Reassessing determinants of urban energy intensity in China: insights from controllable and uncontrollable factors

被引:1
|
作者
Xiao B. [1 ]
Guo X. [1 ]
Si F. [2 ]
机构
[1] School of Business Administration, Northeastern University, Chuangxin Road, Hunnan District, Shenyang
[2] School of Management, Beijing Union University, East Beisihuan Road, Chaoyang District, Beijing
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
City classification; Panel data analysis; Urban energy intensity;
D O I
10.1007/s11356-024-33687-y
中图分类号
学科分类号
摘要
This study adopts a new approach to reassess the factors influencing urban energy intensity in China. Initially, the factors impacting energy intensity are classified into controllable and uncontrollable categories. Subsequently, employing a single-factor multi-stage method combined with the Adaboost method, 289 Chinese cities are categorized based on uncontrollable factors to eliminate the influence of inherent differences on energy intensity. Finally, panel data regression analyses are conducted using data from 289 Chinese cities between 2005 and 2016, individually for each city type, to evaluate the extent to which controllable factors contribute to energy intensity. The findings indicate that (1) heightened energy prices, an increased share of electricity consumption, and a greater proportion of centralized heating significantly influence the reduction of energy intensity across all city types; (2) to optimize energy consumption, each city type should adopt specific strategies. For instance, cities located in resource-rich heating regions with low economic outputs can reduce their energy intensity by increasing electricity consumption, while cities with high economic outputs can decrease their energy intensity by increasing natural gas consumption. The findings of this study carry substantial implications for the Chinese government in shaping targeted energy policies tailored to different city types. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.
引用
收藏
页码:38367 / 38384
页数:17
相关论文
共 50 条
  • [31] China's industrial energy intensity: Regional differences and influencing factors
    Li, J., 1600, Asian Network for Scientific Information (13):
  • [32] Effects of investment on energy intensity:evidence from China
    Junbing Huang
    Shiwei Yu
    ChineseJournalofPopulation,ResourcesandEnvironment, 2016, (03) : 197 - 207
  • [33] Effects of investment on energy intensity: evidence from China
    Huang, Junbing
    Yu, Shiwei
    CHINESE JOURNAL OF POPULATION RESOURCES AND ENVIRONMENT, 2016, 14 (03) : 197 - 207
  • [34] Evolution and determinants of ecosystem services: insights from South China karst
    Zhang, Shihao
    Xiong, Kangning
    Qin, Yao
    Min, Xiaoying
    Xiao, Jie
    ECOLOGICAL INDICATORS, 2021, 133
  • [35] Energy conversion of urban wastes in China: Insights into potentials and disparities of regional energy and environmental benefits
    Wang, Hanning
    Wang, Xian'en
    Song, Junnian
    Ren, Jingzheng
    Duan, Haiyan
    ENERGY CONVERSION AND MANAGEMENT, 2019, 198
  • [36] HERITAGIZATION AS AN AUTHORITARIAN URBAN PRACTICE IN CHINA: Insights from Lijiang
    Mascaro, Giorgia
    INTERNATIONAL JOURNAL OF URBAN AND REGIONAL RESEARCH, 2024, 48 (04) : 708 - 720
  • [37] Are determinants of stunting in rural and urban areas different? Insights from Mozambique.
    Garrett, JL
    Ruel, MT
    FASEB JOURNAL, 1999, 13 (04): : A543 - A543
  • [38] Exploring the Impact of Geographic Factors on Urban Financial Innovation in China: Insights from the Banking, Insurance, and Securities Industries
    Lin, Lichao
    Huang, Ziling
    Pan, Chen
    Wang, Xiaofeng
    JOURNAL OF THE KNOWLEDGE ECONOMY, 2024,
  • [39] Determinants of urban identity in urbanizing China: findings from a survey experiment
    Chen, Juan
    Yue, Chunying
    Ren, Liying
    Yan, Jie
    CHINESE SOCIOLOGICAL REVIEW, 2020, 52 (03) : 295 - 318
  • [40] Determinants of public trust in government: empirical evidence from urban China
    Zhao, Dahai
    Hu, Wei
    INTERNATIONAL REVIEW OF ADMINISTRATIVE SCIENCES, 2017, 83 (02) : 358 - 377