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The second Scenarios Forum took place in June 2022 in Laxenburg, Austria. The goal of the second Scenarios Forum was to bring together the diverse set of communities using or developing scenarios in climate change and sustainability analysis to exchange experiences, ideas, and lessons learned; identify opportunities for synergies and collaboration between communities; reflect on the use of scenarios; and identify knowledge gaps for future research. The Scenarios Forum 2022 brought together over 500 researchers onsite and online to share experiences to date on progress toward this goal. The Forum confirmed that the SSP-RCP framework is being widely and increasingly used across a variety of research communities and assessment processes in the climate and biodiversity communities. Key discussions on future needs during the Scenarios Forum included the need for expansion of the solution space to facilitate a wider diversity of response strategies, broadening the labeling of scenarios to facilitate connection to other communities, initiating a discussion on high-end community scenarios and the tension in the scenarios framework between providing building-blocks for scientists and identifying key community-level scenarios.

We summarize some of the past year’s most important findings within climate change-related research. New research has improved our understanding of Earth’s sensitivity to carbon dioxide, finds that permafrost thaw could release more carbon emissions than expected and that the uptake of carbon in tropical ecosystems is weakening. Adverse impacts on human society include increasing water shortages and impacts on mental health. Options for solutions emerge from rethinking economic models, rights-based litigation, strengthened governance systems and a new social contract. The disruption caused by COVID-19 could be seized as an opportunity for positive change, directing economic stimulus towards sustainable investments.

Nearly 900 million people in Sub-Saharan Africa rely on traditional biomass for cooking, with negative impacts on health, biodiversity and the climate. In this study, we use the IMAGE modelling framework to construct two sets of scenarios for promoting clean cooking solutions. In the first set, specific policy options to promote clean cooking are evaluated, while in the second the SDG target to achieve universal access to modern cooking energy by 2030 is imposed. The study adds knowledge to understanding the impact of individual policy options on access to clean cooking solutions, and provides insight into synergies and trade-offs of achieving the SDG targets on human health, biodiversity and climate change. The results show that, in the absence of coordinated actions, enabling policies and scaled-up finance, the number of people in Sub-Saharan Africa relying on traditional biomass cookstoves could amount to 660–820 million by 2030. Subsidies on specific clean cooking technologies or fuels could increase their use substantially, but could hinder the uptake of alternative clean cooking fuels or technologies. Meeting the SDG target has considerable social, environmental and economic benefits, and could even lead to lower total fuel expenditures. However, investments in cookstoves need to be quadrupled relative to baseline.

This study presents a new comprehensive set of long-term Marginal Abatement Cost (MAC) curves of all major non-CO2 greenhouse gas emission sources. The work builds on existing short-term MAC curve datasets and recent literature on individual mitigation measures. The new MAC curves include current technology and costs information as well as estimates of technology development and removal of implementation barriers to capture long-term dynamics. Compared to earlier work, we find a higher projected maximum reduction potential (MRP) of nitrous oxide (N2O) and a lower MRP of methane (CH4). The combined MRP for all non-CO2 gases is similar but has been extended to also capture mitigation measures that can be realized at higher implementation costs. When applying the new MAC curves in a cost-optimal, integrated assessment model-based 2.6 W/m2 scenario, the total non-CO2 mitigation is projected to be 10.9 Mt CO2 equivalents in 2050 (i.e. 58% reduction compared to baseline emissions) and 15.6 Mt CO2equivalents in 2100 (i.e. a 71% reduction). In applying the new MAC curves, we account for inertia in thline implementation speed of mitigation measures. Although this does not strongly impact results in an optimal strategy, it means that the contribution of non-CO2 mitigation could be more limited if ambitious climate policy is delayed.

The Digital Revolution, including technologies such as virtual and augmented reality, additive manufacturing or 3D-printing, (general purpose) artificial intelligence, or the Internet of Things, has entered the public discourse in many countries. Looking back, it is almost impossible to believe that digitalization is barely featured in the 2030 Agenda or the Paris Agreement. It is increasingly clear that digital changes, we refer to them as the Digital Revolution, are becoming a key driving force in societal transformation. The transformation towards sustainability for all must be harmonized with the threats, opportunities and dynamics of the Digital Revolution, the goals of the 2030 Agenda and the Paris Agreement. At the same time, the digital transformation will radically alter all dimensions of global societies and economies and will therefore change the interpretation of the sustainability paradigm itself. Digitalization is not only an ‘instrument’ to resolve sustainability challenges, it is also fundamental as a driver of disruptive change. This report that focuses on the Digital Revolution is the second one by The World in 2050 (TWI2050) that was established by the International Institute for Applied Systems Analysis (IIASA) and other partners to provide scientific foundations for the 2030 Agenda. This report is based on the voluntary and collaborative effort of more than 50 authors and contributors from about 20 institutions, and some 100 independent experts from academia, business, government, intergovernmental and non-governmental organizations from all the regions of the world, who met four times at IIASA to develop science-based strategies and pathways toward achieving the Sustainable Development Goals (SDGs). Presentations of the TWI2050 approach and work have been made at many international meetings such as the United Nations Science, Technology and Innovation Forums and the United Nations High-level Political Forums. In 2018, the first report by TWI2050 on Transformations to Achieve the Sustainable Development Goals identified Six Exemplary Transformations needed to achieve the SDGs and long-term sustainability to 2050 and beyond: i) Human Capacity Demography; ii) Consumption Production; iii) Decarbonization Energy, iv) Food, Biosphere Water; v) Smart Cities and vi) Digital Revolution. The focus of this report is the Sixth Transformation, The Digital Revolution. Although it is arguably the single greatest enabler of sustainable development, it has, in the past, helped create many negative externalities like transgression of planetary boundaries. Progress on the SDGs will be facilitated if we can build and implement detailed science, technology and innovation (STI) roadmaps at all levels that range from local to global. STI is a forceful driver of change connected to all 17 SDGs. The Digital Revolution provides entirely new and enhanced capacities and thus serves as a major force in shaping both the systemic context of transformative change and future solutions; at the same time it potentially carries strong societal disruptive power if not handled with caution, care, and innovativeness. This report assesses all the positive potential benefits digitalization brings to sustainable development for all. It also highlights the potential negative impacts and challenges going forward, particularly for those impacted by the ‘digital divide’ that excludes primarily people left behind during the Industrial Revolution like the billion that go hungry every night and the billion who do not have access to electricity. The report outlines the necessary preconditions for a successful digital transformation, including prosperity, social inclusion, environmental sustainability and good governance. Importantly it outlines some of the dramatic social implications associated with an increasingly digital future. It also covers a topic that so far has not been sufficiently dealt with in the cross-over discussions between sustainability and the Digital Revolution, that is, the considerations about related governance aspects.

Process-based integrated assessment models (IAMs) analyse transformation pathways to mitigate climate change. Confidence in models is established by testing their structural assumptions and comparing their behaviour against observations as well as other models. Climate model evaluation is concerted, and prominently reported in a dedicated chapter in the IPCC WG1 assessments. By comparison, evaluation of process-based IAMs tends to be less visible and more dispersed among modelling teams, with the exception of model inter-comparison projects. We contribute the first comprehensive analysis of process-based IAM evaluation, drawing on a wide range of examples across eight different evaluation methods testing both structural and behavioural validity. For each evaluation method, we compare its application to process-based IAMs with its application to climate models, noting similarities and differences, and seeking useful insights for strengthening the evaluation of process-based IAMs. We find that each evaluation method has distinctive strengths and limitations, as well as constraints on their application. We develop a systematic evaluation framework combining multiple methods that should be embedded within the development and use of process-based IAMs.

This paper presents a modeling comparison on how stabilization of global climate change at about 2 °C above the pre-industrial level could affect economic and energy systems development in China and India. Seven General Equilibrium (CGE) and energy system models on either the global or national scale are soft-linked and harmonized with respect to population and economic assumptions. We simulate a climate regime, based on long-term convergence of per capita carbon dioxide (CO2) emissions, starting from the emission pledges presented in the Copenhagen Accord to the United Nations Framework Convention on Climate Change and allowing full emissions trading between countries. Under the climate regime, Indian emission allowances are allowed to grow more than the Chinese allowances, due to the per capita convergence rule and the higher population growth in India. Economic and energy implications not only differ among the two countries, but also across model types. Decreased energy intensity is the most important abatement approach in the CGE models, while decreased carbon intensity is most important in the energy system models. The reduction in carbon intensity is mostly achieved through deployment of carbon capture and storage, renewable energy sources and nuclear energy. The economic impacts are generally higher in China than in India, due to higher 2010–2050 cumulative abatement in China and the fact that India can offset more of its abatement cost though international emission trading.

Carbon Capture and Storage (CCS) can be a valuable CO2 mitigation option, but what role CCS will play in the future is uncertain. In this paper we analyze the results of different integrated assessment models (IAMs) taking part in the 27th round of the Energy Modeling Forum (EMF) with respect to the role of CCS in long term mitigation scenarios. Specifically we look into the use of CCS as a function of time, mitigation targets, availability of renewables and its use with different fuels. Furthermore, we explore the possibility to relate model results to general and CCS specific model assumptions. The results show a wide range of cumulative capture in the 2010-2100 period (600-3050 GtCO2), but the fact that no model projects less than 600 GtCO2 indicates that CCS is considered to be important by all these models. Interestingly, CCS storage rates are often projected to be still increasing in the second half of this century. Depending on the scenario, at least six out of eight, up to all models show higher storage rates in 2100 than in 2050. CCS shares in cumulative primary energy use are in most models increasing with the stringency of the target or under conservative availability of renewables. The strong variations of CCS deployment projection rates could not be related to the reported differences in the assumptions of the models by means of a cross-model comparison in this sample.

International audience; This study explores the importance of bioenergy to potential future energy transformation and climate change management. Using a large inter-model comparison of 15 models, we comprehensively characterize and analyze future dependence on, and the value of, bioenergy in achieving potential long-run climate objectives. Model scenarios project, by 2050, bioenergy growth of 1 to 10 % per annum reaching 1 to 35 % of global primary energy, and by 2100, bioenergy becoming 10 to 50 % of global primary energy. Non-OECD regions are projected to be the dominant suppliers of biomass, as well as consumers, with up to 35 % of regional electricity from biopower by 2050, and up to 70 % of regional liquid fuels from biofuels by 2050. Bioenergy is found to be valuable to many models with significant implications for mitigation and macroeconomic costs of climate policies. The availability of bioenergy, in particular biomass with carbon dioxide capture and storage (BECCS), notably affects the cost-effective global emissions trajectory for climate management by accommodating prolonged near-term use of fossil fuels, but with potential implications for climate outcomes. Finally, we find that models cost-effectively trade-off land carbon and nitrous oxide emissions for the long-run climate change management benefits of bioenergy. The results suggest opportunities, but also imply challenges. Overall, further evaluation of the viability of large-scale global bioenergy is merited. © 2013 Springer Science+Business Media Dordrecht.

This paper analyses the impact of postponing global mitigation action on abatement costs and energy systems changes in China and India. It compares energy-system changes and mitigation costs from a global and two national energy-system models under two global emission pathways with medium likelihood of meeting the 2 °C target: a least-cost pathway and a pathway that postpones ambitious mitigation action, starting from the Copenhagen Accord pledges. Both pathways have similar 2010–2050 cumulative greenhouse gas emissions. The analysis shows that postponing mitigation action increases the lock-in in less energy efficient technologies and results in much higher cumulative mitigation costs. The models agree that carbon capture and storage (CCS) and nuclear energy are important mitigation technologies, while the shares of biofuels and other renewables vary largely over the models. Differences between India and China with respect to the timing of emission reductions and the choice of mitigation measures relate to differences in projections of rapid economic change, capital stock turnover and technological development. Furthermore, depending on the way it is implemented, climate policy could increase indoor air pollution, but it is likely to provide synergies for energy security. These relations should be taken into account when designing national climate policies.

A suggestion for mapping the SRES illustrative scenarios onto the new scenarios framework of representative concentration pathways (RCPs) and shared socio-economic pathways (SSPs) is presented. The mapping first compares storylines describing future socio-economic developments for SRES and SSPs. Next, it compares projected atmospheric composition, radiative forcing and climate characteristics for SRES and RCPs. Finally, it uses the new scenarios matrix architecture to match SRES scenarios to combinations of RCPs and SSPs, resulting in four suggestions of suitable combinations, mapping: (i) an A2 world onto RCP 8.5 and SSP3, (ii) a B2 (or A1B) world onto RCP 6.0 and SSP2, (iii) a B1 world onto RCP 4.5 and SSP1, and (iv) an A1FI world onto RCP 8.5 and SSP5. A few other variants are also explored. These mappings, though approximate, may assist analysts in reconciling earlier scenarios with the new scenario framework.

Climate policies must consider radiative forcing from Kyoto greenhouse gases, as well as other forcing constituents, such as aerosols and tropospheric ozone that result from air pollutants. Non-Kyoto forcing constituents contribute negative, as well as positive forcing, and overall increases in total forcing result in increases in global average temperature. Non-Kyoto forcing modeling is a relatively new component of climate management scenarios. This paper describes and assesses current non-Kyoto radiative forcing modeling within five integrated assessment models. The study finds negative forcing from aerosols masking (offsetting) approximately 25 % of positive forcing in the near-term in reference non-climate policy projections. However, masking is projected to decline rapidly to 5-10 % by 2100 with increasing Kyoto emissions and assumed reductions in air pollution-with the later declining to as much as 50 % and 80 % below today's levels by 2050 and 2100 respectively. Together they imply declining importance of non-Kyoto forcing over time. There are however significant uncertainties and large differences across models in projected non-Kyoto emissions and forcing. A look into the modeling reveals differences in base conditions, relationships between Kyoto and non-Kyoto emissions, pollution control assumptions, and other fundamental modeling. In addition, under climate policy scenarios, we find air pollution and resulting non-Kyoto forcing reduced to levels below those produced by air pollution policies alone-e.g., China sulfur emissions fall an additional 45-85 % by 2050. None of the models actively manage non-Kyoto forcing for climate implications. Nonetheless, non-Kyoto forcing may be influencing mitigation results, including allowable carbon dioxide emissions, and further evaluation is merited.

The role of bioenergy in climate change mitigation is a topic of heated debate, as the demand for land may result in social and ecological conflicts. Biodiversity impacts are a key controversy, given that biodiversity conservation is a globally agreed goal under pressure due to both climate change and land use. Impact assessment of bioenergy in various socio-economic and policy scenarios is a crucial basis for planning sound climate mitigation policy. Empirical studies have identified positive and negative local impacts of different bioenergy types on biodiversity, but ignored indirect impacts caused by displacement of other human activities. Integrated assessment models (IAMs) provide land-use scenarios based on socio-economic and policy storylines. Global scenarios capture both direct and indirect land-use change, and are therefore an appealing tool for assessing the impacts of bioenergy on biodiversity. However, IAMs have been originally designed to address questions of a different nature. Here, we illustrate the properties of IAMs from the biodiversity conservation perspective and discuss the set of questions they could answer. We find IAMs are a useful starting point for more detailed regional planning and assessment. However, they have important limitations that should not be overlooked. Global scenarios may not capture all impacts, such as changes in forest habitat quality or small-scale landscape structure, identified as key factors in empirical studies. We recommend increasing spatial accuracy of IAMs through region-specific, complementary modelling, including climate change into predictive assessments, and considering future biodiversity conservation needs in assessments of impacts and sustainable potentials of bioenergy.

The uncertain, future development of emissions of short-lived trace gases and aerosols forms a key factor for future air quality and climate forcing. The Representative Concentration Pathways (RCPs) only explore part of this range as they all assume that worldwide ambitious air pollution control policies will be implemented. In this study, we explore how different assumptions on future air pollution policy and climate policy lead to different concentrations of air pollutants for a set of RCP-like scenarios developed using the IMAGE model. These scenarios combine low and high air pollution variants of the scenarios with radiative forcing targets in 2100 of 2.6 W m(-2) and 6.0 W m(-2). Simulations using the global atmospheric chemistry and transport model TM5 for the present-day climate show that both climate mitigation and air pollution control policies have large-scale effects on pollutant concentrations, often of similar magnitude. If no further air pollution policies would be implemented, pollution levels could be considerably higher than in the RCPs, especially in Asia. Air pollution control measures could significantly reduce the warming by tropospheric ozone and black carbon and the cooling by sulphate by 2020, and in the longer term contribute to enhanced warming by methane. These effects tend to cancel each other on a global scale. According to our estimates the effect of the worldwide implementation of air pollution control measures on the total global mean direct radiative forcing in 2050 is +0.09 W m(-2) in the 6.0 W m(-2) scenario and -0.16 W m(-2) in the 2.6 W m(-2) scenario. (C) 2013 Elsevier Ltd. All rights reserved.

Building bridges between three analytical approaches with quite different foundational bases should lead to a more comprehensive understanding of low-carbon transitions, in turn leading to more informed and effective policy decisions. Low-carbon transitions are long-term multi-faceted processes. Although integrated assessment models have many strengths for analysing such transitions, their mathematical representation requires a simplification of the causes, dynamics and scope of such societal transformations. We suggest that integrated assessment model-based analysis should be complemented with insights from socio-technical transition analysis and practice-based action research. We discuss the underlying assumptions, strengths and weaknesses of these three analytical approaches. We argue that full integration of these approaches is not feasible, because of foundational differences in philosophies of science and ontological assumptions. Instead, we suggest that bridging, based on sequential and interactive articulation of different approaches, may generate a more comprehensive and useful chain of assessments to support policy formation and action. We also show how these approaches address knowledge needs of different policymakers (international, national and local), relate to different dimensions of policy processes and speak to different policy-relevant criteria such as cost-effectiveness, socio-political feasibility, social acceptance and legitimacy, and flexibility. A more differentiated set of analytical approaches thus enables a more differentiated approach to climate policy making.

Long-term scenarios generally project a steep increase in global travel demand, leading to an rapid rise in CO2 emissions. Major driving forces are the increasing car use in developing countries and the global growth in air travel. Meeting the 2 °C climate target, however, requires a deep cut in CO2 emissions. In this paper, we explore how extensive emission reductions may be achieved, using a newly developed travel model. This bottom-up model covers 26 world regions, 7 travel modes and different vehicle types. In the experiments, we applied a carbon tax and looked into the model’s responses in terms of overall travel demand, modal split shifts, and changes in technology and fuel choice. We introduce two main scenarios in which biofuels are assumed to be carbon neutral (not subject to taxation, scenario A) or to lead to some greenhouse gas emissions (and therefore subject to taxation, scenario B). This leads to very different outcomes. Scenario A achieves emission reductions mostly through changes in fuel use. In Scenario B efficiency improvement and model split changes also play a major role. In both scenarios total travel volume is affected only marginally.

Carbon capture and storage (CCS) is a potential key-technology to mitigate greenhouse gas (GHG) emissions as its use can lead to lower mitigation cost. However, research on other economic impacts of using CCS is scarce. In this paper, we look into economic upstream impacts of CCS use in terms of employment, Gross Value Added (GVA) and import dependency on the macro- and sector-level in Western Europe. We determine these impacts by a static comparison of two scenarios of power production with and without CCS (differences in energy efficiency investments between these scenarios were not accounted for). The two scenarios, both representing a stringent climate policy regime, were produced with the energy-system-simulation-model (TIMER) following the same emission profile until 2050. Data from the two scenarios were respectively implemented into a projected version of a global-multiregional IO-Model (EXIOBASE). Macro-level results suggest slightly higher gross employment, but lower Gross Value Added (GVA) (by 25%), and higher import dependency in the CCS-including scenario compared to the CCS-excluding scenario, given that biomass with CCS (BECCS) is available. Sector-level results show disproportionally higher differences between the scenarios in GVA and employment for some sectors compared to other sectors. Particularly, sectors providing fuels (here mostly bio-energy) have significantly higher GVA and employment in the CCS scenario. This study thus reveals interesting upstream economic effects, which can be linked to the technology choice. However, the exact quantitative results depend strongly on model assumptions. Results therefore need to be further explored in other models. (C) 2015 Elsevier Ltd. All rights reserved.

Energy use in developing countries is heterogeneous across households. Present day global energy models are mostly too aggregate to account for this heterogeneity. Here, a bottom-up model for residential energy use that starts from key dynamic concepts on energy use in developing countries is presented and applied to India. Energy use and fuel choice is determined for five end-use functions (cooking, water heating, space heating, lighting and appliances) and for five different income quintiles in rural and urban areas. The paper specifically explores the consequences of different assumptions for income distribution and rural electrification on residential sector energy use and CO2 emissions, finding that results are clearly sensitive to variations in these parameters. As a result of population and economic growth, total Indian residential energy use is expected to increase by around 65–75% in 2050 compared to 2005, but residential carbon emissions may increase by up to 9–10 times the 2005 level. While a more equal income distribution and rural electrification enhance the transition to commercial fuels and reduce poverty, there is a trade-off in terms of higher CO2 emissions via increased electricity use.

This study provides a conceptual framework for exploring the bargaining space within international climate negotiations based on important economic, political and environmental considerations. Based on it, we analyse combinations of the proposed emission reduction ranges for Annex I countries as a group (25–40% below 1990 levels) and non-Annex I as a group (15–30% below baseline) by 2020 to limit global warming to 2 °C. We use results of the FAIR model with costs estimates based on two energy system models. We conclude that the range of targets that comply with a set of criteria for economic, political and environmental considerations is smaller than that by environmental considerations alone. More specifically, we find that according to our criteria, a 30% Annex I reduction target below 1990 levels, combined with a 20% non-Annex I reduction target below baseline emission levels (i.e. 20 to 30% above 2005 levels), is the only combination of targets fulfilling all our criteria for both energy system models. Otherwise, reaching the 2 °C target becomes less likely, technically infeasible, or non-Annex I abatement costs are likely to exceed those of Annex I, a result, which we consider less plausible from a political viewpoint in our conceptual framework.

Uncertainties in energy demand modelling allow for the development of different models, but also leave room for different calibrations of a single model. We apply an automated model calibration procedure to analyse calibration uncertainty of residential sector energy use modelling in the TIMER 2.0 global energy model. This model simulates energy use on the basis of changes in useful energy intensity, technology development (AEEI) and price responses (PIEEI). We find that different implementations of these factors yield behavioural model results. Model calibration uncertainty is identified as influential source for variation in future projections: amounting 30% to 100% around the best estimate. Energy modellers should systematically account for this and communicate calibration uncertainty ranges.

Most global energy models are developed by institutes from developed countries focusing primarily oil issues that are important in industrialized countries. Evaluation of the results for Asia of the IPCC/SRES models shows that broad concepts of energy and development. the energy ladder and the environmental Kuznets curve, call be observed in the results of file models. However, improvements can be made in Modeling the issues that underlie these Concepts, like traditional fuels. electrification, economic structural change, income distribution, and informal economies. Given the rapidly growing importance of energy trajectories of developing countries for global sustainability, the challenge for the future is to develop energy models that include all these aspects of energy and development. (c) 2008 Elsevier Ltd. All rights reserved.

The ongoing discussion about the feasibility of maintaining global temperatures below 2 °C encompasses not only the costs and benefits of achieving the target, but also the difficulty of reconciling regional efforts with the inequity of climate change impacts. If mitigation and adaptation actions, as well as residual damage from climate change, will be distributed diversely across the world, can we devise a policy which aligns different country and regional views and incentives? In most of the scientific literature, equity issues related to mitigation, adaptation, and impacts have been disconnected. Most studies on effort sharing have focused on fair distributions of mitigation costs without considering adaptation costs and residual damage. Our study aims to fill this gap by investigating which mitigation targets in 2030 and 2050 lead to equalizing the sum of mitigation costs, adaptation costs, and residual damage as share of GDP across regions. We employ two alternative modelling frameworks combined with two sets of regional climate change impact functions. These models provide a mapping of the residual climate change damages of 2 °C and of the resulting adaptation costs, and allow exploring how emission rights should be allocated to equalize the sum of mitigation costs, residual damage, and adaptation costs as share of GDP across regions. We show that a 2 °C world leaves considerable residual impacts and adaptation costs. Sharing the burden of the total costs of climate change, including residual damage and adaptation costs, reshuffles the emission allocation compared to an effort-sharing regime based on mitigation costs only. The financial implications can be significant, with a total of additional resources in the order of 100-200 USD billions in 2030 would need to flow to the high impact countries in India, Africa, and Rest of Asia, by means of trading emission rights. Countries with lower-than-average impacts, such as OECD countries and China, would buy such rights thereby financing those transfers. The above numbers assume a global carbon market being in place from 2020 onwards. Even though such a global carbon market with the implied sharing rules is not easy to implement, our paper suggests that accounting for the total costs of climate change and including adaptation and damage considerations could achieve an effort distribution being perceived fair by a wider group of countries.