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10.1016/j.scitotenv.2020.142227

http://scihub22266oqcxt.onion/10.1016/j.scitotenv.2020.142227
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32920418!7473012!32920418
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suck abstract from ncbi


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pmid32920418      Sci+Total+Environ 2021 ; 754 (ä): 142227
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  • Importance of meteorology in air pollution events during the city lockdown for COVID-19 in Hubei Province, Central China #MMPMID32920418
  • Shen L; Zhao T; Wang H; Liu J; Bai Y; Kong S; Zheng H; Zhu Y; Shu Z
  • Sci Total Environ 2021[Feb]; 754 (ä): 142227 PMID32920418show ga
  • Compared with the 21-year climatological mean over the same period during 2000-2020, the aerosol optical depth (AOD) and Angstrom exponent (AE) during the COVID-19 lockdown (January 24-February 29, 2020) decreased and increased, respectively, in most regions of Central-Eastern China (CEC). The AOD (AE) values decreased (increased) by 39.2% (29.4%) and 31.0% (45.3%) in Hubei and Wuhan, respectively, because of the rigorous restrictions. These inverse changes reflected the reduction of total aerosols in the air and the contribution of the increase in fine-mode particles during the lockdown. The surface PM(2.5) had a distinct spatial distribution over CEC during the lockdown, with high concentrations in North China and East China. In particular, relatively high PM(2.5) concentrations were notable in the lower flatlands of Hubei Province in Central China, where six PM(2.5) pollution events were identified during the lockdown. Using the observation data and model simulations, we found that 50% of the pollution episodes were associated with the long-range transport of air pollutants from upstream CEC source regions, which then converged in the downstream Hubei receptor region. However, local pollution was dominant for the remaining episodes because of stagnant meteorological conditions. The long-range transport of air pollutants substantially contributed to PM(2.5) pollution in Hubei, reflecting the exceptional importance of meteorology in regional air quality in China.
  • |*Air Pollutants/analysis[MESH]
  • |*Air Pollution/analysis[MESH]
  • |*Coronavirus Infections[MESH]
  • |*Pandemics[MESH]
  • |*Pneumonia, Viral[MESH]
  • |Betacoronavirus[MESH]
  • |COVID-19[MESH]
  • |China[MESH]
  • |Cities[MESH]
  • |Environmental Monitoring[MESH]
  • |Humans[MESH]
  • |Meteorology[MESH]
  • |Particulate Matter/analysis[MESH]


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