Journal
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
Volume 86, Issue -, Pages -Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.eiar.2020.106487
Keywords
Residential building sector; Carbon emissions; Tapio decoupling; LMDI model; Driving factors; Sustainable development
Categories
Funding
- National Natural Science Foundation of China [71902053, 71901082, 71722004]
- National Key R&D Program of China [2018YFD1100201]
- Fundamental Research Funds for the Central Universities [2020CDJSK03XK15]
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This study explores the decoupling relationship between residential building carbon emissions and residential income across 30 Chinese provinces from 2000 to 2015. Results show a significant change in the decoupling trend, primarily influenced by residential energy intensity and per capita income. The findings provide valuable references for international policymakers to formulate targeted carbon reduction policies.
Decoupling residential building carbon emissions from residential income has great significance for carbon mitigation and even global climate change. However, the nature of the decoupling relationship between them is still unclear. This study adopts the Tapio decoupling model to explore the decoupling relationship among residential building carbon emissions (TC), per capita carbon emissions (PC), residential carbon intensity (FC) and per capita income (PCI) across 30 Chinese provinces from 2000 to 2015. Then, the Logarithmic Mean Divisa Index (LMDI) model is used to decompose the decoupling of residential building carbon intensity and PCI at the provincial level to determine the main factors determining this relationship. Results show that the main decoupling trend between FC and PCI in 30 provinces transformed from weak decoupling state to strong decoupling state during the whole period, while there is still extensive room for TC and PC to decouple with PCI. PCI has the major inhibiting effect on the decoupling between FC and PCI, while residential energy intensity (EI) has the primarily promoting effect on the decoupling. These findings provide valuable references for international policymakers in formulating precisely targeted energy-saving and carbon-reducing policies to coordinate the relationship between income and carbon emissions, and the results also can be applied to other economies and, to a greater extent, other pollutants.
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