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2014-2017 年中国城市 PM 浓度的时空演变及其社会经济影响因素。

Spatial-Temporal Evolution of PM Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014⁻2017.

机构信息

Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China.

College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.

出版信息

Int J Environ Res Public Health. 2019 Mar 19;16(6):985. doi: 10.3390/ijerph16060985.

Abstract

PM is a main source of China's frequent air pollution. Using real-time monitoring of PM 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 PM patterns and a spatial econometric model to quantify the socio-economic driving factors of PM concentration changes. The results are as follows: (1) The annual average value of PM concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014⁻2017, the overall PM pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m³) regulated by Chinese government. PM 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 PM concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM concentration. The results also suggest that China in general remains a "pollution shelter" for foreign-funded enterprises.

摘要

PM 是中国频繁发生空气污染的主要来源。本研究利用 2014-2017 年期间中国 338 个城市的 PM 数据实时监测,采用多时相和多空间尺度的统计分析方法,揭示了 PM 模式的时空特征,并采用空间计量经济学模型量化了 PM 浓度变化的社会经济驱动因素。结果如下:(1)PM 浓度的年平均值逐年下降,月平均值呈 1 月至 12 月的 U 型曲线。PM 浓度的日平均值具有脉冲式波动的特征,小时变化呈现双峰曲线。(2)2014-2017 年期间,整体 PM 污染显著减少,但超过三分之二的城市仍超过中国政府规定的(35μg/m³)标准值。PM 污染模式在中东部城市呈高值,在周边地区呈低值,与中国人口分布不均的分界线明显一致。(3)人口聚集、工业发展、外国投资、交通和污染排放导致了 PM 浓度的增加。城市人口密度的贡献最大,而经济发展和技术进步则降低了 PM 浓度。结果还表明,中国总体上仍然是外资企业的“污染避难所”。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/67c6/6466118/df7eb297aae4/ijerph-16-00985-g001.jpg

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