What causes PM2.5 pollution? Cross-economy empirical analysis from socioeconomic perspective

• Published in: Energy policy 2018-08, Vol.119, p.458-472
• Main Authors: Ji, Xi, Yao, Yixin, Long, Xianling
• Format: Article
• Language: English
• Subjects: Affluence; Air pollution; Developing countries; Economics; Emission analysis; Emissions; Empirical analysis; Energy intensity; Energy policy; Income; Industrialization; Intuition; LDCs; Low level; Nonlinear effect; Panel data; Particulate matter; PM2.5; Pollution; Regression analysis; Regression models; Regulation; Remote sensing; Service industries; Socioeconomic drivers; Socioeconomic factors; Socioeconomics; Stochastic models; Stochasticity; Technology; Urbanization
• ISSN: 0301-4215; 1873-6777
• DOI: 10.1016/j.enpol.2018.04.040

Is it true that, as the mainstream intuition asserts, urbanization and industrialization are the two main socioeconomic drivers of PM2.5? How do the two trends affect PM2.5 emission? This paper quantitatively analyzes the socioeconomic drivers of PM2.5 through assessment on Stochastic Impacts by Regression on Population, Affluence and Technology (STRIPAT), based on the panel data of 79 developing countries over 2001–2010. The average levels of PM2.5 pollution are calculated using remote sensing data, overcoming the difficulties that developing countries are in lack of PM2.5 monitors and that point data cannot reflect the overall level of PM2.5 pollution on a large scale. Squared terms of income and urbanization and their cross term are included in the regression models respectively to analyze the possible heterogeneous impacts on PM2.5 emissions in different development stages. The results show that income, urbanization and service sector have significant impact on PM2.5 pollution. Income has a positive effect on PM2.5 all the time but the effect decreases as the level of urbanization or income goes up. An inverted U relationship exists between urbanization and PM2.5, in which PM2.5 pollution positively correlates with a low level of income or urbanization but negatively at a high level. Policy recommendations from the perspective of macro-level social and economic regulation are provided for developing economies to reduce PM2.5 pollution. •Socioeconomic drivers of PM2.5 are identified for developing countries.•Nonlinear effects of urbanization and income are considered and found.•Income has positive but decreasing effect as urbanization and income level go up.•Urbanization has inverted U-shaped effect across urbanization and income level.