The sustainable development agenda involves complex transformations that significantly interact with climate action. Developing long-term sustainable development pathways typically relies on integrated assessment models (IAMs) by exploring co-benefits and trade-offs between climate policy and sustainable development goals (SDGs), and hardcoding policies into models to understand sustainability implications of climate action. However, most IAMs apply least-cost approaches for defining marginal mitigation efforts, disproportionally favouring maximising performance on economic rather than broader sustainability indicators. Here, we introduce an integrated approach leveraging multi-objective optimisation algorithms linked with IAMs, and Monte Carlo simulations to simultaneously optimise mitigation in terms of multiple SDG indicators, while considering stochastic uncertainty. Our aim is to optimise global mitigation effort allocation across economic sectors based on the performance in indicators along multiple SDGs and assuming a wide range of socioeconomic assumptions, towards developing long-term pathways with balanced sustainability performance. We validate this approach with the GCAM model and the AUGMECON-R algorithm, identifying trade-offs in sectoral and sustainability performance, notably between economic and environmental dimensions. Finally, we highlight the advantages of our approach to inform climate policy by comparing our SDG-balanced pathways with least-cost ones.
Participatory approaches have been argued to bring a more diverse range of views into the ΙΑΜ process, by building a better understanding of the social context and supporting more inclusive decision-making. In IAM COMPACT, we have designed a Policy Response Mechanism (PRM), a co-creation nine step process that facilitates collaboration among modelling teams and with stakeholders that runs throughout the project in two cycles. The PRM dynamically responds to changing policy priorities, aiming for policy relevance, knowledge exchange, and enhanced trust, by providing different layers of inputs and making modelling socially/politically realistic. Stakeholder engagement in IAM COMPACT is organised into themes (for stakeholders within the EU) and regions (for stakeholders outside the EU), which were collaboratively determined within the project. For the themes, the aim was to have a broad enough coverage to capture a range of issues, but also sufficiently selective to lead a clear research agenda later in the project. The first cycle of PRM concluded with seven co-created modelling studies. During our second cycle, 46 questions emerged from high-level exchanges with policy stakeholders (forming the Policy Steering Groups), which were grouped into proposals for seven new modelling studies. These proposals were in turn grouped into four overreaching themes and discussed with a wider policy audience (forming the Core Working Groups) selected on geographical and sectoral criteria. The consultative process helped us evaluate the relevance of policy issues, refine the scope of research questions, and establish a balanced group of stakeholders to participate.
Climate change mitigation strategies face disruption from multiple sources: extreme climate events, socioeconomic crises, geopolitical conflicts, technological breakthroughs, as well as the abrupt transitions and disruptive actions entailed by achieving the stringent Paris Agreement goals. While these disruptive events can fundamentally alter long-term mitigation scenarios, the current literature does not sufficiently assess their implications. Existing long-term mitigation scenario narratives and modelling frameworks, using Integrated Assessment Models (IAMs), lack systematic approaches to analyse their impacts. To address this gap, we introduce the Disruptive Events-Resilient Pathways (DERPs) framework, which provides structured narratives to systematically explore and assess the resilience of climate actions to the impacts of external disruptions and entailed abrupt transitions. To operationalise this framework, we employ multiple IAMs to analyse case studies of distinct disruptions: intensifying heatwaves and droughts affecting energy systems, and the rapid uptake of Direct Air Carbon Capture and Storage (DACCS) technology. Our analysis highlights the inherent limitations of IAMs in capturing the full complexity of disruptive events. We offer novel methodological approaches to overcome them. Our results provide insights into the interplay between the impacts of disruptive events and mitigation scenarios.
We introduce a conceptual framework, alongside qualitative narratives and use cases for validation, to guide the development of Disruptive Events-Resilient Pathways (DERPs). This framework systematically explores the impacts of disruptive events on mitigation and adaptation strategies, allowing to evaluate their resilience to such disruptions. Similar to the widely-adopted SSP scenario framework, which maps socioeconomic developments onto the extent of challenges to mitigation and adaptation (O’Neill et al., 2017), the DERPs framework comprises two dimensions, thereby enabling breaking the developed spectrum into four blocks of narratives, plus an intermediate narrative that reflects current trends. We further reflect on the connection between the DERP and SSP frameworks in the discussion section below.
The DERP dimensions and underlying narratives draw on concrete examples, to make the framework more comprehensive and comprehensible, but remain sufficiently generalisable to allow the framework to serve as a blueprint for conducting similar types of mitigation and adaptation analyses in the future. In determining the two dimensions of the DERP framework, we benefit from van Ginkel et al. (2020), who had proposed two dimensions for exploring how climate change tipping points can cause socioeconomic tipping points (SETPs). In the DERP framework, the focus shifts from climate change tipping points to disruptive events as the drivers of socioeconomic impacts, and on assessing societal resilience to these impacts. Accordingly, the two dimensions are defined as follows:
- climate action effectiveness: this refers to significant and deliberate change in the way societies and systems transition towards mitigating, or preparing for (i.e. adapting to), climate change
- resilience to socioeconomic impacts: this refers to the capacity to withstand unintended shifts in socioeconomic structures that may occur due to abrupt transitions or insufficient mitigation or adaptation failure, and the resulting climate change impacts.
The transition to a low-carbon economy in the EU requires a balance between collective ambition and national priorities. Comparing bottom-up trajectories of National Energy and Climate Plans (NECPs) with top-down EU-wide targets offers valuable insights into the “cost of non-coordination” and its implications for equitable effort-sharing among Member States. In this study, we derive the energy system transformations required at the EU Member State level to achieve the EU’s net-zero target and examine how these transitions differ between EU-level and state-level policies in the short term. Our scenarios are based on (a) the emissions reduction policies, including those outlined in the ‘Fit for 55’ package as well as the NECPs, following which emissions constraints are set at both the EU and Member State levels (policy-driven), and (b) cost-optimal model pathways achieving equivalent GHG emission mitigation as (a) at both levels but without any explicit policies modelled (target-driven). We use two well-established integrated assessment models, GCAM-Europe and TIAM-EU, and soft-link them with a detailed electricity system model (EXPANSE) to additionally derive future trajectories of electricity demand, final energy mix, electricity and storage capacities, investments in transmission and distribution infrastructure, and electricity prices. Finally, we assess how the European (and national) energy systems differ between the two scenarios as well as how effort-sharing varies among Member States when comparing the optimal pathways derived at the EU level to those developed for individual Member States.
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 (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.
Addressing the major challenges of the 21st century, such as climate change, will require complex and ambitious policies that promote social justice. To do so, it is necessary to design efficient policies that do not exacerbate existing inequalities, such as gender or income inequality. In this sense, it is essential to carry out impact analyses of policies from a holistic perspective that evaluates the economy, energy, land, and water systems in an integrated manner before implementing them. While Integrated Assessment Models (IAMs) have been a fundamental tool in the past, micro-simulation models for distributional analysis have the advantage of providing more heterogeneous results that help to more robustly identify the socio-economic impacts of the policies to be implemented. These analyses make it possible to identify the people who will be most affected by policies and to implement compensatory measures to make the policy fairer. Thus, the combination of both models (IAMs and microsimulation models) can provide valuable results for decision making. MEDUSA is an R package that allows the development of distributional analyses in isolation or in connection with other models such as GCAM. Its extensive database allows for highly disaggregated results, taking into account numerous socio-economic and demographic characteristics of households, such as income level, place of residence, type of family or the degree of feminisation of the household. At the moment, the prototype works for Spain, but the idea is to extend it to all EU countries in the short term. However, the package could be extended to all countries that are able to provide the raw data of the model.
Climate change is often seen as an equity problem, as it is caused primarily by richer countries and households, while its impacts are generally expected to affect poorer countries and households significantly stronger. Climate policy aiming at mitigating these impacts, however, can also have a regressive impact on societies, unless it is designed such that the costs of mitigation are shared progressively depending on wealth differences. At the same time, historical energy transitions have often been driven by wealthy consumers demanding higher quality goods and services, which consequently grew from niche to mainstream technologies. Particularly the transportation sector is a sector difficult to decarbonise, while there are significant differences in contribution between poorer and wealthier users. This study uses a global integrated assessment model (GCAM) with 10 different income groups for each of the 32 regions to compare several decarbonisation scenarios for passenger transportation. On the one hand, implementing a general cap-and-trade policy for transport emissions, while traditionally seen as the economically optimal policy, affects poorer individuals significantly more in terms of access to transport services in a decarbonised world. On the other hand, implementing fixed caps for each country and income group, which cannot be traded with consumers at lower other income groups or countries, and are globally equal for each individual, leads to significantly higher costs for higher income individuals, but does not affect the access to transport services of poorer individuals as strongly. Also, this last alternative leads to a significantly faster take-up of modern clean technologies in transport.
Decarbonisation of the energy sector is a critical task in the efforts to mitigate climate change. As sectoral emissions cuts in modelled pathways aligned with the Paris Agreement are projected to come from at-scale diffusion of emerging or new technologies as well as further development of existing solutions, energy-sector decarbonisation entails major investments in low-carbon technologies. At the same time, a significant chunk of these investments must be made in emerging and developing economies, which currently receive just one-fifth of global energy investments. This underinvestment is, at least partly, due to the large disparities in financing conditions and higher-risk profiles in said countries. Models used to assess decarbonisation pathways typically assume a uniform cost of capital; such assumption, however, does not do justice to real-world conditions and may therefore lead to inaccurate policy recommendations. Moreover, there is considerable uncertainty over how these costs may evolve in the future. In this study, we apply an empirical dataset of estimated cost of capital differentiated by technology and country and explore stakeholder-driven pathways of (de-)risking investments in clean energy vs. fossil-fuel technologies, using an ensemble of two global integrated assessment models and one electricity-system model. Furthermore, we attempt to incorporate a corrective justice dimension in our narratives by assessing the impacts of risk underwriting for low-carbon investments through taxing corporate windfall profits for 2022 and distributing the revenue as subsidies towards high-risk regions.
The success of the targets established in the European Green Deal depends on the correct design of ambitious policies that utilize all available instruments, including energy and environmental taxation. In the “Fit for 55” package, the EC proposed a deep reform of the Energy Taxation Directive (New ETD) to update the current taxation and align it with current environmental goals. However, due to the war in Ukraine, the energy crisis, and the risk of regressive effects the current proposal of the EC is stalled. Therefore, this analysis seeks to provide new evidence from a microsimulation model developed to assess the direct, overnight distributional impacts of the proposed new ETD reform on households. Our aim is to explore whether the proposed EU-level polluter pays instruments can be designed to achieve progressive distributional impacts, to identify policy options that ensure they strengthen social justice without undermining it, and thereby remove social barriers. Moreover, we explore a dimension often underrepresented in distributional analyses, namely gender. Our results indicate that, with the correct design from the outset, environmental tax reforms can be progressive and not increase current inequalities between and within Member States of the EU, including those related to gender.