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我国农业面源污染的时空分异与动态演进
引用本文:吴义根,冯开文,李谷成.我国农业面源污染的时空分异与动态演进[J].中国农业大学学报,2017,22(7):186-199.
作者姓名:吴义根  冯开文  李谷成
作者单位:中国农业大学 经济管理学院, 北京 100083;池州学院 商学院, 安徽 池州 247000,中国农业大学 经济管理学院, 北京 100083,华中农业大学 经济管理学院/湖北农村发展研究中心, 武汉 430070
基金项目:安徽省高校自然科学研究重点项目(KJ2014A177);国家自然科学基金面上项目(71273103);国家自然科学基金国际合作项目(NSFC-CGIAR,71461010701)
摘    要:为了准确把握我国农业面源污染的空间分布规律,有效治理农业面源污染。选取1997—2013年中国30个省市面板数据,分析了我国农业面源污染的时间、空间分布特征,利用非参数核密度估计模型讨论了农业面源污染的动态演进情况,进一步利用探索性空间数据分析方法(ESDA)讨论了其空间相关性。结果表明:1)农业化肥投入、农业固体废弃物(秸秆)、水产养殖和畜禽养殖这四类污染源的产生量以及他们产生的氮、磷和化学需氧量三类污染物逐年增长,其中畜禽养殖的贡献最大。2)农业面源污染严重的区域集中在农业大省和经济发达地区,在空间上以中部地区、华北地区为核心区域,向外围辐射并呈现递减趋势。3)农业面源污染区域明显集聚,区域差异较大,极化现象比较严重。4)农业面源污染表现出明显的空间相关性,形成高高型集聚区域,主要位于农业大省。据此,应该加强政策激励和引导农业农户的环保意识,推进农业生产由农业粗放式增长向数量、质量型增长转变。考虑相邻区域政策等要素空间溢出的负效应,在高高型集聚区域内,应该采用区域联防政策,杜绝农业面源污染治理的此消彼长,通过齐抓共管,实现多赢。

关 键 词:农业面源污染  空间相关性  动态演进  空间分异
收稿时间:2016/10/6 0:00:00

Spatial-temporal pattern and dynamic evolution of agricultural non-point source pollution in China
WU Yigen,FENG Kaiwen and LI Gucheng.Spatial-temporal pattern and dynamic evolution of agricultural non-point source pollution in China[J].Journal of China Agricultural University,2017,22(7):186-199.
Authors:WU Yigen  FENG Kaiwen and LI Gucheng
Institution:College of Economics and Management, China Agricultural University, Beijing 100083, China;School of Business, Chizhou University, Chizhou 247000, China,College of Economics and Management, China Agricultural University, Beijing 100083, China and College of Economics & Management/Hubei Rural Development Research Center, Huazhong Agricultural University, Wuhan 430070, China
Abstract:To acquire an accurate understanding the spatial distribution rule of agricultural non-point source pollution in China,the panel data of 30 provinces in China from 1997 to 2013 were adopted to analyze the spatial and temporal distribution characteristics of Chinese agricultural non-point source pollution. A non-parametric kernel density estimation model was built to discuss the dynamic evolution of agricultural non-point source pollution and an exploratory spatial data analysis method was further employed to discuss its spatial correlation.The result showed that:Pollution from four sources including agricultural fertilizer inputs,agricultural solid wastes (straws),aquaculture and livestock and poultry farming,and three kinds of pollutants,which are nitrogen,phosphorus and chemical oxygen demand,kept increasing year by year.Among which,the livestock and poultry breeding contributed the most.The area of serious agricultural non-point source pollution was concentrated in big agricultural provinces and economically developed places.The central and northern regions were the core area in the spatial distribution,and the core area was radiating to the external and shows a decreasing trend.Agricultural non-point source pollution areas agglomerated obviously,but differed greatly,and polarized seriously.Agricultural non-point source pollution showed obvious spatial correlation,and formed a high-high concentration area,mainly located in big agricultural provinces.Therefore,the policy incentives should be strengthened,environmental awareness of farmers should be guided,and agricultural production should be encouraged to develop from extensive growth to quantity and qualitative and quantitative growth.Considering the negative effects of spatial spillovers of adjacent regional policy,the zone defense policy should be utilized to eliminate the shift of agricultural non-point source pollution management in high-high agglomeration areas and to create a win-win situation with great effort and strict control.
Keywords:agricultural non-point source pollution  spatial correlation  dynamic evolution  spatial differentiation
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