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Analysis of Spatio-temporal Characteristics and Driving Forces of Air Quality in the Northern Coastal Comprehensive Economic Zone, China

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  • Ying Su

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    Key Laboratory of Ecology and Resources Statistics of Fujian Province Universities, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    Research Centre of Resource and Environment Spatial Information Statistics of Fujian Province, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    These authors contributed equally to this work.)

  • Chunyan Lu

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    Key Laboratory of Ecology and Resources Statistics of Fujian Province Universities, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    Research Centre of Resource and Environment Spatial Information Statistics of Fujian Province, Fujian Agriculture and Forestry University, Fuzhou 350002, China
    These authors contributed equally to this work.)

  • Xiaoqing Lin

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Lianxiu Zhong

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Yibin Gao

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

  • Yifan Lei

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

Abstract

Comprehensive analysis of air quality is essential to underpin knowledge-based air quality conservation policies and funding decisions by governments and managers. In this paper, air quality change characteristics for the Northern Coastal Comprehensive Economic Zone from 2008 to 2018 were analyzed using air quality indices. The spatio-temporal pattern of air quality was identified using centroid migration, spatial autocorrelation analysis and spatial analysis in a geographic information system (GIS). A spatial econometric model was established to confirm the natural and anthropogenic factors affecting air quality. Results showed that air pollution decreased significantly. PM 2.5 , PM 10 , and O 3 were the primary pollutants. The air quality exhibited an inverted U-shaped trend from January to December, with the highest quality being observed in summer and the lowest during winter. Spatially, the air quality showed an increasing trend from inland to the coast and from north to south, with significant spatial autocorrelation and clustering. Population, energy consumption, temperature, and atmospheric pressure had significant negative impacts on air quality, while wind speed had a positive impact. This study offers an efficient and effective method to evaluate air quality change. The research provides important scientific information necessary for developing future air pollution prevention and control.

Suggested Citation

  • Ying Su & Chunyan Lu & Xiaoqing Lin & Lianxiu Zhong & Yibin Gao & Yifan Lei, 2020. "Analysis of Spatio-temporal Characteristics and Driving Forces of Air Quality in the Northern Coastal Comprehensive Economic Zone, China," Sustainability, MDPI, vol. 12(2), pages 1-23, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:536-:d:307487
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    References listed on IDEAS

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    Cited by:

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    2. Qing Zhao & Chih-Hung Yuan, 2020. "Did Haze Pollution Harm the Quality of Economic Development?—An Empirical Study Based on China’s PM2.5 Concentrations," Sustainability, MDPI, vol. 12(4), pages 1-16, February.
    3. Xueming Li & Songbo Li & Shenzhen Tian & Yingying Guan & He Liu, 2021. "Air Quality and the Spatial-Temporal Differentiation of Mechanisms Underlying Chinese Urban Human Settlements," Land, MDPI, vol. 10(11), pages 1-22, November.

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