Source Regions for Atmospheric Aerosol Measured at Barrow, Alaska

They also could improve the understanding of the climatology and optical properties of aerosol over Alaska that can be used to assess the radiative fo...
0 downloads 0 Views 3MB Size
Download PDF
Environ. Sci. Technol. 2001, 35, 4214-4226

Source Regions for Atmospheric Aerosol Measured at Barrow, Alaska ALEXANDER V. POLISSAR AND PHILIP K. HOPKE* Department of Chemical Engineering, Clarkson University, Potsdam, New York 13699-5705 JOYCE M. HARRIS Climate Monitoring and Diagnostics Laboratory R/E/CG1, NOAA, 325 Broadway, Boulder, Colorado 80303

Aerosol data consisting of condensation nuclei (CN) counts, black carbon (BC) mass concentration, and aerosol light scattering coefficient at the wavelength of 450 nm (SC) measured at Barrow, AK, from 1986 to 1997 have been analyzed. BC and SC show an annual cycle with the Arctic haze maxima in the winter and spring and the minima in the summer. The CN time series shows two maxima in March and August. Potential source contribution function (PSCF) that combines the aerosol data with air parcel backward trajectories was applied to identify potential source areas and the preferred pathways that give rise to the observed high aerosol concentrations at Barrow. Tenday isentropic back trajectories arriving twice daily at 500 and 1500 m above sea level were calculated for the period from 1986 to 1997. The PSCF analyses were performed based on the 80th percentile criterion values for the 2and 24-h averages of the measured aerosol parameters. There was a good correspondence between PSCF maps for the 2- and 24-h averages, indicating that 1-day aerosol sampling in the Arctic adequately represents the aerosol source areas. In winter, the high PSCF values for BC and SC are related to industrial source areas in Eurasia. The trajectory domain in winter and spring is larger than in summer, reflecting weaker transport in summer. No high PSCF areas for BC and SC can be observed in summer. The result is related to the poor transport into the Arctic plus the strong removal of aerosol by precipitation in summer. In contrast to the BC and SC maps, the CN plot for summer shows high PSCF areas in the North Pacific Ocean. High CN values appear to be mostly connected with the longrange transport from Eurasia in winter and spring and with the reduced sulfur compound emission from biogenic activities in the ocean in the summer. PSCF analysis was found to be effective in identifying potential aerosol source areas.

lowest are measured in the summer (3). These seasonal variations of the aerosol concentration in the Arctic are related to a combination of different factors including seasonal variability in the long-range transport (5), in the pollutant removal processes (6), in the oxidation rate of SO2 (7), and in the thickness of surface temperature inversions (8). Surface aerosol data including condensation nuclei, black carbon, particle light scattering, and aerosol optical depth measurements have been reported at Barrow, AK (9-12). These parameters are measured on a real time scale at this site. Particle scattering and absorption coefficients show a strong annual cycle with the Arctic haze maximum in the winter and spring and with a minimum in the summer and fall (9, 11). In contrast, the annual cycle for the condensation nucleus (CN) data shows maxima in March and August (9). A decreasing long-term trend in the tropospheric aerosol optical depth (AOD) and the surface aerosol scattering coefficient in the March-April period from 1982 to 1991 was observed at Barrow (10). A similar decrease of the integral atmospheric optical thickness in the Russian Arctic has been reported by Radionov et al. (13). The decrease in the Arctic haze was explained by possible reduction in anthropogenic pollution emissions in Eurasia (10, 13) and reduced transport of anthropogenic aerosol to Barrow (14). Aerosol data measured at Barrow, AK, have been analyzed by three-way positive matrix factorization and by four factors that indicated four different aerosol sources were active throughout the year in Alaska (4). A positive trend for the factor related to CN counts has been observed. This trend was explained by increased biogenic sulfur production caused by reductions in the sea-ice cover in the Arctic and/or an air temperature increase in the vicinity of Barrow (4). The presence of anthropogenic aerosol over the Arctic may result in climate changes. Therefore, the investigation of the aerosol seasonal variations and sources is important. The results could provide an understanding of the mechanisms of atmospheric aerosol transport and transformation. They also could improve the understanding of the climatology and optical properties of aerosol over Alaska that can be used to assess the radiative forcing of climate in this region and to obtain atmospheric corrections of satellite data. Recently, methods have been developed to identify possible source locations of atmospheric aerosol by combining air parcel back trajectories with aerosol data. One such approach is potential source contribution function (PSCF) analysis (15, 16). This method is used in the current study to identify possible source areas for aerosol measured at Barrow, AK. Initial results of the study were reported by Polissar et al. (4). Current work presents the PSCF results for a larger data set from Barrow (12 vs 5 yr), higher spatial resolution (3 × 3° vs 5 × 5°), and the two starting heights for the trajectories. In addition, a different weighting approach described below provided more easily interpreted PSCF maps.

Instrumentation and Data Introduction Aerosol pollutants from distant industrial sources (Arctic haze) have been observed in the Arctic since 1957 (1). A number of studies of the Arctic haze have been published (e.g., refs 2-4). The highest aerosol concentrations are measured during the winter and spring seasons, and the * Corresponding author phone: (315)268-3861; fax: (315)268-6654; e-mail: [email protected]. 4214

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 35, NO. 21, 2001

The station at Barrow (71.32° N, 156.61° W) is a part of a global network of baseline monitoring stations operated by the Climate Monitoring and Diagnostics Laboratory (CMDL) of the National Oceanic and Atmospheric Administration (NOAA). The description of the monitoring site at Barrow, the instrumentation, and the screened aerosol data have previously been presented by Bodhaine (9, 11). Aerosol scattering coefficient was measured continuously with a Meteorology Research Inc. four-wavelength nephelometer (17) similar to the design of Ahlquist and Charlson 10.1021/es0107529 CCC: $20.00

 2001 American Chemical Society Published on Web 09/26/2001

TABLE 1. Percentage of the Reported Hourly Averages for the NOAA Monitoring Site at Barrow, AK year 1986 1987 1988 1989 a

CN

BC

SC

55.3 0.0a 55.1 57.3 0.0a 64.2 48.5 49.3 55.4 45.8 48.3 57.5

year

CN

BC

SC

year

CN

BC

SC

1990 1991 1992 1993

51.4 55.3 54.3 58.4

53.3 51.4 47.7 41.4

63.0 56.8 47.5 52.5

1994 1995 1996 1997

62.3 57.8 47.0 43.9

54.1 49.1 25.6 59.4

53.7 52.4 45.4 61.1

Measurement of black carbon did not begin until 1988.

(18). A rotating filter wheel in front of the photomultiplier allows continuous measurements at 450-, 550-, 700-, and 850-nm wavelengths. The nephelometer automatically switches between ambient air and filtered air and does a real time subtraction to eliminate the instrument background and Rayleigh scattering of air. The nephelometer can measure aerosol scattering as low as about 10-7 m-1 with the accuracy of about (20%. Scattering coefficients were measured without any preconditioning of the air. Since the air is warmed when it passes through the sampling stack and enters the building, the aerosol may be considered to be dried, especially during the winter. The air was not humidity controlled. It was assumed that dry scattering coefficients would not change the results of the current study because the study depends mainly on annual or semiannual cycles and long-term trends that might change slightly in magnitude but not in timing. Condensation nucleus concentrations were originally measured at Barrow using General Electric automatic counter using modified electronics. The instrument was described by Bodhaine and Murphy (19) A TSI Inc. continuos condensation nucleus counter (model 3760) was installed at Barrow in March 1990. The General Electric CN counter is generally considered to have a lower limit of about 0.015 µm diameter particle (20), and the TSI Inc. counter has a lower detection limit for diameters about 0.01 µm. Black carbon (BC) mass concentration was measured with an aethalometer (21) beginning in 1988. The stability of aethalometer optics allows detection of about 1.5 ng m-3 for a 1-h collection period. The aethalometer measures the light absorption by the collected particles. There is considerable uncertainty in the conversion of the light absorption into the mass concentration of BC. However, since the transformation from absorbance to BC mass concentration, the uncertainty in the conversion factor has no effect on the analyses being reported in this paper. The Barrow data were manually edited to remove spikes due to local contamination. If local pollution was suspected, that hour data point was excluded. Wind data for that hour were checked, and the data point was excluded if wind direction was not from the clean-air sector (0-130°) or if wind speed was less than 0.5 m s -1. The details of the algorithm are provided by Bodhaine (11). The percentages of reported hourly averages are presented in Table 1.

Data Analysis and Results Trajectory Data. The Isentropic Transport Model (22) developed at the CMDL was used in the current study of the PSCF for Barrow, AK. Ten-day backward trajectories arriving twice daily at 00 and 12 UT starting at 500 and 1500 m above sea level were calculated. The movement of an air parcel is described by segment end points of coordinates in terms of latitude, longitude, and height of each point. Isentropic trajectories account for adiabatic vertical motions that air parcels may experience en route to their destinations. In the near-surface layer, an air parcel cannot always be traced isentropically because the isentropic surface on which it is traveling may either intersect the ground or be ill-defined in an unstable boundary layer. This transport

model, therefore, calculates trajectories on isentropic surfaces until the specified surface descends to within 100 m of the ground. At this point, the model switches to a layer-averaged mode, where an air parcel is advected by winds averaged through the layer 100-600 m above the surface topography. These heights were chosen to diminish the effects of surface friction and to represent winds in the lower boundary layer. Input to the trajectory model is in the form of 2.5° latitudelongitude gridded meteorological parameters and topography furnished by the European Centre for Medium Range Weather Forecasts or the U.S. National Centers for Environmental Prediction. Most of the techniques employed in this model, such as the transformation from isobaric to isentropic coordinates, horizontal interpolation procedures, and the predictor-correction method for advection, derive from earlier isobaric (23) and isentropic (24) trajectory models. The trajectory model is subject to uncertainty arising from interpolation of sparse meteorological data, assumptions regarding vertical transport, observational errors, sub-gridscale phenomenon, turbulence, convection, evaporation, and condensation. Estimated average horizontal trajectory errors to be 140-290 km in 24 h (25). Any given trajectory produced by this model should be reasonably representative of the large-scale circulation and, as such, may be used to suggest potential source regions. However, this does not imply that a particular air parcel sampled at the trajectory destination exactly followed this path. Potential Source Contribution Function. The construct of the PSCF can be described as follows: if a trajectory end point lies at a cell of address (i, j), the trajectory is assumed to collect material emitted in the cell. Once aerosol is incorporated into the air parcel, it can be transported along the trajectory to the receptor site. The objective is to develop a probability field suggesting likely source locations of the material that results in high measured values at the receptor site. If the total number of end points that fall in the cell is nij and there are mij points for which the measured aerosol parameter exceeds a criterion value selected for this parameter, then the conditional probability, the PSCF, can then be defined as

PSCFij )

mij nij

(1)

In this work, the criterion values for each parameter is the 80th percentile value for the whole period from 1986 to 1997. Note that the criterion value is obtained through off-line statistical analyses. Thus, the PSCF can be interpreted as a conditional probability describing the spatial distribution of probable geographical source locations inferred by using trajectories arriving at the sampling site. Cells related to the high values of PSCF are the potential source areas. Since the PSCF is computed as a ratio of the counts of selected events (mij) to the counts of all events (nij), it is likely that relatively small mij (enij), which are often related to sparse trajectory coverage of the more distant grid cells, may result in PSCFij with high uncertainty in the apparent high value. For large values of n, there is more statistical stability in the calculated value. Thus, to reduce the effect of small values of nij, an arbitrary weight function W(nij) is multiplied into the PSCF value to better reflect the uncertainty in the values for these cells:

{

1.00 0.70 W(nij) ) 0.42 0.17

150 < nij 15 < nij e 150 5 < nij e 15 nij e 5

}

(2)

The set of trajectory data for each arriving elevation level contained two trajectories per each day of the 12 yr of VOL. 35, NO. 21, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

4215

measurements. There are 80 end points in each trajectory. Therefore, the total number of the end points was 2 × 12 × 365.25 × 80 or about 7.0 × 105. The PSCF grid covers the northern hemisphere with 10800 cells of 3° × 3° latitude and longitude so that in average there are 7.1 × 105/10800 or about 65 end points per cell. The PSCF values were downweighted when the total number of the end points per a particular cell was less than about three times the average value of the end points per each cell. It was found that the 150, 15, and 5 limit values for the weighting function are reasonable, and the number of end points per cell less than 150 could produce high uncertainty of the PSCF calculations. In addition, this weighting function reduces the contribution from the cells with relatively small number of end points representing unusual transport events. These weighting function limit values were obtained empirically by running the PSCF program many times and applying the trial and error method. A similar weighting approach has been used for other PSCF calculations studies (15, 16). Because subsets of the total data set were used for the seasonal PSCF calculations, a different weighting function was used:

{

1.00 0.70 W(nij) ) 0.42 0.17

50 < nij 10 < nij e 50 5 < nij e 10 nij e 5

}

(3)

This weighting function has lower limit values because the seasonal subsets have fewer data points than the whole data set. To perform analysis of the PSCF, 10-day backward trajectories arriving twice daily at 00 and 12 UT starting at 500 and 1500 m above sea level over Barrow for each day of the 12-yr period from 1986 to 1997 were calculated. Arithmetic means of the two consecutive values of each parameter (CN, BC, and SC) reported for 23 and 00 UT (this values represent the averages for the hours 23-00 and 00-01, respectively) and for 11 and 12 UT corresponding to each trajectory for a particular date have been calculated. Then, the 2-h averages, which were higher than the corresponding 12-yr 80th percentile, were identified and used to determine the trajectory segment end point associated with these high pollution level measurements. The PSCF analysis identifies the potential source areas or possible pathways of transport into the Arctic from regions within the domain covered by 10-day back trajectories that result in measurements above the 80th percentile concentrations. However, the analysis does not estimate the spatial distribution of all the emission sources. Only those emissions that have been transported to the sampling site can be identified. A high PSCF region should coincide with a known emissions region within the domain. However, a region with a low value of the PSCF does not necessarily indicate low emissions from the region. The PSCF analysis was used by Cheng et al. (15) and Hopke et al. (16) for identification of possible sources and preferred pathways for biogenic, non-sea-salt sulfur, and other aerosol species to Alert, Canada. Box plots for CN concentration, BC mass concentration, and SC are shown in Figure 1. These plots based on 2-day arithmetic means for each aerosol parameter for avoiding the autocorrelation in reported 1-h average values. The details of the approach are provided by Bodhaine (11) along with more detailed analyses. The scale for the BC and SC plots was chosen to align the lowest June and highest March BC and SC values providing easier comparison of the seasonal variations. BC and SC (Figure 1B) time-series show an annual cycle with the typical Arctic haze maxima in winter-spring and 4216

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 35, NO. 21, 2001

FIGURE 1. Box plots for condensation nucleus number concentration (CN) (A), black carbon mass concentration (BC) (B), and aerosol scattering coefficient at the 450-nm wavelength (SC) (B) obtained for the 2-day means for Barrow for the period from 1986 to 1997. The plots show the median, 10th, 25th, 75th, and 90th percentiles as vertical boxes with error bars. The dotted line represents the January data. with the minima in the summer. It has been hypothesized that the Arctic haze maxima are caused by long-range transport from industrial regions in the winter and spring (3). The scattering coefficient time series usually have broad peaks or a combination of two major peaks when the winter maximum is connected with long-range aerosol transport and the spring peak is associated with the long-range transport plus photochemically enhanced sulfate production from SO2 (7, 26). Therefore, normalized time series for SC show higher than BC median in April-May (Figure 1B). The condensation nucleus plot shows maxima in March and August and minima in May and November (Figure 1A). The spring maximum for the condensation nucleus could be mostly connected with long-range transported aerosol and/ or photochemical oxidation of SO2 while the summer maximum could be related to the formation of biogenic sulfur particles (27, 28). Because of the periodic behavior of the time series shown in Figure 1, the data for the 12-yr period from 1986 to 1997 were divided into three sets representing different seasons. PSCF maps were calculated for the whole data set and for the periods from October to February (winter), from March to May (spring), and from June to September (summer), respectively, corresponding to the properties of the time series shown in Figure 1. The PSCF plots for the whole set and for these three seasons of the 12-yr interval from 1986 to 1997 for CN, BC, and SC and are presented in Figures 2-9. Major sources of BC and particles related to light scattering for both arrival heights are located in the former Soviet Union (Figures 3 and 4). In contrast to this, the PSCF maps for condensation nuclei shows major source areas in the North Pacific Ocean and in the Arctic Ocean (Figure 2). There is also a source area for CN north of Norway (Figure 2A). The

FIGURE 2. Potential source contribution function plots for condensation nuclei (CN) for the 500- (A) and 1500-m (B) elevations above sea level for Barrow for the period from 1986 to 1997. SC 500-m elevation plot also shows a limited area of moderate to high PSCF values in the Pacific Ocean near the west coast of the United States as well as in the Canadian Arctic (Figure 4A). The first high PSCF region in Eurasia is similar for CN, BC, and SC and can be seen in Central Asia, in the vicinities of Dushanbe, Tajikistan; Tashkent, Uzbekistan; and Almaty, Kazakhstan (Figures 2A-4A). A clear pathway crossing

Kazakhstan from south to north from this Central Asian source region toward city of Omsk, Russia, can be seen in Figures 2A-4A. The second source area for the 500-m elevation for CN, BC, and SC in southern Russia is located in the Kuznetsk industrial region near the cities of Novokuznetsk and Biysk close to the border of Russia and China between Kazakhstan VOL. 35, NO. 21, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

4217

FIGURE 3. Potential source contribution function plots for black carbon (BC) for the 500- (A) and 1500-m (B) elevations above sea level for Barrow for the period from 1986 to 1997. and Mongolia (Figures 2A-4A). Transport north from this area along The Ob River can be clearly seen in the CN plot (Figure 2A). High PSCF areas can also be seen in the Russian Arctic; in Norilsk, Vorkuta, and Perm industrial zones; and in Yakutiya north and west of Yakutsk (Figures 2A-4A). These results agree with sulfur emissions results for the former Soviet Union territory (29) and with the global gridded inventories of anthropogenic emissions (30). The potential 4218

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 35, NO. 21, 2001

source area in Yakutiya located near Udachnyy, the largest diamond mine in Russia. There are also several other mines in Yakutiya north of Yakutsk. The high PSCF area in Yakutiya could be connected with the wood and coal combustion smoke as well as emissions from motor vehicles at the mines. Large potential source areas for BC and SC but not for CN can be seen in the vicinity of the Irtysh River in Asian Russia near the Kazakhstan border. This areas could be related to

FIGURE 4. Potential source contribution function plots for particles related to light scattering at 450 nm (SC) for the 500- (A) and 1500-m (B) elevations above sea level for Barrow for the period from 1986 to 1997. combustion sources in large Tiumen oil and gas production area west of the Irtysh River north of Kazakhstan (Figures 3A-4A). Areas with PSCF higher 0.3 for BC and SC cover major part of Siberia east of the Ob River extended toward Yakutiya and the Kolyma River, indicating major source areas and the preferred pathways in Siberia. Relatively high PSCF values

observed within the Arctic basin could be connected with the preferred transport pathways and the aerosol formation caused by the SO2 to SO42- oxidation during the transport rather than with aerosol emissions in the Arctic. All three plots for the 500-m elevation show high PSCF values in the Ottawa and Montreal urban areas (Figures 2A4A). The 500-m elevation plot for SC in addition to the source VOL. 35, NO. 21, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

4219

FIGURE 5. Potential source contribution function plots for particles related to light scattering at 450 nm (SC) for the 500-m elevation above sea level for Barrow for the period from 1986 to 1997. The 24-h averages have been used for the PSCF calculations. areas described above shows sources in European Russia near St. Petersburg and in Finland (Figure 4A). Large potential source areas for SC in the Canadian Arctic most likely represent emissions from the oil and gas production areas near Norman Wells and Fort Liard west of Great Bear and Great Slave Lakes, respectively. These areas also have high PSCF values on the 1500-m elevation SC plot (Figure 4B). There are also potential source areas for SC along the California and Nevada border that may represent transport from the coal-fired power plants in the Southwest that are outside of the range of the trajectories as well as in the vicinity of Winnipeg, Canada (Figure 4A). Higher elevation plots show additional contributions from the areas in the former Soviet Union west of the regions described above, indicating most likely different transport pathways at the higher arriving elevation. The CN 1500-m plot shows source areas in western Norway near Oslo and Great Britain (Figure 2B). These areas could be related to anthropogenic emissions in these countries. In addition to the Kuznetsk and Central Asian regions described above, there are also high potential source areas for the 1500-m elevation for CN, BC, and SC in the Volga and Ural industrial regions (Figures 2B-4B) associated with emissions from large urban areas as well as power plants and metal production facilities in these areas. High PSCF area for the higher elevation for SC also covers eastern part of Moscow region (Figure 4B). The source contribution from the Volga industrial zone near Nighniy Novgorod and from the St. Petersburg area can be seen on both BC and SC plots for the 1500-m elevation (Figures 3B-4B). The BC plot for the 1500-m elevation shows contribution from the northern Russia, Novgorod, and Vologda regions. The CN plot also shows high PSCF areas in Urengoi and Nighnevartovsk oil and gas production areas (Figure 2B). In addition, there is a large high PSCF area for the higher elevation for SC and BC in central Kazakhstan northeast of Aral Sea as well as in the vicinity of Karaganda and Akmola, the new capital of Kazakhstan (Figures 3B and 4B). This source area also can be seen on the CN plot (Figure 2B). 4220

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 35, NO. 21, 2001

The SC plot for the 1500-m elevation shows transport from northern China, from the Harbin and Qiqihar urban areas, and transport from south of European Russia and Ukraine (Figure 4B). BC and SC maps also show potential sources in the western United States in Oregon, Idaho, and Washington (Figures 3B-4B). High PSCF values for both BC and SC for the 1500-m elevation are also obtained for the Salt Lake City area (Figures 3B-4B) and for SC in the area along the Missouri River in North Dakota and South Dakota (Figure 4B). In the Arctic, in addition to the Norilsk industrial zone, a natural gas production source area west of Norilsk near Salekhard, Nadym, and Novyi Urengoi can be seen in the SC plot (Figure 4A,B). This area is less clear on the CN and BC plots. It can be seen that the oil and gas production areas in Canada west of the Great Bear and Great Slave Lakes described above have higher PSCF values for SC than for BC (Figures 3B-4B). This fact could be related to the chemical composition of the aerosol from this source areas and/or the result of the secondary aerosol formation, which could mainly produce particles related to light scattering. BC and SC plots for the both arriving elevations look similar in Eurasia, indicating long-range transport from the same source areas (Figures 3-4). The source areas in the western North America are larger for SC than for BC (Figures 3-4). This result could be related to relatively low black carbon and high sulfate and SO2 loadings in emissions from the western Unites States. In contrast to this, the most likely emissions from the former Soviet Union industrial zones have high loadings of both black carbon and sulfate. Figure 5 shows PSCF plots obtained for the 24-h averages of SC. Arithmetic means of the 24 consecutive values of each parameter (CN, BC, and SC) reported for hours 0-23 UT as well as for 12-11 UT corresponding to each of the two trajectories for a particular date have been calculated. The 24-h averages, which were higher than the 12-yr 80th percentile, were identified and used to determine the trajectory segment end point associated with these high pollution level measurements. A comparison of Figure 4A

FIGURE 6. Potential source contribution function plots for condensation nuclei for the 500-m elevation above sea level for Barrow for the period from 1986 to 1997 during the months of October-February (A) and March-May (B). and Figure 5 shows that there is a good correspondence between PSCF maps for the 2- and 24-h averages, indicating that 1-day aerosol sampling in the Arctic adequately represents the aerosol source areas. In other words, higher than 1-day time resolution aerosol measurements in the Arctic would not provide a better spatial resolution for the source areas identification.

The PSCF plots for the winter (October-February), spring (March-May), and summer (June-September) of the 12-yr interval from 1986 to 1997 for CN, BC, and SC for the 500-m elevations above sea level are presented in Figures 6-9. The Eurasian part of the trajectory domain in spring and summer is smaller than in winter (Figures 6-9); the trajectory domain does not reach any large industrial regions in Eurasia VOL. 35, NO. 21, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

4221

FIGURE 7. Potential source contribution function plots for black carbon for the 500-m elevation above sea level for Barrow for the period from 1986 to 1997 during the months of October-February (A) and March-May (B). and North America in the summer (Figure 9). Thus, longrange transport of anthropogenic aerosol is more effective in winter and spring than in the summer. This conclusion agrees with the seasonal variations shown in Figure 1 and the results reported before (e.g., ref 3). Major sources of black carbon and particles related to light scattering during the winter season are located in the 4222

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 35, NO. 21, 2001

former Soviet Union (Figures 7A and 8A). These source regions are the Norilsk area, Yakutiya, Tiumen oil and gas production area, Ural and Novokuznetsk industrial zones, and industrial regions in Central Asia. These areas were seen on the PSCF plots for the total set of data (Figures 2-4). Thus, the transport from these industrial areas occur during the winter period.

FIGURE 8. Potential source contribution function plots for particles related to light scattering at 450 nm for the 500-m elevation above sea level for Barrow for the period from 1986 to 1997 during the months of October-February (A) and March-May (B). In average, the BC winter map shows higher than for SC and CN values of the PSCF, indicating emissions of aerosol with high loadings of soot (Figure 7). Condensation nuclei source regions in Eurasia during winter and spring (Figure

6) coincide with source regions of black carbon (Figure 7) and particles related to light scattering (Figure 8). However, the high PSCF areas are much smaller for condensation nuclei (Figure 6) than for black carbon (Figure 7) and scattering VOL. 35, NO. 21, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

4223

FIGURE 9. Potential source contribution function plots for condensation nuclei (A) and particles related to light scattering at 450 nm (B) for the 500-m elevation above sea level for Barrow for the period from 1986 to 1997 during the months of June-September. (Figure 8). This result could be related to the shorter residence time for condensation nuclei in air so that fewer of the small particles are transported to the Arctic. In addition, the major source of condensation nuclei in the Arctic during winter and spring could be not a long-range transport itself but SO2 to SO42- conversion during the transport. 4224

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 35, NO. 21, 2001

The spring PSCF plots show larger high PSCF areas in eastern Eurasia indicating less effective long-range transport and more intensive photochemical aerosol formation during the transport in spring than in winter (Figure 9). The CN spring plot at the 500-m elevation (Figures 6B) shows high PSCF areas in Yakutia and in the vicinity of Salekhard in the

West Siberian oil and gas region. The condensation nuclei spring plot shows large high PSCF areas in the North Pacific Ocean (Figure 6B). BC measurements mainly represent the long-range transport of primary particles while measurements of light scattering in the Arctic depend mainly on sulfate concentrations (2, 3) that represent secondary aerosol formation during transport. In the spring, the high PSCF areas for SC are much larger than for BC (Figures 7B and 8B) while in winter areas of high PSCF are much larger for BC than for SC (Figures 7A and 8A). This observation could indicate more effective longrange transport in winter but more effective photochemical aerosol formation during spring transport. Therefore, the scattering coefficient time-series usually has broad peaks or a combination of two major peaks with the winter maximum connected with long-range aerosol transport and the spring peak associated with long-range transport plus photochemically enhanced sulfate production (Figure 1B). Both BC and SC spring plots for show high PSCF areas along the Yenisei River in Siberia, indicating the most likely transport from the Krasnoyarsk industrial area and in the Russian Arctic in the vicinity of Salekhard in the West Siberian oil and gas region (Figures 7B and 8B). There are also potential source areas for BC and SC in Yakutia north of Yakutsk city and in the vicinities of Magadan and Okhotsk along the coast of the Sea of Okhotsk (Figures 7B and 8B). High PSCF areas for BC and SC in Central Siberia can be seen near Bodaibo and Mirnyi (Figures 7B and 8B). The spring PSCF plot for particles related to light scattering also shows potential source areas in northern Canada, most likely indicating emissions from the oil and gas production areas in Norman Wells and Fort Liard (Figure 8B). There is also a possibility that these high PSCF areas in the Canadian Arctic could represent the preferred transport pathways from the Midwestern United States. A small source area in Canada north of Whitehorse related most likely to the mines in Anvill and oil and gas production region in Norman Wells can be seen in the summer SC plot (Figure 9B). However, in the summer no major high PSCF areas for BC and particles connected with light scattering can be observed (Figure 9B). These summer low PSCF values for BC and SC are related to the seasonal variability in the long-range transport (5) and more effective pollutant removal processes in the summer. In contrast, the summer PSCF map for CN shows major sources in the North Pacific Ocean and smaller areas in the Arctic Ocean (Figure 9A). These areas represent sources of particles in the ocean connected with the oxidation of dimethyl sulfide (12, 16, 27). Thus, the summer maximum of the condensation nucleus plot (Figure 1A) is mainly related to the emissions from biological activities in the North Pacific Ocean. There are also high PSCF areas for CN in the summer in the Krasnoyarsk, Norilsk, and Vorkuta industrial areas (Figure 9A). Aerosol data from Barrow, AK, for the period from 1986 to 1997 have been analyzed. BC and SC have seasonal variations with their maxima in December - April associated with long-range aerosol transport. In addition, the SC plot could represent long-range aerosol transport plus more effective photochemical transformation of SO2 to SO42- in the spring. The CN plot hasa maxima in March and JulyAugust. The spring maximum for CN could be connected with the long-range transported aerosol while the summer maximum could be related to biogenic sulfur precursor compounds emitted from the Arctic Ocean and the North Pacific Ocean. PSCF analysis that combines the aerosol data with air parcel backward trajectories was applied to identify potential source areas and the preferred pathways that give rise to the observed high aerosol concentrations at Barrow. Ten-day isentropic back trajectories arriving twice daily at the 500-

and 1500-m elevations above sea level were calculated for the period from 1986 to 1997. The PSCF analyses were performed based on the 80th percentile criterion values for the 2- and 24-h averages of the measured aerosol parameters. There was a good correspondence between PSCF maps for the 2- and 24-h averages indicating that 1-day aerosol sampling in the Arctic adequately represents the aerosol source areas. The PSCF maps show that in winter and spring industrial regions in Eurasia are the major sources of aerosol measured at Barrow with some moderate potential source areas in western North America. A minor contribution from source areas in Western Europe is obtained. In the summer, large areas of the North Pacific Ocean and the Arctic Ocean contribute to observed high condensation nucleus concentrations. It is concluded that PSCF analysis is useful in identifying possible source areas and the potential pathways of aerosol measured at Barrow. It is shown that the long-distance transport from industrial regions, photochemical aerosol production, and emissions from biogenic activities in the ocean are major sources of the aerosol properties measured at Barrow.

Acknowledgments The work at Clarkson University was supported by the National Science Foundation under Grant ATM 9523731. We thank the Barrow observatory staff and NOAA/CMDL base funding. We thank John Ogren, Barry Bodhaine, Yoram J. Kaufman, and Dorothy K. Hall for their helpful comments.

Literature Cited (1) Mitchell, J. M. J. Atmos. Sol.-Terr. Phys. 1957, 195-211. (2) Shaw, G. E.; Khalil, M. A. K. The Handbook of Environmental Chemistry, Vol. 4, Part B; Hutziger, O., Ed.; Springer-Verlag: Berlin, 1989; pp 69-111. (3) Barrie, L. A. Atmos. Environ. 1986, 20, 643-663. (4) Polissar, A. V.; Hopke, P. K.; Paatero, P.; Kaufman, Y. J.; Hall, D. K.; Bodhaine, B. A.; Dutton, E. G.; Harris, J. M. Atmos. Environ. 1999, 33, 2441-2458. (5) Raatz, W. E. Atmos. Environ. 1989, 23, 2501-2504. (6) Barrie, L. A.; Olson, M. P.; Oikawa, K. K. Atmos. Environ. 1989, 23, 2505-2512. (7) Barrie, L. A.; Barrie, M. J. J. Atmos. Chem. 1990, 11, 211-226. (8) Sakunov, G. G.; Timirev, A. A.; Barteneva, O. D. Sov. Meteorol. Hydrol. 1990, 2, 53-58. (9) Bodhaine, B. A. Atmos. Environ. 1989, 23, 2357-2369. (10) Bodhaine, B. A.; Dutton, E. G. Geophys. Res. Lett. 1993, 20, 947950. (11) Bodhaine, B. A. J. Geophys. Res. 1995, 100 (D5), 8967-8975. (12) Ferek, R. J.; Hobbs, P. V.; Radke, L. F.; Herring, J. A. J. Geophys. Res. 1995, 100, 26093-26104. (13) Radionov, V. F.; Marshunova, M. S.; Rusina, Ye. N.; LuboLesnichenko, K. Ye.; Pimanova, Yu. Ye. Izv. Acad. Sci., USSR, Atmos. Oceanic Phys. 1995, 30, 762-766. (14) Jaffe, D.; Iversen, T.; Shaw, G. Geophys. Res. Lett. 1995, 22, 739740. (15) Cheng, M.-D.; Hopke, P. K.; Barrie, L.; Rippe, A.; Olson, M.; Landsberger, S. Environ. Sci. Technol. 1993, 27, 2063-2071. (16) Hopke, P. K.; Barrie, L. A.; Li, S.-M.; Cheng, M.-D.; Li, C.; Xie, Y. J. Geophys. Res. 1995, 100 (D12), 16595-16603. (17) Bodhaine, B. A. Light Absorption by Aerosol Particles; Gerber, H. E., Hindman, E. E., Eds.; Spectrum: Hampton, 1982; pp 149168. (18) Ahlquist, N. C.; Charlson, R. J. Atmos. Environ. 1969, 3, 551564. (19) Bodhaine, B. A.; Murphy, M. E. J. Aerosol Sci. 1980, 11, 305-312. (20) Porstendorfer, J.; Soderholm, S. C. Atmos. Environ. 1978, 12, 1805-1806. (21) Hansen, A. D. A.; Rosen, H.; Novakov, T. Appl. Opt. 1982, 21, 3060-3062. (22) Harris, J. M.; Kahl J. D. W. J. Geophys. Res. 1994, 99 (D12), 2584525855. (23) Harris J. M. The GMCC atmospheric trajectory program; NOAA Technological Memo ERL-ARL-116; NOAA Environmental Research Laboratories: Boulder, CO, 1982; 30 pp. VOL. 35, NO. 21, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

9

4225

(24) Harris, J. M., Bodhaine, B. A., Eds. Geophysical Monitoring for Climatic Change; Summary Report 11; NOAA Environmental Research Laboratories: Boulder, CO, 1982; pp 67-75. (25) Harris, J. M. Tellus 1992, 44B, 409-421. (26) Polissar, A. V.; Hopke, P. K.; Malm, W. C.; Sisler, J. F. J. Geophys. Res. 1998, 103 (D15), 19035-19044. (27) Charlson, R. J.; Lovelock, J. E.; Andreae, M. O.; Warren, S. G. Nature 1987, 326, 655-661. (28) Xie, Y.-L.; Hopke, P. K.; Paatero, P.; Barrie, L. A.; Li, S.-M. J. Atmos. Sci. 1999, 56, 249-260.

4226

9

ENVIRONMENTAL SCIENCE & TECHNOLOGY / VOL. 35, NO. 21, 2001

(29) Ryaboshapko, A.; Gallardo, L.; Kjellstro¨m, E.; Gromov, S.; Paramonov, S.; Afinogenova, O.; Rodhe, H. Atmos. Environ. 1998, 32, 647-658. (30) Benkovitz, C. M.; Scholtz, M. T.; Pacyna, J.; Tarrason, L.; Dignon, J.; Voldner, E. C.; Spiro, P. A.; Logan, J. A.; Graedel, T. E. J. Geophys. Res. 1998, 101 (D22), 29239-29253.

Received for review March 16, 2001. Revised manuscript received August 2, 2001. Accepted August 13, 2001. ES0107529