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Spatio-Temporal Variations of Satellite-Based PM 2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China

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  • Wei Wang

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Alim Samat

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jilili Abuduwaili

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yongxiao Ge

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

With the aggravation of air pollution in recent years, a great deal of research on haze episodes is mainly concentrated on the east-central China. However, fine particulate matter (PM 2.5 ) pollution in northwest China has rarely been discussed. To fill this gap, based on the standard deviational ellipse analysis and spatial autocorrelation statistics method, we explored the spatio-temporal variation and aggregation characteristics of PM 2.5 concentrations in Xinjiang from 2001 to 2016. The result showed that annual average PM 2.5 concentration was high both in the north slope of Tianshan Mountain and the western Tarim Basin. Furthermore, PM 2.5 concentrations on the northern slope of the Tianshan Mountain increased significantly, while showing an obviously decrease in the western Tarim Basin during the period of 2001–2016. Based on the result of the geographical detector method (GDM), population density was the most dominant factor of the spatial distribution of PM 2.5 concentrations ( q = 0.550), followed by road network density ( q = 0.423) and GDP density ( q = 0.413). During the study period (2001–2016), the driving force of population density on the distribution of PM 2.5 concentrations showed a gradual downward trend. However, other determinants, like DEM (Digital elevation model), NSL (Nighttime stable light), LCT (Land cover type), and NDVI (Normalized Difference Vegetation Index), show significant increased trends. Therefore, further effort is required to reveal the role of landform and vegetation in the spatio-temporal variations of PM 2.5 concentrations. Moreover, the local government should take effective measures to control urban sprawl while accelerating economic development.

Suggested Citation

  • Wei Wang & Alim Samat & Jilili Abuduwaili & Yongxiao Ge, 2020. "Spatio-Temporal Variations of Satellite-Based PM 2.5 Concentrations and Its Determinants in Xinjiang, Northwest of China," IJERPH, MDPI, vol. 17(6), pages 1-24, March.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:6:p:2157-:d:336293
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    References listed on IDEAS

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    1. Chengdong Xu, 2017. "Spatio-Temporal Pattern and Risk Factor Analysis of Hand, Foot and Mouth Disease Associated with Under-Five Morbidity in the Beijing–Tianjin–Hebei Region of China," IJERPH, MDPI, vol. 14(4), pages 1-13, April.
    2. Yusuf A. Aina & Johannes H. Van der Merwe & Habib M. Alshuwaikhat, 2014. "Spatial and Temporal Variations of Satellite-Derived Multi-Year Particulate Data of Saudi Arabia: An Exploratory Analysis," IJERPH, MDPI, vol. 11(11), pages 1-15, October.
    3. Qun Liu & Zhaoping Yang & Cuirong Wang & Fang Han, 2019. "Temporal-Spatial Variations and Influencing Factor of Land Use Change in Xinjiang, Central Asia, from 1995 to 2015," Sustainability, MDPI, vol. 11(3), pages 1-14, January.
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