长江经济带工业水环境压力与经济增长脱钩努力研究
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摘要
借助LMDI分解技术和Tapio脱钩模型,研究2000—2017年期间长江经济带工业水环境压力与经济增长的脱钩关系和脱钩努力程度。结果表明:长江经济带工业水环境压力呈现出从弱脱钩到强脱钩的良好态势,各地区的脱钩系数、脱钩状态存在时空差异;长江经济带各地区的脱钩努力程度不同,其中,重庆做出的脱钩努力最大,江西做出的脱钩努力最小;从各脱钩努力指标来看,节水技术的脱钩努力程度显著提高,排污系数的脱钩努力指标先上升后下降且一直处于低效状态,产业结构的脱钩努力状态由无效转为低效,人口规模一直未作出脱钩努力。因此,长江经济带各地区应做到节水增流与控源减污双管齐下,产业优化与人口控制协调配合,实现经济绿色增长。
This paper applied the LMDI method and Tapio index to carry on a decomposition analysis on the decoupling elasticity and effort index between industrial water environment pressure and economic growth in Yangtze River Economic Belt from 2000 to 2017. The results indicated that: The decoupling situation of pressure of industrial water environment and economic development in Yangtze River Economic Belt is from weak decoupling to strong decoupling. The decoupling coefficient and decoupling situation of different regions are different in time and space; The degree of decoupling effort exist regional differences, of which the most effort made by Chongqing, the least effort made by Jiangxi; The decoupling effort indicator of water-saving technology improved markedly. The decoupling effort indicator of pollutant discharge coefficient shows a trend of rising at the beginnings and falling afterwards, and it is normally inefficient. The population size had never made the contributions to the decouple index. Water saving and pollution reduction, industrial structure optimization and population control should be adopted in Yangtze River Economic Belt Region.
This paper applied the LMDI method and Tapio index to carry on a decomposition analysis on the decoupling elasticity and effort index between industrial water environment pressure and economic growth in Yangtze River Economic Belt from 2000 to 2017. The results indicated that: The decoupling situation of pressure of industrial water environment and economic development in Yangtze River Economic Belt is from weak decoupling to strong decoupling. The decoupling coefficient and decoupling situation of different regions are different in time and space; The degree of decoupling effort exist regional differences, of which the most effort made by Chongqing, the least effort made by Jiangxi; The decoupling effort indicator of water-saving technology improved markedly. The decoupling effort indicator of pollutant discharge coefficient shows a trend of rising at the beginnings and falling afterwards, and it is normally inefficient. The population size had never made the contributions to the decouple index. Water saving and pollution reduction, industrial structure optimization and population control should be adopted in Yangtze River Economic Belt Region.
引文
[1] 张陈俊,赵存学,林琳,等.长江三角洲地区用水量时空差异的驱动效应研究[J].资源科学,2018,40(1):89-103.
[2] 刘华军,杨骞.环境污染、时空依赖与经济增长[J].产业经济研究,2014(1):81-91.
[3] 张月,潘柏林,李锦彬,等.基于库兹涅茨曲线的中国工业用水与经济增长关系研究[J].资源科学,2017,39(6):1117-1126.
[4] 刘婷婷,马忠玉,万年青,等.经济增长与环境污染的库兹涅茨曲线分析与预测——以宁夏为例[J].地域研究与开发,2011,30(3):62-66.
[5] APERGIS N.Environmental Kuznets Curves:New Evidence on both Panel and Country-level CO2 Emissions[J].Energy Economics,2016,54:263-271.
[6] 马丽梅,史丹.京津冀绿色协同发展进程研究:基于空间环境库兹涅茨曲线的再检验[J].中国软科学,2017(10):82-93.
[7] 吴玉鸣,田斌.省域环境库兹涅茨曲线的扩展及其决定因素——空间计量经济学模型实证[J].地理研究,2012,31(4):627-640.
[8] 黄滢,王敏.中国的环境污染与经济增长[J].经济学(季刊),2015(1):557-578.
[9] 邓朝晖,薛惠锋,刘洋.基于VAR模型的水资源利用与经济增长动态关系研究[J].中国人口·资源与环境,2012,22(6):128-135.
[10] 雷明,虞晓雯.我国低碳经济增长的测度和动态作用机制——基于非期望DEA和面板VAR模型的分析[J].经济科学,2015(2):44-57.
[11] TAPIO P.Towards A Theory of Decoupling:Degrees of Decoupling in the EU and the Case of Road Traffic in Finland between 1970 and 2001[J].Transport Policy,2005,12(2):137-151.
[12] PAPAGLANNAKI K,DIAKOULAKI D.Decomposition Analysis of CO2 Emissions from Passenger Cars:The Cases of Greece and Denmark[J].Energy Policy,2009,37(8):3259-3267.
[13] GUEVARA Z,DOMINGAOS T.Three-level Decoupling of Energy Use in Portugal 1995—2010[J].Energy Policy,2017,108:134-142.
[14] 王崇梅.中国经济增长与能源消耗脱钩分析[J].中国人口·资源与环境,2010,20(3):35-37.
[15] 王君华,李霞,中国工业行业经济增长与CO2排放的脱钩效应[J].经济地理,2015,35(5):105-110.
[16] 仇方道,张纯敏,张慧敏,等.江苏省城市拓展对资源消耗影响的时空特征[J].地域研究与开发,2015,34(6):131-136.
[17] 吴丹,王亚华.中国经济发展与水环境压力脱钩态势评价与展望[J].长江流域资源与环境,2013,22(9):1103-1109.
[18] 杨丹,张鹏岩,周志民,等.城市用地扩张和经济发展的协整性与因果关系分析——以河南省为例[J].地域研究与开发,2018,37(4):67-72,85.
[19] 郭承龙,张智光.污染物排放量增长与经济增长脱钩状态评价研究[J].地域研究与开发,2013,32(3):94-98.
[20] 夏勇,胡雅蓓.经济增长与环境污染脱钩的因果链分解及内外部成因研究——来自中国30个省份的工业SO2排放数据[J].产业经济研究,2017(5):100-113.
[21] 张成,蔡万焕,于同申.区域经济增长与碳生产率——基于收敛及脱钩指数的分析[J].中国工业经济,2013(5):18-30.
[22] 卢强,吴清华,周永章,等.广东省工业绿色转型升级评价的研究[J].中国人口·资源与环境,2013,23(7):34-41.
[23] ANG B W.The LMDI Approach to Decomposition Analysis:A Practical Guide[J].Energy Policy,2005,33(7):867-871.
[24] 陈东景.我国工农业水资源使用强度变动的区域因素分解与差异分析[J].自然资源学报,2012,27(2):332-343.
[25] 张陈俊,章恒全,陈其勇,等.中国用水量变化的影响因素分析——基于LMDI方法[J].资源科学,2016,38(7):1308-1322.
[26] DIAKOULAKI D,MANDARAKA M.Decomposition Analysis for Assessing the Progress in Decoupling Industrial Growth from CO2 Emissions in the EU Manufacturing Sector[J].Energy Economics,2007,29(4):636-664.
(1)受篇幅限制,仅选择2000—2017年为时间跨度进行工业废水排放量的驱动效应分解,如有需要2000—2017年长江经济带工业废水排放量驱动效应的逐年分解结果,可向作者索取。
[2] 刘华军,杨骞.环境污染、时空依赖与经济增长[J].产业经济研究,2014(1):81-91.
[3] 张月,潘柏林,李锦彬,等.基于库兹涅茨曲线的中国工业用水与经济增长关系研究[J].资源科学,2017,39(6):1117-1126.
[4] 刘婷婷,马忠玉,万年青,等.经济增长与环境污染的库兹涅茨曲线分析与预测——以宁夏为例[J].地域研究与开发,2011,30(3):62-66.
[5] APERGIS N.Environmental Kuznets Curves:New Evidence on both Panel and Country-level CO2 Emissions[J].Energy Economics,2016,54:263-271.
[6] 马丽梅,史丹.京津冀绿色协同发展进程研究:基于空间环境库兹涅茨曲线的再检验[J].中国软科学,2017(10):82-93.
[7] 吴玉鸣,田斌.省域环境库兹涅茨曲线的扩展及其决定因素——空间计量经济学模型实证[J].地理研究,2012,31(4):627-640.
[8] 黄滢,王敏.中国的环境污染与经济增长[J].经济学(季刊),2015(1):557-578.
[9] 邓朝晖,薛惠锋,刘洋.基于VAR模型的水资源利用与经济增长动态关系研究[J].中国人口·资源与环境,2012,22(6):128-135.
[10] 雷明,虞晓雯.我国低碳经济增长的测度和动态作用机制——基于非期望DEA和面板VAR模型的分析[J].经济科学,2015(2):44-57.
[11] TAPIO P.Towards A Theory of Decoupling:Degrees of Decoupling in the EU and the Case of Road Traffic in Finland between 1970 and 2001[J].Transport Policy,2005,12(2):137-151.
[12] PAPAGLANNAKI K,DIAKOULAKI D.Decomposition Analysis of CO2 Emissions from Passenger Cars:The Cases of Greece and Denmark[J].Energy Policy,2009,37(8):3259-3267.
[13] GUEVARA Z,DOMINGAOS T.Three-level Decoupling of Energy Use in Portugal 1995—2010[J].Energy Policy,2017,108:134-142.
[14] 王崇梅.中国经济增长与能源消耗脱钩分析[J].中国人口·资源与环境,2010,20(3):35-37.
[15] 王君华,李霞,中国工业行业经济增长与CO2排放的脱钩效应[J].经济地理,2015,35(5):105-110.
[16] 仇方道,张纯敏,张慧敏,等.江苏省城市拓展对资源消耗影响的时空特征[J].地域研究与开发,2015,34(6):131-136.
[17] 吴丹,王亚华.中国经济发展与水环境压力脱钩态势评价与展望[J].长江流域资源与环境,2013,22(9):1103-1109.
[18] 杨丹,张鹏岩,周志民,等.城市用地扩张和经济发展的协整性与因果关系分析——以河南省为例[J].地域研究与开发,2018,37(4):67-72,85.
[19] 郭承龙,张智光.污染物排放量增长与经济增长脱钩状态评价研究[J].地域研究与开发,2013,32(3):94-98.
[20] 夏勇,胡雅蓓.经济增长与环境污染脱钩的因果链分解及内外部成因研究——来自中国30个省份的工业SO2排放数据[J].产业经济研究,2017(5):100-113.
[21] 张成,蔡万焕,于同申.区域经济增长与碳生产率——基于收敛及脱钩指数的分析[J].中国工业经济,2013(5):18-30.
[22] 卢强,吴清华,周永章,等.广东省工业绿色转型升级评价的研究[J].中国人口·资源与环境,2013,23(7):34-41.
[23] ANG B W.The LMDI Approach to Decomposition Analysis:A Practical Guide[J].Energy Policy,2005,33(7):867-871.
[24] 陈东景.我国工农业水资源使用强度变动的区域因素分解与差异分析[J].自然资源学报,2012,27(2):332-343.
[25] 张陈俊,章恒全,陈其勇,等.中国用水量变化的影响因素分析——基于LMDI方法[J].资源科学,2016,38(7):1308-1322.
[26] DIAKOULAKI D,MANDARAKA M.Decomposition Analysis for Assessing the Progress in Decoupling Industrial Growth from CO2 Emissions in the EU Manufacturing Sector[J].Energy Economics,2007,29(4):636-664.
(1)受篇幅限制,仅选择2000—2017年为时间跨度进行工业废水排放量的驱动效应分解,如有需要2000—2017年长江经济带工业废水排放量驱动效应的逐年分解结果,可向作者索取。