Helge Brattebø
norwegia
Helge Brattebø is Professor of Industrial Ecology at the Norwegian University of Science and Technology (NTNU) and Director of the strategic interdisciplinary program NTNU Sustainability. He has over 25 years university experience and his research is mostly related to industrial ecology modeling of urban built environment, using methods such as dynamic MFA, LCA, LCC and scenario analysis. He has published ca 70 international journal paper, and supervised ca 60 MSc students and 20 PhD students towards their final theses.
Residential buildings are responsible for 24% of the global final energy consumption and associated greenhouse gas emissions. Energy and emission scenario analyses are important to quantify the mitigation potentials of building stocks. However, such analyses require good bottom-up stock models to account for changing stock segment characteristics over time, such as the energy influence of future renovation, new construction technologies, changing type/age stock composition and improved energy intensities of stock segments.
We developed a dynamic segmented stock-driven model, using the Norwegian dwelling stocks towards 2050 as demonstration case. The ‘natural’ ageing process of the stock determines yearly demolition and renovation activities, by use of probability functions. The model estimates yearly energy refurbishment in each stock segment according to the ‘natural’ need for deep renovation in the ageing stock. This approach is novel compared to other studies where the renovation rates is exogenously defined.
Scenarios indicate large future reduction potentials in the aggregated final energy demand and GHG emissions in the Norwegian dwelling stock, as result of large-scale introduction of passive houses and nearly zero emission building (NZEB) technologies in new construction, and continued energy refurbishment measures in renovation of ageing buildings, despite a growing population and stock size. A large share of the energy efficiency potential of existing buildings has already been realized through renovation in previous decades. Further reduction potentials, through more advanced and/or more frequent renovation compared to current practice is relatively limited. On the other hand, extensive use of local renewable energy, by use of heat pumps and photovoltaics, has a significantly higher potential for additional reductions in final energy demand.
User behaviour is of high importance for the real energy use in the system. A prebound effect is commonly observed in dwellings of poor energy quality. Hence, the real energy use is lower than the technical estimate as the dwelling is heated to lower temperatures than assumed in technical estimations. For highly energy-efficient dwellings, on the other hand, we observe a significant rebound effect. When the cost of increasing the indoor temperature is low due to highly energy-efficient buildings or use of a heat pump, the average indoor temperature is often kept at a higher level than when this cost is high.
Our method uses a thermal adaptation factor regression function to account for these prebound and rebound effects over time, and scenario analyses demonstrate the high importance of this for future real energy demand. Currently, the real average energy use is somewhat lower than the technical estimate. In future, however, when highly energy-efficient dwellings and use of local energy sources are much more common, a large share of the possible energy savings in the system is likely to be counteracted by user behaviour. Hence, a future shift towards an aggregated rebound effect in the dwelling stock system is expected. The same phenomena influence aggregated GHG emissions. We demonstrate that it will be very challenging to meet climate mitigation targets in the Norwegian dwelling stock towards 2030 and 2050, particularly when accounting for the rebound effect.
• Socio-economic metabolism and material flow analysis , • Sustainable energy systems , • Infrastructure systems, the built environment, and smart and connected infrastructure
