CLIMATIC IMPACT OF RESIDENTIAL BUILDINGS. An Examination of Greenhouse Gas Emissions in the Residential Building Sector, Factors that influence Energy Use and the Energy Saving Potentials analysed for the Borough Altona in Hamburg

Abstract

Global warming is induced by rising greenhouse gas concentrations. In order to decrease concentrations, mitigation targets for the reduction of greenhouse gas emissions have been defined on global and local levels. The residential building sector represents a keyfield of action where mitigation measures can be implemented. Regarding the life cycle of residential buildings in places like Hamburg, the emissions are highest during the operational phase. Emission investments of retrofitting measures are only amortised after a few years. In Germany, emissions deriving from space heating have the highest share of all operational emissions. The emission factor for applications based on electricity is much higher, but their share in final energy use is rather low. In the case study of Altona, one of seven boroughs in Hamburg, energy use for electricity and heating in private households in the year 2015 was collected, allocated to Statistical Areas and geographically illustrated. Hamburg’s target to limit heat energy use to a maximum of 55 kWh/m² by 2050 could be fulfilled in a small number of Statistical Areas. However, in a much larger share of Statistical Areas, energy use was around four times as high. Energy use and emissions per inhabitant tended to be rather low in urban areas and high in areas close to the river Elbe and in the suburbs. In nearly all areas of Altona, annual emissions per capita exceeded 1 t CO2 with a large number of areas exceeding 2 t CO2. The results emphasize an existing need for action in the residential building sector. The following linear regression analyses have calculated existing correlations of variables regarding urbanization, inhabitants and residential buildings with electricity and heat energy use. The objective was to gain a better understanding of existing interdependencies and the possibility to adjust mitigation action. The results showed that in Altona, density and urbanization, low shares of single family houses and elderly people, as well as low shares in employment and unemployment can serve as indicators for low energy use. Overall, the strongest correlations existed with income and living area per person. Building age did not show any correlation with energy use. The most effective measures of energy efficiency in the borough Altona would target living area per person and retrofits. Regarding carbon intensity, an increase in renewable sources is needed to improve the emission factor of district heat and electricity. Generally, the need and scope of measures could be determined more precisely if a monitoring system was introduced.