Carbon Kuznets curve in China's building operations: Retrospective and prospective trajectories

China has pledged to achieve peak carbon emissions by 2030 and to be carbon neutral by the mid-century, and buildings will be the last mile sector in the transition to carbon neutrality. To help buildings hit the carbon peak goal, we investigate the different emission scales of carbon emission changes of residential and commercial building operations across 30 provinces in China through the carbon Kuznets curve (CKC) model. We observe that (1) more than three-quarters of the samples can be fitted by the CKC model. Most CKCs are the inverted U-shaped, residential and commercial buildings occupying 93% and 90% at the total emission scale, respectively. In addition, the remains can be illustrated as N-shaped curves. (2) Under the premise of CKCs existence, approximately half of the provincial residential and commercial buildings peak at different emission scales, except for emission per floor space (residential: 89%; commercial: 81%). Provinces with better economic development have a higher peaking probability. In the total emissions, the peaking probability in residential buildings is 33% and 50% for provinces with economic indicators <20,000 Chinese Yuan and 30,000-40,000 Chinese Yuan, respectively, and 22% and 67% for commercial buildings, respectively. (3) Taking carbon intensity as a case study, decoupling analysis examines the robustness of the CKC estimation. Overall, we close the gap of the CKC estimation in commercial and residential buildings, and the proposed methods can be treated as a tool for other economies to illustrate the retrospective and prospective trajectories of carbon emissions in building operations. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

This study investigates the carbon emissions of residential and commercial buildings in 30 provinces in China, revealing that the majority of buildings can be fitted by the carbon Kuznets curve model. Provinces with higher economic development have a higher probability of reaching peak emissions. The research closes the gap in estimating the CKC in commercial and residential buildings and provides a tool for analyzing carbon emission trajectories in building operations for other economies.