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Increasing realism in quantitative system modelling with respect to the representation of actors, decision-making, and institutions is critical to better understand the transition towards a low-carbon sustainable society. Yet, studies using quantitative system models, which have become a key analytical tool to support sustainability and decarbonization policies, focus on outcomes, therefore overlooking the dynamics of the drivers of change. We explore opportunities that arise from a deeper engagement of quantitative systems modelling with social science. We argue that several opportunities for enriching the realism in model-based scenario analysis can arise through model refinements oriented towards a more detailed approach in terms of actor heterogeneity, as well as through integration across different analytical and disciplinary approaches. Several opportunities that do not require major changes in model structure are ready to be seized. Promising ones include combining different types of models and enriching model-based scenarios with evidence from applied economics and transition studies.

Increasing realism in quantitative system modelling with respect to the representation of actors, decision-making, and institutions is critical to better understand the transition towards a low-carbon sustainable society. Yet, studies using quantitative system models, which have become a key analytical tool to support sustainability and decarbonization policies, focus on outcomes, therefore overlooking the dynamics of the drivers of change. We explore opportunities that arise from a deeper engagement of quantitative systems modelling with social science. We argue that several opportunities for enriching the realism in model-based scenario analysis can arise through model refinements oriented towards a more detailed approach in terms of actor heterogeneity, as well as through integration across different analytical and disciplinary approaches. Several opportunities that do not require major changes in model structure are ready to be seized. Promising ones include combining different types of models and enriching model-based scenarios with evidence from applied economics and transition studies.

Increasing the realism with respect to the representation of actors, decision-making, and institutions is critical to better understand the transition towards a low-carbon sustainable society since actors, decision-making, and institutions are the defining elements of transition pathways. In this paper, we explore how this can be done by conducting a model-based scenario analysis. The increasing focus on implementation and transition dynamics towards long-term objectives requires a better comprehension of what drives change and how those changes can be accelerated. We explore opportunities that arise from a deeper engagement of quantitative systems modeling with socio-technical transitions studies, initiative-based learning, and applied economics. We argue that a number of opportunities for enriching the realism in model-based scenario analysis can arise through model refinements oriented towards a more detailed approach in terms of actor heterogeneity, as well as through integration across different analytical and disciplinary approaches.

The Energy Modeling Forum 28 (EMF28) performed a large-scale model comparison exercise to illustrate different technology pathways for cutting European greenhouse gas emissions by 80% by 2050. Focusing on selected countries (France, Germany, Italy, Sweden, and UK), this paper first analyzes climate and energy policy objectives and debates in the respective countries. It then compares EMF28 model results to the short-term projections of the National Renewable Energy Action Plans (NREAPs) and the long-term transformation pathway given in the European Commission's "Energy Roadmap 2050". It concludes that there is sufficient agreement with the NREAPs and national policies to accept the model results as conceivable scenarios. The scenarios suggest that in the future a variety of different national energy mixes will continue to reflect the different resource bases and preferences of individual Member States. In order to ensure a cost-efficient transformation, it is important to improve coordination between Member State policies and those at the EU level.

Abstract In this paper, we present ten scenarios developed using the IMAGE2.4 framework (Integrated Model to Assess the Global Environment) to explore how different assumptions on future climate and air pollution policies influence emissions of greenhouse gases and air pollutants. These scenarios describe emission developments in 26 world regions for the 21st century, using a matrix of climate and air pollution policies. For climate policy, the study uses a baseline resulting in forcing levels slightly above RCP6.0 and an ambitious climate policy scenario similar to RCP2.6. For air pollution, the study explores increasingly tight emission standards, ranging from no improvement, current legislation and three variants assuming further improvements. For all pollutants, the results show that more stringent control policies are needed after 2030 to prevent a rise in emissions due to increased activities and further reduce emissions. The results also show that climate mitigation policies have the highest impact on SO2 and NOX emissions, while their impact on BC and OC emissions is relatively low, determined by the overlap between greenhouse gas and air pollutant emission sources. Climate policy can have important co-benefits; a 10% decrease in global CO2 emissions by 2100 leads to a decrease of SO2 and NOX emissions by about 10% and 5%, respectively compared to 2005 levels. In most regions, low levels of air pollutant emissions can also be achieved by solely implementing stringent air pollution policies. The largest differences across the scenarios are found in Asia and other developing regions, where a combination of climate and air pollution policy is needed to bring air pollution levels below those of today.