Work

Research on a Carbon Emission Prediction Model for the Construction Phase of Underground Space Engineering Based on Typical Resource Carbon Consumption and Its Application

Year: 2025

Type: article

Abstract: The trend of global warming remains severe. As one of the major sources of carbon emissions, the construction industry still requires large-scale and effective transformations. This study, grounded in Life Cycle Assessment (LCA) theory, carbon emission factor calculation methods, the Monte Carlo method, and feedforward neural network algorithms, develops a carbon emission prediction model based on the carbon emissions generated by typical resource consumption. The model is established in the context of typical carbon emission patterns observed during the construction phase of subway stations in China. Furthermore, the feasibility of the proposed model is validated through its application to specific engineering projects. The results demonstrate that (1) the newly developed carbon emission model can accurately predict the carbon emissions associated with the construction phase of subway stations in China; (2) actual carbon emission calculations in construction projects require the integration of data from multiple sources to ensure comprehensive coverage and avoid omissions; and (3) during the construction phase of subway stations, the use of concrete and steel constitutes significant sources of carbon emissions.

Source: Buildings

DOI: 10.3390/buildings15081334

Authors: Yuan Mei, Haokun Wang, Dongbo Zhou

Institution: Xi'an University of Architecture and Technology

Language: English

Topic: Environmental Impact and Sustainability

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137