An improved approach for measuring the efficiency of low carbon city practice in China. (1st April 2023)

• Record Type: Journal Article
• Authors: Du, Xiaoyun; Meng, Conghui; Guo, Zhenhua; Yan, Hang
• Is Part Of: Energy. Volume 268(2023)
• Publication Date: 2023-04-01
• Subjects: Low carbon city -- Evaluation method -- Efficiency perspective -- China; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2023.126678
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: To meet the dual carbon goal, Chinese cities have invested a lot of human, material and financial resources in practicing low carbon city (LCC) and have made great progress. However, it seems that the efficiency of LCC performance remains unexplored. This study aims to propose an improved method for measuring LCC performance from an efficiency perspective (LCCE method). In developing this method, LCC practice is considered as a system, and the input factors of LCCE consist of labor force, capital stock, and energy consumption. Economic growth and carbon emissions are overall output factors, and four dimensional output factors, such as optimizing industrial structure are identified. Subsequently, the super-SBM model of LCCE is built up by integrating multiple inputs and outputs. A demonstration of the proposed LCCE method was conducted using data of 256 prefecture-level cities in China from 2006 to 2019. The research findings reveal that: (1) LCCE of cities in the western region performed slightly better than the other three regions; (2) LCCE of Chinese cities shows a U-shaped relationship with city size. This study proposes an improved approach for measuring LCCE and provides an essential reference for central and local governments in China to better formulate low-carbon strategies. Highlights: The efficiency measurement model for low-carbon city is proposed. There are overall and dimensional outputs for practicing in China. The LCCE shows a U-shaped relationship with city size. The case study demonstrates the validity of the proposed method.