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1998~2016年中国地级以上城市PM2.5污染时空格局

Analysis of temporal and spatial patterns of PM2.5 in Prefecture-Level Cities of China from 1998 to 2016

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【作者】 郑保利梁流涛李明明

【Author】 ZHENG Bao-li;LIANG Liu-tao;LI Ming-ming;Key Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education;School of Geographic Sciences, East China Normal University;College of Environment and Planning, Henan University;

【通讯作者】 梁流涛;

【机构】 河南大学黄河中下游数字地理技术教育部重点实验室华东师范大学地理科学学院河南大学环境与规划学院

【摘要】 利用1998~2016年全球PM2.5浓度栅格数据集,以地级以上城市为基本单元提取出PM2.5浓度数据,采用核密度估计法、全局空间自相关、局部空间自相关、热点分析等方法探讨我国地级以上城市PM2.5污染的时空格局演化规律.结果显示:(1)研究期内我国PM2.5浓度总体呈现上升趋势,年均增长0.55μg/m3.变化趋势可以分为2个阶段:1998~2007年呈快速增长态势;2008~2016年呈现"下降~增长~下降"的变化趋势.按地区分析,东部和中部地区呈现相似的变化趋势.西部地区和东北地区均整体呈现增长的态势,但西部地区变化较为平缓,东北地区波动较为剧烈.(2)研究期内核密度曲线峰值逐步右移,这表明中国地级以上城市PM2.5污染程度总体上在加剧,且东部和中部城市加剧程度远大于西部.(3)PM2.5污染在空间分布上具有显著的空间正相关特征.高值聚集区集中分布在山东、河南、河北、江苏、安徽、湖南、湖北的大部分地区以及四川东部地区,1998~2007年间高值聚集城市数量呈现增加的态势,2007年达到峰值,空间上表现为向西部和南部扩张;此后高值集聚城市数量逐渐减少,聚集区南界逐渐北移.低值聚集区集中分布在内蒙古、黑龙江西北部、新疆、西藏、台湾、海南、福建等地区.研究期内低值聚集区城市数量整体呈现先增加后减少的波动状态.

【Abstract】 The spatial-temporal pattern of PM2.5 in Chinese prefecture-level cities over 1998~2016 has been explored in this study based on Kernel Density Estimation(KDE), Global Spatial Autocorrelation, Local Spatial Autocorrelation, Hotspot Analysis and other methods with the data of PM2.5 concentration extracted from the 1998 to 2016 global PM2.5 concentration raster dataset at prefecture-level city. The results showed that first the concentration of PM2.5 in China has been rising with an average annual increase of 0.55μg/m3 as a whole from 1998 to 2016. Its changing trend could be divided into two stages: rapid growth from 1998 to 2007 and decline-growth-decline fluctuations from 2008 to 2016. Geographically, eastern China and central China experienced similar changing trends, while western China experienced a moderate changing trend, and the changing trend of northeastern China was more dramatic. Second, from 1998 to 2016, the peak of the core density curve gradually shifted to the right, indicating that PM2.5 pollution in Chinese prefecture-level cities was generally increasing. The shifting was far more substantial in eastern and central China than in western China. Third, PM2.5 pollution presented a significant positive spatial correlation. The high-value clusters were concentrated in most parts of Shandong, Henan, Hebei, Jiangsu, Anhui, Hunan, Hubei, and eastern Sichuan. The number of high-value cluster cities had increased from 1998 to 2007 with the peak achieved in 2007. The high-value areas westward and southward during this period. After 2007, the number of high-value agglomerated cities had gradually decreased, and its southern boundary gradually moved northward. Low-value city clusters were concentrated in Inner Mongolia, northwestern Heilongjiang, Xinjiang, Tibet, Taiwan, Hainan, Fujian and other regions, and the number of low-value cluster cities showed an increase first and then decreased trend with annual variations.

【基金】 国家自然科学基金资助项目(41771565);河南省高校科技创新人才(人文社科类)支持计划(2019-cx-014)
  • 【文献出处】 中国环境科学 ,China Environmental Science , 编辑部邮箱 ,2019年05期
  • 【分类号】X513
  • 【被引频次】16
  • 【下载频次】635
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