School of Economics and Management, Taiyuan University of Technology, Taiyuan 030024, Shanxi province, China.
J Environ Manage. 2024 Mar;354:120387. doi: 10.1016/j.jenvman.2024.120387. Epub 2024 Feb 22.
The environmental pollution and social well-being issue caused by the huge energy consumption in cities reflect the urgency of improving urban energy performance from multiple dimensions of economy, environment, and well-being. As a result, various countries and cities have promulgated a series of policies. However, the complexity of the policies makes the categories and utilities need to be further clarified, and the diseconomy caused by the lag of policy effect evaluation makes the focus of policy implementation need to be clear in advance. Therefore, based on public choice theory, this research follows the idea of "prior analysis" and takes Chinese cities as the research object. Firstly, the collected energy performance improvement policies of Chinese cities were analyzed and classified by the content analysis method, and the main utilities of all policies and the specific utilities of each category were summarized. Based on the multiple dimensions of urban energy performance research (namely, economy, environment and well-being dimensions), this research summarized the policy utilities that help to improve the urban energy performance of each dimension, and also preset the policy utility values. Secondly, the effect prediction model for urban energy performance improvement policies in each dimension was constructed by Back-propagation (BP) neural network. Thirdly, the energy performance of Chinese cities in 2020 measured by Data Envelopment Analysis method was taken as the benchmark value, and the energy performance of Chinese cities in 2025 measured by the policy effect prediction model was taken as the comparison value. According to the results of performance improvement, the energy performance improvement policies of Chinese cities were selected respectively from the dimensions of economy, environment and well-being. This research shows that: the energy performance improvement policies of Chinese cities mainly include six categories, namely energy conservation and emission reduction policies, energy development policies, ecological environmental policies, fiscal and tax policies, industrial policies and economic and social policies. It is needed to focus on ecological environmental policies, fiscal and tax policies and industrial policies to improve urban energy performance from the economic dimension. For the environmental dimension, the key and priority policies are ecological environmental policies. Compared with the economic dimension, the focus of implementing policies adds economic and social policies in the well-being dimension. In the implementation of policies, the differences of energy performance among cities can be reduced through multi-feature analysis of cities or regions, appropriate adjustment of specific measures and targets, and improvement of digital information management of urban energy performance. This research can effectively help cities clarify which policies require higher implementation intensity and attention before and during policy implementation, thereby maximizing multi-dimensional urban energy performance.
城市巨大能源消耗所带来的环境污染和社会福祉问题,反映出从经济、环境和福祉等多个维度提高城市能源绩效的紧迫性。因此,各国和各城市纷纷出台了一系列政策。然而,政策的复杂性使得类别和效用需要进一步明确,政策效果评估滞后所带来的不经济使得政策实施的重点需要提前明确。因此,本研究基于公共选择理论,遵循“先分析”的思路,以中国城市为研究对象。首先,采用内容分析法对收集到的中国城市能源绩效提升政策进行分析和分类,总结各类政策的主要效用和各类别政策的具体效用。基于城市能源绩效研究的多维视角(即经济、环境和福祉维度),总结有助于提升各维度城市能源绩效的政策效用,并预设政策效用值。其次,通过反向传播(BP)神经网络构建城市各维度能源绩效提升政策效果预测模型。然后,以数据包络分析方法衡量的 2020 年中国城市能源绩效为基准值,以政策效果预测模型衡量的 2025 年中国城市能源绩效为比较值。根据绩效提升结果,从经济、环境和福祉维度分别选取中国城市的能源绩效提升政策。研究结果表明:中国城市能源绩效提升政策主要包括节能降碳政策、能源发展政策、生态环境政策、财税政策、产业政策和经济社会政策等六类。从经济维度提升城市能源绩效,需要重点关注生态环境政策、财税政策和产业政策。从环境维度来看,关键和优先政策是生态环境政策。与经济维度相比,福祉维度实施政策的重点增加了经济社会政策。在政策实施过程中,可通过城市或区域的多特征分析、适当调整具体措施和目标、提高城市能源绩效的数字信息管理等方式,减少城市间能源绩效的差异。本研究可为城市在政策实施前和实施过程中明确需要更高实施强度和关注的政策提供有效帮助,从而实现城市多维度能源绩效的最大化。