摘要
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,PM_(2.5)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PM_(2.5)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PM_(2.5)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PM_(2.5)平均质量浓度约(40.5~59.1)μg/m^(3),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PM_(2.5)质量浓度持续走高,而其他规模城市的PM_(2.5)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PM_(2.5)质量浓度空间聚集性特征明显,PM_(2.5)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PM_(2.5)质量浓度存在空间溢出效应,影响PM_(2.5)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。
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,PM_(2.5)air pollutions in this region have drawn considerable attention.Taking the Yangtze River Delta as our research focus,via remote sensing PM_(2.5) inversion dataset and methods of spatial clustering analysis and spatial panel models,we investigated the spatial–temporal variations of PM_(2.5)and identifying its key driving factors considering different city sizes.Results founds that:1)From 2000—2018,the average value of PM_(2.5)in the Yangtze River Delta was around(40.5-59.1)μg/m^(3),with an overall trend of firstly growing and then decreasing,and the breakpoint appeared in year 2014.2)Over the same time frame,PM_(2.5)concentration in megacities and medium–sized cities was relatively high and showed an increasing trend,while PM_(2.5)concentration in other different sized cities was relatively low and showed a decreasing trend,showing the polarization characteristics.3)The Yangtze River Delta’s PM_(2.5)concentration showed clear spatial aggregation characteristics.The high–high PM_(2.5)concentration areas were distributed in the northeastern sector,and their concentration range continued to shrink.The low–low PM_(2.5)concentration areas were shifted from the Jiangsu Province to Zhejiang Province.4)The Yangtze River Delta’s PM_(2.5)concentration showed a spatial spillover impact.The proportion of secondary industry ranked as the first driving factor influencing PM_(2.5)concentration,followed by the proportion of tertiary industry,while the urbanization rate,GDP and the proportion of built–up areas have weak influence.
作者
何昱
缪丽娟
顾伟男
鞠蕾
He Yu;Miao Lijuan;Gu Weinan;Ju lei(School of Geographical Sciences,Nanjing University of Information Science and Technology,Nanjing 210044,Jiangsu,China)
出处
《地理科学》
CSCD
北大核心
2024年第8期1426-1436,共11页
Scientia Geographica Sinica
基金
国家自然科学基金项目(42101295)
江苏省科技计划项目(BK20210657)
江苏省研究生科研创新计划项目(KYCX24_1408)资助。