Analysis of Carbon Emission Driving Factors and Study of Peak Paths under the Perspective of Spatio-Temporal Heterogeneity

Firstly, we compute the emissions of carbon in the Beijing, Tianjin, and Hebei of China, construct LMDI model, and decompose the CO2 drivers based on the perspective of spatio-temporal heterogeneity. Following the LMDI analysis results, three scenario models are suggested: a baseline scenario, a low...

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Bibliographic Details
Published in:E3S web of conferences 2024-01, Vol.536, p.01014
Main Authors: Ji Jingyi, Shen Longfei
Format: Article
Language:English
Online Access:Get full text
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Summary:Firstly, we compute the emissions of carbon in the Beijing, Tianjin, and Hebei of China, construct LMDI model, and decompose the CO2 drivers based on the perspective of spatio-temporal heterogeneity. Following the LMDI analysis results, three scenario models are suggested: a baseline scenario, a low-carbon model, and a high-carbon model. By integrating the current economic and social development status in Beijing-Tianjin-Hebei and relevant policies, specific model variables are defined to establish the STIRPAT model. Different carbon emission scenarios are then forecasted and evaluated using the STIRPAT model to determine the peak year and the maximum carbon emission level in the Beijing-Tianjin-Hebei region. The research indicates that (1) the highest carbon emission level will reach 377,712,600 tons in 2022 within the study period, with notable variations among different cities. (2) Economic development has the most significant impact on carbon emissions. (3) Under the low-carbon scenario, the 13 cities can attain the carbon emission peak target by 2030. These findings offer quantitative insights to support the transition towards low-carbon development in the Beijing-Tianjin-Hebei region.
ISSN:2267-1242
DOI:10.1051/e3sconf/202453601014