• Energy Research

Abstract Limiting global warming to “well below 2°C” as stated in the Paris Agreement requires ambitious emissions reductions from all sectors. Rapid technology cost declines in the energy sector are changing energy investment and emissions, even with the weak climate policies currently in place. We assess how energy supply costs and carbon dioxide removal (CDR) availability affect mitigation by performing a sensitivity analysis with the energy-economy-climate model REMIND. We use new scenarios with carbon price paths that aim to reduce the frequently seen temperature overshoot. Further, we measure the sensitivities of mitigation indicators to the costs of technologies across economic sectors. We assess the sensitivity to nine techno-economic parameters: the costs of wind, solar, biomass, gas, coal, oil, nuclear, and electric/hydrogen vehicles, as well as the injection rate of Carbon Capture and Storage (CCS). While technology costs play a role in shaping optimal pathways, we find that transport sector costs affect the economics of deep decarbonization, whereas costs of renewables are more important for scenarios under weak climate policies. This further highlights the value of renewable energy deployment as a no-regrets option in climate policy. In terms of the sensitivity of model outputs, economic indicators become more sensitive to costs than emissions, with increasing policy stringency.

Abstract The tightened climate mitigation targets of the EU green deal raise an important question: Which strategy should be used to achieve carbon emissions net neutrality? This study explores stakeholder-designed narratives of the future energy system development within the deep decarbonization context. European carbon net-neutrality goals are put under test in a model comparison exercise using state of the art Energy-Environment-Economy (E3) models: ETM-UCL, PRIMES and REMIND. Results show that while achieving the transition to carbon neutrality by mid-century is feasible under quite different future energy systems, some robust commonalities emerge. Electrification of end use sectors combined with large-scale expansion of renewable energy is a no-regret decision for all strategies; Carbon Dioxide Removal (CDR) plays an important role for achieving net-neutral targets under all scenarios, but is most relevant when demand-side changes are limited; hydrogen and synthetic fuels can be a relevant mitigation option for mid-century mitigation in hard-to-abate sectors; energy efficiency can reduce the supply system strain. Finally, high carbon prices (300-900€/tCO2) are needed under all strategies in order to achieve carbon net neutrality in 2050.

Background: The transition to a carbon neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system models (ESMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESMs have rarely been compared or linked with one another. Methods: This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables We define harmonised regions and a subset of shared result variables that enable the comparison of results across the models. Results: The results highlight similarities and differences on final electricity demand, electricity supply and hydrogen across three levels of aggregation. However, the differences between the regional aggregation of the models limit detailed analysis. Conclusions: This first-of-its-kind comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind.

Cost degression in photovoltaics, wind-power and battery storage has been faster than previously anticipated. In the future, climate policy to limit global warming to 1.5–2 °C will make carbon-based fuels increasingly scarce and expensive. Here we show that further progress in solar- and wind-power technology along with carbon pricing to reach the Paris Climate targets could make electricity cheaper than carbon-based fuels. In combination with demand-side innovation, for instance in e-mobility and heat pumps, this is likely to induce a fundamental transformation of energy systems towards a dominance of electricity-based end uses. In a 1.5 °C scenario with limited availability of bioenergy and carbon dioxide removal, electricity could account for 66% of final energy by mid-century, three times the current levels and substantially higher than in previous climate policy scenarios assessed by the Intergovernmental Panel on Climate Change. The lower production of bioenergy in our high-electrification scenarios markedly reduces energy-related land and water requirements. The impact of rapidly falling costs of renewable energy and battery technology on long-term climate stabilization pathways is not well understood. Luderer et al. show that reduced renewable costs and climate policies will make electricity the cheapest energy carrier and can lead to electricity accounting for nearly two-thirds of global energy use by mid-century.

AbstractEnergy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies.

Background The transition to a climate neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system optimisation models (ESOMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESOMs have rarely been compared or linked with one another. Methods This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables. We define harmonised regions and a subset of shared result variables that enable the comparison of scenario results across the models. Results The results highlight how power generation and demand development are related and driven by regional and sectoral drivers. They also show that demand developments like for hydrogen can be linked with power generation potentials such as onshore wind power. Lastly, the results show that the role of nuclear power is related to the availability of wind resources. Conclusions This comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESOM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind. The comparison shows that regional aggregations might conceal differences within regions that are potentially of interest for national policy makers thereby indicating a need for national-level analysis.