LAPSE:2023.35461
Published Article

LAPSE:2023.35461
Direct and Indirect Carbon Emission from Household Consumption Based on LMDI and SDA Model: A Decomposition and Comparison Analysis
April 28, 2023
Abstract
Household consumption has become an important field of carbon dioxide emissions. Urban−rural disparity in the household carbon emissions (HCEs) of residents and their influencing factors are relevant to HCE reduction. Taking Fujian as the study area, the LMDI and SDA models were used to analyze the effects of influencing factors for the direct household carbon emissions (DHCEs) and indirect carbon emissions (IHCEs) of urban and rural residents from 2006 to 2018. The HCEs continue to rise, approximately 65% from the IHCEs in 2017, and urban areas occupied 67% in 2018. The gap between urban and rural per capita HCEs is narrowing. In 2017, approximately 75% of urban per capita HCEs came from the IHCEs, while the per capita DHCEs’ occupation exceeded the IHCEs in rural areas. Per capita consumption expenditure has the largest positive effect on the DHCEs and IHCEs in urban and rural areas. With the urbanization process, the inhibition effect of rural DHCEs is larger than the positive effect of the urban DHCEs, while the positive impact on urban areas is more substantial than on rural areas in the IHCEs. Combined with regional differences, urban and rural areas should take “common but differentiated” emission reduction responsibilities.
Household consumption has become an important field of carbon dioxide emissions. Urban−rural disparity in the household carbon emissions (HCEs) of residents and their influencing factors are relevant to HCE reduction. Taking Fujian as the study area, the LMDI and SDA models were used to analyze the effects of influencing factors for the direct household carbon emissions (DHCEs) and indirect carbon emissions (IHCEs) of urban and rural residents from 2006 to 2018. The HCEs continue to rise, approximately 65% from the IHCEs in 2017, and urban areas occupied 67% in 2018. The gap between urban and rural per capita HCEs is narrowing. In 2017, approximately 75% of urban per capita HCEs came from the IHCEs, while the per capita DHCEs’ occupation exceeded the IHCEs in rural areas. Per capita consumption expenditure has the largest positive effect on the DHCEs and IHCEs in urban and rural areas. With the urbanization process, the inhibition effect of rural DHCEs is larger than the positive effect of the urban DHCEs, while the positive impact on urban areas is more substantial than on rural areas in the IHCEs. Combined with regional differences, urban and rural areas should take “common but differentiated” emission reduction responsibilities.
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Keywords
household carbon emissions, logarithmic mean divisia index, structural decomposition analysis, urban–rural disparity
Subject
Suggested Citation
Chen J, Lin Y, Wang X, Mao B, Peng L. Direct and Indirect Carbon Emission from Household Consumption Based on LMDI and SDA Model: A Decomposition and Comparison Analysis. (2023). LAPSE:2023.35461
Author Affiliations
Chen J: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Lin Y: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Wang X: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Mao B: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Peng L: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Lin Y: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Wang X: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Mao B: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Peng L: College of the Environment & Ecology, Xiamen University, Xiamen 361102, China
Journal Name
Energies
Volume
15
Issue
14
First Page
5002
Year
2022
Publication Date
2022-07-08
ISSN
1996-1073
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Original Submission
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PII: en15145002, Publication Type: Journal Article
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LAPSE:2023.35461
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https://doi.org/10.3390/en15145002
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Apr 28, 2023
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