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Electrification is widely considered an attractive solution for reducing the oil dependency and environmental impact of road transportation. Many countries have been establishing increasingly stringent and ambitious targets in support of transport electrification. We conducted scenario simulations to depict the role of transport electrification in climate change mitigation and how the transport sector would interact with the energy-supply sector. The results showed that transport electrification without the replacement of fossil-fuel power plants leads to the unfortunate result of increasing emissions instead of achieving a low-carbon transition. While transport electrification alone would not contribute to climate change mitigation, it is interesting to note that switching to electrified road transport under the sustainable shared socioeconomic pathways permitted an optimistic outlook for a low-carbon transition, even in the absence of a decarbonized power sector. Another interesting finding was that the stringent penetration of electric vehicles can reduce the mitigation cost generated by the 2 °C climate stabilization target, implying a positive impact for transport policies on the economic system. With technological innovations such as electrified road transport, climate change mitigation does not have to occur at the expense of economic growth. Because a transport electrification policy closely interacts with energy and economic systems, transport planners, economists, and energy policymakers need to work together to propose policy schemes that consider a cross-sectoral balance for a green sustainable future.

Climate change mitigation generally require rapid decarbonization in the power sector, including phase-out of fossil fuel-fired generators. Given recent technological developments, co-firing of hydrogen or ammonia, could help decarbonize fossil-based generators, but little is known about how its effects would play out globally. Here, we explore this topic using an energy system model. The results indicate that hydrogen co-firing occurs solely in stringent mitigation like 1.5 °C scenarios, where around half of existing coal and gas power capacity can be retrofitted for hydrogen co-firing, reducing stranded capacity, mainly in the Organization for Economic Co-operation and Development (OECD) countries and Asia. However, electricity supply from co-firing generators is limited to about 1% of total electricity generation, because hydrogen co-firing is mainly used as a backup option to balance the variable renewable energies. The incremental fuel cost of hydrogen results in lower capacity factor of hydrogen co-fired generators, whereas low-carbon hydrogen contributes to reducing emission cost associated with carbon pricing. While hydrogen co-firing may play a role in balancing intermittency of variable renewable energies, it will not seriously delay the phase-out of fossil-based generators. Effects of hydrogen and ammonia co-firing with fossil power generation on decarbonization scenario are assessed. Co-fired generation is limited to <1% because of higher cost of hydrogen. It will not delay the phase-out of fossil-based generators.

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.

Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies. There lacks model comparison of global land use change projections. Here the authors explored how different long-term drivers determine land use and food availability projections and they showed that the key determinants population growth and improvements in agricultural efficiency.

We present an overview of results from 11 integrated assessment models (IAMs) that participated in the 33rd study of the Stanford Energy Modeling Forum (EMF-33) on the viability of large-scale deployment of bioenergy for achieving long-run climate goals. The study explores future bioenergy use across models under harmonized scenarios for future climate policies, availability of bioenergy technologies, and constraints on biomass supply. This paper provides a more transparent description of IAMs that span a broad range of assumptions regarding model structures, energy sectors, and bioenergy conversion chains. Without emission constraints, we find vastly different CO2 emission and bioenergy deployment patterns across models due to differences in competition with fossil fuels, the possibility to produce large-scale bio-liquids, and the flexibility of energy systems. Imposing increasingly stringent carbon budgets mostly increases bioenergy use. A diverse set of available bioenergy technology portfolios provides flexibility to allocate bioenergy to supply different final energy as well as remove carbon dioxide from the atmosphere by combining bioenergy with carbon capture and sequestration (BECCS). Sector and regional bioenergy allocation varies dramatically across models mainly due to bioenergy technology availability and costs, final energy patterns, and availability of alternative decarbonization options. Although much bioenergy is used in combination with CCS, BECCS is not necessarily the driver of bioenergy use. We find that the flexibility to use biomass feedstocks in different energy sub-sectors makes large-scale bioenergy deployment a robust strategy in mitigation scenarios that is surprisingly insensitive with respect to reduced technology availability. However, the achievability of stringent carbon budgets and associated carbon prices is sensitive. Constraints on biomass feedstock supply increase the carbon price less significantly than excluding BECCS because carbon removals are still realized and valued. Incremental sensitivity tests find that delayed readiness of bioenergy technologies until 2050 is more important than potentially higher investment costs.

Mitigation pathways by Integrated Assessment Models (IAMs) describe future emissions that keep global warming below specific temperature limits and are compared with countries’ collective greenhouse gas (GHG) emission reduction pledges. This is needed to assess mitigation progress and inform emission targets under the Paris Agreement. Currently, however, a mismatch of ~5.5 GtCO2 yr−1 exists between the global land-use fluxes estimated with IAMs and from countries’ GHG inventories. Here we present a ‘Rosetta stone’ adjustment to translate IAMs’ land-use mitigation pathways to estimates more comparable with GHG inventories. This does not change the original decarbonization pathways, but reallocates part of the land sink to be consistent with GHG inventories. Adjusted cumulative emissions over the period until net zero for 1.5 or 2 °C limits are reduced by 120–192 GtCO2 relative to the original IAM pathways. These differences should be taken into account to ensure an accurate assessment of progress towards the Paris Agreement.There is a mismatch between emission estimates from global land use calculated from IAMs and countries’ greenhouse gas inventories. This study presents a method for reconciling these estimates by reallocating part of the land-use sink, facilitating progress assessment towards climate goals.

Bioenergy is expected to play an important role in the achievement of stringent climate-change mitigation targets requiring the application of negative emissions technology. Using a multi-model framework, we assess the effects of high bioenergy demand on global food production, food security, and competition for agricultural land. Various scenarios simulate global bioenergy demands of 100, 200, 300, and 400 exajoules (EJ) by 2100, with and without a carbon price. Six global energy-economy-agriculture models contribute to this study, with different methodologies and technologies used for bioenergy supply and greenhouse-gas mitigation options for agriculture. We find that the large-scale use of bioenergy, if not implemented properly, would raise food prices and increase the number of people at risk of hunger in many areas of the world. For example, an increase in global bioenergy demand from 200 to 300 EJ causes a − 11% to + 40% change in food crop prices and decreases food consumption from − 45 to − 2 kcal person−1 day−1, leading to an additional 0 to 25 million people at risk of hunger compared with the case of no bioenergy demand (90th percentile range across models). This risk does not rule out the intensive use of bioenergy but shows the importance of its careful implementation, potentially including regulations that protect cropland for food production or for the use of bioenergy feedstock on land that is not competitive with food production.

The 2015 Paris Agreement calls for countries to pursue efforts to limit global-mean temperature rise to 1.5 °C. The transition pathways that can meet such a target have not, however, been extensively explored. Here we describe scenarios that limit end-of-century radiative forcing to 1.9 W m−2, and consequently restrict median warming in the year 2100 to below 1.5 °C. We use six integrated assessment models and a simple climate model, under different socio-economic, technological and resource assumptions from five Shared Socio-economic Pathways (SSPs). Some, but not all, SSPs are amenable to pathways to 1.5 °C. Successful 1.9 W m−2 scenarios are characterized by a rapid shift away from traditional fossil-fuel use towards large-scale low-carbon energy supplies, reduced energy use, and carbon-dioxide removal. However, 1.9 W m−2 scenarios could not be achieved in several models under SSPs with strong inequalities, high baseline fossil-fuel use, or scattered short-term climate policy. Further research can help policy-makers to understand the real-world implications of these scenarios.

Recent criticisms have suggested that future emissions are unlikely to lead to the warmest climate scenario available (SSP5–8.5), which has resulted in the second highest scenario (SSP3–7.0) receiving increased attention. The distinctiveness of SSP3–7.0 has not been well recognized, but it is relevant for the proper interpretation of studies that use this scenario.

A carbon tax is one of the measures used to reduce GHG emissions, as it provides a strong political instrument for reaching the goal, stated in the Paris Agreement, of limiting the global mean temperature increase to well below 2 °C. While one aspect of a carbon tax is its ability to change income distribution, no quantitative assessment has been made within the context of global poverty. Here, we explore future poverty scenarios and show the extent to which carbon tax revenue, obtained to limit global warming to well below 2 °C, has the potential to help eradicate poverty. In order to better understand the relationship between poverty and climate change mitigation policy, we developed a novel modelling framework that includes a module representing poverty indicators in the conventional integrated assessment model. We found that the poverty gap, which is a measure of the shortfall in income relative to the poverty line, is 84 billion US dollars (USD) and that the carbon tax revenue potential for the above-mentioned 2 °C consistent climate change mitigation would be 1600 billion USD in 2030. Many low-income countries cannot fill the poverty gap using only their own domestic revenue; however, this shortfall could be met by using a portion of the revenue in high-income countries. Our results demonstrate that climate change mitigation can have a great potential in synergy effects for resolving poverty and illustrates the importance of international cooperation.