Driving Factors and Peak Forecasting of Carbon Emissions from Public Buildings Based on LMDI-SD. (27th April 2022)

• Record Type: Journal Article
• Authors: Wang, Yongkun; Liang, Yang; Shao, Liangshan
• Other Names: Katina Polinpapilinho Academic Editor.
• Is Part Of: Discrete dynamics in nature and society. Volume 2022(2022)
• Publication Date: 2022-04-27
• Subjects: System analysis -- Periodicals; Dynamics -- Periodicals; Chaotic behavior in systems -- Periodicals; Differentiable dynamical systems -- Periodicals; 003.05
• DOI: 10.1155/2022/4958660
• Languages: English
• ISSNs: 1026-0226

Abstract

Abstract : Public buildings, with the increasing level of energy consumption, are a key area of energy conservation and emission reduction in China's construction industry. In order to reduce carbon emissions of public buildings, realize the targets of energy conservation and emission reduction, the LMDI method is used to construct China's public building macrocarbon factor decomposition model, identify the main driving factors affecting the change of carbon emissions from public buildings, and build a system dynamics model based on the decomposition results to predict China's public building carbon emissions peak. The results show that reducing carbon emission coefficient and reducing energy intensity are the main driving factors to restrain the growth of carbon emission from public buildings. Under the base scenario, carbon emissions from public buildings will peak at 1.242 billion tons in 2041. Under the comprehensive regulation of energy structure, economic growth rate, investment level of scientific research and education, and carbon sink capacity, the carbon emissions of public buildings will reach the peak in 2030, and the adjustment of energy structure has a significant impact on the peak and peak time of carbon emissions of public buildings.