Buildings play a key role in the transition to a low-carbon-energy system and in achieving Paris Agreement climate targets. Analyzing potential scenarios for building decarbonization in different socioeconomic contexts is a crucial step to develop national and transnational roadmaps to achieve global emission reduction targets. This study integrates building stock energy models for 32 countries across four continents to create carbon emission mitigation reference scenarios and decarbonization scenarios by 2050, covering 60% of today's global building emissions. These decarbonization pathways are compared to those from global models. Results demonstrate that reference scenarios are in all countries insufficient to achieve substantial decarbonization and lead, in some regions, to significant increases, i.e., China and South America. Decarbonization scenarios lead to substantial carbon reductions within the range projected in the 2 °C scenario but are still insufficient to achieve the decarbonization goals under the 1.5 °C scenario.

Uncertainty Analysis (UA) and Sensitivity Analysis (SA) offer essential tools to determine the limits of inference of a model and explore the factors which have the most effect on the model outputs. However, despite a wellestablished body of work applying UA and SA to models of individual buildings, a review of the literature relating to energy models for larger groups of buildings undertaken by Fennell et al. (2019) highlighted very limited application at larger scales. This contribution describes the efforts undertaken by a group of research teams in the context of IEA-EBC Annex 70 working with a diverse set of Building Stock Models (BSMs) to apply global sensitivity analysis methods and compare their results. Since BSMs are a class of model defined by their output and coverage rather than their structure and inputs, they represent a diverse set of modelling approaches. Key challenges for the application of SA are identified and explored, including the influence of model form, input data types and model outputs. This study combines results from 7 different modelling teams, each using different models across a range of urban areas to explore these challenges and begin the process of developing standardised workflows for SA of BSMs.

Building stock models are increasingly applied for deriving policy recommendations in achieving climate neutrality of the building sector. However, they are associated with significant uncertainties, which usually are not systematically analysed. We apply the elementary effects method on scenarios calculated with the model Invert/EE-Lab. Among others, we identified parameters relevant for the decision making algorithm within the model as most influential. This has implications on the interpretation of results, in particular for the future mix of energy carriers which show very similar costs and attractiveness. The systematic application of global sensitivity analyses can help to improve the understanding of building stock modelling results and better substantiate related policy conclusions.

In the framework of the Paris Agreement, the European Union (EU) will have to firmly set decarbonization targets to 2050. However, the viability on these targets is an ongoing discussion. The European Commission has made several propositions for energy and climate "roadmaps". In this regard, this paper contributes by analyzing alternative pathways derived in a unique modelling process. As part of the SET-Nav project, we defined four pathways to a clean, secure and efficient energy system taking different routes. Two key uncertainties shape the SET-Nav pathways: the level of cooperation (i.e. cooperation versus entrenchment) and the level of decentralization (i.e. decentralization versus path dependency). All four pathways achieve an 85-95% emissions reduction by 2050. We include a broad portfolio of options under distinct framework conditions by comprehensively analyzing all energy-consuming and energy-providing sectors as well as the general economic conditions. We do this by applying a unique suite of linked models developed in the SET-Nav project. By linking more than ten models, we overcome the traditional limitation of models that cover one single sector while at the same time having access to detail sectoral data and expertise. In this paper, we focus on the implications for the energy demand sectors (buildings, transport, and industry) and the electricity supply mix in Europe and compare our insights of the electricity sector to the scenarios of the recent European Commission (2018a) report "A clean Planet for all".

COP21 led to an agreed target of keeping the increase in global average temperature well below 2 °C compared to pre-industrial levels. Due to its high potential for decarbonisation, the building stock will have to contribute a reduction of at least 85–95% in greenhouse gas (GHG) emissions until 2050. Policy-driven scenario analysis is, therefore, important for assisting policy makers who are called upon to develop a corresponding framework to achieve those targets. The research questions of this paper are (1) Do long-term scenarios (in particular those labelled as ambitious) of energy demand in buildings reflect the COP21 target? (2) If not: What are reasons for the gap in terms of scenario assumptions, in particular, regarding the policy framework in the corresponding scenarios? The method builds on following steps: (1) analysis of GHG-emission reduction in scenarios from the policy-driven, bottom-up model Invert/EE-Lab; (2) compare scenarios among each other and analyse if they are in line with Paris targets; (3) discuss possible explanations for any gaps and the implications on future modelling work and policy making. Results show that scenarios labelled as being “ambitious” for several EU MSs achieve GHG-emission reductions of 56–96% until 2050. However, just 27% of these ambitious scenarios achieve reductions above 85%. The reason is that policies for most of the modelled scenarios were developed together with policy makers and stakeholders, who—for different reasons—were not willing to go beyond a certain stringency in the modelled instruments. In particular, this was the case for regulatory instruments, which show to be essential for achieving ambitious climate targets.

In order to achieve the Paris COP21 agreement, retrofitting activities in the building stock have to be strongly enhanced, therefore individual building renovation roadmaps (IBRR) can be an instrument for guiding building owners through this process. The research question of this paper is: how ambitious should individual building renovation roadmaps be to achieve consistency with future scenarios of the building stock’s energy performance? The methodology applied follows these steps: first, the bottom-up discrete choice building stock model Invert/EE-Lab (www.invert.at) is applied to develop a scenario of building stock related energy demand, CO2-emissions and costs until the year 2050. The scenario is based on the assumption of current or only slightly strengthened policies and results in 77% CO2- emission reductions of the building stock from 2012 to 2050. In the second step, we selected representative building types from the Invert/EE-Lab model scenarios. For these building types, we developed IBRR (individual building renovation roadmaps) based on previous experience and literature research. Further, we calculated the building’s new energy performance after the renovation measures defined in the IBRR. Finally, we analysed to which extent the energy saving through IBRR measures are in line with the simulated scenario. We carried out this study for the case of Germany. Moreover, we restrict the analysis to single-family houses. The results showed that - based on the approach of the IBRR – it would be required that annually about 4-6% of the buildings apply at least one refurbishment measure (change windows or insulate the roof, change heating system, etc.) in order to achieve a scenario, such as the one simulated by the model Invert/EE-Lab.

COP21 led to an agreed target of keeping the increase in global average temperature below 2°C compared to preindustrial levels. The EU-contribution to this target will require GHG-emission reductions of at least 80-95% from 1990-levels until 2050. Due to the high potential for decarbonisation, the building stock will have to achieve at least the same level of reduction. Policy makers are asked to develop a corresponding framework. Important for assisting decision makers in this context are policy driven scenarios. The research questions of this paper are: (1) Do long-term scenarios (and in particular those labelled as ambitious) of energy demand in buildings reflect the COP21 target? (2) If not: What are reasons for the gap? (3) What can we learn for policy making? The method builds on following steps: (1) Analysis of GHG-emission reduction in scenarios from the policy driven bottom-up model Invert/EE-Lab carried out recently for various European countries in several EU and national projects (e.g. ZEBRA2020, progRESsHEAT, Tender for DG Energy on Mapping of Heating/Cooling, etc); (2) compare scenarios among each other and analyse whether the scenarios lead to an achievement of GHG-emission reductions in the range of 80-95% until 2050; (3) identify reasons for possible gaps in GHGemission reductions like insufficient stringency of building codes, deficient economic incentives etc and (4) derive conclusions regarding policy making. Results show that scenarios labelled as being “ambitious” e.g. in ZEBRA2020 for several EU MSs achieve GHG-emission reductions of 56% 95% until 2050, but only three of them above 85%. The reason is that policies have been developed together with policy makers, who were not willing to go beyond certain stringency of modelled instruments. In particular, this was the case for regulatory instruments which turn out to be essential for achieving ambitious climate targets.