Climatological variability Effect on strategies to reduce acid deposition
David G . Streets Barry M. Lesht Jack D. Shannon Thomas D. Veseka Argonne National Laboratory Areonne. Ill. 60439 One major problem with designing control strategies for acid deposition is that future deposition patterns must be simulated using past meteorological conditions. We can estimate the emission reductions that would result from the implementation of a given control strategy, but efforts to predict what effect these reductions would have on deposition levels are hampered by uncertainty about future transport and deposition climatology. This problem has been set aside in most previous work by using a single past year of meteorological data as a surrogate for all future years. Within the limits of current modeling techniques, this meant that we could design an emission reduction strategy to achieve a desired level of deposition, but we could not predict how that level of deposition might fluctuate from year to year or season to season as a result of natural climatological variation. With the recent processing of a six-year record of meteorological data, however, these questions can now be investigated. In this article we examine how a control strategy might vary when optimized under different assumptions about fuNre meteorological conditions. In particular, we evaluate the variations in emission reductions and in emission control costs that derive from the sensitivity of cost-effective control strategies to climatological variability. An emission reduction strategy that assigns a specific contribution to each state in a particular region (as, for example, contained in most bills introduced into Congress in the past four years) would be expected to be rela-
tively insensitive to climatological variability in the sense that the achievement of a particular deposition level is not a prescribed goal of the strategy. In this case, it is straightforward to examine the interannual deposition variation-at a particular receptor site-that would accompany a fixed pattern of emission reductions. Consider, however, a strategy optimized to achieve a particular deposition
W1~93Bx18510919-0887$01.5010!E 1985 American Chemical Society
goal at a specified location. In this case, sites for emission reductions are chosen to take advantage of a particular set of precipitation and wind conditions to maximize the deposition reduction achieved per unit emission reduction or per unit cost. We would expect this kind of strategy to be quite susceptible to climatological variations. Susceptibility could be manifested in two ways: First, a strategy designed to Envimn. s i . Technal.. Vol. 19. NO.10. 1985 88)
achieve a particular deposition goal using one set of meteorological data might be distinctly different from a strategy designed to achieve the same deposition goal using a different set of meteorological data. Alternatively, a strategy designed to achieve a particular deposition goal using one set of meteorological data might not achieve that goal in years when meteorology is markedly different from the average. Analytical approach In an earlier study, we introduced “targeted” strategies for control of acid deposition (1,2). Using these strategies, sites for emission reductions are chosen on the combined bases of lowest cost and highest contribution to deposition, with the aim of achieving the largest possible reduction in deposition at a particular receptor location. The earlier study examined both single and multiple target areas and showed that targeted strategies offer considerable cost advantages over the unfocused approaches currently embodied in congressional proposals. In the earlier study, there was only a limited examination of sensitivity to meteorological conditions, for two months of 1978 and for all of 1980 and 1981. This article is a discussion of a more rigorous treatment using data from 1976 through 1981 for the individual years of data, together with a six-year-averaged data set. The method of meteorological analysis is different here, so results for 1980 and 1981 differ from those in the earlier study. This work examines single-target strategies only. As before, control of sulfur dioxide emissions is the mechanism for reducing acid deposition, and deposition of total sulfur as sulfate equivalent is the measure of effectiveness. The use of atmospheric transport models in control strategy development has been addressed elsewhere by us and by other investigators (1-5). These models all assume linear chemical transformation and removal processes in the atmosphere, although the actual processes may prove to be nonlinear for certain temporal and spatial regimes. There are other uncertainties in modeling long-range transport and deposition that relate to our inadequate knowledge about important physical processes and to necessary model simplifications and assumptions. The caution advised in previous work applies to this study as well: The models are useful for discerning relative merit among different control strategies, but the absolute values predicted by them are associated with a level of uncertainty that is currently unknown. There are no standards or recommendations for the length of meteorological 888 Environ. Sci Technol.. Mi. 19. No. 10, 1985
A
Differencesin the wind andprecipimion panerns for the summers of 1976 and 1980 result in signijicant differences in seasonal mean horizontal dispersion, as shown for a hypotheticnl source in Oklahoma.Because the puffs represent a seasonal mean panern, the implied transport speed is considembly less than might occurfor a release on any given &. Block lines are 1976 seasonal mean plumes; red lines are 1980 seasonal mean plumes; the center of eachplume is indicared by a solid circle.
records necessary for modeling longrange transport and deposition associated with future or hypothetical spatial distributions of emissions. Generally, such modeling attempts to produce the expected or long-term average deposition field, but in some applications modeling of maximum annual or seasonal deposition might be desirable. Most exercises in modeling long-range transport and deposition have suffered due to insufficient meteorological data. Except for statistical models that use many parameters-and often assume temporally and spatially constant representations of meteorology-most models require updated meteorological data at regular intervals during simulations. Although wind and precipitation are routinely observed and objectively analyzed in other meteorological studies, such data are seldom organized in a “model friendly” form for most atmospheric transport and deposition models.
Modeling techniques The model of transport and deposition used here is the Advanced Statistical Trajectory Regional Air Pollution which can simu(ASTRAP) model late long-term deposition of oxides of sulfur or nitrogen. Here we examine only oxides of sulfur. The analyzed forms of meteorological data required
(e,
to exercise the model are time-series studies of horizontal wind and precipitation fields, preferably at least continental in coverage and at intervals of 6 h. Fields of hourly precipitation resolved on a spatial scale of 100-125 km and 12-h wind fields resolved on a scale of uX)-400 km, both obtained from the University of Michigan (7).were added or linearly interpolated, respectively, to produce the 6-h frequency of meteorological input desired for ASTRAP simulations. The data covered the period from 1976 to 1981. A meteorological year in ASTRAP is defined as Dec. 1 through Nov. 30; because data for December 1975 were not available, the 1976 winter deposition simulations are based on a two-month season scaled to three months. Similarly, because analyses for May 1978 were missing, 1978 spring deposition simulations are based on a two-month season scaled to three months. To calculate source-receptor matrices, electric utility emissions within each state in the continental U S . were mapped in a horizontal grid on the same spatial scale as precipitation. Emissions were also distributed vertically in 100-m layers to 400 m and then in 200-111 layers to 800 m on the same grid. Effective stack height was computed from stack parameters and aver-
r
TABLE 1
Sensitive receptor locations and average sulfate deposition'
Latitude Receptor Boundary Waters Algoma. Ont. Muskoka. Ont. Laurentides, Que. South Nova Scotia Vermont-New Hampshire Adirondacks Central Pennsylvania Smokies
(0)
Longltude ("1
48.5 47.0 45.4 47.6 44.5 44.3 44.0 40.8 35.8
93.0 83.8 78.8 71.2 65.0 71.9 74.5 78.3 82.8
Average equivalent sulfate deposition
Coeflicients variation (oh) Dry Wet Total 01
Dry
(Wha-y) Wet
Total
3.8 9.8 23.7 12.8 12.5 24.5 24.6 78.7 34.2
4.4 13.5 25.0 15.2 24.5 24.1 27.6 54.3 23.2
8.3 23.3 48.7 27.9 9 48.5 52.2 133.0 57.5
~~~
6 7 4 8 14 5 5 2 5
18 13 8 8 6 6 5 7 9
11 9 5 5 4 5 4 5
-1976.81 climalOlqy Totals may no1 add due to rounding. All deposition cdculalions assume fixed (actual 1980) emiSSionS. Coenicientsof Variation am calculated for the six individual years 01 meteorology according 10 the slandard expression:
age ambient conditions. The deposition-wet, dry, and total (wet plus dry)-of total sulfur (sulfur dioxide plus sulfate) as equivalent sulfate was computed for the nine sensitive receptor regions shown in Table 1. These sensitive receptor regions are the ones identified by the U.S.-Canada Memorandum of Intent working group as being particularly sensitive to acid deposition (8).Sensitivity was associated primarily with aquatic ecosystems, although many of the same regions or portions of these regions are believed to be vulnerable to terrestrial ecosystem damage. In preliminary work from this study, we identified the receptor regions by the single points chosen in the International Sulfur Deposition Model Evaluation (ISDME), currently being carried out by EPA and the Atmospheric Environment Service of Canada (9). One concern is that the use of single points to represent large receptor regions may produce results that are unrepresentative of the average across the region, especially if there are large sources of emissions nearby. We believe that this may be true for the Smoky Mountains. Here we use a cluster of five points, spaced at about l o latitude or longitude, and distributed evenly across the region. The mean latitude and longitude for each five-point cluster are given in Table I . In comparison with the earlier work (9), the main changes in receptor area locations are shifts southwestward for the Adirondacks receptor (closer to most U.S. utility sources) and northeastward for the Smoky Mountains receptor (farther from utility sources in Georgia). Source-receptor matrices were determined for each annual period and for an
TABLE 2
Selected source-receptor relationships from ASTRAP simulation'
(ktly)
Average equivalent sulfate deposition (kglha-y) Adirondacks Smokies Total Wet Total Wet
8,155 341 551 718 521 1,092 690 434 448 3,360
17.2 0.2 0.8 1.4 0.5 3.8 3.4 0.5 1.6 5.1
6,825 14.980
10.4 27.6
Sulfur Source Utility emissions Georgia illinois
indiana Missouri Ohio
Pennsylvania Tennessee
West Virginia Other states Nonutiliiy and Canadian All sources
26.3
0.3 1.1 1.9 0.7 5.7 5.2
0.6 2.2 8.7 26.0 52.2
17.5 4.8 0.6 0.9 0.7 0.7 0.2 2.9 0.3 6.5 5.8 23.2
43.3 8.7 1.8 2.9 1.6 2.4 0.5 9.0 1.o 15.5 14.2 57.5
emisions and 1976-81 climatology Totals may not add due 10 independent rounding
*1980
average data set covering the six-year period. Wet deposition and total deposition matrices were constructed, making 14 matrices in all. The matrices constructed were appropriate for utility emissions (generally from tall stacks), because these sources were the ones subject to control in this study. For each case, baseline deposition from all U S . and Canadian anthropogenic sources of sulfur dioxide was calculated using a fixed emission inventory (based on 1980 actual emissions). The emissions and cost data used in the emission reduction optimizations are similar to those desfribed earlier (1, 2) with one exception. In this work, emission reduction opportunities are
limited to those obtainable from coalfired power plants. This is done for two reasons. First, opportunities for emission reductions and control costs for coal-fired power plants are known with greater certainty than are opportunities in other emitting sectors (such as industrial boilers) and for other fuels (such as oil-fired power plants). Second, we believe that reductions that might be mandated under a federal control program-either explicitly or through state implementation-are, in general, likely to be limited to coal-fired power plants. In a public policy context, the opporNnities presented by control of coalfired power plants are likely to be realistic. This means, however, that our Enviran. Sci. Technol.. MI. 19. No. to. 1985
889
approach tends to underestimate opportunities for reduced emissions. It also means that our approach does not evaluate the deposition reduction that could be achieved, for example, in the Adirondack Mountains by controlling oil-fired sources in New York State. The emission control cost model, AIRCOST (2.10, I l ) , is used to generate least-cost SO2 control curves for each state in the nation. The incremental emission reduction opportunities are then combined with the ASTRAP source-receptor matrix elements in a state-to-sensitive-receptor array. The matrix gives the contribution of unit change in emissions in each state to deposition in each of the nine sensitive receptors. The most cost-effective control strategy is obtained by totaling contributions to deposition reduction in order of cost effectiveness, choosing the least costly control options first. Such optimized control strategies were developed for each of the 14 meteorological data sets. Control of SO2 emissions from Canadian sources is not included in this analysis.
Results Table 1 shows the averages for the six annual calculations for dry, wet, and total deposition at the receptor sites tcgether with estimates of the climatological variability of deposition across the six years of meteorological data. The percentage coefficients of variation are shown for wet, dry, and total deposition from all anthropogenic sources. It can be seen that wet deposition is more variable than dry deposition and that receptor areas remote from major source regions, such as the Boundary Waters between Minnesota and Ontario, show more variation than recep tor areas near source regions, such as central Pennsylvania. Deposition in remote a m appears to be more sensitive to variations in the frequencies of winds from critical Sectors than is deposition at receptors with contributions from sources oriented in many directions. The variation in Table 1 is smaller than that likely to be experienced at a particular monitoring station. The minimum resolution of ASTRAP (approximately 100 km) effectively filters variations on smaller scales, which may be quite significant in convective precipitation systems or complex terrain. The variation shown here is that appropriate for the average of a network of monitoring sites across a grid cell of about I@ km2, provided that emissions are held constant. In any actual period of several years of monitoring, of course, emissions would vary even in the absence of regulatory action because of variations in demand for electricity, industrial activity, space heating, and 890 Environ. Sci. Technal.. Vol. 19. No. 10. 1985
TABLE 3 Average emission reductions and control costs for selected control strategiee strate.+ - - -=,
Emlslon reductions (losVy) Adirondacks (wet) Adirondacks (total) Smokies (wet) Smokies(total) Control costs ($ bllllonly) Adirondacks (wet)
Adirondacks (total) Smokies (wet) Smokies(total)
10%
20%
40%
40%
20kg
2.53 2.70 1.58 1.60
4.11 4.66
6.21 8.14 2.80 3.10
9.46
5.72 NA 11.69 NA
0.52 0.60 0.43 0.43
0.97 1.25 0.53
1.74 2.69 0.78 0.86
3.14
2.09
2.29
0.56
4.22 4.57
1.32 1.43
1.53 NA 0.45 NA
NA = Not applicable -197681 climatology '10% = 10% reduction in wet (or total) sullale deposition in the Adimndacks (or Smokies). SIC.: 20 kg is the reduction necessary to achieve a wet Sulfate depDSition rate 01 20 kglha-y in the targeted receptor area r40% reduclion 01 total deposition in the Adirondacks is achievable only in three of the six
years
TABLE 4
lnterannual coefficients of percentage of variation for selected target strategies"
Emission reductions (10' tly) Adirondacks (wet) Adirondacks (total) Smokies (wet) Smokies (total) Control costs (S blllionly) Adirondacks (wet) Adirondacks (total) Smokies (wet) Smokies (total)
2 2 1 1
2 2 1 1
4 5 5 2 4 5 4 2
4
3
6 6
11
17 NA 38
7
NA
5 8 8 4
7
6
23 NA
8 4
32 NA
NA = Not applicable -197681 climatology 40% = 10% reduction in wet (or total) Sulfate deposition in the AdirondaCkS (or Smokies), etc.; 20 kg is the reduction necessary lo achieve a wet sulfate deposition rate 01 20 kglhay in the targeted receptor area '400h reduction01 lotai deposition in the Adiiondacks is achievable only in lhree 01 the six
other factors. Variations in energy demand are related to changes in meteorological conditions, but it is not known whether they would increase or decrease deposition variability. Because the control strategy analysis that follows is targeted for the Adirondack and Smoky mountains, it is worth examining some of the model predictions of contributions from certain states and source types to deposition in these receptor areas. Table 2 shows the contributions for those eight
states that have the greatest opportunities for reductions in SO2 emissions from utilities. Note that these are not necessarily the eight states where utility emissions make the greatest contribution to deposition in each receptor area. The proportion of sulfur deposition attributable to US. utilities is considerably larger in the Smoky Mountains than in the Adirondacks; this is primarily because of the relatively greater importance of Canadian sources to d e w sition in the Adirondacks. In addition,
:IGURE 1
3eductions of wet sulfate deposition in the Adirondack Mountains 1
5
r
\
individual years.
Wet sulfate deposition (kg/ha-y)
. . . cosls,based on coststfective strategies
cause, in the hypothetical situation where all sources reduce emissions to the maximum extent possible, there can be no variability in optimum control strategy with differences in meteorology. Second, control strategies designed to achieve reductions in total deposition in the Adirondacks are more sensitive than those designed to achieve a similar reduction in wet deposition. This may be a reflection of the greater emission reductions required in the former cases. In the Smoky Mountains, the opposite is true: Wet deposition strategies are more sensitive than total deposition strategies. In this case the major contribution from a few, relatively close sources to wet deposition in the Smokies makes wet deposition more sensitive to variations in winds From critical sectors. Contributions to total deposition come from a larger number of more dispersed sources. Third, at low levels of deposition reduction, there is no clear trend as to the relative climatological sensitivities of control strategies targeted for the Adirondack or Smoky mountains. However, as deposition reduction increases, the strategies targeted for the Smokies appear to become more sensitive to climatological variability than are strategies targeted for the Adirondacks. Again this may be because deposition in the Smokies is attributed to fewer, larger sources than in the Adirondacks, which would make the Smokies strategy more sensitive to variations in the frequencies of winds from critical sectors. Fourth, strategies designed to achieve an absolute level of wet deposition, for example, 20 kg/ha-y, are considerably more sensitive to meteorological variability than those designed to achieve a specified percentage of reduction in wet deposition. This is because the variation in deposition from all sources is a much larger fraction of the deposition excess above the target loading than it is of the average deposition. For the Adirondacks, interannual wet deposition varies between 25.4 kgl ha-y and 29.0 kglha-y, which corresponds to a 13% variability range about the average deposition (27.6 kglha-y) but almost a 50% range (5.4-9.0 kg/ ha-y) around the average deposition excess (7.6 kg/ha-y). Wet deposition in the Smokies is only slightly in excess of 20 kglha-y, leading to a very high coefficient of variation in the strategy to achieve 20 kg/ha-y. Comparisons between the mean values from six annual calculations and the single value from the six-year average data set show close similarity. This suggests that a long-term averaged matrix is representative of what would be ob-
' * r
15
10 Wet
20
25
sulfatedeposition (kglhby)
nonutility sources, particularly fuel oil the Adirondacks or in the Smokiescombustion for residential space heat- using each of the 14 ASTRAP sourceing, also play a more significant role in receptor matrices. In each case, the mix the Adirondack Mountains. For the of state level emission reductions varsource states and receptor areas exam- ied somewhat, owing to the varying ined in Table 2, the greatest relative nature of the annual meteorology. The contribution is about 20%; the propor- emission reductions and control costs tion of wet deposition in the Smokies is corresponding to each of the six annual attributed to utility sources in Georgia. periods were determined for a variety The Georgia utilities' contribution to of deposition reduction levels. Coeffwet deposition in the Smokies is greater cients of variation were calculated for than that for dry deposition (15%). the set of six years. Tables 3 and 4 show This is in contrast to what might nor- the results. mally be expected as a near-source. effect because Georgia sources are up Observations Several observations can be made wind of the Smokies more frequently during precipitation events than during from Tables 3 and 4: First, the higher the deposition reduction required, the dry periods. As a first step in the control strategy greater the susceptibility of the optianalysis, the modeling system was used mum strategy to climatological variato develop cost-effective strategies for tion. This susceptibility must peak at a reducing sulfate deposition-either in high value of emission reduction be-
Environ. Sci. Twchnol.. Vol. 19. No. 10, 1985 891
FIGURE 2
Reductions of wet sulfate deposition in the Smoky Mountains.
20 kg
.-3
.
Range of results for individual years,
5-
E
W
5
10
15
20
25
Wet Sulfatedeposition (kglha-y)
. . . Costs, based on costeffective strategies 12
1 6 y Average
Wet sulfatedeposition (kglha-y)
tained by replicating calculations with many individual years. Figures I and 2 illustrate the optimized wet deposition reduction curves plotted against emission reduction and control cost for the Adirondacks and Smokies. The range covers the results obtained for the six individual years of meteorology, 1976-81, and the sixyear-average curve is shown. Each curve originates at a point corresponding to the deposition calculated for a specified year and begins with a discontinuity corresponding to compliance control. This discontinuity exists because, in determining which states should reduce emissions under a cost-effective control strategy, it was assumed that plants currently out of compliance with state implementation plans (SIPS) would first have to come into compliance with ex892 Environ. Sci. Technol..VoI. 19, NO. 10. 1985
isting regulations in a control step that is not cost effective but that does lead to a reduction in deposition relative to 1980 levels. Because emission reductions required to achieve SIP compliance are not necessarily cost effective, this part of the curve is steeper than the cost-effective portion that follows. In this work, the compliance reductions amount to a reduction in SO? emissions of 1.3 million tly at a control cost of $0.4 billionly. These curves illustrate most of the features of this study. The rapidly increasing marginal cost of control imparts a much steeper feature to the cost curves than to the emission reduction curves. The end points of these curves represent all reasonable reductions in SO2 emissions from coal-fired power plants. At these end points, the width of the range is approximately 3 kg/ha-y,
representing an estimate of the maximum absolute differences in wet d e p sition to be expected from designing cost-effective control strategies according to different climatological data. The width of the range is somewhat less than the range of annual deposition estimates for the Adirondack or Smoky mountains from all anthropogenic sources, because deposition contributions from Canadian sources and nonutility sources in the U S . also vary. In previous work we cautioned about relying too heavily on predictions of absolute levels of deposition from the current generation of atmospheric transport models (I, 2). Percentage changes in deposition values between different control strategies, with and without simulated emission reductions, are considered more reliable. However, in this case, the implications of Figures 1 and 2 for achieving various target loadings in the Adirondacks and Smokies are forcefully apparent. And although we should not necessarily expect the following observations to reflect the real world directly, they are instructive of generic situations that are likely to occur. A target loading of 20 kglha-y of wet sulfate in the Adirondacks, as suggested by several scientists in the U S . Canada Memorandum of Intent study, can be achieved by reducing SO2 emissions by about 7 million tly, at a cost of about $2 billionly (8).The range of variation over six years is quite significant, however, with standard deviations of 1.3 million t/y in emission reductions and $0.6 billion/y in control costs. A goal of 20 kg/ha-y of wet sulfate deposition in the Smoky Mountains, on the other hand, can be expected to be met essentially by achieving compliance with SIPS, with little additional reduction (0.4 million tly) needed. Costs beyond those of SIP compliance also should be relatively small ($0.05 billionly). The target loading of 20 kg/ha-y was recommended by Canadian scientists in the US-Canada working group as necessary to protect the majority of sensitive aquatic ecosystems (8).This value is approximately equivalent to the precipitation pH range of 4.6-4.7, which has been recommended by the National Academy of Sciences as desirable to protect aquatic ecosystems (12). However, by correlating ionic concentrations in rainfall samples, Gorham et al. have suggested that a more accurate conversion of pH 4 . 6 4 . 7 leads to a wet sulfate deposition range of 14-16 kg/ ha-y (13).This range is also shown in Figures I and 2, and the implications are clear. The achievement of a wetdeposition goal of 14-16 kg/ha-y in the Adirondacks is predicted by the models
to be at the limit of what can be obtained by controlling SO, emissions from coal-fired power plants. In cases such as these, sensitivity to meteorological variability and marginal cost of control are at their greatest. A final point of interest is the question of how much year-to-year variability in deposition there is from a single cost-effective reduction strategy. To investigate this, we hypothesized the implementation of an emission reduction program designed to achieve a 20 kg/ ha-y level of wet sulfate deposition in the Adirondacks, optimized for the 1976-81 average matrix. This, of course, fixes the state emission reduction amounts. This strategy was then run through each of the six annual matrices. A mean value of wet deposition of 20 kg/ha-y was obtained, with a standard deviation of 1.2 kg/ha-y. This value is only slightly smaller than the maximum half-width of the range obtained when different optimal emission reduction patterns are used (about 1.5 kglha-y). Therefore, the optimization of emission reductions among states does not appear to add significantly t o the interannual variation in deposition; meteorological variability is the dominant contributor.
Acknowledgment This work was supported by EPA and the Department of Energy, as part of the National Acid Precipitation Assessment Program and as part of the programs conducted by DOES Office of Environmental Analysis. Because it has not been subjected to policy review, it does not necessarily reflect the views of either agency. We thank Perry Samson for providing the meteorological analyses used in this article.
(IO) E. H.k h a n and Associates. “AIRCOST Model: Technical Documentation”; Springfield, Va.. April 1983. (11) Streets, D.G.; Vernet. I.E.; Veselh, T. D. “Prooosals for Acid-Rain Control from the 9ith Congress,’’ ANLIEES-TM281; Argonne National Laboratory: Argonne. 111.. 1984. (12) National Research Council. “Amosphere-Biosphere Interactions:Toward a Better Understanding of the Ecological Conscquences of Fossil Fuel Combustion”; National Academy Press: Washington, D.C.. 1981; p. 181. (13) Gorham. E.; Martin, E E.;Litzau. 1.7. Scimee 1984,225.407-9.
awid G. Streets (I.) is an environmental scientist and m g e r of the Policy Sciences Section of the Energy and Environmental Systems Division 01 Argonne National Lnboratory. He holds a B.Sc. and a Ph.D. in physics from the University of London. U.K. Streets is responsible for managing on interdisciplinary group that analyzes energy and environmental issues for the Department ofEnergy. Barry M. Lesht f r ) is a physicist in the Atmospheric Physics Program of the Environmental Research Division of Argonne National Laboratory. He holds a Ph.D. in geophysical sciencesfrom the University of Chicago. His research interests include modeling andfield studies of the transporlotion of contaminants in aquatic ond atmospheric systems.
References (I)Stneu. D. G.; Hanson, D. A,; Carter,
L. D. J . Air Pollut. Control Assoc. 1984.34, 1187-97. (2) Strcets, D.G. et al. “Controlling Acidic Dcposition: Targeted Strategies for Reducing Sulfur Dioxide Emissions,” ANLIEESTM-282; Argonne National Laboratory: Argonne, Ill.,1984. (3) National Research Council. “Acid Deposilion: Atmospheric Processes in Eastern North America”; National Academy Press: Washington, D.C.. 1983; pp. 55-86. (4) Streets, D. G.; Knudson, D.A.; Shannon, 1. D.Environ. Sci. Rchnol. 1983. 17. 47485A (5) Shaw. R W , Young, J.WS. Atmoi. Envrm n 1983. /7. 2221-29. 16) Shannon. 1 D Almos Envtron 1981. IS. 689-701. (7) Samson, E l . . University of Michigan, personal communication. 1985. (8) Schiermeier, F. A,; Misra, I! K. In “Transactions: The Meteorology of Acid Deposition”; Samson, I! I. Ed.; Air Pollution Control Association: Pittsburgh, Pa., 1983; pp. 330-45. (9) Shannon, 1. D.; Slrecls, D. G. In “Proceedings of the 15th NATOICCMS International %chnical Meeting on Air Pollution Mudcling and $13 Applications“; De Wirpelacrc. C.. W.:Plenum Prcrs: Ncu Ynrk. N.Y.,’ in press
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l7uma.v D. Wselka ( r ) is an environmental policy analyst in the Energy and Environmental Systems Division of Argonne National Laboratory. He lurr a B. S. and an M.S. in meteorology from Northern Minois University. Veselka is involved in modeling of energy, economic. and environmental issues related to changes in air quality lows and regulations.
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