Spatiotemporal dynamics and impacts of socioeconomic and natural conditions on PM 2.5 in the Yangtze River Economic Belt.

Autor: Liu XJ; College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China., Xia SY; School of Geographical Science, Nanjing Normal University, Nanjing, 210023, China., Yang Y; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address: yangyu@igsnrr.ac.cn., Wu JF; College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China., Zhou YN; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China., Ren YW; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China.
Jazyk: angličtina
Zdroj: Environmental pollution (Barking, Essex : 1987) [Environ Pollut] 2020 Aug; Vol. 263 (Pt A), pp. 114569. Date of Electronic Publication: 2020 Apr 11.
DOI: 10.1016/j.envpol.2020.114569
Abstrakt: The determination of the spatiotemporal patterns and driving factors of PM 2.5 is of great interest to the atmospheric and climate science community, who aim to understand and better control the atmospheric linkage indicators. However, most previous studies have been conducted on pollution-sensitive cities, and there is a lack of large-scale and long-term systematic analyses. In this study, we investigated the spatiotemporal evolution of PM 2.5 and its influencing factors by using an exploratory spatiotemporal data analysis (ESTDA) technique and spatial econometric model based on remote sensing imagery inversion data of the Yangtze River Economic Belt (YREB), China, between 2000 and 2016. The results showed that 1) the annual value of PM 2.5 was in the range of 23.49-37.67 μg/m 3 with an inverted U-shaped change trend, and the PM 2.5 distribution presented distinct spatial heterogeneity; 2) there was a strong local spatial dependence and dynamic PM 2.5 growth process, and the spatial agglomeration of PM 2.5 exhibited higher path-dependence and spatial locking characteristics; and 3) the endogenous interaction effect of PM 2.5 was significant, where each 1% increase in the neighbouring PM 2.5 levels caused the local PM 2.5 to increase by at least 0.4%. Natural and anthropogenic factors directly and indirectly influenced the PM 2.5 levels. Our results provide spatial decision references for coordinated trans-regional air pollution governance as well as support for further studies which can inform sustainable development strategies in the YREB.
Competing Interests: Declaration of competing interest The authors declare that there is no conflict of interest.
(Copyright © 2020 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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