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Composition of the Finnish Arctic aerosol: collection and analysis of historic filter samples
AE International – North America Atmospheric Environment 37 (2003) 2355–2364
Composition of the Finnish Arctic aerosol: collection and analysis of historic filter samples Tarja Yli-Tuomia, Lisa Vendittea, Philip K. Hopkea,*, M. Shamsuzzoha Basuniab, Sheldon Landsbergerb, Yrjo. Viisanenc, Jussi Paateroc a
b
Department of Chemical Engineering, Clarkson University, Box 5705, Potsdam, NY 13699-5705, USA Nuclear Engineering Teaching Laboratory, University of Texas, Pickle Research Campus, Building 159, R-9000, Austin, TX 78712, USA c Air Quality Division, Finnish Meteorological Institute, P.O. Box 503, FIN-00101 Helsinki, Finland Received 11 February 2003; accepted 17 February 2003
Abstract Week-long samples of total suspended particles have been collected between October 1964 and February 1978 from the Finnish Arctic. Neutron activation analysis, ion chromatography, and light-absorption techniques have been used to analyze the concentration of several heavy metals and other elements, major ions, methane sulfonate (MSA), and black carbon. Kevo is located near the Kola Peninsula and the effect of the industrial area can be seen. Compared to previous studies of Arctic aerosols carried out in North American Arctic, the Kevo results show higher concentration of anthropogenic pollutants and the seasonal variability for most constituents is weaker than the typical Arctic haze pattern. MSA, a marker of biogenic activity, has a clear seasonal cycle with a peak from April to August. r 2003 Elsevier Science Ltd. All rights reserved. Keywords: Time series; Heavy metals; Methane sulfonate; Arctic Haze; Kola Peninsula
1. Introduction The occurrence, nature, origin, transport and effects of the Arctic aerosol have been the subjects of active research since 1970. The aerosol concentration in the Arctic has a strong seasonal variation generally characterized by a winter maximum and summer minimum. A review of Arctic haze phenomenon by Shaw (1995) concludes that the seasonal variation is a result of combination of variability in long-range transport of air (Miller, 1981; Raatz and Shaw, 1984; Raatz, 1989), the atmospheric blocking phenomenon (Iversen and Joranger, 1985), pollutant removal processes (Barrie et al., 1981, 1989), the oxidation of SO2 (Barrie and Hoff, 1984; Barrie and Barrie, 1990), and the thickness of *Corresponding author. Tel.: +1-315-268-3861; fax: +1315-268-6610. E-mail address: [email protected] (P.K. Hopke).
surface temperature inversions (Sakunov et al., 1990). During the winter, particles originate mainly from anthropogenic sources, while in summer, the lower concentrations are contributed mainly by natural sources. Glacial ice cores reveal that pollution of the Arctic can be observed to begin in 1912 and has increased significantly since 1956 (Barrie et al., 1985). However, there are relatively few long-term studies of the composition of the Arctic aerosol. The Canadian Aerosol Sampling Network began a routine aerosol sampling at Alert, Northwest Territories on July 1980 and the results have been reported for a time period of up to 16 yr (Barrie and Hoff, 1985; Li and Barrie, 1993; Li et al., 1993; Sirois and Barrie, 1999; Xie et al., 1999a,b). The Interagency Monitoring of PROtected Visual Environments (IMPROVE) has collected aerosol data from March 1988 to February 1995 at Denali National Park in Alaska. The National Park Service
1352-2310/03/$ - see front matter r 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016/S1352-2310(03)00164-X
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Fig. 1. Location of Kevo in the Northern Scandinavian peninsula.
has performed aerosol measurements in additional six sites in Alaska between 1986 and 1992 (Polissar et al., 1998). For this study, the chemical composition of weekly aerosol samples collected between 1964 and 1978 from Finnish Arctic were measured to provide a data set for more than 13 yr. These samples were collected by the Finnish Meteorological Institute (FMI) in order to monitor atmospheric radioactivity. The analysis of this data will provide information about the sources of haze in European Arctic, the long-term changes in the source composition and contribution, as well as their potential source areas. In prior studies of the composition of particles from a long time series of samples collected at Alert, a component representing biogenic sulfur emissions from marine algae was observed. This component was characterized by the presence of methane sulfonate (MSA) and its year-to-year intensity was highly correlated with the northern hemispheric temperature anomaly (Xie et al., 1999a,b). MSA concentration was determined from the Kevo samples in order to test the hypothesis that a relationship between biogenic sulfur particle concentrations and temperature can be observed as part of a climate–biosphere interaction.
The procedures of sampling and chemical analysis along with the results of chemical composition, time series and correlations are reported in this paper. The data is also being analyzed by multivariate methods combined with back trajectory data and those results will be presented in a subsequent report.
2. Sampling and analysis 2.1. Sampling site FMI has been collecting aerosol samples in Northern Finland at Kevo since October 1964. The Kevo Subarctic Research Institute (latitude 69 450 N, longitude 27 020 E, height 98 m) is located about 350 km north of the Arctic circle (Fig. 1). The site belongs to the birch sub-zone of the boreal coniferous forest. The topography of the surrounding area is characterized by gently sloping fell highlands with river valleys. The elevation is mostly between 100 and 400 m above sea level. The area is sparsely populated (0.4 inhab. km2). In the summer, the sun shines without setting from mid-May till the end of July, and remains below the
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horizon from late November to mid-January. The mean temperature of the coldest month (January) is 16 C and the warmest month (July) +13 C. The annual mean temperature is 2 C. The ground is covered with snow from October to mid-May. There were four buildings at the station area when the measurements were started in 1964. Between 1968 and 1978, six other buildings were built. The most likely source of local aerosols is the wood-heated sauna, which is used often during the spring and summer. The heating system of the meteorological station was changed from wood burning to electricity in 1971. Before 1984 there was no road to the station. It was reached by boat during the summer and along an ice road during the winter. 2.2. Sample collection The reason for the aerosol sampling is to monitor natural and artificial radioactivity in the air. The schematic diagram of the sampling system is shown in Fig. 2. Air is drawn alternately through two filters in 4 h time periods. The beta activity accumulating onto the filters is continuously recorded by two cylindrical Geiger–Muller . counters. Rn-222 activity concentration can be calculated from the count rate. Filters are located inside lead shields to reduce background count rates (Paatero et al., 1994). The filters are changed once a week, and thus the two filters constitute the aerosol sample for the week-long period. The sampler is not equipped with size-selective inlet and therefore total suspended particles are collected. The air inlet tube is drawn through the roof of a house and the sampling height is about 7 m above ground level. We have 685 weekly samples from October 1964 to February 1978. During that time period, rectangular 12 cm 14 cm-sized Whatman paper filters (Grade 42) were used and the collection flow rate was about 7 m h1 giving a total sample volume of 1200 m3. After February 1978, circular 24 cm diameter glass fiber filters and a flow rate of 25 m h1 were used, but these filters have not been analyzed for chemical composition. 2.3. Chemical analysis After the filters were removed from the device, they were sent to Helsinki to the FMI Air Quality Department, where they were analyzed for Pb-210 6 months after sampling ((Paatero et al., 1998)). The Pb-210 activity concentrations (Paatero et al., 2000), Rn-222 (Aaltonen et al., 2001) and total beta activity (Finnish Meteorological Institute, 1984) results have been reported earlier. The filters have been stored at room temperature in an envelope with other filters from the same year. A silk
Fig. 2. Schematic diagram of the sampling system.
paper was used to separate the weekly samples. For this research the weekly 12 cm 14 cm filters were cut into two equal pieces using a laminar flow clean bench at FMI. Half of each filter was retained in the FMI archives, while the other half was brought to Clarkson University and further cut into two pieces. One quarter of each filter was used for black carbon (BC) and ion chromatograph (IC) analysis at Clarkson University and the other quarter was sent to University of Texas, Austin, for instrumental neutron activation analysis (INAA). The two filter strips from the two sample lines from the same week were combined to produce one sample. Before analysis, the samples were stored in tightly sealed plastic bags at room temperature at Clarkson University. 2.3.1. Light transmission for BC The BC concentration was analyzed by using diffuse light transmission method. Light attenuation (ATN) is linearly related to the BC mass loading (SBC ) on the filter by the relation: ATN ¼ 100 lnðII01 Þ ¼ BATN SBC ;
ð1Þ
where I0 is the light intensity after passing a blank filter, I the light intensity after passing a particle-loaded filter and BATN is the specific attenuation coefficient (Ballach et al., 2001). In this study, a specific attenuation coefficient of 15 m2 g1 was used according to the recommendation of Tony Hansen (Hansen, 2000).
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Since there were no blank filters available from the same time period as the sample filters, new Whatman 42 paper filters were used as blanks. The average light intensity transmitted through the blank filter was used in the calculations. The blank was very close to the cleanest sample filters from summer periods; so the blank correction for BC appears to be reasonable. Both ends of each filter strip were measured and an average of the four results represents the sample concentration. The difference between the two strips was 7% on average, but in some samples, up to 65% illustrating the effect of the time of day and short episodes of high concentration. 2.3.1.1. IC analysis. For IC analysis, the samples were extracted into 20 ml of chloroform-saturated ultra-pure water (specific resistance=18.3 MO cm) for 24 h in room temperature. Chloroform was used to prevent potential bacterial activity. After the extraction, the samples were stored in a refrigerator. The aliquot of the sample was filtrated with a GHP syringe filter for anion analysis and IC syringe filter for cation analysis. A DX-500 ion chromatograph with a GP50 gradient pump and ED50 electrochemical detector was used in the analysis of major anions (Cl and SO2 4 ), MSA and cations (Na+, K+, Mg2+ and Ca2+). SRS-ULTRA suppressors were used to reduce the baseline conductivity and therefore the background noise. The MSA and major anions were separated with AS4A-SC column using a gradient of 5–28 mM Na2B4O7. The cations were analyzed with a CS12A column and 22 mM H2SO4 eluent. Double injections of 200 ml were used for all samples to ensure the results. Five percent of the samples were repeated in the next batch and the uncertainty was determined based on the reproducibility. The detection limit was determined by the EPA 40 CFR 136, Appendix B method. All the ions in all samples were above the analytical detection limit, but due to blank correction, 38% of blank corrected chloride values were negative. Anion standards were prepared at Clarkson University from A.C.S. certified chemicals. Dionex Six Cation Standard II was used for cations. New Whatman 42 paper filters were used as blanks. 2.3.2. Instrumental neutron activation analysis The instrumental neutron activation analysis (INAA) analysis was performed at the TRIGA MARK II research reactor facility, University of Texas, Austin. Three separate irradiations were performed for each filter, followed a counting by high-purity germanium (HPGe) gamma spectrometry system. The elements analyzed were Al, Ca, Cl, Cu, Mn, Na, Ti and V with 2 min thermal short irradiation, Ag with 1 min and As, Br, Co, I, In, K, Sb, Si, Sn, Zn, and W with 10 min epithermal short irradiation. Selenium was separately
determined in the filters using the short-lived 77mSe (T1=2 ¼ 17:4 s). Each filter was irradiated for 10 s and counted for 50 s after a decay time of about 17 s. New Whatman 42 filters were used for blank correction. The combined filters occupied a volume of about 3 ml in the pneumatic vial. Inside the carrier vial, another 2/ 5th dram vial was placed on top of the filter containing about 500 mg sulfur powder. Sulfur powder was used to normalize the neutron flux for each sample irradiation. All calibrations for elemental concentration determination were done using monoelemental standard solutions from the National Institute of Standards and Technology (NIST) or from laboratory chemicals. NIST Standard Reference Material (SRM) coals 1632a, 1632b, and 1632c, citrus leaves 1572, oyster tissue 1566a, and San Joaquin Soil 2709 were analyzed for quality control on the process. For silver determination, samples were manually counted without transferring the filter from the irradiated vial. However, for all other irradiations, all of the samples were transferred to a non-irradiated vial and counted both in the normal and Compton modes by the HPGe gamma spectrometry system.
3. Results Table 1 lists the chemical constituents analyzed together with the analytical method, geometric mean and standard deviation, detection limit and the percentage of values below the detection limit. In addition to the measured values, non-sea-salt sulfate has been calculated by subtraction of 0.2529 times the sodium concentration. Since sodium was measured by both IC and INAA, the distributional parameters for both values are provided. For W, Ag, and Ca (INAA), more than 40% of the samples are below the detection limit. Difficulties in Cl results resulted from the blank problems. In the IC analysis, all of the samples had Cl concentration higher than the analytical detection limit, but due to high Cl concentrations of the new filters used as blanks, the blank subtraction produced many negative values. The filter chlorine concentrations may have changed during the years of sampling so that it is not possible to obtain a reliable blank value for Cl. Thus, both the IC and INAA results of Cl have been excluded from the data analysis. For three elements (Na, K and Ca), comparison between the two different techniques is possible. Linear regression analysis (Table 2) shows good agreement between IC and INAA for Na. The squared correlation coefficient between the two sets of Na values is 0.999 with a slope of 1.003+0.001 and an intercept of 62+2 ng m3. The reason for this might be a slight variation across the filter deposit, or incomplete dissolution of the sodium into the extraction volume.
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Table 1 The analytical method, geometric mean and standard deviation, detection limits (ng m3), and percentage of data below the detection limit Constituent
Ag Al As Br Ca Co Cu I In K Mn Na Sb Si Se Sn Ti V W Zn BC MSA SO2 4 Na+ + K Mg2+ Ca2+ nss-SO2a 4 nss-SO2b 4 a b
Analytical method
INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA Optical IC IC IC IC IC IC IC-IC IC-NAA
Geometric mean
0.15 34.5 0.61 2.07 54.5 0.06 12.8 0.85 0.00 74.7 1.23 250 0.19 222 0.104 2.49 5.86 0.43 0.09 18.7 238 9.54 1319 235 97.4 14.2 49.0 1310 1223
Geometric std
3.76 1.81 3.03 2.05 1.73 2.34 1.70 1.49 2.09 1.57 2.06 1.59 2.37 2.02 2.38 2.17 1.92 3.01 1.30 1.72 2.07 3.95 2.18 1.57 1.63 1.93 1.70 1.94 1.92
Detection limit
Below DL (%)
from
to
0.03 0.40 0.01 0.06 11.3 0.00 0.53 0.00 0.00 3.33 0.09 1.92 0.01 18.2 0.03 0.11 1.34 0.01 0.01 2.39 25.0 0.05 4.22 0.47 3.44 0.05 0.16 146 88
0.63 14.7 0.20 1.39 278 0.28 8.04 0.06 0.04 59.3 1.27 22.0 0.17 329 0.65 3.06 23.4 0.13 0.65 36.7 711 1.22 99.7 11.0 81.4 1.10 3.73 10,906 10,820
41 0 0 0 51 14 0 0 0 0 0 0 0 1 31 1 22 0 96 2 2 0 0 0 0 0 0 0 0
+ 2 nss-SO2 4 =SO4 0.2529*Na . 2 2 nss-SO4 =SO4 0.2529*Na (INAA).
In preanalysis, complete solubility was achieved in a 4 h extraction, and thus in the 24 h sample extractions, the solubility should not be a problem for Na. The INAA results will be used in further analysis, since the uncertainty is smaller. For K and Ca, a complete solubility was not expected since the crustal forms of these elements are insoluble in water. However, the geometric mean from IC and INAA analysis were close to each other for both K and Ca. These results indicate that there is not much crustal material in the airborne particulate matter at Kevo. The regression for K is good, but the R2 value for Ca is low. INAA gives consistently higher values than IC for those samples collected in 1975 or later. In 40% of those samples, Ca from INAA is more than twice the Ca from IC, with more than 20% of these high values occurring during August. For 1965–1975 samples, the agreement between the methods was good.
Compared to the geometric mean concentrations at Alert, Nanuvut (Barrie and Hoff, 1985; Sirois and Barrie, 1999; Xie et al., 1999a,b), constituents from anthropogenic sources, especially nonferrous metal mining and processing (Zn, Sb, As, In) had four- to eight-fold increased concentrations at Kevo. Potassium, which has a similar distribution of moss concentrations in the Kola Peninsula area to Zn, As and In, but is also a marker of biomass burning, has a 10-fold higher concentration compared to Alert. On the other hand SO2 and V, originating from fossil fuel 4 burning, have only two- to three-fold increase in concentration. MSA concentrations were twice as high compared to Alert. Kevo is downwind of potential sources of MSA in the Northern Atlantic ocean (Hopke et al., 1995). Correlations between crustal elements, Al, Si and Ti, are not as clear as is normally observed. The scatter plot
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Table 2 A comparison of results obtained from two different analytical techniques X
Na (INAA) K (INAA) Ca (INAA) Cl (INAA)
Range of x; yi (ng m3)
Y
+
Na (IC) K+ (IC) Ca2+ (IC) Cl (IC)
51–3700 18–595 6–555 825–1110
Linear regression parameters A
B
R2
N
0.9580.01 1.0480.02 0.4380.03 1.2080.04
–3.884.9 23.382.4 30.182.0 –35.384.3
0.86 0.72 0.28 0.62
681 681 668 681
A linear regression analysis was performed using the model: y ¼ Ax þ B: IC—ion chromatography, INAA—instrumental neutron activation analysis.
Fig. 3. Scatter plot of Si concentration against Al concentration.
of Si against Al (Fig. 3) shows two different Si/Al ratios: 3.5, which is close to typical crustal compositions and 42, indicating substantial excess silicon. The high Si/Al ratios occur from mid-1966 to the end of 1969 mainly from July to October. Ti/Al has a similar behavior with ratios 0.06 (soil) and 1.3 (excess Ti). High titanium concentrations occur mainly from October to December from mid-1967 to 1974. The Environmental Geochemical Atlas of the Central Barents Region (Reimann et al., 1998) shows a higher enrichment of Si than Al in moss around the Nikel/Zapoljarniy area suggesting that the Si emissions are higher. There were no moss data for Ti. The highest Al concentrations occur during March and April, when the ground is still covered by snow at Kevo. Thus, the main source of crustal elements is not the local soil erosion. There are a number of species for which marine aerosol would be a source. According to the Geochemical Atlas (Reimann et al., 1998), in northern Finland, northern Norway and the Kola Peninsula, Mg seems to be mostly from sea aerosol, while Na, K and Ca have other sources in Kola industrial area. However, a good relationship can be observed between sodium and magnesium, although the average Mg/Na ratio is 0.07
instead of 0.13 found in seawater. The ratio decreases gradually from 0.08 before 1970 to 0.04 from 1973 on. The yearly average of Mg decreases from 25 ng m3 in 1965 to 12 ng m3 in 1977. The silver concentration shows an interesting pattern. There are very high Ag concentrations, up to 190 ng m3, in 1965, 1966 and 1969. From the end of 1964 to November 1971, only 13% of the samples are below the detection limit and the geometric mean of Ag is 0.33 ng m3. After November 1971, more than 70% of the values are below the detection limit and the highest value is 0.63 ng m3. Aerosol silver concentrations are seldom analyzed or reported; so there is limited amount of information on high Ag levels in Arctic areas. Vinogradova and Polissar (1995) reported high Ag, Sb and Au concentrations (mean 4.0 ng m3) connected to air masses originating from the center of the Arctic Basin in spring 1988 in the Russian Arctic. Silver occurs in the ores processed in Monchegorsk and Nikel, and there appears to be additional sources at Kandalaksha and Olenegorsk (Reimann et al., 1998). In the early 1970s, the Monchegorsk smelter started to use Norilsk ore instead of the local ore. This change resulted in increased metal production and substantially increased emissions of SO2 (Pozniakov, 1993) and might have effected on the silver emissions. The week-to-week variation of vanadium (Fig. 4A) and arsenic show clearly the typical pattern of Arctic haze. Higher winter concentrations are caused by more efficient transport of polluted air from the mid-latitudes and the lower removal rates during the cold, dark season. High concentrations occur earlier at Kevo than at Alert, because Kevo is located further south. During the summer, the concentrations of most species are low. The other anthropogenic pollutants do not show such clear patterns of Arctic haze. This indicates that there is also transport of polluted air to Kevo during the summer time. The metal mining and smelting and phosphate fertilizer production in the Kola Peninsula region, 130–300 km from Kevo are likely sources. For sulfate (Fig. 4B), there are several sources including anthropogenic sources, sea spray and biogenic activity of marine algae. Fig. 4C shows the Se time
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Fig. 4. Time series of (a) vanadium, (b) sulfate, (c) selenium, (d) selenium, (e) zinc, and (f) MSA.
series. It can be seen that the Se generally follows the sulfur and has a pattern that includes the typical Arctic Haze peaks in the late winter–early spring, but appears at other times as well. The highest concentrations are observed from January to April. Fig. 4D shows the time series of black carbon concentrations. In prior analysis of data from Alaska, the BC/sulfur plot showed two source types that were assigned to woodsmoke and long-range transported anthropogenic aerosols, which could be separated on the basis of different BC-sulfur ratio (Polissar et al., 1996). Such sources are not as distinct at Kevo (Fig. 5), although there are clearly more than one source for these components. The highest BC/SO2 4 ratios occur during the summer time. The correlation between BC and water-soluble non-soil potassium shows that there is wood smoke in the samples (Fig. 6). Because of the moderate concentrations of seasalt at Kevo, the
Fig. 5. BC concentrations plotted against sulfate concentrations.
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Fig. 6. Non-soil potassium concentrations plotted against BC concentrations.
nss-SO2 concentrations were quite close to the total 4 sulfate concentrations. Zinc emissions from the Kola Peninsula are 180 t yr1. The most important sources are the production of phosphate fertilizers and Cu–Ni mining and processing (NILU, 1984). During the 1990–1995 geochemical studies, the environmental Zn concentrations around these areas were not high (Reimann et al., 1998). The zinc concentration at Kevo is 8 times higher than at Alert and it correlates with the Cu concentration. A time-series plot of Zn is presented in Fig. 4D. MSA can be used as a tracer of atmospheric biogenic sulfur. Dimethylsulfide (DMS) is produced in marine surface water by algae, transported into the water and further into the air. In the air, it is oxidized to non-seasalt sulfate and MSA. Sulfur-containing aerosols affect the earth’s radiative balance directly by scattering solar radiation and indirectly through cloud albedo. The amount of incoming radiation affects on the temperature of the sea water and the DMS production of algae (Charlson et al., 1987; Bates et al., 1992). At Kevo, the MSA has a clear seasonal cycle with peak from April to August (Fig. 4E). The concentrations are about double compared to those at Alert, but this result was expected because Kevo is more directly downwind of the potential source areas in the north Atlantic ocean and the transport from these areas is stronger (Hopke et al., 1995). The variation of yearly average of several constituents, normalized with the 1965 level, is shown in Fig. 7. Copper and zinc concentrations have a slowly decreasing pattern, approximately 0.5 and 0.9 ng m3 decrease per year for Cu and Zn respectively, until the steep rise in 1977. Most other constituents (Ag, Al, Br, Ca2+, Co, I, Mn, Na, SO2 4 , Ti, V, and MSA) have the highest yearly average in 1969. The patterns for Mn and Ca2+
Fig. 7. Variation of yearly average normalized to the 1965 average.
are similar (Fig. 7B). There are no emission estimations for industrial sources of Ca2+ available, but Jaffe et al. (1995) observed elevated Ca concentrations in a snowpack near Kirovsk. Apatite contains also manganese and the observed average Ca/Mn of 44 indicates that the apatite mine is a likely source. Other possible sources common for Ca and Mn could be metal industry (iron mining in Kovdor and Olenegorsk) and wood processing. For Co and Al (Fig. 7C), the 1970 concentration is lower and the 1974 peak is higher than for Mn and Ca2+. Al is usually associated with local crustal sources, but, in Kevo, soil seems to be a weak source. Residual oil combustion is a common source for vanadium and coal and oil produce SO2 after atmo4 spheric processing of the emitted SO2. Their year-to-year variations have similar patterns, although the variation in vanadium concentrations is much stronger (Fig. 7D). In early 1970s, the Monchegorsk smelter started to use the high-sulfur Norilsk ore (Pozniakov, 1993). The increased metal production and substantially increased emissions of SO2 are not observed in the yearly averages of species at Kevo. Tuovinen et al. (1993) estimated that the percentage contributions of Nikel, Zapolyarnyy and Monchegorsk SO2 emissions at Kevo in July 1990–June 1991 were 9%, 3% and 6%, respectively. The concentration of BC decreases sharply in 1967, but has increased steadily after that (Fig. 7E). No other
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constituent has a similar trend. The variation in MSA yearly average is small except for the peak at 1969 (Fig. 7F). There is no correlation between the yearly average of MSA and the average northern hemisphere temperature anomaly. These historical values can be compared to more recent measurements made at Sevettij.arvi, Finland (69E350 N, 28E500 E, 130 m AMSL) (Virkkula et al. 1999, 1995; Ricard et al., 2002a,b). The average concentrations of Zn, Cu, As and Sb were 4 to 6 times higher than the average concentrations reported from Sevettij.arvi between 27 October 1993, and 5 July 1994 by Virkkula et al. (1999). Sevettij.arvi is located 60 km WNW from Nikel. Since the 1993–1994 data does not include the time from July to October, when most constituents have lower concentrations than during winter/spring, the actual Kevo/Sevettij.arvi ratio should be even higher suggesting significant decrease in the emissions between 1978 and 1993. Ricard et al. (2002a) made measurements at Sevettij.arvi from September 1997 to June 1999 with results that were similar to those of Virkkula et al. (1999). The seasalt species at Kevo are similar in concentration to those observed at Sevettij.arvi. It is impossible to judge the relative degree of chlorine displacement from the seasalt for Kevo and Sevettij.arvi because of the chlorine blank value problems described earlier.
4. Conclusions The chemical composition of historical samples of Arctic aerosol has been determined to provide the first time series of Arctic Haze compositions from the 1960s and 1970s. These data provide a first view of Arctic air quality in this time period. Because of the proximity of the sampling site at Kevo, Finland to the Kola Peninsula’s highly industrialized area, concentrations of chemical species with anthropogenic origin, especially Zn, Sb, As, In and K, are much higher at Kevo than observed at Alert in the Canadian Arctic from 1980 to 1991 or at Sevettij.arvi, Finland in the 1990s. The MSA at Kevo is much higher than at Alert but somewhat lower than is observed in later years at Sevettij.arvi. Soil and seasalt elements are relatively low in abundance at Kevo and lower than at Sevettij.arvi. Significant changes can be seen in the year-to-year variation, resulting from the variation in emission strength and transportation efficiency. It is not possible to obtain any detailed records on emissions in the Soviet Union from that time period and thus, it is difficult to relate the observed yearto-year variations with industrial activity patterns in the region. Future work will include the data analysis using multivariate time series methods and back trajectory analysis.
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Acknowledgements The work at Clarkson University and University of Texas at Austin was supported by the Cooperative Institute For Arctic Research.
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Li, S.-M., Barrie, L.A., 1993. Biogenic sulfur aerosol in the Arctic troposphere: 1. Contributions to total sulfate. Journal of Geophysical Research 98 (D11), 20613–20622. Li, S.-M., Barrie, L.A., Sirois, A., 1993. Biogenic sulfur aerosol in the Arctic troposphere: 2. Trends and seasonal variations. Journal of Geophysical Research 98 (D11), 20623–20631. Miller, J.M., 1981. A five year climatology of five-day back trajectories from Barrow, Alaska. Atmospheric Environment 15, 1401–1405. NILU (Norwegian Institute for Air Research), 1984. Emission sources in the Soviet Union, NILU 4/84. Paatero, J., Hatakka, R., Mattson, R., Lehtinen, I., 1994. A comprehensive station for monitoring atmospheric radioactivity. Radiation Protection Dosimetry 54 (1), 33–39. Paatero, J., Hatakka, R., Mattson, R., Viisanen, Y., 1998. Analysis of daily 210Pb air concentrations in Finland, 1967–1996. Radiation Protection Dosimetry 77 (3), 191–198. Paatero, J., Hatakka, J., Mattson, R., Aaltonen, V., Viisanen, Y., 2000. Long-term variations of lead-210 concentrations in ground-level air in Finland: effects of the North-Atlantic oscillation transport and chemical transformation in the troposphere. Proceedings of the EUROTRAC-2 Symposium. Springer, Berlin, Germany. Polissar, A.V., Hopke, P.K., Malm, W.C., Sissler, J.F., 1996. The ratio of aerosol optical absorption coefficient to sulfur concentrations, as an indicator of smoke from forest fires when sampling in polar regions. Atmospheric Environment 30 (7), 1147–1157. Polissar, A.V., Hopke, P.K., Malm, W.C., Sissler, J.F., 1998. Atmospheric aerosol over Alaska. 1. Spatial and seasonal variability. Journal of Geophysical Research 103 (D15), 19035–19044. Pozniakov, V.Y., 1993. The Sevoronikel smelter complex: history of development. In: Kozlov, M.V. (Ed.), Aerial Pollution of the Kola Peninsula. University of Turku, Finland. Raatz, W.E., 1989. An anticyclonic point of view on low-level tropospheric long-range transport. Atmospheric Environment 23 (11), 2501–2504. Raatz, W.E., Shaw, G.E., 1984. Long range transport of pollution aerosols into the Alaskan Arctic. Journal of Climate and Applied Meteorology 23, 1052–1064. Reimann, C., Chekushin, V., Bogatyrev, I., Boyd, R., de Caritat, P., Dutter, R., Finne, T.E., Halleraker, J.H., Jæger, Ø., Kashulina, G., Lehto, O., Niskavaara, H., Pavlov, V., R.ais.anen, M.L., Strand, T., Volden, T., 1998. Environ-
mental geochemical atlas of the central Barents region. Geological Survey of Norway, Trondheim, Norway. Ricard, V., Jaffrezo, J.L., Kerminen, V.M., Hillamo, R.E., Sillanpaa, M., Ruellan, S., Liousse, C., Cachier, H., 2002a. Two years of continuous aerosol measurements in northern Finland. Journal of Geophysical Research-Atmosphere 107 (D11). Ricard, V., Jaffrezo, J.L., Kerminen, V.M., Hillamo, R.E., Teinila, K., Maenhaut, W., 2002b. Size distributions and modal parameters of aerosol constituents in northern Finland during the European Arctic Aerosol Study. Journal of Geophysical Research-Atmosphere 107 (D14). Sakunov, G.G., Timirev, A.A., Barteneva, O.D., 1990. Aerosol optical characteristics of the Arctic atmosphere. Soviet Meteorology and Hydrology (2), 53–58. Shaw, G.E., 1995. The Arctic haze phenomenon. Bulletin of the American Meteorological Society 76 (12), 2403–2413. Sirois, A., Barrie, L.A., 1999. Arctic lower tropospheric aerosol trends and composition at Alert, Canada: 1980–1995. Journal of Geophysical Research 104 (D9), 11599–11618. Tuovinen, J.-P., Laurila, T., L.attil.a, H., Ryaboshapko, A., Brukhanov, P., Korolev, S., 1993. Impact of the sulphur dioxide sources in the Kola peninsula on air quality in Northern Europe. Atmospheric Environment 27A (9), 1379–1395. Vinogradova, A.A., Polissar, A.V., 1995. Elemental composition of the aerosol in the atmosphere of the Central Russian Arctic. Atmospheric and Oceanic Physics 31 (2), 248–257. Virkkula, A., Makinen, M., Hillamo, R., Stohl, A., 1995. Atmospheric aerosol in the Finnish Arctic: particle number concentrations, chemical characteristics, and source analysis. Water, Air, and Soil Pollution 85, 1997–2002. Virkkula, A., Aurela, M., Hillamo, R., M.akel.a, T., Pakkanen, T., Maenhaut, W., Fran@ois, F., Cafmeyer, J., 1999. Chemical composition of atmospheric aerosol in the European subarctic: contribution of the Kola peninsula smelter areas, Central Europe, and the Arctic Ocean. Journal of Geophysical Research 104 (D19), 23681–23696. Xie, Y.-L., Hopke, P.K., Paatero, P., Barrie, L.A., Li, S.-M., 1999a. Identification of source nature and seasonal variations of Arctic aerosol by the multilinear engine. Atmospheric Environment 33, 2549–2562. Xie, Y.-L., Hopke, P.K., Paatero, P., Barrie, L.A., Li, S.-M., 1999b. Identification of source nature and seasonal variations of arctic aerosols by positive matrix factorization. Journal of the Atmospheric Sciences 56, 249–260.
Composition of the Finnish Arctic aerosol: collection and analysis of historic filter samples Tarja Yli-Tuomia, Lisa Vendittea, Philip K. Hopkea,*, M. Shamsuzzoha Basuniab, Sheldon Landsbergerb, Yrjo. Viisanenc, Jussi Paateroc a
b
Department of Chemical Engineering, Clarkson University, Box 5705, Potsdam, NY 13699-5705, USA Nuclear Engineering Teaching Laboratory, University of Texas, Pickle Research Campus, Building 159, R-9000, Austin, TX 78712, USA c Air Quality Division, Finnish Meteorological Institute, P.O. Box 503, FIN-00101 Helsinki, Finland Received 11 February 2003; accepted 17 February 2003
Abstract Week-long samples of total suspended particles have been collected between October 1964 and February 1978 from the Finnish Arctic. Neutron activation analysis, ion chromatography, and light-absorption techniques have been used to analyze the concentration of several heavy metals and other elements, major ions, methane sulfonate (MSA), and black carbon. Kevo is located near the Kola Peninsula and the effect of the industrial area can be seen. Compared to previous studies of Arctic aerosols carried out in North American Arctic, the Kevo results show higher concentration of anthropogenic pollutants and the seasonal variability for most constituents is weaker than the typical Arctic haze pattern. MSA, a marker of biogenic activity, has a clear seasonal cycle with a peak from April to August. r 2003 Elsevier Science Ltd. All rights reserved. Keywords: Time series; Heavy metals; Methane sulfonate; Arctic Haze; Kola Peninsula
1. Introduction The occurrence, nature, origin, transport and effects of the Arctic aerosol have been the subjects of active research since 1970. The aerosol concentration in the Arctic has a strong seasonal variation generally characterized by a winter maximum and summer minimum. A review of Arctic haze phenomenon by Shaw (1995) concludes that the seasonal variation is a result of combination of variability in long-range transport of air (Miller, 1981; Raatz and Shaw, 1984; Raatz, 1989), the atmospheric blocking phenomenon (Iversen and Joranger, 1985), pollutant removal processes (Barrie et al., 1981, 1989), the oxidation of SO2 (Barrie and Hoff, 1984; Barrie and Barrie, 1990), and the thickness of *Corresponding author. Tel.: +1-315-268-3861; fax: +1315-268-6610. E-mail address: [email protected] (P.K. Hopke).
surface temperature inversions (Sakunov et al., 1990). During the winter, particles originate mainly from anthropogenic sources, while in summer, the lower concentrations are contributed mainly by natural sources. Glacial ice cores reveal that pollution of the Arctic can be observed to begin in 1912 and has increased significantly since 1956 (Barrie et al., 1985). However, there are relatively few long-term studies of the composition of the Arctic aerosol. The Canadian Aerosol Sampling Network began a routine aerosol sampling at Alert, Northwest Territories on July 1980 and the results have been reported for a time period of up to 16 yr (Barrie and Hoff, 1985; Li and Barrie, 1993; Li et al., 1993; Sirois and Barrie, 1999; Xie et al., 1999a,b). The Interagency Monitoring of PROtected Visual Environments (IMPROVE) has collected aerosol data from March 1988 to February 1995 at Denali National Park in Alaska. The National Park Service
1352-2310/03/$ - see front matter r 2003 Elsevier Science Ltd. All rights reserved. doi:10.1016/S1352-2310(03)00164-X
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Fig. 1. Location of Kevo in the Northern Scandinavian peninsula.
has performed aerosol measurements in additional six sites in Alaska between 1986 and 1992 (Polissar et al., 1998). For this study, the chemical composition of weekly aerosol samples collected between 1964 and 1978 from Finnish Arctic were measured to provide a data set for more than 13 yr. These samples were collected by the Finnish Meteorological Institute (FMI) in order to monitor atmospheric radioactivity. The analysis of this data will provide information about the sources of haze in European Arctic, the long-term changes in the source composition and contribution, as well as their potential source areas. In prior studies of the composition of particles from a long time series of samples collected at Alert, a component representing biogenic sulfur emissions from marine algae was observed. This component was characterized by the presence of methane sulfonate (MSA) and its year-to-year intensity was highly correlated with the northern hemispheric temperature anomaly (Xie et al., 1999a,b). MSA concentration was determined from the Kevo samples in order to test the hypothesis that a relationship between biogenic sulfur particle concentrations and temperature can be observed as part of a climate–biosphere interaction.
The procedures of sampling and chemical analysis along with the results of chemical composition, time series and correlations are reported in this paper. The data is also being analyzed by multivariate methods combined with back trajectory data and those results will be presented in a subsequent report.
2. Sampling and analysis 2.1. Sampling site FMI has been collecting aerosol samples in Northern Finland at Kevo since October 1964. The Kevo Subarctic Research Institute (latitude 69 450 N, longitude 27 020 E, height 98 m) is located about 350 km north of the Arctic circle (Fig. 1). The site belongs to the birch sub-zone of the boreal coniferous forest. The topography of the surrounding area is characterized by gently sloping fell highlands with river valleys. The elevation is mostly between 100 and 400 m above sea level. The area is sparsely populated (0.4 inhab. km2). In the summer, the sun shines without setting from mid-May till the end of July, and remains below the
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horizon from late November to mid-January. The mean temperature of the coldest month (January) is 16 C and the warmest month (July) +13 C. The annual mean temperature is 2 C. The ground is covered with snow from October to mid-May. There were four buildings at the station area when the measurements were started in 1964. Between 1968 and 1978, six other buildings were built. The most likely source of local aerosols is the wood-heated sauna, which is used often during the spring and summer. The heating system of the meteorological station was changed from wood burning to electricity in 1971. Before 1984 there was no road to the station. It was reached by boat during the summer and along an ice road during the winter. 2.2. Sample collection The reason for the aerosol sampling is to monitor natural and artificial radioactivity in the air. The schematic diagram of the sampling system is shown in Fig. 2. Air is drawn alternately through two filters in 4 h time periods. The beta activity accumulating onto the filters is continuously recorded by two cylindrical Geiger–Muller . counters. Rn-222 activity concentration can be calculated from the count rate. Filters are located inside lead shields to reduce background count rates (Paatero et al., 1994). The filters are changed once a week, and thus the two filters constitute the aerosol sample for the week-long period. The sampler is not equipped with size-selective inlet and therefore total suspended particles are collected. The air inlet tube is drawn through the roof of a house and the sampling height is about 7 m above ground level. We have 685 weekly samples from October 1964 to February 1978. During that time period, rectangular 12 cm 14 cm-sized Whatman paper filters (Grade 42) were used and the collection flow rate was about 7 m h1 giving a total sample volume of 1200 m3. After February 1978, circular 24 cm diameter glass fiber filters and a flow rate of 25 m h1 were used, but these filters have not been analyzed for chemical composition. 2.3. Chemical analysis After the filters were removed from the device, they were sent to Helsinki to the FMI Air Quality Department, where they were analyzed for Pb-210 6 months after sampling ((Paatero et al., 1998)). The Pb-210 activity concentrations (Paatero et al., 2000), Rn-222 (Aaltonen et al., 2001) and total beta activity (Finnish Meteorological Institute, 1984) results have been reported earlier. The filters have been stored at room temperature in an envelope with other filters from the same year. A silk
Fig. 2. Schematic diagram of the sampling system.
paper was used to separate the weekly samples. For this research the weekly 12 cm 14 cm filters were cut into two equal pieces using a laminar flow clean bench at FMI. Half of each filter was retained in the FMI archives, while the other half was brought to Clarkson University and further cut into two pieces. One quarter of each filter was used for black carbon (BC) and ion chromatograph (IC) analysis at Clarkson University and the other quarter was sent to University of Texas, Austin, for instrumental neutron activation analysis (INAA). The two filter strips from the two sample lines from the same week were combined to produce one sample. Before analysis, the samples were stored in tightly sealed plastic bags at room temperature at Clarkson University. 2.3.1. Light transmission for BC The BC concentration was analyzed by using diffuse light transmission method. Light attenuation (ATN) is linearly related to the BC mass loading (SBC ) on the filter by the relation: ATN ¼ 100 lnðII01 Þ ¼ BATN SBC ;
ð1Þ
where I0 is the light intensity after passing a blank filter, I the light intensity after passing a particle-loaded filter and BATN is the specific attenuation coefficient (Ballach et al., 2001). In this study, a specific attenuation coefficient of 15 m2 g1 was used according to the recommendation of Tony Hansen (Hansen, 2000).
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Since there were no blank filters available from the same time period as the sample filters, new Whatman 42 paper filters were used as blanks. The average light intensity transmitted through the blank filter was used in the calculations. The blank was very close to the cleanest sample filters from summer periods; so the blank correction for BC appears to be reasonable. Both ends of each filter strip were measured and an average of the four results represents the sample concentration. The difference between the two strips was 7% on average, but in some samples, up to 65% illustrating the effect of the time of day and short episodes of high concentration. 2.3.1.1. IC analysis. For IC analysis, the samples were extracted into 20 ml of chloroform-saturated ultra-pure water (specific resistance=18.3 MO cm) for 24 h in room temperature. Chloroform was used to prevent potential bacterial activity. After the extraction, the samples were stored in a refrigerator. The aliquot of the sample was filtrated with a GHP syringe filter for anion analysis and IC syringe filter for cation analysis. A DX-500 ion chromatograph with a GP50 gradient pump and ED50 electrochemical detector was used in the analysis of major anions (Cl and SO2 4 ), MSA and cations (Na+, K+, Mg2+ and Ca2+). SRS-ULTRA suppressors were used to reduce the baseline conductivity and therefore the background noise. The MSA and major anions were separated with AS4A-SC column using a gradient of 5–28 mM Na2B4O7. The cations were analyzed with a CS12A column and 22 mM H2SO4 eluent. Double injections of 200 ml were used for all samples to ensure the results. Five percent of the samples were repeated in the next batch and the uncertainty was determined based on the reproducibility. The detection limit was determined by the EPA 40 CFR 136, Appendix B method. All the ions in all samples were above the analytical detection limit, but due to blank correction, 38% of blank corrected chloride values were negative. Anion standards were prepared at Clarkson University from A.C.S. certified chemicals. Dionex Six Cation Standard II was used for cations. New Whatman 42 paper filters were used as blanks. 2.3.2. Instrumental neutron activation analysis The instrumental neutron activation analysis (INAA) analysis was performed at the TRIGA MARK II research reactor facility, University of Texas, Austin. Three separate irradiations were performed for each filter, followed a counting by high-purity germanium (HPGe) gamma spectrometry system. The elements analyzed were Al, Ca, Cl, Cu, Mn, Na, Ti and V with 2 min thermal short irradiation, Ag with 1 min and As, Br, Co, I, In, K, Sb, Si, Sn, Zn, and W with 10 min epithermal short irradiation. Selenium was separately
determined in the filters using the short-lived 77mSe (T1=2 ¼ 17:4 s). Each filter was irradiated for 10 s and counted for 50 s after a decay time of about 17 s. New Whatman 42 filters were used for blank correction. The combined filters occupied a volume of about 3 ml in the pneumatic vial. Inside the carrier vial, another 2/ 5th dram vial was placed on top of the filter containing about 500 mg sulfur powder. Sulfur powder was used to normalize the neutron flux for each sample irradiation. All calibrations for elemental concentration determination were done using monoelemental standard solutions from the National Institute of Standards and Technology (NIST) or from laboratory chemicals. NIST Standard Reference Material (SRM) coals 1632a, 1632b, and 1632c, citrus leaves 1572, oyster tissue 1566a, and San Joaquin Soil 2709 were analyzed for quality control on the process. For silver determination, samples were manually counted without transferring the filter from the irradiated vial. However, for all other irradiations, all of the samples were transferred to a non-irradiated vial and counted both in the normal and Compton modes by the HPGe gamma spectrometry system.
3. Results Table 1 lists the chemical constituents analyzed together with the analytical method, geometric mean and standard deviation, detection limit and the percentage of values below the detection limit. In addition to the measured values, non-sea-salt sulfate has been calculated by subtraction of 0.2529 times the sodium concentration. Since sodium was measured by both IC and INAA, the distributional parameters for both values are provided. For W, Ag, and Ca (INAA), more than 40% of the samples are below the detection limit. Difficulties in Cl results resulted from the blank problems. In the IC analysis, all of the samples had Cl concentration higher than the analytical detection limit, but due to high Cl concentrations of the new filters used as blanks, the blank subtraction produced many negative values. The filter chlorine concentrations may have changed during the years of sampling so that it is not possible to obtain a reliable blank value for Cl. Thus, both the IC and INAA results of Cl have been excluded from the data analysis. For three elements (Na, K and Ca), comparison between the two different techniques is possible. Linear regression analysis (Table 2) shows good agreement between IC and INAA for Na. The squared correlation coefficient between the two sets of Na values is 0.999 with a slope of 1.003+0.001 and an intercept of 62+2 ng m3. The reason for this might be a slight variation across the filter deposit, or incomplete dissolution of the sodium into the extraction volume.
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Table 1 The analytical method, geometric mean and standard deviation, detection limits (ng m3), and percentage of data below the detection limit Constituent
Ag Al As Br Ca Co Cu I In K Mn Na Sb Si Se Sn Ti V W Zn BC MSA SO2 4 Na+ + K Mg2+ Ca2+ nss-SO2a 4 nss-SO2b 4 a b
Analytical method
INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA INAA Optical IC IC IC IC IC IC IC-IC IC-NAA
Geometric mean
0.15 34.5 0.61 2.07 54.5 0.06 12.8 0.85 0.00 74.7 1.23 250 0.19 222 0.104 2.49 5.86 0.43 0.09 18.7 238 9.54 1319 235 97.4 14.2 49.0 1310 1223
Geometric std
3.76 1.81 3.03 2.05 1.73 2.34 1.70 1.49 2.09 1.57 2.06 1.59 2.37 2.02 2.38 2.17 1.92 3.01 1.30 1.72 2.07 3.95 2.18 1.57 1.63 1.93 1.70 1.94 1.92
Detection limit
Below DL (%)
from
to
0.03 0.40 0.01 0.06 11.3 0.00 0.53 0.00 0.00 3.33 0.09 1.92 0.01 18.2 0.03 0.11 1.34 0.01 0.01 2.39 25.0 0.05 4.22 0.47 3.44 0.05 0.16 146 88
0.63 14.7 0.20 1.39 278 0.28 8.04 0.06 0.04 59.3 1.27 22.0 0.17 329 0.65 3.06 23.4 0.13 0.65 36.7 711 1.22 99.7 11.0 81.4 1.10 3.73 10,906 10,820
41 0 0 0 51 14 0 0 0 0 0 0 0 1 31 1 22 0 96 2 2 0 0 0 0 0 0 0 0
+ 2 nss-SO2 4 =SO4 0.2529*Na . 2 2 nss-SO4 =SO4 0.2529*Na (INAA).
In preanalysis, complete solubility was achieved in a 4 h extraction, and thus in the 24 h sample extractions, the solubility should not be a problem for Na. The INAA results will be used in further analysis, since the uncertainty is smaller. For K and Ca, a complete solubility was not expected since the crustal forms of these elements are insoluble in water. However, the geometric mean from IC and INAA analysis were close to each other for both K and Ca. These results indicate that there is not much crustal material in the airborne particulate matter at Kevo. The regression for K is good, but the R2 value for Ca is low. INAA gives consistently higher values than IC for those samples collected in 1975 or later. In 40% of those samples, Ca from INAA is more than twice the Ca from IC, with more than 20% of these high values occurring during August. For 1965–1975 samples, the agreement between the methods was good.
Compared to the geometric mean concentrations at Alert, Nanuvut (Barrie and Hoff, 1985; Sirois and Barrie, 1999; Xie et al., 1999a,b), constituents from anthropogenic sources, especially nonferrous metal mining and processing (Zn, Sb, As, In) had four- to eight-fold increased concentrations at Kevo. Potassium, which has a similar distribution of moss concentrations in the Kola Peninsula area to Zn, As and In, but is also a marker of biomass burning, has a 10-fold higher concentration compared to Alert. On the other hand SO2 and V, originating from fossil fuel 4 burning, have only two- to three-fold increase in concentration. MSA concentrations were twice as high compared to Alert. Kevo is downwind of potential sources of MSA in the Northern Atlantic ocean (Hopke et al., 1995). Correlations between crustal elements, Al, Si and Ti, are not as clear as is normally observed. The scatter plot
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Table 2 A comparison of results obtained from two different analytical techniques X
Na (INAA) K (INAA) Ca (INAA) Cl (INAA)
Range of x; yi (ng m3)
Y
+
Na (IC) K+ (IC) Ca2+ (IC) Cl (IC)
51–3700 18–595 6–555 825–1110
Linear regression parameters A
B
R2
N
0.9580.01 1.0480.02 0.4380.03 1.2080.04
–3.884.9 23.382.4 30.182.0 –35.384.3
0.86 0.72 0.28 0.62
681 681 668 681
A linear regression analysis was performed using the model: y ¼ Ax þ B: IC—ion chromatography, INAA—instrumental neutron activation analysis.
Fig. 3. Scatter plot of Si concentration against Al concentration.
of Si against Al (Fig. 3) shows two different Si/Al ratios: 3.5, which is close to typical crustal compositions and 42, indicating substantial excess silicon. The high Si/Al ratios occur from mid-1966 to the end of 1969 mainly from July to October. Ti/Al has a similar behavior with ratios 0.06 (soil) and 1.3 (excess Ti). High titanium concentrations occur mainly from October to December from mid-1967 to 1974. The Environmental Geochemical Atlas of the Central Barents Region (Reimann et al., 1998) shows a higher enrichment of Si than Al in moss around the Nikel/Zapoljarniy area suggesting that the Si emissions are higher. There were no moss data for Ti. The highest Al concentrations occur during March and April, when the ground is still covered by snow at Kevo. Thus, the main source of crustal elements is not the local soil erosion. There are a number of species for which marine aerosol would be a source. According to the Geochemical Atlas (Reimann et al., 1998), in northern Finland, northern Norway and the Kola Peninsula, Mg seems to be mostly from sea aerosol, while Na, K and Ca have other sources in Kola industrial area. However, a good relationship can be observed between sodium and magnesium, although the average Mg/Na ratio is 0.07
instead of 0.13 found in seawater. The ratio decreases gradually from 0.08 before 1970 to 0.04 from 1973 on. The yearly average of Mg decreases from 25 ng m3 in 1965 to 12 ng m3 in 1977. The silver concentration shows an interesting pattern. There are very high Ag concentrations, up to 190 ng m3, in 1965, 1966 and 1969. From the end of 1964 to November 1971, only 13% of the samples are below the detection limit and the geometric mean of Ag is 0.33 ng m3. After November 1971, more than 70% of the values are below the detection limit and the highest value is 0.63 ng m3. Aerosol silver concentrations are seldom analyzed or reported; so there is limited amount of information on high Ag levels in Arctic areas. Vinogradova and Polissar (1995) reported high Ag, Sb and Au concentrations (mean 4.0 ng m3) connected to air masses originating from the center of the Arctic Basin in spring 1988 in the Russian Arctic. Silver occurs in the ores processed in Monchegorsk and Nikel, and there appears to be additional sources at Kandalaksha and Olenegorsk (Reimann et al., 1998). In the early 1970s, the Monchegorsk smelter started to use Norilsk ore instead of the local ore. This change resulted in increased metal production and substantially increased emissions of SO2 (Pozniakov, 1993) and might have effected on the silver emissions. The week-to-week variation of vanadium (Fig. 4A) and arsenic show clearly the typical pattern of Arctic haze. Higher winter concentrations are caused by more efficient transport of polluted air from the mid-latitudes and the lower removal rates during the cold, dark season. High concentrations occur earlier at Kevo than at Alert, because Kevo is located further south. During the summer, the concentrations of most species are low. The other anthropogenic pollutants do not show such clear patterns of Arctic haze. This indicates that there is also transport of polluted air to Kevo during the summer time. The metal mining and smelting and phosphate fertilizer production in the Kola Peninsula region, 130–300 km from Kevo are likely sources. For sulfate (Fig. 4B), there are several sources including anthropogenic sources, sea spray and biogenic activity of marine algae. Fig. 4C shows the Se time
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Fig. 4. Time series of (a) vanadium, (b) sulfate, (c) selenium, (d) selenium, (e) zinc, and (f) MSA.
series. It can be seen that the Se generally follows the sulfur and has a pattern that includes the typical Arctic Haze peaks in the late winter–early spring, but appears at other times as well. The highest concentrations are observed from January to April. Fig. 4D shows the time series of black carbon concentrations. In prior analysis of data from Alaska, the BC/sulfur plot showed two source types that were assigned to woodsmoke and long-range transported anthropogenic aerosols, which could be separated on the basis of different BC-sulfur ratio (Polissar et al., 1996). Such sources are not as distinct at Kevo (Fig. 5), although there are clearly more than one source for these components. The highest BC/SO2 4 ratios occur during the summer time. The correlation between BC and water-soluble non-soil potassium shows that there is wood smoke in the samples (Fig. 6). Because of the moderate concentrations of seasalt at Kevo, the
Fig. 5. BC concentrations plotted against sulfate concentrations.
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Fig. 6. Non-soil potassium concentrations plotted against BC concentrations.
nss-SO2 concentrations were quite close to the total 4 sulfate concentrations. Zinc emissions from the Kola Peninsula are 180 t yr1. The most important sources are the production of phosphate fertilizers and Cu–Ni mining and processing (NILU, 1984). During the 1990–1995 geochemical studies, the environmental Zn concentrations around these areas were not high (Reimann et al., 1998). The zinc concentration at Kevo is 8 times higher than at Alert and it correlates with the Cu concentration. A time-series plot of Zn is presented in Fig. 4D. MSA can be used as a tracer of atmospheric biogenic sulfur. Dimethylsulfide (DMS) is produced in marine surface water by algae, transported into the water and further into the air. In the air, it is oxidized to non-seasalt sulfate and MSA. Sulfur-containing aerosols affect the earth’s radiative balance directly by scattering solar radiation and indirectly through cloud albedo. The amount of incoming radiation affects on the temperature of the sea water and the DMS production of algae (Charlson et al., 1987; Bates et al., 1992). At Kevo, the MSA has a clear seasonal cycle with peak from April to August (Fig. 4E). The concentrations are about double compared to those at Alert, but this result was expected because Kevo is more directly downwind of the potential source areas in the north Atlantic ocean and the transport from these areas is stronger (Hopke et al., 1995). The variation of yearly average of several constituents, normalized with the 1965 level, is shown in Fig. 7. Copper and zinc concentrations have a slowly decreasing pattern, approximately 0.5 and 0.9 ng m3 decrease per year for Cu and Zn respectively, until the steep rise in 1977. Most other constituents (Ag, Al, Br, Ca2+, Co, I, Mn, Na, SO2 4 , Ti, V, and MSA) have the highest yearly average in 1969. The patterns for Mn and Ca2+
Fig. 7. Variation of yearly average normalized to the 1965 average.
are similar (Fig. 7B). There are no emission estimations for industrial sources of Ca2+ available, but Jaffe et al. (1995) observed elevated Ca concentrations in a snowpack near Kirovsk. Apatite contains also manganese and the observed average Ca/Mn of 44 indicates that the apatite mine is a likely source. Other possible sources common for Ca and Mn could be metal industry (iron mining in Kovdor and Olenegorsk) and wood processing. For Co and Al (Fig. 7C), the 1970 concentration is lower and the 1974 peak is higher than for Mn and Ca2+. Al is usually associated with local crustal sources, but, in Kevo, soil seems to be a weak source. Residual oil combustion is a common source for vanadium and coal and oil produce SO2 after atmo4 spheric processing of the emitted SO2. Their year-to-year variations have similar patterns, although the variation in vanadium concentrations is much stronger (Fig. 7D). In early 1970s, the Monchegorsk smelter started to use the high-sulfur Norilsk ore (Pozniakov, 1993). The increased metal production and substantially increased emissions of SO2 are not observed in the yearly averages of species at Kevo. Tuovinen et al. (1993) estimated that the percentage contributions of Nikel, Zapolyarnyy and Monchegorsk SO2 emissions at Kevo in July 1990–June 1991 were 9%, 3% and 6%, respectively. The concentration of BC decreases sharply in 1967, but has increased steadily after that (Fig. 7E). No other
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constituent has a similar trend. The variation in MSA yearly average is small except for the peak at 1969 (Fig. 7F). There is no correlation between the yearly average of MSA and the average northern hemisphere temperature anomaly. These historical values can be compared to more recent measurements made at Sevettij.arvi, Finland (69E350 N, 28E500 E, 130 m AMSL) (Virkkula et al. 1999, 1995; Ricard et al., 2002a,b). The average concentrations of Zn, Cu, As and Sb were 4 to 6 times higher than the average concentrations reported from Sevettij.arvi between 27 October 1993, and 5 July 1994 by Virkkula et al. (1999). Sevettij.arvi is located 60 km WNW from Nikel. Since the 1993–1994 data does not include the time from July to October, when most constituents have lower concentrations than during winter/spring, the actual Kevo/Sevettij.arvi ratio should be even higher suggesting significant decrease in the emissions between 1978 and 1993. Ricard et al. (2002a) made measurements at Sevettij.arvi from September 1997 to June 1999 with results that were similar to those of Virkkula et al. (1999). The seasalt species at Kevo are similar in concentration to those observed at Sevettij.arvi. It is impossible to judge the relative degree of chlorine displacement from the seasalt for Kevo and Sevettij.arvi because of the chlorine blank value problems described earlier.
4. Conclusions The chemical composition of historical samples of Arctic aerosol has been determined to provide the first time series of Arctic Haze compositions from the 1960s and 1970s. These data provide a first view of Arctic air quality in this time period. Because of the proximity of the sampling site at Kevo, Finland to the Kola Peninsula’s highly industrialized area, concentrations of chemical species with anthropogenic origin, especially Zn, Sb, As, In and K, are much higher at Kevo than observed at Alert in the Canadian Arctic from 1980 to 1991 or at Sevettij.arvi, Finland in the 1990s. The MSA at Kevo is much higher than at Alert but somewhat lower than is observed in later years at Sevettij.arvi. Soil and seasalt elements are relatively low in abundance at Kevo and lower than at Sevettij.arvi. Significant changes can be seen in the year-to-year variation, resulting from the variation in emission strength and transportation efficiency. It is not possible to obtain any detailed records on emissions in the Soviet Union from that time period and thus, it is difficult to relate the observed yearto-year variations with industrial activity patterns in the region. Future work will include the data analysis using multivariate time series methods and back trajectory analysis.
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Acknowledgements The work at Clarkson University and University of Texas at Austin was supported by the Cooperative Institute For Arctic Research.
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