Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Life cycle carbon impact of higher education building redevelopment
UK higher education institutions have strong drivers to reduce operational carbon emissions through building refurbishment or replacement. Given their varying nature, determining carbon reductions can be challenging. There is developing interest in the life cycle carbon impact of buildings - operational carbon emissions plus material embodied carbon emissions - particularly in redevelopment where possible operational carbon savings may be offset by new materials. Key questions emerged: what are the main determinants of energy use in higher education buildings; to what extent do redevelopment options have the potential to reduce operational carbon impact; how do embodied and operational carbon impacts compare for different redevelopment options? The following studies were carried out accordingly: development of a database of 1,950 university buildings incorporating high-level building parameters and end energy use; analysis of the database using statistical and artificial neural network methods; investigations on five case studies to model the life cycle carbon impact of building redevelopment using real data; modelling redevelopment of six university building archetypes using the database and case study data. A visualisation was also developed to aid estates managers and designers by grading existing building performance and demonstrating the potential carbon reductions of redevelopment scenarios. In the database analysis, it was found that energy use varied significantly by primary activity and that electricity use was often significantly lower for naturally-ventilated buildings relative to mechanically-ventilated. Older buildings tended to exhibit higher heating fuel use but lower electricity use. Some relationships between energy use and research activity and context were also observed. The artificial neural network approach wassuccessful in terms of generalisation performance and showed potential for use in scoping carbon reduction interventions after further development. From the archetype analysis, it was ...
Life cycle carbon impact of higher education building redevelopment
UK higher education institutions have strong drivers to reduce operational carbon emissions through building refurbishment or replacement. Given their varying nature, determining carbon reductions can be challenging. There is developing interest in the life cycle carbon impact of buildings - operational carbon emissions plus material embodied carbon emissions - particularly in redevelopment where possible operational carbon savings may be offset by new materials. Key questions emerged: what are the main determinants of energy use in higher education buildings; to what extent do redevelopment options have the potential to reduce operational carbon impact; how do embodied and operational carbon impacts compare for different redevelopment options? The following studies were carried out accordingly: development of a database of 1,950 university buildings incorporating high-level building parameters and end energy use; analysis of the database using statistical and artificial neural network methods; investigations on five case studies to model the life cycle carbon impact of building redevelopment using real data; modelling redevelopment of six university building archetypes using the database and case study data. A visualisation was also developed to aid estates managers and designers by grading existing building performance and demonstrating the potential carbon reductions of redevelopment scenarios. In the database analysis, it was found that energy use varied significantly by primary activity and that electricity use was often significantly lower for naturally-ventilated buildings relative to mechanically-ventilated. Older buildings tended to exhibit higher heating fuel use but lower electricity use. Some relationships between energy use and research activity and context were also observed. The artificial neural network approach wassuccessful in terms of generalisation performance and showed potential for use in scoping carbon reduction interventions after further development. From the archetype analysis, it was ...
Life cycle carbon impact of higher education building redevelopment
Hawkins, DP (Autor:in) / Mumovic, D
28.03.2016
Doctoral thesis, UCL (University College London).
Hochschulschrift
Elektronische Ressource
Englisch
life cycle , archetype , higher education , embodied , redevelopment , refurbishment , university , benchmark , carbon , new-build , operational
DDC:
690
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