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基于空间网格尺度的中国PM_(2.5)污染健康效应空间分布
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  • 英文篇名:Health effects' spatial distribution analysis of PM_(2.5) pollution in China based on spatial grid scale
  • 作者:曾贤刚 ; 阮芳芳 ; 彭彦彦
  • 英文作者:ZENG Xian-gang;RUAN Fang-fang;PENG Yan-yan;School of Environment & Natural Resources, Renmin University of China;School of Public Administration and Policy, Renmin University of China;
  • 关键词:PM2.5 ; 健康效应 ; BenMap ; 空间自相关 ; 中国
  • 英文关键词:PM2.5;;health effect;;BenMap;;spatial autocorrelation;;China
  • 中文刊名:中国环境科学
  • 英文刊名:China Environmental Science
  • 机构:中国人民大学环境学院;中国人民大学公共管理学院;
  • 出版日期:2019-06-20
  • 出版单位:中国环境科学
  • 年:2019
  • 期:06
  • 基金:国家重点研发计划(2017YFC0702701)
  • 语种:中文;
  • 页:386-394
  • 页数:9
  • CN:11-2201/X
  • ISSN:1000-6923
  • 分类号:X513
摘要
以全国城市空气质量实时发布平台的监测数据为基础,运用空间插值法模拟中国PM_(2.5)在10km×10km空间网格尺度上的暴露水平,利用BenMap工具估计2017年中国PM_(2.5)污染的健康损失,在城市尺度上对PM_(2.5)污染的健康经济损失进行空间分析.结果表明,在统计意义层面上,2017年PM_(2.5)污染共计造成我国321435例早逝、746078例住院、14877551例患病,健康经济损失约为12625亿元,占当年全国GDP的1.53%.从城市尺度来看,健康效应呈现出一定的空间聚集效应,京津冀地区城市较为严重.在空间分布上,主要以"高-高"型和"低-低"型分布为主,即健康经济损失高值城市相互聚集、健康经济损失低值城市也相互聚集,并且存在高值城市之间相互影响并逐渐向四周扩散,进而影响周围低值城市的现象.
        Based on the monitoring data of the national urban air quality real-time release platform, this study used the spatial interpolation method to simulate the exposure level of China PM_(2.5) on the spatial grid scale of 10 km×10 km, and used the BenMap model to estimate the health loss of China's PM_(2.5) pollution in 2017. Then this study conducted a spatial analysis of the health economic losses of PM_(2.5) pollution on a city scale. In terms of statistical significance, the total PM_(2.5) pollution in 2017 caused 321435 premature deaths, 746078 hospital admissions, and 14877551 morbidity in China. The health economic loss was about 126.25 billion yuan, accounting for 1.53% of the national GDP. From the perspective of urban scale, the health effect showed a certain spatial agglomeration effect, and the cities in Beijing-Tianjin-Hebei region were more serious. In terms of spatial distribution, the main distributions were "high-high" and "low-low", that was, high-value cities of health economic loss gathered with each other, and low-value cities of health economic loss gathered with each other, too. And there existed a phenomenon that the high-value cities influenced each other and gradually spread around, and then affected the low-value cities around.
引文
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