黄河流域环境治理绩效的空间关联网络及影响因素分析

Analysis of Spatial Correlation Network and Influencing Factors of Environment Governance Performance in the Yellow River Basin

黄河流域作为我国重要的生态安全屏障,探索其环境治理绩效的空间关联网络特征及影响因素,有利于推进黄河流域生态保护和高质量发展。本文基于2006−2021年黄河流域60个地级及以上城市的面板数据,在构建超效率SBM模型(Slacks-Based Measurement,SBM)测度黄河流域环境治理绩效的基础上,利用修正的引力模型和社会网络分析法探讨了环境治理绩效的空间关联网络特征及其影响因素。结果表明:①2006−2021年黄河流域环境治理绩效呈波动式上升趋势,且流域上游、中游和下游的环境治理绩效平均值都小于1,环境治理绩效整体偏低。②黄河流域各城市间环境治理绩效的网络密度较低,网络结构相对稳定,关联效率较高,不存在等级森严的网络结构,且济南市、青岛市等城市在网络中处于核心位置,巴彦淖尔市、白银市等城市处于边缘位置。③郑州市、淄博市等中下游城市对板块内外均产生溢出效应,临汾市、西宁市等中上游城市是关联网络的“发动机”,青岛市、济南市等区域核心城市成为关联网络中的受益方,西安市、兰州市等位于黄河“几”字弯都市圈的城市担任了桥梁作用。④地理空间邻近、经济发展差异及产业结构差异对黄河流域环境治理绩效空间关联网络产生正向影响,环境规制差异、科技创新差异、对外开放差异及政府调控差异的影响效果呈现阶段性变化的特征。研究显示,黄河流域环境治理绩效存在显著的空间关联和溢出效应,但空间关联程度较低,需不断提升空间关联网络的紧密程度,推动黄河流域区域间环境的协同治理与平衡发展。

The Yellow River Basin is an important ecological security barrier in China.Exploring the spatial correlation network characteristics and influencing factors of its environmental governance performance will help promote ecological protection and highquality development in the Yellow River Basin.Based on the panel data of 60 prefecture level and above cities in the Yellow River Basin from 2006 to 2021,a slack-based measurement(SBM)model is constructed to measure the performance of environment governance in the Yellow River Basin.Furthermore,the modified gravity model and social network analysis method are used to explore the spatial correlation network characteristics and influencing factors of environment governance performance.The results show that:(1)During the research period,the environmental governance performance of the Yellow River Basin shows a fluctuating upward trend,and the average environmental governance performance in the upstream,midstream,and downstream of the basin is less than 1.The overall environmental governance performance is low,indicating that the Yellow River Basin has not yet achieved efficient environmental governance.(2)The network density of environment governance performance among cities in the Yellow River Basin is relatively low,the network structure is relatively stable,and the correlation efficiency is high.There is no hierarchical network structure,and cities such as Jinan and Qingdao are in the central position of the network,while cities such as Bayannur and Baiyin are on the periphery of the network.(3)The middle and lower reaches cities such as Zhengzhou and Zibo have produced spillover effects on both inside and outside the sector.The upper and middle reaches cities such as Linfen and Xining are the‘engines’of the related network,while regional central cities such as Qingdao and Jinan have become beneficiaries of the network.Cities located in the Yellow River´s‘Ji’shaped metropolitan area,such as Xi´an and Lanzhou,serve as bridges.(4)Geographical proximity,economic development difference,and industrial structure difference have a positive impact on the spatial correlation network of environmental governance performance in the Yellow River Basin.The impact effects of environmental regulation difference,technological innovation difference,opening up difference,and government regulation difference show phased changes.The research shows that there are significant spatial correlations and spillover effects in the environmental governance performance of the Yellow River Basin,but the degree of spatial correlation is relatively low.It is necessary to continuously enhance the closeness of the spatial correlation network in order to promote coordinated environmental governance and balanced development among regions in the Yellow River Basin.