Top-down estimates of benzene and toluene emissions in the Pearl River Delta and Hong Kong, China
Name
Fang-2016-Top-down estimates o.pdf
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1.46 MB
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Checksum (MD5)
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Author(s)
Fang, Xuekun
Shao, Min
Stohl, Andreas
Zhang, Qiang
Zheng, Junyu
Guo, Hai
Wang, Chen
Wang, Ming
Ou, Jiamin
Thompson, Rona L.
Date Issued
March 2016
Journal
Atmospheric Chemistry and Physics
Publisher
Copernicus GmbH
Citation
Fang, Xuekun, Min Shao, Andreas Stohl, Qiang Zhang, Junyu Zheng, Hai Guo, Chen Wang, et al. “Top-down Estimates of Benzene and Toluene Emissions in the Pearl River Delta and Hong Kong, China.” Atmos. Chem. Phys. 16, no. 5 (March 15, 2016): 3369–3382.
Version
Final published version
Abstract
Benzene (C[subscript 6]H[subscript 6]) and toluene (C[subscript 7]H[subscript 8]) are toxic to humans and the environment. They are also important precursors of ground-level ozone and secondary organic aerosols and contribute substantially to severe air pollution in urban areas in China. Discrepancies exist between different bottom-up inventories for benzene and toluene emissions in the Pearl River Delta (PRD) and Hong Kong (HK), which are emission hot spots in China. This study provides top-down estimates of benzene and toluene emissions in the PRD and HK using atmospheric measurement data from a rural site in the area, Heshan, an atmospheric transport model, and an inverse modeling method. The model simulations captured the measured mixing ratios during most pollution episodes. For the PRD and HK, the benzene emissions estimated in this study for 2010 were 44 (12–75) and 5 (2–7) Gg yr[superscript −1] for the PRD and HK, respectively, and the toluene emissions were 131 (44–218) and 6 (2–9) Gg yr[superscript −1], respectively. Temporal and spatial differences between the inversion estimate and four different bottom-up emission estimates are discussed, and it is proposed that more observations at different sites are urgently needed to better constrain benzene and toluene (and other air pollutant) emissions in the PRD and HK in the future.
MIT Department
Massachusetts Institute of Technology. Center for Global Change Science
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.5194/acp-16-3369-2016
