...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Cleaner Production >Quantifying the spatial heterogeneity influences of natural and socioeconomic factors and their interactions on air pollution using the geographical detector method: A case study of the Yangtze River Economic Belt, China
【24h】

Quantifying the spatial heterogeneity influences of natural and socioeconomic factors and their interactions on air pollution using the geographical detector method: A case study of the Yangtze River Economic Belt, China

机译：使用地理探测器方法量化自然和社会经济因素的空间异质性及其对空气污染的相互作用 - 以中国长江经济带的案例研究

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This study takes the Yangtze River Economic Belt as a study area and analyzes the impacts of natural and socioeconomic factors on air pollution based on a dataset of urban air quality monitoring data in 2015 and meteorological and economic statistical data. We first apply the grey relational degree to test for the quantitative relationships between the natural and socioeconomic factors and air pollution. We then employ a novel method, specifically, the geographical detector, from the perspective of spatial stratified heterogeneity to reveal the potential impacts and interaction impacts of the natural and socioeconomic factors on air pollution. The results are as follows. (1) The grey relational degree results reveal that all factors in the topographical and meteorological layer, pollution sources layer, economic development layer, and urbanization layer have high relational degrees, indicating that these factors are closely correlated with air pollution. (2) The factor detector analysis reveals that the PM2.5 factor has the biggest q value, indicating that it is the primary contributor to air pollution, followed by PM10 and elevation. (3) The interaction detector analysis reveals that the interaction of two factors plays a more important role in influencing air pollution than does each factor individually. Moreover, the interactions between pair factors of pollution sources are the strongest. (4) The risk detector analysis reveals that elevation and precipitation are negatively correlated with air pollution, whereas pollution and urbanization factors are positively correlated with air pollution. (5) Finally, two leading impact areas for atmospheric pollution, namely, the Yangtze River Delta urban agglomeration and the Wuhan metropolitan area are predominantly attributed to the combination of natural and urbanization factors, whereas Yunnan and Guizhou are the least impact areas for atmospheric pollution because of their topographical and meteorological factors. (C) 2019 Elsevier Ltd. All rights reserved.
机译：本研究采用长江经济带作为研究区，并在2015年基于城市空气质量监测数据数据集及气象和经济统计数据的基础上自然和社会经济因素对空气污染的影响。我们首先应用灰色关系程度来测试自然和社会经济因素与空气污染之间的定量关系。然后，我们采用一种新颖的方法，具体地，地理探测器，从空间分层异质性的角度来揭示自然和社会经济因素对空气污染的潜在影响和互动影响。结果如下。 （1）灰色关系度结果表明，地形和气象层，污染源层，经济开发层和城市化层中的所有因素都具有高关系度，表明这些因素与空气污染密切相关。 （2）因子检测器分析显示PM2.5因素具有最大的Q值，表明它是空气污染的主要贡献者，其次是PM10和高度。 （3）相互作用探测器分析表明，两个因素的相互作用在影响空气污染方面发挥了更重要的作用，而不是单独的每种因素。此外，污染源对因子之间的相互作用是最强的。 （4）风险探测器分析显示，升高和降水与空气污染呈负相关，而污染和城市化因素与空气污染正相关。 （5）最后，两个主要的污染影响领域，即长江三角洲城市集聚和武汉大都市区主要归因于自然和城市化因素的结合，而云南和贵州是大气污染的最小影响领域因为他们的地形和气象因素。 （c）2019 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号