Font Size: a A A

Research On Carbon Emissions Of Large Stadiums And Its Ancillary Facilities

Posted on:2023-05-28Degree:MasterType:Thesis
Country:ChinaCandidate:D D WanFull Text:PDF
GTID:2532307100475964Subject:Civil engineering
Abstract/Summary:PDF Full Text Request
As a pillar industry of the national economy,the construction industry releases approximately 40%of the total carbon emissions each year.The construction of low-carbon buildings is an important measure to achieve the Chinese government’s goal of achieving carbon peaking by 2030 and carbon neutrality by 2060.With the development of the national economy,sports as an important social,economic and cultural activity,the total carbon emissions generated by sports are always high.As an important carrier of large-scale sports activities,the energy consumption of sports buildings is quite different from that of general public buildings.Therefore,It is particularly important to carry out research specifically on the construction of large stadiums.Based on a large number of references at home and abroad,this thesis determines the goals and boundaries of carbon emission accounting for large stadiums.By comparing different carbon emission accounting methods,the carbon emission factor method is used for analysis.The main research work is as follows:(1)Carbon emission factor is an important basis for the study of carbon emission in the whole life cycle.On the basis of determining the selection principle and accounting method of carbon emission factor,this research comprehensively analyzes the carbon emission sources of common energy and materials,and determines a set of carbon emission factor pool suitable for China’s national conditions.(2)Based on the full life cycle theory,this study divides the full life cycle of large stadiums into three stages:materialization,operation and maintenance,and demolition and recycling,and establishes a carbon emission accounting model for large stadiums.Among them,in the operation stage,the method of Energy Plus energy consumption simulation is used for carbon emission accounting.In this study,some buildings in the Yanqing Winter Olympics were selected to verify the accounting model.The results show that,from the perspective of the entire life cycle,the carbon emissions in the operation stage accounted for the largest proportion,accounting for 70%to 80%,followed by the materialization stage,which accounted for 20%to 30%of the total carbon emissions.The total life cycle carbon emissions of Yanqing Winter Olympic Village and Snowmobile Center are 267.9 kg CO2/m2·a and 133.77 kg CO2/m2·a,respectively.In the use of building materials and energy,the carbon emissions of steel bars,concrete,diesel,steel plates,and aluminum profiles account for the largest proportion,exceeding 95%of the total statistics.(3)Based on the carbon emission accounting model of large stadiums,the influencing factors of each stage of the sports building’s life cycle are analyzed,combined with the characteristics of sports buildings,referring to domestic and foreign literature and low-carbon standards for green buildings,through questionnaires Peer experts and scholars solicited opinions on the importance of the indicators,and finally established the carbon emission evaluation indicators of large stadiums.The AHP is used to complete the weight calculation.Then,based on the setting and scoring standards for the qualitative and quantitative indicators,the grey cluster analysis method combining qualitative and quantitative indicators is used to complete a set of carbon emission evaluation system for large stadiums.Using the established evaluation index system to verify the case of the Winter Olympic town and venue in Yanqing competition area,the results show that the building assembly has reached the low-carbon four-star standard.The research results have important reference value for low-carbon construction,application and evaluation of stadiums.
Keywords/Search Tags:Low-carbon sports stadiums, full life cycle theory, building carbon emissions accounting, evaluation system, grey cluster analysis
PDF Full Text Request
Related items