长江流域资源与环境 >> 2022, Vol. 31 >> Issue (3): 647-658.doi: 10.11870/cjlyzyyhj202203014

• 生态环境 • 上一篇    下一篇

长江经济带PM2.5时空演变及影响因素分析

刘笑杰,王丽丽,何博汶,李丁*   

  1. (兰州大学资源环境学院,甘肃 兰州 730000)
  • 出版日期:2022-03-20 发布日期:2022-04-07

Spatiotemporal Evolution and Drivers of PM2.5 in the Yangtze River Economic Belt

LIU Xiao-jie, WANG Li-li, HE Bo-wen, LI Ding   

  1. (College of Earth and Environmental Science, Lanzhou University, Lanzhou 730000, China)

  • Online:2022-03-20 Published:2022-04-07

摘要: 大气雾霾防治不仅是打赢蓝天保卫战的有力支撑,也是经济新常态下实现高质量发展的必然要求。基于遥感反演数据,运用重力模型与空间自相关分析探究了2000~2018年长江经济带PM2.5时空演变特征,并采用空间计量模型甄别和量化自然与人文影响因子贡献及空间溢出效应。结果表明:(1)长江经济带PM2.5浓度整体呈先升后降的倒U形趋势,区域间保持“上游<中游<下游”的阶梯式格局。PM2.5浓度重心位于湖北省内的潜江、荆州与仙桃三市交界处,重心格局变动明显;(2)长江流域PM2.5浓度水平总体呈现中下游高于上游,北岸大于南岸的对角分布格局,空间异质性明显;(3)PM2.5污染存在显著的空间正相关,高-高型集聚主要分布在上游的成渝地区和中下游的鄂苏皖地区,低-低型集聚基本稳定在上游的川西、云贵等地区,呈现差异显著的两大组团空间俱乐部;(4)PM2.5污染的内源性相互作用显著,邻域PM2.5浓度每增加1%,将导致本地PM2.5浓度至少增加0.4%。自然要素和人为因素直接或间接地影响着PM2.5水平,其中,气象环境因子主要是负向效应,社会经济因子主要起正向效应。

Abstract: The prevention and control of haze pollution is not only a strong support for the battle against blue skies, but a necessary requirement for high-quality economic development under the new normal.This paper investigated thespatiotemporal evolution of PM2.5 and its drivers by using gravity model, spatial autocorrelation analysis and spatial econometric model based on remote sensing imagery inversiondata of the Yangtze River Economic Belt(YREB), China, between 2000 and 2018. The results showed that: (1) The PM2.5 concentration in the YREB posed an inverted U-shaped trend, which first increased and then decreased, and maintained an interregional pattern of "upper reaches < middle reaches < lower reaches". The gravity of PM2.5 concentration was located in the junction of Qianjiang, Jingzhou and Xiantao cities in Hubei province, and the gravity changed significantly. (2) The PM2.5 concentration in the middle and lower reaches of the YREB was higher than that in the upper reaches, and the north bank of the Yangtze was higher than that in the south bank. (3) PM2.5 pollution in the YREB had a significant positive spatial correlation. High-Highclustering was mainly distributed in the Chengdu-Chongqing region and Hubei, Jiangsu and Anhui provinces, while Low-Low clustering was stable in the upstream of western Sichuan and Yunnan-Guizhou regions, presenting a conspicuous spatial convergence feature. (4) The endogenous interaction of PM2.5 was significant, where each 1% increased in the neighbouring PM2.5 levels would cause that local to increase by at least 0.4%.Natural and anthropogenic factors directly and indirectly affected PM2.5, among which meteorological factors mainly had a negative effect, while socio-economic factors chiefly had a positive effect.

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