“双碳”目标下黄河流域城市绿色发展效率测度及提升路径

摘要/Abstract

图/表 10

参考文献 31

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doi:10.12118/j.issn.1000-6060.2023.371

摘要：

研判城市绿色发展效率及其优化路径，是推进黄河流域高质量发展的关键环节，亦是践行“碳达峰、碳中和”战略目标的重要方略。利用EBM-GML模型测算2005—2020年黄河流域58个城市的绿色发展效率，依次采用HP滤波分析、时空交互方法勾勒其演化特征，并对其多元提升路径进行定量识别。结果表明：（1）研究期内黄河流域城市绿色发展效率呈增长态势，由2005年的0.509提升至2020年的0.651，相继经历“波动—提升—共生”3个阶段，区域内部非均衡性特征显著。（2）黄河流域城市绿色发展效率局部空间结构具有良好的稳健性，空间移动方向波动性较强，城际空间协作程度大于空间竞争。（3）模糊集定性比较分析（fsQCA）结果表明，存在经济驱动型、双元驱动型、资源整合型、全面提升型4条优化路径，经济发展、科技创新等因素为必要条件。

关键词: “双碳”目标, 城市绿色发展效率, 时空交互, fsQCA, 黄河流域

Abstract:

Studying and assessing the efficiency of urban green development and delineating its optimization path constitute a key aspect in promoting high-quality development within the Yellow River Basin of China. This endeavor also aligns with the important strategy of realizing the strategic goal of “carbon peak and carbon neutrality”. The EBM-GML model was used to calculate the urban green development efficiency of 58 cities in the Yellow River Basin from 2005 to 2020. The evolution characteristics of the study area were outlined through HP filter analysis and spatiotemporal interaction methods, quantitatively identifying multiple lifting paths. The results show the following facts: (1) During the study period, urban green development efficiency in the Yellow River Basin increased from 0.509 in 2005 to 0.651 in 2020, traversing three successive stages of “fluctuation-improvement-symbiosis”. Notably, the characteristics of intraregional imbalance were remarkable. (2) The local spatial structure of green development efficiency in the Yellow River Basin is robust, with a highly variable spatial movement direction. Additionally, the degree of spatial collaboration in green development efficiency among cities is greater than that of spatial competition. (3) The fsQCA result shows four optimization paths: economic-driven, dual-driven, resource integration, and comprehensive improvement. Economic development and scientific and technological innovation are indispensable prerequisites for achieving these goals.

Key words: carbon peaking and carbon neutrality goals, urban green development efficiency, spatiotemporal interaction, fsQCA, Yellow River Basin

石彩霞, 贺小荣. “双碳”目标下黄河流域城市绿色发展效率测度及提升路径[J]. 干旱区地理, 2024, 47(3): 528-538.

SHI Caixia, HE Xiaorong. Measurement and improvement path of urban green development efficiency in the Yellow River Basin under the “carbon peaking and carbon neutrality” targets[J]. Arid Land Geography, 2024, 47(3): 528-538.

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[1]	陈明华, 刘文斐, 王山, 等. 黄河流域绿色发展绩效评价、差异分解及驱动因素[J]. 中国人口·资源与环境, 2022, 32(4): 126-133.
	[Chen Minghua, Liu Wenfei, Wang Shan, et al. Performance evaluation, difference decomposition and driving factors of green development in the Yellow River Basin[J]. China Population, Resources and Environment, 2022, 32(4): 126-133.]
[2]	郭付友, 高思齐, 佟连军, 等. 黄河流域绿色发展效率的时空演变特征与影响因素[J]. 地理研究, 2022, 41(1): 167-180. doi: 10.11821/dlyj020200895
	[Guo Fuyou, Gao Siqi, Tong Lianjun, et al. Spatio-temporal evolution track and influencing factors of green development efficiency in Yellow River Basin[J]. Geographical Research, 2022, 41(1): 167-180.] doi: 10.11821/dlyj020200895
[3]	孟望生, 刘华桢, 张扬. 黄河流域七大城市群绿色发展效率测度及特征分析[J]. 干旱区地理, 2023, 46(5): 846-856.
	[Meng Wangsheng, Liu Huazhen, Zhang Yang. Measurement and characterization of green development efficiency in seven urban agglomerations in the Yellow River Basin[J]. Arid Land Geography, 2023, 46(5): 846-856.]
[4]	张娜, 郭爱君. 服务业集聚对黄河流域城市绿色经济效率的影响研究[J]. 城市问题, 2022, 321(4): 35-44, 86.
	[Zhang Na, Guo Aijun. The impact of service industry agglomeration on green economic efficiency of cities in the Yellow River Basin[J]. Urban Issues, 2022, 321(4): 35-44, 86.]
[5]	邬彩霞. 中国低碳经济发展的协同效应研究[J]. 管理世界, 2021, 37(8): 105-117.
	[Wu Caixia. Research on the synergistic effect of low-carbon economy in China[J]. Journal of Management World, 2021, 37(8): 105-117.]
[6]	鹿晨昱, 黄萍, 张彤, 等. 甘肃省绿色发展效率时空演化与驱动因素研究[J]. 干旱区地理, 2023, 46(2): 305-315.
	[Lu Chenyu, Huang Ping, Zhang Tong, et al. Spatiotemporal evolution and driving factors of the green development efficiency in Gansu Province[J]. Arid Land Geography, 2023, 46(2): 305-315.]
[7]	周丽, 夏玉辉, 陈文颖. 中国低碳发展目标及协同效益研究综述[J]. 中国人口·资源与环境, 2020, 30(7): 10-17.
	[Zhou Li, Xia Yuhui, Chen Wenying. Review of low carbon development targets and relative co-benefits in China[J]. China Population, Resources and Environment, 2020, 30(7): 10-17.]
[8]	范育鹏, 方创琳. 生态城市与人地关系[J]. 生态学报, 2022, 42(11): 4313-4323.
	[Fan Yupeng, Fang Chuanglin. Eco-city and man-land relationship[J]. Acta Ecologica Sinica, 2022, 42(11): 4313-4323.]
[9]	史晨辰, 朱小平, 王辰星, 等. 韧性城市研究综述——基于城市复杂系统视角[J]. 生态学报, 2023, 43(4): 1726-1737.
	[Shi Chenchen, Zhu Xiaoping, Wang Chenxing, et al. Review and prospect of resilient cities: From the perspective of urban complex systems[J]. Acta Ecological Sinica, 2023, 43(4): 1726-1737.]
[10]	OECD. Towards green growth: A summary for policy makers[R]. Paris: OECD, 2011.
[11]	UNEP. Green economy: Cities Investing in energy and resource efficiency[R]. Nairobi: UNEP, 2011.
[12]	北京师范大学经济与资源管理研究院, 西南财经大学发展研究院, 国家统计局中国经济景气监测中心. 2016中国绿色发展指数报告——区域比较[R]. 北京: 北京师范大学出版社, 2016.
	[Institute of Economics and Resources Management, Beijing Normal University, Institute of Development, Southwestern University of Finance and Economics, China Economic Prosperity Monitoring Center, National Bureau of Statistics. China green development index report 2016: Regional comparison[R]. Beijing: Beijing Normal University Press, 2016.]
[13]	张英浩, 陈江龙, 程钰. 环境规制对中国区域绿色经济效率的影响机理研究——基于超效率模型和空间面板计量模型实证分析[J]. 长江流域资源与环境, 2018, 27(11): 2407-2418.
	[Zhang Yinghao, Chen Jianglong, Cheng Yu. Study on the influence mechanism of environmental regulation on green efficiency in China: Empirical analysis based on super efficiency model and spatial panel metering model[J]. Resources and Environment in the Yangtze Basin, 2018, 27(11): 2407-2418.]
[14]	郗永勤, 吉星. 我国工业行业碳排放效率实证研究——考虑非期望产出SBM超效率模型与DEA视窗方法的应用[J]. 科技管理研究, 2019, 39(17): 53-62.
	[Xi Yongqin, Ji Xing. An empirical study on carbon emission efficiency of industrial industry in China: Considering the super efficiency model of unexpected output SBM and the application of DEA window method[J]. Science and Technology Management Research, 2019, 39(17): 53-62.]
[15]	童昀, 刘海猛, 马勇, 等. 中国旅游经济对城市绿色发展的影响及空间溢出效应[J]. 地理学报, 2021, 76(10): 2504-2521. doi: 10.11821/dlxb202110012
	[Tong Yun, Liu Haimeng, Ma Yong, et al. The influence and spatial spillover effects of tourism economy on urban green development in China[J]. Acta Geographica Sinica, 2021, 76(10): 2504-2521.] doi: 10.11821/dlxb202110012
[16]	Cheng C Y, Ge C Z. Green development assessment for countries along the Belt and Road[J]. Journal of Environmental Management, 2020, 263: 110344, doi: 10.1016/j.jenvman.2020.110344.
[17]	Liu K D, Dong S S, Wen T Z, et al. How has the efficiency of China's green development evolved? An improved non-radial directional distance function measurement[J]. Science of the Total Environment, 2022, 815: 152337, doi: 10.1016/j.scitotenv.2021.152337.
[18]	Yang Y, Huang P P. Has the level of green development in the northwestern provinces of China truly improved? A case study of Shaanxi[J]. Sustainable Cities and Society, 2019, 51(4): 101779, doi: 10.1016/j.scs.2019.101779.
[19]	张军民, 荣城, 马玉香. 新疆城镇化绿色发展时空分异及驱动因子探究[J]. 干旱区地理, 2022, 45(1): 251-262.
	[Zhang Junmin, Rong Cheng, Ma Yuxiang. Spatial and temporal differences and driving factors of the green development of urbanization in Xinjiang[J]. Arid Land Geography, 2022, 45(1): 251-262.]
[20]	窦睿音, 焦贝贝, 张文洁, 等. 西部资源型城市绿色发展效率时空分异与驱动力[J]. 自然资源学报, 2023, 38(1): 238-254. doi: 10.31497/zrzyxb.20230115
	[Dou Ruiyin, Jiao Beibei, Zhang Wenjie, et al. Research on spatiotemporal heterogeneity and driving forces of green development efficiency in resource-based cities in western China[J]. Journal of Natural Resources, 2023, 38(1): 238-254.] doi: 10.31497/zrzyxb.20230115
[21]	赵伟, 黄兰, 李威, 等. 中国乡村包容性绿色发展水平分异及其驱动因素[J]. 经济地理, 2023, 43(3): 68-77. doi: 10.15957/j.cnki.jjdl.2023.03.008
	[Zhao Wei, Huang Lan, Li Wei, et al. The level differentiation driving factors of inclusive green development in rural areas of China[J]. Economic Geography, 2023, 43(3): 68-77.]
[22]	张凯莉, 冯荣荣, 刘潭, 等. 黄河流域城市化与生态系统服务价值协调性及障碍因素研究[J]. 干旱区地理, 2022, 45(4): 1254-1267.
	[Zhang Kaili, Feng Rongrong, Liu Tan, et al. Coordination and obstacle factors of urbanization and ecosystem service value in the Yellow River Basin[J]. Arid Land Geography, 2022, 45(4): 1254-1267.]
[23]	徐小鹰, 田焮焮. 长三角城市群绿色发展水平的时空演变及趋势预测[J]. 长江流域资源与环境, 2022, 31(12): 2568-2581.
	[Xu Xiaoying, Tian Xinxin. Spatial-temporal evolution and trend prediction of green development level of Yangtze River Delta urban agglomerations[J]. Resources and Environment in Yangtze Basin, 2022, 31(12): 2568-2581.]
[24]	孙金欣, 韩美, 孔祥伦, 等. 黄河下游自然保护地时空分布特征与高质量发展建议——以山东省为例[J]. 水土保持研究, 2023, 30(3): 395-402, 412.
	[Sun Jinxin, Han Mei, Kong Xianglun, et al. Spatio-temporal characteristics and suggestions for high-quality development of nature protected areas in the lower reaches of the Yellow River: A case study of Shandong Province[J]. Research of Soil and Water Conservation, 2023, 30(3): 395-402, 412.]
[25]	师博. 黄河流域中心城市高质量发展路径研究[J]. 人文杂志, 2020, 285(1): 5-9.
	[Shi Bo. Research on high-quality development path of central cities in the Yellow River Basin[J]. Chinese Journal of Humanities, 2020, 285(1): 5-9.]
[26]	Chen J D, Gao M, Chen S L, et al. County-level CO₂ emissions and sequestration in China during 1997—2017[J]. Scientific Data, 2020, 7(1): 1-12. doi: 10.1038/s41597-019-0340-y
[27]	丁玉龙. 城市规模对绿色经济效率的影响及空间效应研究——基于我国285个地级及以上城市数据的实证分析[J]. 城市问题, 2021, 317(12): 58-68.
	[Ding Yulong. Study on the influence of city scale on the efficiency of green economy and its spatial effect: Empirical evidence form 285 prefecture-level and above cities in China[J]. Urban Issues, 2021, 317(12): 58-68.]
[28]	李治国, 王杰, 王叶薇. 经济集聚扩大绿色经济效率差距了吗?——来自黄河流域城市群的经验证据[J]. 产业经济研究, 2022, 116(1): 29-42.
	[Li Zhiguo, Wang Jie, Wang Yewei. Does economic agglomeration widen the efficiency gap in green economic efficiency? Evidence from urban agglomerations in the Yellow River Basin[J]. Journal of Industrial Economics, 2022, 116(1): 29-42.]
[29]	彭坤杰, 许春晓, 贺小荣. 长三角地区城市人居环境韧性水平演化特征[J]. 经济地理, 2023, 43(6): 74-84. doi: 10.15957/j.cnki.jjdl.2023.06.008
	[Peng Kunjie, Xu Chunxiao, He Xiaorong. Spatiotemporal evolution characteristics of urban human settlement resilience in Yangtze River Delta[J]. Economic Geography, 2023, 43(6): 74-84.] doi: 10.15957/j.cnki.jjdl.2023.06.008
[30]	王峥, 程占红. “双碳”目标下中国服务业碳强度时空交互特征及跃迁机制[J]. 地理学报, 2023, 78(1): 54-70. doi: 10.11821/dlxb202301004
	[Wang Zheng, Cheng Zhanhong. Spatiotemporal interaction characteristics and transition mechanism of carbon intensity in China's service industry under the targets of carbon peak and carbon neutrality[J]. Acta Geographica Sinica, 2023, 78(1): 54-70.] doi: 10.11821/dlxb202301004
[31]	吴成颂, 昂昊. 中国绿色金融效率时空分异及其提升路径[J]. 资源科学, 2022, 44(12): 2456-2469. doi: 10.18402/resci.2022.12.06
	[Wu Chengsong, Ang Hao. Spatiotemporal variations in the efficiency of green finance in China and its enhancement paths[J]. Resources Science, 2022, 44(12): 2456-2469.] doi: 10.18402/resci.2022.12.06

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系统层	要素层	指标层	单位	属性
投入	劳动	全市年末单位从业人数	10⁴人	+
	劳动	规模以上工业企业数	个	+
	资本	科学技术支出	10⁴元	+
		全社会固定资产投资	10⁴元	+
		城市建设用地面积	km²	+
	能源	供气总量	10⁴ t	+
		供水总量	m³	+
		用电总量	10⁴ kW·h	+
产出	期望产出	人均绿地面积	m²	+
		人均社会消费零售额	元	+
		绿色专利申请数量	件	+
	非期望产出	工业废水排放量	10⁴ t	-
		工业SO₂排放量	t	-
		工业固体废弃物排放量	t	-
		城市CO₂排放量	t	-

变量	“十一五”时期模糊校准点			“十二五”时期模糊校准点			“十三五”时期模糊校准点
变量	完全隶属	交叉点	完全不隶属	完全隶属	交叉点	完全不隶属	完全隶属	交叉点	完全不隶属
城市绿色发展效率（GTFP）	0.537	0.404	0.301	0.757	0.538	0.364	1.002	0.645	0.459
经济发展（ECO）	3.122	1.887	1.222	5.648	3.934	2.644	7.398	5.233	3.668
城镇化水平（URB）	0.569	0.442	0.371	0.627	0.491	0.421	0.692	0.558	0.494
产业结构（IND）	0.601	0.496	0.417	0.570	0.486	0.419	0.496	0.417	0.344
外商投资（EDI）	0.350	0.120	0.030	1.195	0.440	0.170	2.930	1.370	0.390
科技创新（INO）	3.064	1.003	0.322	6.805	2.650	0.548	7.801	2.244	0.559
环境规制（ENV）	0.970	0.871	0.660	0.984	0.916	0.733	0.944	0.829	0.593

变量	“十一五”时期		“十二五”时期		“十三五”时期
变量	一致性	覆盖度	一致性	覆盖度	一致性	覆盖度
经济发展（ECO）	0.624	0.617	0.776	0.713	0.633	0.618
~经济发展（ECO）	0.466	0.457	0.295	0.605	0.469	0.447
城镇化水平（URB）	0.579	0.605	0.780	0.718	0.619	0.621
~城镇化水平（URB）	0.505	0.470	0.305	0.623	0.498	0.463
产业结构（IND）	0.436	0.614	0.296	0.687	0.558	0.542
~产业结构（IND）	0.622	0.471	0.758	0.663	0.558	0.533
外商投资（EDI）	0.887	0.495	0.846	0.748	0.654	0.648
~外商投资（EDI）	0.031	0.887	0.208	0.467	0.460	0.434
科技创新（INO）	0.636	0.664	0.562	0.736	0.592	0.577
~科技创新（INO）	0.457	0.427	0.513	0.631	0.526	0.502
环境规制（ENV）	0.594	0.586	0.415	0.723	0.559	0.521
~环境规制（ENV）	0.488	0.480	0.669	0.667	0.547	0.548

变量	“十一五”时期			“十二五”时期				“十三五”时期
变量	组态A₁	组态A₂		组态B₁	组态B₂	组态B₃	组态B₄	组态C₁	组态C₂
经济发展（ECO）	●	●		●	●	●	●	●	●
城镇化水平（URB）	⊗	●		⊗	●	●	-	⊗	●
产业结构（IND）	●	⊗		●	●	⊗	⊗	●	●
外商投资（EDI）	⊗	-		-	⊗	⊗	●	⊗	●
科技创新（INO）	●	●		●	●	●	●	●	●
环境规制（ENV）	⊗	●		●	●	-	⊗	●	●
一致性	0.877	0.884		0.849	0.898	0.913	0.926	0.832	0.902
原始覆盖度	0.140	0.112		0.469	0.114	0.076	0.145	0.114	0.094
唯一覆盖度	0.048	0.019		0.042	0.005	0.005	0.079	0.175	0.155
总体一致性	0.867		0.826					0.874
总体覆盖度	0.459		0.484					0.457