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大气污染物排放量与颗粒物环境空气质量的空间非协同耦合研究——以武汉市为例
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  • 英文篇名:Spatial non-coupling of air pollutant emissions and particulate matter-related air quality:A case study in Wuhan City, China
  • 作者:张金亭 ; 赵玉丹 ; 田扬戈 ; 何青青 ; 庄艳华 ; 彭韵羲 ; 洪松
  • 英文作者:ZHANG Jinting;ZHAO Yudan;TIAN Yangge;HE Qingqing;ZHUANG Yanhua;PENG Yunxi;HONG Song;School of Resources and Environmental Sciences, Wuhan University;School of Remote Sensing Information Engineering, Wuhan University;School of Resources and Environmental Engineering, Wuhan University of Technology;Institute of Geodesy and Geophysics, CAS;Geospatial Information Technology Collaborative Innovation Center;Shenzhen Research Institute, Wuhan University;
  • 关键词:大气污染 ; 空气质量 ; 气溶胶光学厚度(AOD) ; 耦合度 ; 空间错位指数 ; 武汉市
  • 英文关键词:air pollution;;air quality;;aerosol optical depth(AOD);;coupling;;spatial dislocation index;;Wuhan City
  • 中文刊名:地理科学进展
  • 英文刊名:Progress in Geography
  • 机构:武汉大学资源与环境科学学院;武汉大学遥感信息工程学院;武汉理工大学资源与环境工程学院;中国科学院测量与地球物理研究所;地球空间信息技术协同创新中心;武汉大学深圳研究院;
  • 出版日期:2019-04-28 17:08
  • 出版单位:地理科学进展
  • 年:2019
  • 期:04
  • 基金:深圳市科技计划项目(JCYJ20150630153917252);; 国家自然科学基金项目(41601608)~~
  • 语种:中文;
  • 页:150-162
  • 页数:13
  • CN:11-3858/P
  • ISSN:1007-6301
  • 分类号:X51
摘要
针对区域大气污染物排放量与空气质量在时空分布上存在不完全协同、匹配的现象,论文选择SO_2、NO_X、PM_(2.5)、CO和VOCs作为大气污染物指标,选择气溶胶光学厚度(Aerosol Optical Depth, AOD)表征颗粒物环境空气质量,以武汉市为例,综合应用耦合模型和空间错位指数模型研究2类指标之间的空间非协同耦合规律。主要结论如下:①武汉市大气污染物排放量与颗粒物空气质量具有不同空间分布特征,大气污染物排放量呈现由城市中心城区向远城区递减的趋势,其中SO_2、PM_(2.5)和VOCs的排放具有明显的中心聚集现象,而NO_X和CO聚集现象不显著,且与道路分布明显相关;AOD分布具有明显的空间差异性,总体上呈由西北向东南依次递减的趋势。②武汉市大气污染物排放与颗粒物空气质量的空间非协同耦合规律:越靠近城市中心城区,空间协同耦合现象越显著,空间错位现象越弱;越远离主城区,空间非协同耦合现象越显著,空间错位现象越显著;SO_2排放量与AOD在武汉市远城区的空间错位指数均大于0.7,且耦合度指数小于0.3,呈现较强的非协同耦合特征,NO_X、VOCs、PM_(2.5)的排放量与AOD在武汉中心城区的空间错位指数均小于0.5,且耦合度指数大于0.5,协同耦合现象较为显著。③基于时空非协同耦合分析城市大气环境污染治理建议:针对污染物与AOD空间错位不显著的城市中心城区,以本地减排治理为主;针对污染物与AOD空间错位显著的远城区,应在污染溯源分析的基础上进行区域协调综合治理。
        As the spatial and temporal distributions of regional air pollutant emissions and air quality do not completely match, SO_2, NO_X, PM_(2.5), CO, and VOCs were selected as indicators of air pollutants, and aerosol optical depth(AOD) was selected to characterize the ambient air quality of particulate matters in this study to examine their spatial coupling. Taking Wuhan City as an example, the coupling model and spatial dislocation index model were used to study the spatial non-coupling pattern of the two indices. The main conclusions are as follows: 1) Air pollutant emissions and particulate matter-related air quality in Wuhan City present different spatial distribution characteristics. The emissions of atmospheric pollutants showed a decreasing trend from the central area of the city to the surrounding areas. The emissions of SO_2, PM_(2.5), and VOCs presented an obvious central aggregation phenomenon, while NO_X and CO aggregation was not significant, but was significantly related to the distribution of roads. The distribution of AOD showed clear spatial heterogeneity, and generally decreased from northwest to southeast. 2) The spatial coupling pattern of air pollutant emissions and particulate matter-related air quality in Wuhan City indicates that the closer to the urban center, the more significant the spatial co-occurrence, and the weaker the spatial dislocation was. The farther away from the main urban area, the more significant the spatial non-coupling or dislocation was. The spatial dislocation index value of SO_2 emission and AOD in the surrounding urban areas of Wuhan City was greater than 0.7 and the coupling index value was less than 0.3, showing a strong non-coupling feature. The spatial dislocation index of NO_X, VOCs, and PM_(2.5) emissions and AOD in the central urban area of Wuhan City was less than 0.5 and the coupling index was greater than 0.5, showing a significant coupling phenomenon. 3) The suggestions for urban air pollution control based on the spatiotemporal non-coupling analysis are: for the central urban areas where the spatial dislocation between pollutant discharge and AOD is not significant, local emission reduction is the main method for pollution control. Comprehensive measures should be formulated on the basis of pollution souce identification for the surrounding areas with significant spatial dislocation of pollutant discharge and AOD.
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