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In 2015, the United Nations articulated the ambition to move toward a prosperous, socially inclusive, and environmentally sustainable future for all by adopting the Sustainable Development Goals (SDGs). However, little is known about the pathways that could lead to their concurrent achievement. We provide an overview of the current literature on quantitative pathways toward the SDGs, indicate the commonly used methods and indicators, and identify the most comprehensive pathways that have been published to date. Our results indicate that there is a need for more scenarios toward the full set of SDGs, using a wider range of underlying narratives. Technical Summary Quantitative goal-seeking scenario studies could help to explore the needed systems' transformations to implement the 2030 Agenda for Sustainable Development by identifying enabling conditions and accounting for the synergies and trade-offs between the SDGs. Given that the SDGs were adopted some time ago, here, we review the existing global scenario literature to determine what it can offer in this context. We found only a few scenarios that address a large set of SDGs, while many more deal with specific clusters of 2–6 SDGs. We identified the most frequent clusters and compared the results of the most comprehensive sustainable development scenarios. The latter is complicated because of the diversity of methods, indicators, and assumptions used. Therefore, we suggest that an effort is needed to develop a wider set of scenarios that would achieve multiple SDGs, using a more standardized framework of targets and indicators. Social Media Summary This study reviews the current global pathways toward the SDGs and shows the need for a broader set of SDG scenarios.

The sustainable development goals (SDGs) represent the global ambition to accelerate sustainable development. Several SDGs are directly related to climate change and policies aiming to mitigate it. This includes, among others, the set of SDGs that directly influence the climate, land, energy, and water (CLEW) nexus (SDGs 2, 6, 7, 13, 15). This study aims at understanding the synergies and trade-offs between climate policy and the SDGs agenda: how does near-term action on SDGs influence long-term climate goals? Based on a multi-model comparison, we evaluate three scenarios: (i) reference; (ii) climate mitigation; and (iii) a CLEW nexus SDGs scenario. We find clear positive effects of combining the climate and the sustainable development agendas. Notably, healthier diets, with reduced meat consumption, have strong co-benefits for climate, with positive effects across multiple SDGs: improvements in food security, reductions in air pollution and water stress, and improvements in biodiversity conservation. Such positive outcomes are prominent in the Global South, where regions typically at higher risk of food and energy insecurity and other environmental stresses (e.g. Sub-Saharan Africa, Asia and Latin America) benefit from a shorter term agenda focusing not only on the climate but also on the other sustainable development dimensions. However, trade-offs are also observed (e.g. increases in the prices of food and electricity), especially in the dynamics of land and the food systems, highlighting the importance of exploring policy synergies: if individually applied, some measures can negatively impact other sustainability goals, while taking into consideration the nexus interactions can reduce trade-offs and increase co-benefits. Finally, near-term action on SDGs can help speed up the transition towards the long-term climate goals, reducing the reliance on negative emissions options. In 2100, the SDG scenario in significantly less reliant on carbon dioxide removals both

Adaptation is a key societal response to reduce the impacts of climate change, yet it is poorly represented in current modelling frameworks. We identify key research gaps and suggest entry points for adaptation in quantitative assessments of climate change to enhance policy guidance.

Chapter 3 assesses the emissions pathways literature in order to identify their key characteristics (both in commonalities and differences) and to understand how societal choices may steer the system into a particular direction (high confidence). More than 2000 quantitative emissions pathways were submitted to the IPCC’s Sixth Assessment Report AR6 scenarios database, out of which 1202 scenarios included sufficient information for assessing the associated warming consistent with WGI.

The use of scenarios and modelling methods are pillars in IPCC Working Group III (WGIII) Assessment Reports. Past WGIII assessment report cycles identified knowledge gaps about the integration of modelling across scales and disciplines, mainly between global integrated assessment modelling methods and bottom-up modelling insights of mitigation responses. The need to improve the transparency of model assumptions and enhance the communication of scenario results was also recognised. This annex on Scenarios and Modelling Methods aims to address some of these gaps by detailing the modelling frameworks applied in the WGIII Sixth Assessment Report (AR6) chapters and disclose scenario assumptions and its key parameters. It has been explicitly included in the Scoping Meeting Report of the WGIII contribution to the AR6 and approved by the IPCC Panel at the 46th Session of the Panel.

While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the “climate-assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to “1.5 ∘C (with a probability of greater than 50 %) with no or limited overshoot” includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 ∘C for up to a few decades before returning to below 1.5 ∘C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3–0.4 ∘C after peaking at 1.5–

Countries’ emission reduction commitments under the Paris Agreement have significant implications for lifestyles. National planning to meet emission targets is based on modelling and analysis specific to individual countries, whereas global integrated assessment models provide scenario projections in a consistent framework but with less granular output. We contribute a novel methodology for translating global scenarios into lifestyle implications at the national and household levels, which is generalisable to any service or country and versatile to work with any model or scenario. Our 5Ds method post-processes Integrated Assessment Model projections of sectoral energy demand for the global region to derive energy-service-specific lifestyle change at the household level. We illustrate the methodology for two energy services (mobility, heating) in two countries (UK, Sweden), showing how effort to reach zero carbon targets varies between countries and households. Our method creates an analytical bridge between global model output and information that can be used at national and local levels, making clear the lifestyle implications of climate targets.

The expected growth in the demand for passenger and freight services exacerbates the challenges of reducing transport GHG emissions, especially as commercial low-carbon alternatives to petroleum fuels are limited for shipping, air and long-distance road travel. Biofuels can offer a pathway to significantly reduce emissions from these sectors, as they can easily substitute for conventional liquid fuels in internal combustion engines. In this paper, we assess the potential of bioenergy to reduce transport GHG emissions through an analysis leveraging various integrated assessment models and scenarios, as part of the 33rd Energy Modeling Forum study (EMF-33). We find that bioenergy can contribute a significant, albeit not dominant, proportion of energy supply to the future transport sector: in scenarios aiming to keep the temperature increase below 2 °C by the end of the twenty-first century, models project that in 2100 bioenergy can provide on average 42 EJ/yr (ranging from 5 to 85 EJ/yr) for transport (compared to 3.7 EJ in 2018), mainly through lignocellulosic fuels. This makes up 9–62% of final transport energy use. Only a small amount of bioenergy is projected to be used in transport through electricity and hydrogen pathways, with a larger role for biofuels in road passenger transport than in freight. The association of carbon capture and storage (CCS) with bioenergy technologies (BECCS) is a key determinant in the role of biofuels in transport, because of the competition for biomass feedstock to provide other final energy carriers along with carbon removal. Among models that consider CCS in the biofuel conversion process the average market share of biofuels is 21% in 2100 (ranging from 2 to 44%), compared to 10% (0–30%) for models that do not. Cumulative direct emissions from the transport sector account for half of the emission budget (from 306 to 776 out of 1,000 GtCO2). However, the carbon intensity of transport decreases as much as other energy sectors in 2100

Low-carbon pathways consistent with the 2°C and 1.5°C long-term climate goals defined in the Paris Agreement are likely to induce substantial co-benefits for air pollution and associated health impacts. In this analysis, using five global integrated assessment models, we quantify the emission reductions in key air pollutants resulting from the decarbonization of energy systems and the resulting changes in premature mortality attributed to the exposure to ambient concentrations of fine particulate matter. The emission reductions differ by sectors. Sulfur emissions are mainly reduced from power plants and industry, cuts in nitrogen oxides are dominated by the transport sector, and the largest abatement of primary fine particles is achieved in the residential sector. The analysis also shows that health benefits are the largest when policies addressing climate change mitigation and stringent air pollution controls are coordinated. We decompose the key factors that determine the extent of health co-benefits, focusing on Asia: changes in emissions, urbanization rates, population growth and ageing. Demographic processes, particularly due to ageing population, counteract in many regions the mortality reductions realized through lower emissions.

Process-based integrated assessment models (IAMs) project long-term transformation pathways in energy and land-use systems under what-if assumptions. IAM evaluation is necessary to improve the models’ usefulness as scientific tools applicable in the complex and contested domain of climate change mitigation. We contribute the first comprehensive synthesis of process-based IAM evaluation research, drawing on a wide range of examples across six different evaluation methods including historical simulations, stylised facts, and model diagnostics. For each evaluation method, we identify progress and milestones to date, and draw out lessons learnt as well as challenges remaining. We find that each evaluation method has distinctive strengths, as well as constraints on its application. We use these insights to propose a systematic evaluation framework combining multiple methods to establish the appropriateness, interpretability, credibility, and relevance of process-based IAMs as useful scientific tools for informing climate policy. We also set out a programme of evaluation research to be mainstreamed both within and outside the IAM community.

The steel industry is responsible for a large share of the industrial energy consumption and greenhouse gas emissions and several long-term energy models have some representation of this sub-sector. It is found that models, commonly use a flow-based approach for projecting steel demand neglecting that in-use steel stocks serve as a better demand indicator than steel consumption. A stock-based method that uses the historical steel stock results from detailed material flow analysis is developed for making steel demand projections and implemented in the IMAGE Integrated Assessment Model. Large differences between the two approaches arise. For the first half of the 21st century, global steel demand increases with both approaches and at a similar rate to reach 2300 Mt/yr by 2050. For the second half of the 21st century, however, the developments differ drastically. With the stock-based approach, global steel demand decreases by 0.8%/a to reach 1600 Mt/yr, while with the flow-based approach it increases by 0.3%/a to reach 2600 Mt/yr in 2100. Given that steel production levels have a profound contribution to greenhouse gas emissions, using the right approach is crucial. This means that long-term energy models may currently overestimate the industrial emissions in the last half of the century. © 2021

Integrated assessment models (IAMs) form a prime tool in informing about climate mitigation strategies. Diagnostic indicators that allow comparison across these models can help describe and explain differences in model projections. This increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler (2015 Technol. Forecast. Soc. Change 90 45–61)). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, to systematically and routinely assess IAM behaviour, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index, emission reduction type index, inertia timescale, fossil fuel reduction, transformation index and cost per abatement value. We apply the approach to 17 IAMs, assessing both older as well as their latest versions, as applied in the IPCC 6th Assessment Report. The study shows that the approach can be easily applied and used to indentify key differences between models and model versions. Moreover, we demonstrate that this comparison helps to link model behavior to model characteristics and assumptions. We show that together, the set of six indicators can provide useful indication of the main traits of the model and can roughly indicate the general model behavior. The results also show that there is often a considerable spread across the models. Interestingly, the diagnostic values often change for different model versions, but there does not seem to be a distinct trend.

Keeping the Earth system in a stable and resilient state, in order to safeguard Earth's life support systems while ensuring that Earth's benefits, risks and related responsibilities are equitably shared, constitutes the grand challenge for human development in the Anthropocene. Here, we describe a framework that the recently formed Earth Commission will use to define and quantify target ranges for a ‘safe and just corridor’ that meets these goals. Although ‘safe’ and ‘just’ Earth system targets are interrelated, we see safe as primarily referring to a stable Earth system and just targets as being associated with meeting human needs and reducing exposure to risks. To align safe and just dimensions, we propose to address the equity dimensions of each safe target for Earth system regulating systems and processes. The more stringent of the safe or just target ranges then defines the corridor. Identifying levers of social transformation aimed at meeting the safe and just targets and challenges associated with translating the corridor to actors at multiple scales present scope for future work.

Given the increasing interest in keeping global warming below 1.5°C, a key question is what this would mean for China's emission pathway, energy restructuring, and decarbonization. By conducting a multimodel study, we find that the 1.5°C-consistent goal would require China to reduce its carbon emissions and energy consumption by more than 90 and 39%, respectively, compared with the "no policy" case. Negative emission technologies play an important role in achieving near-zero emissions, with captured carbon accounting on average for 20% of the total reductions in 2050. Our multimodel comparisons reveal large differences in necessary emission reductions across sectors, whereas what is consistent is that the power sector is required to achieve full decarbonization by 2050. The cross-model averages indicate that China's accumulated policy costs may amount to 2.8 to 5.7% of its gross domestic product by 2050, given the 1.5°C warming limit.

Limiting warming to well below 2°C requires rapid and complete decarbonisation of energy systems. We compare economy-wide modelling of 1.5°C and 2°C scenarios with sector-focused analyses of four critical sectors that are difficult to decarbonise: aviation, shipping, road freight transport, and industry. We develop and apply a novel framework to analyse and track mitigation progress in these sectors. We find that emission reductions in the 1.5°C and 2°C scenarios of the IMAGE model come from deep cuts in CO2 intensities and lower energy intensities, with minimal demand reductions in these sectors’ activity. We identify a range of additional measures and policy levers that are not explicitly captured in modelled scenarios but could contribute significant emission reductions. These are demand reduction options, and include less air travel (aviation), reduced transportation of fossil fuels (shipping), more locally produced goods combined with high load factors (road freight), and a shift to a circular economy (industry). We discuss the challenges of reducing demand both for economy-wide modelling and for policy. Based on our sectoral analysis framework, we suggest modelling improvements and policy recommendations, calling on the relevant UN agencies to start tracking mitigation progress through monitoring key elements of the framework (CO2 intensity, energy efficiency, and demand for sectoral activity, as well as the underlying drivers), as a matter of urgency.

Despite the scientific consensus on the extinction crisis and its anthropogenic origin, the quantification of historical trends and of future scenarios of biodiversity and ecosystem services has been limited, due to the lack of inter-model comparisons and harmonized scenarios. Here, we present a multi-model analysis to assess the impacts of land-use and climate change from 1900 to 2050. During the 20th century provisioning services increased, but biodiversity and regulating services decreased. Similar trade-offs are projected for the coming decades, but they may be attenuated in a sustainability scenario. Future biodiversity loss from land-use change is projected to keep up with historical rates or reduce slightly, whereas losses due to climate change are projected to increase greatly. Renewed efforts are needed by governments to meet the 2050 vision of the Convention on Biological Diversity.

Previous studies have projected a significant role for bioenergy in decarbonizing the global economy and helping realize international climate goals such as limiting global average warming to 2 ˚C or 1.5 ˚C. However, with substantial variability in bioenergy results and significant concerns about potential environmental and social implications, greater transparency and dedicated assessment of the underlying modeling and results and more detailed understanding of the potential role of bioenergy are needed. Stanford University’s Energy Modeling Forum (EMF) initiated a 33rd study (EMF-33) to explore the viability of large-scale bioenergy as part of a comprehensive climate management strategy. This special issue presents the papers of the EMF-33 study—a multi-year inter-model comparison project designed to understand and assess global, long-run biomass supply and bioenergy deployment potentials and related uncertainties. Using a novel scenario design with independent biomass supply and bioenergy demand protocols, EMF-33 separately elucidates and explores the modeling of biomass feedstock supplies and bioenergy technologies and their deployment—revealing, comparing, and assessing the modeling that is suggesting that bioenergy could be a key climate containment strategy. This introduction provides an overview of the EMF-33 study design and the overview, thematic, and individual modeling team papers and types of insights that make up this special issue. By providing enhanced transparency and new detailed insights, we hope to inform policy dialogue about the potential role of bioenergy and facilitate new research.

This paper explores the potential role of bioenergy coupled to carbon dioxide (CO2) capture and storage (BECCS) in long-term global scenarios. We first validate past insights regarding the potential use of BECCS in achieving climate goals based on results from 11 integrated assessment models (IAMs) that participated in the 33rd study of the Stanford Energy Modeling Forum (EMF-33). As found in previous studies, our results consistently project large-scale cost-effective BECCS deployment. However, we also find a strong synergistic nexus between CCS and biomass, with bioenergy the preferred fuel for CCS as the climate constraint increases. Specifically, the share of bioenergy that is coupled to CCS technologies increases since CCS effectively enhances the emissions mitigation capacity of bioenergy. For the models that include BECCS technologies across multiple sectors, there is significant deployment in conjunction with liquid fuel or hydrogen production to decarbonize the transportation sector. Using a wide set of scenarios, we find carbon removal to be crucial to achieving goals consistent with 1.5 °C warming. However, we find earlier BECCS deployment but not necessarily greater use in the long-term since ultimately deployment is limited by economic competition with other carbon-free technologies, especially in the electricity sector, by land-use competition (especially with food) affecting biomass feedstock availability and price, and by carbon storage limitations. The extent of BECCS deployment varies based on model assumptions, with BECCS deployment competitive in some models below carbon prices of 100 US$/tCO2. Without carbon removal, 2 °C is infeasible in some models, while those that solve find similar levels of bioenergy use but substantially greater mitigation costs. Overall, the paper provides needed transparency regarding BECCS’ role, and results highlight a strong nexus between bioenergy and CCS, and a large reliance on not-yet-commercial BECCS technologie

The role of energy in social and economic development is recognised by sustainable development goal 7 that targets three aspects of energy access: ensure universal access to affordable, reliable and modern energy services, substantially increase the share of renewable energy, and double the global rate of improvement in energy efficiency. With the projected increase in population, income and energy access in Sub-Saharan Africa, demand for energy services is expected to increase. This increase can be met through increasing the supply while at the same time improving households' energy efficiency. In this paper, we explore the interactions between the three SDG7 targets by applying two Integrated Assessment Models, IMAGE and MESSAGE, that incorporate socio-economic heterogeneity of the end-user. The results of the study depict the synergistic relationships between the three SDG7 objectives. Relative to pursuing only the universal access target, integration of all three targets could i) reduce residential final energy consumption by up to 25%, enabling the use of mini-grid and stand-alone systems to provide better energy services, ii) cut annual energy-use-related residential emissions by a third, and iii) lower energy related investments by up to 30% to save scarce finance.

To halt climate change this century, we must reduce carbon dioxide (CO2) emissions from human activities to net zero. Any emission sources, such as in the energy or land-use sectors, must be balanced by natural or technological carbon sinks that facilitate CO2 removal (CDR) from the atmosphere. Projections of demand for large-scale CDR are based on an integrated scenario framework for emission scenarios composed of emission profiles as well as alternative socio-economic development trends and social values consistent with them. The framework, however, was developed years before systematic reviews of CDR entered the literature. This primer provides an overview of the purposes of scenarios in climate-change research and how they are used. It also introduces the integrated scenario framework and why it came about. CDR studies using the scenario framework, as well as its limitations, are discussed. Possible future developments for the scenario framework are highlighted, especially in relation to CDR.

Mitigation of black carbon (BC) aerosol emissions can potentially contribute to both reducing air pollution and climate change, although mixed results have been reported regarding the latter. A detailed quantification of the synergy between global air quality and climate policy is still lacking. This study contributes with an integrated assessment model-based scenario analysis of BC-focused mitigation strategies aimed at maximizing air quality and climate benefits. The impacts of these policy strategies have been examined under different socio-economic conditions, climate ambitions, and BC mitigation strategies. The study finds that measures targeting BC emissions (including reduction of co-emitted organic carbon, sulfur dioxide, and nitrogen dioxides) result in significant decline in premature mortality due to ambient air pollution, in the order of 4 to 12 million avoided deaths between 2015 and 2030. Under certain circumstances, BC mitigation can also reduce climate change, i.e., mainly by lowering BC emissions in the residential sector and in high BC emission scenarios. Still, the effect of BC mitigation on global mean temperature is found to be modest at best (with a maximum short-term GMT decrease of 0.02 °C in 2030) and could even lead to warming (with a maximum increase of 0.05 °C in case of a health-focused strategy, where all aerosols are strongly reduced). At the same time, strong climate policy would improve air quality (the opposite relation) through reduced fossil fuel use, leading to an estimated 2 to 5 million avoided deaths in the period up to2030. By combining both air quality and climate goals, net health benefits can be maximized.

Seasonal mismatches between electricity supply and demand is increasing due to expanded use of wind, solar and hydropower resources, which in turn raises the interest on low-cost seasonal energy storage options. Seasonal pumped hydropower storage (SPHS) can provide long-term energy storage at a relatively low-cost and co-benefits in the form of freshwater storage capacity. We present the first estimate of the global assessment of SPHS potential, using a novel plant-siting methodology based on high-resolution topographical and hydrological data. Here we show that SPHS costs vary from 0.007 to 0.2 US$ m−1 of water stored, 1.8 to 50 US$ MWh−1 of energy stored and 370 to 600 US$ kW−1 of installed power generation. This potential is unevenly distributed with mountainous regions demonstrating significantly more potential. The estimated world energy storage capacity below a cost of 50 US$ MWh−1 is 17.3 PWh, approximately 79% of the world electricity consumption in 2017.

The concept of experience curves is normally applied to analyze cost or price developments of technologies, but studies have shown that the concept can also be extended to other applications and fields. In this chapter, we show the application of experience curves to analyze energy use in industrial processes, energy demand of household appliances and discuss its application to describe and project developments in environmental impact of technologies. A second part of the chapter shows a case study of applying the concept of technological learning to the field of social behavior in what is called social learning (SL). This part of the chapter shows how the diffusion of electric vehicles is affected by different SL mechanisms.