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Urban mobility solutions foster climate mitigation Global emissions scenarios studies, such as those informing the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5), highlight the importance of the transport sector for climate change mitigation—along with the difficulties of achieving deep reductions therein ( 1 ) [supplementary materials (SM)]. Transport is responsible for about 23% of total energy-related CO 2 emissions worldwide ( 2 ). The sector is growing more rapidly than most others, with emissions projected to double by 2050. Global scenario studies, specifically those produced by integrated assessment models (IAMs), communicate aggregate mitigation potentials by sectors in IPCC reports. Yet recent evidence indicates that emissions may be reduced further than these global scenario studies suggest—if policy-makers use the full suite of policies at their disposal.

The Paris Agreement—which is aimed at holding global warming well below 2 °C while pursuing efforts to limit it below 1.5 °C—has initiated a bottom-up process of iteratively updating nationally determined contributions to reach these long-term goals. Achieving these goals implies a tight limit on cumulative net CO2 emissions, of which residual CO2 emissions from fossil fuels are the greatest impediment. Here, using an ensemble of seven integrated assessment models (IAMs), we explore the determinants of these residual emissions, focusing on sector-level contributions. Even when strengthened pre-2030 mitigation action is combined with very stringent long-term policies, cumulative residual CO2 emissions from fossil fuels remain at 850–1,150 GtCO2 during 2016–2100, despite carbon prices of US$130–420 per tCO2 by 2030. Thus, 640–950 GtCO2 removal is required for a likely chance of limiting end-of-century warming to 1.5 °C. In the absence of strengthened pre-2030 pledges, long-term CO2 commitments are increased by 160–330 GtCO2, further jeopardizing achievement of the 1.5 °C goal and increasing dependence on CO2 removal.

Mitigation scenarios that achieve the ambitious targets included in the Paris Agreement typically rely on greenhouse gas emission reductions combined with net carbon dioxide removal (CDR) from the atmosphere, mostly accomplished through large-scale application of bioenergy with carbon capture and storage, and afforestation. However, CDR strategies face several difficulties such as reliance on underground CO2 storage and competition for land with food production and biodiversity protection. The question arises whether alternative deep mitigation pathways exist. Here, using an integrated assessment model, we explore the impact of alternative pathways that include lifestyle change, additional reduction of non-CO2 greenhouse gases and more rapid electrification of energy demand based on renewable energy. Although these alternatives also face specific difficulties, they are found to significantly reduce the need for CDR, but not fully eliminate it. The alternatives offer a means to diversify transition pathways to meet the Paris Agreement targets, while simultaneously benefiting other sustainability goals.

Achieving universal access to a sufficient electricity supply is a crucial component of the Sustainable Development Goals. However, model projections suggest that under current policies, this goal will not be reached by 2030. There is still little understanding of the possible electrification strategies and associated costs across global regions. To address this gap, we explore scenarios for achieving universal electricity access globally in 2030 based on high-resolution data and energy projections from the integrated assessment model IMAGE. The scenarios consider baseline development, implementation of electricity supply per household consistent with decent living standards and synergies with climate change mitigation. The results indicate that off-grid systems, i.e. mini-grids and solar home systems, are the least-cost solution for most people gaining access after 2023 (base year). Furthermore, targeting universal access leads to at least 70GW of off-grid additional capacity needed, most of which is required for Sub-Saharan Africa. If combined with climate goals, the optimal strategy increases renewables, reducing CO 2 emissions by around 30%, while system cost remains similar to the scenarios without climate policies.

Hydropower, despite its operational flexibility, is increasingly challenged by droughts which can constrain electricity generation. In this study, we present a hybrid modelling framework that bridges physically-based hydropower potential simulations and observed generation with machine learning to estimate monthly, plant-level hydropower generation at the global scale. The hybrid model improves the representation of hydropower generation for both run-of-river and storage (STO) plants, effectively capturing systems where STO dynamics plays a major role. Using this framework, we quantify the impacts of historical droughts on hydropower generation over the period 1982–2022. On average, drought conditions led to approximately 11% reduction in global hydropower generation relative to the long-term average with, larger declines in regions such as Western and Eastern North America, Southeastern South America, the Mediterranean, East Asia, and comparatively smaller impacts in Northern Europe and South Asia. Overall, the proposed hybrid modelling framework represents an important initial step towards developing tools for monitoring the impacts of climate extremes on hydropower. This work can support future research on the water-energy nexus and eventually contributes to the development of policies aimed at ensuring a reliable and resilient energy supply.

Hydropower is a crucial renewable source that depends heavily on water availability. Analyzing drought and climate change impacts on hydropower potential requires detailed data on both hydropower plant attributes (e.g. plant type and head) and reservoir characteristics (e.g. area, depth and volume). However, existing open-source datasets are poorly integrated: hydropower plant datasets often lack reservoir information, while reservoir datasets commonly miss hydropower plant information. This paper addresses this gap by introducing GloHydroRes, a global dataset that combines existing open-source hydropower plant and reservoir datasets. GloHydroRes includes attributes like plant location, head, plant type as well as reservoir details such as dam and reservoir location, dam height, reservoir depth, area, and volume for 7,775 plants in 128 countries. GloHydroRes covers nearly 79% and 81% of the global installed capacity when compared with installed hydropower data as reported by the EIA(2022) and IRENA (2023), respectively. The open-source GloHydroRes dataset provides crucial data to improve hydropower generation modelling at plant level and can support energy security and planning at continent to global scale.

Decarbonization of energy-using sectors is essential for tackling climate change. We use an ensemble of global integrated assessment models to assess CO2 emissions reduction potentials in buildings and transport, accounting for system interactions. We focus on three intervention strategies with distinct emphases: reducing or changing activity, improving technological efficiency and electrifying energy end use. We find that these strategies can reduce emissions by 51–85% in buildings and 37–91% in transport by 2050 relative to a current policies scenario (ranges indicate model variability). Electrification has the largest potential for direct emissions reductions in both sectors. Interactions between the policies and measures that comprise the three strategies have a modest overall effect on mitigation potentials. However, combining different strategies is strongly beneficial from an energy system perspective as lower electricity demand reduces the need for costly supply-side investments and infrastructure.

Burgeoning demands for mobility and private vehicle ownership undermine global efforts to reduce energy-related greenhouse gas emissions. Advanced vehicles powered by low-carbon sources of electricity or hydrogen offer an alternative to conventional fossil-fuelled technologies. Yet, despite ambitious pledges and investments by governments and automakers, it is by no means clear that these vehicles will ultimately reach mass-market consumers. Here, we develop state-of-the-art representations of consumer preferences in multiple global energy-economy models, specifically focusing on the non-financial preferences of individuals. We employ these enhanced model formulations to analyse the potential for a low-carbon vehicle revolution up to 2050. Our analysis shows that a diverse set of measures targeting vehicle buyers is necessary to drive widespread adoption of clean technologies. Carbon pricing alone is insufficient to bring low-carbon vehicles to the mass market, though it may have a supporting role in ensuring a decarbonized energy supply. Achieving transport decarbonization targets depends on vehicle-purchasing decisions. Non-financial consumer preferences presented in six global energy-economy models reveal that diverse policies targeting vehicle buyers are necessary for the widespread adoption of clean technologies.

While material resources form a critical foundation for human society, their extraction, processing, and use are also a major driver of environmental pressures. Understanding future material consumption is therefore vital. This study presents a comprehensive assessment of future global bulk material consumption, covering metals (steel, aluminium, copper) and non-metallic minerals (cement, sand, limestone, clay). We use the Integrated Assessment Model IMAGE, combined with a stock-driven dynamic material flow analysis model, to provide full coverage of global and regional material flows. We project material consumption for a current-policy baseline, a climate policy scenario (1.5 °C) and two scenarios that add resource efficiency measures on top of the climate policies. Following current policies, by 2050 consumption of steel, aluminium, copper are expected to increase by 25%, 97%, and 84% respectively. Cement, sand, limestone and clay increase by 5%–23%. The climate policy scenario shows increases compared to baseline across all metals and cement, especially in the 2030/2040 period driven by required electricity and vehicle system transformations. The largest relative increase is projected for copper and aluminium, i.e. 22% and 9%, compared to current policies in 2050. Combining climate policies and resource efficiency, however, can reduce the use of non-metallic minerals below current levels and stabilize steel consumption, thus enabling growth in housing, transport, and decarbonized electricity systems. The most effective measures are related to efficiency and sufficiency measures (such as building with less material and reducing floor space). Although copper and aluminium consumption continue to rise across all scenarios, this can be significantly limited by resource efficiency measures. Overall, our findings highlight that resource efficiency policies are critical to managing the additional material consumption induced by climate policy.

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