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Future energy demand is likely to increase due to climate change, but the magnitude depends on many interacting sources of uncertainty. We combine econometrically estimated responses of energy use to income, hot and cold days with future projections of spatial population and national income under five socioeconomic scenarios and temperature increases around 2050 for two emission scenarios simulated by 21 Earth System Models (ESMs). Here we show that, across 210 realizations of socioeconomic and climate scenarios, vigorous (moderate) warming increases global climate-exposed energy demand before adaptation around 2050 by 25–58% (11–27%), on top of a factor 1.7–2.8 increase above present-day due to socioeconomic developments. We find broad agreement among ESMs that energy demand rises by more than 25% in the tropics and southern regions of the USA, Europe and China. Socioeconomic scenarios vary widely in the number of people in low-income countries exposed to increases in energy demand. Future energy demand maybe induced by climate change and subject to uncertainties arising from different extent of climate change and socioeconomic development. Here the authors follow a top-down approach and combined the recently developed socio-economic and climate scenarios and found that across 210 scenarios, moderate warming increases global climate-exposed energy demand before adaptation by 25–58% between 2010 and 2050.

Long-term global scenarios have underpinned research and assessment of global environmental change for four decades. Over the past ten years, the climate change research community has developed a scenario framework combining alternative futures of climate and society to facilitate integrated research and consistent assessment to inform policy. Here we assess how well this framework is working and what challenges it faces. We synthesize insights from scenario-based literature, community discussions and recent experience in assessments, concluding that the framework has been widely adopted across research communities and is largely meeting immediate needs. However, some mixed successes and a changing policy and research landscape present key challenges, and we recommend several new directions for the development and use of this framework.The SSP–RCP scenario framework has been an important component of physical, social and integrated climate change research for the past decade. This Perspective reviews the successes of the framework and the challenges it faces, and provides suggestions for improvement moving forward.

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

Long-term mitigation scenarios developed by integrated assessment models underpin major aspects of recent IPCC reports and have been critical to identify the system transformations that are required to meet stringent climate goals. However, they have been criticized for proposing pathways that may prove challenging to implement in the real world and for failing to capture the social and institutional challenges of the transition. There is a growing interest to assess the feasibility of these scenarios, but past research has mostly focused on theoretical considerations. This paper proposes a novel and versatile multidimensional framework that allows evaluating and comparing decarbonization pathways by systematically quantifying feasibility concerns across geophysical, technological, economic, socio-cultural and institutional dimensions. This framework enables to assess the timing, disruptiveness and scale of feasibility concerns, and to identify trade-offs across different feasibility dimensions. As a first implementation of the proposed framework, we map the feasibility concerns of the IPCC 1.5 °C Special Report scenarios. We select 24 quantitative indicators and propose feasibility thresholds based on insights from an extensive analysis of the literature and empirical data. Our framework is, however, flexible and allows evaluations based on different thresholds or aggregation rules. Our analyses show that institutional constraints, which are often not accounted for in scenarios, are key drivers of feasibility concerns. Moreover, we identify a clear intertemporal trade-off, with early mitigation being more disruptive but preventing higher and persistent feasibility concerns produced by postponed mitigation action later in the century.

This study considers how large-scale application of solar panels will affect climate. Electricity generation leads to regional cooling but this is countered by the power’s use, affecting global circulation patterns with changes in regional rainfall. Regardless of the harmful effects of burning fossil fuels on global climate 1 , 2 , other energy sources will become more important in the future because fossil fuels could run out by the early twenty-second century 3 given the present rate of consumption 4 . This implies that sooner or later humanity will rely heavily on renewable energy sources. Here we model the effects of an idealized large-scale application of renewable energy on global and regional climate relative to a background climate of the representative concentration pathway 2.6 scenario (RCP2.6; ref.  5 ). We find that solar panels alone induce regional cooling by converting incoming solar energy to electricity in comparison to the climate without solar panels. The conversion of this electricity to heat, primarily in urban areas, increases regional and global temperatures which compensate the cooling effect. However, there are consequences involved with these processes that modulate the global atmospheric circulation, resulting in changes in regional precipitation.

Low-carbon energy transitions taking place worldwide are primarily driven by the integration of renewable energy sources such as wind and solar power. These variable renewable energy (VRE) sources require energy storage options to match energy demand reliably at different time scales. This article suggests using a gravitational-based energy storage method by making use of decommissioned underground mines as storage reservoirs, using a vertical shaft and electric motor/generators for lifting and dumping large volumes of sand. The proposed technology, called Underground Gravity Energy Storage (UGES), can discharge electricity by lowering large volumes of sand into an underground mine through the mine shaft. When there is excess electrical energy in the grid, UGES can store electricity by elevating sand from the mine and depositing it in upper storage sites on top of the mine. Unlike battery energy storage, the energy storage medium of UGES is sand, which means the self-discharge rate of the system is zero, enabling ultra-long energy storage times. Furthermore, the use of sand as storage media alleviates any risk for contaminating underground water resources as opposed to an underground pumped hydro storage alternative. UGES offers weekly to pluriannual energy storage cycles with energy storage investment costs of about 1 to 10 USD/kWh. The technology is estimated to have a global energy storage potential of 7 to 70 TWh and can support sustainable development, mainly by providing seasonal energy storage services.

Emission reduction scenarios to meet climate change mitigation policy goals rarely explore the differential impact of alternative pathways on access to energy for different economic strata of society across countries. Here we show that even under optimistic socioeconomic growth scenarios, inequalities in use of modern energy in homes could persist. We find that, although access improves in high growth scenarios, over 10% of populations in sub-Saharan Africa and South Asia could lack access to energy services for thermal comfort, food preparation and conservation, and cleaning in 2050. Ambitious climate mitigation scenarios do not substantially alter household access to energy services in the Global South, and only affect gas consumption in high-income regions. Our work suggests that efforts to meet climate mitigation policy goals are not at odds with progress towards universal access to modern energy services in the Global South, however, directed policy will be needed to meet access goals. Energy system scenarios to meet climate mitigation goals rarely explore the evolution of energy access and equity. Now, Poblete-Cazenave et al. show that, under many baseline and decarbonization scenarios, energy access for people in Africa and South Asia remains insufficient.

On the basis of the IPCC B2, A1b and B1 baseline scenarios, mitigation scenarios were developed that stabilize greenhouse gas concentrations at 650, 550 and 450 and - subject to specific assumptions - 400 ppm CO₂-eq. The analysis takes into account a large number of reduction options, such as reductions of non-CO₂ gases, carbon plantations and measures in the energy system. The study shows stabilization as low as 450 ppm CO₂-eq. to be technically feasible, even given relatively high baseline scenarios. To achieve these lower concentration levels, global emissions need to peak within the first two decades. The net present value of abatement costs for the B2 baseline scenario (a medium scenario) increases from 0.2% of cumulative GDP to 1.1% as the shift is made from 650 to 450 ppm. On the other hand, the probability of meeting a two-degree target increases from 0%-10% to 20%-70%. The mitigation scenarios lead to lower emissions of regional air pollutants but also to increased land use. The uncertainty in the cost estimates is at least in the order of 50%, with the most important uncertainties including land-use emissions, the potential for bio-energy and the contribution of energy efficiency. Furthermore, creating the right socio-economic and political conditions for mitigation is more important than any of the technical constraints.

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

The trade impacts of the COVID-19 pandemic and the Russian invasion of Ukraine have raised questions about the role of trade and climate policies in energy security and global emissions. This study updates a widely used integrated assessment model (IAM), MESSAGEix-GLOBIOM, to represent complex trade networks to explicitly draw energy flows from their origins to their destination. It then examines the effects of (1) energy trade tariff policies, such as import tariffs, as a proxy to represent an unfriendly trade environment and (2) a global carbon emissions tax on the global energy trade network. Results indicate that trade tariff policies have marginal effects on the trade network, i.e., the size of trade and importing-exporting regions do not change significantly. While high import tariffs significantly reduce emissions due to reduced fossil fuel imports in the importing region, this effect does not translate to significant emission reductions globally, as trade policies only impact downstream of the energy supply chain. However, a carbon emission tax dramatically alters the trade network, by (1) reducing its size by up to 50% and (2) forming trade linkages that allow for a more complex and diverse network of suppliers. This diversity under the emissions tax scenario improves the energy security of major energy-importing regions. Moreover, under an emission tax scenario, a friendly trade environment reduces the energy system costs globally. However, trade friction, such as sanctions or high import tariffs, will increase the energy supply cost significantly, especially for energy-importing regions such as Europe, East and South Asia.