ambient silver concentration anomaly in the finnish arctic lower atmosphere

Ambient Silver ConcentrationAnomaly in the Finnish Arctic LowerAtmosphereM . S H A M S U Z Z O H A B A S U N I A A N DS H E L D O N L A N D S B E R G E R *

Nuclear Engineering Teaching Lab, University of Texas,Pickle Research Campus, R-9000, Austin, Texas 78712

T A R J A Y L I - T U O M I A N DP H I L L I P K . H O P K E

Department of Chemical Engineering, Clarkson University,Box 5705, Potsdam, New York 13699-5705

P A U L W I S H I N S K I

Vermont Air Pollution Control Division,103 South Main Street, Building 3 South,Waterbury, Vermont 05671-0402

J U S S I P A A T E R O A N D Y R J O V I I S A N E N

Air Quality Division, Finnish Meteorological Institute,P.O. Box 503, FIN-00101 Helsinki, Finland

Mean silver concentrations in weekly particle samplescollected at Kevo, northern Finland, were determined forthe period of October 1964-March 1978 by neutron activationanalysis. Two distinct periods were observed in thesilver concentration levels over this time frame. During 1964-1970, mean weekly silver concentration levels werefound in the range of 0.01-190 ng/m3 with an arithmeticmean of 2.19 ng/m3. A few very high silver concentrationlevels (>10 ng/m3) were observed in this period, some ofwhich simultaneously occurred with some of the highestbromine and iodine concentration levels. During 1971-1978,silver concentration levels were in the range of 0.02-0.89 ng/m3 with a mean value of 0.09 ng/m3. The observedconcentration levels in the later period matched wellthe data from the early 1990s reported at Sevettijarvi,northern Finland, about 60 km east of Kevo. Data analysis,historical records for this region, and residence timeanalysis (RTA) using wind back-trajectories show thatoccasional smelting of silver-rich Norilsk ores at the Nikelsmelter, Kola Peninsula, was probably a significantcontributor to elevated mean silver concentration levelsduring 1964-1970. RTA alone was not able to unambiguouslyidentify the most probable source region for highestsilver impacts at Kevo due to the weekly integrated natureof the samples collected. Critical examination of wind back-trajectories (24 per day) for specific high silver, bromine,and iodine concentration weeks was carried out to supplementthe ensemble RTA analysis (2 back-trajectories per day).The supplemental back-trajectory analysis revealedthat deposition of the smelter component silver as well asthe sea components (bromine and iodine) could occurtogether at Kevo during these weekly sampling periods.The study implies that data from weekly integrated samplesare insufficiently time-resolved for RTA methods alone to

unambiguously resolve the sources contributing toambient atmospheric concentrations at Kevo, Finland.

IntroductionArctic air pollutants originate from various sources in Europe,Russia, far East Asia, and North America. Subsequentlyatmospheric transport of natural and anthropogenic emis-sions from mid-latitudes causes the Arctic haze phenomenonduring the winter months in the High Arctic. NorthernFinland, northern Norway, and northwest Russia inside the66°32′ N latitude are known as the European sub-Arctic. Thispart of the sub-Arctic region has received attention inenvironmental research in the past decades mainly becauseof the large industrial activities beginning from the start ofthe last century. Some of the world’s largest emitters of heavymetals and sulfur dioxide are located in the Kola Peninsula,Russia. A wide variety of industrial activities, like ferrous andnon-ferrous smelters or peat-fired power plants, have oper-ated in this region for more than 60 yr. Heavy metal emissionsare much higher for the non-ferrous mining, smelting,roasting, processing of nickel, copper, aluminum, etc. to theatmospheric environment than any ferrous industry (1). AfterWorld War II, the need for minerals and natural resourcesexpedited the rapid expansion of these facilities under thesocialist development policy until 1992 (1).

Beginning in 1921, various ore bodies have been discov-ered in Kola Peninsula. The location of Kevo in northernFinland and parts of northern Norway and the Kola Peninsulaare shown in Figure 1. In 1932, a nickel smelter was built atNikel for smelting local ore bodies. In 1938, a larger nickelsmelter was built at Monchegorsk. In 1965, a roasting plantat Zapoljarnij was built after discovering a good quality orebody in 1956 (2). Since 1938, at Monchegorsk good qualitynickel ores of the local Pechenga area, near Zapoljarnij, weresmelted.

However, these ores were quickly exhausted, and veryhigh quality ore bodies, rich with nickel, cobalt, silver, gold,and platinum, were discovered in Norilsk, northern Siberia.Norilsk is an isolated place and had no road or rail links tocentral Russia. The lack of a transportation system fromNorilsk to major Russian cities and the extreme Siberianweather prohibited any attempt to develop a completesmelting facility at Norilsk. Thus, it was decided in 1964 toship Norilsk ore to the Kola region for processing. Initiallythe transportation was seasonal. In 1969, ships from Norilskreached the Kola Peninsula as late as November. Later theshipping season was lengthened from 5 to 10 months andresulted in an increase in ore processing from 600 000 tonin 1970 to 1 million ton in 1977 (3). Atmospheric emissionsin the European sub-Arctic region resulted from the smeltingof these different quality ore bodies in the Kola Peninsulasmelters during the last century.

While many episodic studies on particle chemical com-positions have been reported for different locations aroundthe circumpolar Arctic (4-8), there are a few data setsavailable with systematic long-term particulate matter col-lection and analysis (9-13). A long-term (1980-1995)systematic particle sampling and chemical characterizationat Alert (82°5′ N, 62°3′ W) in the Canadian Arctic is reportedin detail by several authors (14-16). Among these results,silver concentrations were only reported at Sevettijarvi,Finland; Ny A° lesund and Vardø, Norway; and North EarthArchipelago, Russia, from episodic studies (12, 13, 17).

Historical long-term (October 1964-February 1978) weeklyair particulate samples archived in Finland have been

* Corresponding author phone: (512)232-2467; fax: (512)471-4589;e-mail: [email protected].

Environ. Sci. Technol. 2003, 37, 5537-5544

10.1021/es034004q CCC: $25.00 2003 American Chemical Society VOL. 37, NO. 24, 2003 / ENVIRONMENTAL SCIENCE & TECHNOLOGY 9 5537Published on Web 11/11/2003

analyzed for Ag, Al, As, Br, Ca, Cl, Co, Cu, I, In, K, Mn, Na,Sb, Se, Si, Sn, Ti, V, W, and Zn using neutron activationanalysis (NAA) (18). These data provide the longest and mostcontinuous set of concentrations ever reported for the sub-Arctic region. Locations of the various types of industry anddistances around the sampling location from Kevo arepresented in Table 1. In this paper, only the silver concen-trations at Kevo are presented and discussed relative to someother elements.

Sampling and AnalysisThe Finnish Meteorological Institute (FMI) collected totalsuspended aerosol particle samples in Kevo (69°45′ N, 27°02′E, 98 m above the sea level) during the period of late October1964 to early March 1978. Their primary purpose was to

monitor for potential airborne radioactivity arising fromSoviet nuclear tests. A schematic diagram of the samplingarrangement is presented in Figure 2. The sampling unit hadtwo filters. Each filter was lead shielded and equipped witha Geiger Muller (GM) counter for radioactivity measurement.

During a week-long sampling period, the airflows werealternatively directed for 4 h through each of the filters, andthe aerosol radioactivity was continuously recorded fromboth online and offine filters. The air inlet was 7 m highabove the ground. The particles were collected on Whatman42 paper filters. The sampling procedure generated two filtersper week, which were combined to give a total of 685 samplesfor the studied period (∼13.2 yr × 52 week). These sampleswere analyzed in a single batch to obtain the mean weeklyconcentration levels in the Kevo ambient atmosphere.

TABLE 1. Location, Distance, and Industrial Activities around Kevo

sampling locationat Finland (a)

industriallocations (b)

approximate distancefrom a to b (km) type of industry

Kevo(69°45′ N, 27°03′ E)

Kirkenes, Norway(69°41′ N, 30°02′ E)

115 iron ore mine and mill

Gallivare, Sweden(67°10′ N, 20°39′ E)


Kiruna, Sweden(67°51′ N, 20°14′ E)


Nikel, KPa

(69°25′ N, 30°15′ E)134 nickel smelter

Zapoljarnij, KP(69°30′ N, 30°43′ E)

145 nickel ore roasting

Murmansk, KP(69°02′ N, 33°15′ E)

256 large harbor town with related industries,base of about 150 nuclear-powered vessels

Kovdor, KP(67°35′ N, 30°40′ E)


Monchegorsk, KP(67°51′ N, 32°48′ E)

313 nickel, copper, and cobalt smelters

Olenegorsk, KP(68°08′ N, 33°30′ E)

314 iron ore mining and mill

Apatity, KP(67°40′ N, 32°47′ E)

327 thermal power station, processing of apatite ore

Kandalaksha, KP(67°13′ N, 32°13′ E)

352 aluminum smelter, nuclear power station

Kirovsk, KP(67°36′ N, 34° E)

370 apatite open pit mine

a KP ) Kola Peninsula.

FIGURE 1. Locations of Kevo and important industrial cities in thisregion.

FIGURE 2. Schematic diagram of the aerosol sampling unit in Kevo.

5538 9 ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 37, NO. 24, 2003

Silver in the filters was determined by epithermal NAA.Each of the filters was irradiated by epithermal neutrons for1 min at the University of Texas 1-MW nuclear researchreactor facility, followed by a 25-s decay time and 100-scounting time with a high-purity germanium (HPGe) γ-rayspectrometry system. Silver concentrations were determinedby measuring the induced radioactivity of 110Ag (half-life )25 s) isotope in the aerosol filters. Irradiation and countingof all the samples were carried out within a 2-week period.The measurements were calibrated using a silver solution,and quality control was maintained by analyzing the standardreference material Gold Ore-CH2 from the Canada Centerfor Mineral and Energy Technology. Our result of 25.1 ( 2.6ppm agreed very well with the certified value of 24.2 ( 2.0ppm. Neutron flux was normalized for each of the sampleirradiation days using sulfur powder irradiation. Otherelements, like Cu, In, Sn, Zn, Br, I and Na, are determinedin all the samples by thermal and epithermal NAA anddiscussed elsewhere (18).

Residence Time AnalysisThe Residence Time Analysis (RTA) technique is a probabilitymetric to identify the potential source locations affecting thereceptor site for a series of measured ambient species usinga back-trajectory ensemble. The technique used in this workhas been previously described (19, 20).

Air parcel back-trajectories were computed using theHYSPLIT_4 model (21) developed at the National Oceanicand Atmospheric Administration (NOAA). The output ofHYSPLIT_4 provided text files containing end points of hourlylatitude, longitude, height, etc. of an air parcel. The use ofthese end points to develop a probability metric on a griddedarray of cells in and around the receptor location is the keytechnique to locate the likely emission sources of air pollution.The metric first calculates a total residence time probabilityfor each grid square considering all air parcel back-trajectoriesduring the sampling period. Then a second residence timeprobability is calculated using only the back-trajectoriesassociated with the high concentration subset sampling daysfor an element of concern (e.g., silver), called the high-valueresidence time probability. The difference between the high-value and the total residence time probabilities representsthe incremental probability for the concerned ambientelement. Grid cells with the highest incremental probabilitiessignify potential source locations for the high concentrationmeasurement days for that element. Finally, gridded arrayplots can be created for the incremental probabilities,producing a visual display to help identify the source region-(s). The incremental probability can be calculated for a gridsquare (i,j) by the following equation:

where TR(i,j) is the total residence time for all the trajectoriesover grid square (i,j); TR(i,j)

h is the total residence time for allthe trajectories related to high subset samples over grid square(i,j) and can be calculated by

and

In this work, a gridded domain of 500 × 500 cells with celldimension 10 km × 10 km was used for RTA over and around

Kevo. Two back-trajectories were computed per day at 6:00and 18:00 UTC at a starting height of 500 m using HYSPLIT_4for a 5-day (120-h) period. Thus, for a weeklong samplingperiod, 14 back-trajectories represent the total air masshistory for a particular sample. A total of 9608 back-trajectories were computed for the whole sampling periodfrom 1964 to 1978 and used in RTA. The total residence timeprobability for each of the cells was calculated using alltrajectories, while the high-value RT probabilities wereevaluated for a subset of trajectories associated with the 7%highest silver concentrations for each of the 1964-1970 and1971-1978 periods. The 2% highest silver concentrationswere also examined during these periods in order to try todistinguish influence at the receptor on the very highest silvermeasurement days. Several high-subset cutoff values wereconsidered, ranging from the highest 2% (very exclusive) tothe highest 10% (inclusive of many moderate values)measurement weeks. For these data set of weekly integratedsamples, the 7% level was the most inclusive cutoff usedbecause it was the cutoff that began to resolve incrementalprobability patterns over the gridded region.

ResultsMeasured Data. The measured weekly mean silver concen-trations along with bromine and iodine in the Kevo atmo-sphere are presented in Figure 3 as time-series plots. As canbe seen in Figure 3a, silver concentrations present two verydifferent patterns during 1964-1970 and 1971-1978. Mostof the silver concentrations were above the detection limitand had only 13% below detection limit (bdl) data pointsduring 1964-1970. A few very high silver concentration levels(>10 ng/m3) were observed in this period, some of whichsimultaneously occurred with the highest bromine and iodineconcentration levels in 1965, 1966, and 1969. However, inthe period of 1971-1978, 73% bdl data points were found forsilver concentrations at Kevo. In the earlier period, anarithmetic mean of 2.19 ng/m3 was found with a few highvalues around 100 ng/m3. In the later period, an averageabout 0.1 ng/m3 was observed with no value higher than 1ng/m3. Virkkula et al. (17) reported average silver concentra-tions at Sevettijarvi, 60 km east from Kevo, of 0.09 and 0.13ng/m3 for fine and coarse particles, respectively. Other silverdata with the statistical results of the present work arepresented in Table 2. As can be seen from Table 2, an averagevalue of silver was 4.0 ( 10.0 ng/m3 in North EarthArchipelago, Russia (12). It was reported from a one-spring-month sampling period in 1988. It may be noted that thisvalue was much higher than the other two measurements in1985 and 1986 and possibly represented a special case.Statistically, this average value is comparable to 2.19 ( 13.92ng/m3 for the period of 1964-1970 in the present work.

A correlation study of 20 elements, determined in thiswork, showed a strong correlation of silver with bromineand iodine and a weak correlation with the other non-ferroussmelter elements such as copper, indium, tin, zinc, etc. It isobserved that simultaneous occurrence of high silver,bromine, and iodine in some samples worked as leverage inthe correlation study and showed a strong correlation amongthem, suppressing any significant correlation of silver withthe other non-ferrous smelter elements such as copper,indium, tin, zinc, etc. The first 10 highest silver concentrationsare presented in Table 3 with sampling periods along withthe corresponding bromine and iodine concentration levels.It was found that measurements for sample numbers 233,35, 232, 49, 87, and 230 represented some of the highestvalues of silver, bromine, and iodine in the database. Theobservations might be interpreted as implying that thesethree elements were coming from the same source and poseda great puzzle in this work. Also of interest is the fact that

TRIP% ) (TRp(i,j)h - TRp(i,j)) × 100

TRp(i,j) ) (TR(i,j)/∑i)1

l

∑j)1

m

TR(i,j))

TRp(i,j)h ) (TR(i,j)

h /∑i)1

l

∑j)1

m

TR(i,j)h )

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the highest six weekly measurements of silver were all inthese six samples, taken during the period 1964-1970. Usingdetailed analysis of individual daily back-trajectories duringthe weekly sampling periods, interpretation of the RTA plots,

and data analysis, both the puzzling silver concentrationanomaly and its strong correlation with the sea components(bromine and iodine) are resolved and presented in thefollowing sections.

FIGURE 3. Time-series plots of the silver, bromine, and iodine concentration levels measured in Kevo, northern Finland.

TABLE 2. Silver Statistical Data of This Work and Literature Data of the Arctic Region

description bdla

this work, Kevo, Finland 1964-1970 avg ( SD median 2.19 ( 13.92 0.31 13%(69°75′ N, 27°02′ E) 1971-1978 avg ( SD median 0.09 ( 0.12 0.02 73%

Sevettijarvi, Finland (17) 1992-1994 fine avg ( SD 0.09 ( 0.05(69°35′ N, 28°50′ E) 1992-1994 coarse one sample 0.13

North Earth Archipelago, Russia (12) 1985 avg ( SD 0.12 ( 0.07(79°5′ N, 95°4′ E) 1986 avg ( SD 0.16 ( 0.26

1988 avg ( SD 4.0 ( 10.0Ny A° lesund, Norway (13) 1983, 1984, & 1986 winters median 0.52

(78°9′ N, 11°9′ E) 1984 summer median 0.01Vardø, Norway (13) 1983 & 1984 winters median 0.016

(70°4′ N, 31°1′ E) 1984 summer median <0.010a bdl ) below detection limit.

TABLE 3. Sample Week, Duration, and 10 Highest Concentration Levels of Silver with Corresponding Bromine, Iodine, and Sodium

sample no. sampling dates Ag (ng/m3) Br (ng/m3) I (ng/m3) Na (ng/m3)

233 05/12/69-05/19/69 190.7 ( 2.7 144.5 ( 1.7 0.97 ( 0.01 166.6 ( 2.135 06/23/65-06/28/65 118.4 ( 1.8 108.7 ( 1.2 0.60 ( 0.01 168.0 ( 2.2

232 05/05/69-05/12/69 77.6 ( 1.1 114.2 ( 1.2 0.78 ( 0.01 278.1 ( 3.649 10/11/65-10/18/65 60.0 ( 0.9 58.5 ( 0.6 0.44 ( 0.01 679.0 ( 7.287 07/25/66-08/01/66 25.9 ( 0.4 19.7 ( 0.2 0.63 ( 0.01 248.2 ( 3.0

230 04/21/69-04/28/69 16.6 ( 0.3 17.3 ( 0.3 0.49 ( 0.01 322.2 ( 3.66 11/23/64-11/28/64 7.8 ( 0.2 2.7 ( 0.2 0.65 ( 0.01 190.9 ( 3.0

15 01/28/65-02/01/65 4.4 ( 0.1 1.6 ( 0.1 0.70 ( 0.01 278.2 ( 3.378 05/23/66-05/30/66 4.4 ( 0.1 6.4 ( 0.1 0.56 ( 0.01 400.0 ( 4.413 01/11/65-01/18/65 3.8 ( 0.1 0.6 ( 0.1 0.68 ( 0.01 207.4 ( 3.0


RTA Results. The RTA incremental probability plots using7% highest subsets of the silver data are presented in Figure4a,b for the periods of 1964-1970 and 1971-1978, respec-tively. The 7% highest subset was selected from a numberof repeated trials to obtain better resolution plots consistentwith some known elemental source regions, particularly seacomponents. The 0.00125% incremental probability isoplethof the RTA plot shown in Figure 4a identifies, as probablesource locations for silver during the 1964-1970 period, anarea of northern Finland and a western portion of the KolaPeninsula including the Nikel area. Within the same isoplethvalue can be seen a region of the sea to the north of Nikel,consistent with high sodium and iodine associated with highsilver in this time period. Figure 4b indicates the Monchegorsksmelter as being in the center of the most probable sourcelocations for silver (although average values were much lower)during the 1971-1978 period, which is consistent with otherliterature reports (2). In Finland, open-pit chromate miningbegan in 1968 at Kemi (65°47′ N, 24°42′ E) by the north-

ernmost bay of the Baltic Sea. There has been ferrochromeproduction at nearby Tornio (65°46′ N, 24°11′ E) since 1968,and a stainless steel plant has been in operation in Torniosince 1976. However, there no noticeable high silver con-centration levels were observed in the moss study from thecentral or northern Finland (2). On the basis of this, althoughthe RTA results in Figure 4a identify northern Finland as apotential source region, it is unlikely that the high silvermeasurements during the 1964-1970 period at Kevo origi-nated in this region. Nikel, with a known smelter, appearsto be the most likely source area for high silver levelsmeasured at Kevo in this period.

The 7% high-subset incremental probability results shownin Figure 4a are seen to be somewhat ambiguous. Withoutadditional information about the actual sources of silver beingabsent in the northern Finland region, there might be noreason to discount that high probability location. The use ofweekly integrated samples is suspected as being a possiblereason for this ambiguity. Also, since the 7% high-value subset

FIGURE 4. (a) RTA incremental probability percent plots for silver using highest 7% subset from 1964 to 1970. (b) RTA incremental probabilitypercent plots for silver using highest 7% subset from 1971 to 1978.


contains approximately 24 weeks of samples during each ofthe two time periods, this cutoff level is too inclusive to

actually pinpoint the six unusually high silver measurementstaken in the earlier period that are seen to be anomalous for

FIGURE 5. RTA incremental probability plots for silver using highest 2% subset (color scales are relative and not consistent among plots).Panels a and b were created by averaging the RTA incremental probabilities of the nearest 9 × 9 grid cells, and panels c and d werecreated by averaging the RTA incremental probabilities of the nearest 5 × 5 grid cells.

FIGURE 6. RTA incremental probability plots for silver using highest 3.5% subset.


the entire measurement program from 1964 to 1978. MoreRTA plots were generated using gradually less inclusive valuesfor the high-value subset for the periods of 1964-1970 and1971-1978. The 2% high-value subset was selected becauseof its highly distinct values in the 1964-1970 period. At the2% level, this represents only 6 weeks in each of the two timeperiods. This cutoff was used to clearly focus on the probablesource locations for the anomalous high levels of silvermeasured in the Kevo atmosphere. At this level of exclusionhowever, the RTA results become more and more compro-mised by the lack of temporal resolution of the samples.Examination of individual back-trajectories for each of thesix highest silver sample weeks confirms that a sampleintegrated over any week was influenced by different locationson different days during the weekly period.

Figure 5a-d shows 2% high-value subset RTA plots forincremental probability. The figure also illustrates the effectof employing a technique to try to smooth the blotchy resultthat is inevitable when plotting grid square incremental valuesthat are generated from relatively few back-trajectories. Figure5a,b was created by averaging the RTA incremental prob-

abilities of the nearest 9 × 9 grid cells (81 cell average), andFigure 5c,d was generated by averaging the incrementalprobabilities of the nearest 5 × 5 grid cells (25 cell average).As can be seen in Figure 5, panels a and c, which representthe 1964-1970 time period, the most probable location fora silver source is Nikel in this time period. However, in Figure5, panels b and d, representing the 1971-1978 time period,the higher incremental probability locations do not includethe Monchegorsk area at all, although it was a known smeltinglocation of Norilsk ore after 1971.

For the period of 1964-1970, the 2% highest value subsetwas very distinct because of its very high concentrations,about 2 orders of magnitude higher than the rest of the data.During the period 1971-1978, the concentration levels wereall very similar to one another with no truly high valuesseparable into a distinctly high-value subset, which inconjunction with the weekly integrated nature of the samples,meant that RTA methods during this period were not ableto produce meaningful source patterns at the 2% high-valuelevel. Figure 6 shows the RTA analysis at a less exclusive 3.5%high-value cutoff. The plots are limited to the immediate

FIGURE 7. Sample number vs concentration levels for Ag, Cu, In, Sn, and Zn. For samples 233, 239, 6, and 40 the trend of Ag concentrationmatches very well with the other smelting component elements (legends are same for all three panels).


region around Kevo to more clearly show the source regionsidentified. Figure 6 shows results comparable to Figure 4,and as with the 7% highest silver subset case, the results forthis 3.5% high-value analysis clearly indicate a predominantsilver influence from Monchegorsk during the period 1971-1978, consistent with literature reports.

Silver Concentration Anomaly. It has been shown thatduring the 1964-1970 period, Nikel, approximately 134km from Kevo, was a more likely source location for theelevated silver concentration levels in the Kevo atmosphere.It is reported that Nikel smelters mainly smelted localPechenga ore and occasionally Norilsk ore (22), and thesmelter in Monchegorsk smelted Norilsk ore from 1971onward (3). It may be noted that Norilsk ores were rich insilver (2). Thus, on the basis of all the historical records, dataanalyses, and RTA plots, it is hypothesized that the high silverconcentrations observed at Kevo during 1964-1970 werecaused by occasional smelting of silver-rich Norilsk ores atthe Nikel smelter. Smelting of silver-rich Norilsk ore inthe Monchegorsk smelter during 1971-1978 had a lesserinfluence (note relatively weaker incremental probabilitysignal in Figure 6) on ambient silver concentration levelsat Kevo partially due to its greater distance from Kevo(∼313 km).

Silver Correlation with Sea Components. The correlationstudy showed strong correlation of silver with bromine andiodine only. However, data analysis showed that severalhighest sodium concentration levels of the database werealso associated with samples 233, 232, and 6 as can be seenin Table 3. Extensive study of the hourly air parcel back-trajectory paths for the concerned samples showed that seacomponents (like Br, I, and Na) that were deposited into thefilters sometimes during the earlier part of the week camedirectly to the sampling location from locations over theBarents Sea, the Norwegian Sea, or the Gulf of Bothnia. Thesmelting component silver was deposited in the same filterin the later part of these weeks when air parcels passed overthe Kola Peninsula.

Silver concentration levels with other non-ferrous smeltingcomponents such as Cu, In, Sn, and Zn for a few samplesaround the samples with the highest silver content arepresented in Figure 7 to illustrate an expected correlationamong these smelting components. As can be seen for samplenumbers 6, 40, 233, and 239 in Figure 7a-c, all these smeltingcomponents show a similar trend for the concentration levelsin the same samples. This clearly supports their associationwith the same source affecting the Kevo atmosphere.

On the basis of all aforementioned analysis, facts, andobservations, it is concluded that elevated ambient high silverconcentration levels observed in the Kevo atmosphere during1964-1970 were caused by the occasional smelting of silver-rich Norilsk ore at the Nikel smelter. The combination of thesmelting component (silver) with some sea componentelements occurred due to the 7-day sampling period, duringwhich day to day patterns of atmospheric transport over

both the marine region and the Kola Peninsula contributedto high deposition of these elements in some samples.

AcknowledgmentsThis work is supported by the International Arctic ResearchCenter/CIFAR.

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(22) Reimann, C.; de Caritat, P.; Halleraker, J. H.; Finne, T. E.; Boyd,R.; Jæger, Ø.; Volden, T.; Kashulina, G.; Bogatyrev, I.; Chekushin,V.; Pavlov, V.; Ayras, M.; Raisanen, M. L.; Nishkavara, H. Atmos.Environ. 1997, 31, 3887-3901.

Received for review January 3, 2003. Revised manuscriptreceived September 14, 2003. Accepted September 22, 2003.

ES034004Q


ambient silver concentration anomaly in the finnish arctic lower atmosphere

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