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Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area

QIU Fangdao CHEN Yang TAN Juntao LIU Jibin ZHENG Ziyan ZHANG Xinlin

QIU Fangdao, CHEN Yang, TAN Juntao, LIU Jibin, ZHENG Ziyan, ZHANG Xinlin. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area[J]. 中国地理科学, 2020, 30(2): 352-365. doi: 10.1007/s11769-020-1114-3
引用本文: QIU Fangdao, CHEN Yang, TAN Juntao, LIU Jibin, ZHENG Ziyan, ZHANG Xinlin. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area[J]. 中国地理科学, 2020, 30(2): 352-365. doi: 10.1007/s11769-020-1114-3
QIU Fangdao, CHEN Yang, TAN Juntao, LIU Jibin, ZHENG Ziyan, ZHANG Xinlin. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area[J]. Chinese Geographical Science, 2020, 30(2): 352-365. doi: 10.1007/s11769-020-1114-3
Citation: QIU Fangdao, CHEN Yang, TAN Juntao, LIU Jibin, ZHENG Ziyan, ZHANG Xinlin. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area[J]. Chinese Geographical Science, 2020, 30(2): 352-365. doi: 10.1007/s11769-020-1114-3

Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area

doi: 10.1007/s11769-020-1114-3
基金项目: 

Under the auspices of the National Natural Science Foundation of China (No. 41671123, 41971158, 41671122), Major Project of Philosophy and Social Science Research of Jiangsu Universities (No. 2018SJZDA010)

详细信息
    通讯作者:

    TAN Juntao.E-mail:tanjuntaocf@163.com

    LIU Jibin.E-mail:liujb034@163.com

Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area

Funds: 

Under the auspices of the National Natural Science Foundation of China (No. 41671123, 41971158, 41671122), Major Project of Philosophy and Social Science Research of Jiangsu Universities (No. 2018SJZDA010)

  • 摘要:

    This study analyzed the spatial-temporal heterogeneity of green development efficiency and its influencing factors in the growing Xuzhou Metropolitan Area for the period 2000-2015. The slacks-based measure (SBM) model, spatial autocorrelation, and the geographically weighted regression (GWR) model were used to conduct the analysis. The conclusions were as follows:first, the overall efficiency of green development of the Xuzhou Metropolitan Area decreased, the regional differences and spatial agglomeration shrunk and differences within the region were the main contributors to the regional differences of green development efficiency. Second, the counties with high-efficiency green development were distributed along the coast, and along the routes of the Beijing-Shanghai and the Eastern Longhai railways. A developing axis of the high-efficiency counties was the main feature of the spatial pattern for green development efficiency. Third, regarding spatial correlation and green development efficiency, the High-High type counties in the Xuzhou Metropolitan Area formed a centralized distribution corridor along the inter-provincial border areas of Henan and Jiangsu, whereas the Low-Low type counties were concentrated in the external, marginal parts of the metropolitan area. Fourth, the major factors (ranked in decreasing order of impact) influencing green development efficiency were innovation, government regulations, the economic development level, energy consumption, and industrial structure. These factors exerted their influence to varying extents; the influence of the same factor had different effects in different regions and obvious spatial differences were observed for the different regions.

  • [1] Affolderbach J, Schulz C, 2017. Positioning Vancouver through urban sustainability strategies? The greenest city 2020 action plan. Journal of Cleaner Production, 164:676-685. doi: 10.1016/j.jclepro.2017.06.234
    [2] Anselin L, 1999. Interactive techniques and exploratory spatial data analysis. In Longley P A, Goodchild M F, Maguire D J et al (eds). Geographical Information Systems:principles, techniques, management and applications. Wiley, New York, Chichestre, Toronto and Brisbane, 251-264.
    [3] Che Lei, Bai Yonping, Zhou Liang et al., 2018. Spatial pattern and spillover effects of green development efficiency in China. Scientia Geographica Sinica, 38(11):1788-1798. (in Chinese)
    [4] Di Qianbin, Meng Xue, 2017. Spatial and temporal disparities of urban development efficiency of coastal cities in China based on undesirable outputs. Scientia Geographica Sinica, 37(6):807-816. (in Chinese)
    [5] Fang C L, Liu H M, Li G D et al., 2015. Estimating the impact of urbanization on air quality in China using spatial regression models. Sustainability, 7(11):15570-15592. doi: 10.3390/su71115570
    [6] Fay M, Hallegatte S, Bank W, 2012. Inclusive Green Growth:The Pathway to Sustainable Development. Washington, DC:World Bank.
    [7] Hennig T, Harlan T, 2018. Shades of green energy:geographies of small hydropower in Yunnan, China and the challenges of over-development. Global Environmental Change, 49:116-128. doi: 10.1016/j.gloenvcha.2017.10.010
    [8] Hosseini S E, Wahid M A, 2016. Hydrogen production from renewable and sustainable energy resources:promising green energy carrier for clean development. Renewable and Sustainable Energy Reviews, 57:850-866. doi:10.1016/j.rser. 2015.12.112.
    [9] Hu Angang, Zhou Shaojie, 2014. Green development:functional definition, mechanism analysis and development strategy. China Population, Resources and Environment, 24(1):14-20. (in Chinese)
    [10] Hu Yanxing, Pan Jinghu, Wang Yirui, 2015. Spatial-temporal evolution of provincial carbon emission in China from 1997 to 2012 based on ESDA and GWR model. Acta Scientiae Circumstantiae, 35(6):1896-1906. (in Chinese)
    [11] Hu Yanxing, Pan Jinghu, Li Zhen et al., 2016. Spatial-temporal analysis of provincial carbon emissions in China from 1997 to 2012 with EOF and GWR methods. Acta Scientiae Circumstantiae, 36(5):1866-1874. (in Chinese)
    [12] Hu Zongyi, Li Yi, Liu Yiwen, 2017. Regional differences and convergence analysis of green technology efficiency in China. Soft Science, 31(8):1-4. (in Chinese)
    [13] LI Shu, YING Zhixia, ZHANG Huan et al., 2019. Comprehensive assessment of urbanization coordination:a case study of Jiangxi Province, China. Chinese Geographical Science, 2019 (3):488-502. doi: 10.1007/s11769-019-1021-7
    [14] Lin Xiao, Xu Wei, Yang Fan et al., 2017. Spatio-temporal characteristics and driving forces of green economic efficiency in old industrial base of northeastern China:a case study of Liaoning province. Economic Geography, 37(5):125-132. (in Chinese)
    [15] Liu Chengliang, Yu Ruiling, Xiong Jianping et al., 2009. Spatial accessibility of road network in Wuhan metropolitan area. Acta Geographica Sinica, 61(12):1488-1498. (in Chinese)
    [16] Liu Mingguang, 2017. Research on spatial distribution and convergence of green innovation efficiency in regional innovation system. Journal of Industrial Technological Economics, (4):10-18. (in Chinese)
    [17] Long R Y, Shao T X, Chen H, 2016. Spatial econometric analysis of China's province-level industrial carbon productivity and its influencing factors. Applied Energy, 166:210-219. doi: 10.1016/j.apenergy.2015.09.100
    [18] Luo Liangwen, Liang Shengrong, 2016. Green technology innovation efficiency and factor decomposition of China's industrial enterprises. China Population, Resources and Environment, 26(9):149-157. (in Chinese)
    [19] Lyytimäki J, Antikainen R, Hokkanen J et al., 2018. Developing key indicators of green growth. Sustainable Development, 26(1):51-64. doi: 10.1002/sd.1690
    [20] Ma Hailiang, Ding Yuanqing, Wang Lei, 2017. Measurement and convergence analysis of green water utilization efficiency. Journal of Natural Resources, 32(3):406-417. (in Chinese)
    [21] Moutinho V, Madaleno M, Robaina M, 2017. The economic and environmental efficiency assessment in EU cross-country:evidence from DEA and quantile regression approach. Ecological Indicators, 78:85-97. doi: 10.1016/j.ecolind.2017.02.042
    [22] Mu Xueying, Liu Kai, Ren Jianlan, 2017. Spatial differentiation and change of green production efficiency in China. Progress in Geography, 36(8):1006-1014. (in Chinese)
    [23] NBSC (National Bureau of Statistics of China), 2001-2016. China City Statistical Yearbook. Beijing:China Statistics Press. (in Chinese).
    [24] NBSC (National Bureau of Statistics of China), 2001-2016. Jiangsu Statistical Yearbook. Beijing:China Statistics Press. (in Chinese).
    [25] NBSC (National Bureau of Statistics of China), 2001-2016. Anhui Statistical Yearbook. Beijing:China Statistics Press. (in Chinese).
    [26] NBSC (National Bureau of Statistics of China), 2001-2016. Shandong Statistical Yearbook. Beijing:China Statistics Press. (in Chinese).
    [27] NBSC (National Bureau of Statistics of China), 2001-2016. Henan Statistical Yearbook. Beijing:China Statistics Press. (in Chinese).
    [28] NBSC (National Bureau of Statistics of China), 2001-2016. China Statistical Yearbook. Beijing:China Statistics Press. (in Chinese).
    [29] Nie Yuli, Wen Huwei, 2015. Green economic efficiency of Chinese city at the level of municipality or above. China Population, Resources and Environment, 25(5):409-413. (in Chinese)
    [30] Peng Wei, Xiong Ke, 2018. Ecological efficiency evaluation and spatial evolution of Guangdong province from the perspective of environmental pressure. Economic Geography, 38(8):179-186. (in Chinese)
    [31] Ren Tingting, Zhou Zhongxue, 2019. Influence of agricultural structure transformation on ecosystem services and human well-being:case study in Xi'an metropolitan area. Acta Ecologica Sinica, 39(7):2353-2365. (in Chinese)
    [32] Richter B, Behnisch M, 2019. Integrated evaluation framework for environmental planning in the context of compact green cities. Ecological Indicators, 96:38-53. doi: 10.1016/j.ecolind.2018.05.025
    [33] Sun Caizhi, Jiang Kun, Zhao Liangshi, 2017. Measurement of green efficiency of water utilization and its spatial pattern in China. Journal of Natural Resources, 32(12):1999-2011. (in Chinese)
    [34] Tao X P, Wang P, Zhu B Z, 2016. Provincial green economic efficiency of China:a non-separable input-output SBM approach. Applied Energy, 171:58-66. doi:10.1016/j.apenergy. 2016.02.133
    [35] Tone K, 2004. Dealing with Undesirable Outputs in DEA:A Slacks-Based Measure (SBM) Approach. North American Productivity Workshop 2004, Toronto, 23-25 June 2004, 44-45.
    [36] Wang C J, Wang F, 2017. China can lead on climate change. Science, 357(6353):764. doi: 10.1126/science.aao2785.
    [37] Wang Qi, Huang Jinchuan, 2018. Atmospheric pollution control policies of the Tokyo metropolitan area as a reference for the Beijing-Tianjin-Hebei urban agglomeration. Progress in Geography, 37(6):790-800. (in Chinese)
    [38] Xiao Hongwei, Yi Danhui, 2014. Empirical study of carbon emissions drivers based on geographically time weighted regression model. Statistics & Information Forum, 29(2):83-89. (in Chinese)
    [39] Xing Z C, Wang J G, Zhang J, 2018. Expansion of environmental impact assessment for eco-efficiency evaluation of China's economic sectors:an economic input-output based frontier approach. Science of the Total Environment, 635:284-293. doi: 10.1016/j.scitotenv.2018.04.076
    [40] Xu B, Lin B Q, 2017. Factors affecting CO2 emissions in China's agriculture sector:evidence from geographically weighted regression model. Energy Policy, 104:404-414. doi: 10.1016/j.enpol.2017.02.011
    [41] Yan Guanghua, 2016. Geographic area and fractal study of towns spatial distribution of Shenyang metropolitan area. Scientia Geographica Sinica, 36(11):1736-1742. (in Chinese)
    [42] Yang Q, Wan X Z, Ma H M, 2015. Assessing green development efficiency of municipalities and provinces in China integrating models of super-efficiency DEA and Malmquist index. Sustainability, 7(4):4492-4510. doi: 10.3390/su7044492
    [43] Yang Qingke, Duan Xuejun, Ye Lei et al., 2014. Efficiency evaluation of city land utilization in the Yangtze River delta using a SBM-undesirable model. Resources Science, 36(4):712-721. (in Chinese)
    [44] Yang Yu, Liu Yi, 2016. Progress in China's sustainable development research:contribution of Chinese geographers. Journal of Geographical Sciences, 26(8):1176-1196. doi: 10.1007/s11442-016-1321-0
    [45] Yang Zhijiang, Wen Chaoxiang, 2017. Evaluation on China's green development efficiency and regional disparity. Economic Geography, 37(3):10-18. (in Chinese)
    [46] You Huaimo, Fang Hong, Zhai Zhuyu et al., 2017. Study on green development efficiency of Chinese photovoltaic enterprises based on DEA and Tobit regression model. Mathematics in Practice and Theory, 47(18):63-71. (in Chinese)
    [47] Zhang X L, Zhao Y, 2018. Identification of the driving factors' influences on regional energy-related carbon emissions in China based on geographical detector method. Environmental Science and Pollution Research, 25(10):9626-9635. doi: 10.1007/s11356-018-1237-6
    [48] Zhang X L, Zhao Y, Wang C J et al., 2019. Decoupling effect and sectoral attribution analysis of industrial energy-related carbon emissions in Xinjiang, China. Ecological Indicators, 97:1-9. doi: 10.1016/j.ecolind.2018.09.056
    [49] Zhu Chuangeng, Zhang Chunmin, Qiu Fangdao et al., 2017. Transformation of industrial structure and layout optimization based on low-carbon economy in Xuzhou Metropolitan Area. Economic Geography, 37(10):126-135. (in Chinese)
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Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area

doi: 10.1007/s11769-020-1114-3
    基金项目:

    Under the auspices of the National Natural Science Foundation of China (No. 41671123, 41971158, 41671122), Major Project of Philosophy and Social Science Research of Jiangsu Universities (No. 2018SJZDA010)

    通讯作者: TAN Juntao.E-mail:tanjuntaocf@163.com; LIU Jibin.E-mail:liujb034@163.com

摘要: 

This study analyzed the spatial-temporal heterogeneity of green development efficiency and its influencing factors in the growing Xuzhou Metropolitan Area for the period 2000-2015. The slacks-based measure (SBM) model, spatial autocorrelation, and the geographically weighted regression (GWR) model were used to conduct the analysis. The conclusions were as follows:first, the overall efficiency of green development of the Xuzhou Metropolitan Area decreased, the regional differences and spatial agglomeration shrunk and differences within the region were the main contributors to the regional differences of green development efficiency. Second, the counties with high-efficiency green development were distributed along the coast, and along the routes of the Beijing-Shanghai and the Eastern Longhai railways. A developing axis of the high-efficiency counties was the main feature of the spatial pattern for green development efficiency. Third, regarding spatial correlation and green development efficiency, the High-High type counties in the Xuzhou Metropolitan Area formed a centralized distribution corridor along the inter-provincial border areas of Henan and Jiangsu, whereas the Low-Low type counties were concentrated in the external, marginal parts of the metropolitan area. Fourth, the major factors (ranked in decreasing order of impact) influencing green development efficiency were innovation, government regulations, the economic development level, energy consumption, and industrial structure. These factors exerted their influence to varying extents; the influence of the same factor had different effects in different regions and obvious spatial differences were observed for the different regions.

English Abstract

QIU Fangdao, CHEN Yang, TAN Juntao, LIU Jibin, ZHENG Ziyan, ZHANG Xinlin. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area[J]. 中国地理科学, 2020, 30(2): 352-365. doi: 10.1007/s11769-020-1114-3
引用本文: QIU Fangdao, CHEN Yang, TAN Juntao, LIU Jibin, ZHENG Ziyan, ZHANG Xinlin. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area[J]. 中国地理科学, 2020, 30(2): 352-365. doi: 10.1007/s11769-020-1114-3
QIU Fangdao, CHEN Yang, TAN Juntao, LIU Jibin, ZHENG Ziyan, ZHANG Xinlin. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area[J]. Chinese Geographical Science, 2020, 30(2): 352-365. doi: 10.1007/s11769-020-1114-3
Citation: QIU Fangdao, CHEN Yang, TAN Juntao, LIU Jibin, ZHENG Ziyan, ZHANG Xinlin. Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area[J]. Chinese Geographical Science, 2020, 30(2): 352-365. doi: 10.1007/s11769-020-1114-3
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