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Analysis of Air Pollution Impact Factors in China: A MIMIC Modeling Approach

机译:中国空气污染影响因素分析:一种MIMIC建模方法

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摘要

In this study, we investigate the impact factors on air pollution in terms of CO_2, SO_2 and NO_x emissions simultaneously in China and compare changes in air pollution across provinces from 1998 to 2011 using a Multiple Indicators and Multiple Causes Model (MIMIC) within a Structural Equation Model (SEM) framework. Our findings reveal that GDP per capita and total population have the largest impacts on air pollution, followed by energy intensity, foreign direct investment, population density, and industrialization. The results also reveal that the inverted U-shaped Environmental Kuznets Curve (EKC) hypothesis exists in China. Our findings also demonstrate that Shandong, Jiangxi and Liaoning are the top three provinces with the most deteriorated air quality while Xinjiang, Fujian and Ningxia are with the best. These results not only contribute to advancing the existing literature, but also merit particular attention from policy-makers in China.
机译:在这项研究中,我们同时调查了中国在CO_2,SO_2和NO_x排放方面对空气污染的影响因素,并使用结构内的多指标和多原因模型(MIMIC)比较了1998年至2011年各省空气污染的变化。方程模型(SEM)框架。我们的发现表明,人均GDP和总人口对空气污染的影响最大,其次是能源强度,外国直接投资,人口密度和工业化。结果还表明,中国存在倒U型环境库兹涅茨曲线(EKC)假设。我们的发现还表明,山东,江西和辽宁是空气质量恶化最严重的三个省份,而新疆,福建和宁夏则是最好的。这些结果不仅有助于推动现有文献的发展,而且还应引起中国决策者的特别关注。

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