| 基于GIS的中国PM2.5浓度的空间分布及影响因素分析 |
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| 引用本文： | 李松,罗绪强,李恋,万红燕.基于GIS的中国PM2.5浓度的空间分布及影响因素分析[J].水土保持通报,2015,35(4):202-205,212. |
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| 作者姓名： | 李松 罗绪强 李恋 万红燕 |
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| 作者单位： | 贵州师范学院资源环境与灾害研究所, 贵州贵阳 550018;中国科学院遥感与数字地球研究所, 北京 100101;贵州师范学院资源环境与灾害研究所, 贵州贵阳 550018;贵州师范学院资源环境与灾害研究所, 贵州贵阳 550018;贵州师范学院资源环境与灾害研究所, 贵州贵阳 550018 |
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| 基金项目： | 国家自然科学基金项目"喀斯特植物磷、钙胁迫的生态适应性调控机制研究"(31100187); 贵州教育厅科技项目(13GH069); 乌当科技局科研项目([2012]乌科技合同字48号) |
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| 摘 要： | 目的]研究中国PM2.5的空间分布特征及其影响因素,为区域可持续发展提供科学依据。方法]利用2014年2月25日上午9时和3月23日9时来自国家环保部的PM2.5时均浓度值,以GIS为平台利用双三次B样条方法,以中国陆疆国界为内插区域,模拟两个时相PM2.5浓度的空间分布,并在此基础上对比分析了中国和美国PM2.5浓度标准的差异,进一步分析荒漠化、降水、风速和经济增长水平对PM2.5浓度空间分异的影响。结果]模拟结果表明,京、津为中心的华北地区是中国PM2.5污染严重的区域,珠三角是另一个污染较严重的区域,西藏、新疆和贵州等西部省区是中国PM2.5浓度较低,空气质量较好的区域。结论]我国各地区PM2.5浓度与区域经济发展水平表现出显著的相关性。
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| 关 键 词： | 空间分布 PM2.5 空间内插 影响因素 GIS |
| 收稿时间： | 5/6/2014 12:00:00 AM |
| 修稿时间： | 2014/6/17 0:00:00 |
Spatial Distribution Model of Countrywide PM2.5 Concentration and Influence Factors Using Geographical Information System |
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| LI Song,LI Lian,LI Lian and WANG Hongyan.Spatial Distribution Model of Countrywide PM2.5 Concentration and Influence Factors Using Geographical Information System[J].Bulletin of Soil and Water Conservation,2015,35(4):202-205,212. |
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| Authors: | LI Song LI Lian LI Lian and WANG Hongyan |
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| Institution: | Institute of Resources Environment and Disaster, Guizhou Normal College, Guiyang, Guizhou 550018, China;Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;Institute of Resources Environment and Disaster, Guizhou Normal College, Guiyang, Guizhou 550018, China;Institute of Resources Environment and Disaster, Guizhou Normal College, Guiyang, Guizhou 550018, China;Institute of Resources Environment and Disaster, Guizhou Normal College, Guiyang, Guizhou 550018, China |
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| Abstract: | Objective] The characteristics of spatial distribution of PM2.5 in China and the influence factors were studied to provide scientific basis for environment monitoring. Methods] This paper collected hourly concentrations of PM2.5 pollutant at 9:00 on February 25 th and 9:00 on March 23 th, 2014. Consequentially, the countrywide spatial distribution of PM2.5 concentration was simulated within national boundaries using bicubic B-spline method in GIS. The concentration distribution was compared with that of USA spatially atdifferent standard. Results] The most serious polluted region is Beijing and Tianjin-centered north China, and another is Pearl River Delta. The western provinces, including Tibet, Xinjiang and Guizhou area are good-air regions with low concentration. Conclusion] There is a stable relationship between economic growth and PM2.5 concentration. |
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| Keywords: | spatial distribution PM2 5 spatial interpolation influence factors GIS |
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