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Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017

机译:2014-2017年中国城市PM2.5浓度的时空变化及其社会经济影响因素

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摘要

PM2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM2.5 concentration changes. The results are as follows: (1) The annual average value of PM2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014–2017, the overall PM2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m3) regulated by Chinese government. PM2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China’s uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM2.5 concentration. The results also suggest that China in general remains a “pollution shelter” for foreign-funded enterprises.
机译:PM2.5是中国频繁发生空气污染的主要来源。利用2014-2017年间中国338个城市的PM2.5数据的实时监测,本研究采用多时间和多空间尺度的统计分析,揭示了PM2.5模式的时空特征和空间计量经济学模型,量化PM2.5浓度变化的社会经济驱动因素。结果如下:(1)PM2.5浓度的年平均值逐年下降,1月至12月的月平均值呈U形曲线。 PM2.5浓度的日平均值具有脉冲型波动的特征,小时变化呈双峰曲线。 (2)在2014-2017年期间,PM2.5的总体污染水平显着降低,但仍有三分之二以上的城市仍超过中国政府规定的标准值(35μg/ m 3 ) 。 PM2.5污染模式在中国中部和东部城市显示出较高的价值,而在周边地区则显示出较低的价值,这一明显的区别体现了中国人口分布不均的现象。 (3)人口聚集,工业发展,外国投资,运输和污染排放导致PM2.5浓度增加。城市人口密度的贡献最大,而经济发展和技术进步降低了PM2.5浓度。结果还表明,中国总体上仍然是外资企业的“污染庇护所”。

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