Statistical Analysis of Survey Results.

Within the context of advancing global sustainable development goals, universities are recognized as leaders in energy conservation and emissions reduction within the education sector. Universities should actively engage in the accounting and analysis of carbon emissions. This study uses Sichuan University Jinjiang College(Hereafter referred to as J University) in Sichuan, China, as a case study, where the campus’s carbon emissions for the year 2023 were calculated using the Emission Factor Method and the Delphi Method. The uncertainty associated with these emissions was further explored using Monte Carlo simulation. The results indicate that the net carbon emissions of J University amounted to 44,584.33 tons of CO2 equivalent (tCO2e), with per capita emissions of 1.89 tCO2e. The primary sources of campus carbon emissions, in descending order, include electricity (18879.94tCO2e), natural gas (8647.25tCO2e), business travel (5224.55tCO2e), campus commuting (3852.33tCO2e), food (3444.67tCO2e), and thermal energy (2566.63tCO2e). Among these sources, the carbon emissions from electricity, natural gas, and thermal energy were closely correlated with seasonal and regional factors. The uncertainties related to commuting and business travel had the most significant impact on the overall carbon emissions accounting for the campus. The study presents a framework for campus carbon emission accounting, providing a concrete case study for future researchers in this field. In particular, an in-depth exploration of statistical uncertainties is conducted, offering a scientific basis for the accurate calculation of carbon emissions in future studies.