Articles | Volume 17, issue 21
https://doi.org/10.5194/acp-17-13473-2017
https://doi.org/10.5194/acp-17-13473-2017
Research article
 | 
13 Nov 2017
Research article |  | 13 Nov 2017

Analysis of influential factors for the relationship between PM2.5 and AOD in Beijing

Caiwang Zheng, Chuanfeng Zhao, Yannian Zhu, Yang Wang, Xiaoqin Shi, Xiaolin Wu, Tianmeng Chen, Fang Wu, and Yanmei Qiu

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Cited articles

Alebrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989.
Bibi, H., Alam, K., Christie, F., Bibi, S., Shahid, I., and Blaschke, T.: Intercomparison of MODIS, MISR, OMI, and CALIPSO aerosol optical depth retrievals for four locations on the Indo-Gangetic plains and validation against AERONET data, Atmos. Environ., 111, 113–126, https://doi.org/10.1016/j.atmosenv.2015.04.013, 2015.
Charlson, R. J., Schwartz, S. E., Hales, J. M., Cess, R. D., Coakley, J. A., Hansen, J. E., and Hofmann, D. J.: Climate forcing by anthropogenic aerosols, Science, 255, 423–430, https://doi.org/10.1126/science.255.5043.423, 1992.
CMA (China Meteorological Administration): Hourly averaged meteorological parameters, available at: http://data.cma.cn/site/index.html (last access: March 2017), 2011–2015.
Corbin, K. C., Kreidenweis, S. M., and Vonder Haar, T. H.: Comparison of aerosol properties derived from Sun photometer data and ground-based chemical measurements, Geophys. Res. Lett., 29, 1363, https://doi.org/10.1029/2001gl014105, 2002.
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This study analyzes influential factors including the aerosol type, relative humidity (RH), atmospheric boundary layer height (BLH), wind speed and direction, and aerosol vertical structure to the AOD–PM2.5 relationship. It shows that the ratio of PM2.5 to AOD, η, varies a lot with aerosol type. η is smaller for scattering-dominant (coarse mode) than for absorbing-dominant (fine mode) aerosol. The higher the RH (BLH), the larger (smaller) the η. η also decreases with the surface wind speed.
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