Quantitative Carbon Emission Prediction Model to Limit Embodied Carbon from Major Building Materials in Multi-Story Buildings

Abstract

As the largest contributor of carbon emissions in China, the building sector currently relies mostly on enterprises’ own efforts to report carbon emissions, which usually results in challenges related to information transparency and workload for regulatory bodies, who play an otherwise vital role in controlling the building sector’s carbon footprint. In this study, we established a novel regulatory model known as QCEPM (Quantitative Carbon Emission Prediction Model) by conducting multiple linear regression analysis using the quantities of concrete, rebar, and masonry structures as independent variables and the embodied carbon emissions of a building as the dependent variable. We processed the data in the detailed quantity list of 20 multi-story frame structure buildings and fed them to the QCEPM for the solution. Comparison of the QCEPM-calculated results against the time-consuming and error-prone manual calculation results suggested a mean absolute percentage error (MAPE) of 2.36%. Using this simplified model, regulatory bodies can efficiently supervise the embodied carbon emissions in multi-story frame structures by setting up a carbon quota for a project in its approval stage, allowing the construction enterprise to carry out dynamic control over the three most important audited building materials throughout a project’s planning and implementation phase.