自然资源学报 ›› 2021, Vol. 36 ›› Issue (1): 223-239.doi: 10.31497/zrzyxb.20210115

• 资源分配与效率 • 上一篇    下一篇

黄河流域资源型城市生态效率时空演变及驱动因素

阎晓1,2(), 涂建军3()   

  1. 1.山西财经大学资源型经济转型协同创新中心,太原 030006
    2.山西财经大学资源型经济转型发展研究院,太原 030006
    3.西南大学经济管理学院,重庆 400700
  • 收稿日期:2020-05-18 修回日期:2020-07-17 出版日期:2021-01-28 发布日期:2021-03-28
  • 通讯作者: 涂建军 E-mail:yanxiao85China@163.com;654532972@qq.com
  • 作者简介:阎晓(1985- ),女,山西大同人,博士,副教授,研究方向为产业生态、生态经济与区域可持续发展。E-mail:yanxiao85China@163.com
  • 基金资助:
    国家自然科学基金项目(41701630);国家社会科学基金西部项目(16XSH001);山西省高等学校哲学社会科学研究项目(2017246)

The spatio-temporal evolution and driving factors of eco-efficiency of resource-based cities in the Yellow River Basin

YAN Xiao1,2(), TU Jian-jun3()   

  1. 1. Cooperative Innovation Center for Transition of Resource-based Economics, Shanxi University of Finance & Economics, Taiyuan 030006, China
    2. Research Institute of Transition of Resource-based Economics, Shanxi University of Finance & Economics, Taiyuan 030006, China
    3. College of Economics and Management, Southwest University, Chongqing 400700, China
  • Received:2020-05-18 Revised:2020-07-17 Online:2021-01-28 Published:2021-03-28
  • Contact: TU Jian-jun E-mail:yanxiao85China@163.com;654532972@qq.com

摘要:

生态效率是区域发展质量和人地协调程度的综合体现。采用TOPSIS法测度2003—2017年黄河流域37个资源型城市的生态效率,借助泰尔指数、全局空间自相关和热点分析揭示其时空演变规律,利用面板Tobit回归模型探寻关键驱动因素。结果表明:(1)黄河流域资源型城市生态效率总体上以2007年为分水岭,先平稳、后上升;不同城市生态效率的增速和增幅差异较大,下游城市明显高于中、上游城市,再生型城市明显高于成长、成熟和衰退型城市。 (2)城市间生态效率差异大小先略微下降、后持续上升;生态效率空间格局由随机分布向集聚分布演变,低值集聚区从山西、河南交界处向山西中、北部移动,高值集聚区分布具有空间粘性,一直位于下游山东境内。(3)产业转型、科技创新、基础设施完善和区位条件对生态效率改善具有显著正向驱动作用,外向型经济、资源依赖和环境规制抑制生态效率提高,城镇化、工业化和外资利用对生态效率演变的影响不显著;不同类型资源型城市生态效率改善的主要驱动因素存在异质性。

关键词: 黄河流域, 资源型城市, 生态效率, 时空演变, 驱动因素

Abstract:

Eco-efficiency is the comprehensive embodiment of regional development quality, and the synthetic reflection of coordination degree between socio-economic system and environmental system. Taking the Yellow River Basin as the research area, this study explored the spatio-temporal evolution and driving forces of eco-efficiency of resource-based cities. At first, eco-efficiencies of 37 resource-based cities from 2003 to 2017 were evaluated, using the TOPSIS method. Then, the spatio-temporal changing trends were revealed through the Theil index, the Global Spatial Autocorrelation analysis and the Hotspot analysis. At last, the key driving factors of eco-efficiency change were explored by the Panel Tobit Regression model. The results showed that: (1) On the whole, the eco-efficiency of resource-based cities in the Yellow River Basin stabilized first and then increased during 2003 and 2017, with 2007 as the turning point. However, the quantity and rate of eco-efficiency growth varied considerably among resource-based cities. The two indexes of downstream cities were significantly higher than those of middle and upstream cities, and these two indexes of regenerative cities were significantly higher than those of growing cities, grow-up cities and recessionary cities. (2) The eco-efficiency gap between resource-based cities decreased slightly at first and then increased continuously during 2003 and 2017. Meanwhile, the eco-efficiency spatial distribution pattern of resource-based cities evolved from random state to aggregate state. Specifically, the low-value agglomeration areas were distributed at the junction of Shanxi and Henan provinces at first, and then moved upstream to the central and northern parts of Shanxi province. The high-value agglomeration areas, however, remained consistently in Shandong province, which is located in the lower reaches of the Yellow River. (3) In general, industrial transformation, scientific and technological innovation, infrastructure improvement and location conditions had significant positive effects on the improvement of eco-efficiency in the study area. However, export-oriented economy, resource dependence and environmental regulation had significant inhibitory effects, and urbanization, industrialization and foreign capital utilization had no significant impact. It is worth noting that the driving factors of eco-efficiency were heterogeneous across different types of resource-based cities, which means that different resource-based cites should take different measures to improve their eco-efficiencies.

Key words: Yellow River Basin, resource-based cities, eco-efficiency, spatio-temporal evolution, driving factors