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Apartment related energy performance gap – How to address internal heat transfers in multi-apartment buildings

Abstract Households’ heating energy consumption is one of the most important sources of a nation's total CO2 emissions. But there remains uncertainty about the impact of occupant behaviour on heating energy consumption, especially in multi-apartment buildings. In bringing together apartment specific data of occupant behaviour and physical building properties of multi-apartment buildings, the quantitative influence of different factors determining apartments’ heating energy consumption can be separated by means of OLS-regression. For multi-apartment buildings the heating energy consumption of a single apartment seems to be determined not only by the behaviour of households in opening windows and using radiators but also by internal heat transfers, triggered by temperature differences between neighbouring apartments. This study shows some limits of refurbishment policies and consumer education and points to the importance of considering both data on occupant behaviour and building physics at the apartment level together to understand households’ heating energy consumption.
- Technical University of Munich Germany
- Ludwig-Maximilians-Universität München Germany
- Institut Wohnen und Umwelt Germany
- Institut Wohnen und Umwelt Germany
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).25 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
