Calculation of Carbon Emission from Operation of University Campus Buildings and Their Temporal and Spatial Characteristics:A Case Study Based on South China University of Technology

ZHANG Yueming; WANG Jing; YAN Shuai

doi:10.3969/j.issn.1000-0232.2025.03.011

Abstract：The construction industry is a key sector for China to achieve its carbon neutrality goals,and differentiated spatial scale adaptation strategies must be explored for carbon reduction.As meso-scale urban spaces,university campuses are characteristic of functional complexity,intensive energy demand,and intricate carbon emission patterns.However,existing studies mainly focus on macro(national/regional)or micro(individual building)scales,with a lack of systematic exploration into the mechanisms of carbon emissions at the meso-scale level,particularly on campuses.As a result,carbon reduction measures are disconnected from campus planning and design.University campuses currently face two core challenges in reducing carbon emissions:1)the fundamental factors affecting carbon emissions within campus spaces are not yet clear,and 2)the absence of a unified calculation model and data standard hinders precise carbon reduction decisions. Therefore,an empirical study on the Wushan Campus,University Town Campus,and Guangzhou International Campus of South China University of Technology(SCUT)was carried out.The technical route of"constructing a quantitative analysis model-campus case calculations-refinement of carbon emission characteristics"was applied.First,factors influencing carbon emission from building operations were identified from the spatial and temporal dimensions based on a literature review and field surveys.The temporal dimension includes climate characteristics and building operational schedules.The spatial dimension covers overall planning(floor area ratio,year of construction,and per capita floor area),functional cluster types(teaching and scientific research,student living),and properties of individual buildings(function type and enclosure structure).Second,a calculation model was built using the carbon emission factor method covering 12 types of buildings.Finally,the temporal and spatial characteristics of carbon emissions were analyzed,and the areas with potential for carbon reduction were identified by combining monthly and seasonal energy consumption data with spatial attributes. The results indicate:(1)in the temporal dimension,the carbon emissions from building operations on the three campuses of SCUT show significant seasonal differences.The peak carbon emissions per unit area in the third quarter are 2.64 to 3.76 times higher than in the first quarter.The carbon emissions of buildings like administrative offices,libraries,and teaching buildings are affected by their operational periods.(2)In the spatial dimension,the floor area ratio,year of construction,and per capita floor area significantly affect carbon emissions on the overall planning level.The carbon emissions per unit building area in the Guangzhou International Campus is only 32％ of those in the Wushan Campus,which is attributed to its higher floor area ratio,modern construction,and larger per capita floor area.On the functional cluster level,carbon emission characteristics vary significantly with functional orientations.The carbon emission of teaching and scientific research buildings accounts for the highest proportion of total carbon emissions on the campus,which is about 50％in all three campuses.With respect to individual buildings,student dormitories,research buildings,and comprehensive buildings are major contributors to annual operational carbon emissions.(3)A quantitative analysis shows that the teaching and research buildings and the technological industrial buildings on the Wushan Campus,the logistics service buildings on the University Town Campus,and the student dormitories on Guangzhou International Campus are key areas for carbon reduction. In sum,this study aims to build a quantitative analysis model for carbon emission from building operation on university campuses,disclose the spatial and temporal distribution laws of carbon emissions,identify areas with potential for carbon reduction,and provide scientific references for low-carbon campus planning.Future research will incorporate additional variables like architectural morphology and user behavior to improve model accuracy and offer more comprehensive theoretical and technical support for achieving carbon neutrality on meso-scale campuses.