Prediction of Peak Path of Building Carbon Emissions Based on the STIRPAT Model: A Case Study of Guangzhou City

Carbon emissions from the building sector have a substantial effect on peak carbon targets. However, there are large differences in the carbon peak paths between different regions and buildings. This study used the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to study the peak carbon emission paths of buildings in Guangzhou City. Through ridge regression and F-tests, the main driving factors affecting carbon emissions from buildings were identified. Finally, the decreasing rate of carbon emissions per unit of building area in Guangzhou was changed to predict the time of the carbon peak. The results of the ridge regression analysis and F-test show that the urbanization rate, total floor area, consumption level of residents, value-added of the tertiary industry, and carbon emissions per unit of public floor area are the main driving factors of the model. The minimum reduction rate of carbon emissions per unit floor area required to achieve a building carbon peak in Guangzhou City by 2030 is 5%. This study provides a theoretical reference for Guangzhou to realize peak building carbon emissions.