The building sector is a major contributor to global energy consumption and carbon emissions, accounting for over 40 % of the total, and thus plays a pivotal role in mitigating climate change and enhancing societal well-being. The specific drivers and carbon peaking pathways associated with different developmental stages and building types remain insufficiently quantified in fast‑urbanizing regions. This study developed an integrated framework to address this research gap by (i) accounting for energy-related CO 2 emissions across both construction and operational phases, covering urban residential, rural residential, and public buildings; (ii) identifying key drivers using Kaya identity and LMDI decomposition; and (iii) projecting future emissions under three scenarios, with Monte Carlo simulation incorporated to characterize uncertainty. Using Shaanxi Province, China as a case study, we found that GDP growth served as the dominant driver for construction-phase emissions, while operational emissions were primarily driven by urbanization, per-capita floor area, energy intensity, and emission factors, with variations across building types. Scenario results indicated that total emissions peak in 2033 (101.97 Mt) under the baseline scenario, 2030 (97.97 Mt) under the low-carbon peak scenario, and around 2025 (91.28 Mt) under the enhanced low-carbon scenario. Monte Carlo simulation indicated that the probability of achieving peak emissions before 2030 was 19.9 %, 65.05 %, and 99.9 % under the baseline, low-carbon peak, and enhanced low-carbon scenarios, respectively. Sensitivity analysis highlighted the critical roles of urbanization rate and renewable-energy-related emission-factor improvements, with mitigation measures potentially reducing emissions by up to 29.68 Mt by 2030 in the study area. Optimizing the energy mix and adjusting emission factors are identified as essential strategies for achieving emission reductions within the current development framework. These findings provided quantitative evidence for prioritizing efficiency improvement, electrification, and clean energy supply to achieve carbon-peaking targets. • Building-sector CO 2 in Shaanxi rose by 68.32 Mt from 2001 to 2020. • Influencing factors of construction emissions from various sources are revealed. • Characterization and prediction model for construction emissions has been established. • Carbon peak pathway in the study area is predicted using both dynamic and static methods.
Li et al. (Thu,) studied this question.