Source apportionment of PM_(2.5) light extinction in an urban atmosphere in China
Haze in China is primarily caused by high pollution of atmospheric fine particulates(PM2.5).However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This...
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Published in: | Journal of environmental sciences (China) Vol. 63; no. 1; pp. 277 - 284 |
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Main Authors: | , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Netherlands
2018
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Subjects: | |
Online Access: | Get full text |
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Summary: | Haze in China is primarily caused by high pollution of atmospheric fine particulates(PM2.5).However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This study obtained the mass concentrations of the chemical compositions and the light extinction coefficients of fine particles in the winter in Dongguan, Guangdong Province, using high time resolution aerosol observation instruments. We combined the positive matrix factor(PMF) analysis model of organic aerosols and the multiple linear regression method to establish a quantitative relationship model between the main chemical components, in particular the different sources of organic aerosols and the extinction coefficients of fine particles with a high goodness of fit(R~2= 0.953). The results show that the contribution rates of ammonium sulphate,ammonium nitrate, biomass burning organic aerosol(BBOA), secondary organic aerosol(SOA) and black carbon(BC) were 48.1%, 20.7%, 15.0%, 10.6%, and 5.6%, respectively. It can be seen that the contribution of the secondary aerosols is much higher than that of the primary aerosols(79.4% versus 20.6%) and are a major factor in the visibility decline. BBOA is found to have a high visibility destroying potential, with a high mass extinction coefficient, and was the largest contributor during some high pollution periods. A more detailed analysis indicates that the contribution of the enhanced absorption caused by BC mixing state was approximately 37.7% of the total particle absorption and should not be neglected. |
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Bibliography: | Fine particles Organic aerosol Positive matrix factorisation Light extinction Multiple linear regression Haze in China is primarily caused by high pollution of atmospheric fine particulates(PM2.5).However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This study obtained the mass concentrations of the chemical compositions and the light extinction coefficients of fine particles in the winter in Dongguan, Guangdong Province, using high time resolution aerosol observation instruments. We combined the positive matrix factor(PMF) analysis model of organic aerosols and the multiple linear regression method to establish a quantitative relationship model between the main chemical components, in particular the different sources of organic aerosols and the extinction coefficients of fine particles with a high goodness of fit(R~2= 0.953). The results show that the contribution rates of ammonium sulphate,ammonium nitrate, biomass burning organic aerosol(BBOA), secondary organic aerosol(SOA) and black carbon(BC) were 48.1%, 20.7%, 15.0%, 10.6%, and 5.6%, respectively. It can be seen that the contribution of the secondary aerosols is much higher than that of the primary aerosols(79.4% versus 20.6%) and are a major factor in the visibility decline. BBOA is found to have a high visibility destroying potential, with a high mass extinction coefficient, and was the largest contributor during some high pollution periods. A more detailed analysis indicates that the contribution of the enhanced absorption caused by BC mixing state was approximately 37.7% of the total particle absorption and should not be neglected. 11-2629/X |
ISSN: | 1001-0742 1878-7320 |
DOI: | 10.1016/j.jes.2017.07.016 |