The decarbonization of shipping has become an important policy goal. While integrated assessment models (IAMs) are often used to explore climate mitigation strategies, they typically provide little information on international shipping, which accounts for emissions of around 0.7 GtCO₂ yr⁻¹. Here we perform a multi-IAM analysis of international shipping and show the potential for decreasing annual emissions in the next decades, with reductions of up to 86% by 2050. This is primarily achieved through the deployment of low-carbon fuels. Models that represent several potential low-carbon alternatives tend to show a deeper decarbonization of international shipping, with drop-in biofuels, renewable alcohols and green ammonia standing out as the main substitutes for conventional maritime fuels. While our results align with the 2018 emission reduction goal of the International Maritime Organization, their compatibility with the agency’s revised target is still subject to a more definitive interpretation.

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The need for engaging citizens in climate policymaking is increasingly recognised. Despite indications that the form of expert involvement can strongly influence participatory processes, this remains scarcely researched. We analysed two unique and contrasting cases of citizen engagement in national climate mitigation policy: (1) the Irish Citizens’ Assembly (ICA), the first national climate assembly involving live expert presentations and face-to-face deliberations; and (2) the Participatory Value Evaluation (PVE) on Dutch climate policymaking, where more than 10,000 citizens compared policy options in an online environment based on expert-based information on policy effects. Taking a dramaturgical approach, we found that the opening up and closing down of policy options and perspectives was influenced by the setting, staging and scripting of expertise. Apart from providing information on policy options, experts had significant roles in design choices and formulating recommendations, which shaped citizens’ deliberations and policy advice. In deliberative processes, citizens’ deliberations can be further influenced by putting experts in a privileged spot and emphasising their authority, whereas in the setting of an online tool, experts’ design choices may be masked by the fact-like presentation of expertise. Future research should further investigate the role of experts and expertise across a wider range of practices. Nevertheless, we conclude that the high degree of required technical knowledge in climate mitigation policy naturally implies strong expert involvement, which concomitantly steers the results. Alternatively, we may search to enhance citizens’ engagement in guiding climate policymakers by focusing on citizens’ normative perspectives.

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Energy models are used to study emissions mitigation pathways, such as those compatible with the Paris Agreement goals. These models vary in structure, objectives, parameterization and level of detail, yielding differences in the computed energy and climate policy scenarios. To study model differences, diagnostic indicators are common practice in many academic fields, for example, in the physical climate sciences. However, they have not yet been applied systematically in mitigation literature, beyond addressing individual model dimensions. Here we address this gap by quantifying energy model typology along five dimensions: responsiveness, mitigation strategies, energy supply, energy demand and mitigation costs and effort, each expressed through several diagnostic indicators. The framework is applied to a diagnostic experiment with eight energy models in which we explore ten scenarios focusing on Europe. Comparing indicators to the ensemble yields comprehensive ‘energy model fingerprints’, which describe systematic model behaviour and contextualize model differences for future multi-model comparison studies.@en

Correction to: Nature Climate Change https://doi-org.tudelft.idm.oclc.org/10.1038/s41558-020-00949-9, published online 11 January 2021. In the version of this Article originally published, the colours in the scale bars in Figs. 1c and 2, Extended Data Figs. 2c and 4, and Supplementary Figs. 2c and 4 were inadvertently flipped such that they were shown as being blue to red, from left to right, but should have been red to blue. The online versions of the Article have been corrected and the Supplementary Information file has been replaced. The tick marks and values have not changed.@en

Renewable energy resources, which depend on climate, may be susceptible to future climate change. Here we use climate and integrated assessment models to estimate this effect on key renewables. Future potential and costs are quantified across two warming scenarios for eight technologies: utility-scale and rooftop photovoltaic, concentrated solar power, onshore and offshore wind energy, first-generation and lignocellulosic bioenergy, and hydropower. The generated cost–supply curves are then used to estimate energy system impacts. In a baseline warming scenario, the largest impact is increased availability of bioenergy, though this depends on the strength of CO₂ fertilization. Impacts on hydropower and wind energy are uncertain, with declines in some regions and increases in others, and impacts on solar power are minor. In a future mitigation scenario, these impacts are smaller, but the energy system response is similar to that in the baseline scenario given a larger reliance of the mitigation scenario on renewables.

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Although our knowledge of climate change impacts on energy systems has increased substantially over the past few decades, there remains a lack of comprehensive overview of impacts across spatial scales. Here, we analyse results of 220 studies projecting climate impacts on energy systems globally and at the regional scale. Globally, a potential increase in cooling demand and decrease in heating demand can be anticipated, in contrast to slight decreases in hydropower and thermal energy capacity. Impacts at the regional scale are more mixed and relatively uncertain across regions, but strongest impacts are reported for South Asia and Latin America. Our assessment shows that climate impacts on energy systems at regional and global scales are uncertain due partly to the wide range of methods and non-harmonized datasets used. For a comprehensive assessment of climate impacts on energy, we propose a consistent multi-model assessment framework to support regional-to-global-scale energy planning.

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Limiting climate change below a given temperature will require fundamental changes in the current energy system, both in the energy supply and the energy demand sectors. Previous global model-based analyses, however, have focused mostly on energy supply transformations. Therefore, in this study we respond to this knowledge gap by analysing the future energy demand projections in both baseline and climate policy scenarios of global models in detail. We examine the projections for the industry, transport and buildings sectors across four models and three different reference scenarios from the Shared-Socioeconomic Pathway framework by applying a decomposition analysis. We compare the projected demand side mitigation efforts to a more detailed, sector-specific, technology-oriented assessment of demand-side abatement potential for the year 2030. Without climate policy, model-based projections show that baseline emissions can grow rapidly in industry and transport sectors, but are also highly uncertain across models. The decomposition analysis shows that the key uncertainty across the global scenarios is the projected final energy per capita. For modellers therefore there lies a challenge to better understand drivers of future energy efficiency and service demand, that contribute to the projected energy demand. This model enhancement would moreover allow to evaluate policy measures that can impact this relation. The technology assessment estimates that in particular in the transport and buildings sector there is a higher potential to reduce demand-side emissions through energy efficiency improvements than implemented in the scenarios. Improved insulation, higher electric vehicle penetration rates and modal shift for example could reduce final energy demand to lower levels in the short term than currently projected, reducing the dependency on fuel switching required in current scenarios to meet the stringent climate targets.@en

The aim of this article is to provide an overview of greenhouse gas emission reduction potentials for 2030 based on the assessment of detailed sectoral studies. The overview updates a previous assessment that dates back more than ten years. We find a total emission reduction potential of 30-36 GtCO2e compared to a current-policies baseline of 61 GtCO2e. The energy production and conversion sector is responsible for about one third of this potential and the agriculture, buildings, forestry, industry, and transport sectors all contribute substantially to the total potential. The potential for 2030 is enough to bridge the gap towards emissions pathways that are compatible with a maximum global temperature rise of 1.5-2 °C compared to preindustrial levels.

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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.

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We present an extension of the dynamic global vegetation model, Lund-Potsdam-Jena Managed Land (LPJmL), to simulate planted forests intended for carbon (C) sequestration. We implemented three functional types to simulate plantation trees in temperate, tropical, and boreal climates. The parameters of these functional types were optimized to fit target growth curves (TGCs). These curves represent the evolution of stemwood C over time in typical productive plantations and were derived by combining field observations and LPJmL estimates for equivalent natural forests. While the calibrated model underestimates stemwood C growth rates compared to the TGCs, it represents substantial improvement over using natural forests to represent afforestation. Based on a simulation experiment in which we compared global natural forest versus global forest plantation, we found that forest plantations allow for much larger C uptake rates on the timescale of 100 years, with a maximum difference of a factor of 1.9, around 54 years. In subsequent simulations for an ambitious but realistic scenario in which 650Mha (14% of global managed land, 4.5% of global land surface) are converted to forest over 85 years, we found that natural forests take up 37PgC versus 48PgC for forest plantations. Comparing these results to estimations of C sequestration required to achieve the 2°C climate target, we conclude that afforestation can offer a substantial contribution to climate mitigation. Full evaluation of afforestation as a climate change mitigation strategy requires an integrated assessment which considers all relevant aspects, including costs, biodiversity, and trade-offs with other land-use types. Our extended version of LPJmL can contribute to such an assessment by providing improved estimates of C uptake rates by forest plantations.

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

The Fourth Assessment Report of IPCC reports that greenhouse gas emissions can be reduced by about 30-50% in 2030 at costs below 100 US$/tCO₂ based on an assessment of both bottom-up and top-down studies. Here, we have looked in more detail into the outcomes of specific models and also analyzed the economic potentials at the sectoral and regional level. At the aggregated level, the findings of the IPCC report are confirmed. However, substantial differences are found at the sectoral level. At the same time, there seems to be no systematic difference in the reduction potential reported by top-down and bottom-up approaches. The largest reduction potential as a response to carbon prices exists in the energy supply sector. Reduction potential in the building sector may carry relatively low costs. Although uncertainties are considerable, the modeling results and the bottom-up analyses all suggest that at the global level around 50% of greenhouse gas emissions may be reduced at carbon price (costs) below 100$/tCO₂-eq-but with a wide range of 30-60%. At a carbon price (costs) less than 20$/tCO₂-eq, still 10-35% of emissions may be abated. The variation of results is higher at low carbon-price levels than at high levels.

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