Carbon Price Scenarios Research Articles

Modeling cost-optimal fuel choices for truck, ship, and airplane fleets: The impact of sustainability commitments

For the next 25 years, numerous transport operators have introduced sustainability commitments to mitigate carbon emissions. However, static goals to reduce fossil fuel usage and adopt renewable fuel technologies pose economic risk. This study analyzes the costs of strategic fleet replacement through a mixed integer linear program. Comparing three Norwegian transport operators, we determine cost-optimal investments in fossil and renewable fuel technologies for two approaches: One integrating and the other neglecting sustainability commitments. Our findings reveal that the truck operator’s sustainability commitments incur minimal additional costs, with battery-electric trucks proving cost-effectiveness early. In contrast, ship and airplane operators exhibit significant differences in fleet replacement decisions, resulting in additional costs ranging from +6% to +31% for ships and +4% to +11% for airplanes, across fuel cost and carbon price scenarios. Norwegian carbon price regulations fall short in incentivizing a cost-competitive technology transition for ships and airplanes. Additional policies are needed to encourage gradual fleet replacement.

THE FINANCIAL IMPACT OF CARBON EMISSIONS ON POWER UTILITIES UNDER CLIMATE SCENARIOS

Power utilities, especially those that generate electricity by burning fossil fuels, produce significant amounts of carbon emissions. Mitigation of [Formula: see text]-equivalent ([Formula: see text]) emissions can be achieved by replacing power plants with renewable power installations and by adopting carbon-sequestration technologies. Physical upgrades are expensive, but carbon taxes, or the purchase of certificates and allowances on a voluntary carbon market, can be costly, too. Carbon costs may increasingly become a threatening liability for power utilities, eating into profits and undermining the financial viability of emission-intensive electricity generation. Thus, we consider an asset-and-liability, structural firm model to investigate the creditworthiness of a generic power utility. The utility’s assets dynamics are driven by the financial returns generated from the sold electricity for a set tariff which is modeled by a simple stochastic process. The liabilities not only depend on fuel, running, and depreciation costs, but also on the costs of [Formula: see text] emissions. As a case study, we consider Eskom, the South African power utility. We show the evolution of Eskom’s default probability under various fuel mix plans and technologies (as per SA’s Integrated Resources Plan (IRP) 2019), and under the Network for Greening the Financial System (NGFS) carbon price scenarios. The obtained results and insights present a trying path ahead, especially for carbon-intensive power utilities.

Cost, market, and policy constraints on mitigating climate change through afforestation in China

Afforestation is a promising nature-based climate solution for mitigating climate change, but it is subject to a complex web of biophysical, cost-benefit, market, and policy processes. Although its biophysical feasibility has been established, the cost, market, and policy constraints that affect climate change mitigation through afforestation are still unclear. Here, we estimate such cost, market, and policy constraints on the basis of biophysical feasibility. Our findings reveal that implementation costs are a more relevant constraint than opportunity costs on mitigating climate change through afforestation. The China Certified Emission Reduction market currently provides only a 0.308 % incentive for climate change mitigation through afforestation, due to market access constraints. The current market prices of China Certified Emission Reduction, China Carbon Emissions Trading Exchange, and Nature Based Carbon Offset in Voluntary Carbon Market constrain 88.15 %, 87.95 %, and 85.75 % of CO2 removal actions through afforestation, compared to the carbon price scenario (US$62.97 tCO2-1) of the EU Emissions Trading System. Moreover, land policy under the scenarios of prohibiting conversion of cultivated land to forest and forest restoration in degraded areas exhibit 8.87–29.59 % and 65.16–74.10 % constraints, respectively, on mitigating climate change through afforestation compared to land-use freedom conversion scenarios from 2020 to 2060. Thus, enhancing the incentive price of CO2 removal, addressing the market access barrier, strengthening cooperation between global carbon markets, and exploring carbon–neutral and food multi-oriented land policies can be valuable sources of mitigation efforts over the next 40 years.

A modelling framework for equity portfolio projections under different carbon price scenarios

It is recognised that climate risks (including carbon pricing policy) are a new source of risk for the financial system. We propose a modelling framework for medium-term projections of stock returns under different carbon price scenarios. First, we construct a green factor to augment the classic capital asset pricing model (CAPM) and capture a firm’s exposure to climate policy risks. Then, we project to 2040 the factors of the CAPM, conditional on different carbon price pathways, using the estimated medium-scale Bayesian vector autoregressive model (MBVAR). Finally, we project the stock returns of each firm in the portfolio. Our scenarios suggest that the impacts of a carbon price policy are not confined to the most polluting firms (mining and quarrying, transportation and storage firms) for the effect of systematic risk. Moreover, in the short term, the negative impacts of a carbon price policy are more accentuated under a disorderly than an orderly transition. In the medium term, the projections suggest that the stock market progressively adapts to new conditions and believes in the benefits of rigorous carbon policies to incentivise the transition to a low-carbon economy. The proposed toolbox may represent effective support for investors in preparing portfolios for climate transition risks in the context of uncertainty regarding the timing of the introduction of a carbon policy. For policymakers, it can help shed light on how policies to prevent or mitigate climate change effects can affect financial stability.

Emissions offset incentives, carbon storage and profit optimization for Australian timber plantations

This article evaluates additional carbon storage that becomes profitable over a range of carbon credit prices through Australian Emissions Reduction Fund (ERF) methods introduced in 2017 for timber plantations. We found prices of $20 and $50 CO2-eq t−1 motivated switching 4% and 29% of southern Australian case study estate stands from short-rotation E. globulus to long-rotation P. radiata, resulting in 10% and 48% more estate carbon storage. We found no uptake of not for harvest environmental plantings to be profitable, even at carbon prices of $100 CO2-eq t−1. This appears to be because of the relatively faster initial growth and carbon gain for long-rotation timber as compared to environmental planting species and the detail of baseline and comparison scenario definitions used in credit calculations. We also evaluated carbon storage versus profit trade-offs over the full set of technically possible and efficient estate management options to achieve abatement, greater than levels that maximize profit. Key conclusions from this analysis were that significant carbon storage increases even beyond what is profitable are possible for the case study estate at relatively little reduced profit opportunity cost for carbon prices of $20 CO2-eq t−1 and less. In contrast, managing all stands in the estate for the sole objective of improving carbon storage could nearly double carbon storage but result in a significant 27% profit reduction under a $20 CO2-eq t−1 carbon price scenario.

TEMPERATURE AND ENERGY SECURITY: WILL FOREST BIOMASS HELP IN THE FUTURE?

Despite the numerous technical, logistical, and policy challenges associated with the use of bioenergy to mitigate climate change, the latest IPCC report identifies bioenergy as a high-value and large-scale mitigation option to support the transition to a cleaner energy system. This paper links a climate-economic-energy model and a land model to measure the net mitigation effect of using forest biomass for electricity generation and corresponding implications on global temperature. Through the soft-link, the energy model provides to the land model the cost-effective regional consumption of forest biomass under nine carbon price scenarios and measures the effects of its use on fossil fuel emissions and carbon sequestered in carbon capture and storage (CCS). The land model provides the dynamic supply of forest biomass and measures the change in land management/use under each demand scenario and corresponding changes in carbon sequestered in forests. Results suggest that forest biomass should be part of global mitigation efforts despite the expected small share of electricity sourced from it. The net climate benefits of forest biomass energy vary across scenarios and temporally — in most scenarios increased biomass demand results in near term reductions in global forest carbon stocks, but at carbon prices starting at $40/tCO2e or greater, results show positive net sequestration by 2030. This increased sequestration, coupled with energy emissions displacement and bioenergy with carbon capture and storage (BECCS) implies substantial long-term mitigation potential for forest biomass energy. Our results suggest that high forest biomass demand pathways could also help reduce the magnitude of future temperature growth. Further, we explore the regional effects on energy security of using forest biomass. Results show that its use can have potential large effects on trade dynamics and regional energy security issues, with 4 of the 17 global regions found to be net exporters of forest biomass.

The role of carbon pricing in achieving energy transition in the Post-COP26 era: Evidence from China's industrial energy conservation

Carbon pricing is expected to meet COP26 targets and carbon neutrality goals by promoting energy transition. However, the role of carbon pricing in energy transition has been challenged largely because of limited empirical evidence. Most empirical studies draw on samples with low-to-moderate carbon prices, which might underestimate the potential impact of carbon pricing with much higher prices. Accordingly, this study takes energy prices as proxies for carbon prices to estimate the price elasticity of energy consumption. It employs a mapping relationship between carbon and energy prices to conduct simulations under various carbon price scenarios. Using China's industry as an example, the following main findings were obtained. First, the price elasticities of energy consumption are heterogeneous across sectors, implying that the role of carbon pricing may be underestimated if sector heterogeneity is not considered. Second, carbon pricing could considerably decrease energy consumption, particularly in high-energy-consuming sectors, such as ferrous metals, petroleum processing, chemicals, non-metal products, as well as power and heat. Third, by adopting China's Emissions Trading Scheme, the eight planned covered sectors could achieve reductions of 8% or 19% in energy consumption with carbon prices set at 100 or 300 Yuan/tCO2, respectively, which would significantly contribute to the phasedown of coal. Therefore, carbon pricing could play an important role in achieving energy transition in the post-COP26 era.

Optimizing the aluminum supply chain network subject to the uncertainty of carbon emissions trading market

Aluminum production is characterized by high electricity consumption; hence its decarbonization hinges on upstream low-carbon electricity generation. As a result, the supply chain of aluminum product manufacturing can be strongly affected by the uncertainty of carbon emissions price via electricity generation. This paper investigates these impacts on the strategic design and the tactic operations of the aluminum supply chain by constructing a stochastic mixed-integer linear programming (SMILP) model, in which carbon price uncertainty and demand uncertainty are both accounted for. The supply chain case in the study covers a full process from upstream power generation to end-use consumption. A variety of stochastic carbon price scenarios are designed and assessed. Sensitivity analysis with respect to demand fluctuation is also performed. The results show that carbon price uncertainty significantly affects the configuration of the whole system. The main driving forces are the supplier selection and configuration alteration triggered by the carbon price variation, whereas other metrics such as carbon emissions costs and the responses to demand fluctuations display complicated patterns of change. This study provides a useful analytical framework that can be applied to the planning problem for other industries facing the same challenge.

Optimal rotation period ofPopulusplantations considering multiple carbon pools and carbon cap policies in Jiangsu, East China

AbstractForests provide wood biomass to produce various wood products while sequestering CO2 from the atmosphere. The joint benefits of wood production and carbon sequestration should be considered when making forest management decisions such as those related to optimal rotation periods. In this study, we extend the Faustmann model to consider the effects of timber value and the dynamics of forests’ multiple carbon pools (biomass, dead organic matter and long-period forest products) on the optimal rotation and the corresponding net present value (NPV). The theoretical framework also takes account of dynamic carbon prices and potential effects of carbon cap policies. We showcase our approach using Populus × euramericana “Nanlin895” as an example. This tree species is an important species for the planted forests in East China. The results show that: (1) multiple carbon pools increase the optimal rotation period by 4.76 per cent and the NPV by 45.66 per cent under the static carbon price scenario, (2) the tightening carbon cap facilitates carbon price variation and results in a significant increase in the NPV, while the optimal rotation period fluctuates between 8 and 10 years and (3) frequent cap policy adjustments shorten the optimal rotation period and lower the NPV even if the cap reduction target is achieved. Although the effect of carbon benefits on the optimal rotation period is small, the forest carbon trade mechanism could effectively enhance landowners’ income through the tightening carbon cap. These findings have significant policy implications for forest management.Highlights • We analyze the effects of multiple carbon pools on the optimal rotation period and the net present value.• We examine how carbon trade affects the management decision of Populus plantations.• Tightening the carbon cap promotes dynamic carbon price variation, benefiting landowners.

Scenario modelling of biomass usage in the Australian electricity grid

Responding to the global crises - Covid19 and climate change - governments around the world are formulating green recovery plans to stimulate economic growth, boost clean energy technologies and cut emissions. Potential transition pathways for low carbon energy systems, however, remain as open questions. Generally, the simulation of biomass in the grid models is limited in their tempo-spatial resolution, transition pathways description, and/or biomass feedstock supply representation. This study aims to provide spatio-temporal highly resolved grid configurations featuring disaggregated biomass feedstocks, to assess Australia's potential energy transition pathways and 100% renewable electricity supply scenarios under various biomass bidding strategies and cost assumptions. We find that, as carbon prices increase, bioelectricity will prove to be a cost-effective flexible option compared to other low-carbon (such as CSP) and fossil-based flexible options (e.g. coal and gas), with its generation share reaching ∼9%-12% at higher carbon price scenarios. Biomass power plants can be well suited for operating in gap-filling mode to provide flexible power generation and to facilitate grid stability and load balancing. In light of the high biomass resource potential in Australia, keeping bioelectricity in the generation mix is beneficial for reducing system capacity and cost by 32% and 21%, respectively, under a future renewable-dominated Australian grid system.

Design a sustainable supply chain for the textile and clothing industry with consideration of carbon emissions

The clothing industry accounts for nearly 60% of the global textile industry. It is largely responsible for the consumption of non-renewable resources. According to studies, it is responsible for nearly 10% of greenhouse gas emissions in the world (Cuc and Vidovic (2014)). The aim of this article is to propose a planning approach that integrates two decision levels (strategic and tactical), using a new mixed integer linear programming model (MILP) that integrates carbon emissions in SCMP (Supply Chain Management Planning). This approach must be used in a general way in all SCMP industries for the control of carbon flows and resources. It could be used as a decision support tool to evaluate and monitor the effects of carbon emissions. This tool offer to the industrials the best choices at different stages (selection of suppliers, plants, transportation modes, storage etc.), with lower cost and carbon emissions. For this purpose, the approach is tested on several scenarios, based on severals literature case studies in the textile and clothing sectors. The results show that carbon price uncertainty would significantly influence the economic and environmental management of the supply chain, and the repartition of the manufacturing activity (insource or outsource). Over a range of carbon price scenarios, the results show a reduction over to 36% in carbon emissions in the supply chain.

Hydrogen supply chain optimisation for the transport sector – Focus on hydrogen purity and purification requirements

This study presents a spatially-resolved optimisation model to assess cost optimal configurations of hydrogen supply chains for the transport sector up to 2050. The model includes hydrogen grades and separation/purification technologies, offering the possibility to assess the effects that hydrogen grades play in the development of cost-effective hydrogen supply chains, including the decisions to repurpose gas distribution networks or blending hydrogen into them. The model is implemented in a case study of Great Britain, for a set of decarbonisation and learning rate scenarios. A base case with a medium carbon price scenario shows that the total discounted cost of the hydrogen supply chain is significantly higher than shown in previous studies, largely due to the additional costs from purification/separation needed to meet hydrogen purity standards for transport applications. Furthermore, it was shown that producing hydrogen from steam methane reforming with carbon capture and storage; installing new transmission pipelines; repurposing the gas distribution network to supply 100% hydrogen; and purifying hydrogen with a pressure swing adsorption system locally at the refuelling station; is a cost optimal configuration for the given technoeconomic assumptions, providing hydrogen at £6.18 per kg at the pump. Purification technologies were found to contribute to 14% and 30% of total discounted investment and operation costs respectively, highlighting the importance of explicitly including them into hydrogen supply chain models for the transport sector.

Demand for Storage and Import of Natural Gas in China until 2060: Simulation with a Dynamic Model

China has been reforming its domestic natural gas market in recent years, while construction of storage systems is lagging behind. As natural gas accounts for an increasing proportion due to the goal of carbon neutrality, large-scale gas storage appears to be necessary to satisfy the needs for gas peak shaving and national strategic security. Additionally, the domestic gas production in China cannot meet consumption demands, and imports will play a significant role on the supply side. This paper developed a system dynamics (SD) model and applied it to simulate gas market behaviors and estimated China’s gas storage capabilities and import demands over the next 40 years. To achieve carbon neutrality, it is necessary for China to make great progress in its energy intensity and improve its energy structure, which have a great impact on natural gas consumption. Thus, alternative scenarios were defined to discuss the changes in the gas market with different gas storage goals and environmental constraints. The results show that under low and medium carbon price scenarios, natural gas demand will continue to grow in the next 40 years, but it will be difficult to achieve the goal of carbon neutrality. Under the high carbon price scenario, natural gas consumption will grow rapidly and reach a peak in approximately 2040, after which renewable energy will play a more important role to help achieve carbon neutrality. At the peak time, China’s gas storage demand will be 205.5 billion cubic meters (bcm) and import demand will reach 635.4 bcm, accounting for 72.8% of total consumption. We also identified the contradiction between the estimated storage capability, import demand and infrastructure planning. There will be a gap of 28.1–69.3 bcm between the planned storage capacity and simulated demand by 2030, while import facilities may partly strand assets. Finally, we provided some policy recommendations for constructing gas storage and import management and operation systems.

Towards improved cost evaluation of Carbon Capture and Storage from industry

This paper contributes to the development of improved guidelines for cost evaluation of Carbon Capture and Storage (CCS) from industrial applications building on previous work in the field. It discusses key challenges and factors that have a large impact on the results of cost evaluations, but are often overlooked or insufficiently addressed. These include cost metrics (especially in the context of industrial plants with multiple output products), energy supply aspects, retrofitting costs, CO2 transport and storage, maturity of the capture technology. Where possible examples are given to demonstrate their quantitative impact and show how costs may vary widely on a case-by-case basis.Recommendations are given to consider different possible heat and power supply strategies, as well as future energy and carbon price scenarios, to better understand cost performances under various framework conditions. Since retrofitting CCS is very relevant for industrial facilities, further considerations are made on how to better account for the key elements that constitute retrofitting costs. Furthermore, instead of using a fixed unit cost for CO2 transport and storage, cost estimates should at least consider the flowrate, transport mode, transport distance and type of storage, to make more realistic cost estimates. Recommendations are also given on factors to consider when assessing the technological maturity level of CCS in various industrial applications, which is important when assessing cost contingencies and cost uncertainties.Lastly, we urge techno-economic analysis practitioners to clearly report all major assumptions and methods, as well as ideally examine the impact of these on their estimates.

Towards Improved Cost Evaluation of Carbon Capture, Transport and Storage From Industry

This paper briefly summarises the development of improved guidelines for cost evaluation of carbon dioxide capture, transport and storage (CCS) from industrial applications [1] building on previous work in the field. It discusses key challenges and factors that have a large impact on the results of cost evaluations but are often overlooked or insufficiently addressed. These include cost metrics (especially in the context of industrial plants with multiple output products), energy supply aspects, retrofitting costs, CO2 transport and storage, and maturity of the capture technology. Where possible, examples are given to demonstrate their quantitative impact and show how costs may vary widely on a case-by-case basis. Recommendations are given to consider different possible heat and power supply strategies, as well as future energy and carbon price scenarios, in order to better understand CCS costs under various conditions. Since retrofitting CCS is especially relevant for industrial facilities, further recommendations are made on how to better account for the key elements that constitute retrofitting costs. Furthermore, instead of using a fixed unit cost for CO2 transport and storage, cost estimates should at least consider the CO2 flowrate, transport mode, transport distance and type of storage, to obtain more realistic cost estimates. Recommendations are also given on factors to consider when assessing the technological maturity level of CCS in various industrial applications, which is important when assessing cost contingencies and uncertainties. Lastly, we urge techno-economic analysis practitioners to clearly report all major assumptions and methods, as well as comprehensively examine the impact of uncertainties on their cost estimates.

Development of a framework for the assessment of the market penetration of novel in situ bitumen extraction technologies

Greenhouse gas (GHG) mitigation opportunities from emerging in situ mining technologies in oil sands production can play a role in reducing global warming. There is limited research on quantitative assessments of the penetration of emerging oil sands technology in the energy sector. This study addresses this gap by developing a novel framework (MAPL-OET) to assess the market penetration of emerging oil sands extraction technologies. The framework is robust and data-intensive as it combines diffusion models, econometrics models, cost models, and energy-economy equilibrium models. The combined model evaluates the adoption of new energy technologies resulting from carbon price measures and other economic factors, as well as the GHG mitigation potential in the oil sands sector. The accumulated GHG mitigation potential from high carbon and BAU scenarios (i.e., a carbon price of $30/tonne of CO2 in 2030, increasing at a rate of 4%/yr to reach about $105/tonne of CO2) was estimated to be 192.8 Mt of CO2 eq between 2018 and 2050. New extraction technologies also improve average energy intensities by 1.3% annually in the high carbon price scenarios. The developed new framework can help public and private organizations to achieve energy or environmental targets.

The future of coal supply in China based on non-fossil energy development and carbon price strategies

To realize China’s low-carbon development, coal needs to be produced and consumed in a clean and efficient way. In this paper, a multi-regional coal supply model is developed to gain insights into China’s coal supply system up to 2050. Regional disparity, coal classification, and the development of clean coal technologies are specified in the model. Based on MESSAGEix, this model takes full consideration of coal mining, preparation, transformation, and transportation processes. Moreover, the effects of non-fossil energy development and carbon price are discussed. With the above framework, the future of China’s coal supply system is optimized. Results indicate that: 1) China’s national raw coal production will peak in 2030 under the business-as-usual scenario, while it has already peaked under the GREEN and carbon price scenarios, 2) The amount of coal used in final consumption and transformed into coke decreases, while coal transformed into liquids and SNG increases from 11 Mt in 2015 to 221 Mt in 2050 under the business-as-usual scenario, 3) both non-fossil fuel development and carbon price strategies have a positive effect on coal supply regulation and coal-related GHG emission reduction, 4) carbon price could facilitate the adoption of CCS technology and can effectively reduce coal-related GHG emissions.

The economic costs of planting, preserving, and managing the world\u2019s forests to mitigate climate change

Forests are critical for stabilizing our climate, but costs of mitigation over space, time, and stakeholder group remain uncertain. Using the Global Timber Model, we project mitigation potential and costs for four abatement activities across 16 regions for carbon price scenarios of $5–$100/tCO2. We project 0.6–6.0 GtCO2 yr−1 in global mitigation by 2055 at costs of 2–393 billion USD yr−1, with avoided tropical deforestation comprising 30–54% of total mitigation. Higher prices incentivize larger mitigation proportions via rotation and forest management activities in temperate and boreal biomes. Forest area increases 415–875 Mha relative to the baseline by 2055 at prices $35–$100/tCO2, with intensive plantations comprising <7% of this increase. Mitigation costs borne by private land managers comprise less than one-quarter of total costs. For forests to contribute ~10% of mitigation needed to limit global warming to 1.5 °C, carbon prices will need to reach $281/tCO2 in 2055.

Selection of representative slices for generation expansion planning using regular decomposition

In power and energy system planning tools, the temporal detail is often reduced by selecting representative slices out of longer time series. Various methods exist for the selection task, but they may prove slow or otherwise unfavourable in practical applications. Here, a generalized clustering algorithm, referred to as regular decomposition, is presented and applied to a power system planning study covering countries in the Northern Europe. The algorithm is compared with other selection methods, and the comparison is repeated with various number of representative slices and in three carbon price scenarios in order to provide more robust results. When selecting four weeks or more, regular decomposition is shown to perform relatively well compared to the other selection methods in terms of the total costs resulting from the power system model runs. When applied to inter-annual time series, regular decomposition is demonstrated to scale well. Although random sampling shows the most stable performance overall, the results indicate the need to test several methods for each system. Moreover, the results highlight the need to include net load peaks in the selected slices and to carefully estimate their position in the time series. A two-stage method for including net load peaks is presented.

Achieving the Paris Agreement’s 2 degree target in Nepal: the potential role of a carbon tax

ABSTRACT The 2015 Paris Agreement aims to limit global temperature rise in this century to well below 2°C above the pre-industrial level, and pursue efforts to limit further the temperature rise below 1.5°C. All parties ratifying the Paris Agreement have submitted Nationally Determined Contributions (NDCs), many stating emission reduction targets. The international climate research community has designed five different Shared Socioeconomic pathways (SSPs) to characterize various possibilities in demographic and economic changes over the next century. These SSPs were implemented by six integrated assessment model (IAM) teams, which also determined the carbon price trajectory required to limit the temperature rise below 2°C in respective SSPs. In SSP5, also termed the fossil-fueled development scenario, only three IAMs identified that the 2°C target would be feasible, with carbon prices ranging from 220 to 518 US$/tCO2e in 2050. This study aims to analyse the effects of these carbon prices on energy and emissions during 2015–2050 in Nepal. It does so using a long-term energy system model using the framework of the Asia-Pacific Integrated Model/Enduse (AIM/Enduse) modelling tool. The base case scenario and three carbon price scenarios are developed. Primary energy supply, energy security, energy technology-mix (especially renewable energy usage and hydropower development), emissions of greenhouse gases (GHGs) and local pollutants, and local/regional environmental co-benefits are compared between the base case scenario and carbon price scenarios. The study finds that the implementation of a carbon tax would promote domestic hydropower, improve energy-efficiency and reduce imports of fossil fuels when compared to the base case. Hydropower-based electricity would have a major role in reducing emissions. Key policy insights The carbon prices in SSP5 determined by IAMs to achieve the 2°C target would be sufficient to achieve Nepal’s targets under its NDC in the energy sector. The industry and transport sectors would offer the highest GHG emission reduction. Hydropower and biomass would have major roles in decarbonizing the energy system.