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中国主要城市空气污染的影响因素——基于污染源解析的研究 被引量:8

Impact Factors of Air Pollution in Chinese Important Cities: Based on Source Apportionment
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摘要 根据环保部门的污染源解析结果,建立面板计量经济学模型,探讨2002--2015年74个按空气质量新标准第一阶段监测城市的空气污染人为影响因素,并按冬季是否集中供暖分为南方与北方城市,按经济发展状况分为东部、中部与西部城市。结果表明,煤炭消耗、第二产业比重几乎是南北方、东中西部所有城市空气污染的显著性影响因素,汽车拥有量主要对南方城市、东部城市有显著影响,房地产开发的影响则不太显著。最后从煤炭消耗、第二产业发展、汽车使用、建筑施工等方面提出治理空气污染的建议。 According to source apportionment of air pollutants, this paper researches the main man-made factors of air pollution in 74 monitoring cities in the first phase of the new standards for air quality based on panel econometric model in 2002-2015. In order to research deeply, these cities are divided into southern cities and northern cities according to central heating, and eastern cities, middle cities and western cities according to economic conditions. The results show that coal consumption and the proportion of secondary industry are significant factors of air pollutant in most southern cities and northern cities, eastern cities, middle cities and western cities. Vehicle number just has significant impacts on southern cities and eastern cities. Real estate industry is not a significant factor. At last, some recommendations are put forward to control air pollution from coal consumption, secondary industry development, vehicles use and building operations etc.
作者 李惠娟 周德群 魏永杰 LI Huijuan1, 2, ZHOU Dequn2, WEI Yongjie3(1. School of Economy, Xuzhou University of Technology, Xuzhou Jiangsu 22111 l, China; 2. College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing Jiangsu 211106, China; 3. China Research Academy of Environment Science, Beijing 100012, Chin)
出处 《生态经济》 北大核心 2018年第4期197-203,共7页 Ecological Economy
基金 国家社会科学基金重大项目“新常态下产业集聚的环境效应与调控政策研究”(15ZDA053) 国家社会科学基金项目“基于公众健康的长三角雾霾协同治理动力机制与责任成本分配研究”(17BGL141) 国家自然科学基金项目“考虑大气污染物协同控制和减排策略差异的城市二氧化碳减排成本研究”(71573119) 江苏省“六大人才高峰”高层次人才项目“长三角地区大气污染区域联防联控的动力机制”(JY-082) 江苏高校哲学社会科学项目“江苏省空气污染的健康经济损失评估及应对策略研究”(2016SJD790028)
关键词 空气污染 污染源解析 影响因素 面板模型 地域差异 air pollution source apportionment impact factors panel model regional difference
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