标题: Spatiotemporal Patterns of Air Pollutants over the Epidemic Course: A National Study in China
作者: Qin, K (Qin, Kun); Wang, ZP (Wang, Zhanpeng); Dai, SQ (Dai, Shaoqing); Li, YC (Li, Yuchen); Li, MY (Li, Manyao); Li, C (Li, Chen); Qiu, G (Qiu, Ge); Shi, YY (Shi, Yuanyuan); Yin, C (Yin, Chun); Yang, SJ (Yang, Shujuan); Jia, P (Jia, Peng)
来源出版物: REMOTE SENSING 卷: 16 期: 7 文献号: 1298 DOI: 10.3390/rs16071298 Published Date: 2024 APR
摘要: Air pollution has been standing as one of the most pressing global challenges. The changing patterns of air pollutants at different spatial and temporal scales have been substantially studied all over the world, which, however, were intricately disturbed by COVID-19 and subsequent containment measures. Understanding fine-scale changing patterns of air pollutants at different stages over the epidemic's course is necessary for better identifying region-specific drivers of air pollution and preparing for environmental decision making during future epidemics. Taking China as an example, this study developed a multi-output LightGBM approach to estimate monthly concentrations of the six major air pollutants (i.e., PM2.5, PM10, NO2, SO2, O-3, and CO) in China and revealed distinct spatiotemporal patterns for each pollutant over the epidemic's course. The 5-year period of 2019-2023 was selected to observe changes in the concentrations of air pollutants from the pre-COVID-19 era to the lifting of all containment measures. The performance of our model, assessed by cross-validation R-2, demonstrated high accuracy with values of 0.92 for PM2.5, 0.95 for PM10, 0.95 for O-3, 0.90 for NO2, 0.79 for SO2, and 0.82 for CO. Notably, there was an improvement in the concentrations of particulate matter, particularly for PM2.5, although PM10 exhibited a rebound in northern regions. The concentrations of SO2 and CO consistently declined across the country over the epidemic's course (p < 0.001 and p < 0.05, respectively), while O-3 concentrations in southern regions experienced a notable increase. Concentrations of air pollutants in the Beijing-Tianjin-Hebei region were effectively controlled and mitigated. The findings of this study provide critical insights into changing trends of air quality during public health emergencies, help guide the development of targeted interventions, and inform policy making aimed at reducing disease burdens associated with air pollution.
作者关键词: air pollutant; PM2.5; PM10; emerging hot spot analysis; multi-output LightGBM
地址: [Qin, Kun; Wang, Zhanpeng; Li, Manyao; Li, Chen; Qiu, Ge; Shi, Yuanyuan; Yin, Chun; Jia, Peng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.
[Qin, Kun; Wang, Zhanpeng; Dai, Shaoqing; Li, Yuchen; Li, Manyao; Li, Chen; Qiu, Ge; Shi, Yuanyuan; Yin, Chun; Yang, Shujuan; Jia, Peng] Wuhan Univ, Int Inst Spatial Lifecourse Hlth ISLE, Wuhan 430072, Peoples R China.
[Dai, Shaoqing] Univ Twente, Fac Geoinformat Sci & Earth Observat, NL-7500 AE Enschede, Netherlands.
[Li, Yuchen] Univ Cambridge, MRC Epidemiol Unit, Cambridge CB2 1TN, England.
[Li, Yuchen] Ohio State Univ, Dept Geog, Columbus, OH 43210 USA.
[Yang, Shujuan] Sichuan Univ, West China Sch Publ Hlth, Chengdu 610041, Peoples R China.
[Yang, Shujuan] Sichuan Univ, West China Hosp 4, Chengdu 610041, Peoples R China.
[Jia, Peng] Hubei Luojia Lab, Wuhan 430072, Peoples R China.
[Jia, Peng] Wuhan Univ, Sch Publ Hlth, Wuhan 430071, Peoples R China.
通讯作者地址: Jia, P (通讯作者),Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.
Jia, P (通讯作者),Wuhan Univ, Int Inst Spatial Lifecourse Hlth ISLE, Wuhan 430072, Peoples R China.
Jia, P (通讯作者),Hubei Luojia Lab, Wuhan 430072, Peoples R China.
Jia, P (通讯作者),Wuhan Univ, Sch Publ Hlth, Wuhan 430071, Peoples R China.
电子邮件地址: s.dai@utwente.nl; chunyin@whu.edu.cn; jiapengff@hotmail.com
影响因子:5
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