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基于卫星的 PM 浓度的时空变化及其在中国西北地区新疆的决定因素。

Spatio-Temporal Variations of Satellite-Based PM Concentrations and Its Determinants in Xinjiang, Northwest of China.

机构信息

State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China.

Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China.

出版信息

Int J Environ Res Public Health. 2020 Mar 24;17(6):2157. doi: 10.3390/ijerph17062157.

Abstract

With the aggravation of air pollution in recent years, a great deal of research on haze episodes is mainly concentrated on the east-central China. However, fine particulate matter (PM) pollution in northwest China has rarely been discussed. To fill this gap, based on the standard deviational ellipse analysis and spatial autocorrelation statistics method, we explored the spatio-temporal variation and aggregation characteristics of PM concentrations in Xinjiang from 2001 to 2016. The result showed that annual average PM concentration was high both in the north slope of Tianshan Mountain and the western Tarim Basin. Furthermore, PM concentrations on the northern slope of the Tianshan Mountain increased significantly, while showing an obviously decrease in the western Tarim Basin during the period of 2001-2016. Based on the result of the geographical detector method (GDM), population density was the most dominant factor of the spatial distribution of PM concentrations ( = 0.550), followed by road network density ( = 0.423) and GDP density ( = 0.413). During the study period (2001-2016), the driving force of population density on the distribution of PM concentrations showed a gradual downward trend. However, other determinants, like DEM (Digital elevation model), NSL (Nighttime stable light), LCT (Land cover type), and NDVI (Normalized Difference Vegetation Index), show significant increased trends. Therefore, further effort is required to reveal the role of landform and vegetation in the spatio-temporal variations of PM concentrations. Moreover, the local government should take effective measures to control urban sprawl while accelerating economic development.

摘要

近年来,随着空气污染的加剧,大量关于雾霾的研究主要集中在中国中东部地区。然而,中国西北地区的细颗粒物(PM)污染却很少被讨论。为了填补这一空白,我们基于标准差椭圆分析和空间自相关统计方法,探讨了 2001 年至 2016 年新疆 PM 浓度的时空变化和聚集特征。结果表明,天山北坡和塔里木盆地西部的年平均 PM 浓度都很高。此外,2001-2016 年期间,天山北坡的 PM 浓度显著增加,而塔里木盆地西部则明显下降。基于地理探测器方法(GDM)的结果,人口密度是 PM 浓度空间分布的最主要因素(=0.550),其次是路网密度(=0.423)和 GDP 密度(=0.413)。在研究期间(2001-2016 年),人口密度对 PM 浓度分布的驱动力呈逐渐下降趋势。然而,其他决定因素,如数字高程模型(DEM)、夜间稳定灯光(NSL)、土地覆盖类型(LCT)和归一化植被指数(NDVI),则呈现出显著的上升趋势。因此,需要进一步努力揭示地形和植被在 PM 浓度时空变化中的作用。此外,地方政府应采取有效措施控制城市扩张,同时加快经济发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6694/7143496/038ece68717c/ijerph-17-02157-g001.jpg

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