Scientific publications

There is an urgent need for multi-model studies to characterize uncertainty arising from model heterogeneity. These studies aim to build a more reliable and transparent framework, informing policymakers in the design and implementation of climate policies (Guivarch et al., 2022). In response to this challenge, multiple institutes and organizations have adopted the standardized data template developed by the Integrated Assessment Modeling Consortium (IAMC). This template is maintained by the International Institute for Applied Systems Analysis (IIASA) and aims to standardize and facilitate model intercomparison exercises. For the latest Assessment Report (AR6), the Intergovernmental Panel on Climate Change (IPCC) required all contributors to homogenize their data to enable comparisons and ensure full transparency (V. Krey et al., 2014). This practice has set the foundation for a new open management of the outputs in the area of global scenario analysis. In the case of the Global Change Analysis Model (GCAM) (Calvin et al., 2019), a well-regarded model that has been extensively used for different international and national scenario analysis, the harmonization code has never been documented nor standardized, making it difficult to reproduce outputs and hindering the transparency of results. To overcome these limitations, we have developed gcamreport, an R package that systematizes the transformations of GCAM outputs, generates figures to facilitate the analysis of the results, and allows user interaction with the produced outputs. Furthermore, the tool can be used embedded in a Docker image, which allows users to use the package in a virtual environment without having to install any specific software or library. Finally, each gcamreport release is linked to either a version of GCAM or a study in which GCAM was used, ensuring reproducibility, interoperability, accessibility, and findability, which is in line with the well-known open science principles FAIR and TRUST (Lin et al., 2020; Wilkinson et al., 2016).

Climate action to achieve the Paris Agreement should respect the United Nations Sustainable Development Goals. Here, we use an integrated assessment modelling framework comprising nine climate policy models and quantify the impacts of decarbonisation pathways on Sustainable Development Goals in the European Union at regional and national levels. We show that scenario-consistent assumptions of future socio-economic trends and current climate policies would improve energy- and carbon-related aspects of sustainability and reduce inequalities. Ambitious net-zero emissions pathways would further improve health and agricultural productivity. Furthermore, countries currently lagging in achieving sustainable development goals would see the greatest benefits from ambitious climate action. Negative socio-economic impacts from climate action on poverty, hunger, and economic growth will require specific corrective policies. While our analysis does not quantify the negative effects of less ambitious climate policy, it demonstrates where co-benefits and trade-offs of greenhouse gas mitigation and sustainable development agenda exist and can guide policy formulation.

A rapid phase-out of unabated coal use is essential to limit global warming to below 2 °C. This review presents a comprehensive assessment of coal transitions in mitigation scenarios consistent with the Paris Agreement, using data from more than 1500 publicly available scenarios generated by more than 30 integrated assessment models. Our ensemble analysis uses clustering techniques to categorize coal transition pathways in models and bridges evidence on technological learning and innovation with historical data of energy systems. Six key findings emerge: First, we identify three archetypal coal transitions within Paris-consistent mitigation pathways. About 38% of scenarios are 'coal phase out' trajectories and rapidly reduce coal consumption to near zero. 'Coal persistence' pathways (42%) reduce coal consumption much more gradually and incompletely. The remaining 20% follow 'coal resurgence' pathways, characterized by increased coal consumption in the second half of the century. Second, coal persistence and resurgence archetypes rely on the widespread availability and rapid scale-up of carbon capture and storage technology (CCS). Third, coal-transition archetypes spread across all levels of climate policy ambition and scenario cycles, reflecting their dependence on model structures and assumptions. Fourth, most baseline scenarios—including the shared socio-economic pathways (SSPs)—show much higher coal dependency compared to historical observations over the last 60 years. Fifth, coal-transition scenarios consistently incorporate very optimistic assumptions about the cost and scalability of CCS technologies, while being pessimistic about the cost and scalability of renewable energy technologies. Sixth, evaluation against coal-dependent baseline scenarios suggests that many mitigation scenarios overestimate the technical difficulty and costs of coal phase-outs. To improve future research, we recommend using up-to-date cost data and evidence about innovation and diffusion dynamics of different groups of zero or low-carbon technologies. Revised SSP quantifications need to incorporate projected technology learning and consistent cost structures, while reflecting recent trends in coal consumption.

We attribute variations in key energy sector indicators across global climate mitigation scenarios to climate ambition, assumptions in background socioeconomic scenarios, differences between models and an unattributed portion that depends on the interaction between these. The scenarios assessed have been generated by Integrated Assessment Models (IAMs) as part of a model intercomparison project exploring the Shared Socio-economic Pathways (SSPs) used by the climate science community. Climate ambition plays the most significant role in explaining many energy-related indicators, particularly those relevant to overall energy supply, the use of fossil fuels, final energy carriers and emissions. The role of socioeconomic background scenarios is more prominent for indicators influenced by population and GDP growth, such as those relating to final energy demand and nuclear energy. Variations across some indicators, including hydro, solar and wind generation, are largely attributable to inter-model differences. Our Shapley–Owen decomposition gives an unexplained residual not due to the average effects of the other factors, highlighting some indicators (such as the use of carbon capture and storage (CCS) for fossil fuels, or adopting hydrogen as an energy carrier) with outlier results for particular ambition-scenario-model combinations. This suggests guidance to policymakers on these indicators is the least robust.

Energy system models are important tools to guide our understanding of current and future carbon dioxide emissions as well as to inform strategies for emissions reduction. These models offer a vital evidence base that increasingly underpins energy and climate policies in many countries. In light of this important role in policy formation, there is growing interest in, and demands for, energy modellers to integrate more diverse perspectives on possible and preferred futures into the modelling process. The main purpose of this is to ensure that the resultant policy decisions are both fairer and better reflect people's concerns and preferences. However, while there has been a focus in the literature on efforts to bring societal dimensions into modelling tools, there remains a limited number of examples of well-structured participatory energy systems modelling processes and no available how-to guidance. This paper addresses this gap by providing good practice guidance for integrating stakeholder and public involvement in energy systems modelling based on the reflections of a diverse range of experts from this emergent field. The framework outlined in this paper offers multiple entry points for modellers to incorporate participatory elements either throughout the process or in individual stages. Recognising the messiness of both fields (energy systems modelling and participatory research), the good practice principles are not comprehensive or set in stone, but rather pose important questions to steer this process. Finally, the reflections on key issues provide a summary of the crucial challenges and important areas for future research in this critical field.

Acknowledgements

Thanks to Andrzej Ceglarz and Amanda Schibline from the Renewables Grid Initiative for their valuable input in the workshops held. This research was funded by the Science Foundation Ireland MaREI Centre and ESB Networks under grant number 12/RC/2302/P2 and the US-Ireland R, D & D Partnership Programme funded by Science Foundation Ireland (SFI) together with the National Science Foundation under grant number 16/US-C2C/3290. It also involved researchers from H2020 ENCLUDE (GA: 101022791), EU LIFE programme JUSTEM (project ID 101076151), H2020 PARIS REINFORCE (GA: 820846), Horizon Europe IAM COMPACT (GA: 101056306), Horizon Europe DIAMOND (GA: 101081179), and the Portuguese Science Foundation FCT/MCTES (UID/04085/2020, 2020.00038. CEECIND).

The Paris Agreement rests on individual countries and regions identifying stretching but feasible mitigation pathways. These must be acceptable and achievable in the eyes of a range of stakeholders in those countries or regions, including those from civil society, governments, and businesses. This Special Issue explores a range of feasible yet ambitious greenhouse gas emissions reduction pathways in a diversity of regions/countries of the world, in principle compatible with the goals of the Paris Agreement on climate change. Each of these pathways have been developed using energy system models or whole-economy models, in most cases using mitigation scenarios co-created with a range of policy, civil society, academic, and business stakeholders.

If rapid and just transformations to low-carbon societies are to take place, citizens need to obtain the necessary knowledge and skills to critically examine and choose adequate climate policy options. An emphasis on critical climate education research and implementation is therefore required.

Clean energy technological innovations are widely acknowledged as a prerequisite to achieving ambitious long-term energy and climate targets. However, the optimal speed of their adoption has been parsimoniously studied in the literature. This study seeks to identify the optimal intensity of moving to a green hydrogen electricity sector in Greece, using the OSeMOSYS energy modeling framework. Green hydrogen policies are evaluated, first, on the basis of their robustness against uncertainty and, afterwards, against conflicting performance criteria and for different decision-making profiles towards risk, by applying the VIKOR and TOPSIS multi-criteria decision aid methods. Although our analysis focuses exclusively on the power sector and compares different rates of hydrogen penetration compared to a business-as-usual case without considering other game-changing innovations (such as other types of storage or carbon capture and storage), we find that a national transition to a green hydrogen economy can support Greece in potentially cutting at least 16 MtCO2 while stimulating investments of EUR 10–13 bn. over 2030–2050.

The proposed framework is an intuitively obvious one, yet still serves as a climate technology-specific “checklist” to ensure that any newly proposed technologies or products can succeed. There will be continuous changes to the regulations, infrastructures, and political contexts, in which new technologies will be developed, which is why each consideration is not intended as a one-shot “yes/no” process but must rather be continuously reviewed and reconsidered in light of potentially rapid developments.

Climate change and air pollution are two interconnected major risks for human health. For calculations of the health co-benefits, we combine the Global Change Analysis Model (GCAM) with rfasst, a tool designed to calculate a range of adverse health and agricultural effects attributable to air pollution for alternative scenarios. In summary, health co-benefits associated with current policies and nationally determined contributions are relatively small. The results show that to reduce health impacts attributable to ambient air pollution rapidly, additional policy action that is explicitly designed for tackling air pollutant emissions will be needed.

Our plans to tackle climate change could be thrown off-track by shocks such as the coronavirus pandemic, the energy supply crisis driven by the Russian invasion of Ukraine, financial crises and other such disruptions. We should therefore identify plans which are as resilient as possible to future risks, by systematically understanding the range of risks to which mitigation plans are vulnerable and how best to reduce such vulnerabilities. Here, we use electricity system decarbonization as a focus area, to highlight the different types of technological solutions, the different risks that may be associated with them, and the approaches, situated in a decision-making under deep uncertainty (DMDU) paradigm, that would allow the identification and enhanced resilience of mitigation pathways.

There are multiple ways in which society can theoretically transition from its current carbon-intensive state to a zero-carbon future, ideally fast enough to limit global warming to 1.5^oC above pre-industrial levels. Although the carbon budget associated with this temperature is close to being consumed (IPCC 2021), it still remains achievable - just. Furthermore, we know what needs to be done to achieve it, because we know what contributes to CO₂ emissions. We need energy sources, whose carbon content results in emissions. Reducing both our demand for energy and its carbon intensity (by increasing the share of zero-carbon fuels in our energy mix) is thus of paramount importance. Some industrial manufacturing processes, particularly in cement production, produce CO₂ as a chemical by-product. Capturing that CO₂, finding alternative ways to produce cement, or reducing cement demand, is therefore necessary. Our agriculture, forestry and other land use (AFOLU) can be a net source or sink of CO₂, so making it a large net sink by enhancing carbon dioxide removals (CDR), for example through afforestation, would help. And we hope to have available a range of human-made CDR technologies and measures, such as bioenergy with carbon capture and storage (BECCS), Direct Air Capture (DAC) and enhanced weathering (EW). Scaling these in an
environmentally sustainable way would enhance our chances of keeping within the carbon budget. Finally, rapid progress in reducing short-lived greenhouse gases, particularly methane, would further help our chances of achieving 1.5^oC.

While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the “climate-assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to “1.5 ∘C (with a probability of greater than 50 %) with no or limited overshoot” includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 ∘C for up to a few decades before returning to below 1.5 ∘C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3–0.4 ∘C after peaking at 1.5–1.6 ∘C in 2035–2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss their implications. This article also introduces a “climate-assessment” Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work provides a community tool for assessing the temperature outcomes of emissions pathways and provides a basis for further work such as extending the workflow to include downscaling of climate characteristics to a regional level and calculating impacts.

Current technological improvements are yet to put the world on track to net-zero, which will require the uptake of transformative low-carbon innovations to supplement mitigation efforts. However, the role of such innovations is not yet fully understood; some of these ‘miracles’ are considered indispensable to Paris Agreement-compliant mitigation, but their limitations, availability, and potential remain a source of debate. We evaluate such potentially game-changing innovations from the experts' perspective, aiming to support the design of realistic decarbonisation scenarios and better-informed net-zero policy strategies. In a worldwide survey, 260 climate and energy experts assessed transformative innovations against their mitigation potential, at-scale availability and/or widescale adoption, and risk of delayed diffusion. Hierarchical clustering and multi-criteria decision-making revealed differences in perceptions of core technological innovations, with next-generation energy storage, alternative building materials, iron-ore electrolysis, and hydrogen in steelmaking emerging as top priorities. Instead, technologies highly represented in well-below-2°C scenarios seemingly feature considerable and impactful delays, hinting at the need to re-evaluate their role in future pathways. Experts' assessments appear to converge more on the potential role of other disruptive innovations, including lifestyle shifts and alternative economic models, indicating the importance of scenarios including non-technological and demand-side innovations. To provide insights for expert elicitation processes, we finally note caveats related to the level of representativeness among the 260 engaged experts, the level of their expertise that may have varied across the examined innovations, and the potential for subjective interpretation to which the employed linguistic scales may be prone to.

In a new paper in Nature Energy, Odenweller et al. use uncertainty analysis to derive a probabilistic feasibility space for green hydrogen supply. Their analysis shows that even if electrolysis capacity grows as fast as wind and solar power have done, green hydrogen supply will remain scarce in the short term and uncertain in the long term.