Ž .The Science of the Total Environment 223 1998 53]63

Intercomparison between three receptor-oriented modelsapplied to acidic species in precipitation

A. CharronU, H. Plaisance, S. Sauvage, P. Coddeville, J.C. Galloo,R. Guillermo

Ecole des Mines de Douai, Departement Chimie et En¨ironnement 941, rue Charles Bourseuil } B.P. 838,´59508 Douai Cedex, France

Received 24 July 1998; accepted 1 September 1998

Abstract

Three different receptor-oriented models have been tested on the precipitation chemical data of a backgroundstation in France from 1992 to 1995. These models which allowed the identification of source]receptor relationships

Ž 2y y q.for acidic species non-sea salt SO , NO and NH in rain have been compared. The receptor-oriented4 3 4methodologies are based on the same construction scheme. Precipitation data and air parcel backward trajectorieswere combined in the model calculations to produce probability or concentration maps of likely contributing sources.The regions of Europe identified by the three models generally coincide well with the location of known emissionsources. Using non-parametric Spearman rank-order correlation, the computed concentrations provided by thesethree models were compared with the European emissions established by EMEP. A good correlation was foundbetween computed ionic concentrations and the emissions of SO , NO and NH . Each model shows its own2 x 3advantages to examine the source regions that give high concentrations of acidic species at a receptor site. Q 1998Elsevier Science B.V. All rights reserved.

Keywords: Receptor-oriented models; Source]receptor relationships; Long range transport; Acid deposition;Sulphate; Ammonia; Nitrate; SO ; NOx x

1. Introduction

Ecosystem damage such as the deterioration inthe state of forests and the increase of acidity inthe mountain lakes and streams are the conse-quences of long range transport of acidifying pol-

U Corresponding author.

Žlutants Strauss and Cuiller, 1986; Dambrine et.al., 1995; Probst et al., 1995 . Sulphur dioxide

Ž . Ž .SO and nitrogen oxides NO , in part trans-2 xŽ .formed in strong acids H SO and HNO dur-2 4 3

ing their residence time in the atmosphere, arethe main gases responsible for increasing the

Ž .acidity of precipitation e.g. Galloway et al., 1976 .Ž .On the other hand, ammonia NH , originating3

mainly from agriculture, contributes to nitrogen

0048-9697r98r$ - see front matter Q 1998 Elsevier Science B.V. All rights reserved.Ž .P I I S 0 0 4 8 - 9 6 9 7 9 8 0 0 3 0 8 - 8

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]6354

eutrophication and acidification of ecosystemsŽ .Fangmeier et al., 1994 .

Air mass trajectories have often been used toidentify the source areas or origin sectors of

Žchemical species in precipitation Billman-Stunderet al., 1986; Loye-Pilot and Morelli, 1988; Colin et

.al., 1989; Sanusi et al., 1996 . Many authors havedeveloped statistical methodologies associatingthe atmospheric measurements to the corre-

Žsponding trajectories Moody, 1986; Moody andGalloway, 1988; Moody and Samson, 1989; Hilst

.and Chapman, 1990; Deininger and Saxena, 1997 .The results indicate that the relationships betweenemissions and wet deposition remain strongly de-

Žpendent on meteorological conditions Moody andGalloway, 1988; Moody and Samson, 1989; Brook

.et al., 1993 . Knowledge of these relationships isessential to define an international strategy toreduce the anthropogenic emissions of these pol-lutants. A receptor-oriented model called PSCFhas been successfully applied to acidic species in

Žrain Zeng and Hopke, 1994; Plaisance et al.,.1996, 1997a . Originally proposed by Ashbaugh et

Ž .al. 1985 , it combines atmospheric chemical datawith air mass backward trajectories to producethe probability maps of source areas. Variousreceptor-oriented models have been developed toboth identify the possible source areas and esti-mate the importance or the contribution of these

Žsources for different atmospheric species Chengand Hopke, 1993; Stohl and Kromp-Kolb, 1994;

.Liu et al., 1996 .This paper presents a comparison between

three receptor-oriented models applied to threeŽ 2y yprecipitation species non-sea salt SO , NO ,4 3

q.NH . The source maps produced by these mod-4els are compared with the European inventory ofSO , NO and NH emission maps established by2 x 3EMEP. The quantitative relationships betweenthe results of the three models and the emissiondata are examined performing the non-paramet-ric Spearman correlation analysis.

2. Data base and method

2.1. Precipitation chemistry

Precipitation chemistry data are daily precipita-

Žtion samples collected at the Morvan site eleva-.tion 620 m, latitude 478169 N, longitude 048059 E ,

a background station of the French atmosphericŽ .deposition network MERA Fig. 1 . The sampling

network and the sampling and analysis protocolsŽ .are described by Coddeville et al. 1993 . The

MERA stations are located in rural sites far fromthe main urban and industrial emission regions inFrance and are all equipped with automatic wet-only collectors. The data used in this study arethose collected from January 1992 to December1995. A dynamic validation procedure, es-

Ž .tablished by Plaisance et al. 1997b , and appliedto these data, has been used to eliminate the

Ž .unreliable samples 6.8% of the data . To associ-ate an air parcel back trajectory with each sam-ple, a reference gauge installed near the collectorrecords the start and end times of the precipita-tion events. The precipitation samples which can-

Žnot be associated with only one trajectory dailysamples corresponding with several rain eventsand rain events divided in two daily samples,

.which represent 6.4% of the data are eliminated.After rejecting these data, 395 precipitation sam-ples associated with a trajectory have been re-tained for this study. The precipitation compo-nents selected for this study are the non-sea-salt

Ž 2y.sulfate ions non-sea salt SO , the nitrate ions4

Fig. 1. Location of the Morvan station, France.

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]63 55

Ž y. Ž q.NO and the ammonium ions NH . Sodium3 4Ž q.ions Na which are mainly of marine origin are

used to evaluate the non-sea salt SO2y through4the ratio in seawater SO2yrNaqs0.12, where4SO2y and Naq are the concentrations in eq. ly1

4Ž .Jacob et al., 1985 . Table 1 gives the descriptionof these variables.

2.2. Meteorological data

The ionic concentrations of the precipitationcollected at the receptor site are dependent onthe areas crossed by the air masses which give theprecipitation event at the receptor site. Thethree-dimensional trajectory model developed by

Ž .Martin et al. 1987 is used to reconstruct airparcel movements in the atmosphere. This trajec-tory model utilizes the analysed synoptic wind

Ž .fields zonal, meridian and vertical componentsŽat eight pressure levels 1000, 850, 700, 500, 400,

. Ž300, 250, 200 hPa four times per day 00.00,.06.00, 12.00, 18.00 h UT . These wind fields data

have been achieved by the European Centre forŽ .Medium Range Weather Forecast ECMWF . The

trajectory segment endpoint for each 5-min timestep are calculated from linear spatial and tem-poral interpolations using central and lateral ad-

Ž .vances. Martin et al. 1990 has shown that thistrajectory model is suitable to follow the atmo-spheric transport of pollutants. For our study, aprecipitation sample is associated with the corre-sponding 72-h backward trajectory ending at thereceptor site at the 850-hPa pressure level. The850-hPa pressure level is used because it providesreasonable results concerning the transport ofpollutants in the troposphere and their interac-

Table 1Variable description for acidic species in the 395 precipitation

Žsamples collected from January 1992 to December 1995 datay1 .in mmol l

2y q ynss-SO NH NO4 4 3

Average concentration 19.84 87.74 32.41Minimum concentration 0.26 2.14 0.17Maximum concentration 160.50 519.03 267.01Standard deviation 22.09 77.39 37.17

Ž .tion with clouds Casado et al., 1995 . Air masstravels are described by 1-h segment endpoints ofcoordinates in terms of latitude and longitude.Thus 72 endpoint locations are associated witheach precipitation sample. The whole geographicregion covered by the trajectories is divided into

Ž150=150-km cells according to the EMEP Co-operative Programme for Monitoring and Evalua-tion of the Long Range Transmission of Air Pol-

.lutants in Europe grid of Europe.

2.3. Description of models

The three receptor-oriented models which aretested in this study are based on the same con-struction scheme. If a trajectory endpoint falls in

Ž .a grid cell i, j the air mass is assumed to collectcomponents emitted in this cell and, once thecomponents are incorporated, they are trans-ported along the trajectory to the receptor site.These models do not explicitly take into accountthe atmospheric diffusion, the chemical transfor-mations and the removal mechanisms occuringfrom the sources to the receptor. The Potential

Ž .Source Contribution Function PSCF model isdescribed as follows:

Let N represent the total number of trajectorysegment endpoints during the study period. Theprobability of the event A that n endpointsi j i j

Ž .have fallen into the grid cell of indices i, j is:

ni jw xP A si j N

Precipitation events with measured concentra-tions higher than a pre-specified criterion valueare considered to represent polluted events. Theaverage concentration provides a reasonable cri-

Ž .terion value Cheng and Hopke, 1993 . Theprobability of the event B that m endpoints ofi j i jpolluted event trajectories have fallen into the

Ž .same grid cell i, j is:

mi jw xP B si j N

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]6356

The PSCF value for the ij-th cell is then definedas the conditional probability:

w xP B mi j i jPSCF s si j w x nP A i ji j

The PSCF is the conditional probability that ani jair mass giving a polluted event of rain arrives atthe receptor site after having crossed over theij-th cell.

The two other models created by Seibert et al.Ž . Ž .1994 and Stohl 1996 allow the establishment ofconcentration field maps for the selected species.The Seibert et al. concentration fields are calcu-lated via:

M

n = logCÝ i jl lls1logC si j M

nÝ i jlls1

Ž .where i, j are the indices of the grid cell, l theindex of the trajectory, M the total number oftrajectories, C the component concentrationlobserved on the receptor site corresponding totrajectory l and n the number of endpoints ofi jltrajectory l fallen into the ij-th cell. n corre-i jlsponds to the hourly time spent in the grid cellŽ .i, j by the trajectory l.

Ž .The Stohl 1996 model uses the Seibert et al.Ž .1994 concentration field to redistribute the con-centrations along the trajectories according to theformula:

Ci jqlC sC qs1,...,N ls1,...,Mql l lCi jql

where N is the number of 1-h endpoints of theltrajectory l, C is the concentration of the ij-thi jq lgrid cell calculated by the Seibert et al. formulaand hit by the endpoint q belonging to the trajec-tory l, C is the average of the concentrationsi jq lof the grid cells hit by the N endpoints of theltrajectory l and C is the new concentration ofqlthe endpoint q of the trajectory l. Then, the Stohlconcentration fields are calculated via:

NM 1

n = logCÝ Ý i jq l qlls1 qs1

logC si j NM 1

nÝ Ý i jq lls1 qs1

where n the number of endpoints q of thei jq ltrajectory l fallen into the ij-th cell. The Stohlmodel, created to improve the Seibert et al. model,has proved satisfying to identify precisely the

Ž .source regions of particulate sulfate Stohl, 1996 .In the models of Seibert et al. and Stohl, a highC means that, on average, air masses passingi j

Ž .over cell i, j entail high concentration events atthe receptor site.

In the three models, the grid cells counting lessthan 10 endpoints are not taken into account inthe analysis because the confidence of their re-sults is considered too low. Finally, a smoothingof the probability and concentration fields is car-ried out to take into account the uncertainties oftrajectories. The displacement error of three-di-mensional trajectories is mainly due to the inter-polation of the vertical velocity and has been

Ževaluated at 600 km after 96 h travel time Stohl.et al., 1995 . To consider the possible error after

72 h travel time, a smoothing is applied to thewhole of cell values: the average between the grid

Ž . Žcell i, j information probability or concentra-.tion and the neighbouring cell information is

calculated according to the following formula:

8

I qIÝ p i jž /ps1SI si j 9

S Žwhere I is the cell information probability ori j.concentration after smoothing, I sPSCF ori j i j

C is the information cell before smoothing andi jI with ps1]8, the value of the neighbouringpcells.

The results of the three models for non-sea saltSO2y, NOy, NHq are compared with the EMEP4 3 4emission inventory of SO , NO and NH for2 x 3

Ž .1993 Barrett et al., 1995 performing the Spear-man rank-order correlation analysis.

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]63 57

3. Results

The results obtained by the three models ap-plied to the non-sea salt SO2y give similar pat-4

Ž .terns Fig. 2 . The lowest probabilities and con-centrations are found in marine areas and thehighest in continental areas. Therefore the SO2emissions from fossil-fuel burning seem to be theprincipal source of non-marine sulfate in precipi-tation at the Morvan site. The influence of thereaction of dimethyl sulfide with hydroxyl radicals

Žto produce SO from the ocean refer to Yin et2.al., 1990 seems to be negligible. The Stohl and

Seibert et al. models point out a known region ofhigh anthropogenic emissions in Europe namely

Žthe ‘Black Triangle’ Polish]Czech]German.border area . The high values of PSCF can be

seen in an extensive region of Europe whichcorresponds to a large part of Germany, the west

Žof Poland, the Czech Republic including the.‘Black Triangle’ , Belgium, The Netherlands, Slo-

vakia, a part of Hungary and the north of Austria.The three models clearly delineate the same re-gion of Europe, but it seems that the PSCF hasthe worst resolution in the determination of highemission areas. Through the three model results,SO emissions of Great Britain and southern2European countries seem to weakly affect thesulphur concentrations in precipitation at theMorvan site.

The PSCF and Seibert et al. model patterns forNOy give a similar extensive area of high com-3puted values including the north of France, Bel-gium, The Netherlands and the north of GermanyŽ .Fig. 3 . This large area is a region with a densemotorway network. Two cell clusters of high com-puted concentrations are observed in the Stohlpattern for NOy. The first one corresponds to the3north of Germany and seems to be the same areawhich is revealed by the PSCF and Seibert et al.models. The second one is an industrialized areaof central Europe including Poland, the CzechRepublic and Slovakia. Only the Seibert et al.model points out the part of England with highNO emissions. The area located in northern ItalyxŽ .i.e. the Po valley does not have any influence onthe chemical concentrations of rain at Morvan. Apossible explanation could be the large precipita-

Žtion amounts in the Alps due to orographic ef-.fects which wash out the air masses and then,

play the role of a barrier of pollutants to France.q Ž .The three spatial patterns for NH Fig. 44

reveal the same cell cluster of high computedvalues in the areas located near northern Ger-many, a part of Denmark and a part of The

ŽNetherlands see the map of Seibert et al.’s.model . This region coincides with an area of

intensive livestock breeding. The Seibert et al.and Stohl models identify a second region of highcomputed concentrations located in central Eu-rope. This region corresponds to the area of highnon-sea salt SO2y and NOy computed concen-4 3trations. This result can be explained by the exis-tence of a long range transport of ammonium

w Ž . xaerosols NH HSO , NH SO and NH NO4 4 4 2 4 4 3resulting from the combination of anthropogenicemissions of SO , NO and NH . This long range2 x 3transport of ammonium aerosols also has been

Žreported in the literature Kitto and Harrison,.1992 . None of the models indicate the high NH3

source areas located in Great Britain and Brit-tany.

On the whole, the three models show relativelysimilar and consistent patterns for the three stud-ied species. Concerning the concentration fields,only the computed concentrations of the Seibertet al. model seem directly comparable with con-centration values observed in rain at the Morvan

Ž .station see Table 1 . Stohl’s redistributionmethodology has modified the size order of com-puted concentrations. Nevertheless, the Stohlmethodology seems to better identify the area ofhigh emissions. Similar results have been observed

Ž .for particulate sulfate Stohl, 1996 . The resultssuggest the existence of preferred pathways of airmasses containing acidic pollutants and importantlosses of pollutants in particular regions as moun-tainous and coastal areas that explains the weakinfluence of Great Britain, Spain and the north ofItaly.

Spearman’s rank correlation analysis has beenused to examine the quantitative relationshipsbetween the non-sea salt SO2y, NOy and NHq

4 3 4computed concentrations and the emissions ofSO , NO and NH emissions established by2 x 3

Ž .EMEP Barrett et al., 1995 .

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]6358

2y Ž . Ž .Fig. 2. nss-SO probability and concentration fields computed with the PSCF method. a the Seibert et al. method; b the Stohl4Ž .method; c ‘S’ represents the Morvan receptor site. Grid cell size is 150=150 km.

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]63 59

y Ž . Ž .Fig. 3. NO probability and concentration fields computed with the PSCF method. a The Seibert et al. method; b the Stohl3Ž .method; c ‘S’ represents the Morvan receptor site. Grid cell size is 150=150 km.

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]6360

q Ž . Ž .Fig. 4. NH probability and concentration fields computed with the PSCF method. a The Seibert et al. method; b the Stohl4Ž .method; c ‘S’ represents the Morvan receptor site. The grid cell size is 150=150 km.

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]63 61

P-values indicate statistically significant corre-lations at the 99.99% confidence level. The threemodels show relatively similar correlation coef-ficients. These medium correlation coefficientscan be derived from the non-considered removal

Ž .mechanisms dry and wet deposition occurringfrom the sources to the receptor, but also canunderline the already noticed existence of pre-ferred pathways or uninfluential regions of acidicpollutants to Morvan.

The correlation coefficient values are relativelysimilar for non-sea salt SO2y vs. SO and NOy

4 2 3q Ž .vs. NO and weaker for NH vs. NH Table 2 .x 4 3

Stronger correlations have been found with theSO emissions above 100 m than with the SO2 2emissions below 100 m suggesting that the SO2emitted above is the main contribution of highSO2y events. The lower correlations found4between the NHq computed probabilities or con-4centrations and the NH emissions can be ex-3plained by the low capacity of transport of NH3over long distances referred by Hov and HjolloŽ .1994 .

The influential sources of acidic species in pre-cipitation for the Morvan site are essentially lo-cated outside of the country. This indicates thathigh concentrations in precipitation are due tolong-range transport of acid species coming fromthe high anthropogenic emission areas.

4. Conclusion

Three receptor-oriented methodologies have

Table 2Spearman’s rank correlation coefficients for computedprobabilities and concentrations vs. emission values

2y qnss-SO NH NO4 4 3vs. SO vs. NH vs. NO2 3 x

N 446 170 281

PSCF 0.516 0.443 0.6130.0000 0.0000 0.0000

Seibert et al. 0.549 0.482 0.6370.0000 0.0000 0.0000

Stohl 0.602 0.353 0.6270.0000 0.0000 0.0000

Notes. Top row, correlation coefficients; bottom row, P val-ues; N, the number of cells included in the comparison.

been applied to precipitation data to identify thesource locations responsible for high acidic speciesdeposition in a background station at Morvan inFrance. A comparison has been made betweenthe different types of models. The three modelshave identified almost the same emission areas inEurope that are likely to contribute to the in-creasing of acid species in precipitation at thesampling site. These identified areas are similarto the regions known for their high anthropogenicemissions.

Spearman rank-order correlation analysis wasused to compare quantitatively the computedconcentrations of non-sea salt SO2y, NOy and4 3NHq found by the three models with the Euro-4pean emissions of SO , NO and NH . Satisfying2 x 3correlations are found between the computedconcentrations of the three models and the emis-sions. Despite their different constructions, thethree models give suitable results to analyse thesource]receptor relationships for acidic species inprecipitation. Nevertheless, significant differencesbetween the results of the three models appeared.In fact, according to these differences and accord-ing to the objectives of the study, another modelcould be chosen.

v Simple application of the PSCF model pro-vides facilities to find the source locations.

v The Seibert et al. methodology allows identi-fication of the sources and provides computeddata which could be used to examine thequantitative relationships between the mea-sured concentrations and the emissions.

v The Stohl methodology gives concentrationsmaps with a better resolution and could beused in an exhaustive research of sources.

The medium correlation coefficients can arisefrom non-considered factors in these models andfrom uninfluential areas on the receptor site.

This work confirms the results of earlier studieswhich indicate that the long range transport ofpollutants coming from neighbouring countries isthe main cause of rain events containing highconcentrations in acidic species.

Lastly, receptor-oriented methodology is anefficient tool to find the source regions responsi-

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]6362

ble for high concentrations in precipitation col-lected at a background station.

Acknowledgements

The authors would like to thank all the opera-tors of the Morvan station as well as the analyti-cal laboratory members for the quality of thedatabase. We are also grateful to Ms Suez for herliterary remarks and A. Robache for his valuableremarks on this paper.

References

Ashbaugh LL, Malm WC, Sadeh WZ. A residence timeprobability analysis of sulfur concentrations at GrandCanyon National Park. Atmos Environ 1985;19:1263]1270.

Barrett KO, Seland A, Foss A, Mylona S, Sandnes H, Styve H,Tarrason L. European transboundary acidifying air pollu-tion. EMEPrMSC-W Report 1r95, Oslo, Norway: Meteo-rological Synthesizing Centre, 1995.

Billman-Stunder BJ, Heffter JL, Dayan U. Trajectory analysisof wet deposition at Whiteface Mountain: a sensitivitystudy. Atmos Environ 1986;20:1691]1695.

Brook JR, Samson PJ, Sillman S. The relationship betweenupwind SO emissions and SO2y concentrations in precipi-2 4tation at six sites in the Eastern U.S.A. Atmos Environ1993;27A:1765]1779.

Casado H, Encinas D, Lacaux JP. Evaluation of origin anddistribution of wet deposition recorded in the SpanishBasque country. J Environ Sci Health 1995;30:695]712.

Cheng M-D, Hopke PK. A receptor-oriented methodology fordetermining source regions of particulate sulfate observedat Dorset, Ontario. J Geophys Res 1993;98:16839]16849.

Coddeville P, Guillermo R, Houdret JL. Les retombees atmo-´spheriques en France}Reseau MERA, Douai, France:´ ´Report of Mines School, 1993.

Colin JL, Renard D, Lescoat V, Jaffrezo JL. Relationshipbetween rain and snow acidity and air mass trajectory inEastern France. Atmos Environ 1989;23:1487]1498.

Dambrine E, Ulrich E, Cenac N, et al. Atmospheric deposi-´tion in France and possible relation with forest decline. In:Landmann G, Bonneau M, editors. Forest decline andatmospheric deposition effects in the French mountains.Berlin: Springer, 1995:177]199.

Deininger CK, Saxena VK. A validation of back trajectories ofair masses by principal component analysis of ion concen-trations in cloud water. Atmos Environ 1997;31:295]300.

Fangmeier A, Hadwiger-Fangmeier A, Eerden LVd, Jager¨H-J. Effects of atmospheric ammonia on vegetation } areview. Environ Pollut 1994;86:43]82.

Galloway JN, Likens GE, Edgerton ES. Acid precipitation inthe northeastern United States: pH and acidity. Science1976;194:722]724.

Hilst GR, Chapman EG. Source-receptor relationships for wetSO2y and NOy production. Atmos Environ 1990;4 324A:1889]1901.

Hov O, Hjollo BA. Transport distance of ammonia and am-monium in Northern Europe. 2. Its relation to emissions ofSO and NO . J Geophys Res 1994;99:18749]18755.2 x

Jacob Dj, Waldman JM, Muncer JW, Hoffmann MR. Chemi-cal composition of fogwater collected along the Californiacoast. Environ Sci Technol 1985;8:730]736.

Kitto A-BN, Harrison RM. Processes affecting concentrationsof aerosol strong acidity at sites in eastern England. AtmosEnviron 1992;26A:2389]2399.

Liu X, Gao N, Hopke PK, Cohen D, Bailey G, Crisp P.Evaluation of spatial patterns of fine particle sulfur andlead concentrations in New South Wales, Australia. AtmosEnviron 1996;30:9]24.

Loye-Pilot MD, Morelli J. Fluctuations of ionic compositionof precipitations collected in Corsica related to changes inthe origins of incoming aerosols. J Aerosol Sci1988;19:577]585.

Martin D, Mithieux C, Strauss B. On the use of the synopticvertical wind component in a transport trajectory model.Atmos Environ 1987;21:45]52.

Martin D, Bergametti G, Strauss B. On the use of the synopticvertical velocity in trajectory model: validation bygeochemical tracers. Atmos Environ 1990;24A:2059]2069.

Moody JL. The influence of meteorology on precipitationchemistry at selected sites in the eastern United States.PhD thesis: University of Michigan, 1986.

Moody JL, Galloway JN. Quantifying the relationship betweenatmospheric transport and the chemical composition ofprecipitation on Bermuda. Tellus 1988;40B:463]479.

Moody JL, Samson PJ. The influence of atmospheric transporton precipitation chemistry at two sites in the midwesternUnited States. Atmos Environ 1989;23:2117]2132.

Plaisance H, Coddeville P, Guillermo R. A qualitative de-termination of the source locations of precipitation con-stituents in Morvan, France. Environ Sci Technol1996;17:977]986.

Plaisance H, Coddeville P, Guillermo R, Roussel I. Dynamicvalidation procedure for the MERA and French WMO-GAW precipitation chemistry networks. Water Air SoilPollut 1997a;93:267]284.

Plaisance H, Galloo JC, Guillermo R. Source identificationand variation in the chemical composition of precipitationat two rural sites in France. Sci Total Environ1997b;206:79]93.

Probst A, Fritz B, Viville D. Mid-term trends in acid precipita-tion, streamwater chemistry and element budgets in the

Ž .strengbach catchment Vosges mountains, France . WaterAir Soil Pollut 1995;79:39]59.

Sanusi A, Wortham H, Millet M, Mirabel P. Chemical compo-sition of rainwater in Eastern France. Atmos Environ1996;30:59]71.

Seibert P, Kromp-Kolb H, Baltensperger U, Jost DT,Schwikowski M, Kasper A, Puxbaum H. Trajectory analysisof aerosol measurements at high alpine sites. In: The

( )A. Charron et al. r The Science of the Total En¨ironment 223 1998 53]63 63

Proceeding of EUROTRAC Symposium 94. The Hague:Academic Publishing bv, 1994.

Stohl A. Trajectory statistics } a new method to establishsource]receptor relationships of air pollutants and its ap-plication to the transport of particulate sulfate in Europe.Atmos Environ 1996;30:579]587.

Stohl A, Kromp-Kolb H. Origin of ozone in Vienna andsurroundings, Austria. Atmos Environ 1994;28:1255]1266.

Stohl A, Wotawa G, Seibert P, Kromp-Kolb H. Interpolationerrors in wind fields as a function of spatial and temporalresolution and their impact on different types of kinematictrajectories. J Appl Meteorol 1995;34:1927]1932.

Strauss B, Cuiller G, Trajectographie a l’echelle synoptique.`In: DEFORPA program Report, Deperrissement des forets´ ˆattribue a la pollution atmospherique, vol. 2, 1986.´ ` ´

Yin F, Grosjean D, Flagan RC, Seinfeld JH. Photooxidationof dimethyl sulfide and dimethyl disulfide, II: Mechanismevaluation. J Atmos Chem 1990;11:365]399.

Zeng Y, Hopke PK. Comparaison of the source locations andseasonal patterns for acidic species in precipitation andambient particles in southern Ontario. Sci Total Environ1994;143:245]260.