In this study, concentrations of elements and ions were measured in atmospheric aerosol and rainwater samples collected at two rural stations on the Mediterranean and Black Sea coasts of Turkey. The ...relationship between chemical compositions of atmospheric aerosol and rainwater was investigated using receptor-oriented methods utilizing long-term data collected at the Antalya and Amasra stations in Turkey. Factor analysis performed on aerosol and rainwater data sets yielded that source types affecting chemical composition of rain and atmospheric particles were generally the same, but the contribution of each source type to rain and aerosol compositions showed differences. Potential source contribution function calculations were performed to determine if source regions affecting the chemical composition of rain and atmospheric particles were identical. The general pattern observed in distribution of source regions in rainwater and aerosol data sets showed some similarities at both stations, but there were substantial differences in detail.
Source regions at the Antalya Station affecting the chemical composition of rainwater were local as compared to source regions affecting the composition of aerosol. The same difference was not observed in the Amasra Station. The source regions for crustal components of rainwater at the Antalya Station included western parts of Turkey, while European countries and North Africa were found to be the source regions affecting crustal components of aerosol at the Antalya Station. Potential source contribution function calculations indicated that major contributions to the anthropogenic components of aerosol at Antalya came mostly from the western parts of Turkey and European countries, while central Anatolia was the major source region contributing to anthropogenic components of rainwater at the Antalya Station. At the Amasra Station, the area north of the Black Sea and western parts of Turkey were the most important source regions affecting crustal and anthropogenic components for both aerosol and rainwater. It was observed that northern Europe, parts of Turkey, Ukraine, Russia, and some Balkan regions were the main source regions contributing to SO
4
2− concentrations both in rainwater and aerosol samples collected at both sampling sites.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
A Sunset Laboratory carbon analyzer with 1-hour time resolution was used to measure organic carbon (OC) and elemental carbon (EC) in fine particles (PM
2.5) at an urban site of Incheon, Korea between ...August and October 2004. Hourly EC measurements yielded an average diurnal pattern that peaked during the morning rush hour traffic on weekdays but not on weekends. However, OC concentrations showed no significant diurnal patterns during the weekday/weekend. Conditional probability functions were used to identify likely local emission source locations of the EC and OC observed at the site, indicating that the EC and OC contributions to the site were mostly coming from the northerly and southerly directions, where two heavy traffic highways and residential area are located. Throughout the study period, numerous short-term excursions of the EC and OC data were identified, but only two distinct carbon elevated events are discussed in this study. The potential source contribution function (PSCF) analysis, which combines hourly EC and OC data with air mass backward trajectories, is performed to help identify the likely source locations and the preferred pathways that cause the two carbon pollution events. One is associated with high ozone episode occurred in the afternoon, resulting in accumulation of secondary organic aerosol. During the high ozone pollution period, the high PSCF values for EC and OC are related to local source and upwind pollution areas. The other was strongly associated with long-range transport of smoke plumes from fires in northern China and southeastern Russia, leading to high enrichment of OC concentrations at the site. This event is clearly observed in the PSCF maps for EC and OC. There was a good correspondence between the hotspot locations identified based on MODIS satellite image data and the high PSCF valued grid cells.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Week-long samples of total suspended particles were collected between 1964 and 1978 from Kevo at the Finnish Arctic and analyzed for a number of chemical species. The chemical composition data was ...analyzed using a mixed 2-way/3-way model. The results of receptor modeling were connected with the back trajectory data in a Potential Source Contribution Function analysis to determine the likely source areas. Nine sources, namely silver emissions, coal/oil shale combustion, biomass burning, non-ferrous smelters (two sources), crustal elements from remote sources, excess silicon from local sources, sea salt particles and biogenic sulfur emissions from marine algae were found. Although the emissions from industrial areas in the Kola Peninsula had an effect on the concentration of anthropogenic pollutants at Kevo, the highest concentrations during winter were transported from the sources in the mid-latitudes. The yearly strength of the biogenic sulfur emissions showed no dependence on the Northern Hemisphere temperature anomaly and thus, a climatic feedback loop could not be confirmed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Introduction Inorganic ion concentrations in event-based wet-only precipitation samples collected during the south-west (SW) monsoon at an urban location in Western India, Ahmedabad between July 2000 ...and September 2002 were measured by Rastogi and Sarin (2007). Methods For the first time at a location in India, an advanced factor analysis model was retrospectively applied to the measured concentrations of ions (Rastogi and Sarin 2007) in precipitation for source apportionment. Positive matrix factorization resolved five factors, including crustal material, sea salt, nitrate/sulfate-rich factor, ammonium-rich factor, and free acidity. Results and discussion Amongst the model-resolved factors, crustal material was the highest contributor to the total dissolved solids (TDS) accounting for 44.1% on average. Potential source contribution function (PSCF) analysis identified source locations along the eastern coast of Somalia, Yemen, Oman, and the United Arab Emirates for this factor. Sea salt was the second highest contributor accounting for 29.8%. The potential source regions of this factor were also identified in the Arabian Sea and the southern Indian Ocean along the coast of Africa, and the Arabian Gulf. This study also examined the spatial relationships between the source locations of chemical species in precipitation and in ambient aerosol (resolved in an earlier study). Conclusions Crustal material was the highest contributor to TDS at the study location. Spatial relationships between aerosol and precipitation factor source regions suggested that below-cloud scavenging of aerosol particles was a likely contributor to the chemical species apportioned to various precipitation factors. Additionally, source types of chemical species in precipitation resolved in this study were qualitatively compared with those identified at other locations in India. The comparison showed that soil was an important contributor to the dissolved mass of chemical species in precipitation at all locations in India.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Potential source contribution function (PSCF) was employed to study the source receptor relationships for 14 chemical species (Mn, SO
4
2−, Zn, Al, Fe, Cu, Cr, Ni, Cd, NO
3, NH
4
+, K
+, Mg
2+,and ...Pb) found in precipitation collected at Lewes, Delaware. This study identified areas of the Eastern United States as possible emission source areas that could have contributed to the 14 element concentrations observed at Lewes. The identified regions in the Eastern United States generally coincide well with known emission source areas. The likely emission sources for these chemical species include oil- and coal-fired power plants, incinerators, motor vehicles, and iron and steel mills.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
An air trajectory statistical approach was developed to estimate the relative contributions of various sources within a planning domain for a receptor site during high air pollution. The proposed ...approach is based on the coupling of residence time analysis and a known emission inventory. The theoretical basis of the approach is detailed. The approach was applied to investigate the relative contributions of various anthropogenic volatile organic compound (VOC) sources to the ozone formation potential of a receptor site in southern Taiwan. One hundred and ninety‐seven ozone events (defined as those with an hourly ozone concentration that exceeded 120 ppb standard) over 1994–1998 were selected to undergo the residence time analysis. The VOC emission inventory was adjusted to reflect the different ozone formation potentials of the various sources by considering the source VOC profiles and the maximum incremental reactivity scales of each VOC compound. The results show that the sources that influenced the evaluated receptor site were located in northwestern coastal regions; the relative contributions of the point, line, and area sources were in the ration of approximately 5:2:3. Two districts, Kaohsiung City and Kaohsiung Hsien, were the dominant contributors of the five investigated districts. The proposed method may act as a preliminary tool to efficiently select the potential source region/category, such that mitigation and control strategies can be targeted, and/or used to guide a comprehensive modeling study.
Comparison of ionic and carbonaceous compositions of PM2.5 in 2009 and 2012 in Shanghai, China Zhao, Mengfei; Ting QiaoauthorState Environment Protection Key Laboratory on Environmental Risk Assessment and Control on Chemical Processes, East China University of Science & Technology, Shanghai 200237, China; Zhongsi HuangauthorState Environment Protection Key Laboratory on Environmental Risk Assessment and Control on Chemical Processes, East China University of Science & Technology, Shanghai 200237, China ...
2015
Journal Article