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Some of the most influential explorations of low-carbon transformations are conducted with Integrated Assessment Models (IAMs). The recent attempts by the IPCC to look for pathways compatible with the 1.5 °C and 2 °C temperature goals are a case in point. Earlier scholarship indicates that model-based pathways are persuasive in bringing specific possible future alternatives into view and guiding policymaking. However, the process through which these shared imaginations of possible futures come about is not yet well understood. By closely examining the science-policy dynamics around the IPCC SR1.5, we observe a sequence of mutually legitimising interactions between modelling and policy making through which the 1.5 °C goal gradually gained traction in global climate politics. Our findings reveal a practice of 'political calibration', a continuous relational readjustment between modelling and the policy community. This political calibration is indicative of how modellers navigate climate politics to maintain policy relevance. However, this navigation also brings key dilemmas for modellers, between 1) requirements of the policy process and experts' conviction of realism; 2) perceived political sensitivities and widening the range of mitigation options; and 3) circulating crisp storylines and avoiding policy-prescriptiveness. Overall, these findings call into question the political neutrality of IAMs in its current position in the science-policy interface and suggest a future orientation in which modellers aim to develop additional relations with a broader set of publics resulting in more diverse perspectives on plausible and desirable futures. • IAMs legitimised policy commitments to the 1.5 °C goal. • 1.5 °C pathways gained traction through mutually legitimising science-policy dynamics. • Model analysis is calibrated to policy requirements to maintain policy relevance. • Modellers face dilemmas when navigating between policy relevance and policy shaping. [ABSTRACT FROM AUTHOR]

All modelled global mitigation pathways assessed by the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6) project rapid deployment of land-based mitigation measures for staying within the remaining carbon budget for 1.5°C or 2 °C. However, there is sparse literature on the burden-sharing and equity implications of the IPCC-assessed global mitigation pathways. This is a severe lacuna given the influential role of the IPCC assessments in shaping political deliberations about possible futures and in informing the sectoral guidance and strategy documents of multilateral climate funds and organisations. This paper addresses this gap by evaluating the distributional implications of IPCC AR6 global mitigation pathways for land-based mitigation, specifically focusing on the Global North and South and socio-economic and political implications for food security. Our findings reveal that the modelled pathways disproportionately distribute the burden of land-based mitigation onto the Global South with an adverse impact on food security, raising questions about the normative choices embedded in cost-optimizing Integrated Assessment Models (IAMs). Furthermore, we examine existing scenarios and policy recommendations for addressing food security concerns in stringent climate change mitigation pathways and find them both to be inequitable with attendant feasibility concerns. Our analysis underscores the need for equity-based scenarios in IPCC assessments and calls for transparency in communicating regional distributional assumptions and results of the global mitigation pathways. • IPCC AR6 global mitigation pathways emphasise the rapid deployment of land-based measures to meet 1.5°C or 2°C targets. • Analysis of mitigation pathways reveals a disproportionate burden on the Global South, affecting food security. • Modelled pathways raise questions about normative choices in cost-optimizing Integrated Assessment Models (IAMs). • Alternative scenarios and policy recommendations for food security in 1.5°C or 2°C pathways are also inequitable. • Need for equity-based scenarios and transparently communicating regional distributional assumptions and implications. [ABSTRACT FROM AUTHOR]

• Examines how the Intergovernmental Panel on Climate Change (IPCC) performs as 'mapmaker'. • Illustrates how it acts a corridor maker, effectively narrowing down the range of possible climate futures to a limited range consistent with the relevant 1.5 or 2 °C temperature targets. • Explores the implicit, rarely explicated assumptions made about the feasibility of CDR technologies that justify model and policy choices. • Illustrates how these assumptions pre-empt political consideration of alternative futures. • Concludes by giving a more comprehensive understanding of what is at stake in the politics of anticipation. The article examines how the Intergovernmental Panel on Climate Change (IPCC) performs its self-proclaimed role as 'mapmaker. We seek to contribute to the emerging literature on global environmental assessments (GEA) and climate politics by reconstructing how the IPCC imagines the corridor for climate mitigation. Our particular focus is on the emergence of Integrated Assessment Models (IAMs) as the preferred scientific approach to projecting mitigation pathways consistent with average global temperature target. Taking our lead from current research in science and technology studies (STS) and sociology of futures, we reconstruct the emergence of a science policy tradition of modeling in the field of climate change as a particular mode of anticipation. We summarize the main findings of this literature in order to illustrate the historical and socio-political context in which this mode of anticipation is embedded. Based on this genealogy, we demonstrate how, in its role as mapmaker, the IPCC has also functioned as a corridor maker. We highlight how the IPCC has achieved consensus on a limited set of mitigation pathways, thus effectively narrowing down the discursive space for imagining potential futures to pathways that are deemed technically feasible and cost-efficient. We conclude by discussing the political consequences of this mode of anticipation in order to give us a more comprehensive understanding of what is at stake in the politics of anticipation. We elucidate why the techno-economic framing of current mitigation pathways is highly restrictive, especially when it omits many cultural, political, and other dimensions involved in deploying CDR at scale in their 'real-world' context of application. [ABSTRACT FROM AUTHOR]

Deep decarbonization scenarios indicate a decline in fossil oil usage in the coming decades, meaning that oil refineries must adapt. This work evaluates the refining sector in deep decarbonization pathways using Brazil as a case study. BLUES – a national integrated assessment model – is employed to investigate the evolution of the sector in mitigation scenarios until 2050. The production of feedstocks for the petrochemical industry, of fuels for the aviation and maritime sectors, and biomass co-processing are analyzed. These strategies may bring resilience to the sector. The potential for avoiding emissions in refineries' operations is also explored. Findings show that the refining sector operates at 70% and 74% of its nameplate capacity in decarbonization scenarios. These results are used as the starting point for a detailed analysis of Brazilian refineries. Results show that the employment of refineries' assets for purposes aligned with decarbonization targets, along with emissions mitigation in the sector, reduces risks of carbon lock-in and of asset stranding. To our knowledge, this is the first study that evaluates emissions mitigation in the refining sector and also uses an integrated assessment model to investigate oil refining repurposing and co-processing options in the context of decarbonization. • The refining sector is evaluated using an integrated assessment model for Brazil. • A comparison is made between business- as -usual and decarbonization scenarios. • Opportunities for refineries' assets and mitigation measures are explored. • Opportunities for refineries depend on their location and type of processing units. • Risks of carbon lock-in and asset stranding can be reduced. [ABSTRACT FROM AUTHOR]

Abstract Integrated assessment models are extensively used in the analysis of climate change mitigation and are informing national decision makers as well as contribute to international scientific assessments. This paper conducts a comprehensive review of techno-economic assumptions in the electricity sector among fifteen different global and national integrated assessment models. Particular focus is given to six major economies in the world: Brazil, China, the EU, India, Japan and the US. The comparison reveals that techno-economic characteristics are quite different across integrated assessment models, both for the base year and future years. It is, however, important to recognize that techno-economic assessments from the literature exhibit an equally large range of parameters as the integrated assessment models reviewed. Beyond numerical differences, the representation of technologies also differs among models, which needs to be taken into account when comparing numerical parameters. While desirable, it seems difficult to fully harmonize techno-economic parameters across a broader range of models due to structural differences in the representation of technology. Therefore, making techno-economic parameters available in the future, together with of the technology representation as well as the exact definitions of the parameters should become the standard approach as it allows an open discussion of appropriate assumptions. Highlights • Comparison of technology representation and techno-economic parameters of 15 IAMs. • Structural differences in representing technology in IAMs are identified. • Methods of projecting techno-economic parameters differ across IAMs. • Strict harmonization of techno-economic parameters across models is difficult. • Recommendation to publish techno-economic parameters and technology representation. [ABSTRACT FROM AUTHOR]

The multi-faceted emergencies of our time (recession, pandemics, and international conflict) can disrupt progress towards sustainable development goals (SDGs). While climate-economy models can show pathways out of these disruptions, numerous stakeholder-informed enhancements are required to navigate through the interconnected SDG landscape. We introduce a novel Fuzzy Cognitive Maps (FCMs) approach that integrates Monte Carlo simulations, aiming to capture and understand the differences among modellers' and experts' perceptions of the impacts of such crises on broader sustainability, considering models' existing/planned capacity and uncertainty over perceived magnitude and propagation of impacts across SDGs. Our application shows that expert stakeholders appeared more concerned over the implications of these crises for sustainable development than modellers, but expectations were considerably constrained by model capabilities. SDGs 8 (growth), 7 (energy-sector sustainability), and 13 (climate action) were robustly found as most prone to examined shocks. Our proposed Monte Carlo Fuzzy Cognitive Mapping (MCFCM) approach also highlighted potentially important propagation effects as well as gaps in integrated assessment model capabilities to holistically study the SDG spectrum. • We integrate Monte Carlo into Fuzzy Cognitive Mapping to allow uncertainty assessment. • We measure how SDGs are impacted by today's crises according to modelers and experts. • Expert perceptions of bigger & wider crisis propagation can inform model developments. • Modelers' perceptions may be biased based on their models' current/planned capacities. • Progress in SDGs 7, 8, 13 appears most prone to emergencies such as pandemics or wars. [ABSTRACT FROM AUTHOR]

The industry sector is a major energy consumer and GHG emitter. Effective climate change mitigation strategies will require a significant reduction of industrial emissions. To better understand the variations in the projected industrial pathways for both baseline and mitigation scenarios, we compare key input and structure assumptions used in energy-models in relation to the modeled sectors' mitigation potential. It is shown that although all models show in the short term similar trends in a baseline scenario, where industrial energy demand increases steadily, after 2050 energy demand spans a wide range across the models (between 203 and 451 EJ/yr). In Non-OECD countries, the sectors energy intensity is projected to decline relatively rapidly but in the 2010–2050 period this is offset by economic growth. The ability to switch to alternative fuels to mitigate GHG emissions differs across models with technologically detailed models being less flexible in switching from fossil fuels to electricity. This highlights the importance of understanding economy-wide mitigation responses and costs and is therefore an area for improvements. By looking at the cement sector in more detail, we show that analyzing each industrial sub-sector separately can improve the interpretation and accuracy of outcomes, and provide insights in the feasibility of GHG abatement. [ABSTRACT FROM AUTHOR]

Phasing-out fossil fuels is key to limiting global warming to 1.5 °C. Recent studies indicated huge amounts of unextracted oil resources in deep mitigation scenarios. However, crude oil heterogeneity and related refining yields have been overlooked. The same holds for the impact of carbon dioxide removal (CDR) and sequestration technologies on stranded oil resources, and the pace of crude oil extraction in different world regions in scenarios with and without average global surface temperature overshoot for the 2020–2100 period. This study uses a global Integrated Assessment Model (IAM) to assess the impact of considering such complexities when running full-century and peak budget carbon scenarios. When "turning off" the detailed oil quality module of this IAM, an overproduction of crude oil with a smaller throughput of oil refineries was found, as the model simplified the oil supply-demand balance. "Turning on" the detailed oil module and simulating the energy-land nexus showed that CDR allowed the remaining use of oil in hard-to-abate sectors, while refineries were better adjusted to oil supply. African and Latin American regions produced more oil before 2050 in the full-century-budget scenario than in the peak budget scenario. This has implications for just transition, as these regions usually prefer anticipating rents. • Phasing-out fossil fuels and CDR options are key to limiting global warming. • Crude oil quality matters to estimate stranded oil resources. • Climate ambitions and negative emissions affect just transition. • The distribution of unextracted oil resources differs regionally. • Temperature overshoot allows some developing regions to anticipate oil revenues. [ABSTRACT FROM AUTHOR]

To illustrate the power and utility of macro-level decomposition tools, this article presents a structured comparison of two all-sector global modeling exercises that assess emissions reductions compatible with climate stabilization at roughly 1.5C above pre-industrial levels. It uses an expanded Kaya Identity combined with the LMDI (Logarithmic Mean Divisia Index) method to decompose the effects of key drivers of changes in emissions over time in these scenarios. The most important drivers of emissions reductions include final energy intensity of economic activity, the fraction of primary energy delivered by fossil fuels, and emissions from non-CO 2 warming agents. Land-use change and the carbon intensity of fossil energy are also important. The article suggests additional data modelers should release to allow more rapid analysis of results and ways to facilitate cross-study comparisons (such as adopting "best of breed" sectoral models instead of relying solely on in-house expertise for model development). Global change; Climate change; Emissions reduction modeling; Model comparisons; Energy resources; Environmental policy; Environmental technology; Energy Policy. • Detailed decomposition analysis gives visibility into key drivers and model structure. • Key drivers include energy intensity, fossil fuel fraction, and non-CO 2 warming agents. • Analyzing "edge cases" can help suggest superior technology/policy combinations. • Analyzing "edge cases" can help demonstrate the limits of feasible climate mitigation. • "Best of breed" sectoral models are an essential complement to IAMs. [ABSTRACT FROM AUTHOR]

Integrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wide range of models. Diagnostics can uncover patterns of model behavior and indicate how results differ between model types. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study of 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity, and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to explain variations among policy-relevant model results. [ABSTRACT FROM AUTHOR]

• Current national policies are not sufficient to meet the Paris Agreement goals. • Collective increase in climate action is needed to stabilize warming at safe levels. • Good practice policies can bridge the emissions gap to a below 2 °C world. • These policies can create a bridge trajectory in key major-emitting countries. One key aspect of the Paris Agreement is the goal to limit the global average temperature increase to well below 2 °C by the end of the century. To achieve the Paris Agreement goals, countries need to submit, and periodically update, their Nationally Determined Contributions (NDCs). Recent studies show that NDCs and currently implemented national policies are not sufficient to cover the ambition level of the temperature limit agreed upon in the Paris Agreement, meaning that we need to collectively increase climate action to stabilize global warming at levels considered safe. This paper explores the generalization of previously adopted good practice policies (GPPs) to bridge the emissions gap between current policies, NDCs ambitions and a well below 2 °C world, facilitating the creation of a bridge trajectory in key major-emitting countries. These GPPs are implemented in eleven well-established national Integrated Assessment Models (IAMs) for Australia, Brazil, Canada, China, European Union (EU), India, Indonesia, Japan, Russia, South Korea, and the United States, that provide least-cost, low-carbon scenarios up to 2050. Results show that GPPs can play an important role in each region, with energy supply policies appearing as one of the biggest contributors to the reduction of carbon emissions. However, GPPs by themselves are not enough to close the emission gap, and as such more will be needed in these economies to collectively increase climate action to stabilize global warming at levels considered safe. [ABSTRACT FROM AUTHOR]

Numerous ways to improve the usefulness of climate change mitigation scenarios that rely on the Shared Socioeconomic Pathway (SSP) framework that was developed over the last 10 years have been suggested. The problem with these proposals is that the diagnosis of what has led to the inability of integrated assessment modelers to properly analyze mitigation policies is wrong. The first main problem with the past use of the SSP-based mitigation scenarios is that few input variables for what is supposed to be the same SSP are given the same numerical values by different modeling teams. The more significant problem with the way in SSP-based mitigation scenarios have been used to analyze mitigation policies is that the different integrated assessment models (IAMs) have very different structures and functions. Thus, even if all the input variables comprising a single SSP had the same numerical values, the scenario results from running such a SSP through different IAMs would be quite different, leading to different understandings of the usefulness of different mitigation policies. This situation can be avoided by developing just two or three more detailed and improved IAMs focused on the critical next 10–20 years for mitigating climate change. [ABSTRACT FROM AUTHOR]