Search

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. [ABSTRACT FROM AUTHOR]

The inclusion of Sustainable Development Goals (SDGs) in climate mitigation pathways is critical and can be reached by assessing their consequences through the deployment of appropriate indicators to that end. Integrated Assessment Models (IAMs) are important tools for understanding possible impacts caused by adopting new policies. We investigate terrestrial biodiversity trends (life on land: SDG 15) for three different climate mitigation scenarios for Brazil: (1) A scenario compatible with a world that maintains its current policies with current deforestation rates in the Amazon and the Cerrado biomes; (2) A scenario in which Brazil fulfils its Nationally Determined Contribution (NDC); and (3) A scenario compatible with a world that limits warming to 1.5°C. We use the Brazilian Land-Use and Energy System model (BLUES), a national IAM, to show the implications of the transitions involved in the above-mentioned scenarios for the country up to 2050. We conduct a post-processing analysis using consolidated biodiversity indicators to emphasize how different IAM greenhouse gas (GHG) emissions mitigation solutions present distinct positive and negative potential impacts on biodiversity in Brazil. However, our analysis does not consider the impacts associated with climate change, but only the risks imposed by mitigation policies. Our results indicate that biodiversity loss decreases in the scenarios from (1) to (3), implying that stronger climate change mitigation actions could result in smaller biodiversity losses. We conclude that Brazil has the opportunity to align its biodiversity and climate goals through nature-based solutions (NBS), such as forest conservation, restoration, pasture recovery, and the use of crop-pasture and agroforestry systems. [ABSTRACT FROM AUTHOR]

Intensifying climate change impacts can divert the economic resources away from emission reduction toward adaptation to reduce rising damages, jeopardizing temperature stabilization within safe levels. Indeed, the traditional static welfare‐maximizing climate policy design leads to a conflict between mitigation and adaptation, invalidating the recently established consistency of cost‐benefit analysis with the Paris Agreement's targets. Here, we show that this tension can be resolved by integrating multi‐objective optimization and feedback control in the Dynamic Integrated Climate Economy model to design self‐adaptive climate policies trading off welfare maximization with the Paris Agreement compliance. These policies allow adjusting against uncertainty as information on the socio‐climatic system accumulates, thus representing the policy‐making process more realistically. We show that, the costs being the same as in traditional methods, warming above 2°C and the probability of overshooting can be drastically reduced, emphasizing the need for integrating adaptation and mitigation strategies and the value of embracing a self‐adaptive, multi‐objective perspective. Plain Language Summary: Traditionally, computer models are used to study the timing and magnitude of greenhouse gases emissions reduction, adopting an economic perspective. Yet, some well‐known major issues affect such analyses. First, the decisions need to be taken in an uncertain context, that is, without exact knowledge about the future evolution of climate and economy. Second, these decisions should be contemplating multiple climate policy targets and objectives simultaneously. Third, decisions can be refined and adjusted as we gain more information about the economy, the climate, and their interactions. Finally, climate adaptation strategies, that is, actions and policies that can reduce a part of future climate impacts, are often overlooked as they are treated implicitly. While the models have been improved over time, these problems have never been examined all at once. In this work, we explicitly consider climate adaptation and jointly solve the above issues to show that mitigation and adaptation strategies can be adjusted flexibly to reduce conflicts between different climate policy objectives. Yet, to achieve good performance across the indicators examined, fast climate action is required. Key Points: Dealing explicitly with conflicting objectives, multi‐objective climate policies align mitigation, and adaptation strategiesSelf‐adaptive multi‐objective policies provide the best objectives' trade‐offs by flexibly balancing mitigation and adaptation strategiesAny climate action delay sharpens the conflicts between the objectives and reduces the benefits associated with self‐adaptive policies [ABSTRACT FROM AUTHOR]

The Paris Agreement, adopted in 2015, paved the way for a new hybrid global climate governance architecture with both bottom-up and top-down elements. While governments can choose individual climate goals and actions, a global stocktake and a ratcheting-up mechanism have been put in place with the overall aim to ensure that collective efforts will prevent increasing adverse impacts of climate change. Integrated assessment models show that current combined climate commitments and policies of national governments fall short of keeping global warming to 1.5 °C or 2 °C above preindustrial levels. Although major greenhouse gas emitters, such as China, the European Union, India, the United States under the Biden administration, and several other countries, have made new pledges to take more ambitious climate action, it is highly uncertain where global climate policy is heading. Scenarios in line with long-term temperature targets typically assume a simplistic and hardly realistic level of harmonization of climate policies across countries. Against this backdrop, this article develops four archetypes for the further evolution of the global climate governance architecture and matches them with existing sets of scenarios developed by integrated assessment models. By these means, the article identifies knowledge gaps in the current scenario literature and discusses possible research avenues to explore the pre-conditions for successful coordination of national policies towards achieving the long-term target stipulated in the Paris Agreement. [ABSTRACT FROM AUTHOR]

The implementation of ambitious climate policies consistent with the goals of the Paris Agreement is fundamentally influenced by political dynamics. Yet, thus far, climate mitigation pathways developed by integrated assessment models (IAMs) have devoted limited attention to the political drivers of climate policymaking. Bringing together insights from the political science and socio-technical transitions literature, we summarize evidence on how emissions lock-in, capacity, and public opinion can shape climate policy ambition. We employ a set of indicators to describe how these three factors vary across countries and regions, highlighting context-specific challenges and enablers of climate policy ambition. We outline existing studies that incorporate political factors in IAMs and propose a framework to employ empirical data to build climate mitigation scenarios that incorporate political dynamics. Our findings show that there is substantial heterogeneity in key political drivers of climate policy ambition within IAM regions, calling for a more disaggregated regional grouping within models. Importantly, we highlight that the political challenges and enablers of climate policy ambition considerably vary across regions, suggesting that future modeling efforts incorporating political dynamics can significantly increase the realism of IAM scenarios. [ABSTRACT FROM AUTHOR]

A large-scale transformation of the energy system, which climate mitigation entails, is a global and highly politicized problem. This thematic issue brings together scholars who work with Integrated Assessment Models (IAMs)--which are used for Intergovernmental Panel on Climate Change (IPCC) reports and other key analyses of future climate trajectories--and social scientists working on climate and energy issues to highlight how the two strands of research could benefit from combining insights across different disciplines and methods. One of the key messages across almost all contributions is that the more technical perspectives could benefit from adjusting their assumptions to reflect the patterns observed in quantitative and qualitative social science. Combining different disciplines is methodologically challenging but promising to ensure that the mitigation strategies developed are considered technically and politically feasible, as well as just. [ABSTRACT FROM AUTHOR]

Individual countries are requested to submit nationally determined contributions (NDCs) to alleviate global warming in the Paris Agreement. However, the global climate effects and regional contributions are not explicitly considered in the countries' decision-making process. In this study, we evaluate the global temperature slowdown of the NDC scenario (ΔT = 0.6°C) and attribute the global temperature slowdown to certain regions of the world with a compact earth system model. Considering reductions in CO2, CH4, N2O, BC, and SO2, the R5OECD (the Organization for Economic Co-operation and Development in 1990) and R5ASIA (Asian countries) are the top two contributors to global warming mitigation, accounting for 39.3% and 36.8%, respectively. R5LAM (Latin America and the Caribbean) and R5MAF (the Middle East and Africa) followed behind, with contributions of 11.5% and 8.9%, respectively. The remaining 3.5% is attributed to R5REF (the Reforming Economies). Carbon Dioxide emission reduction is the decisive factor of regional contributions, but not the only one. Other greenhouse gases are also important, especially for R5MAF. The contribution of short-lived aerosols is small but significant, notably SO2 reduction in R5ASIA. We argue that additional species beyond CO2 need to be considered, including short-lived pollutants, when planning a route to mitigate climate change. It needs to be emphasized that there is still a gap to achieve the Paris Agreement 2-degree target with current NDC efforts, let alone the ambitious 1.5-degree target. All countries need to pursue stricter reduction policies for a more sustainable world. [ABSTRACT FROM AUTHOR]

Abstract Intensifying climate change impacts can divert the economic resources away from emission reduction toward adaptation to reduce rising damages, jeopardizing temperature stabilization within safe levels. Indeed, the traditional static welfare‐maximizing climate policy design leads to a conflict between mitigation and adaptation, invalidating the recently established consistency of cost‐benefit analysis with the Paris Agreement's targets. Here, we show that this tension can be resolved by integrating multi‐objective optimization and feedback control in the Dynamic Integrated Climate Economy model to design self‐adaptive climate policies trading off welfare maximization with the Paris Agreement compliance. These policies allow adjusting against uncertainty as information on the socio‐climatic system accumulates, thus representing the policy‐making process more realistically. We show that, the costs being the same as in traditional methods, warming above 2°C and the probability of overshooting can be drastically reduced, emphasizing the need for integrating adaptation and mitigation strategies and the value of embracing a self‐adaptive, multi‐objective perspective.

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]

Questions around the technical and political feasibility of deep mitigation scenarios assessed by the Intergovernmental Panel on Climate Change have increasingly been raised as have calls for more directly analyzing and incorporating aspects of justice and fairness. Simultaneously, models are increasing the technical representation of novel carbon-dioxide removal (CDR) approaches to provide policy-relevant analyses of mitigation portfolios in the context of the rising number of net-zero CO _2 and GHG targets made by parties to the Paris Agreement. Still, in most cost-effective mitigation scenarios developed by integrated assessment models, a significant portion of mitigation is assumed to take place in developing regions. We address these intersecting questions through analyzing scenarios that include direct air capture of CO _2 with storage (DACCS), a novel CDR technology that is not dependent on land potential and can be deployed widely, as well as regional variations in institutional capacity for mitigation based on country-level governance indicators. We find that including novel CDR and representations of institutional capacity can enhance both the feasibility and fairness of 2 °C and 1.5 °C high-overshoot scenarios, especially in the near term, with institutional capacity playing a stronger role than the presence of additional carbon removal methods. However, our results indicate that new CDR methods being studied by models are not likely to change regional mitigation outcomes of scenarios which achieve the 1.5 °C goal of the Paris Agreement. Thus, while engineered carbon removals like DACCS may play a significant role by midcentury, gross emissions reductions in mitigation pathways arriving at net-zero CO _2 emissions in line with 1.5 °C do not substantially change. Our results highlight that further investment and development of novel CDR is critical for post-net-zero CO _2 mitigation, but that equitable achievement of this milestone will need to arrive through technical and financial transfers, rather than by substantial carbon removals in developed countries before mid-century.

Tracking progress towards the Paris Agreement climate goal requires understanding the 2030 emission levels implied by countries’ National Determined Contributions (NDCs). However, key uncertainties and assumptions impact greenhouse gas (GHG) emission projections implied by the NDCs. This study analyses this impact, both globally and for major emitting countries. We find that the assessed uncertainties markedly affect global GHG emission projections. Full achievement of NDC targets is estimated to result in a range of 46–60 GtCO _2 eq by 2030 (median estimate: 53 GtCO _2 eq). The uncertainty in measuring historical emissions, including land-use, as reflected by different datasets is the most important contributing factor. This is followed by two equally important factors globally: socio-economic baseline uncertainty and uncertainty about the emissions implied by current policies in case NDCs are less ambitious than these. Overall, the impact of policy uncertainty (i.e. uncertainty resulting from conditionality of or ranges in NDC targets and uncertainty in emissions resulting from current policies) is about equally important as model/technical uncertainty (i.e. uncertainty in historical emissions and socio-economic baseline variations). This new insight is important for decision makers and researchers because a larger share of the total uncertainty is now attributable to aspects that can be influenced by policy decisions compared to previous analyses of NDC uncertainty.

Many global climate change mitigation pathways presented in IPCC assessment reports rely heavily on the deployment of bioenergy, often used in conjunction with carbon capture and storage. We review the literature on bioenergy use for climate change mitigation, including studies that use top‐down integrated assessment models or bottom‐up modelling, and studies that do not rely on modelling. We summarize the state of knowledge concerning potential co‐benefits and adverse side effects of bioenergy systems and discuss limitations of modelling studies used to analyse consequences of bioenergy expansion. The implications of bioenergy supply on mitigation and other sustainability criteria are context dependent and influenced by feedstock, management regime, climatic region, scale of deployment and how bioenergy alters energy systems and land use. Depending on previous land use, widespread deployment of monoculture plantations may contribute to mitigation but can cause negative impacts across a range of other sustainability criteria. Strategic integration of new biomass supply systems into existing agriculture and forest landscapes may result in less mitigation but can contribute positively to other sustainability objectives. There is considerable variation in evaluations of how sustainability challenges evolve as the scale of bioenergy deployment increases, due to limitations of existing models, and uncertainty over the future context with respect to the many variables that influence alternative uses of biomass and land. Integrative policies, coordinated institutions and improved governance mechanisms to enhance co‐benefits and minimize adverse side effects can reduce the risks of large‐scale deployment of bioenergy. Further, conservation and efficiency measures for energy, land and biomass can support greater flexibility in achieving climate change mitigation and adaptation. [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]

Long-term mitigation scenarios developed by integrated assessment models underpin major aspects of recent IPCC reports and have been critical to identify the system transformations that are required to meet stringent climate goals. However, they have been criticized for proposing pathways that may prove challenging to implement in the real world and for failing to capture the social and institutional challenges of the transition. There is a growing interest to assess the feasibility of these scenarios, but past research has mostly focused on theoretical considerations. This paper proposes a novel and versatile multidimensional framework that allows evaluating and comparing decarbonization pathways by systematically quantifying feasibility concerns across geophysical, technological, economic, socio-cultural and institutional dimensions. This framework enables to assess the timing, disruptiveness and scale of feasibility concerns, and to identify trade-offs across different feasibility dimensions. As a first implementation of the proposed framework, we map the feasibility concerns of the IPCC 1.5 °C Special Report scenarios. We select 24 quantitative indicators and propose feasibility thresholds based on insights from an extensive analysis of the literature and empirical data. Our framework is, however, flexible and allows evaluations based on different thresholds or aggregation rules. Our analyses show that institutional constraints, which are often not accounted for in scenarios, are key drivers of feasibility concerns. Moreover, we identify a clear intertemporal trade-off, with early mitigation being more disruptive but preventing higher and persistent feasibility concerns produced by postponed mitigation action later in the century.

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]

This paper reviews the many criticisms that Integrated Assessment Models (IAMs)—the bedrock of mitigation analysis—have received in recent years. Critics have asserted that there is a lack of transparency around model structures and input assumptions, a lack of credibility in those input assumptions that are made visible, an over-reliance on particular technologies and an inadequate representation of real-world policies and processes such as innovation and behaviour change. The paper then reviews the proposals and actions that follow from these criticisms, which fall into three broad categories: scrap the models and use other techniques to set out low-carbon futures; transform them by improving their representation of real-world processes and their transparency; and supplement them with other models and approaches. The article considers the implications of each proposal, through the particular lens of how it would explore the role of a key low-carbon technology—bioenergy with carbon capture and storage (BECCS), to produce net negative emissions. The paper concludes that IAMs remain critically important in mitigation pathways analysis, because they can encompass a large number of technologies and policies in a consistent framework, but that they should increasingly be supplemented with other models and analytical approaches.

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]

This paper aims at providing a consistent framework to appraise alternative modeling choices that have driven the so-called 'when flexibility' controversy since the early 1990s, dealing with the optimal timing of mitigation efforts and the social cost of carbon (SCC). The literature has emphasized the critical impact of modeling structures on the optimal climate policy. We estimate within a unified framework the comparative impact of modeling structures and investigate the structural modeling drivers of differences in climate policy recommendations. We use the integrated assessment model (IAM) RESPONSE to capture a wide array of modeling choices. Specifically, we analyse four emblematic modeling choices, namely the forms of the damage function (quadratic vs. sigmoid) and the abatement cost (with or without inertia), the treatment of uncertainty, and the decision framework, deterministic or sequential, with different dates of information arrival. We define an original methodology based on an equivalence criterion to compare modeling structures, and we estimate their comparative impact on two outputs: the optimal SCC and abatement trajectories. We exhibit three key findings: (1) IAMs with a quadratic damage function are insensitive to changes of other features of the modeling structure, (2) IAMs involving a non-convex damage function entail contrasting climate strategies, (3) Precautionary behaviors can only come up in IAMs with non-convexities in damage. [ABSTRACT FROM AUTHOR]

That climate policies are costly is evident and therefore often create major fears. But the alternative (no action) also has a cost. Therefore, mitigation costs netted of the damage costs avoided are the only figure that can seriously be considered as the "genuine cost" of a policy. We elaborate on this view of a policy's cost by distinguishing between its "direct" cost component and its avoided damage cost component; we then confront the two so as to evaluate its genuine cost. As damages avoided are equivalent to the benefits generated, this brings climate policies naturally in the realm of benefit-cost analysis. However, the sheer benefit-cost criterion may not be a sufficient incentive for a country to be induced to cooperate internationally, a necessary condition for an effective global climate policy. We therefore also explore how to make use of this criterion in the context of international climate cooperation. [ABSTRACT FROM AUTHOR]

Co-benefits rarely enter quantitative decision-support frameworks, often because the methodologies for their integration are lacking or not known. This review fills in this gap by providing comprehensive methodological guidance on the quantification of co-impacts and their integration into climate-related decision making based on the literature. The article first clarifies the confusion in the literature about related terms and makes a proposal for a more consistent terminological framework, then emphasizes the importance of working in a multiple-objective-multiple-impact framework. It creates a taxonomy of co-impacts and uses this to propose a methodological framework for the identification of the key co-impacts to be assessed for a given climate policy and to avoid double counting. It reviews the different methods available to quantify and monetize different co-impacts and introduces three methodological frameworks that can be used to integrate these results into decision making. On the basis of an initial assessment of selected studies, it also demonstrates that the incorporation of co-impacts can significantly change the outcome of economic assessments. Finally, the review calls for major new research and innovation toward simplified evaluation methods and streamlined tools for more widely applicable appraisals of co-impacts for decision making. [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]

This paper reviews the many criticisms that Integrated Assessment Models (IAMs)—the bedrock of mitigation analysis—have received in recent years. Critics have asserted that there is a lack of transparency around model structures and input assumptions, a lack of credibility in those input assumptions that are made visible, an over-reliance on particular technologies and an inadequate representation of real-world policies and processes such as innovation and behaviour change. The paper then reviews the proposals and actions that follow from these criticisms, which fall into three broad categories: scrap the models and use other techniques to set out low-carbon futures; transform them by improving their representation of real-world processes and their transparency; and supplement them with other models and approaches. The article considers the implications of each proposal, through the particular lens of how it would explore the role of a key low-carbon technology—bioenergy with carbon capture and storage (BECCS), to produce net negative emissions. The paper concludes that IAMs remain critically important in mitigation pathways analysis, because they can encompass a large number of technologies and policies in a consistent framework, but that they should increasingly be supplemented with other models and analytical approaches. [ABSTRACT FROM AUTHOR]