4.3 Article

Examining the Driving Factors of Urban Residential Carbon Intensity Using the LMDI Method: Evidence from China's County-Level Cities

Publisher

MDPI
DOI: 10.3390/ijerph18083929

Keywords

carbon intensity; residential sector; urban expansion; LMDI; county level

Funding

  1. National Natural Science Foundation of China [42001220]
  2. Innovation Team of Philosophy and Social Science of Colleges and Universities in Henan Province [2021-CXTD-04]
  3. Key Scientific Research Projects of Colleges and Universities in Henan Province [21B170001]
  4. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences

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This study analyzed the spatiotemporal variation of carbon intensity in 620 county-level cities in China from 2001 to 2015 using the logarithmic mean Divisia index (LMDI). It was found that high carbon intensity is mainly present in large cities, such as Beijing, Tianjin, and Shanghai. Energy consumption, urban sprawl, and land demand were identified as the three most influential factors in determining changes in carbon intensity.
Improving carbon efficiency and reducing carbon intensity are effective means of mitigating climate change. Carbon emissions due to urban residential energy consumption have increased significantly; however, there is a lack of research on urban residential carbon intensity. This paper examines the spatiotemporal variation of carbon intensity in the residential sector during 2001-2015, and then identifies the causes of the variation by utilizing the logarithmic mean Divisia index (LMDI) with the help of Microsoft Excel 2016 for 620 county-level cities in 30 Chinese provinces. The results show that high carbon intensity is mainly found in large cities, such as Beijing, Tianjin, and Shanghai. However, these cities showed a downward trend in carbon intensity. In terms of influencing factors, the energy consumption per capita, urban sprawl, and land demand are the three most influential factors in determining the changes in carbon intensity. The effect of energy consumption per capita mainly increases the carbon intensity, and its impact is higher in the municipal districts of provincial capital cities than in other types of cities. Similarly, the urban sprawl effect also promotes increases in carbon intensity, and a higher degree of influence appears in large cities. However, as urban expansion plateaus, the effect of urban sprawl decreases. The land-demand effect reduces the carbon intensity, and the degree of influence of the land-demand effect on carbon intensity is also clearly stronger in big cities. Our findings show that lowering the energy consumption per capita and optimizing the land-use structure are a reasonable direction of efforts, and the effects of differences in influencing factors should be paid more attention to reduce carbon intensity.

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