Literature DB >> 30523528

Urbanization impact on residential energy consumption in China: the roles of income, urbanization level, and urban density.

Qiaoran Wang1,2, Xianming Yang3.   

Abstract

This paper investigated the impact of urbanization on residential energy consumption (REC) in China by taking cognizance of the levels of income, urbanization and urban density. Threshold analyses were employed to investigate the nonlinear relationships based on the STIRPAT (Stochastic Impacts by Regression on Population, Affluence, and Technology) framework using a balanced panel dataset of 29 provinces of China over the period of 1998-2014. The common correlated effects mean group estimator (CCEMG) was used to address time-series cross-section (TSCS) issues. The results confirmed the existence of the nonlinear relationship between urbanization and REC in China. The impact of urbanization on REC varied at different economic development levels and urbanization levels. Specifically, urbanization decreased REC at the stage that per capita disposable income of urban residents (PDI) less than 2615 USD, while it increased REC at the stage that PDI higher than 2615 USD. Similarly, urbanization decreased REC at the stage that urbanization rate lower than 55.31% and increased REC after urbanization rate exceeded 55.31%. This study did not find evidence to support the urban environmental transition theory, indicating there was still no region in China had stepped into the win-win stage of urbanization and energy consumption. Furthermore, the nonlinear impact of urban density on REC was estimated and the results indicated that urban density exerted a positive effect on REC when urban density was lower than 808 inhabitants per square kilometer, while it was no longer relevant to REC after that threshold point. Based on these results, the corresponding countermeasures and suggestions to achieve low-carbon urbanization were put forward.

Entities:  

Keywords:  CCEMG; Household income; Residential energy consumption; STIRPAT; Threshold regression; Urban density; Urbanization

Mesh:

Year:  2018        PMID: 30523528     DOI: 10.1007/s11356-018-3863-4

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


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