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What Factors Dominate the Change of PM 2.5 in the World from 2000 to 2019? A Study from Multi-Source Data

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  • Xiankang Xu

    (Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China)

  • Kaifang Shi

    (Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China)

  • Zhongyu Huang

    (Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China)

  • Jingwei Shen

    (Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
    Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China)

Abstract

As the threat to human life and health from fine particulate matter (PM 2.5 ) increases globally, the life and health problems caused by environmental pollution are also of increasing concern. Understanding past trends in PM 2.5 and exploring the drivers of PM 2.5 are important tools for addressing the life-threatening health problems caused by PM 2.5 . In this study, we calculated the change in annual average global PM 2.5 concentrations from 2000 to 2020 using the Theil–Sen median trend analysis method and reveal spatial and temporal trends in PM 2.5 concentrations over twenty-one years. The qualitative and quantitative effects of different drivers on PM 2.5 concentrations in 2020 were explored from natural and socioeconomic perspectives using a multi-scale geographically weighted regression model. The results show that there is significant spatial heterogeneity in trends in PM 2.5 concentration, with significant decreases in PM 2.5 concentrations mainly in developed regions, such as the United States, Canada, Japan and the European Union countries, and conversely, significant increases in PM 2.5 in developing regions, such as Africa, the Middle East and India. In addition, in regions with more advanced science and technology and urban management, PM 2.5 concentrations are more evenly influenced by various factors, with a more negative influence. In contrast, regions at the rapid development stage usually continue their economic development at the cost of the environment, and under a high intensity of human activity. Increased temperature is known as the most important factor for the increase in PM 2.5 concentration, while an increase in NDVI can play an important role in the reduction in PM 2.5 concentration. This suggests that countries can achieve good air quality goals by setting a reasonable development path.

Suggested Citation

  • Xiankang Xu & Kaifang Shi & Zhongyu Huang & Jingwei Shen, 2023. "What Factors Dominate the Change of PM 2.5 in the World from 2000 to 2019? A Study from Multi-Source Data," IJERPH, MDPI, vol. 20(3), pages 1-28, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:3:p:2282-:d:1048351
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