京津冀城市群大气污染的时空特征与影响因素解析
The spatial-temporal characteristics and influencing factors of air pollution in Beijing-Tianjin-Hebei urban agglomeration
查看参考文献72篇
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文摘
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京津冀城市群是中国雾霾最严重的区域,在京津冀协同发展背景下,探究该地区大气污染的时空分布和影响因素具有重要意义。运用空间自相关分析和三种空间计量模型,分析了京津冀202个区县PM_(2.5)的时空分异特征,创新性地对自然与人文影响因素贡献及其空间溢出效应进行系统地甄别和量化。结果表明:2000-2014年来京津冀城市群PM_(2.5)浓度整体呈上升趋势,季节上呈秋冬高、春夏低,空间上呈东南高、西北低的特点,且城市建成区PM_(2.5)浓度比周围郊区和农村平均高10~20 μg/m~3;2014年仅有13.9%的区县空气质量达标,PM_(2.5)浓度存在显著的空间集聚性与扩散性,城市间交互影响距离平均为200 km,邻近地区的PM_(2.5)每升高1%,将导致本地PM_(2.5)至少升高0.5%;社会经济内因对PM_(2.5)主要是正向影响,自然外因主要是负向影响;影响因素中对本地大气污染的直接效应贡献强度依次是:年均风速>年均气温>人口密度>地形起伏度>第二产业占比>能源消费>植被覆盖度,人均GDP、年降水量和相对湿度对本地PM_(2.5)没有显著影响;对邻近地区大气污染具有显著空间溢出效应的因素排序是:植被覆盖度>地形起伏度>能源消费>人口密度;对于自然和人文影响因素应分别采取针对性的适应策略和调控策略,加强区域间联防联控与合作治理,在城市群规划中注重环保规划与立法。 |
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其他语种文摘
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Air pollution is now the most serious environmental problem in China, especially for Beijing-Tianjin-Hebei (Jing-Jin-Ji) urban agglomeration. Under the background of Jing-Jin-Ji integrated development, it is of great importance to study the spatio-temporal distribution and its influencing factors. This paper firstly analyzed the spatio-temporal characteristics of PM_(2.5) concentration in 202 counties of Jing-Jin-Ji urban agglomeration using spatial analysis and visualization. Then we quantified the effect degree of different natural and human factors and the spatial spillover effect of these factors using Spatial Durbin Model (SDM). The results are as follows: (1) The PM_(2.5) concentration was on the rise as a whole from 2000-2014, and it was high in autumn and winter, while low in spring and summer. Seen from spatial distribution, the PM_(2.5) concentration was high in the southeast, while low in the northwest of the study area, and the concentration in urban built-up area was 10-20 μg/m~3 higher than that of its surrounding suburban and rural areas. (2) The counties, whose PM_(2.5) concentration was below 35 μg/m~3, only accounted for 13.9% in 2014. There were significant spatial agglomeration and diffusivity of PM_(2.5), and the mean distance interacting among the cities was 200 km. The PM_(2.5) of a city increased by more than 0.5% for every 1% increase in the average PM_(2.5) of neighboring cities. (3) Socio-economic factors have positive impact on PM_(2.5), and most of natural factors have negative impact. (4) Among the influencing factors, contributions to local atmospheric pollution with direct effect are: mean wind speed > annual mean temperature > population density > relief amplitude > the secondary industry share of GDP > energy consumption > vegetation coverage; however, per capita GDP, annual precipitation, and relative humidity have no significant effect on local pollution. (5) Contributions to neighborhood atmospheric pollution with spatial spillover effect are: vegetation coverage > relief amplitude > population density. The findings suggest that we should adopt the adaptation strategies for natural factors and control strategies for human factors. A coordinated and strengthened cooperation between local governments should be established for air pollution control, and environmental planning and legislation should be strengthened in a new round of urban agglomeration planning in China. |
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来源
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地理学报
,2018,73(1):177-191 【核心库】
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DOI
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10.11821/dlxb201801015
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关键词
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大气污染
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雾霾
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PM_(2.5)
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时空演变
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联防联控
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空间杜宾模型
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京津冀城市群
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地址
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中国科学院地理科学与资源研究所, 北京, 100101
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中国科学院大学资源与环境学院, 北京, 100049
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武汉理工大学资源与环境工程学院, 武汉, 430070
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北京大学城市与环境学院, 北京, 100871
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中国科学院遥感与数字地球研究所, 北京, 100094
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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0375-5444 |
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学科
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环境污染及其防治 |
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基金
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国家自然科学基金重大项目
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文献收藏号
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CSCD:6155257
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