Historical carbon peak situation and its driving mechanisms in the commercial building sector in China
Evaluating the peak situation of commercial building carbon emissions (CBCE) at the provincial level and revealing their differentiated driving mechanisms are extremely significant for achieving the national “Dual carbon” target. In this study, a new provincial-level carbon peak situation assessment...
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Published in | Sustainable production and consumption Vol. 44; pp. 25 - 38 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.01.2024
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Subjects | |
Online Access | Get full text |
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Summary: | Evaluating the peak situation of commercial building carbon emissions (CBCE) at the provincial level and revealing their differentiated driving mechanisms are extremely significant for achieving the national “Dual carbon” target. In this study, a new provincial-level carbon peak situation assessment model is constructed to evaluate the historical CBCE peak situations in China by integrating conditional judgement function, Mann-Kendall trend test, and Tapio decoupling model. Furthermore, the STIRPAT model and grouped regression model are combined to investigate the driving mechanisms on CBCE under different carbon peaking situations. Results showed that the CBCE in Beijing have reached the peak, and Shandong and Inner Mongolia have entered the peak potential period. Beijing achieved the decoupling of CBCE from value added of tertiary sector and floor space per capita. The most important factors leading to different peak situations of CBCE are commercial floor space per capita and energy intensity. Urban population, industrial structure, value added of tertiary industry per capita and energy structure show different degrees of influence on different peak stages of CBCE. This study provides a general methodology for evaluating the carbon peak situation and its driving mechanism. It sets the foundation for the formulation of the differentiated carbon peak pathway and provides a reference for the carbon emission assessment of other countries with regional carbon peak differences in the world. |
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ISSN: | 2352-5509 2352-5509 |
DOI: | 10.1016/j.spc.2023.11.018 |