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A new paper in Nature by Welsby et al. makes clear that pursuing efforts to limit global average temperature increase to 1.5°C above pre-industrial levels—the most frequently stated goal of the 2015 Paris Agreement—implies the vast majority of coal, crude oil, and natural gas must remain underground and undeveloped.

Globally, there are a wide variety of policies in place that could help contribute to deep greenhouse gas (GHG) emissions reductions in the light-duty vehicle sector. Most regions are impacted by a mix of such policies. However, the transportation literature has devoted little attention to policy mixes, especially in the light-duty vehicles sector, so here we review and draw insights from the broader, mostly non-transport literature. We identify several rationales for pursuing mixes of policies: (i) the “three legs” approach to transport decarbonization, namely that different policies should address different GHG reduction areas (low-carbon fuels, vehicle efficiency and reduced travel demand), (ii) the “market failure” perspective that a different policy is needed to correct each market failure, (iii) the “political process” perspective that considers the real-world need for a policy mix to be perceived as political acceptability, and (iv) the “systems” perspective that policy needs to send signals to channel technological innovation and break the lock-in of incumbent practices. Based on this review, we develop a simple framework for examining policy interactions across multiple criteria, namely GHG mitigation, cost-effectiveness, political acceptability, and transformative signal. We demonstrate this framework by setting hypotheses for interactions across six light-duty vehicle policies in the case of British Columbia, Canada – including a carbon tax, electric vehicle purchase incentives, infrastructure deployment, and three regulations. We conclude with a summary of important research gaps and implications for policy design, as well as quantitative modeling.

Integrated assessment models (IAMs) connect trends in future socioeconomic and technological development with impacts on the environment, such as global climate change. They occupy a critical position at the global science-policy interface. IAMs and associated scenarios have come under intense scrutiny, with critiques addressing both methodological and substantive issues, such as land use, carbon dioxide removal and technology performance. Criticisms have also addressed the transparency of IAM methods and assumptions as well as the transparency of the Intergovernmental Panel on Climate Change (IPCC) assessment of IAMs. This paper, authored by the co-chairs of IPCC Working Group III and members of the Technical Support Unit, documents activities aiming to enhance the transparency of IAMs and their assessment. It includes a history of IPCC's approach to scenarios covering the formation of the Integrated Assessment Modeling Consortium (IAMC) in 2007 and the emergence of the approach by which IPCC facilitates the development of scenarios, but does not produce them itself. An IPCC Expert Meeting at the start of the current assessment cycle made transparency recommendations targeted at both the research community and IPCC. The community has taken steps to “open the black box” by moving toward open-source and web-publishing IAM documentation. IPCC has included an Annex to its next report focusing on scenarios and modeling methodologies. An open call for scenario data linked to the current IPCC report includes an expanded set of input and output variables. This paper ends with suggested criteria for measuring the success of these efforts to improve transparency.

Governments around the globe are responding to the coronavirus disease 2019 (COVID-19)–related economic crisis with unprecedented economic recovery packages (1), which at the time of writing surpassed USD 12 trillion. Several influential voices, including the United Nations (UN) secretary-general, heads of state, companies, investors, and central banks, have called for post–COVID-19 economic recovery efforts to be used to catalyze the necessary longer-term transformation toward a more sustainable and resilient society. Here we shine a light on the opportunity for these investments to support a green recovery by inventorying and classifying the latest information on governments' fiscal stimulus plans (1) and comparing the size of these measures to estimates of low-carbon energy investment needs compatible with the 2015 UN Paris Agreement. We show that low-carbon investments to put the world on an ambitious track toward net zero carbon dioxide emissions by mid-century are dwarfed by currently announced COVID-19 stimulus funds. But marked differences across countries and regions at differing stages of development emphasize the role that international support and global partnership must play to create conditions that enable a global climate-positive recovery.

Climate change mitigation scenarios are finding a wider set of users, including companies and financial institutions. Increased collaboration between scenario producers and these new communities will be mutually beneficial, educating companies and investors on climate risks while grounding climate science in real-world needs.

The existing literature has shown the important role of electrification in deep decarbonization pathways, increasing electricity demand as end uses decarbonize. However, studies have not focused on the effects of electrification on aggregate load shapes and peak demand, which influence power sector investments, operations, and costs. Here we investigate potential impacts of deep decarbonization on regional load shapes and peak electricity demand using a detailed end-use simulation model linked to an electric sector capacity planning model. Scenario results suggest that electrification may contribute to peak load increases and shifts from summer peaks to winter ones, especially in cooler climates due to space heating electrification. We illustrate how net-zero emissions goals can amplify electrification and may entail 120%–165% increases in electric system capacity by 2050 due to a combination of electrification and high renewables deployment. The intensity and frequency of peak demand can be limited by load flexibility (providing incentives for electric end uses to shift away from periods of high demand, e.g. through deferrable electric vehicle charging), alternate end-use technology configurations (deploying higher efficiency end-use equipment to lower electricity consumption during peaks or using dual-fuel systems such as heat pumps paired with gas furnaces), and carbon removal (displacing higher marginal abatement cost electrification while reaching an equivalent emissions cap). This analysis is a first step toward systematically exploring load curves for electrified and decarbonized energy systems, and the results highlight opportunities for future research to better understand load shape impacts and flexibility.

Energy scenarios project future possibilities based on a variety of assumptions, yet do not fully account for inherent friction in the energy transition, particularly over the near term. A new study shows how machine learning can complement existing scenario tools by incorporating lessons from the past into projections for the future.

Income and fuel price pathways are key determinants in projections of the energy system in integrated assessment models. In recent years, more details have been added to the transport sector representation in these models. To better understand the model dynamics, this manuscript analyses transport fuel demand elasticities to projected income and fuel price levels. Fuel price shocks were simulated under various scenario assumptions to isolate price effects on energy demand and create a transparent environment to compare fuel demand response. Interestingly, the models show very comparable oil price elasticity values for the projected first 10-20. years that are also close to the range described in the empirical literature. When looking at the very long term (30-40. years), demand elasticity values widely vary between models, between 0.4 and -1.9, showing either continuous demand or increased demand responses over time. The latter can be the result of long response time to fuel price shocks, availability of new technologies, and feedback effects on fuel prices. The projected transport service demand is more responsive to changes in income than fuel price pathways, corresponding with the literature. Calculating the models' inherent elasticities proved to be a suitable method to evaluate model behaviour and its application is also recommended for other models as well as other sectors represented in integrated assessment models.

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.

International audience

Exploring potential future pathways for developing Asia’s energy consumption, CO2 emissions and infrastructure investment needs is essential to understanding how the countries of this rapidly growing region may contribute to the global climate targets set out in the 2015 Paris Agreement. To this end, this study employs the state-of-the-art global integrated assessment model MESSAGEix-GLOBIOM to investigate mid-century decarbonization strategies for developing Asia to 2050. Our results indicate that a radical change in the energy portfolio is required to reach the target of ‘well below’ 2°C. Specifically, our scenarios point to a rapid reduction of fossil fuel utilization, enhancement of low-carbon energy supply, and boosting of energy efficiency efforts. Such a transformation leads to a deep cut in CO2 emissions by 78% and 93% by 2050 in scenarios consistent with the 2°C and 1.5°C targets, respectively. Electricity generation and final energy consumption become dominated by low-carbon energy by 2050 in these scenarios. In terms of investment needs beyond a baseline scenario, the 2°C and 1.5°C pathways imply that the scale of low-carbon investment may need to double and triple, respectively. These increases would be partially offset by disinvestment in coal, oil and natural gas extraction and conversion infrastructure. Decarbonizing the energy system also impacts the capital needed for making progress on other sustainable development goals (SDGs), such as air pollution, clean water and food security.

Little research explores automaker response to supply-focused regulation in the long-run, such as zero-emissions vehicle (ZEV) mandates. To that end, we develop and apply the AUtomaker-consumer Model (AUM), which simulates interactions between behaviorally-realistic consumers and a profit maximizing automaker from 2020 to 2030. AUM endogenously represents multi-year foresight for the automaker, including decisions about: (i) increasing ZEV model variety, (ii) intra-firm cross-price subsidies, and (iii) investing in R&D to reduce future ZEV costs. Under both optimistic and pessimistic conditions, automakers are simulated to fully or mostly comply with a 2030 requirement of 30% ZEV sales (rather than pay a penalty). Of the three compliance mechanisms, intra-firm cross-price subsidization dominates. The policy could reduce automaker profit by 7% to 44% in 2030 (relative to the baseline in the same year), mostly due to reduced vehicle sales in total, though overall profits still grow year-on-year from 2020. We identify key uncertainties in these results.

The authors are founding team members of a new effort to develop an Open Energy Outlook for the United States. The effort aims to apply best practices of policy-focused energy system modeling, ensure transparency, build a networked community, and work toward a common purpose: examining possible US energy system futures to inform energy and climate policy efforts. Individual author biographies can be found on the project website: https://openenergyoutlook.org/. DeCarolis et al. articulate the benefits of forming collaborative teams with a wide array of disciplinary and domain expertise to conduct analysis with macro-energy system models. Open-source models, tools, and datasets underpin such efforts by enabling transparency, accessibility, and replicability among team members and with the broader modeling community.

Energy systems support technical solutions fulfilling the United Nations’ Sustainable Development 2 Goal for clean water and sanitation (SDG6), with implications for future energy demands and greenhouse 3 gas emissions. The energy sector is also a large consumer of water, making water efficiency targets in4 grained in SDG6 important constraints for long-term energy planning. Here, we apply a global integrated 5 assessment model to quantify the cost and characteristics of infrastructure pathways balancing SDG6 tar6 gets for water access, scarcity, treatment and efficiency with long-term energy transformations limiting climate warming to 1.5 ◦ 7 C. Under a mid-range human development scenario, we find that approximately 8 1 trillion USD2010 per year is required to close water infrastructure gaps and operate water systems consistent with achieving SDG6 goals by 2030. Adding a 1.5 ◦ 9 C climate policy constraint increases these costs by up to 8 %. In the reverse direction, when the SDG6 targets are added on top of the 1.5 ◦ 10 C policy 11 constraint, the cost to transform and operate energy systems increases 2 to 9 % relative to a baseline 1.5 ◦ 12 C scenario that does not achieve the SDG6 targets by 2030. Cost increases in the SDG6 pathways 13 are due to expanded use of energy-intensive water treatment and costs associated with water conserva14 tion measures in power generation, municipal, manufacturing and agricultural sectors. Combined global spending (capital and operational expenditures) in the integrated SDG6-1.5 ◦ 15 C scenarios to 2030 on water and energy systems increases 92 to 125 % relative to a baseline scenario without 1.5 ◦ 16 C and SDG6 17 constraints. Evaluation of the multi-sectoral policies underscores the importance of water conservation 18 and integrated water-energy planning for avoiding costs from interacting water, energy and climate goals.

The radical change in recent global climate governance calls for China and Europe to ramp up their efforts in leading the world to reach the long-term climate goals. By analyzing the results from the state-of-the-art global integrated assessment model, MESSAGEix-GLOBIOM, this paper aims to understand the future levels of financial investment needed for building and maintaining energy-related infrastructure in the two regions for fulfilling stringent targets consistent with ‘well below 2 °C’. The results indicate that a rapid upscaling and structural change of these investments towards decarbonization are necessitated by the climate stringent scenarios. China and Europe need to increase their low carbon investments by 65% and 38% in a scenario reaching the 2° target relative to their respective reference scenarios which assume no such target from 2016–2050. In a more stringent climate policy scenario of the 1.5° target, these investment needs will increase by 149% and 79% for China and Europe respectively. Among all the energy sectors, energy efficiency, renewable electricity generation and electricity transmission and distribution are the three largest investing targets for the two regions. However, those investments will not likely be realized without strong policy incentives. Implications for green finance and multilateral cooperation initiatives are discussed in the context of the scenario results.

The bottom-up approach of the Nationally Determined Contributions (NDCs) in the Paris Agreement has led countries to self-determine their greenhouse gas (GHG) emission reduction targets. The planned ‘ratcheting-up’ process, which aims to ensure that the NDCs comply with the overall goal of limiting global average temperature increase to well below 2 °C or even 1.5 °C, will most likely include some evaluation of ‘fairness’ of these reduction targets. In the literature, fairness has been discussed around equity principles, for which many different effort-sharing approaches have been proposed. In this research, we analysed how country-level emission targets and carbon budgets can be derived based on such criteria. We apply novel methods directly based on the global carbon budget, and, for comparison, more commonly used methods using GHG mitigation pathways. For both, we studied the following approaches: equal cumulative per capita emissions, contraction and convergence, grandfathering, greenhouse development rights and ability to pay. As the results critically depend on parameter settings, we used the wide authorship from a range of countries included in this paper to determine default settings and sensitivity analyses. Results show that effort-sharing approaches that (i) calculate required reduction targets in carbon budgets (relative to baseline budgets) and/or (ii) take into account historical emissions when determining carbon budgets can lead to (large) negative remaining carbon budgets for developed countries. This is the case for the equal cumulative per capita approach and especially the greenhouse development rights approach. Furthermore, for developed countries, all effort-sharing approaches except grandfathering lead to more stringent budgets than cost-optimal budgets, indicating that cost-optimal approaches do not lead to outcomes that can be regarded as fair according to most effort-sharing approaches.

In the version of ‘Supplementary Data 1’ originally published with this Article, the units for the ‘Capacity|Electricity|*’ variables in the ‘Non_Investment_Annual’ tab were incorrectly given as EJ/yr; they should have read GW. This has now been corrected. Also, some of the variables listed in the ‘Non_Investment_Variable_Defs’ were not required and have therefore been removed.

Scenarios that limit global warming to 1.5 °C describe major transformations in energy supply and ever-rising energy demand. Here, we provide a contrasting perspective by developing a narrative of future change based on observable trends that results in low energy demand. We describe and quantify changes in activity levels and energy intensity in the global North and global South for all major energy services. We project that global final energy demand by 2050 reduces to 245 EJ, around 40% lower than today, despite rises in population, income and activity. Using an integrated assessment modelling framework, we show how changes in the quantity and type of energy services drive structural change in intermediate and upstream supply sectors (energy and land use). Down-sizing the global energy system dramatically improves the feasibility of a low-carbon supply-side transformation. Our scenario meets the 1.5 °C climate target as well as many sustainable development goals, without relying on negative emission technologies. Achieving sustainable development goals while meeting the 1.5 °C climate target requires radical changes to how we use energy. A scenario of low energy demand shows how this can be done by down-sizing the global energy system to enable feasible deployment rates of renewable energy resources.

To investigate the complex relationships among the energy-related challenges faced by humanity, we marry a large-scale energy systems model, MESSAGE, with a multi-criteria model analysis tool. Such an approach is applicable to other modelling frameworks and can significantly improve the analysis of multiple goals. We focus our study on nuclear power – a technology viewed differently by different stakeholders. We find that nuclear power plays an important role in global climate change mitigation efforts where energy security and affordability goals take precedence, but that the total amount of nuclear in the system is highly dependent on stakeholders' preferences. We also find synergies among climate mitigation and energy security goals, and also between these two goals and the reduced need for underground carbon storage. Keywords: Energy system model, Nuclear power, Multi-criteria analysis, Climate change

Pursuing integrated research and decision-making to advance action on the sustainable development goals (SDGs) fundamentally depends on understanding interactions between the SDGs, both negative ones (“trade-offs”) and positive ones (“co-benefits”). This quest, triggered by the 2030 Agenda, has however pointed to a gap in current research and policy analysis regarding how to think systematically about interactions across the SDGs. This paper synthesizes experiences and insights from the application of a new conceptual framework for mapping and assessing SDG interactions using a defined typology and characterization approach. Drawing on results from a major international research study applied to the SDGs on health, energy and the ocean, it analyses how interactions depend on key factors such as geographical context, resource endowments, time horizon and governance. The paper discusses the future potential, barriers and opportunities for applying the approach in scientific research, in policy making and in bridging the two through a global SDG Interactions Knowledge Platform as a key mechanism for assembling, systematizing and aggregating knowledge on interactions.

The transition to electric vehicles is an important strategy for reducing greenhouse gas emissions from passenger cars. Modelling future pathways helps identify critical drivers and uncertainties. Global integrated assessment models (IAMs) have been used extensively to analyse climate mitigation policy. IAMs emphasise technological change processes but are largely silent on important social and behavioural dimensions to future technological transitions. Here, we develop a novel conceptual framing and empirical evidence base on social learning processes relevant for vehicle adoption. We then implement this formulation of social learning in IMAGE, a widely-used global IAM. We apply this new modelling approach to analyse how technological learning and social learning interact to influence electric vehicle transition dynamics. We find that technological learning and social learning processes can be mutually reinforcing. Increased electric vehicle market shares can induce technological learning which reduces technology costs while social learning stimulates diffusion from early adopters to more risk-averse adopter groups. In this way, both types of learning process interact to stimulate each other. In the absence of social learning, however, the perceived risks of electric vehicle adoption among later-adopting groups remains prohibitively high. In the absence of technological learning, electric vehicles remain relatively expensive and therefore is only an attractive choice for early adopters. This first-of-its-kind model formulation of both social and technological learning is a significant contribution to improving the behavioural realism of global IAMs. Applying this new modelling approach emphasises the importance of market heterogeneity, real-world consumer decision-making, and social dynamics as well as technology parameters, to understand climate mitigation potentials.

Hopes are high that removing fossil fuel subsidies could help to mitigate climate change by discouraging inefficient energy consumption and levelling the playing field for renewable energy. In September 2016, the G20 countries re-affirmed their 2009 commitment (at the G20 Leaders' Summit) to phase out fossil fuel subsidies and many national governments are using today's low oil prices as an opportunity to do so. In practical terms, this means abandoning policies that decrease the price of fossil fuels and electricity generated from fossil fuels to below normal market prices. However, whether the removal of subsidies, even if implemented worldwide, would have a large impact on climate change mitigation has not been systematically explored. Here we show that removing fossil fuel subsidies would have an unexpectedly small impact on global energy demand and carbon dioxide emissions and would not increase renewable energy use by 2030. Subsidy removal would reduce the carbon price necessary to stabilize greenhouse gas concentration at 550 parts per million by only 2-12 per cent under low oil prices. Removing subsidies in most regions would deliver smaller emission reductions than the Paris Agreement (2015) climate pledges and in some regions global subsidy removal may actually lead to an increase in emissions, owing to either coal replacing subsidized oil and natural gas or natural-gas use shifting from subsidizing, energy-exporting regions to non-subsidizing, importing regions. Our results show that subsidy removal would result in the largest CO 2 emission reductions in high-income oil- and gas-exporting regions, where the reductions would exceed the climate pledges of these regions and where subsidy removal would affect fewer people living below the poverty line than in lower-income regions.

Low-carbon investments are necessary for driving the energy system transformation that is called for by both the Paris Agreement and Sustainable Development Goals. Improving understanding of the scale and nature of these investments under diverging technology and policy futures is therefore of great importance to decision makers. Here, using six global modelling frameworks, we show that the pronounced reallocation of the investment portfolio required to transform the energy system will not be initiated by the current suite of countries’ Nationally Determined Contributions. Charting a course toward ‘well below 2 °C’ instead sees low-carbon investments overtaking fossil investments globally by around 2025 or before and growing thereafter. Pursuing the 1.5 °C target demands a marked upscaling in low-carbon capital beyond that of a 2 °C-consistent future. Actions consistent with an energy transformation would increase the costs of achieving the goals of energy access and food security, but reduce the costs of achieving air-quality goals. The scale and nature of energy investments under diverging technology and policy futures is of great importance to decision makers. Here, a multi-model study projects investment needs under countries’ nationally determined contributions and in pathways consistent with achieving the 2 °C and 1.5 °C targets as well as certain SDGs.

The CA-TIMES optimization model of the California Energy System (v1.5) is used to understand how California can meet the 2050 targets for greenhouse gas (GHG) emissions (80% below 1990 levels). This model represents energy supply and demand sectors in California and simulates the technology and resource requirements needed to meet projected energy service demands. The model includes assumptions on policy constraints, as well as technology and resource costs and availability. Multiple scenarios are developed to analyze the changes and investments in low-carbon electricity generation, alternative fuels and advanced vehicles in transportation, resource utilization, and efficiency improvements across many sectors. Results show that major energy transformations are needed but that achieving the 80% reduction goal for California is possible at reasonable average carbon reduction cost ($9 to $124/tonne CO2e at 4% discount rate) relative to a baseline scenario. Availability of low-carbon resources such as nuclear power, carbon capture and sequestration (CCS), biofuels, wind and solar generation, and demand reduction all serve to lower the mitigation costs, but CCS is a key technology for achieving the lowest mitigation costs.

A large body of transport sector-focused research recognizes the complexity of human behavior in relation to mobility. Yet, global integrated assessment models (IAMs), which are widely used to evaluate the costs, potentials, and consequences of different greenhouse gas emission trajectories over the medium-to-long term, typically represent behavior and the end use of energy as a simple rational choice between available alternatives, even though abundant empirical evidence shows that real-world decision making is more complex and less routinely rational. This paper demonstrates the value of incorporating certain features of consumer behavior in IAMs, focusing on light-duty vehicle (LDV) purchase decisions. An innovative model formulation is developed to represent heterogeneous consumer groups with varying preferences for vehicle novelty, range, refueling/recharging availability, and variety. The formulation is then implemented in the transport module of MESSAGE-Transport, a global IAM, although it also has the generic flexibility to be applied in energy-economy models with varying set-ups. Comparison of conventional and ‘behaviorally-realistic’ model runs with respect to vehicle purchase decisions shows that consumer preferences may slow down the transition to alternative fuel (low-carbon) vehicles. Consequently, stronger price-based incentives and/or non-price based measures may be needed to transform the global fleet of passenger vehicles, at least in the initial market phases of novel alternatives. Otherwise, the mitigation burden borne by other transport sub-sectors and other energy sectors could be higher than previously estimated. More generally, capturing behavioral features of energy consumers in global IAMs increases their usefulness to policy makers by allowing a more realistic assessment of a more diverse suite of policies.

The UK electricity system is undergoing a significant transformation. Increasing penetration of renewable generation and integration of new consumer technologies (e.g. electric vehicles) challenge the traditional way of balancing electricity in the grid, whereby supply matches demand. Demand-side management (DSM) has been shown to offer a promising solution to the above problem. However, models proposed in literature typically consider an isolated system whereby a single aggregator coordinates homogeneous consumers. As a result potential externalities of DSM are overlooked. This work explores the value of DSM in the context of an interacting electricity system, where utilities compete for cheap electricity in the wholesale market. A stylized model of the UK electricity system is proposed, whereby a traditional supplier competes with a ‘green’ supplier in the wholesale market. The modelling was able to show that with enough dispatchable capacity the traditional supplier was able to benefit from instructing his consumers to increase demand peaks, which had an adverse effect on the system.

Representative Concentration Pathways (RCPs) play a central role in assessments conducted by the climate modelling community. This study comprehensively assesses air pollution emissions in the RCPs and provides projections for air pollutants over the 21st century. Such projections should increase understanding of the range of possible impacts of air pollutants on the climate.

This paper analyzes the role of transport electrification in the broader context of energy system transformation and climate stabilization. As part of the EMF27 model inter-comparison exercise, we employ the MESSAGE integrated assessment modeling framework to conduct a systematic variation of availability, cost, and performance of particular energy supply technologies, thereby deriving implications for feasibility of climate stabilization goals and the associated costs of mitigation. In addition, we explore a wide range of assumptions regarding the potential degree of electrification of the transportation sector. These analyses allow us to (i) test the extent to which the feasible attainment of stringent climate policy targets depends on transport electrification, and (ii) assess the far-reaching impacts that transport electrification could have throughout the rest of the energy system. A detailed analysis of the transition to electricity within the transport sector is not conducted. Our results indicate that while a low-carbon transport system built upon conventional liquid-based fuel delivery infrastructures is destined to become increasingly reliant on biofuels and synthetic liquids, electrification opens up a door through which nuclear energy and non-biomass renewables can flow. The latter has important implications for mitigation costs.

International audience; The transport sector is growing fast in terms of energy use and accompanying greenhouse gas emissions. Integrated assessment models (IAMs) are used widely to analyze energy system transitions over a decadal time frame to help inform and evaluating international climate policy. As part of this, IAMs also explore pathways of decarbonizing the transport sector. This study quantifies the contribution of changes in activity growth, modal structure, energy intensity and fuel mix to the projected passenger transport carbon emission pathways. The Laspeyres index decomposition method is used to compare results across models and scenarios, and against historical transport trends. Broadly-speaking the models show similar trends, projecting continuous transport activity growth, reduced energy intensity and in some cases modal shift to carbon-intensive modes - similar to those observed historically in a business-as-usual scenario. In policy-induced mitigation scenarios further enhancements of energy efficiency and fuel switching is seen, showing a clear break with historical trends. Reduced activity growth and modal shift (towards less carbon-intensive modes) only have a limited contribution to emission reduction. Measures that could induce such changes could possibly complement the aggressive, technology switch required in the current scenarios to reach internationally agreed climate targets.

We present a unique and transparent approach for incorporating social influence effects into global integrated assessment models used to analyse climate change mitigation. We draw conceptually on Rogers (2003) diffusion of innovations, introducing heterogeneous and interconnected consumers who vary in their aversion to new technologies. Focussing on vehicle choice, we conduct novel empirical research to parameterise consumer risk aversion and how this is shaped by social and cultural influences. We find robust evidence for social influence effects, and variation between countries as a function of cultural differences. We then formulate an approach to modelling social influence which is implementable in both simulation and optimisation-type models. We use two global integrated assessment models (IMAGE and MESSAGE) to analyse four scenarios that introduce social influence and cultural differences between regions. These scenarios allow us to explore the interactions between consumer preferences and social influence. We find that incorporating social influence effects into global models accelerates the early deployment of electric vehicles and stimulates more widespread deployment across adopter groups. Incorporating cultural variation leads to significant differences in deployment between culturally divergent regions such as the USA and China. Our analysis significantly extends the ability of global integrated assessment models to provide policy-relevant analysis grounded in real world processes.

At Rio+20, the United Nations established global targets for energy access, renewable energy and energy efficiency in the context of sustainable development and eradication of poverty, as well as climate risk mitigation. This Perspective discusses the consistency of these targets with the overarching goal of limiting global temperature increase to below 2 °C.

This paper assesses three key energy sustainability objectives: energy security improvement, climate change mitigation, and the reduction of air pollution and its human health impacts. We explain how the common practice of narrowly focusing on singular issues ignores potentially enormous synergies, highlighting the need for a paradigm shift toward more holistic policy approaches. Our analysis of a large ensemble of alternate energy-climate futures, developed using MESSAGE, an integrated assessment model, shows that stringent climate change policy offers a strategic entry point along the path to energy sustainability in several dimensions. Concerted decarbonization efforts can lead to improved air quality, thereby reducing energy-related health impacts worldwide: upwards of 2–32 million fewer disability-adjusted life years in 2030, depending on the aggressiveness of the air pollution policies foreseen in the baseline. At the same time, low-carbon technologies and energy-efficiency improvements can help to further the energy security goals of individual countries and regions by promoting a more dependable, resilient, and diversified energy portfolio. The cost savings of these climate policy synergies are potentially enormous: $100–600 billion annually by 2030 in reduced pollution control and energy security expenditures (0.1–0.7 % of GDP). Novel aspects of this paper include an explicit quantification of the health-related co-benefits of present and future air pollution control policies; an analysis of how future constraints on regional trade could influence energy security; a detailed assessment of energy expenditures showing where financing needs to flow in order to achieve the multiple energy sustainability objectives; and a quantification of the relationships between different fulfillment levels for energy security and air pollution goals and the probability of reaching the 2 °C climate target.

For more than a decade, the target of keeping global warming below 2 °C has been a key focus of the international climate debate. In response, the scientific community has published a number of scenario studies that estimate the costs of achieving such a target. Producing these estimates remains a challenge, particularly because of relatively well known, but poorly quantified, uncertainties, and owing to limited integration of scientific knowledge across disciplines. The integrated assessment community, on the one hand, has extensively assessed the influence of technological and socio-economic uncertainties on low-carbon scenarios and associated costs. The climate modelling community, on the other hand, has spent years improving its understanding of the geophysical response of the Earth system to emissions of greenhouse gases. This geophysical response remains a key uncertainty in the cost of mitigation scenarios but has been integrated with assessments of other uncertainties in only a rudimentary manner, that is, for equilibrium conditions. Here we bridge this gap between the two research communities by generating distributions of the costs associated with limiting transient global temperature increase to below specific values, taking into account uncertainties in four factors: geophysical, technological, social and political. We find that political choices that delay mitigation have the largest effect on the cost-risk distribution, followed by geophysical uncertainties, social factors influencing future energy demand and, lastly, technological uncertainties surrounding the availability of greenhouse gas mitigation options. Our information on temperature risk and mitigation costs provides crucial information for policy-making, because it clarifies the relative importance of mitigation costs, energy demand and the timing of global action in reducing the risk of exceeding a global temperature increase of 2 °C, or other limits such as 3 °C or 1.5 °C, across a wide range of scenarios.

Fossil resource endowments and the future development of fossil fuel prices are important factors that will critically influence the nature and direction of the global energy system. In this paper we analyze a multi-model ensemble of long-term energy and emissions scenarios that were developed within the framework of the EMF27 integrated assessment model intercomparison exercise. The diverse nature of these models highlights large uncertainties in the likely development of fossil resource (coal, oil, and natural gas) consumption, trade, and prices over the course of the twenty-first century and under different climate policy frameworks. We explore and explain some of the differences across scenarios and models and compare the scenario results with fossil resource estimates from the literature. A robust finding across the suite of IAMs is that the cumulative fossil fuel consumption foreseen by the models is well within the bounds of estimated recoverable reserves and resources. Hence, fossil resource constraints are, in and of themselves, unlikely to limit future GHG emissions this century. Our analysis also shows that climate mitigation policies could lead to a major reallocation of financial flows between regions, in terms of expenditures on fossil fuels and carbon, and can help to alleviate near-term energy security concerns via the reductions in oil imports and increases in energy system diversity they will help to motivate. Aggressive efforts to promote energy efficiency are, on their own, not likely to lead to markedly greater energy independence, however, contrary to the stated objectives of certain industrialized countries., JRC.J.1-Economics of Climate Change, Energy and Transport

This is a corrigendum for the article 2015 Environ. Res. Lett. 10 075003

Oil prices have fluctuated remarkably in recent years. Previous studies have analysed the impacts of future oil prices on the energy system and greenhouse gas emissions, but none have quantitatively assessed how the broader, energy-system-wide impacts of diverging oil price futures depend on a suite of critical uncertainties. Here we use the MESSAGE integrated assessment model to study several factors potentially influencing this interaction, thereby shedding light on which future unknowns hold the most importance. We find that sustained low or high oil prices could have a major impact on the global energy system over the next several decades; and depending on how the fuel substitution dynamics play out, the carbon dioxide consequences could be significant (for example, between 5 and 20% of the budget for staying below the internationally agreed 2 ∘C target). Whether or not oil and gas prices decouple going forward is found to be the biggest uncertainty. The recent drop in oil prices is having a profound impact on global energy markets, raising questions about how these markets might evolve over the long term. This study uses scenarios to assess the energy and emissions impacts of diverging oil price futures and which uncertainties they depend upon.

Studies of global environmental change make extensive use of scenarios to explore how the future can evolve under a consistent set of assumptions. The recently developed Shared Socioeconomic Pathways (SSPs) create a framework for the study of climate-related scenario outcomes. Their five narratives span a wide range of worlds that vary in their challenges for climate change mitigation and adaptation. Here we provide background on the quantification that has been selected to serve as the reference, or ‘marker’, implementation for SSP2. The SSP2 narrative describes a middle-of-the-road development in the mitigation and adaptation challenges space. We explain how the narrative has been translated into quantitative assumptions in the IIASA Integrated Assessment Modelling Framework . We show that our SSP2 marker implementation occupies a central position for key metrics along the mitigation and adaptation challenge dimensions. For many dimensions the SSP2 marker implementation also reflects an extension of the historical experience, particularly in terms of carbon and energy intensity improvements in its baseline. This leads to a steady emissions increase over the 21st century, with projected end-of-century warming nearing 4 °C relative to preindustrial levels. On the other hand, SSP2 also shows that global-mean temperature increase can be limited to below 2 °C, pending stringent climate policies throughout the world. The added value of the SSP2 marker implementation for the wider scientific community is that it can serve as a starting point to further explore integrated solutions for achieving multiple societal objectives in light of the climate adaptation and mitigation challenges that society could face over the 21st century.

We use the MESSAGE model to examine multiple dimensions of sustainable development for three Asian regions in a set of scenarios developed for the Asian Modelling Exercise. Using climate change mitigation as a starting point for the analysis, we focus on the interaction of climate and energy with technology choice, energy security, energy access, and air pollution, which often have higher policy priority than climate change. Stringent climate policies drive the future energy supply in Asia from being dominated by coal and oil to a more diversified system based mostly on natural gas, coal with CCS, nuclear and renewable energy. The increase in diversity helps to improve the energy security of individual countries and regions. Combining air pollution control policies and universal energy access policies with climate policy can further help to reduce both outdoor and indoor air pollution related health impacts. Investments into the energy system must double by 2030 to achieve stringent climate goals, but are largely offset by lower costs for O&M and air pollution abatement. Strong focus on end-use efficiency also helps lowering overall total costs and allows for limiting or excluding supply side technologies from the mitigation portfolio. Costs of additional energy access policies and measures are a small fraction of total energy system costs.

Reaching the economic, environmental and sustainability objectives of all societies requires overcoming several major energy challenges; it necessitates rapid progress in multiple areas. The scenario pathways presented in this paper describe transformative changes toward these goals, taking a broad view of the four main energy challenges faced by society in the 21st century: providing universal access to modern energy for all; reducing the impacts of energy production on human health and the environment; avoiding dangerous climate change; and enhancing energy security. The overarching objective of the paper is to provide policy guidance on how to facilitate the transformation of the energy system to achieve these multiple energy objectives. Particular focus is given to the required pace of the transformation at both the global and regional levels, and to the types of financial and policy measures that will be needed to ensure a successful transition. Synergies and trade-offs between the objectives are identified, and co-benefits quantified. The paper makes an important contribution to the scenario literature by approaching the global transition toward sustainable development in a more integrated, holistic manner than is common in other studies.

California has taken a leading role in regulating greenhouse gas (GHG) emissions, requiring that its economy-wide emissions be brought back down to the 1990 level by 2020. The state also has a long-term, aspirational goal of an 80 percent reduction below the 1990 level by 2050. While the steps needed to achieve the near-term target have already been clearly defined by California policy makers, the suite of transformational technologies and policies required to decarbonize the energy system over the long term have not yet been explored. This paper describes an effort to fill this important gap, introducing CA-TIMES, a bottom-up, technologically-rich, integrated energy–engineering–environmental–economic systems model that has been developed to guide the long-term policy planning process. CA-TIMES is useful for exploring low-carbon scenarios, and the analyses described here focus on the potential evolution of the transportation, fuel supply, and electric generation sectors over the next several decades in response to various energy and climate policies. We find that meeting California’s 80% emission reduction goal can be achieved through a combination of mitigation strategies, including managing the growth in energy service demand, increasing investments in efficiency and low-carbon energy supply technologies, and promoting demand technologies that facilitate end-use device electrification and a decrease in the direct use of hydrocarbon fuels through efficiency improvement and fuel switching. In such deep emission reduction scenarios, we estimate that energy system costs (accounting for investments on the energy supply side and in transportation demand technologies, as well as fuel and O&M costs) could be around 8–17% higher than in a reference case. Meanwhile, average abatement costs could range from $107 to $225/tCO2. These estimates are very much dependent on a range of socio-political and technological uncertainties, for instance, the availability and cost of biomass, nuclear power, carbon capture and storage, and electric and hydrogen vehicles. Keywords: Energy modeling, Energy scenarios, Climate change mitigation, Transportation, Alternative fuels

This paper investigates the potential for making deep cuts in US transportation greenhouse gas (GHG) emissions in the long-term (50–80% below 1990 levels by 2050). Scenarios are used to envision how such a significant decarbonization might be achieved through the application of advanced vehicle technologies and fuels, and various options for behavioral change. A Kaya framework that decomposes GHG emissions into the product of four major drivers is used to analyze emissions and mitigation options. In contrast to most previous studies, a relatively simple, easily adaptable modeling methodology is used which can incorporate insights from other modeling studies and organize them in a way that is easy for policymakers to understand. Also, a wider range of transportation subsectors is considered here—light- and heavy-duty vehicles, aviation, rail, marine, agriculture, off-road, and construction. This analysis investigates scenarios with multiple options (increased efficiency, lower-carbon fuels, and travel demand management) across the various subsectors and confirms the notion that there are no “silver bullet” strategies for making deep cuts in transport GHGs. If substantial emission reductions are to be made, considerable action is needed on all fronts, and no subsectors can be ignored. Light-duty vehicles offer the greatest potential for emission reductions; however, while deep reductions in other subsectors are also possible, there are more limitations in the types of fuels and propulsion systems that can be used. In all cases travel demand management strategies are critical; deep emission cuts will not likely be possible without slowing growth in travel demand across all modes. Even though these scenarios represent only a small subset of the potential futures in which deep reductions might be achieved, they provide a sense of the magnitude of changes required in our transportation system and the need for early and aggressive action if long-term targets are to be met.

This study seeks to identify potential capacity constraints within the US rail network that could limit expanded use of coal for electricity generation and hydrogen fuel production. We estimate the costs of alleviating those constraints under various scenarios of future coal demand growth. By 2050, coal transportation is projected to increase 35–90% necessitating rail capital investments of $1.5–11.0 billion. These investments are within the range of historical expenditures in the railroad industry, so it is unlikely that delivered prices of coal will necessarily increase or that rail capacity will be a barrier to a future coal-based “Hydrogen Economy”.

Household air pollution from traditional cook stoves presents a greater health hazard than any other environmental factor. Despite government efforts to support clean-burning cooking fuels, over 700 million people in South Asia could still rely on traditional stoves in 2030. This number could rise if climate change mitigation efforts increase energy costs. Here we quantify the costs of support policies to make clean cooking affordable to all South Asians under four increasingly stringent climate policy scenarios. Our most sringent mitigation scenario increases clean fuel costs 38% in 2030 relative to the baseline, keeping 21% more South Asians on traditional stoves or increasing the minimum support policy cost to achieve universal clean cooking by up to 44%. The extent of this increase depends on how poliymakers allocate subsidies between clean fuels and stoves. These additional costs are within the range of financial transfers to South Asia estimated in efforts-sharing scenarios of international climate agreements. Three billion people globally burn solid fuels such as firewood, charcoal, coal, dung, and crop resides in open fires and traditional stoves for cooking and heating. Household air pollution from the incomplete combustion of these fuels globally leads to 4.3 million premature deaths each year, with 1.7 million of those in South Asia. This exceeds the burden of disease from any other energy-related or environmental risk factor. Solid-fuel use also perpetuates income and gender inequality by forcing users, mostly poor women and children, to spend long hours collecting fuels and to suffer from its adverse health effects. To address this problem, the United Nations Secretary-General's Sustainable Energy for All (SE4All) initiative and the new Sustainable Development Goals aim to achieve universal access to modern energy services by 2030. Numerous intervention efforts have focused on distributing more efficient and cleaner burning biomass stoves, but several of these programmes have had little or no demonstrable impact on health outcomes. In India, the nation with the largest population of solid-fuel users globally, government interventions have sought to make petroleum-based fuels, such as kerosene and liquefied petroleum gas (LPG), more affordable through subsidy at an estimated cost of over US$6 billion per year. Although LPG use has grown rapidly, particularly in rural areas, over 72% of Indians continued to rely primarily on solid fuels in 2012. In the future, expanding clean cooking may become more challenging if climate policies increase the cost of fuels. Previous research has found that greenhouse gas (GHG) emissions reductions in Asia and Africa would increase the cost of kerosene and LPG. However, these studies do not explore compensatory policies that could counteract these effects, and assess only a limited set of climate mitigation scenarios. Only two studies explore normative scenarios that achieve access and climate goals simultanously, both of which do not explore the cost-effectiveness or distributional impacts on population subgroups of these policies. Meanwhile, studies that have evaluated the cost-effectiveness of energy access policies have not considered the impact of climate policy. Te latest assessment of the Intergovernmental Panel on Climate Change (IPCC) concludes that we have only low confidence in our understanding of the possible impacts of climate policy on access to modern energy services, and medium confidence in the policies needed to counteract them. In this study, we contribute new insights to the interaction of climate policy and clean cooking acces policies by quantifying the feasibility and costs of achieving universal access by 2030 for a range of climate policy stringencies, and under a wide range of fuel and stove price support policies. Our analysis suggests that the potential trade-offs between the two goals might be arger than suggested by previous studies. However, we find that efficient policy design could partially compensate for the additional access policy costs associated with climate mitigation. Furthermore, these costs fall below the level of potential financial transfers to South Asia that may result from international climate agreements.