072              6.40+0.80                 0.707+.031
                 FLd            0.931+,057              6.34+0.59                 0.559+.025
                 FLa            1.001+,046              7.44+0.42                 0.597+.017
                 FLf            1.016+.079              6.76+0.65                 0.632+.023

                 GAb            1.311+.085              6.85+0.44                 0.659+.024
                 GAc            0.984+.069              5.90+0.42                 0.665+.027
                 GAa            1.161+.052              7.49;0.39                 0.5307.013

                 ALb            1.167+.098              6.44+0.43                 0.  474+.017
                 ALa            1.033+.061              7.15+0.43                 0.598+.019

                 MSa            1.165+.051              10.30+0.52                0.596+.014
                 MSd
                 IMSC           1.118+.072              8.41+0.57                 0.745+.029
                 MSb            1.163+.077              7.43+0.52                 0.713+.035

                 LAc            1.140+.070              10.95+0.65                0.693+.022
                 LAa            1.230+.066              10.14+0.69                0.686+.021
                 I-Ab           1.221+.073              7.91+0.56                 0.730+.022

                 SCb            1.034+.070              5.33+0.49                 0.577+.029
                 SCa            1.579+.075              10.81+0.60                0.575+.015

                 NCa            1.491+.073              10.08+0.47                0.602+.014
                 NCd            1.408+.067              8.73+0.42                 0.569+.010
                 NCe            1.61' 8+.074            9.12+0.42                 0.627+.017
                 NCi            1.318+.085              9.59+0.67                 Mog+.017
                 NCc            1.689+.065              11.56+0.55                0.589+.016
                 NCj            0.986+.184              5.08+0.52                 0.470+.021
                 NCb            1.107+.045              10.90+0.46                0.541+.011

                 TNb            1.254+.061              8.32+0.43                 0.593+.016
                 TNa            1.580+.063              11.18+0.48                0.529+.024
                 TNc            1.212+.073              8.91+0.64                 0.631+.052
                 TNd            1.033ï¿½.061              7.50+0.54                 0.693+.028









                 Table    2.    Comparison of average ion transport in Apalachicola River flow at
                          Chattahoochee with average wet deposition measured at five NADP sites in the
                          Flint and Chattahoochee River basins.
                          River transport       ion concentration (mg Ll x measured water flow (M3                 sec-1).
                          Wet deposition        ion concentration (mg L' ) x measured precipitation (mm) x
                          entire basin area (kM2).      Units converted to metric kilotons of the ions per year.


                                     Apalachicola                    NADP Wet Deposition Site                     5 Site
                 Ion                          River             NCb      ALb      GAa     GAc         FLf      Averages

                 Cl-      Average                86.8              13.9      8.8    12.5     16.0     24.0             15.0
                          +Std error            .+4.8              +1.0    +0.7     +0.7     +1.2     +3.0             +1.3
                          Dedian                 @9.4               7.1    -5.7     -7.4     TO.2     T2.0               8.5
                          Geom. mean             68.7               6.8      5.4      7.2     8.8     11.1               7.9

                 Na+      Average                98.3               9.3      4.9      8.2     9.0     13.7               8.0
                          +Std error             +5.1              +0.7    +0.4     +0.6     +0.6     +1.7             +0.8
                          j@ledian               @7. 0              4.2    -3.0     -4.5     -6.0     -6.8             -4.9
                          Geom. mean             82.4               4.0      2.9      4.4     5.3      6.4               4.6

                 K+       Average                27.7               1.4      1.0      1.5     3.5      1.5               1.8
                          +Std error             +1.7              +0.1    +0.1     +0.2     +0.9     .+0.2            +0.3
                          Dedian                 T7.7               0.8    -0.6     -0.7     -0.9     -0.7             -0.7
                          Geom. mean             21.5               0.7      0.5      0.6     0.9      0.6               0.7

                 Ca 2+    Average               208.5               5.2      3.3      4.4     4.2      4.1               4.2
                          +Std error             +8.4              +0.4    +0.2     +0.3     +0.4     +0.5             +0.4
                          !@Iedian              [email protected]               3.2    -2.1     -2.6     -2.2     -2.3               2.5
                          Geom. mean            183.4               3.2      2.3      2.7     2.3      2.1               2.5

                 Mg  2'   Average                22.2               1.5      0.9      1.4     1.6      2.0               1.5
                          +Std error             +1.2              +0.1    +0.1     +0.1     +0.1     +0.2             +0.1
                          j@edian                T6.1               0.9    -0.7     -0.9     -1.1     -1.1               0.9
                          Geom. mean             18.5               0.9      0.6      0.9     1.0      0.9               0.9
                 P04  3-  Average                  1.22            <0.51   <0.54    <0.33    <0.66    <0.67            <0.54
                          +Std error               0.13             0.04     0.05     0.03    0.08     0.07            +0.05
                          @@edian                  0.59            <0.22   <0.37    <0. 15   <0.32    <0.30            <0.27
                          Geom. mean               0.72            <0.22   <0.31    <0.14    <0.28    <0.30            <0.25









                                    Apalachicola                 NADP Wet Deposition Site                   5 Site
                Ion                         River            NCb      ALb    GAa      GAc       FLf     Averages
                S04 2-  Average               115.2           100.0    70.3    71.0    46.9     53.8            68.4
                        +Std error            +7.6            +4.3     +5.1    +4.1    +3.4     +5.5            +4.5
                        j@eclian              @7.2            74.2     -48.1   @4.4    k2       @2.4            @6.7
                        Geom. mean            87.0            66.6     48.3    44.9    28.5     28.4            43.3

                N03-    Average               26.2            48.3     28.6    33.3    26.2     30.0            33.3
                        +Std error            +2.1            +2.1     +1.9    +1.7    +1.8     +2.9            +2.1
                        Median                T3.8            @7.3     22.4    @2.2    T8.5     T7.6            @3.6
                        Geom. mean            13.8            32.0     20.2    20.0    16.1     15.6            20.8

                NH4+    Average                 1.18            9.2      8.9     5.9     4.9      4.9             6.8
                        +Std error            +0.21           +0.6     +1.3    +0.4    +0.5     +0.6            +0.7
                        j@eclian                0.50            5.3    -5.1    -3.5    -2.5     -1.9              3.7
                        Geom. mean              0.61            4.2      4.5     2.9     2.0      1.7             3.1

                Org N   Average               10.2
                (as N)  ï¿½Std error              0.8
                        Median                  6.4
                        Geom. mean              7.1

                Numbers of samples                            418     142     371      199      168

                  Numbers of river samples averaged for the different chemical concentrations were Cl' 203,
                        Na" 182, W 182, Ca      2+  182,  Mg2+  182, P04  3- 148, S04  2- 183, N03- 200, NH4+ 94, Org
                        N (organic nitrogen) 152. Wet deposition samples averaged were the same for all ions
                        at each NADP site as indicated.

                Water total, kM3    yr-1      24.1            75.0     38.6    56.2    45.8     49.0            52.9
                  averaged over              6/79-          6/79- 10/84- 6/79- 10/83- 3/84-
                   the period                5/80            5/80     8/89   5/80     8/89   8/89









                Table 3. Transport of sulfate and forms of nitrogen in Apalachicola River flow
                                 at Chattahoochee compa     red with atmospheric deposition at five
                                 NADIP sites. Units: 10 moles per year.

                                  Apalachicola          Atmospheric Deposition, 5 Site Average
                Ion                        River                Wet only        2xWet = Wet+Dry
                S04  2-  Average               1.20                    0.71            1.42
                         +Std error           +0.08                    0.05            0.09
                         j@edian               0.80                    0.49            0.97
                         Geom. mean            0.91                    0.45            0.90

                NO  3'   Average               0.42                    0.54            1.07
                         +Std error            +0.03                   0.03            0.07
                         j@edian               0.22                    0.38            0.76
                         Geom. mean            0.22                    0.34            0.67

                NH4+     Average               0.066                   0.38            0.75
                         +Std error            +0.012                  0.04            0.07
                         j@edian               0,028                   0.20            0.41
                         Georn. mean           0.034                   0.17            0.34

                Org N    Average               0.73
                (as N)   ï¿½Std error            0.06
                         Median                0.46
                         Geom. mean            0.51

                  N      Average               1.22                    0.92            1.82
                         Median                0.71                    0.58            1.17
                         Geom. mean            0.76                    0.51            1.01







                                Table 4. Examples of Factor Analysis of Ion Concentrations
                                              at Two NADP Wet Deposition Sites

                                A. A Florida near coastal site, FLf Quincy, 3 significant factors
                                                       Factor loadings (correlation coefficients)
                       Variable                                 Factor 1        Factor 2      Factor 3
                       Cl-                                           0.98           0.06            0.07
                       Na-'                                          0.98           0.08            0.04
                       Mg    2+                                      0.94           0.27            0.11
                       Ca    2+                                      0.62           0.64            0.09
                       S04   2-                                      0.12           0.87            0.32
                       N03-                                          0.10           0.93            0.21
                       NH4   +                                       0.11           0.39            0.91
                       Variance explained, 93%                      46%            33%             14%
                                                       Factor concentrations    ug L-) and ion ratios
                       Variable                  Const.         Factor 1        Factor 2       Factor 3
                       Cl-                          57+18         1030+13          32+7            29+5
                       Na'                          32+11         607+9            24+4            10+3
                       Mg    2+                     -4+2            86+1           12+1             4+1
                       Ca    2+                    -20+8          111+46           58+3             6+2
                       S04   2-                    100+68         224+51          843+26         231+20
                       N03-                         46+34         118+26          562+13           94+10
                       NH4+                         -4+2            21+1           41+1            72+1-
                       Equivalent ratios
                       NO    3-/XSO42-                            1.25+0,92       0.52+0.02      0-32+0.04
                       NH4+/(NO3-+XS04                            0,35+0.12     0.085+0.002      0-63+0.05

                                B. A North   Carolina inland site, NCb Coweeta, 2 significant factors
                                                       Factor loadings (correlation coefficients)
                       Variable                                 Factor 1        Factor 2
                       Cr                                            0.12           0.91
                       Na+                                           0.04           0.86
                       Mg    2+                                      0.40           0.85
                       Ca    2+                                      0.68           0.44
                       S04   2-                                      0.89           0.10
                       N03+'                                         0.89           0.20
                       NH4                                           0.87           0.06
                       Variance explained, 79%                      43%            36%
                                                       Factor concentrations (ug L") and ion ratios
                       Variable                  Const.         Factor 1        Factor 2
                       Cl-                          28+11           52+8          167+3
                       Na    +                      23+14           15+10         149+4
                       Mg    2+                     -6+1            21+1           19+1
                       Ca    2+                    -13+6          106+4            30+2
                       S04   2-                    234+62         1769+44          87+20
                       N 03-                       101+28         887+20           88+9
                       NH4+                        -27+8          204+6             6+2
                       Equivalent ratios
                       NO    3-/XSO42-                            0.39+0.01       1.38+0.56
                       NH4 /(N03'+XS04                            0.22+0.01       0.14+0.06
                Notes: At site NCb several high Ca     2+ concentrations were not correlated with the factors and
                were not included in defining them. At both sites K+ generally was not strongly correlated with
                the factors and was not included. xS04       2- is excess sulfate over 0.25 x Na+ (weight), that
                expected from sea salt. Ion ratios are given as chemical equivalents (+ and - charges).







                                        Table 5. Examples of Factor Analysis of Ion Concentrations in
                                                 Apalachicola River at Chattahoochee

                    A. Factor analysis with 11 variables, 6 significant factors
                                                           Factor loadings (correlation coefficients)
                    Var.       Factor I            Factor 2            Factor 3           Factor 4           Factor 5           Factor 6
                    Cl-               0.78               0.32                0.16                0.12             -0.07                0.05
                    Na@               0.89               0.25               -0.18              -0.05              -0.03                0.00
                    Mg     2+         0.64               0.65               -0.17                0.03             -0.01                -0.00
                    so     42-        0.85               0.06                0.22              -0.15              -0.05                0.16
                    NO     3'         0.08               -0.02               0.98              -0.02               0.13                0.04
                    K+                0.90               -0.08               0.03                0.00              0.09                0.07
                    Ca     2-+        0.09               0.98                0.02                0.06             -0.03                0.05
                    Hardness          0.14               0.98               -0.00                0.06             -0.03                0.05
                    OrgN              0.14               0.08                0.05                0.07             -0.02                0.98
                    NH +              -004               0.10               -0.02                0.99             -0.01                0.07
                           43-
                    PO     4          -0.02              -0.04               0.12              -0.01               0.99                -0.02

                    B. Factor analysis with 9            variables, 4 significant factors
                                                           Factor loadings (correlation coefficients)
                    Variable                       Factor 1            Factor 2           r1actor 3          Factor 4
                    Cl'                                  0.76                0.37                0.19              0..07
                    Na'                                  0.89                0.27              -0.05               0.01
                    Mg     2+                            0.62                0.53              -0.21               0.07
                    SO42-                                0.82                0.09                0.23              0.22
                    NO     3-                            0.11               -0.08                0.97              0.04
                    K'                                   0.86               -0.18                0.02              0.05
                    Ca     2+                            0.08                0.98              -0.03               0.03
                    Hardness (CaCO.)                     0.14                0.98              -0.04               0.04
                    OrgN                                 0.14                0.06                0.04              0.98

                    C. Factor analysis         with 8    variables, 3 significant factors
                                                           Factor loadings (correlation coefficients)
                    Variable                                Factor 1                      Factor 2                    Factor 3
                    Ci-                                            0.77                          0.30                        0.24
                    Na'                                            0.011                         0.16                       -0.01
                    Mg     2+                                      0.67                          0.45                       -0.24
                    S04    2-                                      0.76                          0.10                        0.36
                    N03-                                           0.14                          0.02                        0. 9 5
                    K'                                             0.83                        -0.31                         0.09
                    Ca     2+                                      0.07                          0.98                        0.05
                    Hardness (CaC03)                               0.13                          0.98                        0.02
                    Variance explained, 84%                       40%                          29%                          15%
                                                           Factor concentrations (ug           L-1) and ion ratios
                    Variable               Const.           Factor I                      Factor 2                    Factor 3
                    Cl'                    -823+225            3936+188                      0112+114                       48+7
                    Na+                    -1492+219           5932+183                      650+111                        -3+7
                    Mg     2+                185+46             665+38                       270+23                        -10+2
                    so     42-             -2916+475           7717+397                      630+241                      143+16
                    NO     3-                385+60             387+50                         35+31                       101+2
                    K'                       550-4-47           974+40                       -222-4-.24                      4+2
                    Ca     2+              1194+241            1046+202                     9252+122                        28+8
                    (CaC03)                3977 +49            5201+410                   24152+249                         37+16
                    Equivalent ratios
                    NO     3'/xS042-                           0.048+0.007                 0.058+0.059                  0.543+0.059

                    Factor identification                      Aged rain               Ground water                     Fresh rain









                     Table 6.    Comparison of groundwater component composition in the
                             Apalachicola River with well water in northwest Florida counties
                                              (N = number of data averaged)


                                                     River              N          Well              N

              Ca 2+ + std error (mg L-)               9.94+0.15       141          36.95+0.97      125
              Hardness ï¿½ std error (mg L")           26.08+0.30       141         114.97+5.42       37
                     (CaC03)









                     Table 7. Comparison of results calculated from U.S.G.S. Apalachicola
                             River data (June 1979 to May 1980) with published report
                             [Mattraw and Elder, 1984)


                                                                           U. S. G. S.
                                                     Report        Median      Average+Std error
              Flowrate (kM3  yr")                    24.13          24.80          27.98+3.02

              Organic and inorganic nitrogen         82.28          85.19          96.16+8.93
                output, kilotons N03- yr













                                                                              Week I   prpcipit--,tior, at
                                                                              FlorA Cu-Iricy HH"U' site

                                                                                                    ..............
                               240                         .......     ...............................          ..............  ..................

                         E
                         E     2W  -    ....................... ......................... ...................................................................... ........................

                                                                                       .... .            ...... . ...................
                               160      ....................... .......................... ............                                ........
                         0


                                                                             ......... ....  .......................I.. ................... .........  ............
                               In


                               80       ..... ... . ................. ..                     ........ ........ ..    .............. ........ ...............


                                                                                                                                         ..........
                               40
                                                                                                                                   ... ... . ...
                                       84               85               86               1117                rj,..             r2              90
                                                                                         Year
                                                                                                                            Fig.   1
                                                                         Factor I sea s-,ffl collicPritration it
                                                                              Florida (kincy IMP site

                                                      .......... ........ ...... ........ ............... ...................:.......... .......... I .... .........................




                                                                                                .................. ..............  ........
                               5.5                                       ... ....       ......



                               3.5  . ........................... ..... ................ .......................................... ............ .. .......




                                                                            .... . ............... .......... ....................   ...........
                                                                                                                I!
                                                                                                                ke   7, , j
                                                                                                                       r
                                                                               ...... ....          .......   ................................ ......
                               0.5                    .......................
                                       84               85               8@1               Of
                                                                                         Year
                                                                                                                           Fig.   2









                                                                               Factor I ,ii         i@p,:,:ition at
                                                                                  Florija N@inry Wl'? iite

                                            ........................           . . . . . .            -  -                 ,  ,     I........ .........
                                                              ...................................  ...............:................... .................


                                    2M      .......................                                                ....................... ......... ............

                                            ................I ...... .......... ............ ......  *",: ............................. ....... .........  ............


                                    130 . .............................................. .. .................................................................... .........  ............


                                    80  . .......  ................. ........ .......  .............. .......................I........................ ......


                                            .... . .........                             .......    ......              ................I... ..  ..........
                                                                                           Ali
                                                                                       Iwo          1,4 40WJ 1,
                                          -.1 .................. ...................                ..........  ............. .............r ........
                                    -20 @ I I I I ; I , ,                                           , I   , I       . .
                                          84                  85               86                                                                     90
                                                                                                    Ypar
                                                                                                                              Fig.   3
                                                                               Factor 2 arid rain   dep ns I t i on at
                                                                                  Florida Quincy    HOP site

                                                                               . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
                                    190 . ................... ...................                                    ............... ..... .........  .........


                             L
                                    IR  . ..........................  ........ ........................ .................... ...... ....... .........

                             x
                                    lie     ..... ......................................................  ............. ................................ - ..............

                                    70    .........  .................I....... ............ .............  ....... .......................I.......... ........................ -_-

                             L
                                                                      .. .......... ......... ..                   .. .....
                                            .... . ....... )-x  ......
                                    yj


                             +
                                                   ..........        ........ ........... I ... ....... ....................... ................
                                          84                  85               26                                                                     90
                             14                                                                     YT--,Lr
                             0                                                                                                  Fig. 4
                                                                               Factor   acid        rain dcpnlif ion at
                                                                                  Florida Qvinry 11H-!.'P site
                                    2N  . ................... ................... ......................  ....................................I.......  ...............
                                                                                                                                           .............




                                    160 . ............................................  ..................................................... ............. ......... ........  ..............




                                            ................. ......I....... ...............                                               . .....
                                                                                                    ............. .........





                                                                      ......................... . .... ....................         ........  .............-
                                    40



                                                  .......  .... ............   .......................:........................ .... .... .
                                    -20                                                                              .... . ........... .......................
                                          84                                   66                                  K                                  AA
                                                                                                    y er
                                                                                                                                Fig. 5






































                                                                            kalachicola Rl-@*r f1r.-Ij rate



                                12




                                             . . . . . . . . . .. . . . .. . . . . . . . . . . . . . . ... . . . . . . . . . . . . . . . . . . . . . ... . . . . .. . . . . . . . . .... . . . . .. . . . . .. . . . ... . . . . . . . . . . . . .





                                                                         ............
                                               .................... ............... .......... .......         ......... .......  ..........





                                    . ......... .......... ..... .... .... ...              ... . ...                                     ... ..... ..
                                                                                                           .............. ........  ............


                                               ..........;...... .... ... ... .... ...                      ......... . ..           ................


                                 2
                                                           i.... ......

                                                                                                                                     ..........


                                       65 66 VP '-S 69 70 71 72 7 74 75 ?-"- 71)                          'M 2,2 E-.'7 S-4    1-6 -,7 C-3 19
                                                                                                                                        1.
                                                                                          YeAT.                            Fig.   6








                                                                                                                                 kp a I ar h i  o 1 a  RMr f-vf-,-r I
                                                                                                                                             r
                                                                                                                                                 i n r r! il, pritr--@ @ i on
                                                                                                                                               ..       A.




                                                                     ...........                                                                ............ ...........  :............ ............                .................



                                                                                                                                                                                           ..............
                                           V              6                                                                                  .............
                                                                                                                                                                               it i        :I A f@@
                                                                                                                                                           . ... ..                        IT                  ...........
                                                          4
                                                                                                                                               J i

                                                                                                                     ..........  I                                                         I...... ...
                                                          2  - .                 . .............



                                                                                                                                                                                                                           ...................
                                                                  65    66     67     68 6F 70            71 72 73 74 75 76 771 '72 7? 80 81 C82 93                                                84 85         86 87         80" 87 90
                                                                                                                                                      Ye.ar
                                                                                                                                                                                                            Fig. 7
                                                                                                                                 Apalachirol--@                    f4cfor 2



                                                                                                                                                                                                                                  ...............



                                                                                                                                                           ..........   .........  ....... ........... ............
                                                          5  -- --------                 ............        .................

                                                          4                                                                      ......                                       ......       ..... .......   ......



                                                                                                                                                                                                              ... .....      .........


                                                                                          .....    .... ... I                                         ... . ...             ..... ...      ....... ......................

                                                                  .., ...........                                                                                                           ...........................   :...... ......:

                                                                  65 66 6? 68 6? 70 21 r2 73                                     '114 75 76 T, 71.1 ?rl 8111 101, 8"" V 1214 @C'15 rcl@- 8-7 88, K %
                                                                                                                                                      Year
                                                                                                                                                                                                             Fig.       8
                                                                                                                                 Apilichicol.i Rive farfpr
                                                                                                                                   4re-A rain cro:wfraicc

                                                      3.9
                                                                                                                      . ........................ .. ........ .                                                                             .......


                                                      2.9             ..........................                                                                                           ......*                   ........


                                                                                                                                                                     .... ...... ...



                                       0              0.9         .......... ... ...


                                                                                                                                                                      Al


                                                                                                                                          ...........                                                 ...........  I         ..................
                                                                                                                      ...........I
                                                                                                            IV

















































                                       a            -2.1                                 ...........                  ...........        .......................                .......    .................          .........................
                                                                  65    66     67 @2 69 70 71 72 73 74 ?5 76                                          7? 70 72 K' 01 62                      0 84 85 086' 87 88 89 90
                                                                                                                                                      Ypir
                                                                                                                                                                                                          Fig. 9









                                                                                                                                                           Five factor I
                                                                                                                                                aqed rain flux

                                                               5                                     ....... ...............


                                                               4   . .........           ................... ....          .........                                     ..............   ....................................
                                                                                                                                                                                                                                    ...........


                                                               3          ...........         ...... :                           ...........         ...........                                                       ..........
                                                                                                                                                                              ..................          ...........
                                                                                                                                                                         -lit
                                                               2  . ........      .......                                ..........                                             ..........          .... ...           .................


                                                                                                                                 d                   Al                          ... ....




                                                                                                                                                                                                   ..........   .... ........
                                                                                                                                                                                                                ILL"   a."
                                                                              U          67  68      69 -(Vj      71     72 7")         74 75'                             80     81 `2
                                                                       ;j                                                                                                  C'.           C.      "'     84 rc'-j V        87      80 89        5' 0
                                                                                                                                                           Ypar
                                                                                                                                                                                                                Fig.      10
                                                                                                                                        Hpalachico].-i. Riv-ir               or 2
                                                                                                                                                ground vater flux

                                                               2                                                                                           .......       .. ...... ..........



                                                                                                                                                           .............                                        ...............................
                                                                                                     ..................  ...........                 .......             . .......................



                                                                                                                                                                                 ...............                ..... ................
                                                           1.2             ...........   ....        .........................................       .......             . ......


                                                           0.8    . .........     .....  .. ...................                         .. ....
                                                                                                                                        J1





                                                                                                                  .........................     .....................    ................           ........... .....................   .......
                                                                        I-, I     ...    1'- 1; "*.",j*.,.",,;7'*t,T, I  '',1; , i -0           1, - 1                   1; .1,

                                                                                                                         1., 17 -M
                                                                                                                                                                                                        C..
                                                                      65 6-A 6?             610"     617" 70      ?i     z  i           i It               7-7   7--i    7"i      -P 1                  84

                                                                                                                                                                 r
                                                                                                                                                                                                                Fig.
                                                                                                                                                                 j                 7
                                                                                                                                        r       .. .I.- @  *     a
                                                                                                                                                                         T
                                                                                                                                                           r.-@Jr, Hu

                                                                                         ...............                                ......  .......    ;,-   ....................... .    -         .1-j.-       ......
                                                               12                        ...........                     . .. ..................     ...... ...........        .......              ........... ................................

                                                                                                     ...........  ................      ............ ....                .... ......                      .............................
                                                                                                                                                                                                                                       ...........


                                                                  . .............             ...... t      ......I.......       .....          ..... .......                                               ...........              ......


                                                                                                     ................

                                                               4       ........   .....  .... ......                                                                                                                                       ........

                                                                       ...............                                                  . ... . .
                                                               2

                                                                                                                                                           T
                                                                                                                                                                                   tA
                                                                                                                                                                                              4


































                                                                                                                         ....... .....................                   .......................................       .................
                                                                                                                  ........................      I...........     ......  :...................      .......      ....... ......

                                                                      65 66              67 6ro' 69 ?0 71 72 73 N 7.5                                      77 7@- 717' E-0 or-I EO-21 IK 84 @5 0-30: 2.7                          'E."o [`7@ 5-

                                                                                                                                                                                                                Fig. 12









                           Acid Deposition Relationships in Florida and Southeastern U.S.A.


                                            Jin-You Liang and John W. Winchester
                                       Dept. of Oceanography, Florida State University
                                                     Tallahassee, FL 32306


                                                             Abstract

                       The general uniformity of yearly average nitrate and sulfate deposition fluxes from acid
               air pollution over southeastern U.S.A. obscures possibly important differences on a smaller
               geographic scale and on seasonal or shorter time scales. A statistical analysis of weekly
               NADP wet chemical data from 18 sites over most of an eight state region has been carried
               out. Groupings of sites are identified that indicate uniformity over a state-wide scale, but not
               larger, in correlations based on short term variability in acid air pollution deposition fluxes.
               Thus, groups of sites within this geographic scale could serve as predictors of deposition on
               a shorter time scale than is possible based on long term averages of deposition data. For
               deposition to the watershed of the Apalachicola River, both meteorological conditions and
               transport from pollution sources appear to control deposition fluxes of nitrate and sulfate acid
               air pollutants.


                                                         1. Introduction

                       Rainfall chemistry data from the National Acid Deposition Program can be examined
               statistically to determine correlations between sites in the magnitudes of their acid air pollutant
               deposition fluxes. The finding of correlations among groups of sites can facilitate prediction
               at any location within the area of a group of sites.. By comparing correlations in deposition
               for acid pollutants with those for sea salt or just rainfall, a judgement can be made about the
               factors that may influence the deposition, for instance meteorological factors that lead to rain
               or sources of emissions that are scavenged by the rain.

                       In order to improve prediction of nitrate from acid deposition to the watershed of the
               Apalachicola River, a statistical comparison of sites in southeastern U.S.A. was carried out.
               NADP operated 30 sites in eight southeastern states, shown in Table 1 and Fig. 1, the earliest
               reporting data starting in 1978. As long term averages, the concentrations and deposition
               fluxes of nitrate and the ratios of nitrate to sulfate do not vary greatly from site to site.
               Although there is a tendency for sites near urban or industrial centers to be higher than further
               away, comparing long term averages does not give insights concerning how adjacent sites may
               be correlated for samples collected concurrently. That is, possible similarities in seasonal or
               shorter term deposition variations at different sites in the region are not revealed by comparing
               long term averages. Yet, such similarities may aid in predicting deposition and in judging the
               relative influences of meteorological and pollution source processes on deposition fluxes.

                       With special attention to acid deposition in Florida, 18 NADP sites in seven states were
               compared statistically in a procedure based on factor analysis. The sites, at locations shown
               in Fig. 1, are listed in Tables 2, 3, and 4. For these sites NADP reported weekly rainfall
               amounts and chemical concentration measurements for at least 300 weeks (6 years) to mid
               1989. Of these weeks, an average + standard deviation of 66 + 7 % had data reported. The
               remaining weeks of missing data may have been weeks without rain or with operational
               problems at the sites. Although there were no weeks when all 18 sites reported data, yet for
               most weeks data were reported for the great majority of sites. This data set was thus suitable
               for comparison of deposition fluxes between sites.











                                                                  2




                                                            2. Methods

                        In order to examine in detail the relationships between sites, we have employed factor
                analysis in a procedure analogous to that used for resolving principal components of chemical
                constituents at any one site [Winchester and Fu, 1990]. However, the present procedure,
                based on a data matrix of variables vs. weeks of data, uses sites rather than chemical
                constituents as the variables, so that the fluxes of a chosen chemical variable are compared
                over the 18 sites in 300 weeks of data record. Groupings of sites into principal components
                express their high degree of correlation in short term variability.

                        Our procedure contains certain improvements over the only other similar analysis of wet
                deposition monitoring data known to us [Eder, 1989]. The first improvement is a way to avoid
                the assumption made by Eder that all sulfate is an acid air pollutant, in view of some sulfate
                originating with sea salt. In our procedure we perform an initial factor analysis of the chemical
                data at each site to resolve its principal components and then select one of these (e.g. sea
                salt or acid pollution) for comparison between sites in the 18 site region by a second factor
                analysis.   In this way, the data for two or more chemical variables are pooled for greater
                precision of data analysis, and those that may be derived from different sources (e.g. sulfate
                from sea  salt and pollution) are properly apportioned between components. The factor scores
                from the  initial analysis are used as input data for the second analysis.

                        Another is our use of deposition flux (concentration x rainfall amount) instead of
                concentration in rain water as input data for the.analysis as was done by Eder. Moreover,
                noting their log-normal distributions, deposition data were logarithmically transformed for the
                factor analysis of sites vs. weeks of measurements (though not for the initial factor analysis
                of chemical data at each site, since normal and log-normal distributions described the data
                equally well).

                        Still another improvement is devising a procedure that allows use of all weeks of data,
                including weeks when some sites did not report. Eder pooled his weekly data into months in
                order to increase the percentage of time that all sites in the network reported data, causing
                a 4-fold reduction in length of data record. In our procedure we introduced a pseudo detection
                limit for non-reporting weeks (instead of zero deposition which would preclude logarithmic
                transformation), choosing a value below the lowest finite data reported at the sites.

                        In the procedure we carried out separate analyses of three kinds of data:

                        First, the amount of weekly precipitation at each site was examined in order to identify
                groups of sites that may vary in similar ways. No initial factor analysis was needed, since the
                weekly precipitation amounts could be input directly to the factor analysis of 18 site data.

                        Second, by an initial factor analysis of data at each site, a sea salt component was
                identified. The factor scores for this component were entered into a data array of 18 sites vs.
                the 300 weeks of record, and a second factor analysis was performed to identify groups of
                correlated sites in sea salt deposition. It should be noted that a model is assumed in which
                correlations between groups are absent, i.e. a linear "mixing" model of independently varying
                components. Although all sites may to some degree be intercorrelated, the procedure resolves
                groups of the most highly correlated sites.

                        Third, the same procedure was applied to a principal component from the initial factor











                                                                3

                analysis that resembled acid rain pollutants (mainly nitrate and sulfate), leading by the second
                factor analysis to identifying groups of correlated sites in acid pollution deposition fluxes.

                       The first factor analysis of deposition data at each site included a dummy sample with
                zero deposition for each constituent (variable). The data were standardized by subtracting the
                mean and dividing by the standard deviation of each variable, then factor analysis was carried
                out with varimax rotation. The factor scores, having a zero mean for each variable, were
                increased to "absolute" factor   scores by subtracting the (negative) score for the dummy
                sample. These absolute factor    scores were used as input to the second factor analysis. In
                this case, missing data were     replaced by a pseudo detection limit, and all scores were
                reexpressed as equivalent Na     or N03 fluxes (for sea salt and acid pollution components,
                respectively), before logarithmic transformation for the factor analysis.

                       By carrying out these     three separate analyses of precipitation amount, sea salt
                deposition, and acid pollution deposition, we are better able to judge whether deposition may
                be governed mainly by meteorological conditions that lead to rainfall or whether the
                characteristics of sources, acidic pollution or natural sea salt, also may contribute to the
                regional variation of deposition fluxes.


                                                           3. Results

                       Tables 2, 3, and 4 present factor loadings for three separate factor analyses of
                precipitation, sea salt, and acid pollution deposition fluxes at the 18 NADP sites. Calculations
                for various numbers of factors were carried out, but those for six factors were judged to be
                the most informative for indicating groups of highly correlated sites. For each analysis, the
                factors (principal components) are arranged in decreasing order (F1 to 176) in explaining
                variance. Thus, F1 represents a component that is highly variable in deposition flux, from very
                high to very low over the 300 weeks of data. In all three analyses F1 is a group of sites in
                North Carolina, suggesting meteorological control in this state situated between coastal and
                continental weather influences. In contrast, sites in peninsular Florida are assigned to lower
                variance factors, suggesting less variable meteorological conditions in its relatively more
                maritime climate.

                       Of special interest for acid pollution deposition the Apalachicola River watershed are
                sites in Georgia, Alabama, and Mississippi. To the extent that they are well correlated they
                may, as a group, serve as predictors of short term variability in deposition anywhere in their
                region, not merely of a long term average. For acid deposition fluxes Table 4 shows them
                mainly assigned to factor F2, quite highly variable and rather well correlated, so that weeks
                of high deposition fluxes at one are likely to be high at the others as well. The lowest
                loadings of sites in this group, Ga b and Ms a, lie at the eastern and western extremities of
                their region as shown in Fig. 1.

                       Deposition of sea salt also shows high correlation among this group of sites (F2 in
                Table 3). However, for precipitation itself (the amount of rainfall) the correlation between sites
                is much weaker (F2, F3, and F4 in Table 2).. This distinction between fluxes of precipitation
                and of the sea salt and acid air pollutants scavenged by precipitation indicates that the
                deposition fluxes cannot be predicted by rainfall alone. Instead, the concentrations of these
                chemical substances in air must also be important. Since Tables 3 and 4 show similar factor
                assignments for sea salt and acid pollution, both may be distributed over the region after
                transport from their respective sources. Yet this region appears to comprise only parts of two
                states rather than the southeast as a whole.











                                                                    4




                                                            4. Discussion

                        Comparison of long term average deposition fluxes of nitrate and sulfate pollution shows
                little variation, although higher than average fluxes are found near urban and industrial centers.
                But the general uniformity of fluxes over the southeastern U.S.A. obscures possibly important
                differences on a smaller geographic scale and on seasonal or shorter time scales. The results
                .of the present statistical comparison of wet deposition fluxes from weekly NADP data indicates
                considerable correlation between sites on a state-wide scale. For estimating likely deposition
                at a specific locality, for instance of acid air pollution nitrate and sulfate within the watershed
                of the Apalachicola River system, a group of well correlated sites mainly in western Georgia
                and Alabama can serve as better predictors than sites over a larger region. However, it is
                equally clear that smaller scale geographic differences in deposition fluxes within this 2-state
                region cannot be discerned based on 6 years of weekly NADP wet deposition measurements.


                        The controlling influences on deposition fluxes may be both meteorological and
                chemical, i.e. physical processes leading to rainfall and the locations of pollution sources and
                transport pathways of their emissions. By comparing similar statistical analys        es of rainfall, sea
                salt deposition, and acid pollution deposition, a judgement can be reached that both influences
                are important for pollution deposition to the watershed of the Apalachicola River system.


                                                            5. References
                Eder B. [1989]. A principal component analysis of S04         2- precipitation concentrations over the
                        eastern United States. Atmos. Environ. 23, 2739-2750.

                Winchester J.W. and Fu Ji-Meng [1990]. Atmospheric Deposition of Nitrate and Its Transport
                        to the Apalachicola Bay Estuary in Florida. (This report, Paper 1).





















                                   .9                   b      b
                                     I L    b     0 H
                                                       r,
                                            I N  d
                                                        WV    b
                                      h    d         C  -b! V;d
                                      b
                              hio       ci,-@'f b.
                         b                   K Y        e
                                   b                    *@r- N C
                                                    b/  . 0
                                             TU         I    .. d
                                       'd
                                                         S C
                               A A            b            b
                              d-     Co
                                 PbI        AL      GA
                               -------iM S                b
                               0     a   .11!a
                         d          b     I         C
                               LA    C.Oll
                                                         FL


                                                          e
                               0  100 200 300 400  Miles
                               j   i   i  i
                               0  161 32-2 483 644 Kilomelers C



                                                                               a





            Fig. 1. NADP sites in the southeastern U.S.A. Of these, 18 with data extending over at least
                 300 weeks (6 years) were selected for data analysis.









                               Table 1. Nitrate and sulfate concentration and deposition averages
                                              + standard error (68% confidence interval)

                         Site             NO,- conc.               NO,- wet dep.             N03-/SO4   2-
                         1. D.            m_q L-1                  kq ha-1 yr"              wt. ratio

                         FL    c         0.643+.037               4.23+0.36                0.577+.025
                         FL    e         0.988+.072               6.40+0.80                0.707+.031
                         FL    d         0.931+.057               6.34+0.59                0.559+.025
                         FL    a         1.001+.046               7.44+0.42                0.597+.017
                         FL    f         11.016+.079              6.76+0.65                0.632+.023

                         GA b            1.311+.085               6.85+0.44                0.659+.024
                         GA c            0.984+.069               5.90+0.42                0.665+.027
                         GA    a         1.161+.052               7.49+0.39                0.530+.013


                         AL    b         1.167+.098               6.44+0.43                0.474+.017
                         AL    a         1.033+.061               7.15+0.43                0.598+.01


                         MS    a         1.165+.051             10-30+0.52                 0.596+.014
                         IVIS d
                         MS    c         1.118+.072               8.41+0.57                0.745+.029
                         MS    b         1.163+.077               7.43+0.52                0.713+.035


                         LA    c         1.140+.070             10.95+0.65                 0.693+.022
                         LA    a         1.230+.066             10.14+0.69                 0.686+.021
                         LA    b         1.221+.073               7.91+0.56                0.730+.022


                         SC    b         1.034+.070               5.33+0.49                0.577+.029
                         SC    a         1.579+.075             10.81+0.60                 0.575+.015


                         NC    a         1.491+.073             10.08+0.47                 0.602+.014
                         NC    d         1.408+.067               8.73+0.42                0.569+.010
                         NC    e         1.618+.074               9,12+0.42                0.627+.017
                         NC    i         1.318+.085               9.59+0.67                0.609+.017
                         NC    c         1.689+.065             11.56+0.55                 0.589+.016
                         NC    j         0.986+.184               5.08+0.52                0,470+.021
                         NC    b         1.107+.045             10.90-i-0.46               0.541+.011


                         TN    b         1.254+.061               8.32+0.43                0.593+.016
                         TN    a         1.580+.063             11.18+0.48                 0.529+.024
                         TN    c         1.212+.073               8.91+0.64                0.631+.052
                         TN    d         1.033+.061               7.50+0.54                0.693+.028









                                    Table 2. Factor loadings based on weekly rainfall amount
                                                 (73.2 % of total variance explained)


                 Site                                                      Factor
                 I.D.,            F1             F2               F3               F4              F5              F6


                 NC    a        0.85
                 NC    c        0.73                                            (0.37)
                 NC    d        0.81
                 NC    e        0.85
                 NC    i        0.77           (0.33)
                 AL    a                       (0.31)            0,57            0.51
                 GA    a                                                                                          0.99
                 GA c                           0.79
                 MS    a                                         0.50            0.54

                 GA b                           0.80
                 LA    c                                         0.83
                 LA    a                                         0.85
                 FL d                                                                            0.69
                 FL    a                        0.67                                             0.42
                 FL    e                                                                         0.72
                 TN    b                                                         0.84
                 TN    a        0.43                                             0.67
                 FL    c                                                                         0.82


                 Var. %        20.8            12.5            12.0             11.3            10.9              5.7


                 Note: Factor loadings are correlation coefficients between sites and factors. Lo             adings >0.4
                         are most significant, 0.3-0.4 may be marginally significant (indicated by parentheses)
                         and <0.3 are least significant and are indicated by blanks in the table.








                       Table 3. Factor loadings based on weekly deposition flux of sea salt component
                                                 (62.3 % of total variance explained)


                 Site                                                      Factor
                 I.D.             F1              F2               F3             F4              F5              F6


                 NC    a        0.76
                 NC    c        0.64            (0.31)
                 NC    d        0.81
                 NC    e        0.80

                 NC    i        0.76
                 AL    a                        0.44            0.46            (0.34)
                 GA    a                        0.50                            (0.30)
                 GA    c                        0.76
                 MS    a                        (0.38)          0.56
                 GA    b                        0.69
                 LA    c                        (0.31)          0.66
                 LA    a                                        0.85
                 FIL d                                                                                           0.63
                 FIL   a                        0.48                                            0.56
                 FIL   e                                                                        0.77
                 TN    b                                                        0.81
                 TN    a                                                        0.78
                 FL    c                                                                                        0.82


                 Var. %       16.8            11.7             10.5             9.4             7.2             6.8


                 Note: See caption to Table 2.









                      Table 4. Factor loadings based on weekly deposition flux of acid rain component
                                                (61.6 % of total variance explained)


                Site                                                    Factor
                I.D.            F1              F2               F3            F4              F5              F6


                NC    a        0.77

                NC    c        0.67

                NC    d        0.74

                NC    e        0.71

                NC    i        0.72
                AL    a                       0.69           (0.38)
                GA    a                       0.65
                GA c                          0.64                           (0.35)
                MS    a                       0.52            0.46
                .GA   b       (0.36)          0.47
                LA c                                          0.79
                LA    a                                       0.78
                FL    d'                                                      0.74

                FL    a                                                       0.74
                FL.e                                                          0.53                           0.45
                TN b                                                                          0.78
                TN a          (0.33)                                                          0.66
                FL c                                                                                         0.88



                Var. %        16.8           11.0             9.8             8.9             8.3            6.7


                Note: See     caption to Table 2.









                                   Comparison of Acid Deposition and Surface Transport

                                              in Three Watersheds of North Florida



                                               Ji-Meng Fu and John W. Winchester
                                         Dept. of Oceanography, Florida State University
                                                       Tallahassee, FL 32306



                                                                Abstract

                        Comparison of sulfate, different forms of nitrogen, and other chemical compositions
                between atmospheric deposition and surface transport has been made for the Apalachicola,
                Sopchoppy, and Ochlockonee Rivers in north Florida by mass balance and multivariate
                statistical methods. The results show that the chemical compositions of all rivers, in general,
                can be represented as a mixture of three groups of dissolved constituents. One, containing
                nitrogen and sulfate, resembles the composition of rain water; another, containing calcium,
                resembles ground water; and a third, containing chloride and sodium, resembles sea salt.
                Total mass flow of nitrogen in all three rivers agrees well with the average atmospheric
                deposition to their watersheds, suggesting that the atmosphere is the major source of nitrogen
                to their watersheds. However, for Cl-, Na', Mg2,, Ca       2, , K', P 04 3-, the calculated atmospheric
                contribution is much less than their river fluxes, implying that surface processes, including
                urban, agricultural, and industrial releases and weathering of soil, are dominant. The three
                rivers differ considerably in types of watersheds.          The finding that atmospheric nitrogen
                deposition fluxes agree well with transport of nitrogen by river flow and that river nitrate is
                largely correlated with non-seasalt sulfate implies that on the average the watersheds are in
                a quasi steady state and that additional surface sources or sinks are relatively small.
                Moreover, the high relative river flow of organic nitrogen, which is not present in rain water,
                suggests that it may be a watershed transformation product of atmospheric inorganic nitrogen.


                                                            1. Introduction

                        The present study represents an extension of our previous analysis of Apalachicola
                River composition data [Winchester and Fu, 1990]. The results from that single watershed
                system leave unresolved a question whether surface sources of nitrate or other nitrogen
                species could be large, but by coincidence a mass balance agreement between atmospheric
                deposition and river flux could still be achieved.         Therefore, we have undertaken similar
                analyses of two additional north Florida rivers that have very different watershed
                characteristics, the Sopchoppy, that drains a wetland without agricultural, urban, or industrial
                activity, and the Ochlockonee upstream of Lake Talquin, where agricultural activity may be
                present. Although we have not yet carried out a survey of various kinds of human activity in
                these or the Apalachicola River watersheds, qualitatively they differ considerably, and a
                comparison may indicate whether these differences could lead to observable differences in
                their flows of nitrogen compounds toward estuaries of the Gulf of Mexico.


                                                             2. Methods

                        Two methods have been used for comparison of the three watersheds, a mass balance
                between atmospheric deposition and river flow and resolution of principal components by factor
                analysis according to a linear mixing model. In our previous study of the Apalachicola River
                system, the first method indicated that atmospheric deposition was sufficiently large to account











                                                                2

               for nitrogen in the river, and the second indicated that most river nitrate was correlated with
               sulfate, suggesting that both are principally of atmospheric origin. We have now applied these
               two methods to two additional rivers.

                       In all three rivers, mainly three chemical forms of nitrogen have been routinely
               measured several times per year for more than 20 years by the U.S. Geological Survey
               (USGS): N03', NH4+1 and organic nitrogen. The flows of these and other chemical species
               can be compared with the record of atmospheric deposition at sites in or near the watersheds,
               especially at five sampling sites of the National Atmospheric Deposition Program (NADP) that
               have operated mainly during the 1980's. The NADP data show that N03-and NI-14            + are the
               major forms of nitrogen in atmospheric wet deposition, but the river data show substantial
               amounts of organic nitrogen, usually in excess of inorganic nitrogen concentrations. From the
               river and atmospheric data the deposition and river surface transport fluxes can be calculated:
                       River surface transport    ion concentration (mg L-)
                                                     x river flow (m3 sec-1)
                              Wet deposition     ion concentration (mg L-)
                                                     x measured precipitation (mm)
                                                     x entire basin area (km  2

                       The methods used for factor analysis of both rain water and river water have been
               described previously (Winchester and Fu, 19901. Factors (principal components) are resolved
               into groups of measured chemical variables that are highly correlated. These groups may be
               recognized as representing components in the atmosphere or surface water that have been
               mixed in varying proportions in the different samples but otherwise are relatively constant in
               their individual compositions. In the Apalachicola River we recognized the three significant
               components to represent ground water (high in Ca), aged rain water (containing sulfate and
               smaller amounts of nitrate than measured in rain water), and relatively fresh rain water (with
               nitrate and sulfate in proportions closer to that in rain water).


                                                          3. Results

                       In Table 1, mass flows of ions in two rivers, Sopchoppy and Ochlockonee, are
               compared with atmospheric deposition fluxes at the nearest NADP site.                 As for the
               Apalachicola River [Winchester and Fu, 1990], the first six ions show greater flows in river
               water than can be accounted for by atmospheric deposition, wet + dry estimated to be twice
               wet only. For S04'2    atmospheric deposition is similar to river flow and for NO.- and NH4+
               atmospheric deposition is much greater.

                       Table 2 shows the comparison of sulfate and forms of nitrogen for the three rivers more
               explicitly after conversion of metric kiloton to mole units. For sulfate, considering the standard
               errors of the mean values listed, no significant difference is seen between atmospheric
               deposition and river flow. For total nitrogen in all its chemical forms the same is true, with
               agreement well within a factor of 2 between atmospheric deposition and river flow. However,
               in all three rivers organic nitrogen greatly exceeds nitrate and ammonium ion concentrations,
               whereas in the atmosphere organic nitrogen is undetectable and therefore not routinely
               monitored by NADP. The mass balance suggests that much of the atmospheric input of
               inorganic nitrogen undergoes transformation to organic nitrogen in the watershed.

                       Further insights into relationships among species of nitrogen and other ions in the











                                                               3

               watershed can be gained from correlations revealed by factor analysis.          Tables 3 and 4
               present results for the Sopchoppy and Ochlockonee Rivers that may be compared with those
               of the Apalachicola [Winchester and Fu, 1990]. In each river three significant factors are found
               that account for most of the concentration of each ion and for most of overall data variance.
               These factors resemble those for the Apalachicola River and suggest that they represent
               mixing of ground water (high Ca), relative saline water (high Cl and Na), and rainwater (high
               sulfate and nitrate, though nitrate being lower than in rain water implies aging in the
               watershed).


                                                        4. Discussion

                      The three rivers show agreement in mass balance and factor analysis relationships that
               support our previous conclusion that river borne nitrogen can be accounted for largely by
               atmospheric deposition. They also show that organic nitrogen always exceeds inorganic
               forms. The temporal variation in the ratio organic nitrogen to total nitrogen in the Apalachicola
               River from 1970 through 1989 is shown in Fig. 1 to exhibit marked summer maxima. By
               factor analysis we find that organic nitrogen is not well correlated with inorganic nitrogen, as
               pointed out previously for the Apalachicola River, implying time delays or seasonal dependence
               in biochemical transformations that can remove correlations.

                      The most "natural" of the three rivers, the Sopchoppy, often has nitrate below detection
               limit, but factor analysis shows a ratio of river nitrate to excess non-seasalt sulfate of 0.042
               in the most sulfate-rich component, in good agreement with the Apalachicola. However, the
               Ochlockonee ratio is larger. Further study of specific differences between watersheds that
               could underlie these observations should be carried out.

                      This study has shown that a judgement can be made whether additional surface
               sources of nitrogen to the rivers is likely to be large compared to atmospheric deposition. The
               agreement among three rivers, having different watershed characteristics in mass balance and
               ionic correlations revealed by factor analysis, suggests that additional surface sources of
               nitrogen are likely to be small. However, a research program to measure their magnitudes
               directly, as well as to survey land use and other practices in the watersheds that may affect
               nitrogen transport to coastal estuaries in Florida, would be desirable.


                                                     5. Raference cited

               Winchester J.W. and Fu Ji-Meng [1990]. Atmospheric Deposition of Nitrate and Its Transport
                      to the Apalachicola Bay Estuary in Florida. (This report, Paper 1).








                Table 1.    Comparison of average ion transport in flow of Sopchoppy River, Wakulla County,
                        with wet depositon measured at Quincy, Florida, NADP site (FLf).
                        River transport     ion concentration (mg L") x measured water flow          (M3  sec-1).
                        Wet deposition        ion concentration (mg L") x measured precipitation (mm) x entire
                                basin area (kM2).
                        Units converted to metric kilotons of the ions per year.

                                         Sopchoppy              NADIP Wet       Ochlockonee             NADP Wet
                Ion                             River           Deposition              River           Deposition

                Cl-     Average                0.66            0.14                   11.2             1.59
                        +Std error            +0.08           +0.02                   +0.85            +.20
                        Kledian                0.28            0.07                   -6.3             @.80

                Na+     Average                0.27            0.08                    6.96            0.91
                        +Std error            +0.03           +0.01                   +0.51           +0.11
                        Dedian                 0.11            0.04                    4.00            0.45

                K+      Average                0.020           0.009                   1.51            0.10
                        +Std error            +0.002          +0.001                  +0.15           +0.02
                        Median                 0.007           0.004                   0.69            0.04

                Ca   2+ Average                0.66            0.024                   3.19            0.27
                        +Std error            +0.08           +0.003                  +0.22           +0.03
                        j@leclian              0.28            0.013                   2.06            0.15

                Mg   2+ Average                0.05            0.012                   1.30            0.13
                        +Std error            +0.005          +0.001                  +0.09           +0.02
                        Median                 0.03            0.007                   0.84            0.07
                P04  3- Average                0.008          <0.0040                  0.066          <0.044
                        +Std error            +0.002          +0.0004                 +0.008          +0.005
                        Dedian                 0.002          <0.0018                  0.043          <0.020
                S04  2- Average                1.03            0.32                    4.62            3.57
                        +Std error            +0.19           +0.03                   +0.55           +0.37
                        Median                 0.62            0.19                    2.14            2.15

                N03-    Average                0.008           0.18                    1.34            1.99
                        +Std error            +0.002          +0.02                   +0.12           +0.19
                        Median                 0.002           0.10                    1.01            1.16

                NH4  +  Average                0.006           0.029                   0.079           0.32
                        +Std error            +0.001          +0.004                  +0.008          +0.04
                        Median                 0.002           0.011                   0.046           0.12

                Org N   Average                0.12                                    0.68
                as N    +Std error            +0.02                                   +0.08
                        J@edian                0.04                                   -0.28









                  Table 2.      Transport of sulfate and forms of nitrogen in Apalachicola, Sopchoppy, and
                           Ochlockonee River flows compred to atmospheric deposition to their watersheds
                           (Units are 109 or     106 moles yr- ; total deposition = 2 x wet deposition)
                                                    N03-              N H4+            Org N            Total N           S04 2-
                  Apalachicola (109 moles yr-)
                           Wet Deposition
                                   Average         0.54             0.38                               0.92             0.71
                                   +Std err       +0.03            +0.04                             +0.05             +0.05
                                   Dedian         -0.38             0.20                               0.58             0.49

                           Total Deposition
                                   Average         1.07             0.75                               1.82             1.42
                                   .+Std err      +0.07            +0.07                             +0.10             +0.09
                                   Dedian         -0.76             0.41                               1.17             0.97

                           River Flux
                                   Average         0.42             0.066             0.73             1.22             1.20
                                   +Std err       +0.03            +0.012           +0.06            +0.07             .+0.08
                                   i@edian        -0.22             0.028             0.46             0.71             0.80
                  Sopchoppy (106 moles         yr-1)
                           Wet Deposition
                                   Average         2.90             1.61                               4.51             3.33
                                   +Std err       +11.11           +0.22                             +1.12             +0.31
                                   -@4edian       -1.61             0.61                               2.22             1.99

                           Total   Deposition
                                   Average         5.80             3.62                               9.02             6.66
                                   +Std err       +2.22            +0.44                             +2.24             +0.62
                                   Dedian         -3.22             1.22                             -4.44              3.98

                           River Flux
                                   Average         0.13             0.33              8.57             9-03            10.7
                                   +Std err       +0.03            +0.06            +11.43           +1.43             +11.98
                                   Dedian         -0.03             0.11            -2.86            -3.00              6.46
                  Ochlockonee      (106 moles   yr-)
                           Wet Deposition
                                   Average        32.1             17.8                              49.9              37.2
                                   +Std err       +3.06            +2.22                             +3.78             +3.85
                                   Median         18.7              6.67                             @5-4              @2.4

                           Total   Deposition
                                   Average        64.2             55.6                              99.8              74.4
                                   +Std err       +6.12            +4.44                             +7.56             +7.70
                                   Median         37.4             13.34                             50.8              44.8


                           River Flux
                                   Average        21.6              4.33            48.6             74.5              48.1
                                   +Std err       +1.94            +0.44            +5.71            +6.05             +5.73
                                   j@ledian       16.3             -2.56            [email protected]            38.9              -@2-3









                Table 3, Factor   Analysis of Ion Concentrations in Sopchoppy River, Florida,
                               with 8 Variables and 3 Significant Factors


                                             Factor loadings (correlation coefficients)
                Variable                             Factor 1               Factor 2               Factor 3


                cl-                                  -0.088                 0.92                   0.035
                Na'                                  0.60                   0.57                   0.018
                Mg   2+                              0.98                  -0.004                 -0.091
                Ca   2+                              0.97                  -0.02                  -0.10
                Hardness                             0.98                  -0.02                  -0.10
                N03-                                 0.082                  0.25                   0.75
                S04  2-                              -0.24                 -0.22                   0.78
                K+                                   0.81                   0.15                  -0-0005


                Variance explained, 81%                49%                     16%                    15%


                                   Factor concentrations (ug L-) and ion ratios     (equivalents)
                Variable         Const.         Factor 1               Factor 2               Factor 3


                Cl-                391+390         -101+36               4302+147                 59+54
                Na+                367+123         342+27                1314+110                 15+40
                Mg   2+              95+92        1164+20                 -21+82                 -161+30
                Ca   2+            242+941      11546+206               -1206+841              -1795+307
                Hardness          1210+2521     33762+552              -3341+2253              -5169+821
                N03-               -357+55           21+12               259+49                  291+18
                S04  2-           6998+1052     -1166+231               -4257+940               5391+343
                K+                    -3+30         103+6                  75+25                -0.1+9


                Ion equivalent ratios
                N03-/XS04  2-                   -0.013+0.008           -0.044+0.012            0.042+0.004









                Table 4.    Factor Analysis of Ion Concentrator ,,.,;th 8     Variables, 3 Sigi-,;ficant Factors in
                               Ochlockonee River.


                                            Factor loadings (correlation coefficients)
                Variable                             Factor 1               Factor 2               Factor 3


                Cl-                                  0.29                   0.91                   0.30
                Na'                                  0.36                   0.87                   0.32
                Mg   2+                              0.82                   0.36                   0.41
                Ca   2+                              0.90                   0.30                   0.30
                Hardness(CaCO,)                      0.87                   0.32                   0.35
                N03-                                 0.64                   0.27                   0.54
                S04  2-                              0.42                   0.35                   0.79
                K+                                   0.38                   0.35                   0.79


                Variance explained, 93%               40%                    28%                    25%


                                   Factor concentrations (ug L-) and ion ratios    (equivalents)
                Variable         Const.         Factor 1               Factor 2               Factor 3


                Cl-                 716+225       3224+79               7442+57                 8238+186
                Na+                -914+157       2904+54               5072+40                 6053+130
                Mg   2+              17+51         953+18                 300+13                1151+43
                Ca   2+             629+95        2605+32                 639+24                2105+79
                Hardness           1630+302      10427+104              2810+76                10088+250
                N03-                957+84        1065+214                326+156               2148+514
                S04  2-           -2289+482       1732+166              1052+121                7354+399
                K+                  506+60         250+21                 170+15                1252+49


                Ion equivalent ratios
                N03-/XS04  2-                     0.82+0.21             -1.17+0.82              0.28+0.07


























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                                                                             71
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                                    Fig. 1.            Variation of ratio of organic nitrogen to total organic plus inorganic forms of nitrogen
                                                    in the Apalachicola River at Chattahoochee, plotted vs. year from 1970 through 1989.






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