Spatiotemporal dynamics and impacts of socioeconomic and natural conditions on PM2.5 in the Yangtze River Economic Belt
2020
Liu, Xiao-Jie | Xia, Si-You | Yang, Yu | Wu, Jing-fen | Zhou, Yan-Nan | Ren, Ya-Wen
The determination of the spatiotemporal patterns and driving factors of PM₂.₅ 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 PM₂.₅ 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 PM₂.₅ was in the range of 23.49–37.67 μg/m³ with an inverted U-shaped change trend, and the PM₂.₅ distribution presented distinct spatial heterogeneity; 2) there was a strong local spatial dependence and dynamic PM₂.₅ growth process, and the spatial agglomeration of PM₂.₅ exhibited higher path-dependence and spatial locking characteristics; and 3) the endogenous interaction effect of PM₂.₅ was significant, where each 1% increase in the neighbouring PM₂.₅ levels caused the local PM₂.₅ to increase by at least 0.4%. Natural and anthropogenic factors directly and indirectly influenced the PM₂.₅ 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.
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