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Chemical composition and source apportionment of PM10 and PM2.5 in different functional areas of Lanzhou,China 被引量:34

Chemical composition and source apportionment of PM_(10) and PM_(2.5) in different functional areas of Lanzhou,China
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摘要 To elucidate the air pollution characteristics of northern China, airborne PM_10(atmospheric dynamic equivalent diameter ≤ 10 μm) and PM_(2.5)(atmospheric dynamic equivalent diameter ≤ 2.5 μm) were sampled in three different functional areas(Yuzhong County,Xigu District and Chengguan District) of Lanzhou, and their chemical composition(elements, ions, carbonaceous species) was analyzed. The results demonstrated that the highest seasonal mean concentrations of PM_10(369.48 μg/m^3) and PM_(2.5)(295.42 μg/m^3) were detected in Xigu District in the winter, the lowest concentration of PM_(2.5)(53.15 μg/m^3) was observed in Yuzhong District in the fall and PM_10(89.60 μg/m^3) in Xigu District in the fall.The overall average OC/EC(organic carbon/elemental carbon) value was close to the representative OC/EC ratio for coal consumption, implying that the pollution of Lanzhou could be attributed to the burning of coal. The content of SNA(the sum of sulfate, nitrate,ammonium, SNA) in PM_(2.5)in Yuzhong County was generally lower than that at other sites in all seasons. The content of SNA in PM_(2.5)and PM_10 in Yuzhong County was generally lower than that at other sites in all seasons(0.24–0.38), indicating that the conversion ratios from precursors to secondary aerosols in the low concentration area was slower than in the area with high and intense pollutants. Six primary particulate matter sources were chosen based on positive matrix factorization(PMF) analysis, and emissions from dust, secondary aerosols, and coal burning were identified to be the primary sources responsible for the particle pollution in Lanzhou. To elucidate the air pollution characteristics of northern China, airborne PM_10(atmospheric dynamic equivalent diameter ≤ 10 μm) and PM_(2.5)(atmospheric dynamic equivalent diameter ≤ 2.5 μm) were sampled in three different functional areas(Yuzhong County,Xigu District and Chengguan District) of Lanzhou, and their chemical composition(elements, ions, carbonaceous species) was analyzed. The results demonstrated that the highest seasonal mean concentrations of PM_10(369.48 μg/m^3) and PM_(2.5)(295.42 μg/m^3) were detected in Xigu District in the winter, the lowest concentration of PM_(2.5)(53.15 μg/m^3) was observed in Yuzhong District in the fall and PM_10(89.60 μg/m^3) in Xigu District in the fall.The overall average OC/EC(organic carbon/elemental carbon) value was close to the representative OC/EC ratio for coal consumption, implying that the pollution of Lanzhou could be attributed to the burning of coal. The content of SNA(the sum of sulfate, nitrate,ammonium, SNA) in PM_(2.5)in Yuzhong County was generally lower than that at other sites in all seasons. The content of SNA in PM_(2.5)and PM_10 in Yuzhong County was generally lower than that at other sites in all seasons(0.24–0.38), indicating that the conversion ratios from precursors to secondary aerosols in the low concentration area was slower than in the area with high and intense pollutants. Six primary particulate matter sources were chosen based on positive matrix factorization(PMF) analysis, and emissions from dust, secondary aerosols, and coal burning were identified to be the primary sources responsible for the particle pollution in Lanzhou.
出处 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2016年第2期75-83,共9页 环境科学学报(英文版)
基金 supported by the Special Scientific Research Funds for Environment Protection Commonweal Section (Nos.201409003,201309011) the National Natural Science Foundation of China (No.41375132) the CAS Strategic Priority Research Program (No.XDB05030400) the National Basic Research Program of China (No.2014CB441203) the Beijing Municipal Science and Technology Plan (No.Z131100006113013)
关键词 Chemical composition Particulate matter Source apportionment Functional areas Chemical composition Particulate matter Source apportionment Functional areas
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