Integrated Assessment Model Research Articles

The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures

Abstract. While the Intergovernmental Panel on Climate Change (IPCC) physical science reports usually assess a handful of future scenarios, the Working Group III contribution on climate mitigation to the IPCC's Sixth Assessment Report (AR6 WGIII) assesses hundreds to thousands of future emissions scenarios. A key task in WGIII is to assess the global mean temperature outcomes of these scenarios in a consistent manner, given the challenge that the emissions scenarios from different integrated assessment models (IAMs) come with different sectoral and gas-to-gas coverage and cannot all be assessed consistently by complex Earth system models. In this work, we describe the “climate-assessment” workflow and its methods, including infilling of missing emissions and emissions harmonisation as applied to 1202 mitigation scenarios in AR6 WGIII. We evaluate the global mean temperature projections and effective radiative forcing (ERF) characteristics of climate emulators FaIRv1.6.2 and MAGICCv7.5.3 and use the CICERO simple climate model (CICERO-SCM) for sensitivity analysis. We discuss the implied overshoot severity of the mitigation pathways using overshoot degree years and look at emissions and temperature characteristics of scenarios compatible with one possible interpretation of the Paris Agreement. We find that the lowest class of emissions scenarios that limit global warming to “1.5 ∘C (with a probability of greater than 50 %) with no or limited overshoot” includes 97 scenarios for MAGICCv7.5.3 and 203 for FaIRv1.6.2. For the MAGICCv7.5.3 results, “limited overshoot” typically implies exceedance of median temperature projections of up to about 0.1 ∘C for up to a few decades before returning to below 1.5 ∘C by or before the year 2100. For more than half of the scenarios in this category that comply with three criteria for being “Paris-compatible”, including net-zero or net-negative greenhouse gas (GHG) emissions, median temperatures decline by about 0.3–0.4 ∘C after peaking at 1.5–1.6 ∘C in 2035–2055. We compare the methods applied in AR6 with the methods used for SR1.5 and discuss their implications. This article also introduces a “climate-assessment” Python package which allows for fully reproducing the IPCC AR6 WGIII temperature assessment. This work provides a community tool for assessing the temperature outcomes of emissions pathways and provides a basis for further work such as extending the workflow to include downscaling of climate characteristics to a regional level and calculating impacts.

Pathfinder v1.0.1: a Bayesian-inferred simple carbon–climate model to explore climate change scenarios

Abstract. The Pathfinder model was developed to fill a perceived gap within the range of existing simple climate models. Pathfinder is a compilation of existing formulations describing the climate and carbon cycle systems, chosen for their balance between mathematical simplicity and physical accuracy. The resulting model is simple enough to be used with Bayesian inference algorithms for calibration, which enables assimilation of the latest data from complex Earth system models and the IPCC sixth assessment report, as well as a yearly update based on observations of global temperature and atmospheric CO2. The model's simplicity also enables coupling with integrated assessment models and their optimization algorithms or running the model in a backward temperature-driven fashion. In spite of this simplicity, the model accurately reproduces behaviours and results from complex models – including several uncertainty ranges – when run following standardized diagnostic experiments. Pathfinder is an open-source model, and this is its first comprehensive description.

Integrated assessment model of medical organization management efficiency based on mathematical approach

The article considers the problem of forming an integral indicator for evaluating the effectiveness of management in terms of ranking factors by their informativeness based on mathematical methods of pattern recognition. Since in the modern realities of the crisis, pandemic and other socio-political challenges, medical issues are becoming more and more relevant, it is proposed to take a more qualitative approach to assessing the effectiveness of management in this area. Assumptions are made about an integrated approach to the development of such an assessment that would cover the entire pool of necessary indicators. However, there are difficulties on this path, because in this case there will be many factors; with such a volume of data, calculations are difficult even with the available computing power. It is assumed that some of the parameters can be discarded, but the question arises: which are really less important, and which are simply necessary. To do this, it is proposed to use an algorithm to identify the most informative factors, as well as to use an integral evaluation indicator. The whole procedure for constructing an integral indicator for evaluating the effectiveness of management is divided into several parts. The most important part is the choice of informative factors. It is proposed to consider factors as some vector, with a priori weights found in a certain way. From a mathematical point of view, informativeness is proposed to be understood as the average distance between certain quantities. Then, with the help of the majority committee, the problem of pattern recognition is directly solved. At the same time, a question arises regarding the construction of the majority committee itself, and the main drawback of this approach is also indicated. The Seniority Committee is not considered in this case because of its inefficiency. To eliminate all the vulnerabilities, it is proposed to solve the problem of constructing a separating majority committee for sets by modifying the N. Nilson linear correction algorithm, which is the novelty of this method. This modification makes it possible to build the necessary dividing majority committee for the set, which subsequently leads to the choice of informative factors. The algorithm for selecting the most informative indicators is carried out for each enlarged group of factors. After its implementation, we get a certain number of indicators, much smaller than they were at the beginning, while the question of assigning weight to each factor remains open. To solve this problem, the authors propose the use of expert assessments. Thus, within each enlarged group of indicators, we get the sum of indicators with weighting coefficients, from which an integral indicator of the effectiveness of the management of a medical organization is already obtained.

Reduced-form and complex ACTM modelling for air quality policy development: A model inter-comparison

Simulation models can be valuable tools in supporting development of air pollution policy. However, exploration of future scenarios depends on reliable and robust modelling to provide confidence in outcomes which cannot be tested against measurements. Here we focus on the UK Integrated Assessment Model, a fast reduced-form model with a purpose to support policy development with modelling of multiple alternative future scenarios, and the EMEP4UK model which is a complex Eulerian Atmospheric Chemistry Transport Model requiring significant computing resources. The EMEP4UK model has been used to model selected core scenarios to compare with UKIAM, and to investigate sensitivity studies such as the interannual variability in response to meteorological differences between years. This model intercomparison addresses total PM2.5, primary PM2.5 and Secondary Inorganic Aerosol concentrations for a baseline of 2018 and selected scenarios for projections to 2040. This work has confirmed the robustness of the UK Integrated Assessment Model for assessing alternative futures through a direct comparison with EMEP4UK. Both models have shown good agreement with measurements, and EMEP4UK shows an ability to replicate past trends. These comparisons highlight how a combination of reduced-form modelling (UKIAM) and complex chemical transport modelling (EMEP4UK) can be effectively used in support of air pollution policy development, informing understanding of projected futures in the context of emerging evidence and uncertainties.

Climate change mitigation scenario databases should incorporate more non-IAM pathways

Ajay Gambhir is a senior research fellow at the Grantham Institute, Imperial College London. His research focuses on climate change mitigation, including integrated assessment modeling, national and sectoral energy modeling, and rural electrification. He also researches low-carbon technology innovation and cost-reduction processes, as well as just transitions and climate change mitigation co-benefits. Before becoming an academic, he was a UK government economist and policy analyst, during which time he worked on the UK Climate Change Act and the development of the UK’s carbon budgets. He holds a PhD in energy economics from Imperial College London. Gaurav Ganguly is the Chief Economist for Europe and the Middle East and the Head of the Climate Scenario Group at Moodys Analytics. He specializes in creating macroeconomic scenarios that explain the transmission of a range of risks such as climate change, geopolitics, deglobalization, and fiscal and monetary policy. He has been a fellow at the Grantham Institute at Imperial College London where he developed a framework for using climate scenarios within financial institutions. He holds a DPhil in economics from the University of Oxford. Shivika Mittal is a research fellow at the Grantham Institute, Imperial College London, with eight years’ experience working on climate change mitigation. Her work focuses on assessing low-carbon pathways at global, regional, and national levels using integrated assessment models, as well as national and sectoral energy models. She was a contributing author on the low-carbon transport chapter of the IPCC’s Sixth Assessment Report on mitigation of climate change. She holds a PhD in integrated assessment modeling from the Public Systems Group at the Indian Institute of Management, Ahmedabad, India. Ajay Gambhir is a senior research fellow at the Grantham Institute, Imperial College London. His research focuses on climate change mitigation, including integrated assessment modeling, national and sectoral energy modeling, and rural electrification. He also researches low-carbon technology innovation and cost-reduction processes, as well as just transitions and climate change mitigation co-benefits. Before becoming an academic, he was a UK government economist and policy analyst, during which time he worked on the UK Climate Change Act and the development of the UK’s carbon budgets. He holds a PhD in energy economics from Imperial College London. Gaurav Ganguly is the Chief Economist for Europe and the Middle East and the Head of the Climate Scenario Group at Moodys Analytics. He specializes in creating macroeconomic scenarios that explain the transmission of a range of risks such as climate change, geopolitics, deglobalization, and fiscal and monetary policy. He has been a fellow at the Grantham Institute at Imperial College London where he developed a framework for using climate scenarios within financial institutions. He holds a DPhil in economics from the University of Oxford. Shivika Mittal is a research fellow at the Grantham Institute, Imperial College London, with eight years’ experience working on climate change mitigation. Her work focuses on assessing low-carbon pathways at global, regional, and national levels using integrated assessment models, as well as national and sectoral energy models. She was a contributing author on the low-carbon transport chapter of the IPCC’s Sixth Assessment Report on mitigation of climate change. She holds a PhD in integrated assessment modeling from the Public Systems Group at the Indian Institute of Management, Ahmedabad, India.

Socio-technical modelling of UK energy transition under three global SSPs, with implications for IAM scenarios

The potential for using findings from socio-technical energy transition (STET) models in integrated assessment models (IAMs) has been proposed by several authors. A STET simulation model called TEMPEST, which includes the influence of societal and political factors in the UK’s energy transition, is used to model three of the global shared socioeconomic pathways (SSPs) at the national level. The SSP narratives are interpreted as inputs to TEMPEST, which drive scenario simulations to reflect varying societal preferences for mitigation measures, the level of political support for energy transition, and future economic and population trends. SSP1 and SSP2 come close to meeting UK net zero targets in 2050 but SSP5 does not reach net zero before 2080. An estimate of the total societal, political, and economic cost of scenarios indicates that while SSP1 achieves the best emissions reductions it also has the highest total cost, and SSP2 achieves the best ratio between rate of emissions reductions and total cost. Feasibility appears to be highest for SSP2 since it is the least different to historical precedent. Current UK government energy strategy is closer to the narrative in SSP5, however, which has the highest total cost and exceeds an estimated carbon budget by 32%. Three key TEMPEST findings are recommended for use in IAMs: (i) the uncertainty in emissions savings due to variability in political and societal support for energy transition, (ii) the influence of negative societal pushback to policies in achievement of expected policy outcomes, and (iii) the combined influence on energy service demand of disposable income, public willingness to participate, and user impacts from measures.

Critical mineral constraints in global renewable scenarios under 1.5 °C target

To avoid catastrophic climate change, the world is promoting a fast and unprecedented transition from fuels to renewables. However, the infrastructures of renewables, such as wind turbines and solar cells, rely heavily on critical minerals like rare earths, indium, etc. Such interactions between climate targets, energy transitions, and critical minerals were widely overlooked in the present climate scenario analysis. This study aims to fill this gap through an introduction of metal–energy–climate nexus framework with its application on global energy transition towards a carbon-neutral (or below 1.5 °C) target, in which six state-of-the-art integrated assessment models (IAMs) under different shared socioeconomic pathways were applied. Our analysis revealed that climate mitigation is expected to boost significantly the critical mineral demand by 2.6–267-fold, which varies greatly by IAM models. Solar power development may be constrained by tellurium (Te) and selenium (Se) shortage, while wind power will be jeopardized by the limited scalability of rare earth production. Moreover, a more sustainable pathway may come at higher demand for critical minerals along with higher renewable ratios. Consequently, a holistic investigation of the interaction of mineral, energy, and climate systems is highly recommended for future scenario designing.

Beyond climate economics orthodoxy: impacts and policies in the agent-based integrated-assessment DSK model*

Though climate physical and transition risks will likely affect socio-economic dynamics along any transition pathway, their unfolding is still poorly understood. This also affects the development of climate-change policies to achieve sustainable growth. In this paper, the authors discuss a series of results, assessing the materiality of climate risks for economic and financial stability and alternative policy pathways by means of the Dystopian Schumpeter meeting Keynes (DSK) agent-based integrated-assessment model. Their results suggest that the emergence of tipping points due to unmitigated physical risks will reduce long-run growth and spur financial and economic instability. Moreover, diverse types of climate shocks have a different impact on economic dynamics and on the chances of observing a transition to carbonless growth. While these results call for immediate and ambitious interventions, appropriate mitigation policies need to be designed. The authors’ results show that carbon taxation is not the most suitable tool to achieve zero-emission growth, given its serious transition costs. On the contrary, command-and-control regulation and innovation policies to foster green investments are the key elements of the most promising policy mix to put the economy on a green growth pathway. Overall, their results contradict the standard tenets of cost–benefit climate economics and suggest the absence of any trade-off between decarbonization and growth.

Measuring the compliance of management system in manufacturing SMEs: An integrated model

Research on the efficiency and sustainability of production systems has drawn attention to the importance of monitoring the social and environmental impacts of production processes and management systems. In particular, integrated models and tools need to be developed to assess the application of sustainable operations – especially in those sectors characterized by a high presence of SMEs.This paper proposes an integrated assessment model – the Small and Medium Enterprise Compliance Assessment (SECA) – for SMEs involved in manufacturing and production. SECA provides an integrated tool to detect a firm's compliance with mandatory requirements on environmental and social issues in accordance with relevant legislation applicable in the country. This assessment model employs a new Index of Small and Medium Enterprise Compliance to synthesize both the levels of compliance and the complementary risks to which the enterprise is exposed to, given the applicable legislative domains.To test the model, a pilot application was conducted based on the analysis of 99 Chinese-owned SMEs operating in the textile and fashion manufacturing district in Prato. These enterprises voluntarily underwent the assessment procedure to measure their compliance with mandatory processes and regulations.The results that emerge from this pilot application demonstrate the relevance and capacity of SECA to assess and understand the degree of SMEs' compliance with relevant legislation on sustainability matters. The application also demonstrates the models' potential to be adapted to other local contexts and SMEs as required.

Integrated value model for sustainability assessment of residential solar energy systems towards minimizing urban air pollution in Tehran

Renewable energy applications are lucrative alternatives to minimize urban environmental impacts. Solar energy, the most abundant, inexhaustible, and cleanest of all renewable sources, provides an opportunity to transform buildings from energy consumers into active energy producers. Nevertheless, photovoltaic (PV) and hybrid photovoltaic/thermal (PV/T) are considered the most viable alternatives for urban settlements. This study, as part of a broader research project, develops a new model to evaluate solar systems' air pollution mitigation capacity and assist decision-makers in adopting the most suitable solution. The approach is based on the integrated value model for sustainability assessment (MIVES), combined with the analytic hierarchy process (AHP) and sensitivity analysis. This multi-objective tool is applied to residential buildings in Tehran, a megacity example with unused rooftops, solar energy harvest potential, and air pollution reduction needs. Results reveal one square meter of PV and PV/T enables avoiding 211 and 488 kg CO2 emissions annually, as well as 1.2 and 1.9 g PM pollutants, respectively. Although PV achieves higher sustainability indexes as a better socio-economic alternative, PV/T can be a robust solution when stakeholders are more sensitive to environmental requirements and air pollution decrement potential. The critical obstacle to PV/T deployment is the lack of financial incentives. However, allocating 38 % of solar electricity feed-in tariffs to solar thermal energy could solve this issue. Compared to green roofs, solar systems stand out with CO2 saving and energy production potential. Researchers expect future solar collectors’ improvements, such as lower resource consumption, thus, becoming more environmentally friendly and cost-effective solutions.

GIS-Based Cluster and Suitability Analysis of Crop Residues: A Case Study in Yangon Region, Myanmar

In the study of biomass assessment, geospatial modeling-based analysis becomes crucial for the sustainable management of agriculture. Currently, there is no integrated sustainability assessment of the geographic information system (GIS) cluster or suitability analysis for the feedstock of crop residues. In order to fill this research gap and support the strategy of bioenergy formulation with the circular economy concept in agriculture residues in Myanmar, this study aims to assess the energy generation potential and site locations of treatment facilities for crop residue, utilizing the integrated assessment of GIS cluster and suitability modeling. The cluster analysis identifies the rice straw as the highest feedstock of crop residues and township-based high/low clusters. In addition, the electricity generation potential is estimated at 279.14 MW for different clusters of rice straw. Moreover, the suitability analysis in the study uses the conceptual model of variables for constraints and factors with the analytical hierarchy process (AHP) technique to evaluate the weights. The suitability analysis found high suitability areas of 14,603 hectares for treatment facilities within the high/low cluster of feedstock for rice straw. The multicriteria and GIS integrated assessment model adopted in this research can support the decision-makers in developing spatial-based strategic planning for bioenergy promotion which will support sustainable farming practices in Myanmar. Additionally, the proposed model is adaptable in study areas with similar feedstock.

Imagining a Place for Sustainability Management: An Early Career Call for Action

Imagining a Place for Sustainability Management: An Early Career Call for Action

Mitigation effects of global low carbon technology financing and its technological and economic impacts in the context of climate cooperation

This study developed a climatic-economic-technological integrated assessment model named CIECIA-TD-F. Based on model, the implementation effects of low carbon technology financing on climate mitigation, technology promotion, and economic development in the context of climate change cooperation were studied. The results indicate that carbon reduction, under the current pledged climate financing scale, is limited. Global surface warming in 2100 is still around 2.38 °C even when the technologies are globally shared. Low carbon technology financing improves technology R&D and absorptive capacities of the least developed countries. Their carbon reduction rates reach 50 percent under the capacity principle. However, donations impair the R&D inputs of developed countries and delay their advanced technological progress, leading to 1 percent more carbon emissions. This limits the imitations of China and Russia in turn by decreasing their imitation numbers by 1–2 percent. Collecting 800 billion USD per year from 2030 to 2100 is a climatically effective means. It holds global warming to 1.99 °C. However, the donors suffer more than 1 percent of economic losses. That indicates the economic feasibility of this means is weak. On this basis, we proposed a Pareto-improvement scheme which combines financing with technology sharing and national R&D improvements. This policy mix both achieves the 2 °C goal and protect the economic benefits of all countries. Thus, policy mix combining different measures will be more suitable for improving reduction effects and achieving multiple goals. Compared with sole technology financing, it has more significant global carbon governance meanings and is noteworthy in future climate negotiations.

Re-examining the impact of annual weather fluctuations on global livestock production

Attempts to analyze the effect of weather shocks on livestock production have been carried out using integrated assessment models (IAMs) or the cross-sectional (Ricardian) method. However, these methodologies are fraught with obvious shortcomings, such as omitted variable bias, amongst others. This paper, therefore, re-examines the relationship between weather changes and global livestock production using an established econometric strategy that takes care of the pitfalls inherent in the conventional approaches. Using country-level data and a variety of specifications, we find that a 1 °C increase in temperature will lead to a 9.7% reduction in global beef production on average. These adverse effects are amplified in hot, poor, and agriculture-dependent countries. Besides, we find that a marginal increase in annual precipitation would lead to a 2.1% increase in beef production in tropical countries but a 1.9% decrease in temperate ones. Also, our forecasts show that climate change will reduce animal output by a further 20% in the mid-century and an additional 40% by the end of the century assuming no adaptation other than the degree of adaptation observed in the historical period.

Quantifying value and representing competitiveness of electricity system technologies in economic models

Evaluating competition between electricity technologies is challenging because it depends on both their costs and their values. While technology costs can typically be estimated from projections of the cost components—capital, fuel, and O&M—estimating a technology’s value is more complex due to its dependence on its contributions to multiple different grid services, each with prices that can vary substantially over space and time. In this work, using an electricity model of the contiguous United States, we develop relationships between relative value and share of total generation for major electricity generation technologies which, when paired with projections of technology costs, can be used to estimate technology competitiveness. We identify significant differences in the relationship between relative value and generation share for variable renewable energy (VRE) and non-VRE sources, but we demonstrate that all technologies require consideration of their dynamic values (in addition to cost) when evaluating competitiveness. In addition, we demonstrate that relative value of a technology is substantially impacted by not only its own generation share but also other aspects of the system state, in particular the mix of other technologies present in the system. Finally, we use the developed relative value relationships in combination with projections of future technology costs in a coarse resolution model that competes technologies based on a comprehensive competitiveness metric: profitability-adjusted LCOE (PLCOE). We show that this simple representation of technology competition approximately recovers the generation mix from a detailed model, which is not possible using LCOE alone. Such an approach can be used to improve the representation of technology competition in coarse-resolution models such as integrated assessment models, for which simplified metrics are often needed.

Deployment of CO2 capture and storage in Europe under limited public acceptance—An energy system perspective

In this paper we analyse how in Europe large-scale deployment of CO2 capture and storage (CCS) technology may be hindered by limited public acceptance. We develop scenarios for how public acceptance may constrain the diffusion of CCS, either by reducing the overall amount of installable CCS capacity or by delaying its introduction, and show with an integrated assessment model how the type of limitation in CCS acceptance can critically impact the development of all sectors in the overall energy system over time. We also demonstrate that a reduction or delay in CCS diffusion as a result of critical public opinion can have substantial energy system impacts that differ across not only the nature of acceptance profile but also the sector(s) in which limited public acceptance materializes. Applying a constraint to CCS deployment in both industry and the power sector simultaneously leads to an energy system that is fundamentally different from the one that emerges if the constraint is only applied to the power sector. Depending on how and where CCS diffusion is constrained, net additional annual energy system costs in 2050 can vary between -50 billion up to nearly 800 billon $/yr.

From The Limits to Growth to Greenhouse Gas Emissions Pathways: Technological Change in Global Computer Models (1972–2007)

From the World2 and World3 models to contemporary Integrated Assessment Models (IAMs) that model carbon neutral emission pathways, global computer models have served as virtual laboratories for addressing economic, environmental and technological concerns together. Representing technological change has been a controversial element of global modelling efforts because, to a great extent, it sets the parameters on conceivable futures. To retrace this history, this article analyses four moments when modellers debated technological change: the controversy spurred by The Limits to Growth in the 1970s; subsequent global future studies during that decade; the IIASA Energy in a Finite World study in the 1980s; and the shift to endogenous technological change in IAMs in the 2000s. It shows that the notion of technological change as a predictable parameter affecting the future of society was not a given. Technological change progressively became a parameter in models as more elaborate methodologies were developed to simulate it. When modellers began to focus on climate action in the 1990s and 2000s, their interest in the relationship between technological change and social change dwindled. The increasing skill with which modellers formally represented technological dynamics was commensurate to the decline of heated discussions over how conflicting worldviews shaped simulations.

Net GHG emissions and air quality outcomes from different residential building electrification pathways within a California disadvantaged community

• Electrification can reduce net GHG emissions and public health impacts from PM-2.5 μ exposures. • Electrification of different gas appliances produces different load profile shapes. • Load profile shapes determine grid fossil generator unit responses and overall net impacts. • Local air quality benefits are principally determined by the volume of avoided gas use. • Ambient air quality impacts are principally determined by the timing of load profile changes. Electrification of gas appliances in residential buildings will be necessary to rapidly decarbonize the energy system. In California however, recent rates of adoption of electric appliances, especially within disadvantaged and vulnerable communities (DVCs), have been insufficient to meet the state's ambitious GHG emissions abatement targets. In this study we use an integrated assessment modeling framework to quantify the holistic benefits of different electrification pathways within a representative study area DVC. Results indicate that aggressive electrification retrofits can deliver significant net reductions in GHG emissions, even when future grid emissions from increased electric loads are factored in. We also find that these measures can also create significant net public health benefits, in terms of overall avoided impacts from particulate matter (PM-2.5 μ ) exposures. However, the realization of these net benefits requires tradeoffs between local improvements in air quality in the areas where electrification occurs, for smaller, but still significant, reductions in air quality, in areas where fossil fueled electricity generators remain active. We conclude with a discussion of some of the persistent barriers to electrification within DVCs and the import role of electrification within broader efforts to combat climate change and improve equity within the energy system.

Assessment of comprehensive energy systems for achieving carbon neutrality in road transport

The world is seeking to achieve carbon neutrality by 2050. In general, electrification is a key measure in all sectors. Meanwhile, there are several emissions reduction options also in the road transport sector to achieve carbon neutrality when considering the energy system as a whole. Hydrogen, hydrogen-based synthetic fuels, and bioenergy can serve as alternative energy sources, and carbon dioxide removal (CDR) technologies, including direct air capture, can offset CO2 emissions from petroleum fuels. Comprehensive analyses that consider outlooks for both automobiles and energy supply with spatiotemporal variation are thus needed to explore possible strategies for the rational achievement of carbon neutrality. Our analyses, based on the integrated assessment model DNE21+, show that, although battery electric vehicles (BEV) are important, hybrid and plug-in hybrid vehicles, accompanied by the introduction of CDR and synthetic fuels, can play important roles. Globally uniform regulations for introducing only BEV could hinder cost-effective emissions reduction.

Implications of intercontinental renewable electricity trade for energy systems and emissions

A rapid global energy transition, including the ramping up of electricity generation from renewables, is needed to limit global warming to 2 °C or 1.5 °C. However, renewable resource endowments vary widely between regions, and renewable electricity is currently mainly used locally. Here we use a global integrated assessment model to explore the implications of renewable electricity trade via a set of planned direct-current-type ultra-high-voltage (UHVDC) transmission lines for global energy transition and climate change. We find that renewable electricity trade across large world regions via the underlying UHVDC interconnection can boost renewable electricity production and reduce 2020–2100 cumulative CO2 emissions from the power sector up to 9.8%. Financial investments in the UHVDC lines are offset in the long term by reduced investments in other electricity-generation options, including nuclear and storage. Finally, we find that renewable electricity trade can substantially reduce air pollutant emissions in importing regions. Projects are under way for direct-current ultra-high-voltage transmission lines that would allow trading of renewable electricity across world regions. Guo et al. use integrated assessment models to explore different scenarios for the operation of these projects and assess their potential for decarbonization.