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Identifying common drivers of PM2.5 on the supply and demand sides

Author

Listed:
  • Jiang, Yuqing
  • Tang, Xu
  • Ren, Kaipeng
  • Ding, Yu
  • Luo, Pengfei
  • Wang, Min

Abstract

The concentration threshold of 5 μg/m3 issued by the World Health Organization is another reminder of the severity of PM2.5 management in countries around the world. Identifying PM2.5 emission drivers on both the supply and demand sides is a key part of enhancing the effectiveness of governance. In this study, a multi-regional input-output model is combined with an econometric model to systematically account for the effects of PM2.5 emission drivers on both the supply and demand sides in global countries from 1995 to 2022. The major findings are as follows. First, global PM2.5 emissions increase from 11.79 million tons to 26.98 million tons between 1995 and 2022. Second, there is an inverted U-shaped relationship between GDP per capita and PM2.5 emissions from the production perspective, which is only reflected in developed countries. Third, Population factor has the greatest positive impact on PM2.5 emissions on the two sides, followed by energy mix. The negative effect of energy efficiency improvement on PM2.5 emissions is evident in developing countries, whereas the opposite is true in developed countries. The impact of urbanization rate on PM2.5 emissions is relatively complex. Finally, the PM2.5 emission pattern is closely related to the stage of economic development. Per capita GDP shows a negative correlation with export embodied PM2.5 emissions and a positive correlation with import embodied PM2.5 emissions. These findings reveal how socio-economic factors influence PM2.5 emission reductions differently on both the supply and demand sides, providing novel insights into targeted zoning regulations at the global and national levels.

Suggested Citation

  • Jiang, Yuqing & Tang, Xu & Ren, Kaipeng & Ding, Yu & Luo, Pengfei & Wang, Min, 2026. "Identifying common drivers of PM2.5 on the supply and demand sides," Energy Economics, Elsevier, vol. 157(C).
  • Handle: RePEc:eee:eneeco:v:157:y:2026:i:c:s0140988326001507
    DOI: 10.1016/j.eneco.2026.109271
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