...
首页> 外文期刊>Sustainability >Spatiotemporal Features and Socioeconomic Drivers of PM 2.5 Concentrations in China
【24h】

Spatiotemporal Features and Socioeconomic Drivers of PM 2.5 Concentrations in China

机译:中国PM 2.5浓度的时空特征和社会经济驱动力

获取原文

摘要

Fine particulate matter (PM 2.5 ) has been an important environmental issue because it can seriously harm human health and can adversely affect the economy. It poses a problem worldwide and especially in China. Based on data of PM 2.5 concentration and night light data, both collected from satellite remote sensing during 1998–2013 in China, we identify the socio-economic determinants of PM 2.5 pollution by taking into account the spatial flow and diffusion of regional pollutants. Our results show PM 2.5 pollution displays the remarkable feature of spatial agglomeration. High concentrations of PM 2.5 are mainly found in Eastern China (including Shandong, Jiangsu, and Anhui provinces) and the Jing-Jin-Ji Area region in the north of China (including Beijing, Tianjin, and Hebei provinces) as well as in the Henan provinces in central China. There is a significant positive spatial spillover effect of PM 2.5 pollution, so that an increase in PM 2.5 concentration in one region contributes to an increase in neighboring regions. Whether using per capita GDP or nighttime lighting indicators, there is a significant N-shaped curve that relates PM 2.5 concentration and economic growth. Population density, industrial structure, and energy consumption have distinct impacts on PM 2.5 pollution, while urbanization is negative correlated with PM 2.5 emissions. As a result, policies to strengthen regional joint prevention and control, implement cleaner manufacturing techniques, and reduce dependence on fossil fuels should be considered by policy makers for mitigating PM 2.5 pollution.
机译:细颗粒物(PM 2.5)已成为一个重要的环境问题,因为它会严重危害人类健康并会对经济产生不利影响。这在世界范围内,特别是在中国构成了问题。根据1998-2013年间从中国的卫星遥感收集到的PM 2.5浓度和夜光数据,我们通过考虑区域污染物的空间流动和扩散来确定PM 2.5污染的社会经济决定因素。我们的结果表明,PM 2.5污染表现出空间集聚的显着特征。高浓度的PM 2.5主要分布在中国东部地区(包括山东,江苏和安徽省)和中国北部的京津冀地区(包括北京,天津和河北省)以及中部地区。中国中部的河南省。 PM 2.5污染具有显着的积极的空间溢出效应,因此一个区域中PM 2.5浓度的增加会导致邻近区域中PM 2.5浓度的增加。无论是使用人均GDP还是夜间照明指标,都有一条显着的N形曲线将PM 2.5浓度与经济增长联系起来。人口密度,产业结构和能源消耗对PM 2.5污染有明显影响,而城市化与PM 2.5排放负相关。因此,决策者应考虑采取政策来加强区域联合预防和控制,实施更清洁的制造技术以及减少对化石燃料的依赖,以减轻PM 2.5污染。

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