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机构地区:[1]南昌大学经济管理学院,中国江西南昌330031 [2]浙江财经大学经济学院,中国浙江杭州310018
出 处:《经济地理》2017年第3期174-181,共8页Economic Geography
基 金:国家社会科学基金重点项目(2015AZD070);国家社会科学基金项目(15FJL012);浙江省社会科学规划项目(14NDJC100YB)
摘 要:采用工业SO_2排放总量作为环境压力的衡量指标,基于自然正交函数(EOF)揭示了长江中游城市群工业SO_2排放量的时空演变特征,将工业SO_2排放的空间异质性纳入STIRPAT模型分析框架中,通过地理加权回归(GWR)模型进行空间变系数的驱动因素分析。结果表明:长江中游城市群工业SO_2排放总体处于上升态势,但增加速度呈现明显的减缓趋势。EOF第一模态结果显示,SO_2排放量以武汉和长株潭为中心向周边地区扩散。低值地区集中在江西的东南部和湖南的西南部。第二模态结果显示,SO_2排放量增加速度较快的城市大部分位于湖北的宜昌、荆州、黄冈地区和湖南的株洲、衡阳、永州地区以及江西的萍乡、新余和赣州地区,SO_2排放量增加速度减缓的地区则是三省省会城市及其相邻地市。驱动因素分析结果显示,SO_2强度、人口、第二产业比重和人均GDP是SO_2排放的主要影响因素,并且各个因素存在明显的空间差异。因此,各个地区必需制定区域差异化的环境保护政策。The economy of the urban agglomeration in the middle reaches of the Yangtze River has grown rapidly recently. Consequently, environmental problems have worsened. Various kinds of pollutant emissions, notably SO: emissions results in serious environmental degradation and thus undermines sustainability of the urban agglomeration in the middle reaches of the Yangtze River. This paper takes industrial SO2 emissions as the indicator of environmental pressures, analyzes spatio-temporal characteristics of industrial SO2 emissions of the urban agglomeration in the middle reaches of the Yangtze River based on empirical orthogonal function (EOF) method, and estimates driving forces of SO2 emissions in the framework of STIRPAT model by means of geographically weighted regression (GWR). The results show that SO2 emissions grow in an increasing trend overall but obviously rise slowly. The results of the first mode function of EOF indicate that cities centered on Wuhan and Chang-Zhu-Tan cluster emit high levels of SO2 emission while the southeast cities of Jiangxi Province and southwest cities of Hunan Province emit low levels of SO2 emissions. The results of the second mode function discover that cities with rapid growth of SO2 emissions are Yichang, Jingzhou, Huanggang of Hubei Province, Zhuzhou, Hengyang, Yongzhou of Hunan Province, and Pingxiang, Xinyu and Ganzhou of Jiangxi Province. Wuhan, Changsha and Nanchang as well as their peripheral cities are characterized with low growth of SO2 emissions. The results of GWR show that SO2 intensity, population, the share of the secondary sector and GDP per capita are the main driving forces of SO2 emissions. These driving forces have different impacts from cities to cities. Differentiated polices targeted to different cities need to be made to protect environment.
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