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In 2008 United Kingdom adopted an ambitious target to reduce its greenhouse gas emissions by 80% by 2050, compared to the levels of 1990. This is an unprecedented challenge to the power sector and multiple energy-environment-economic modeling activities have been undertaken to inform the energy policy to deliver this low-carbon transition. The role of governance, choices and strategies of the key actors is increasingly acknowledged as an influential determinant of such transition, but traditional energy-environment-economic models can hardly analyze these aspects. This paper proposes a methodological approach to integrating the governance aspects into energy-environment-economic modeling. In the Realizing Transition Pathways project three qualitative storylines of governance were developed through expert and stakeholder engagement. "Market Rules" storyline envisions that market will deliver low-carbon energy transition. "Central Coordination" storyline envisions increased role of the government in shaping this transition. "Thousand Flowers" storyline envisions the wider civic society leading through bottom-up initiatives. These three qualitative storylines are then translated into a range of modeling assumptions for the D-EXPANSE model (Dynamic version of EXploration of PAtterns in Near-optimal energy ScEnarios). D-EXPANSE has the structure of a bottom-up energy-environment-economic model, but is more flexible and allows for systematic exploration of large numbers of power system transition pathways that are cost-optimal and near optimal. Every governance storyline is thus represented by a large number of quantitative pathways and this provides unique insights into the influence of governance on the future UK power system transition.

Energy scenarios should ideally account for societal feasibility and hence they could be informed by surveys on citizens' preferences. This study surveyed consensus among citizens of France (N = 202), Germany (N = 199), and Poland (N = 200) on their national and EU electricity supply for 2035, considering different demographics, political orientations, and attitudes towards the transition and its governance. Results showed a broad consensus among surveyed citizens who positively viewed hydro, rooftop and open field solar, onshore and offshore wind power, biomass, and electricity savings, and who negatively viewed Carbon Capture and Storage (CCS) and net electricity imports. Citizens on average preferred diversified national and EU scenarios with rapid decarbonization and denuclearization, limited imports from neighboring countries, and small shares of CCS. Such scenarios should be now evaluated by modelers.

AbstractSubsurface energy activities entail the risk of induced seismicity including low‐probability high‐consequence (LPHC) events. For designing respective risk communication, the scientific literature lacks empirical evidence of how the public reacts to different written risk communication formats about such LPHC events and to related uncertainty or expert confidence. This study presents findings from an online experiment (N = 590) that empirically tested the public's responses to risk communication about induced seismicity and to different technology frames, namely deep geothermal energy (DGE) and shale gas (between‐subject design). Three incrementally different formats of written risk communication were tested: (i) qualitative, (ii) qualitative and quantitative, and (iii) qualitative and quantitative with risk comparison. Respondents found the latter two the easiest to understand, the most exact, and liked them the most. Adding uncertainty and expert confidence statements made the risk communication less clear, less easy to understand and increased concern. Above all, the technology for which risks are communicated and its acceptance mattered strongly: respondents in the shale gas condition found the identical risk communication less trustworthy and more concerning than in the DGE conditions. They also liked the risk communication overall less. For practitioners in DGE or shale gas projects, the study shows that the public would appreciate efforts in describing LPHC risks with numbers and optionally risk comparisons. However, there seems to be a trade‐off between aiming for transparency by disclosing uncertainty and limited expert confidence, and thereby decreasing clarity and increasing concern in the view of the public.

Abstract
Projections of granular energy technology diffusion can support decision-making on climate mitigation policies and infrastructure investments. However, such projections often do not account for uncertainties and have low spatial resolution. S-curve models of technology diffusion are widely used to project future installations, but the results of the different models can vary significantly. We propose a method to create probabilistic projections of granular energy technology diffusion at subnational level based on historical time series data and testing how various projection models perform in terms of accuracy and uncertainty to inform the choice of models. As a case study, we investigate the growth of solar photovoltaics, heat pumps, and battery electric vehicles at municipality level throughout Switzerland in 2000–2021 (testing) and until 2050 (projections). Consistently for all S-curve models and technologies, we find that the medians of the probabilistic projections anticipate the diffusion of the technologies more accurately than the respective deterministic projections. While accuracy and probabilistic density intervals of the models vary across technologies, municipalities, and years, Bertalanffy and two versions of the generalized Richards model estimate the future diffusion with higher accuracy and sharpness than logistic, Gompertz, and Bass models. The results also highlight that all models come with trade-offs and eventually a combination of models with weights is needed. Based on these weighted probabilistic projections, we show that, given the current dynamics of diffusion in solar photovoltaics, heat pumps, and battery electric vehicles in Switzerland, the net-zero emissions target would be missed by 2050 with high certainty.

The UKERC Systems Theme has played an important role in the development of the UK's capacity to think systematically about the future of the energy system. Key tools in this process have been the development of scenarios, and the development and use of the MARKAL energy system model. This project reflects on scenarios and on the use and communication of MARKAL, with a view to informing future UKERC work. Specifically, the project conducted retrospective analysis of pre-UKERC energy scenarios for the UK (published from 1977-2002), examined the scenarios produced by the UKERC systems theme, and studied the use and communication of the UK MARKAL model. The diversity of scenario methods and approaches developed within UKERC is valuable, and should be fostered further. Too narrow a range of techniques and teams developing scenarios would risk constraining the ability of UKERC to open up thinking to a wide range of possibilities, perspectives and framings, which history suggests is important. UKERC scenarios have tended to be dominated by futures in which mitigation goals are met, and in which scenario differences are driven by policy or technology, though there are of course exceptions. As UKERC Phase 3 begins, there is a case for reflecting further on the range and type of uncertainties addressed within energy system scenarios, and the diversity of tools and techniques used to generate them. A core tool of the UKERC systems theme has been the UK MARKAL model. The research undertaken for this project indicates that MARKAL has generally been used and communicated appropriately, in part because of good working relationships between government analysts and UKERC researchers. There are also areas in which there is room for improvement, and UKERC Phase 3 provides an opportunity to learn the lessons from previous experience.

The Paris Agreement and SDG13 on Climate Action require a global drop in GHG emissions to stay within a ´well below 2 degrees´ climate change trajectory. Cities will play a key role in achieving this, being responsible for 60 to 80% of the global GHG emissions depending on the estimate. Here we describe how Research and Innovation (R&I) can play a key role in decarbonizing European cities, and the role that research and education institutions can play in that regard. We highlight critical R&I actions in cities, based on three pillars: (1) innovative technology and integration (2) governance innovation and (3) social innovation. Further, we stress the research needs to harmonize climate mitigation and adaptation in cities.

BACKGROUND: The UK government has an ambitious goal to reduce carbon emissions from the housing stock through energy efficiency improvements. This single policy goal is a strong driver for change in the housing system, but comes with positive and negative "unintended consequences" across a broad range of outcomes for health, equity and environmental sustainability. The resulting policies are also already experiencing under-performance through a failure to consider housing as a complex system. This research aimed to move from considering disparate objectives of housing policies in isolation to mapping the links between environmental, economic, social and health outcomes as a complex system. We aimed to support a broad range of housing policy stakeholders to improve their understanding of housing as a complex system through a collaborative learning process. METHODS: We used participatory system dynamics modelling to develop a qualitative causal theory linking housing, energy and wellbeing. Qualitative interviews were followed by two interactive workshops to develop the model, involving representatives from national and local government, housing industries, non-government organisations, communities and academia. RESULTS: More than 50 stakeholders from 37 organisations participated. The process resulted in a shared understanding of wellbeing as it relates to housing; an agreed set of criteria against which to assess to future policy options; and a comprehensive set of causal loop diagrams describing the housing, energy and wellbeing system. The causal loop diagrams cover seven interconnected themes: community connection and quality of neighbourhoods; energy efficiency and climate change; fuel poverty and indoor temperature; household crowding; housing affordability; land ownership, value and development patterns; and ventilation and indoor air pollution. CONCLUSIONS: The collaborative learning process and the model have been useful for shifting the thinking of a wide range of housing stakeholders towards a more integrated approach to housing. The qualitative model has begun to improve the assessment of future policy options across a broad range of outcomes. Future work is needed to validate the model and increase its utility through computer simulation incorporating best quality data and evidence. Combining system dynamics modelling with other methods for weighing up policy options, as well as methods to support shifts in the conceptual frameworks underpinning policy, will be necessary to achieve shared housing goals across physical, mental, environmental, economic and social wellbeing.

The UK government has an ambitious goal to reduce carbon emissions from the housing stock through energy efficiency improvements. This single policy goal is a strong driver for change in the housing system, but comes with positive and negative "unintended consequences" across a broad range of outcomes for health, equity and environmental sustainability. The resulting policies are also already experiencing under-performance through a failure to consider housing as a complex system. This research aimed to move from considering disparate objectives of housing policies in isolation to mapping the links between environmental, economic, social and health outcomes as a complex system. We aimed to support a broad range of housing policy stakeholders to improve their understanding of housing as a complex system through a collaborative learning process.

Europe's capacity to explore the envisaged pathways that achieve its near- and long-term energy and climate objectives needs to be significantly enhanced. In this perspective, we discuss how this capacity is supported by energy and climate-economy models, and how international modelling teams are organised within structured communication channels and consortia as well as coordinate multi-model analyses to provide robust scientific evidence. Noting the lack of such a dedicated channel for the highly active yet currently fragmented European modelling landscape, we highlight the importance of transparency of modelling capabilities and processes, harmonisation of modelling parameters, disclosure of input and output datasets, interlinkages among models of different geographic granularity, and employment of models that transcend the highly harmonised core of tools used in model inter-comparisons. Finally, drawing from the COVID-19 pandemic, we discuss the need to expand the modelling comfort zone, by exploring extreme scenarios, disruptive innovations, and questions that transcend the energy and climate goals across the sustainability spectrum. A comprehensive and comprehensible multi-model framework offers a real example of "collective" science diplomacy, as an instrument to further support the ambitious goals of the EU Green Deal, in compliance with the EU claim to responsible research.

Europe's capacity to explore the envisaged pathways that achieve its near- and long-term energy and climate objectives needs to be significantly enhanced. In this perspective, we discuss how this capacity is supported by energy and climate-economy models, and how international modelling teams are organised within structured communication channels and consortia as well as coordinate multi-model analyses to provide robust scientific evidence. Noting the lack of such a dedicated channel for the highly active yet currently fragmented European modelling landscape, we highlight the importance of transparency of modelling capabilities and processes, harmonisation of modelling parameters, disclosure of input and output datasets, interlinkages among models of different geographic granularity, and employment of models that transcend the highly harmonised core of tools used in model inter-comparisons. Finally, drawing from the COVID-19 pandemic, we discuss the need to expand the modelling comfort zone, by exploring extreme scenarios, disruptive innovations, and questions that transcend the energy and climate goals across the sustainability spectrum. A comprehensive and comprehensible multi-model framework offers a real example of "collective" science diplomacy, as an instrument to further support the ambitious goals of the EU Green Deal, in compliance with the EU claim to responsible research. ; This work was supported by the H2020 European Commission Projects "PARIS REINFORCE" under Grant Agreement No. 820846, "LOCOMOTION" under Grant Agreement No. 821105, "SENTINEL" under Grant Agreement No. 837089, and "NAVIGATE" under Grant Agreement No. 821124. The sole responsibility for the content of this paper lies with the authors; the paper does not necessarily reflect the opinion of the European Commission.