The pollution characteristics and source apportionment of regional atmospheric fine particles

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作者
机构
[1] Chen, Duo-Hong
[2] Li, Mei
[3] Huang, Bo
[4] Jiang, Bin
[5] Zhang, Tao
[6] Jiang, Ming
[7] Xie, Min
[8] Zhong, Liu-Ju
[9] Bi, Xin-Hui
[10] Lv, Xiao-Ming
[11] Zhang, Gan
[12] Zhou, Zhen
来源
Li, Mei (limei2007@163.com) | 1600年 / Chinese Society for Environmental Sciences卷 / 36期
关键词
Organic carbon - Heavy metals - Photochemical reactions - Aerosols - Particles (particulate matter) - Coal industry;
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摘要
Single particle aerosol mass spectrometer (SPAMS) was used to analyze the single particle characteristics of aerosols in Heshan, in December 2012. Two typical pollution processes were captured during the sampling period. The fine particles were dominated by elemental carbon (EC), which accounted for 56.8% of total particles. Organic carbon (OC) and heavy metal (HM) accounted for 12.7% and 10.1% of sampled particles, respectively. Different particle types showed different temporal profiles during the two pollution processes, indicating the characteristics of the two processes were different. The source apportionment results showed that the most important PM2.5 sources in this region were vehicle emission and coal combustion, accounting for 24.8% and 22% of PM2.5, respectively. Industry emission and biomass burning were also important, contributing 16.4% and 10.3% to total PM2.5 particles, respectively. During the first pollution process, industry emission was the most important source, and the contribution of coal combustion and secondary inorganic aerosol were found to be increasing with PM2.5 concentration, implying that primary emission as well as enhanced secondary photochemical reaction played important roles in the increasing of PM2.5 concentration. However, vehicle emission was the most important source during the secondary pollution process, and the proportion of each source was stable during the whole pollution process, indicating this process was induced by the accumulation of pollutants under unfavorable meteorological conditions. © 2016, Chinese Society for Environmental Sciences. All right reserved.
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