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Effects of socioeconomic and natural factors on air pollution in China: A spatial panel data analysis

机译：社会经济与自然因素对我国空气污染的影响：空间面板数据分析

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China's energy use has increased significantly in recent years with the country's rapid economic growth and large-scale urbanization. Therefore, air pollution has become a major issue. In this study, we conducted spatial autocorrelation and spatial panel regression analyses of sulfur dioxide (SO_2) and nitrogen oxide (NO_x) emissions using the panel data of 31 provincial-level administrative units in China during the period 2011 -2017 to comprehensively understand the factors affecting air pollutant emissions. This study contributes to the literature by considering comprehensive factors and spatial effects in the panel-data econometric framework of the whole country of China. The analysis of spatial characteristics shows that during the study period, pollutant emissions in China declined, although emissions in northern regions were still relatively high. Furthermore, SO_2 and NO_x emissions showed significant positive spatial autocorrelations. The results of a fixed-effect spatial lag model showed that both socioeconomic and natural factors were statistically significant for air pollutant emissions, although the degree differed by the type of pollutant. The population, the urbanization rate, the share of added value of secondary industry, and heating and cooling degree days positively affected emissions, while population density, per-capita gross regional product, precipitation, and relative humidity negatively affected emissions. Based on these results, we have put forward suggestions to address the issue of air pollution and achieve environmental sustainability, such as the promotion of regional cooperation and a transition of the economic structure.
机译：近年来，中国的能源利用随着国家的快速经济增长和大规模城市化而增加。因此，空气污染已成为一个主要问题。在这项研究中，我们在2011年至2017年期间，我们在2011年至2017年期间使用了31个省级行政单位的面板数据进行了二氧化硫（SO_2）和氮氧化物（NO_X）排放的空间自相关和空间面板回归分析，以全面了解这些因素影响空气污染物排放。这项研究通过考虑全国各国的小组数据计量框架中的综合因素和空间效应，有助于文献。空间特征分析表明，在研究期间，中国的污染物排放均下降，尽管北部地区的排放仍然比较高。此外，SO_2和NO_X排放显示出显着的正空间自相关。固定效应空间滞后模型的结果表明，对于空气污染物排放，社会经济和自然因素均有统计学意义，尽管污染物类型不同。人口，城市化率，二级行业的附加值份额，以及加热和冷却度积极影响的排放，而人口密度，人均区域产物，降水和相对湿度的排放负面影响负面影响负面影响负面影响。基于这些结果，我们提出了解决空气污染问题并实现环境可持续性问题的建议，如促进区域合作和经济结构的转型。

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