经济集聚对区域水污染物排放的影响及溢出效应
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摘要
基于化学需氧量和氨氮排放数据集,构建影响因素计量模型,探讨经济集聚同水污染物排放的影响效应及其在不同规模城镇下影响程度的差异性,采取双变量空间自相关解析中国经济集聚对水污染物排放的溢出效应,以期为促进经济集聚与污染减排良性互动提供参考。结论如下:(1)从全国总体样本来看,经济集聚能有效降低区域水污染排放强度,经济集聚度每增长1个百分点,化学需氧量和氨氮排放将分别减少0.491%和0.166%;(2)经济集聚对中小城市水污染排放的减排效应更为突出,在化学需氧量估计模型中,中等城市、小城市样本的经济集聚度弹性系数分别为-0.679、-0.546,而大城市及特大城市样本仅为-0.252;(3)经济集聚同水污染物排放的空间溢出效应显著,且呈现高集聚—高排放、低集聚—低排放、低集聚—高排放等空间关联模式,其中,高集聚—高排放区从京津冀向山东半岛绵延分布,还包括哈长城市群、苏北和苏中、长株潭、珠三角等地区。政策启示包括:积极培育中小城市并发挥其经济聚集的减排效应,促进生产技术更新和扩散,提高能源利用效率和环保投入;合理控制大城市经济与人口规模,加快产业结构调整和落后产能淘汰,强化环境规制以防止"污染避难所"效应;遏制经济集聚对水污染物排放的溢出效应,重点推进高集聚—高排放区联防联控和流域共治。
Based on the database of COD and NH3-N emissions from 339 cities at prefecture level in China, this paper explores the impact of economic agglomeration on regional water pollutant emissions and the differences in the impact levels between different city-size by using the econometric model. Meanwhile, a bivariate spatial autocorrelation method is adopted to analyze the spillover effect of economic agglomeration on water pollutant emissions, which provides a reference for making a benign interactive countermeasure to promote economic agglomeration and pollution mitigation. The results show that: according to the whole sample,economic agglomeration can effectively reduce the intensity of the regional water pollutant emissions. The degree of economic agglomeration increases by 1%, and the COD and NH3-N emissions will decrease by 0.491% and 0.166% respectively. Compared with the large cities and mega-cities, economic agglomerations have more prominent reduction effects on water pollutant in small and medium-sized cities. Economic agglomeration and water pollutant discharge have shown significant spatial spillover effects, and present spatial agglomeration patterns of high agglomeration-high emission, low agglomeration-low emission, and low agglomeration-high emission. High agglomeration-high emission areas are located from Beijing-Tianjin-Hebei region to the Shandong Peninsula, as well as other highly urbanized area such as Harbin-Changchun, the Yangtze River Delta, the Pearl River Delta and ChangshaZhuzhou-Xiangtan. Policy implications and suggestions include: actively nurturing small and medium-sized cities, exerting significant reduction effects of economic agglomeration,promoting technological upgrade and diffusion of production technologies, improving energy efficiency and environmental protection input; rationally controlling the economic and population size of large cities and mega-cities, improving environmental regulations to prevent "Pollution Haven" effects, and accelerating industrial restructuring and outdated production capacity to eliminate and strictly control over-standard and over-total emissions; reducing the negative externalities of economic agglomeration, with a focus on promoting joint prevention and basin governance of high agglomeration-high emission area.
Based on the database of COD and NH3-N emissions from 339 cities at prefecture level in China, this paper explores the impact of economic agglomeration on regional water pollutant emissions and the differences in the impact levels between different city-size by using the econometric model. Meanwhile, a bivariate spatial autocorrelation method is adopted to analyze the spillover effect of economic agglomeration on water pollutant emissions, which provides a reference for making a benign interactive countermeasure to promote economic agglomeration and pollution mitigation. The results show that: according to the whole sample,economic agglomeration can effectively reduce the intensity of the regional water pollutant emissions. The degree of economic agglomeration increases by 1%, and the COD and NH3-N emissions will decrease by 0.491% and 0.166% respectively. Compared with the large cities and mega-cities, economic agglomerations have more prominent reduction effects on water pollutant in small and medium-sized cities. Economic agglomeration and water pollutant discharge have shown significant spatial spillover effects, and present spatial agglomeration patterns of high agglomeration-high emission, low agglomeration-low emission, and low agglomeration-high emission. High agglomeration-high emission areas are located from Beijing-Tianjin-Hebei region to the Shandong Peninsula, as well as other highly urbanized area such as Harbin-Changchun, the Yangtze River Delta, the Pearl River Delta and ChangshaZhuzhou-Xiangtan. Policy implications and suggestions include: actively nurturing small and medium-sized cities, exerting significant reduction effects of economic agglomeration,promoting technological upgrade and diffusion of production technologies, improving energy efficiency and environmental protection input; rationally controlling the economic and population size of large cities and mega-cities, improving environmental regulations to prevent "Pollution Haven" effects, and accelerating industrial restructuring and outdated production capacity to eliminate and strictly control over-standard and over-total emissions; reducing the negative externalities of economic agglomeration, with a focus on promoting joint prevention and basin governance of high agglomeration-high emission area.
引文
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[3]陈祖海,雷朱家华.中国环境污染变动的时空特征及其经济驱动因素.地理研究, 2015, 34(11):2165-2178.[CHEN Z H, LEIZHU J H. The spatial-temporal characteristics and economic drivers of environmental pollution changes in China.Geographical Research, 2015, 34(11):2165-2178.]
[4]陆大道.中速增长:中国经济的可持续发展.地理科学, 2015, 35(10):1207-1219.[LU D D. Moderate-speed growth:Sustainable development of China's economy. Scientia Geographica Sinica, 2015, 35(10):1207-1219.]
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[10] HOSSEIN H M, KANEKO S. Can environment quality spread through institutions?. Energy Policy, 2013, 56(2):312-321.
[11] FRANK A, MOUSSIOPOULOSB N, BARTONOVAC A, et al. Urban air quality in larger conurbations in the European Union. Environmental Modelling&Software, 2001, 16(4):399-414.
[12]徐林清,聂楠.污染物排放的空间集聚及其影响因素:基于岭回归模型的分析.生态经济, 2015, 31(5):160-165.[XU L Q, NIE N. Spatial agglomeration and influencing factors of pollutant emissions:The analysis based on ridge regression model. Ecological Economy, 2015, 31(5):160-165.]
[13] ZHAO X F, DENG C L, HUANG X J, et al. Driving forces and the spatial patterns of industrial sulfur dioxide discharge in China. Science of the Total Environment, 2017, 577:279-288.
[14] NIJKAMP P, VERHOEF E T. Urban environmental externalities, agglomeration forces, and the technological"deus ex machina". Environment&Planning A, 2008, 40(4):928-947.
[15] THISSE J F. Human capital and agglomeration economies in urban development. The Developing Economies, 2018, 56(2):117-139.
[16] LIU G Y, YANG Z F, TANG Y C, et al. Spatial correlation model of economy-energy-pollution interactions:The role of river water as a link between production sites and urban areas. Renewable&Sustainable Energy Reviews, 2017, 69:1018-1028.
[17]于峰,齐建国.开放经济下环境污染的分解分析:基于1990-2003年间我国各省市的面板数据.统计研究, 2007, 24(1):47-53.[YU F, QI J G. Decomposing and analyzing the environmental pollution under the opening economic circumstances:Based on the panel data of provinces, autonomous regions and municipals of China from 1990 to 2003. Statistical Research, 2007, 24(1):47-53.]
[18]刘满凤,谢晗进.中国省域经济集聚性与污染集聚性趋同研究.经济地理, 2014, 34(4):25-32.[LIU M F, XIE H J.The convergence research of economy aggregation and pollution aggregation among China's provinces. Economic Geography, 2014, 34(4):25-32.]
[19] FRANK A. Urban air quality in larger conrbations in the European Union. Environmental Modeling and Software,2011, 16(4):399-414.
[20] VERHOEF E T, NIJKAMP P. Externalities in urban sustainability:Environmental versus localization-type agglomeration externalities in a general spatial equilibrium model of a single-sector monocentric industrial city. Ecological Economics, 2002, 40(2):157-179.
[21]高爽,魏也华,陈雯,等.发达地区制造业集聚和水污染的空间关联:以无锡市区为例.地理研究, 2011, 30(5):902-912.[GAO S, WEI Y H, CHEN W, et al. Study on spatial-correlation between water pollution and industrial agglomeration in the developed region of China:A case study of Wuxi city. Geographical Research, 2011, 30(5):902-912.]
[22] HOSOE M, NAITO T. Trans-boundary pollution transmission and regional agglomeration effects. Papers in Regional Science, 2006, 85(1):99-120.
[23]闫逢柱,苏李,乔娟.产业集聚发展与环境污染关系的考察:来自中国制造业的证据.科学学研究, 2011, 29(1):79-83.[YAN F Z, SU L, QIAO J. The exploration of the relationship between the industrial agglomeration's developments and the environmental pollution:The evidence from the manufacturing in China. Studies in Science of Science, 2011, 29(1):79-83.]
[24] GUO J, XU Y, PU Z. Urbanization and its effects on industrial pollutant emissions:An empirical study of a Chinese case with the spatial panel model. Sustainability, 2016, 8(8):812.
[25] WANG Z, JIA H F, XU T, et al. Manufacturing industrial structure and pollutant emission:An empirical study of China.Journal of Cleaner Production, 2018, 197(1):462-471.
[26]王晓硕,宇超逸.空间集聚对中国工业污染排放强度的影响.中国环境科学, 2017, 37(4):1562-1570.[WANG X S,YU C Y. Impact of spatial agglomeration on industrial pollution emissions intensity in China. China Environmental Science, 2017, 37(4):1562-1570.]
[27]张可.空间视角下经济集聚的减排效应研究.华中科技大学学报:社会科学版, 2017, 31(3):86-97.[ZHANG K. The reduction emissions effect of agglomeration based on spatial perspectives. Journal of Huazhong University of Science and Technology:Social Science Edition, 2017, 31(3):86-97.]
[28]徐成龙,程钰.新常态下山东省环境规制对工业结构调整及其大气环境效应研究.自然资源学报, 2016, 31(10):1662-1674.[XU C L, CHENG Y. The action of environmental regulation on industrial structure adjustment and atmospheric environment effect under the new normal in Shandong province. Journal of Natural Resources, 2016, 31(10):1662-1674.]
[29]邓玉萍,许和连.外商直接投资、集聚外部性与环境污染.统计研究, 2016, 33(9):47-54.[DENG Y P, XU H L. Foreign direct investment, agglomeration externalities and environmental pollution. Statistical Research, 2016, 33(9):47-54.]
[30] FERARD J F, BLAISE C. Encyclopedia of Aquatic Ecotoxicology. Dordrecht:Springer Science, 2013.
[31] SCHOLTEN M C T, FOEKEMA E M, DOKKUM H P V, et al. Eutrophication Management and Ecotoxicology. Heidelberg:Springer Berlin Heidelberg, 2005.
[32]陆大道,姚士谋.中国城镇化进程的科学思辨.人文地理, 2007, 22(4):1-5.[LU D D, YAO S M. A scientific thought about urbanization progress in China. Human Geography, 2007, 22(4):1-5.]
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