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Closing the emissions gap between Nationally Determined Contributions (NDCs) and the global emissions levels needed to achieve the Paris Agreement’s climate goals will require a comprehensive package of policy measures. National and sectoral policies can help fill the gap, but success stories in one country cannot be automatically replicated in other countries. They need to be adapted to the local context. Here, we develop a new Bridge scenario based on nationally relevant, short-term measures informed by interactions with country experts. These good practice policies are rolled out globally between now and 2030 and combined with carbon pricing thereafter. We implement this scenario with an ensemble of global integrated assessment models. We show that the Bridge scenario closes two-thirds of the emissions gap between NDC and 2 °C scenarios by 2030 and enables a pathway in line with the 2 °C goal when combined with the necessary long-term changes, i.e. more comprehensive pricing measures after 2030. The Bridge scenario leads to a scale-up of renewable energy (reaching 52%–88% of global electricity supply by 2050), electrification of end-uses, efficiency improvements in energy demand sectors, and enhanced afforestation and reforestation. Our analysis suggests that early action via good-practice policies is less costly than a delay in global climate cooperation., Comprehensive policy measures are needed to close the emissions gap between Nationally Determined Contributions and emissions goals of the Paris Agreement. Here the authors present a Bridge scenario that may aid in closing the emissions gap by 2030.

Given concerns about the ambition and effectiveness of current climate pledges, a case has been made for the integration of demand-side policies such as carbon pricing with supply-side bans on fossil fuel extraction. However, little is known about their interplay in the context of climate stabilization strategies. Here, we present the first multi-model assessment quantifying the effectiveness of supply-side policies and their interactions with demand-side ones. We design narratives of fossil fuel bans and explore a variety of scenarios with four integrated assessment models, to find that widespread international supply side policies significantly reduce emissions but not at sufficient levels to stabilize temperature increase to well below 2°C. When combined with demand-side policies, supply side policies reduce the required carbon price to meet the Paris goals, dampen reliance on CO2 removal and increase investment in renewable energy. The results indicate the opportunity to introduce fossil fuel bans alongside price-based, demand-focused policies when exploring climate neutrality pathways.

Research and development (R&D) investments foster green innovation, which is key to decarbonize the energy system and attain long-term climate goals. In this paper, we link three integrated assessment models that possess a macroeconomic framework – WITCH, MERGE-ETL and GEM-E3 – with the bottom-up technology-rich energy system model TIAM-ECN, in order to quantitatively explore how investments in R&D can support deep decarbonization pathways. We take advantage of the endogenous technological learning feature of the first three models to derive R&D-induced capital cost reductions for strategic clusters of low-carbon technologies: solar energy, on- and offshore wind energy, carbon capture and storage, advanced fuels, and batteries for electric vehicles. We examine scenarios with different assumptions on CO2 mitigation and R&D policy. These assumptions are harmonized among our four models, and capital cost reductions driven by R&D are exogenously incorporated in TIAM-ECN, which enables a detailed assessment of the required energy transition. Our results show that the stringency of climate change mitigation policy remains the key factor influencing the diffusion of low-carbon technologies, while R&D can support mitigation goals and influence the contribution of different types of technologies. If implemented effectively and without worldwide barriers to knowledge spill-overs, R&D facilitates the deployment of mature technologies such as solar, wind, and electric vehicles, and enables lower overall energy system costs.

Given concerns about the ambition and effectiveness of current climate pledges, a case has been made for the integration of demand-side policies such as carbon pricing with supply-side bans on fossil fuel extraction. However, little is known about their interplay in the context of climate stabilization. Here, we present the first multi-model assessment quantifying the effectiveness of supply-side policies and their interactions with demand-side ones. We design narratives of fossil fuel bans and explore a variety of scenarios with four process-based integrated assessment models. We find that supply side treaties reduce emissions but not enough to stabilize temperature increase to well below 2°C. When combined with demand-side policies, supply side policies reduce the required carbon price to meet the Paris goals, dampen reliance on CO2 removal and increase investment in renewable energy while increasing fossil producer revenues. The results indicate the opportunity to integrate price-based policies with fossil bans when exploring climate neutrality pathways.

Closing the remaining emissions gap between Nationally Determined Contributions (NDCs) and the global emissions levels needed to achieve the Paris Agreement’s climate goals will likely require a comprehensive package of policy measures. National and sectoral policies can help fill the gap, but success stories in one country cannot be automatically replicated in other countries, but need to be adapted to the local context. Here, we develop a new Bridge scenario based on nationally relevant measures informed by interactions with country experts. We implement this scenario with an ensemble of global integrated assessment models (IAMs). We show that a global roll-out of these good practice policies closes the emissions gap between current NDCs and a cost-optimal well below 2 °C scenario by two thirds by 2030 and more than fully by 2050, while being less disruptive than a scenario that delays cost-optimal mitigation to 2030. The Bridge scenario leads to a scale-up of renewable energy (reaching 50%-85% of global electricity supply by 2050), electrification of end-uses, efficiency improvements in energy demand sectors, and enhanced afforestation and reforestation. Our analysis suggests that early action via good-practice policies is less costly than a delay in global climate cooperation.

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.

Several studies have shown that the greenhouse gas reduction resulting from the current nationally determined contributions (NDCs) will not be enough to meet the overall targets of the Paris Climate Agreement. It has been suggested that more ambition mitigations of short-lived climate forcer (SLCF) emissions could potentially be a way to reduce the risk of overshooting the 1.5 or 2 °C target in a cost-effective way. In this study, we employ eight state-of-the-art integrated assessment models (IAMs) to examine the global temperature effects of ambitious reductions of methane, black and organic carbon, and hydrofluorocarbon emissions. The SLCFs measures considered are found to add significantly to the effect of the NDCs on short-term global mean temperature (GMT) (in the year 2040: − 0.03 to − 0.15 °C) and on reducing the short-term rate-of-change (by − 2 to 15%), but only a small effect on reducing the maximum temperature change before 2100. This, because later in the century under assumed ambitious climate policy, SLCF mitigation is maximized, either directly or indirectly due to changes in the energy system. All three SLCF groups can contribute to achieving GMT changes.

The COVID-19 pandemic reveals that societies place a high value on healthy lives. Leveraging this momentum to establish a more central role for human health in the policy process will provide further impetus to a sustainable transformation of energy and food systems.

Future socioeconomic developments and climate policies will play a role in air quality improvement since greenhouse gases and air pollutant emissions are highly connected. As these interactions are complex, air quality indices are useful tools to assess the sustainability of future policies. Here, we compute new global annual air quality indices to provide insights into future global and regional air quality, allowing for the evaluation of the sustainability of climate policies. We project the future concentrations of major the air pollutants for five socioeconomic pathways covering a broad range of climate radiative forcing targets in 2100, using a fast transport chemistry emulator and the emission database produced for the sixth assessment report of the Intergovernmental Panel on Climate Change. Our findings show that climate policies are very relevant in reducing air pollution exposure by mid-century. Climate policies will have a stronger effect on the pollution reduction timing, while socioeconomic developments will have a greater impact on the absolute pollution level. A 1.5 ∘ C policy target may prevent all regions from exceeding the annual average limit for all pollutants considered, except PM 2 . 5 . We emphasize the importance of considering exposure air quality indices, when assessing sustainable policies, as being more informative rather than a population-weighted average index.

The Paris Agreement is a milestone in international climate policy as it establishes a global mitigation framework towards 2030 and sets the ground for a potential 1.5 °C climate stabilization. To provide useful insights for the 2018 UNFCCC Talanoa facilitative dialogue, we use eight state-of-the-art climate-energy-economy models to assess the effectiveness of the Intended Nationally Determined Contributions (INDCs) in meeting high probability 1.5 and 2 °C stabilization goals. We estimate that the implementation of conditional INDCs in 2030 leaves an emissions gap from least cost 2 °C and 1.5 °C pathways for year 2030 equal to 15.6 (9.0–20.3) and 24.6 (18.5–29.0) GtCO2eq respectively. The immediate transition to a more efficient and low-carbon energy system is key to achieving the Paris goals. The decarbonization of the power supply sector delivers half of total CO2 emission reductions in all scenarios, primarily through high penetration of renewables and energy efficiency improvements. In combination with an increased electrification of final energy demand, low-carbon power supply is the main short-term abatement option. We find that the global macroeconomic cost of mitigation efforts does not reduce the 2020–2030 annual GDP growth rates in any model more than 0.1 percentage points in the INDC or 0.3 and 0.5 in the 2 °C and 1.5 °C scenarios respectively even without accounting for potential co-benefits and avoided climate damages. Accordingly, the median GDP reductions across all models in 2030 are 0.4%, 1.2% and 3.3% of reference GDP for each respective scenario. Costs go up with increasing mitigation efforts but a fragmented action, as implied by the INDCs, results in higher costs per unit of abated emissions. On a regional level, the cost distribution is different across scenarios while fossil fuel exporters see the highest GDP reductions in all INDC, 2 °C and 1.5 °C scenarios.

In this paper we standardize, compare, and aggregate results from thirteen surveys of technology experts, performed over a period of five years using a range of different methodologies, but all aiming at eliciting expert judgment on the future cost of five key energy technologies and how future costs might be influenced by public R&D investments. To enable researchers and policy makers to use the wealth of collective knowledge obtained through these expert elicitations we develop and present a set of assumptions to harmonize them. We also aggregate expert estimates within each study and across studies to facilitate the comparison. The analysis showed that, as expected, technology costs are expected to go down by 2030 with increasing levels of R&D investments, but that there is not a high level of agreement between individual experts or between studies regarding the technology areas that would benefit the most from R&D investments. This indicates that further study of prospective cost data may be useful to further inform R&D investments. We also found that the contributions of additional studies to the variance of costs in one technology area differed by technology area, suggesting that (barring new information about the downsides of particular forms of elicitations) there may be value in not only including a diverse and relatively large group of experts, but also in using different methods to collect estimates.

We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We include in our assessment, a range of alternative assumptions on the implementation of current and planned pollution control policies. The resulting air pollution emission ranges significantly extend those in the Representative Concentration Pathways. Climate mitigation policies complement current efforts on air pollution control through technology and fuel transformations in the energy system. A combination of stringent policies on air pollution control and climate change mitigation results in 40% of the global population exposed to PM levels below the WHO air quality guideline; with the largest improvements estimated for India, China, and Middle East. Our results stress the importance of integrated multisector policy approaches to achieve the Sustainable Development Goals.

Governments worldwide have agreed that international climate policy should aim to limit the increase of global mean temperature to less than 2°C with respect to pre-industrial levels. The purpose of this paper is to analyse the emission reductions and related energy system changes in various countries in pathways consistent with the 2°C target. We synthesize and provide an overview of the national and regional information contained in different scenarios from various global models published over the last few years, as well as yet unpublished scenarios submitted by modelling teams participating in the MILES project (Modelling and Informing Low-Emission Strategies). We find that emissions in the mitigation scenarios are significantly reduced in all regions compared to the baseline without climate policies. The regional cumulative CO2 emissions show on average a 76% reduction between the baseline and 450 scenario. The 450 scenarios show a reduction of primary energy demand in all countries of roughly 30-40% compared to the baseline. In the baseline scenario, the contribution of low-carbon energy technology remains around 15%, i.e. similar as today. In the mitigation scenario, these numbers are scaled up rapidly towards 2050. Looking at air quality, sulphur dioxide and black carbon emissions are strongly reduced as a co-benefit of greenhouse gas emission reductions, in both developing and developed countries. However, black carbon emissions increase in countries that strongly rely on bioenergy to reach mitigation targets. Concerning energy security, energy importing countries generally experience a decrease in net-energy imports in mitigation scenarios compared to the baseline development, while energy exporters experience a loss of energy export revenues.

Developing Asia has the world’s fastest greenhouse gas emissions growth. This study uses an economy–energy–climate model to assess the effects of Paris Agreement pledges on Asia, in comparison with business as usual (BAU) and more ambitious scenarios. Results confirm that pledges must be strongly increased in ambition to achieve the Paris Agreement’s goal of less than 2 degrees Celsius (2°C) warming. The policy costs of Asia’s pledges are found to be less than 1% of gross domestic product (GDP) through 2050, while 2°C scenarios may cost less than 2% of GDP. However, costs are sensitive to assumptions about international carbon markets and mitigation timing, with costs for 2°C scenarios doubling in the absence of carbon trade, and increasing the later that mitigation is initiated. Under the 2°C scenarios, annual average energy supply investments are about $300 billion above the BAU levels through 2050. Mitigation policy may substantially reduce air pollution mortality, with up to 600,000 fewer deaths in Asia annually by 2050. When costs, benefits of avoided climate change, and cobenefits are considered together, investment in mitigation policy is found to have substantial economic returns for the region — if action is taken rapidly and international carbon market mechanisms are implemented.

Mitigating climate change will require innovation in energy technologies. Policy makers are faced with the question of how to promote this innovation, and whether to focus on a few technologies or to spread their bets. We present results on the extent to which public R&D might shape the future cost of energy technologies by 2030. We bring together three major expert elicitation efforts carried out by researchers at UMass Amherst, Harvard, and FEEM, covering nuclear, solar, Carbon Capture and Storage (CCS), bioelectricity, and biofuels. The results show experts believe that there will be cost reductions resulting from R&D and report median cost reductions around 20 % for most of the technologies at the R&D budgets considered. Although the improvements associated to solar and CCS R&D show some promise, the lack of consensus across studies, and the larger magnitude of the R&D investment involved in these technologies, calls for caution when defining what technologies would benefit the most from additional public R&D. In order to make R&D funding decisions to meet particular goals, such as mitigating climate change or improving energy security, or to estimate the social returns to R&D, policy makers need to combine the information provided in this study on cost reduction potentials with an analysis of the macroeconomic implications of these technological changes. We conclude with recommendations for future directions on energy expert elicitations.

Results from four integrated assessment models show countries’ efforts to cut emissions fall towards the lower end of the social cost of carbon distribution, suggesting insufficient levels of ambition to meet the Paris Agreement goals. The Paris Agreement culminates a six-year transition towards an international climate policy architecture based on parties submitting national pledges every five years1. An important policy task will be to assess and compare these contributions2,3. We use four integrated assessment models to produce metrics of Paris Agreement pledges, and show differentiated effort across countries: wealthier countries pledge to undertake greater emission reductions with higher costs. The pledges fall in the lower end of the distributions of the social cost of carbon and the cost-minimizing path to limiting warming to 2 °C, suggesting insufficient global ambition in light of leaders’ climate goals. Countries’ marginal abatement costs vary by two orders of magnitude, illustrating that large efficiency gains are available through joint mitigation efforts and/or carbon price coordination. Marginal costs rise almost proportionally with income, but full policy costs reveal more complex regional patterns due to terms of trade effects.

Emissions of air pollutants such as sulfur and nitrogen oxides and particulates have significant health impacts as well as effects on natural and anthropogenic ecosystems. These same emissions also can change atmospheric chemistry and the planetary energy balance, thereby impacting global and regional climate. Long-term scenarios for air pollutant emissions are needed as inputs to global climate and chemistry models, and for analysis linking air pollutant impacts across sectors. In this paper we present methodology and results for air pollutant emissions in Shared Socioeconomic Pathways (SSP) scenarios. We first present a set of three air pollution narratives that describe high, central, and low pollution control ambitions over the 21st century. These narratives are then translated into quantitative guidance for use in integrated assessment models. The resulting pollutant emission trajectories under the SSP scenarios cover a wider range than the scenarios used in previous international climate model comparisons. In the SSP3 and SSP4 scenarios, where economic, institutional and technological limitations slow air quality improvements, global pollutant emissions over the 21st century can be comparable to current levels. Pollutant emissions in the SSP1 scenarios fall to low levels due to the assumption of technological advances and successful global action to control emissions.

The use of integrated assessment models, in air quality policy, which combines atmospheric models with others from different fields, raises the need of developing specific air quality modelling concepts. The air quality model, AUSTAL2000-AYLTP uses an adapted version of AUSTAL2000 model to calculate transport coupled with a fast photochemical module. Two approaches are compared: one using a look-up table and the other using a coupled box model. The lookup table has been built using the OZIPR model by simulating a large set of possible combinations of meteorological variables and precursor concentrations. The second approach consists of coupling the Lagrangian model AUSTAL2000 with the OZIPR box model. In both approaches the photochemistry is included in the mode by using a quasi-linear reaction rates coefficient which is used to affect the mass of the Lagrangian particles. We discuss the differences and the suitability of the two model versions, through exploring CPU time flexibility, applicability and accuracy.

Expert elicitation is a process for eliciting subjective probability distributions from experts about items of interest to decision makers. These methods have been increasingly applied in the energy domain to collect information on the future cost and performance of specific energy technologies and the associated uncertainty. This article reviews the existing expert elicitations on energy technologies with three main objectives: (1) to provide insights on expert elicitation methods and how they compare/complement other approaches to inform public energy decision making; (2) to review all recent elicitation exercises about future technology costs; and (3) to discuss the main results from these expert elicitations, in terms of implied rates of cost reduction and the role of R&D investments in shaping these reductions, and compare it with insights from backward looking approaches. We argue that the emergence of data on future energy costs through expert elicitations provides the opportunity for more transparent and robust analyses incorporating technical uncertainty to assess energy and climate change mitigation policies.

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

In order to evaluate the effectiveness of climate policy, it is important to understand emission trends and policies at the national level. The 2015 Paris Agreement includes (Intended) Nationally Determined Contributions, so-called (I)NDCs, outlining the contribution of different Parties to the overall target of the agreement to limit global mean temperature increase to well below 2 °C. Here, we assess emission trajectories and the energy system transition of 11 major economies (in the remainder: countries) projected by integrated assessment models (IAMs) for baseline and cost-optimal 450 ppm CO2 eq mitigation scenarios and compare the results with the (I)NDCs. Limiting global temperature increase to below 2 °C implies a substantial reduction of the estimated available carbon budget for each country. The national carbon budgets between 2010 and 2100 showed reductions between the baseline and the 2 °C consistent mitigation scenario ranging from 52% in South Korea to 95% in Brazil. While in the baseline scenario, the share of low-carbon primary energy sources is projected to remain around 15% (with Brazil being a notable exception, reaching 30%); in the mitigation scenarios, the share of low-carbon energy is projected to increase to over 50% in 2050 in nearly all countries, with the EU, Japan and Canada reaching the largest shares. Comparison with the (I)NDCs shows that in Brazil, Canada, the EU, Mexico (conditional target), South Korea and the USA, the emission reduction targets of the NDCs are closer to the mitigation requirement of the 2 °C scenario; in other countries, however, there is still a large gap. The national detail of the indicators adds to the literature on low-carbon emission pathways, assists the assessment of the Paris Agreement and provides support to national policymakers to identify focus areas for climate policy in the coming years.

The harsh lockdown measures that marked the response to the COVID-19 outbreak in the Italian region of Lombardy provides a unique natural experiment for assessing the sensitivity of local air pollution to emissions. However, evaluating the pollution benefits of the lockdown is complicated by confounding factors such as variations in weather. We use a machine learning algorithm that does not require identifying comparable but unaffected regions while addressing the effect of weather. We show that the lockdown, albeit virtually halting most human activities, reduced background concentrations of PM2.5 by 3.84 µg/m3 (16%) and NO2 by 10.85 µg/m3 (33%). Improved air quality has saved at least 11% of the years of life lost and 19% of the premature deaths attributable to COVID-19 in the region. Although air pollution has significantly decreased, it has often remained above safety thresholds. The analysis highlights the diversity of air pollution sources and the need for an expansive policy response.