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[1]BAI Ling,JIANG lei,ZHOU Haifeng,et al.Spatiotemporal Heterogeneity of Air Quality Index and Its Socio-economic Factors in the Yangtze River Economic Belt[J].Research of Soil and Water Conservation,2019,26(02):312-319.

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Spatiotemporal Heterogeneity of Air Quality Index and Its Socio-economic Factors in the Yangtze River Economic Belt

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 26 Number of periods: 2019 02 Page number: 312-319 Column: Public date: 2019-04-28

Title:: Spatiotemporal Heterogeneity of Air Quality Index and Its Socio-economic Factors in the Yangtze River Economic Belt

Author(s):: BAI Ling^1,2, JIANG lei³, ZHOU Haifeng³, CHEN Zhongsheng⁴; 1. Research Center of the Central China Economic Development, Nanchang University, Nanchang 330031, China;
2. School of Economics & Management, Nanchang University, Nanchang 330031, China;
3. School of Economics, Zhejiang University of Finance & Economics, Hangzhou 310018, China;
4. College of Land and Resources, China West Normal University, Nanchong, Sichuan 637002, China

Keywords:: Yangtze River Economic Belt; air quality index; spatiotemporal heterogeneity; empirical orthogonal function; geographically weighted regression

CLC:: F205;X823

DOI:: -

Abstract:: We employed a cross-sectional data of the Yangtze River Economic Belt at the city level to investigate spatiotemporal variation characteristics of air quality index (AQI) of 126 cities by means of the empirical orthogonal function (EOF) method, and then applied the geographically weighted regression method to analyze socio-economic factors of AQI from a perspective of spatial heterogeneity. The findings are the followings. (1) The first mode of EOF has high eigenvector values in Jiangsu Province, Wuhan metropolitan region, Chang-Zhu-Tan region and Chengdu-Chongqing urban cluster while low high eigenvector values are shown in most cities of Yunnan Province, Qiannan of Guizhou Province, Aba of Sichuan Province and Zhoushan, Taizhou and Lishui of Zhejiang Province. (2) On the monthly time scale, the time coefficient of AQI displays a U-shaped curve. Specifically, it first declines with fluctuations from January to May, and then keeps the lowest values from June to August, and finally increases from September to December. In other words, air quality is the worst in winter and the best in summer within the year of 2015. (3) The increase in per capita GDP, population density, PM_2.5 concentration and SO₂concentration are the important factors worsening air quality while FDI and green coverage ratio contribute to improving air quality. Finally, socio-economics factors may have impacts on air quality from city to city, presenting significant spatial heterogeneity.

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