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2000-2016 年中国城市群 PM 浓度的时空变化趋势及影响因素。

Spatio-temporal trends and influencing factors of PM concentrations in urban agglomerations in China between 2000 and 2016.

机构信息

College of Geography and Environment, Shandong Normal University, Jinan, 250358, China.

Collaborative Innovation Center of Human-Nature and Green Development in Universities of Shandong, Shandong Normal University, Jinan, 250358, China.

出版信息

Environ Sci Pollut Res Int. 2021 Mar;28(9):10988-11000. doi: 10.1007/s11356-020-11357-z. Epub 2020 Oct 27.

Abstract

An urban agglomeration (UA), similar to a megalopolis or a metropolitan area, is a region where cities and people are concentrated, and where air pollution has adversely impacted on sustainable and high quality development. Studies on the spatio-temporal trends and the factors which influence PM concentrations may be used as a reference to support air pollution control policy for major UAs throughout the world. Nineteen UAs in China covering the years 2000-2016 were chosen as the research object, the PM concentrations being used to reflect air pollution and being estimated from analysis of remote sensing images. The Exploratory Spatial Data Analysis method was used to study the spatio-temporal trends for PM concentrations, and the Geodetector method was used to examine the factors influencing the PM concentrations. The results revealed that (i) the temporal trend for the average values of the PM concentrations in the UAs followed an inverted U-shaped curve and the inflection points of the curve occurred in 2007. (ii) The PM concentrations in the UAs exhibited significant global spatial autocorrelation with the high-high type and the low-low type being the main categories. (iii) The rate of land urbanization and the structure of energy consumption were the main factors which influenced the PM concentrations in the UAs.

摘要

城市群(UA)类似于特大城市或大都市区,是城市和人口集中的地区,空气污染对可持续和高质量发展产生了不利影响。研究 PM 浓度的时空趋势和影响因素可以作为参考,为全球主要城市群的空气污染控制政策提供支持。选择了中国 19 个城市群,研究年限为 2000-2016 年,利用 PM 浓度来反映空气污染情况,并通过遥感图像分析进行估算。采用探索性空间数据分析方法研究 PM 浓度的时空趋势,利用地理探测器方法检验影响 PM 浓度的因素。结果表明:(i)城市群 PM 浓度平均值的时间趋势呈倒 U 型曲线,曲线的拐点出现在 2007 年。(ii)城市群 PM 浓度具有显著的全局空间自相关,主要类型为高高型和低低型。(iii)土地城镇化率和能源消费结构是影响城市群 PM 浓度的主要因素。

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