The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Fine particulate matter (PM 2.5 ) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology
Open accessAbstract
Abstract. Fine particulate matter (PM2.5) is a severe air pollution problem in China. Observations of PM2.5 have been available since 2013 from a large network operated by the China National Environmental Monitoring Center (CNEMC). The data show a general 30 %–50 % decrease in annual mean PM2.5 across China over the 2013–2018 period, averaging at −5.2 µg m−3 a−1. Trends in the five megacity cluster regions targeted by the government for air quality control are -9.3±1.8 µg m−3 a−1 (±95 % confidence interval) for Beijing–Tianjin–Hebei, -6.1±1.1 µg m−3 a−1 for the Yangtze River Delta, -2.7±0.8 µg m−3 a−1 for the Pearl River Delta, -6.7±1.3 µg m−3 a−1 for the Sichuan Basin, and -6.5±2.5 µg m−3 a−1 for the Fenwei Plain (Xi'an). Concurrent 2013–2018 observations of sulfur dioxide (SO2) and carbon monoxide (CO) show that the declines in PM2.5 are qualitatively consistent with drastic controls of emissions from coal combustion. However, there is also a large meteorologically driven interannual variability in PM2.5 that complicates trend attribution. We used a stepwise multiple linear regression (MLR) model to quantify this meteorological contribution to the PM2.5 trends across China. The MLR model correlates the 10 d PM2.5 anomalies to wind speed, precipitation, relative humidity, temperature, and 850 hPa meridional wind velocity (V850). The meteorology-corrected PM2.5 trends after removal of the MLR meteorological contribution can be viewed as being driven by trends in anthropogenic emissions. The mean PM2.5 decrease across China is −4.6 µg m−3 a−1 in the meteorology-corrected data, 12 % weaker than in the original data, meaning that 12 % of the PM2.5 decrease in the original data is attributable to meteorology. The trends in the meteorology-corrected data for the five megacity clusters are -8.0±1.1 µg m−3 a−1 for Beijing–Tianjin–Hebei (14 % weaker than in the original data), -6.3±0.9 µg m−3 a−1 for the Yangtze River Delta (3 % stronger), -2.2±0.5 µg m−3 a−1 for the Pearl River Delta (19 % weaker), -4.9±0.9 µg m−3 a−1 for the Sichuan Basin (27 % weaker), and -5.0±1.9 µg m−3 a−1 for the Fenwei Plain (Xi'an; 23 % weaker); 2015–2017 observations of flattening PM2.5 in the Pearl River Delta and increases in the Fenwei Plain can be attributed to meteorology rather than to relaxation of emission controls.
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Cites
Cohen, A. J., Brauer, M., Burnett, R., Anderson, H. R., Frostad, J., Estep, K., Balakrishnan, K., Brunekreef, B., Dandona, L., Dandona, R., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)30505-6 · Cited by 6,583
Effect of climate change on air quality
Jacob, D. J., & Winner, D. A. (2009) · Atmospheric Environment · doi:10.1016/j.atmosenv.2008.09.051 · Cited by 1,979
Self-citationAnthropogenic drivers of 2013–2017 trends in summer surface ozone in China
Li, K., Jacob, D. J., Liao, H., Shen, L., Zhang, Q., & Bates, K. H. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1812168116 · Cited by 1,804
Self-citationFine particulate matter (PM2.5) in China at a city level
Zhang, Y.-L., & Cao, F. (2015) · Scientific Reports · doi:10.1038/srep14884 · Cited by 921
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A two-pollutant strategy for improving ozone and particulate air quality in China
Li, K., Jacob, D. J., Liao, H., Zhu, J., Shah, V., Shen, L., Bates, K. H., Zhang, Q., & Zhai, S. (2019) · Nature Geoscience · doi:10.1038/s41561-019-0464-x · Cited by 874
Self-citationOzone pollution threatens the production of major staple crops in East Asia
Feng, Z., Xu, Y., Kobayashi, K., Dai, L., Zhang, T., Agathokleous, E., Calatayud, V., Paoletti, E., Mukherjee, A., Agrawal, M., et al. (2022) · Nature Food · doi:10.1038/s43016-021-00422-6 · Cited by 322
Shah, V., Jacob, D. J., Li, K., Silvern, R. F., Zhai, S., Liu, M., Lin, J., & Zhang, Q. (2020) · Atmospheric Chemistry and Physics · doi:10.5194/acp-20-1483-2020 · Cited by 298
Self-citationReductions in crop yields across China from elevated ozone
Wang, Y., Wild, O., Ashworth, K., Chen, X., Wu, Q., Qi, Y., & Wang, Z. (2022) · Environmental Pollution · doi:10.1016/j.envpol.2021.118218 · Cited by 63
Shi, H., Zhang, J., Zhao, B., Xia, X., Hu, B., Chen, H., Wei, J., Liu, M., Bian, Y., Fu, D., et al. (2021) · Geophysical Research Letters · doi:10.1029/2020gl091105 · Cited by 44
Metadata
- Authors
- Zhai, S., Jacob, D. J., Wang, X., Shen, L., Li, K., Zhang, Y., Gui, K., Zhao, T., & Liao, H.
- Venue
- Atmospheric Chemistry and Physics
- Publisher
- Copernicus GmbH
- Published
- 2019-08-29
- Volume
- 19
- Issue
- 16
- Pages
- 11031-11041
- ISSN
- 1680-7316 (ISSN-L)
- 1680-7324
- OpenAlex
- W2970481843
- Cited by
- 785
- References
- 4
- FWCI
- 40.89
- Type
- journal article
- Language
- en
- Open access
- gold
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- Zhai, S., Jacob, D. J., Wang, X., Shen, L., Li, K., Zhang, Y., Gui, K., Zhao, T., & Liao, H. (2019). Fine particulate matter (PM 2.5 ) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-19-11031-2019
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