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The relationship between secondary sulfate and primary regional signatures in northeastern aerosol and precipitation
THE RELATIONSHIP BETWEEN SECONDARY SULFATE AND PRIMARY REGIONAL SIGNATURES IN NORTHEASTERN AEROSOL AND PRECIPITATION DCXJCLAS
and KENNETH A. RAHN
~.~OWENTHAL
Center for Atmosphe~c Chemistry Studies, Graduate School of O~a~ography, Narragansett, RI 02882-l 197, U.S.A. (First recked
University of Rhode Island,
27 June 1988 and in$nul form 1 December 1988)
A~-Re~~~~l
ap~rtionme~t of 3 years of aerosol and ~r~pi~tion samples from N~ag~~tt, RI, demonstrates that the relatjons~p between secondary sulfate and primary signatures is ~~ional~y linear, at least For the main northeastern and midwestern source regions. ~urthe~ore, the relationship for local (northeastern) sources appears to be no more variable than for the more-distant (midwestern) sources. The correlation of sulfate with regional signatures shows that the regionahty of secondary sulfate is not significantly greater than that of the primary tracer elements. Key word index: Secondary sulfate, linearity, primary regional signatures, source strength, regression, residuals, apportionment,
INTRQDUCTION
Because sulfate is associated with two-thirds of the acidity of pr~ipitation in eastern North America, knowledge of its areas of origin will play an important role in developing effective control strategies for acid rain. Two distinctly different methods are available for determining regional sources of sulfate in precipitation and precursor aerosol: large-scale transport modeling and regional elemental tracers. Transport models combine emissions of SO,, chemical reactions in the atmosphere, and meteorology to predict downwind concentrations and deposition of SO, and sulfate. Several versions of transport models have existed for more than a decade. Currently, a number of elaborate Eulerian models are being developed in various countries (see review by Venka~~ and Karamchandani (1986), for example), and will soon begin to be validated. The regional elemental tracer technique uses seven elements and five regional signatures from eastern North America to determine the regional-scale sources of pollution aerosol and contaminants in precipitation (Rahn and Lowenthal, 1984, 1985; Rahn et al., 1987; Lowenth~l et al., 1988a,b; Lowenthal and Rahn, 1988a,b). Sources of SO:- are more difficult to determine than those of many other constituent because atmospheric SOi- is mostly secondary, i.e. is formed from atm~phe~c SO2 during transport rather than being emitted directly. Transport models simulate this transformation by incorporating chemical reactions of varying degrees of complexity. The regional tracer system approaches the problem empirically; rather than trying to theoretically model the oxidation of SO2 to SO:-, it attempts to establish o~rational site-
specific and season-specific relations between SO:and the (p~mary~ regional signatures. Because of the great impo~an~ of underst~ding sources of SO:-, this note examines the tracer technique for SOi- in more detail, and presents evidence in support of the long-term site-specific linearity between SOi- and the tracer elements and the apportionments derived from the tracer system.
SUMMARY OF THE REGIONAt TRACERSYSTEM The regional tracer system for eastern North America uses the seven tracer elements As, Sb, Se, Zn, In, noncrustal V, and nonerustal Mn and five regional si~atures, from northern New England and southeastern Canada (NENG), the urbanized Central East Coast (CEC), the Lower Midwest (LMW), the Upper Midwest (UMW), and the nonferrous smelters and surroundings of the Sudbury Basin in Ontario and Quebec (SONT). Regional contributions to the tracer elements in a receptor sample are estimate by the chemical element balance (CEB) procedure, which apportions the con~ntra~o~ of the tracer elements among the signatures with the following least-squares regression:
where C,i, the concentration of the ith species in the tth receptor sample, is the sum of the contributions of the ith species from p sources, s;ti is the estimated contribution of the jth source to the tth sample, A, is the con~ntration of the ith species in the jth signature, and e,, is the random error for the ith species in
1511
1512
DOUGLAS H. ~O~NT~~L
the t th sample. “EfIective-variance” weighting suggested by Watson et al. (1984), which includes uncertainties in both sources (Aji) and samples (C,i), is used: P d
03%
=
u2Cti
f
c
u:jig
(2)
j=l
where for the tth sample, ofav),, is the ‘effective variance’ of the ith species, a&, is the variance of the ith species in the sample, and cr& is the variance of the ith species in the jth signature. The least-~uares estimates for the source strengths are (in matrix notation): S=(A’V-‘A)-‘A’V-‘C
(3)
where V-’ is a diagonal matrix whose elements are the inverses of the effective variances. Sulfate is apportioned among the regional signatures by regressing (with effective-variance weighting) its concentrations in a series of samples from a given season against the regional coefficients gj of those samples: (SO:-),=
i j=l
&Ej
(4)
where p is the number of sources, (SO;-), is the concentration of SO:- in the tth sample, $j is the regional coefhcient of thejth source in the tth sample, and El is the regression coefficient which represents the derived mean SO:-/Se ratio, or ‘effective sulfate’, for the jth source. The effective SO:- represents the mean SO:- (per unit Se) associated with the jth signature over the series, i.e. the initial SOi- near the source plus that formed from SO, during transport to the receptor. The ~ont~bution of the jth source region to the SOi- of a sample is the product of Ej and &, which is the effective SO:- of the signature multiplied by the coefficient of the signature. In general, apportionments of SO:- will be meaningful when two conditions are met. First, regional signatures must be distinct, comprehensive, and essentially correct. Unless primary tracer elements are apportioned correctly, the resulting source strengths cannot be used to apportion related constituents such as SO:-. In this regard, regional apportionments in the Northeast have been extensively tested and validated (Lowenthal et at., 198X; Lowenthal and Rahn, 1988a,b). For example, peaks in midwestem aerosol at Underhill, Vermont derived from regional signatures accompanied maxima in gaseous perfluorocarbon tracer released in Dayton, Ohio during CAPTEX ‘83 (Ferber and Heffter, 1984; Lowenthal et al., 198ga,b). Second, the long-term relationship between SO:- and tracer elements from various regions (seasonal or longer) must be e#ktiuely linear. If this is true, there is no reason why the SO:--tracer relationship cannot be used for long-term apportionments of SO:-, even though the underlying short-term relationship is variable and nonlinear.
and
KENNETH
A. RAHN
THiS STUDY AND ITS RESULTS
Regional apportionments of SOi- have already been presented for three summers and three winters of daily aerosol samples at Narragansett, RI, and Underhill, VT (Lowenthal and Rahn, 1988a,b), and for 3 years of precipitation samples in southern RI (Rahn et al., 1987). For this study, the 3 years of aerosol data from Narragansett, RI, were combined and SOi- was apportioned seasonally, in order to better examine the relationship between (primary) regional signatures and (secondary) SO: - there. For simplicity, SO: - was regressed on summed northeastern and summed midwestern source strengths. Of particular interest was whether the relationship with the signatures was as clear for local (northeastern) SO:- as for the moredistant midwestern SO: -. Table 1 gives the results for summer and winter, expressed as both effective sulfates for the various regions and the actual percentage apportionments of SO:-. The apportionments are listed as per cent of total predicted SOifor northeastern and midwestern sources, and for the southern Ontario smelters (SONT). Winter rain and snow samples were treated separately because they have widely different effective sulfates. The fact that the apportionments of SO:- in aerosol, for the combined 3 years of samples, agree to within 3% of the averages of apportionments of the individual seasons (Lowenthal and Rahn, 1988a.b) implies that summing source strengths within major regions and combining data from different seasons was justified. The effective sulfates display several interesting features. In all but one case (for SONT), their 95% confidence intervals did not contain zero. The fact that sulfate in SONT was detected during winter is reasonable because northerly winds carrying aerosol from Ontario and Quebec to New England are stronger and more frequent in winter than in summer. Second, effective sulfates for both aerosol and precipitation are generally higher in summer than winter, in accordance with higher oxidation rates of summer. The one exception to this was the northeastern effective SOiin rain, which was higher in winter than summer. This may be due to increased local SO, emissions in winter which double northeastern SO2 concentrations then. Third, effective sulfates are systematically higher in precipitation than in aerosol, presumably because SO:- enters pr~ipi~tion both from scavenging of aerosol (which would produce the same values as in aerosol) and by dissolving and oxidizing SO,. Fourth, effective sulfates in precipitation are 2-5 times higher for northeastern than for midwestem sources, whereas no such effect is seen for aerosol. The higher northeastern effective SO:- may come from relatively more SO2 available for the droplets from the local (CRC) source than from the midwestem sources. All regressions were statistically significant, and all but one accounted for 81% or more of the variance of SOi- (see R2s, Table 1). However, these measures do
1513
Secondary sulfate and primary regionalsi~tur~ Table 1. Ap~~ionmen~
of sulfate in aerosoi and p~pitation
from
Narragansett,RI Aerosol Summer(N=238) 95% crt EEC* f&w* EsQNr R2
Northeast Midwest Smelters
6.9kO.S 6.310.5 O*O& 3.0 0.81 56+3% 44zt3%
6.0-7.8 54-7.2 -5.8-5.8
Winter (N = 293) 95% CI 3.2-4.0 3.1-4.0 2.7-7.0
3.6iO.2 3.6kO.2 4.84 1.1 0.86 6f&3% 33&3% 6&l%
Precipitation Summer (N = 8i) 95% CL EEC E R”z” Northeast Midwest
k6.6 18.2&1.6 0.85
29.1
16.042.2 15.0-21.4
23f2% 77&7%
inter
rain (lv = 81) 95% ci
48.1f 12.8 9.5f 1.9 0.65 40&3% 60&S%
22.6-13.7 5.7-13.3
Winter snow (N = 19) 95% CI EEC E $w Northeast Midwest
12.7k2.3 6.lf1.6 0.84 58rt9% 42&110/c
7.9-17.5 2.7-9.6
* Effectivesulfate; EC = NENG + CEG for aerosol, CEC for precipitation, MW-LMW cUMW. t 95% canfidence interval.
not indicate ~i~e~~ty, as it is possible to obtain a high R2 even though the underlying retationship is nonlinear. Draper and Smith (1966) showed that deviations from linearity can be demonstrate by examining the residuals from the regression. They suggested plotting the independent variables against the residuals; significant nonlinearity will show up as curvature in these plots. Scatter diagrams of regional source strengths vs residual SOi- are given in Figs 1 and 2 for aerosbl at Narragansett and in Figs 3-5 for precipitation there. Recause the regression was weighted by the effective variances, the weighted source strengths and residuals were plotted. Although there are some outliers, we see no trend or curvature; variations in the residuals appear to be random. In other words, at the empirical level,SOi- in both aerosol and pr~ipitation is related linearly to the signatures. According to Figs 1 and 2, the relationship for local (northeastern) aerosol is no more variable than for distant midwestem aerosol. This also agrees with Table 1, which shows that the fractional errors of northeastern and midwestem eff&tive sulfates are
similar. ~though ~o~h~~rn
sources are closer to N~aga~tt and scattered relative to midwestem sources, their long-term contributions to aerosol SOL- seem to be ~timat~ as preciseiy as those of the more-distant sources.
SCALEOF REGIONALI~ FOR SULFATE
The above results also show that the secondary aature of atmosphe~ SOi- does not expand its regionality si~~fi~ntly beyond that of the primary tracers. ~though the five regions with distinct signatures do not have sharp boundaries, our measurements can be combined with those of others,to suggest that a typical region is 390-500 km in size (Lowenth~ and Rahn, 1988a,b; Dutkiewicz et al., 1988). Were SO:- ‘super-regional’,i.e. well-mixed on the scale of eastern North America or larger, it would not be correlated with the tracer elements from individual regions such as Northeast and Midwest in the manner demonstrated here.
i5f4
IXPJGLASH. LOWENTHALand KENNETHA. RAHN Narragansatt
Summer
Aarosot
Narragsnsatt
Summer
Rain
I---‘-l
-5
”
0.1
“2
L-
0.00
0.3
Northeastern Source Strength
1
0.2
04
0.00
Midwestern Source Strength
Fig. 1. Weighted residual sulfate vs weighted source strength for northeastern and midwestern components of Narragansett summer aerosol, daily samples 1982-1985.
Narregensatt
Wtnter
0.03
008
Nartheastern Source Strength
A
0.09 Midw88t8rnSource Strength
0 fR
Fig. 3. Wei~t~ residual sulfate vs weighted source strength for northeastern and midwestern components of Narragansett summer rain, 19851987.
Aerosoi
Nerragansett
Winter
Rain
I
.4-
& 0.0
0.8
0.3
0.03
Northe8etern Scurce Strength
I
J
)
0.0
0.8
0.4 UidwWi.?fI
Source
0 06
No~heaetern Scurce Streftgth
StrenSth
Fig. 2. Weighted regiduat sulfate vs wei@d source strength fur northeastern and midwestern components of Narragansett winter aerosol, daily samples 1982-1985.
0.15
000
0.30
~~~~
Fig. 4. Weighted residual sulfate vs weighted source strength for northeastern and midwestem components of Narragansett winter rain, 1985-t987.
Secondary sulfate and primary regional signatures Narragansett
Winter
Snow
1515
Acknowledgements-We thank R. Poirot of the Vermont Agency of Environmental Conservation for providing aerI osol samples from Underhill. We thank Roy Heaton for the precipitation data. Samples were analyzed at the Rhode Island Nuclear Science Center, Narragansett. This work was supported by Cooperative Agreement CR-810905 and Grant R813451-01-0 of the United States Environmental Protection Agency, DOE Grant DE-FG22-84PC71253, Contracts N00014-76-C-0435 and NOOO14-84-C-0035of the Officc of Naval Research, and a Grant from the Ohio Electric Utility Institute. Although the research described in this 0.18 article has been funded in part by the USEPA, it has not been subject to Agency review and therefore does not necessarily reflect the views of the Agency; no official endorsement should be inferred.
5-
0.W Northeastern Source Strength
REFERENCES Draper N. R. and Smith H. (1966) Applied Regression Analysis. John Wiley, New York. Ferber G. J. and Heffter J. L. (1984) Cross-Appalachian Tracer Experiment (CAPTEX ‘83) with Model Evaluation Workshop Information. Preliminary Report, NOAA Air
00
0.2
0.4
Midwestern Source Strength
Fig. 5. Weighted residual sulfate vs weighted source strength for northeastern and midwestem components of Narragansett winter snow, 1985-1987.
Resources Laboratory, Rockville, MD, June 1984. Lowenthal D. H., Rahn K. A., Dutkiewicz V. A., Parekh P. P. and Husain L. (1988a) Discussion of “An evaluation of regional elemental signatures relevant to the northeastern United States”. Atmospheric Environment 22, 609-616. Lowenthal D. H., Wunschel K. R. and Rahn K. A. (1988b) Tests of regional elemental tracers of pollution aerosols: I. Distinctness of regional signatures, stability during transport, and empirical validation. Envir. Sci. Technol. 22, 413-420.
CONCLUDING REMARKS Secondary SOi- and primary regional tracers are linearly related in aerosol and precipitation samples from Narragansett, RI, a rural East Coast site. As noted above, similarity of scatter for northeastern and midwestern sources implies that SOi- may be apportioned as reliably for the local northeastern region as for the more distant midwestem sources. Finally, it should be noted that ‘linearity’ as used here differs from its common meaning in acid rain. Our linearity describes the empirical relationship between SO:- and primary regional tracers. It is descriptive, limited to simultaneous measurements of SOi- and the tracers, and does not explicitly involve SO,. The more-conventional acid-rain ‘linearity’ refers to the response of SOi- in air or precipitation to reductions in SO2 emissions; the existence of our type of linearity may not imply anything about the existence of the latter type.
Lowenthal D. H. and Rahn K. A. (1988a) Tests of regional elemental tracers of pollution aerosols: II. Sensitivity of signatures and apportionments to variations in operating parameters. Envir. Sci. Technol. 22, 420-426. Lowenthal D. H. and Rahn K. A. (1988b) Reproducibility of regional apportionments of pollution aerosol in the northeastern United States. Atmospheric Environment 22, 1829-1833.
Rahn K. A. and Lowenthal D. H. (1984) Elemental tracers of distant regional pollution aerosols. Science 223, 132-139. Rahn K. A. and Lowenthal D. H. (1985) Pollution aerosol in the Northeast: northeastern-midwestem contributions. Science 228,275-284. Rahn K. A., Heaton R. and Lowenthal D. H. (1987) Empirical regional source-receptor relationships for acid rain and precursors in New England determined by elemental tracers. Paper 87-89.5, Proceedings of the 80th Annual Meeting of APCA, New York, NY, 21-26 June 1987 Venkatram A. and Karamchandani P. (1986) Source-receptor relationships: A look at acid deposition modeling. Envir. Sci. Technol. 20, 1084-1091. Watson J. G., Cooper J. A. and Huntzicker J. J. (1984) The effective variance weighting for least squares calculations applied to the mass baiance receptor model. Atmospheric Environment 18, 1347-1355.
and KENNETH A. RAHN
~.~OWENTHAL
Center for Atmosphe~c Chemistry Studies, Graduate School of O~a~ography, Narragansett, RI 02882-l 197, U.S.A. (First recked
University of Rhode Island,
27 June 1988 and in$nul form 1 December 1988)
A~-Re~~~~l
ap~rtionme~t of 3 years of aerosol and ~r~pi~tion samples from N~ag~~tt, RI, demonstrates that the relatjons~p between secondary sulfate and primary signatures is ~~ional~y linear, at least For the main northeastern and midwestern source regions. ~urthe~ore, the relationship for local (northeastern) sources appears to be no more variable than for the more-distant (midwestern) sources. The correlation of sulfate with regional signatures shows that the regionahty of secondary sulfate is not significantly greater than that of the primary tracer elements. Key word index: Secondary sulfate, linearity, primary regional signatures, source strength, regression, residuals, apportionment,
INTRQDUCTION
Because sulfate is associated with two-thirds of the acidity of pr~ipitation in eastern North America, knowledge of its areas of origin will play an important role in developing effective control strategies for acid rain. Two distinctly different methods are available for determining regional sources of sulfate in precipitation and precursor aerosol: large-scale transport modeling and regional elemental tracers. Transport models combine emissions of SO,, chemical reactions in the atmosphere, and meteorology to predict downwind concentrations and deposition of SO, and sulfate. Several versions of transport models have existed for more than a decade. Currently, a number of elaborate Eulerian models are being developed in various countries (see review by Venka~~ and Karamchandani (1986), for example), and will soon begin to be validated. The regional elemental tracer technique uses seven elements and five regional signatures from eastern North America to determine the regional-scale sources of pollution aerosol and contaminants in precipitation (Rahn and Lowenthal, 1984, 1985; Rahn et al., 1987; Lowenth~l et al., 1988a,b; Lowenthal and Rahn, 1988a,b). Sources of SO:- are more difficult to determine than those of many other constituent because atmospheric SOi- is mostly secondary, i.e. is formed from atm~phe~c SO2 during transport rather than being emitted directly. Transport models simulate this transformation by incorporating chemical reactions of varying degrees of complexity. The regional tracer system approaches the problem empirically; rather than trying to theoretically model the oxidation of SO2 to SO:-, it attempts to establish o~rational site-
specific and season-specific relations between SO:and the (p~mary~ regional signatures. Because of the great impo~an~ of underst~ding sources of SO:-, this note examines the tracer technique for SOi- in more detail, and presents evidence in support of the long-term site-specific linearity between SOi- and the tracer elements and the apportionments derived from the tracer system.
SUMMARY OF THE REGIONAt TRACERSYSTEM The regional tracer system for eastern North America uses the seven tracer elements As, Sb, Se, Zn, In, noncrustal V, and nonerustal Mn and five regional si~atures, from northern New England and southeastern Canada (NENG), the urbanized Central East Coast (CEC), the Lower Midwest (LMW), the Upper Midwest (UMW), and the nonferrous smelters and surroundings of the Sudbury Basin in Ontario and Quebec (SONT). Regional contributions to the tracer elements in a receptor sample are estimate by the chemical element balance (CEB) procedure, which apportions the con~ntra~o~ of the tracer elements among the signatures with the following least-squares regression:
where C,i, the concentration of the ith species in the tth receptor sample, is the sum of the contributions of the ith species from p sources, s;ti is the estimated contribution of the jth source to the tth sample, A, is the con~ntration of the ith species in the jth signature, and e,, is the random error for the ith species in
1511
1512
DOUGLAS H. ~O~NT~~L
the t th sample. “EfIective-variance” weighting suggested by Watson et al. (1984), which includes uncertainties in both sources (Aji) and samples (C,i), is used: P d
03%
=
u2Cti
f
c
u:jig
(2)
j=l
where for the tth sample, ofav),, is the ‘effective variance’ of the ith species, a&, is the variance of the ith species in the sample, and cr& is the variance of the ith species in the jth signature. The least-~uares estimates for the source strengths are (in matrix notation): S=(A’V-‘A)-‘A’V-‘C
(3)
where V-’ is a diagonal matrix whose elements are the inverses of the effective variances. Sulfate is apportioned among the regional signatures by regressing (with effective-variance weighting) its concentrations in a series of samples from a given season against the regional coefficients gj of those samples: (SO:-),=
i j=l
&Ej
(4)
where p is the number of sources, (SO;-), is the concentration of SO:- in the tth sample, $j is the regional coefhcient of thejth source in the tth sample, and El is the regression coefficient which represents the derived mean SO:-/Se ratio, or ‘effective sulfate’, for the jth source. The effective SO:- represents the mean SO:- (per unit Se) associated with the jth signature over the series, i.e. the initial SOi- near the source plus that formed from SO, during transport to the receptor. The ~ont~bution of the jth source region to the SOi- of a sample is the product of Ej and &, which is the effective SO:- of the signature multiplied by the coefficient of the signature. In general, apportionments of SO:- will be meaningful when two conditions are met. First, regional signatures must be distinct, comprehensive, and essentially correct. Unless primary tracer elements are apportioned correctly, the resulting source strengths cannot be used to apportion related constituents such as SO:-. In this regard, regional apportionments in the Northeast have been extensively tested and validated (Lowenthal et at., 198X; Lowenthal and Rahn, 1988a,b). For example, peaks in midwestem aerosol at Underhill, Vermont derived from regional signatures accompanied maxima in gaseous perfluorocarbon tracer released in Dayton, Ohio during CAPTEX ‘83 (Ferber and Heffter, 1984; Lowenthal et al., 198ga,b). Second, the long-term relationship between SO:- and tracer elements from various regions (seasonal or longer) must be e#ktiuely linear. If this is true, there is no reason why the SO:--tracer relationship cannot be used for long-term apportionments of SO:-, even though the underlying short-term relationship is variable and nonlinear.
and
KENNETH
A. RAHN
THiS STUDY AND ITS RESULTS
Regional apportionments of SOi- have already been presented for three summers and three winters of daily aerosol samples at Narragansett, RI, and Underhill, VT (Lowenthal and Rahn, 1988a,b), and for 3 years of precipitation samples in southern RI (Rahn et al., 1987). For this study, the 3 years of aerosol data from Narragansett, RI, were combined and SOi- was apportioned seasonally, in order to better examine the relationship between (primary) regional signatures and (secondary) SO: - there. For simplicity, SO: - was regressed on summed northeastern and summed midwestern source strengths. Of particular interest was whether the relationship with the signatures was as clear for local (northeastern) SO:- as for the moredistant midwestern SO: -. Table 1 gives the results for summer and winter, expressed as both effective sulfates for the various regions and the actual percentage apportionments of SO:-. The apportionments are listed as per cent of total predicted SOifor northeastern and midwestern sources, and for the southern Ontario smelters (SONT). Winter rain and snow samples were treated separately because they have widely different effective sulfates. The fact that the apportionments of SO:- in aerosol, for the combined 3 years of samples, agree to within 3% of the averages of apportionments of the individual seasons (Lowenthal and Rahn, 1988a.b) implies that summing source strengths within major regions and combining data from different seasons was justified. The effective sulfates display several interesting features. In all but one case (for SONT), their 95% confidence intervals did not contain zero. The fact that sulfate in SONT was detected during winter is reasonable because northerly winds carrying aerosol from Ontario and Quebec to New England are stronger and more frequent in winter than in summer. Second, effective sulfates for both aerosol and precipitation are generally higher in summer than winter, in accordance with higher oxidation rates of summer. The one exception to this was the northeastern effective SOiin rain, which was higher in winter than summer. This may be due to increased local SO, emissions in winter which double northeastern SO2 concentrations then. Third, effective sulfates are systematically higher in precipitation than in aerosol, presumably because SO:- enters pr~ipi~tion both from scavenging of aerosol (which would produce the same values as in aerosol) and by dissolving and oxidizing SO,. Fourth, effective sulfates in precipitation are 2-5 times higher for northeastern than for midwestem sources, whereas no such effect is seen for aerosol. The higher northeastern effective SO:- may come from relatively more SO2 available for the droplets from the local (CRC) source than from the midwestem sources. All regressions were statistically significant, and all but one accounted for 81% or more of the variance of SOi- (see R2s, Table 1). However, these measures do
1513
Secondary sulfate and primary regionalsi~tur~ Table 1. Ap~~ionmen~
of sulfate in aerosoi and p~pitation
from
Narragansett,RI Aerosol Summer(N=238) 95% crt EEC* f&w* EsQNr R2
Northeast Midwest Smelters
6.9kO.S 6.310.5 O*O& 3.0 0.81 56+3% 44zt3%
6.0-7.8 54-7.2 -5.8-5.8
Winter (N = 293) 95% CI 3.2-4.0 3.1-4.0 2.7-7.0
3.6iO.2 3.6kO.2 4.84 1.1 0.86 6f&3% 33&3% 6&l%
Precipitation Summer (N = 8i) 95% CL EEC E R”z” Northeast Midwest
k6.6 18.2&1.6 0.85
29.1
16.042.2 15.0-21.4
23f2% 77&7%
inter
rain (lv = 81) 95% ci
48.1f 12.8 9.5f 1.9 0.65 40&3% 60&S%
22.6-13.7 5.7-13.3
Winter snow (N = 19) 95% CI EEC E $w Northeast Midwest
12.7k2.3 6.lf1.6 0.84 58rt9% 42&110/c
7.9-17.5 2.7-9.6
* Effectivesulfate; EC = NENG + CEG for aerosol, CEC for precipitation, MW-LMW cUMW. t 95% canfidence interval.
not indicate ~i~e~~ty, as it is possible to obtain a high R2 even though the underlying retationship is nonlinear. Draper and Smith (1966) showed that deviations from linearity can be demonstrate by examining the residuals from the regression. They suggested plotting the independent variables against the residuals; significant nonlinearity will show up as curvature in these plots. Scatter diagrams of regional source strengths vs residual SOi- are given in Figs 1 and 2 for aerosbl at Narragansett and in Figs 3-5 for precipitation there. Recause the regression was weighted by the effective variances, the weighted source strengths and residuals were plotted. Although there are some outliers, we see no trend or curvature; variations in the residuals appear to be random. In other words, at the empirical level,SOi- in both aerosol and pr~ipitation is related linearly to the signatures. According to Figs 1 and 2, the relationship for local (northeastern) aerosol is no more variable than for distant midwestem aerosol. This also agrees with Table 1, which shows that the fractional errors of northeastern and midwestem eff&tive sulfates are
similar. ~though ~o~h~~rn
sources are closer to N~aga~tt and scattered relative to midwestem sources, their long-term contributions to aerosol SOL- seem to be ~timat~ as preciseiy as those of the more-distant sources.
SCALEOF REGIONALI~ FOR SULFATE
The above results also show that the secondary aature of atmosphe~ SOi- does not expand its regionality si~~fi~ntly beyond that of the primary tracers. ~though the five regions with distinct signatures do not have sharp boundaries, our measurements can be combined with those of others,to suggest that a typical region is 390-500 km in size (Lowenth~ and Rahn, 1988a,b; Dutkiewicz et al., 1988). Were SO:- ‘super-regional’,i.e. well-mixed on the scale of eastern North America or larger, it would not be correlated with the tracer elements from individual regions such as Northeast and Midwest in the manner demonstrated here.
i5f4
IXPJGLASH. LOWENTHALand KENNETHA. RAHN Narragansatt
Summer
Aarosot
Narragsnsatt
Summer
Rain
I---‘-l
-5
”
0.1
“2
L-
0.00
0.3
Northeastern Source Strength
1
0.2
04
0.00
Midwestern Source Strength
Fig. 1. Weighted residual sulfate vs weighted source strength for northeastern and midwestern components of Narragansett summer aerosol, daily samples 1982-1985.
Narregensatt
Wtnter
0.03
008
Nartheastern Source Strength
A
0.09 Midw88t8rnSource Strength
0 fR
Fig. 3. Wei~t~ residual sulfate vs weighted source strength for northeastern and midwestern components of Narragansett summer rain, 19851987.
Aerosoi
Nerragansett
Winter
Rain
I
.4-
& 0.0
0.8
0.3
0.03
Northe8etern Scurce Strength
I
J
)
0.0
0.8
0.4 UidwWi.?fI
Source
0 06
No~heaetern Scurce Streftgth
StrenSth
Fig. 2. Weighted regiduat sulfate vs wei@d source strength fur northeastern and midwestern components of Narragansett winter aerosol, daily samples 1982-1985.
0.15
000
0.30
~~~~
Fig. 4. Weighted residual sulfate vs weighted source strength for northeastern and midwestem components of Narragansett winter rain, 1985-t987.
Secondary sulfate and primary regional signatures Narragansett
Winter
Snow
1515
Acknowledgements-We thank R. Poirot of the Vermont Agency of Environmental Conservation for providing aerI osol samples from Underhill. We thank Roy Heaton for the precipitation data. Samples were analyzed at the Rhode Island Nuclear Science Center, Narragansett. This work was supported by Cooperative Agreement CR-810905 and Grant R813451-01-0 of the United States Environmental Protection Agency, DOE Grant DE-FG22-84PC71253, Contracts N00014-76-C-0435 and NOOO14-84-C-0035of the Officc of Naval Research, and a Grant from the Ohio Electric Utility Institute. Although the research described in this 0.18 article has been funded in part by the USEPA, it has not been subject to Agency review and therefore does not necessarily reflect the views of the Agency; no official endorsement should be inferred.
5-
0.W Northeastern Source Strength
REFERENCES Draper N. R. and Smith H. (1966) Applied Regression Analysis. John Wiley, New York. Ferber G. J. and Heffter J. L. (1984) Cross-Appalachian Tracer Experiment (CAPTEX ‘83) with Model Evaluation Workshop Information. Preliminary Report, NOAA Air
00
0.2
0.4
Midwestern Source Strength
Fig. 5. Weighted residual sulfate vs weighted source strength for northeastern and midwestem components of Narragansett winter snow, 1985-1987.
Resources Laboratory, Rockville, MD, June 1984. Lowenthal D. H., Rahn K. A., Dutkiewicz V. A., Parekh P. P. and Husain L. (1988a) Discussion of “An evaluation of regional elemental signatures relevant to the northeastern United States”. Atmospheric Environment 22, 609-616. Lowenthal D. H., Wunschel K. R. and Rahn K. A. (1988b) Tests of regional elemental tracers of pollution aerosols: I. Distinctness of regional signatures, stability during transport, and empirical validation. Envir. Sci. Technol. 22, 413-420.
CONCLUDING REMARKS Secondary SOi- and primary regional tracers are linearly related in aerosol and precipitation samples from Narragansett, RI, a rural East Coast site. As noted above, similarity of scatter for northeastern and midwestern sources implies that SOi- may be apportioned as reliably for the local northeastern region as for the more distant midwestem sources. Finally, it should be noted that ‘linearity’ as used here differs from its common meaning in acid rain. Our linearity describes the empirical relationship between SO:- and primary regional tracers. It is descriptive, limited to simultaneous measurements of SOi- and the tracers, and does not explicitly involve SO,. The more-conventional acid-rain ‘linearity’ refers to the response of SOi- in air or precipitation to reductions in SO2 emissions; the existence of our type of linearity may not imply anything about the existence of the latter type.
Lowenthal D. H. and Rahn K. A. (1988a) Tests of regional elemental tracers of pollution aerosols: II. Sensitivity of signatures and apportionments to variations in operating parameters. Envir. Sci. Technol. 22, 420-426. Lowenthal D. H. and Rahn K. A. (1988b) Reproducibility of regional apportionments of pollution aerosol in the northeastern United States. Atmospheric Environment 22, 1829-1833.
Rahn K. A. and Lowenthal D. H. (1984) Elemental tracers of distant regional pollution aerosols. Science 223, 132-139. Rahn K. A. and Lowenthal D. H. (1985) Pollution aerosol in the Northeast: northeastern-midwestem contributions. Science 228,275-284. Rahn K. A., Heaton R. and Lowenthal D. H. (1987) Empirical regional source-receptor relationships for acid rain and precursors in New England determined by elemental tracers. Paper 87-89.5, Proceedings of the 80th Annual Meeting of APCA, New York, NY, 21-26 June 1987 Venkatram A. and Karamchandani P. (1986) Source-receptor relationships: A look at acid deposition modeling. Envir. Sci. Technol. 20, 1084-1091. Watson J. G., Cooper J. A. and Huntzicker J. J. (1984) The effective variance weighting for least squares calculations applied to the mass baiance receptor model. Atmospheric Environment 18, 1347-1355.