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

机译：是什么导致PM2.5污染？社会经济角度的跨经济实证分析

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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.
机译：是否如主流直觉所言，城市化和工业化是PM2.5的两个主要社会经济驱动力？这两种趋势如何影响PM2.5排放？本文通过评估79个发展中国家在2001-2010年间的面板数据，通过评估回归对人口，富裕和技术的随机影响（STRIPAT）定量分析了PM2.5的社会经济驱动因素。 PM2.5污染的平均水平是使用遥感数据计算的，克服了发展中国家缺乏PM2.5监测器且点数据无法反映大规模PM2.5污染总体水平的困难。收入和城市化的平方项及其交叉项分别包含在回归模型中，以分析不同发展阶段可能对PM2.5排放产生的不同影响。结果表明，收入，城市化和服务业对PM2.5污染有重大影响。收入一直对PM2.5产生积极影响，但随着城市化水平或收入水平的提高，影响逐渐减弱。城镇化与PM2.5之间存在倒U关系，其中PM2.5污染与低收入水平或城市化呈正相关，而与高水平呈负相关。从宏观社会和经济监管的角度提出了政策建议，为发展中经济体减少PM2.5污染。

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