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Influence of pollution control measures on the reduction of black carbon in an urban site of megacity, Tianjin, China based on ground-monitored and MERRA-2 reanalysis data.
Cheng, Xin; Yu, Jie; Chen, Li; Sun, Yanling; Zhang, Hui; Gao, Shuang; Kong, Shaofei; Zheng, Huang; Wang, Hui.
Afiliação
  • Cheng X; School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China.
  • Yu J; School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China.
  • Chen L; School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China.
  • Sun Y; School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China.
  • Zhang H; School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China.
  • Gao S; School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China. Electronic address: shuang1gao@tjnu.edu.cn.
  • Kong S; Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China. Electronic address: kongshaofei@cug.edu.cn.
  • Zheng H; Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China; Research Centre for Complex Air Pollution of Hubei Province, Wuhan 430078, China.
  • Wang H; Tianjin Changhai Environmental Monitoring Service Corporation, Tianjin, China.
Sci Total Environ ; 912: 169466, 2024 Feb 20.
Article em En | MEDLINE | ID: mdl-38145677
ABSTRACT
The concentration of particulate matter (PM) has been reduced significantly with the implementation of air pollution control plans in Tianjin. However, as an important component of PM that can lead to global warming and adverse health effects, the influence of pollution control measures (PCM) on black carbon (BC) has been less studied. In this study, ten years of BC concentration satellite-based reanalysis data were collected from MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2), and their reliability was verified using ground-monitored BC data. Using the proposed Kolmogorov-Zurbenko and artificial neural network (KZ-ANN) model, the influences of meteorology and emission measures were separated. The results indicated that the overall meteorological conditions were not conducive to BC diffusion, especially in autumn and winter with low temperature, surface solar radiation, boundary layer height, and high atmospheric pressure, all of which increased the BC concentration. This study also found that although a significant reduction in BC emissions was observed in Tianjin (the total emissions of BC in 2020 dropped by 52 % compared with the level in 2013), the change in emission-influenced BC was relatively low (the concentration of emission-influenced BC in 2022 dropped by only 2.39 % compared to that in 2013). The reduction of emission-influenced BC concentration during the air pollution prevention control and action plan (APPC) was higher than the level during of the three-year action plan for winning the blue sky defense war (abbreviated as the Blue Sky Defense War). In addition, the lockdown measures during the Corona Virus Disease 2019 (COVID-19) did not have beneficial effect on the reduction of emission-influenced BC concentration. This phenomenon can be explained by the long-range transport of BC from surrounding areas, which was also proven by the results of the backward trajectory analysis. Therefore, efforts on emissions reduction in Tianjin were diminished. It is necessary to cooperate with the governments in surrounding areas to implement joint BC control measures, especially in autumn and winter.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article