Abstract

As the greenhouse effect intensifies, controlling carbon emissions has become increasingly critical. China, having the world's highest carbon emissions, sees almost half of its total emissions from the building sector. China is confronted with the challenge of different provinces having diverse timelines for achieving carbon peak in the building sector, leading to “undesirable responses”. To address this, our study expands the research scope and introduces dynamic forecasting methods through the D-STIRPAT model. The model has produced more accurate predictions for carbon emissions in the building sector of the Central China region. The research results indicate that collaborative optimization between urban and construction industries is the most effective pathway to reduce carbon emissions. Henan Province can achieve peak emissions in the building sector relatively quickly, with most scenarios reaching their peak by 2040, with the lowest peak value reaching 415.4 MtCO2e. Hubei and Hunan provinces are likely to achieve peak emissions for most scenarios between 2050 and 2060. However, the building sector in the Central China region can achieve peak emissions between 2030 and 2045, with peak values ranging from 1.235 to 1.702 BtCO2e. In terms of carbon reduction effects, the overall strategy for achieving peak emissions in the building sector in Central China should focus primarily on optimizing urban and building sector development, supported by energy structure optimization and the promotion of building energy efficiency. Henan and Hubei provinces should prioritize urban and building sector development, while Hunan Province should emphasize both urban and building sector development and energy structure optimization concurrently. This study highlights the benefits of regional carbon emissions regulation in the building sector, provides innovative solutions for achieving dual carbon targets, and offers guidance and approaches for achieving peak emissions in the building sector through regional collaboration.

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