浏览全部资源
扫码关注微信
黄河流域城市群生态效率评价及归因分析
Ecological efficiency evaluation and attribution analysis of urban agglomerations in the Yellow River Basin
- 西北大学学报（自然科学版） 2024年54卷第3期 页码：513-526
- 作者机构：
西北大学 城市与环境学院，陕西 西安 710127
- 作者简介：
刘虹，女，从事区域可持续发展研究，liuhong5rainbow@163.com。
雷敏，女，副教授，从事福祉地理研究，xdleimin@126.com。
- 基金信息：国家自然科学基金(42171197)
DOI：10.16152/j.cnki.xdxbzr.2024-03-015
中图分类号： F124.5纸质出版日期：2024-06-25，
收稿日期：2023-11-30，
扫 描 看 全 文
刘虹, 雷敏, 杨晨, 等. 黄河流域城市群生态效率评价及归因分析[J]. 西北大学学报（自然科学版）, 2024,54(3):513-526.
LIU Hong, LEI Min, YANG Chen, et al. Ecological efficiency evaluation and attribution analysis of urban agglomerations in the Yellow River Basin[J]. Journal of Northwest University (Natural Science Edition), 2024,54(3):513-526.
刘虹, 雷敏, 杨晨, 等. 黄河流域城市群生态效率评价及归因分析[J]. 西北大学学报（自然科学版）, 2024,54(3):513-526. DOI： 10.16152/j.cnki.xdxbzr.2024-03-015.
LIU Hong, LEI Min, YANG Chen, et al. Ecological efficiency evaluation and attribution analysis of urban agglomerations in the Yellow River Basin[J]. Journal of Northwest University (Natural Science Edition), 2024,54(3):513-526. DOI： 10.16152/j.cnki.xdxbzr.2024-03-015.
摘要
黄河流域城市群是黄河流域生态保护和高质量发展的重要载体，提高黄河流域城市群生态效率有利于提升其绿色经济发展水平。基于城市群视角，利用超效率SBM模型测度黄河流域七大城市群60个城市2006—2020年的生态效率值，借助Dagum基尼指数进行区域差异性分析，进一步通过面板分位数模型识别影响城市群生态效率的主要因素。结果表明：①黄河流域地区及各城市群生态效率明显改善，呼包鄂榆城市群和宁夏沿黄城市群生态效率水平最高，而中原城市群和兰西城市群生态效率水平最低；②黄河流域生态效率空间分布格局由“低值区抱团分布、高值区离散分布”转变为高值区和低值区“小集聚、大分散”的交叉分布格局；③七大城市群总体差异缩小，组间差异和超变密度是总体差异的主要来源；④产业结构、人口密度、对外开放水平制约了城市群生态效率的发展，而经济发展水平、技术进步与生态效率呈正相关关系。
Abstract
The urban agglomerations in the Yellow River Basin play a crucial role in preserving the environment and fostering high-quality development in this area. Improving the eco-efficiency of these urban agglomerations has the potential to boost their green economic growth. We approached this from the perspective of urban agglomerations and used the super-SBM model to assess the ecological efficiency of 60 cities across seven urban agglomerations in the Yellow River Basin from 2006 to 2020. Afterward
we analyzed regional differences using the Dagum Gini index and identified the key factors affecting the ecological efficiency of urban agglomerations through the panel quantile model.The results are as follows: ① Eco-efficiency has significantly improved throughout the Yellow River Basin
including all urban agglomerations. The Hu-bao-Eyu urban agglomeration and the Ningxia urban agglomeration along the Yellow River exhibited the highest eco-efficiency levels
while the Central Plains urban agglomeration and the Lanxi urban agglomeration showed the lowest eco-efficiency levels. ② The spatial distribution of eco-efficiency in the Yellow River Basin has shifted from a " clustered distribution in low-value areas
discrete distribution in high-value areas" to a " cross-distribution pattern with small clusters and large dispersion of high-value areas and low-value areas". ③ Overall disparities among the seven major urban agglomerations have decreased. The primary contributors to these differences are disparities between groups and Hypervariable density. ④ Industrial structure
population density
and openness levels constrain the ecological efficiency of urban agglomerations. In contrast
economic development levels and technological progress are positively correlated with ecological efficiency.
关键词
生态效率超效率SBM模型Dagum基尼指数面板分位数回归黄河流域
Keywords
ecological efficiencysuper-SBM modelDagum Gini indexpanel quantile regressionYellow River Basin
references
陈明华, 王山, 刘文斐. 黄河流域生态效率及其提升路径：基于100个城市的实证研究[J]. 中国人口科学, 2020(4): 46-58.
CHEN M H, WANG S, LIU W F. Ecological efficiency and its improvement path in the Yellow River Basin: An empirical study based on 100 cities[J]. Chinese Population Science, 2020(4): 46-58.
习近平. 在黄河流域生态保护和高质量发展座谈会上的讲话[J]. 中国水利, 2019(20): 1-3.
XI J P. Speech at the symposium on ecological protection and high-quality development in the Yellow River Basin[J]. China Water Resources, 2019(20): 1-3.
HUPPES G, ISHIKAWA M. A framework for quantified eco-efficiency analysis[J]. Journal of Industrial Ecology, 2005, 9(4): 25-41.
DAI Z M, GUO L, JIANG Z Y. Study on the industrial eco-efficiency in east China based on the super efficiency DEA model: An example of the 2003—2013 panel data[J]. Applied Economics, 2016, 48(59): 5779-5785.
SCHALTEGGER S, STURM A. Ökologische rationalität[J]. Die Unternehmung, 1990, 44(4): 273-290.
WBCFS . Eco-efficiency leadership for improved economic and environmental performance[M].Genva: WBCFS, 1992: 3-16.
HIROSE K, MISHIMA N. Eco-efficiency evaluation of modular design smartphones[J]. Procedia CIRP, 2019, 84: 1054-1058.
张展, 廖小平, 李春华, 等. 湖南省县域农业生态效率的时空特征及其影响因素[J]. 经济地理, 2022, 42(2): 181-189.
ZHANG Z, LIAO X P, LI C H, et al. Spatial and temporal characteristics and influencing factors of county agricultural eco-efficiency in Hunan Province[J]. Economic Geography, 2022, 42(2): 181-189.
RASHIDI K, SHABANI A, FARZIPOOR SAEN R. Using data envelopment analysis for estimating energy saving and undesirable output abatement: A case study in the Organization for Economic Co-Operation and Development (OECD) countries[J]. Journal of Cleaner Production, 2015, 105(15): 241-252.
李丽平, 田春秀, 国冬梅. 生态效率：OECD全新环境管理经验[J]. 环境科学动态, 2000, 25(1): 33-36.
LI L P, TIAN C X, GUO D M. Eco-efficiency: The OECD’s new experience in environmental management[J]. Journal of Environmental Science, 2000, 25(1): 33-36.
诸大建, 朱远. 生态效率与循环经济[J]. 复旦学报(社会科学版), 2005, 47(2): 60-66.
ZHU D J, ZHU Y. Eco-efficiency and circular economy[J]. Journal of Fudan University (Social Science Edition), 2005, 47(2): 60-66.
戴铁军, 陆钟武. 钢铁企业生态效率分析[J]. 东北大学学报, 2005, 26(12): 1168-1173.
DAI T J, LU Z W. Ecological efficiency analysis of iron and steel enterprises[J]. Journal of Northeastern University, 2005, 26(12): 1168-1173.
杨斌.2000—2006年中国区域生态效率研究：基于DEA方法的实证分析[J]. 经济地理, 2009, 29(7): 1197-1202.
YANG B. Study on regional eco-efficiency in China from 2000 to 2006: Empirical analysis based on DEA method[J]. Economic Geography, 2009, 29(7): 1197-1202.
KUOSMANEN T, KORTELAINEN M. Measuring eco-efficiency of production with data envelopment analysis[J]. Journal of Industrial Ecology, 2005, 9(4): 59-72.
韩瑞玲, 佟连军, 宋亚楠. 基于生态效率的辽宁省循环经济分析[J]. 生态学报, 2011, 31(16): 4732-4740.
HAN R L, TONG L J, SONG Y N. Analysis of circular economy in Liaoning Province based on eco-efficiency[J]. Acta Ecologica Sinica, 2011, 31(16): 4732-4740.
肖黎明, 张仙鹏. 强可持续理念下绿色创新效率与生态福利绩效耦合协调的时空特征[J]. 自然资源学报, 2019, 34(2): 312-324.
XIAO L M, ZHANG X P. Spatio-temporal characteristics of coupling coordination between green innovation efficiency and ecological welfare performance under the concept of strong sustainability[J]. Journal of Natural Resources, 2019, 34(2): 312-324.
YAMASAKI J, ITSUBO N, MURAYAMA A, et al. Eco-efficiency assessment of 42 countries’ administrative divisions based on environmental impact and gross regional product[J]. City and Environment Interactions, 2021, 10: 100061.
孙丛婷, 傅莉媛, 蒋犇, 等. 中国生态效率时空动态分布与区域差异[J]. 生态学报, 2023, 43(4): 1366-1379.
SUN C T, FU L Y, JIANG B, et al. Spatio-temporal dynamic distribution and regional differences of eco-efficiency in China[J]. Acta Ecologica Sinica, 2023, 43(4): 1366-1379.
YAO T T, HUANG Z L, ZHAO W. Are smart cities more ecologically efficient? Evidence from China[J]. Sustainable Cities and Society, 2020, 60: 102008.
沈伟腾, 胡求光, 李加林, 等. 中国区域生态效率的时空演变及空间互动特征[J] 自然资源学报, 2020, 35(9): 2149-2162.
SHEN W T, HU Q G, LI J L, et al. Spatio-temporal evolution and spatial interaction characteristics of regional eco-efficiency in China[J] Journal of Natural Resources, 2020, 35(9): 2149-2162.
田鹏, 汪浩瀚, 李加林, 等. 东海海岸带县域城市生态效率评价及影响因素[J] 地理研究, 2021, 40(8): 2347-2366.
TIAN P, WANG H H, LI J L, et al. Ecological efficiency evaluation and influencing factors of county cities in the East China Sea coastal zone[J]. Geographical Research, 2021, 40(8): 2347-2366.
阎晓, 涂建军. 黄河流域资源型城市生态效率时空演变及驱动因素[J] 自然资源学报, 2021, 36(1): 223-239.
YAN X, TU J J. Spatio-temporal evolution and driving factors of eco-efficiency of resource-based cities in the Yellow River Basin[J]. Journal of Natural Resources, 2021, 36(1): 223-239.
徐维祥, 郑金辉, 王睿, 等. 黄河流域城市生态效率演化特征及门槛效应[J]. 地理科学, 2022, 42(1): 74-82.
XU W X, ZHENG J H, WANG R, et al. Evolution characteristics and threshold effect of urban eco-efficiency in the Yellow River basin[J]. Scientia Geographica Sinica, 2022, 42(1): 74-82.
李露, 徐维祥, 郑金辉. 黄河流域城镇化进程与生态效率的空间交互效应研究[J]. 经济经纬, 2022, 39(5): 25-34.
LI L, XU W X, ZHENG J H. Spatial interaction between urbanization process and eco-efficiency in the Yellow River basin[J]. Economic Journal, 2022, 39(5): 25-34.
杨燕燕, 王永瑜, 韩君. 新发展理念下黄河流域生态效率测度及空间异质性研究[J]. 统计与决策, 2021, 37(24): 110-114.
YANG Y Y, WANG Y Y, HAN J. Ecological efficiency measurement and spatial heterogeneity in the Yellow River Basin under the new development concept[J]. Journal of Statistics and Decision Making, 2021, 37(24): 110-114.
李贝歌, 胡志强, 苗长虹, 等. 黄河流域工业生态效率空间分异特征与影响因素[J]. 地理研究, 2021, 40(8): 2156-2169.
LI B G, HU Z Q, MIAO C H, et al. Spatial differentiation characteristics and influencing factors of industrial eco-efficiency in the Yellow River Basin[J]. Geographical Research, 2021, 40(8): 2156-2169.
TONE K. A slacks-based measure of super-efficiency in data envelopment analysis[J]. European Journal of Operational Research, 2002, 143(1): 32-41.
DAGUM C. A new approach to the decomposition of the Gini income inequality ratio[J]. Empirical Economics, 1997, 22(4): 515-531.
KOENKER R, BASSETT G W. Regression quantiles[J]. Econometrica, 1978, 46(1): 33-50.
KOENKER R. Quantile regression for longitudinal data[J]. Journal of Multivariate Analysis, 2004, 91(1): 74-89.
吴健生, 牛妍, 彭建, 等. 基于DMSP/OLS夜间灯光数据的1995—2009年中国地级市能源消费动态[J]. 地理研究, 2014, 33(4): 625-634.
WU J S, NIU Y, PENG J, et al. Energy consumption dynamics of Chinese prefecty-level cities from 1995 to 2009 based on DMSP/OLS nighttime light data[J]. Geographical Research, 2014, 33(4): 625-634.
张军, 吴桂英, 张吉鹏. 中国省际物质资本存量估算：1952—2000[J]. 经济研究, 2004, 39(10): 35-44.
ZHANG J, WU G Y, ZHANG J P. Estimation of inter-provincial physical capital stock in China: 1952—2000[J]. Economic Research Journal, 2004, 39(10): 35-44.
任晓松, 刘宇佳, 赵国浩. 经济集聚对碳排放强度的影响及传导机制[J]. 中国人口·资源与环境, 2020, 30(4): 95-106.
REN X S, LIU Y J, ZHAO G H. Influence of economic agglomeration on carbon emission intensity and its transmission mechanism[J]. China Population, Resources and Environment, 2020, 30(4): 95-106.
任力, 朱东波. 中国金融发展是绿色的吗：兼论中国环境库兹涅茨曲线假说[J]. 经济学动态, 2017(11): 58-73.
REN L, ZHU D B. Is China’s financial development green? Also on China’s environmental Kuznets curve hypothesis[J]. Journal of Economic Dynamics, 2017(11): 58-73.
文琦, 侯凯元, 郑殿元, 等. 成长型资源城市产业转型能力评价与优化路径：以榆林市为例[J]. 地理科学, 2022, 42(4): 682-691.
WEN Q, HOU K Y, ZHENG D Y, et al. Evaluation and optimization path of industrial transformation ability of growth resource cities: A case study of Yulin City[J]. Scientia Geographica Sinica, 2022, 42(4): 682-691.
周力, 李静. 外商直接投资与PM2.5空气污染：基于中国数据的“污染避难所”假说再检验[J]. 国际经贸探索, 2015, 31(12): 98-111.
ZHOU L, LI J. Foreign direct investment and PM2.5 air pollution: Retesting the ”pollution sanctuary” hypothesis based on Chinese data[J]. International Economic and Trade Exploration, 2015, 31(12): 98-111.
邱兆林. 长江经济带与黄河流域生态效率差异及影响因素分析[J]. 当代经济管理, 2022, 44(6): 39-49.
QIU Z L. Differences and influencing factors of eco-efficiency between Yangtze River Economic Belt and Yellow River Basin[J]. Contemporary Economic Management, 2022, 44(6): 39-49.
王少剑, 谢紫寒, 王泽宏. 中国县域碳排放的时空演变及影响因素[J]. 地理学报, 2021, 76(12): 3103-3118.
WANG S J, XIE Z H, WANG Z H. Spatio-temporal evolution and influencing factors of county carbon emissions in China[J]. Acta Geographica Sinica, 2021, 76(12): 3103-3118.
0
浏览量
0
下载量
0
CSCD
- 网络PDF下载
- Meta-XML下载
- BibTeX下载
- Endnote下载
- RefMan 下载
- NoteExpress下载
- NoteFirst下载
关联资源
相关文章
相关作者
相关机构
- 地址：陕西省西安市太白北路229号
- 联系电话：029-88302822 Email：xdxbzr@nwu.edu.cn
- 技术支持由北京北大方正电子有限公司提供 陕ICP备05010980号-4
京公网安备11010802024621 - 本系统建议在Chrome、 IE9+ 以上版本浏览器阅读本站内容，360浏览器请切换至极速模式
- Cookies帮助我们提供服务并提供个性化体验。使用本网站，即表示您同意我们使用Cookies