Provincial allocation of China's commercial building operational carbon toward carbon neutrality

Yanqiao Deng, Minda Ma, Nan Zhou, Chenchen Zou, Zhili Ma, Ran Yan and Xin Ma

Applied Energy, 2025, vol. 384, issue C, No S0306261925001801

Abstract: National carbon peak track and optimized provincial carbon allocations are crucial for mitigating regional inequality within the commercial building sector during China's transition to carbon neutrality. This study proposes a top-down model to evaluate carbon trajectories in operational commercial buildings up to 2060. Through Monte Carlo simulation, scenario analysis is conducted to assess carbon peak values and the corresponding peaking year, thereby optimizing carbon allocation schemes both nationwide and provincially. The results reveal that (1) the nationwide carbon peak for commercial building operations is projected to reach 890 (± 50) megatons of carbon dioxide (MtCO2) by 2028 (± 3.7 years) in the case of the business-as-usual scenario, with a 7.87 % probability of achieving the carbon peak under the decarbonization scenario. (2) Significant disparities will exist among provinces, with Shandong's carbon peak projected at 69.6 (± 4.0) MtCO2 by 2029, approximately 11 times higher than Ningxia's peak of 6.0 (± 0.3) MtCO2 by 2027. (3) Guided by the principle of maximizing the emission reduction potential, the optimal provincial allocation scheme reveals the top three provinces requiring the most significant reductions in the commercial sector: Xinjiang (5.6 MtCO2), Shandong (4.8 MtCO2), and Henan (4.7 MtCO2). Overall, this study offers optimized provincial carbon allocation strategies within the commercial building sector in China via dynamic scenario simulations, with the goal of hitting the carbon peak target and progressing toward a low-carbon future for the building sector.

Keywords: Carbon peak; Carbon allocation; Commercial building; Dynamic scenario analysis; Monte Carlo approach (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2025.125450

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