首页|基于不同城市规模的长三角地区PM2.5质量浓度变化及其影响因素

基于不同城市规模的长三角地区PM2.5质量浓度变化及其影响因素

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长三角地区是中国经济发展最活跃、创新能力最强的区域之一,但随工业化和城市化迅速推进,PM2.5污染问题受到了广泛关注.本文以长三角地区为研究对象,基于2000-2018年遥感反演的PM2.5数据,利用空间聚集分析、空间面板计量模型等方法,揭示不同人口规模城市PM2.5质量浓度的时空演变特征,及其关键影响因素.研究表明:①2000-2018年长三角地区PM2.5平均质量浓度约(40.5~59.1)μg/m3,整体呈现先上升后下降的趋势.②其中,特大城市与中等城市的PM2.5质量浓度持续走高,而其他规模城市的PM2.5质量浓度则呈现下降趋势,出现显著的"两极分化"现象.③长三角地区PM2.5质量浓度空间聚集性特征明显,PM2.5质量浓度"高-高"聚集区分布在长三角地区东北部,且聚集范围持续缩小,"低-低"聚集区从江苏中部转移至浙江中南部.④长三角地区PM2.5质量浓度存在空间溢出效应,影响PM2.5质量浓度变化的最重要因素是第二产业占比,其次是第三产业占比,城镇化率、地区生产总值和建成区占比的影响较小.
Analysis of PM2.5 concentration dynamics and its influencing factors in the Yangtze River Delta based on different city sizes
In terms of economic development,the Yangtze River Delta belongs to one of China's most active,open,and creative regions.However,due to the rapid industrialization,PM2.5 air pollutions in this region have drawn considerable attention.Taking the Yangtze River Delta as our research focus,via remote sensing PM2.5 inversion dataset and methods of spatial clustering analysis and spatial panel models,we investigated the spa-tial-temporal variations of PM2.5 and identifying its key driving factors considering different city sizes.Results founds that:1)From 2000-2018,the average value of PM2.5 in the Yangtze River Delta was around(40.5-59.1)ug/m3,with an overall trend of firstly growing and then decreasing,and the breakpoint appeared in year 2014.2)Over the same time frame,PM2.5 concentration in megacities and medium-sized cities was relatively high and showed an increasing trend,while PM2.5 concentration in other different sized cities was relatively low and showed a decreasing trend,showing the polarization characteristics.3)The Yangtze River Delta's PM2.5 con-centration showed clear spatial aggregation characteristics.The high-high PM2.5 concentration areas were dis-tributed in the northeastern sector,and their concentration range continued to shrink.The low-low PM2.5 con-centration areas were shifted from the Jiangsu Province to Zhejiang Province.4)The Yangtze River Delta's PM2.5 concentration showed a spatial spillover impact.The proportion of secondary industry ranked as the first driving factor influencing PM2.5 concentration,followed by the proportion of tertiary industry,while the urban-ization rate,GDP and the proportion of built-up areas have weak influence.

PM2.5spatial autocorrelationspatial panel modelsthe Yangtze River Delta

何昱、缪丽娟、顾伟男、鞠蕾

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南京信息工程大学地理科学学院,江苏南京 210044

PM2.5质量浓度 空间自相关 空间面板模型 长三角地区

国家自然科学基金项目江苏省科技计划项目江苏省研究生科研创新计划项目

42101295BK20210657KYCX24_1408

2024

地理科学
中国科学院 东北地理与农业生态研究所

地理科学

CSTPCDCSSCICHSSCD北大核心
影响因子:3.117
ISSN:1000-0690
年,卷(期):2024.44(8)
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