Scientific publications

There is scientific consensus that limiting warming in line with the Paris Agreement goals requires reaching net zero CO₂ emissions by mid-century and net negative emissions thereafter. Because of the entrenchment of current fossil fuel energy and feedstock demand estimated in almost all global modelled scenarios, 'abated' fossil fuel and industrial process and product use (IPPU) CO₂ emissions, using carbon capture and storage (CCS) technologies to perform carbon management, are likely to be part of any transition. In addition to fossil fuel combustion, this will be primarily in cement & lime kilns, chemical production, and possibly waste incineration and iron and steel making, in processes producing maximally concentrated CO₂ waste streams. Abated fossil fuel and IPPU CO₂ emissions in the context of recent commitments, however, requires consideration of capture rates for fuel processing and end-use, permanence of storage, reduction of upstream production and end-use fugitive methane, and sufficient means to sequester residual emissions. Based on an assessment of evolving CCS technologies in existing sectors and jurisdictions, criteria are proposed for defining a benchmark for 'abated' fossil fuel and IPPU emissions as where near 100 % GHG abatement is to be eventually achieved, with N₂O and fluorinated gases considered separately. This can be accomplished through: 1) CO₂ capture rates of more than or equal to 95 % of CO₂ emitted; 2) permanent storage of captured emissions; 3) reducing upstream and end-use fugitive methane emissions to <0.5 % and towards 0.2 % of gas production & an equivalent for coal; and 4) counterbalancing remaining emissions using permanent carbon dioxide removal. Application of these criteria to just steel and cement yields estimates of more than or equal to 1.37 Gt CO₂ per year reductions after all other reasonable and lower cost actions are taken. At the same time, we acknowledge the value of capture rates below 95 %, so as long they are designed to enable eventual full abatement through process learning. We also discuss commercialisation and deployment policy for CCS, highlighting the need to integrate these criteria into international climate agreements.

Recent evidence highlights household air pollution as a significant health risk, particularly in the Global South. However, its impacts are frequently overlooked in the integrated assessment models widely used for global scenario analyses. Alternative scenarios with diverse socioeconomic pathways or climate policies could reshape access to affordable clean energy, particularly for low-income groups, directly impacting household air pollution. rhap is an R package developed to estimate health impacts attributable to household air pollution (HAP) under alternative scenarios simulated using the Global Change Analysis Model (GCAM). These impacts are derived using an econometric model that links health outcomes from HAP to various air pollutant emissions and socioeconomic variables, all of which can be extracted from scenario-specific GCAM outputs. Figure 1 provides an overview of the rhap package structure.

Climate change scientific assessments prepared by the Intergovernmental Panel on Climate Change (IPCC) face interconnected dual challenges: the exponential growth of literature, hindering synthesis efficiency, and the increasing length of its reports, impeding accessibility. Building upon the emerging discussion of adopting artificial intelligence (AI) tools in scientific assessments, this essay develops specific operational and governance frameworks to guide the IPCC’s integration of these tools. It makes three distinct contributions. First, it develops a systematic framework for AI-augmented evidence synthesis, detailing how machine learning (ML) can be integrated into each stage of the assessment workflow. Second, it provides a critical analysis of Large Language Models' (LLMs) use for reports communication through the lens of ‘addressable’ versus ‘inherent’ limitations, clarifying which risks require technical solutions versus those that demand robust governance. Finally, it proposes a novel governance structure for the IPCC based on two institutional roles, the ‘producer’ and the ‘assessor’ of AI products, to ensure scientific integrity is maintained. This essay provides a clear path for the responsible, expert-led integration of AI, ensuring it serves to augment, not replace, human expertise.

Addressing 21𝑠𝑡-century challenges, such as climate change, demands policies that not only advance social justice but also prevent the exacerbation of existing inequalities. While Integrated Assessment Models (IAMs) are a fundamental tool to carry out impact analyses of policies from a holistic perspective, micro-simulation models are crucial for identifying heterogeneous socioeconomic impacts and ensuring fairer and more targeted policies. medusa is an R package designed for conducting distributional analyses, either independently or in conjunction with other models, including IAMs. The extensive database in which the microsimulation model is based allows highly disaggregated results by considering a wide range of socioeconomic and demographic characteristics of households, such as income level, place of residence, type of family, and feminization degree. The package combines this detailed household data with the calculation of energy and transport poverty indices. 

COVID-19 reshaped global economic priorities at the time, with recovery packages offering unprecedented fiscal stimuli aimed at revitalising economies from the impacts of the pandemic and associated policy responses—including lockdowns. While these packages were quickly framed as an opportunity for aligning socioeconomic recovery spending with near- and longer-term climate goals, early assessments of their decarbonisation footprint were constrained by and/or oriented towards optimistic interpretations of the limited information available then. We examine the potential of recovery packages to bridge the medium- and long-term climate ambition gap towards meeting the Paris Agreement goals. To enable such a comprehensive assessment, we first develop an open-access database of global green recovery measures. Second, we explicitly translate these measures as inputs into three Integrated Assessment Models, to assess their implications for energy systems, emissions, and technology development globally. Third, we quantify the missed opportunity in global recovery spending in terms of accelerating the clean energy transition, by exploring a theoretical reallocation of funding from energy affordability measures towards green technologies. Our results suggest that, while the actual synthesis of global recovery funding may not be sufficient to boost climate efforts towards meeting the Paris climate goals with sustained effects post-2030, redirecting part of the funds to low-carbon technologies could accelerate decarbonisation and electrification trends in some sectors. Whether or not the global COVID-19 recovery portfolio is adjusted to better support transition goals, recovery funds alone cannot guarantee a comprehensive and effective transition; this requires complementary systemic reforms, targeted sectoral strategies, and international collaboration.

Electricity supply transition to reach carbon neutrality in Europe is expected to bring air quality and health co-benefits, but their regional distribution has not been investigated in detail. This study quantifies these co-benefits for 250 European electricity scenarios in 2035 across 296 sub-national regions. The study links a spatially-explicit electricity sector model with an air quality and health impact model and then accounts for susceptibility and vulnerability of populations to adverse health effects. In case of low-carbon transition, direct PM2.5 concentrations attributable to European electricity generation in 2035 could be reduced by 45–99% compared to a system with the generation capacities of 2018. Depending on the system’s make-up, health co-benefits can vary significantly, as does their regional distribution. Focus on the minimum system costs leads to 15 times higher continent-wide excess deaths and to higher regional inequality than the scenario with minimum air pollutant emissions, which would almost entirely eliminate PM2.5-related mortality attributable to electricity generation. The most vulnerable regions (Balkans, Northern Germany, Southeast France, and the West Midlands in England) would benefit from higher air quality co-benefits than the continental average.

Renewable hydrogen has emerged as a potentially critical energy carrier for achieving climate change mitigation goals. International trade could play a key role in meeting hydrogen demand in a globally decarbonised energy system. To better understand this role, we have developed a modelling framework that incorporates hydrogen supply and demand curves and a market equilibrium model to maximize social welfare. Applying this framework, we investigate two scenarios: an unrestricted trade scenario where hydrogen trade is allowed between all regions globally, and a regional independence scenario where trade is restricted to be intra-regional only. Under the unrestricted trade scenario, global hydrogen demand could reach 234 Mt by 2050, with 31.2% met through international trade. Key trade routes identified include North Africa to Europe, the Middle East to Developing Asia, and South America to Japan and South Korea. In the regional independence scenario, most regions could meet their demand domestically, except for Japan and South Korea due to self-insufficiency. Finally, this analysis reveals that producers in North Africa and South America are likely to gain more economic value from international trade compared to other producing regions. The results offer key insights for policymakers and investors for shaping future hydrogen trade policies and investment decisions.

Charting future emissions pathways is a central tenet of IPCC assessment reports (AR), yet it is unclear how underlying drivers (including around policy and technology) have influenced the evolution of emissions pathways. Here we compare scenarios in AR5 and AR6 and find that scenarios without specific climate policies enforced have shifted lower in each scenario generation, owing to falling low-carbon technology costs and reduced expectations for economic growth, reducing fossil-fuel shares in energy and industry. Mitigation pathways consistent with 1.5–2 °C have seen increasing electrification rates and higher shares of variable renewables in electricity in more recent scenario generations, implying reduced reliance on coal, nuclear, bioenergy and carbon capture and storage, reflecting changing costs. Despite the shrinking carbon budget due to insufficient recent climate action, mitigation costs have not increased given more optimistic low-carbon technology cost projections. Moving forward, scenario producers must continually recalibrate to keep abreast of technology, policy and societal developments to remain policy relevant.

Every five to seven years, the Intergovernmental Panel on Climate Change (IPCC) convenes the climate science community to assess the latest knowledge on climate change relevant to policy-makers. This generally takes the form of Assessment Reports (AR) covering the scientific basis of climate change, its impacts and future risks, and options for adaptation and mitigation. With each cycle, these reports have grown in scope, length, number of referenced papers, and underpinning datasets. During the sixth assessment cycle, a large-scale collective effort went into archiving digital products assessed and generated through the IPCC process. The main objectives driving this initiative are making IPCC’s work more transparent, improving the reproducibility and reusability of the assessment outcomes, better utilization of the services of the IPCC Data Distribution Centre (DDC), and, more generally, compliance with best practices in open science. This paper expands on the motivations for the curation and preservation of digital objects in the IPCC. It gives an overview of how FAIR (Findable, Accessible, Interoperable, Reusable) and open data principles have been implemented in practice and explores some of the successes and setbacks of the AR6 experience. It concludes with recommendations for consolidation and expansion of the approach for AR7. These include a tighter integration of digital curation activities in the IPCC timeline and workflows, better support of IPCC authors and contributors through early training and use of suitable software, improved standardization and harmonization of data and software handling across Working Groups (WGs), and close collaboration with key external data providers and research organizations.

The implementation of asymmetric emission reduction policies can not only increase the cost of reducing emissions but also reduce the effectiveness of climate policies themselves, leading to policy inefficiencies such as carbon leakage. This paper investigates the impact of asymmetric emission reduction policies on the cost-effectiveness and efficiency of climate strategies in North America. Using a model inter-comparison approach, which combines two bottom-up global models and one top-down global model, this study assesses the effects of such policies on fuel substitution, global fossil fuel trade, and emissions in North America and globally. It is the first work where a multi-model approach is used for exploring how different energy systems react to asymmetric carbon policies. This provides critical insights into regional policy design within a global emissions framework. Quantitatively, the study reveals that asymmetric carbon pricing can lead to more than 60% global emissions reduction in certain models, but can also drive trade distortions, where U.S. exemptions result in emissions rising by more than 10% compared to reference scenarios. Qualitatively, significant fuel substitution patterns across Canada, Mexico, and the U.S. demonstrate increased coal consumption when carbon prices are unevenly applied. While no global emission increase was observed, asymmetric policies result in inefficiencies between local policy costs and emissions reduction outcomes, such as rising fossil fuel trade in non-abating regions. The findings suggest that harmonising carbon policies across regions would reduce inefficiencies and minimise carbon leakage.

Climate stabilisation requires the mobilization of substantial investments in low- and zero-carbon technologies, especially in emerging and developing economies. However, access to stable and affordable finance varies dramatically across countries. Models used to evaluate the energy transition do not differentiate regional financing costs and therefore cannot study risk-sharing mechanisms for renewable electricity generation. In this study, we incorporated the empirically estimated cost of capital differentiated by country and technology into an ensemble of five climate–energy–economy models. We quantified the additional financing cost of decarbonisation borne by developing regions and explored policies of risk premium convergence across countries. We found that alleviating financial constraints benefits both climate and equity as a result of more renewable and affordable energy in the developing world. This highlights the importance of fair finance for energy availability, affordability and sustainability, as well as the need to include financial considerations in model-based assessments.

To effectively meet the ambitious objectives set by the Paris Agreement, gaining a deeper understanding of the relationships between the key technologies involved in mitigation activities is pivotal. This research uses Bayesian Network (BN) methodology on a large ensemble of energy system model runs, aiming to shed light on the complex interdependencies, and related uncertainties, among the various technologies within the pathways. We specifically focus on tracking the evolution and interconnectedness of technology portfolios over time, enabling dynamic assessments of the impacts linked to specific deployment strategies. The results suggest that prioritizing early-stage transitions within the building sector is imperative and the consistent deployment of district heating emerges as a pivotal element in the long-term plans for decarbonisation. In the power sector, the rising trends in electrification and the substantial growth in low-carbon power plants and wind energy deployment, underscore the urgency for adaptable strategies within the power sector. Notably, the integration of bioenergy with carbon capture and storage (BECCS) also emerges as a crucial technology, offering a means to counterbalance emissions from carbon-intensive industries. The BN-based approach provides decision makers a powerful tool for comprehensive, informed, and systematic planning as they navigate towards a carbon-neutral future, but it is also crucial to acknowledge the reliance of our analysis on assumptions inherent in energy system models. Studies using different assumptions and model structures are needed to confirm the generalizability of our findings.

We reflect on the development of digital twins of the Earth, which we associate with a reductionist view of nature as a machine. The projects of digital twins deviate from contemporary scientific paradigms in the treatment of complexity and uncertainty, and does not engage with critical and interpretative social sciences. We contest the utility of digital twins for addressing climate change issues and discuss societal risks associated with the concept, including the twins' potential to reinforce economicism and governance by numbers, emphasizing concerns about democratic accountability. We propose a more balanced alternative, advocating for independent institutions to develop diverse models, prioritize communication with simple heuristic-based models, collect comprehensive data from various sources, including traditional knowledge, and shift focus away from physics-centered variables to inform climate action. We argue that the advancement of digital twins should hinge on stringent controls, favoring a nuanced, interdisciplinary, and democratic approach that prioritizes societal well-being over blind pursuit of computational sophistication.

Achieving the long-term temperature goal of the Paris Agreement relies on every actor maximising their effort to reduce emissions. Generic targets claiming a basis in science have been used to justify inequitable efforts that insufficiently stretch the ambition of the best-resourced countries and companies.

Hydrogen has gained significant attention as a possibly important energy vector in the pursuit of climate change mitigation objectives. Global demand for renewable hydrogen is anticipated to increase across many decarbonization scenarios. To meet this demand, many countries have unveiled strategies aimed at bolstering domestic low-carbon hydrogen production or facilitating imports. Within this context, international trade has emerged as a means of importing hydrogen from regions with low-cost production capabilities. However, investment decisions in the development of international hydrogen markets are moving slowly due to large uncertainties regarding the magnitude of future demand and willingness to pay for hydrogen in key end- use applications.

In this study, we develop a novel modelling framework capable of simulating global hydrogen market equilibrium and international trade scenarios in the long-term future. Our methodology includes the development of supply and demand curves, as well as a global hydrogen trade model that takes into account various supply chain options. Using this framework, we are able to derive quantitative insights into equilibrium supply and demand, pricing dynamics, trade flows, costs, and many more. We apply this framework to investigate the optimal development of hydrogen markets in 2050 under a 1.5°C climate change mitigations scenario. Our findings indicate that new hydrogen sectors could see a global demand surge to 195.2 Mt, with international trade constituting a quarter of this demand.

The year 2015 was an important milestone in the world’s struggle for sustainability. Although mostly remembered for the landmark Paris Agreement, which formalised and operationalised a mechanism for globally coordinated and cooperative efforts to address the climate crisis, it also featured the UN-wide adoption of the 2030 Agenda for Sustainable Development, embodied in seventeen distinct yet highly intertwined dimensions—the Sustainable Development Goals (SDGs). These inter alia include poverty and hunger elimination, alleviating social and gender inequalities, fostering peace and the development of strong institutions, making production responsible, environmental and biodiversity protection, and achieving good health and well-being.

Income and its distribution profile are important determinants of residential energy demand and carry direct implications for human well-being and climate. We explore the sensitivity of residential energy systems to income growth and distribution across SSP-RCP scenarios using a global, integrated, multisector dynamics model, GCAM, which tracks national/regional household energy services and fuel choice by income decile. Nation/region energy use patterns across deciles tend to converge over time with aggregate income growth, as higher-income consumers approach satiation levels in floorspace and energy services. However, in some regions, existing within-region inequalities in energy consumption persist over time due to slow income growth in lower income groups. Due to continued differences in fuel types, lower income groups will have higher exposure to household air pollution, despite lower contributions to greenhouse gas emissions. We also find that the share of income dedicated to energy is higher for lower deciles, with strong regional differences.

As a key material for manufacturing clean energy technologies, steel is crucial for energy transition, but its production causes 2.6 Gton of CO2 emissions at global level each year. In 2020 the European Union (EU) set a net-zero emissions target by 2050, fostering innovation in the steel industry to reduce its environmental impact. However, a scenario-oriented and technologically comprehensive analysis assessing prospected environmental and market implications of steel decarbonisation strategies remains a gap, which is addressed in this paper. The analysis adopts a hybrid input-output-based LCA model built in the MARIO framework, extending the Exiobase database to represent the supply chains of the most promising low-carbon steelmaking technologies in the EU, such as hydrogen- or charcoal-injected blast furnaces and natural gas- and hydrogen-based direct reduction routes. The penetration of these technologies is explored by formulating scenarios resembling European climate targets. The results show a reduction in the carbon footprint of steel across all scenarios, ranging up to -26% in 2030 and to -60% in 2050. However, the extent of footprint reduction is highly dependent on the share of clean electricity in the European supply mix, highlighting the relevance of holistic decarbonization strategies. Economic implications affect steel prices, which rise up to 25% in 2030 and 56% in 2050, opening discussions on the need for suitable policies such as CBAM to avoid protectionism and encourage international technological progress.

Even though we have known about climate change for more than 30 years, humans are releasing higher amounts of greenhouse gases, like carbon dioxide, than ever before. Scientists have shown that stopping carbon dioxide emissions could prevent global warming from getting worse. The single biggest source of greenhouse gas emissions is burning fossil fuels for electricity or transportation. Technologies like solar and wind power, electric vehicles, and advanced batteries can replace fossil fuels and help reduce emissions while also decreasing other problems like air pollution. Many countries have promised to stop their carbon dioxide emissions, and if their promises are backed up with laws, then global warming could be limited. Unfortunately, current laws are not good enough. We need to ensure that countries meet their promises, so that society can avoid the worst effects of global warming.

As the imperative to address climate change intensifies, understanding the effectiveness of policy interventions becomes paramount. In the context of addressing these urgent challenges and given the inadequacy of current policies to address this issue, this study examines the extent to which Nationally Determined Contributions (NDCs) and Long-Term Targets (LTTs) can contribute to achieving ambitious climate goals. Recognizing the critical need for effective climate action, we employ the advanced modelling tools PROMETHEUS and GCAM to assess the implications of different scenarios–Current Policies (CP), Nationally Determined Contributions (NDC), and combination of NDCs with Long-Term Targets (NDC_LTT)–on the future development of energy system and emission. This study, by employing these well-known models, seeks to provide an improved understanding of the impacts of NDCs on global emission trajectories and whether the integration of NDCs and LTTs can help close the gap towards Paris-compatible pathways. The study analyzes various sectors including buildings, transportation, electricity generation, and industry to provide insights into the limitations of existing policies and the potential of enhanced commitments to drive transformative changes in a global scale. The effectiveness of these policies varies across different sectors, highlighting the challenges that need to be addressed for achieving the required emission reduction targets in the medium- and long-term. Key findings indicate significant shifts in energy consumption, fuel mix, technology adoption, and emission trajectories, particularly under the synergistic action represented by the NDC_LTT scenario.

The reduction of the EU's pipeline gas imports from Russia because of the Russian war against Ukraine has had severe economy-wide implications for the bloc. Using a multisector integrated assessment model (GCAM), we find that a potential complete cut-off of Russian pipeline gas exports to the EU unevenly impacts the energy mix and gas prices across subregions within the EU, depending on their access to alternative gas pipelines and liquefied natural gas infrastructure. The restrictions also affect global gas infrastructure capacity additions, asset stranding, and trade dynamics. Our results show that the Fit-for-55 policy framework already improves the EU's resilience against a cut-off of Russian pipeline gas, while additional improvements in energy efficiency and renewable targets could further soften impacts.

In every Intergovernmental Panel on Climate Change (IPCC) Assessment cycle, a multitude of scenarios are assessed, with different scope and emphasis throughout the various Working Group reports and special reports, as well as their respective chapters. Within the reports, the ambition is to integrate knowledge on possible climate futures across the Working Groups and scientific research domains based on a small set of “framing pathways” such as the so-called representative concentration pathways (RCPs) in the Fifth IPCC Assessment Report (AR5) and the shared socioeconomic pathway (SSP) scenarios in the Sixth Assessment Report (AR6). This perspective, initiated by discussions at the IPCC Bangkok workshop in April 2023 on the “Use of Scenarios in AR6 and Subsequent Assessments”, is intended to serve as one of the community contributions to highlight the needs for the next generation of framing pathways that is being advanced under the Coupled Model Intercomparison Project (CMIP) umbrella, which will influence or even predicate the IPCC AR7 consideration of framing pathways. Here we suggest several policy research objectives that such a set of framing pathways should ideally fulfil, including mitigation needs for meeting the Paris Agreement objectives, the risks associated with carbon removal strategies, the consequences of delay in enacting that mitigation, guidance for adaptation needs, loss and damage, and for achieving mitigation in the wider context of societal development goals. Based on this context, we suggest that the next generation of climate scenarios for Earth system models should evolve towards representative emission pathways (REPs) and suggest key categories for such pathways. These framing pathways should address the most critical mitigation policy and adaptation plans that need to be implemented over the next 10 years. In our view, the most important categories are those relevant in the context of the Paris Agreement long-term goal, specifically an immediate action (low overshoot) 1.5 °C pathway and a delayed action (high overshoot) 1.5 °C pathway. Two other key categories are a pathway category approximately in line with current (as expressed by 2023) near- and long-term policy objectives, as well as a higher-emission category that is approximately in line with “current policies” (as expressed by 2023). We also argue for the scientific and policy relevance in exploring two “worlds that could have been”. One of these categories has high-emission trajectories well above what is implied by current policies and the other has very-low-emission trajectories which assume that global mitigation action in line with limiting warming to 1.5 °C without overshoot had begun in 2015. Finally, we note that the timely provision of new scientific information on pathways is critical to inform the development and implementation of climate policy. Under the Paris Agreement, for the second global stocktake, which will occur in 2028, and to inform subsequent development of nationally determined contributions (NDCs) up to 2040, scientific inputs are required by 2027. These needs should be carefully considered in the development timeline of community modelling activities, including those under CMIP7.

Off-grid photovoltaic systems have been proposed as a panacea for economies with poor electricity access, offering a lower-cost “leapfrog” over grid infrastructure used in higher-income economies. Previous research examining pathways to electricity access may understate the role of off-grid photovoltaics as it has not considered reliability and carbon pricing impacts. We perform high-resolution geospatial analysis on universal household electricity access in Sub-Saharan Africa that includes these aspects via least-cost pathways at different electricity demand levels. Under our “Tier 3" demand reference scenario, 24% of our study’s 470 million people obtaining electricity access by 2030 do so via off-grid photovoltaics. Including a unit cost for unmet demand of 0.50 US dollars ($)/kWh, to penalise poor system reliability increases this share to 41%. Applying a carbon price (around $80/tonne CO₂-eq) increases it to 38%. Our results indicate considerable diversity in the level of policy intervention needed between countries and suggest several regions where lower levels of policy intervention may be effective.

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.