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An Amended Chemical Mass Balance Model for Source Apportionment of PM2.5 in Typical Chinese Eastern Coastal Cities
An adequate air quality analysis requires interpretation regarding not only how severe pollution is but also how the pollution is formed. In this work, an amendment to the chemical mass balance (CMB) model is proposed to obtain better source apportionment of PM2.5. First, localized PM2.5 source profiles for Chinese eastern coastal cities are obtained by in situ sampling. Then, a judgment diagram is established for quick preliminary judgment. CMB models, including an original standard model and an amended two‐step model, are applied to apportion highly mixed samples. For the amended CMB model, simulation is first executed with the ratios of metal elements to Al, to apportion windowsill dust into soil dust, road dust, construction dust, and vehicle dust. Then, a virtual mixed source profile was built with the proportion ratio. The second CMB model is executed to apportion ambient dust based on the virtual mixed source profile instead of divided dusts. Finally, the proportions of soil dust, road dust, and construction dust are obtained by redistributing the virtual mixed sources within ambient dust. The modeling results show that the amended CMB method could separate different fugitive dusts and obtain reasonable results: secondary sulfate contributes the most to PM2.5 pollution in Chinese eastern coastal cities at 44.50%, followed by vehicle exhaust dust and ammonium nitrate; the fugitive dusts are more precisely apportioned and soil dust, road dust, construction dust, and windowsill dust contribute 2.24, 0.47, 0.09, and 1.84%, respectively.
An Amended Chemical Mass Balance Model for Source Apportionment of PM2.5 in Typical Chinese Eastern Coastal Cities
An adequate air quality analysis requires interpretation regarding not only how severe pollution is but also how the pollution is formed. In this work, an amendment to the chemical mass balance (CMB) model is proposed to obtain better source apportionment of PM2.5. First, localized PM2.5 source profiles for Chinese eastern coastal cities are obtained by in situ sampling. Then, a judgment diagram is established for quick preliminary judgment. CMB models, including an original standard model and an amended two‐step model, are applied to apportion highly mixed samples. For the amended CMB model, simulation is first executed with the ratios of metal elements to Al, to apportion windowsill dust into soil dust, road dust, construction dust, and vehicle dust. Then, a virtual mixed source profile was built with the proportion ratio. The second CMB model is executed to apportion ambient dust based on the virtual mixed source profile instead of divided dusts. Finally, the proportions of soil dust, road dust, and construction dust are obtained by redistributing the virtual mixed sources within ambient dust. The modeling results show that the amended CMB method could separate different fugitive dusts and obtain reasonable results: secondary sulfate contributes the most to PM2.5 pollution in Chinese eastern coastal cities at 44.50%, followed by vehicle exhaust dust and ammonium nitrate; the fugitive dusts are more precisely apportioned and soil dust, road dust, construction dust, and windowsill dust contribute 2.24, 0.47, 0.09, and 1.84%, respectively.
An Amended Chemical Mass Balance Model for Source Apportionment of PM2.5 in Typical Chinese Eastern Coastal Cities
Wang, Qiaoli (author) / Cheng, Nana (author) / Li, Sujing (author) / Dong, Minli (author) / Wang, Xiangqian (author) / Ge, Linlin (author) / Guo, Tianjiao (author) / Li, Wei (author) / Gao, Xiang (author)
2019-02-01
12 pages
Article (Journal)
Electronic Resource
English
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