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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Economic and Environmental Analysis to Evaluate the Potential Value of Co-Optima Diesel Bioblendstocks to Petroleum Refiners

The U.S. petroleum refining sector is undergoing a period of historic transformation, catalyzed by the decarbonization of the U.S. economy. Diesel-boiling-range bioblendstocks have gained traction, owing to their superior fuel properties and environmental performance as compared to traditional petroleum fuels. This work couples refinery linear programming models with life cycle assessment to quantify the potential economic and environmental benefits, and trade-offs, of blending diesel-boiling-range bioblendstocks at petroleum refineries. Linear programming models were developed in Aspen Process Industry Modeling Systems (PIMS) for three representative petroleum refinery configurations of differing complexity. Seven diesel-boiling-range bioblendstocks: 4-butoxyheptane, 5-ethyl-4-propylnonane, soy biodiesel, sludge hydrothermal liquefaction diesel, polyoxymethylene ethers, renewable diesel, and hexyl hexanoate, were investigated to identify key fuel properties that influence refineries' economics and to track the effect of adding bioblendstocks on refinery-wide cradle-to-gate greenhouse gases (GHG) emissions. These analyses considered blending levels from 10 to 30 vol% and fuel demand projections over the period 2040 to 2050. This analysis determines that bioblendstock sulfur content and cetane number are the primary fuel attributes with the potential to provide value to refiners. Life cycle assessment results indicate that the use of diesel-boiling-range bioblendstocks can reduce cradle-to-gate refinery GHG emissions by up to ~ 40 % relative to conventional refinery operations when considering carbon uptake in the supply chain of the bioblendstock. Refinery-wide marginal GHG abatement costs range from 120 to 3,600 USD2016/metric tons carbon dioxide equivalent avoided across the scenarios evaluated. Reducing the price of bioblendstocks is identified as a key to their adoption.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS,ENERGY P↗
DOE OSTI2023

Chapter 13: All-Electric Vertical Take-Off and Landing Aircraft (eVTOL) for Sustainable Urban Travel

Increasing urbanization, ground congestion, and greenhouse gas emissions have spurred aircraft pioneers to capitalize on advancements in battery technology, electric motors, software, and other advances to develop all-electric vertical take-off and landing (eVTOL) aircraft intended to save travelers time within densely populated urban regions. This study served as an example for conducting a life-cycle analysis (LCA) of an eVTOL aircraft, analyzing its manufacturing process, its in-life operation as a passenger transportation service between urban locations, and (in part) end-of-life treatment. This case study aims to provide guidance on how to accurately conduct eVTOL LCA, particularly on how to define the problem, how to obtain the right information from engineers inside and outside their own organizations, and what areas to focus on. As LCA results are only as accurate as the assumptions that were made, a more rigorous LCA that includes sensitivity analysis and uncertainty characterization can help further understand the limitations of those assumptions. New technologies such as blockchain may also play an important role in LCA, including the life-cycle inventory and improving confidence intervals. Completing a credible LCA is central to supporting the argument in favor of introducing the new technology. Completing such a study will allow companies to demonstrate to relevant stakeholders the likely impact of their aircraft on the environment by quantifying the operational climate footprint of the aircraft and the manufacturing process used to build it. To this end, this case study also provides examples of how to report and present LCA results, optimizing for communications to non-LCA experts. The LCA can also assist in identifying opportunities to improve the environmental performance at various life-cycle stages, informing decision makers as products and manufacturing processes evolve or are redesigned. Given the nascency of both eVTOL aircraft manufacturing and operations, it is strongly recommended that LCA analysts treat reports on eVTOL aircraft as works-in-progress. As new information is found, design changes are made, and the aircraft or operation gains maturity, it is inevitable that some amendments will need to be made to the LCA. It is suggested that a complete overhaul of the LCA be made every 18-24 months throughout the R&D, design, and operational scale-up phases of the project.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

New Engineering Concepts to High Energy Density Li-S Batteries

Li-S batteries (LSBs) with energy densities > 500 Wh/kg @ C/5 and >1000 cycles, cycle life operating over wide temperatures has been identified to be critical for meeting the global energy demands. Progress is however, very much limited due to several major hurdles related to the following: (a) poor Li' reaction kinetics (conductivity/diffusivity) enabling full reversible S conversion to Li2S, (b) inferior electron (e) conductivity, specific capacity and cycle life due to electrolyte soluble species of polysulfides (PSs) formed with the reaction of Li ions with sulfur migrating to anode, (c) unstable solid electrolyte interphase (SEI) formation and finally, (d) dendrites that are formed on the Li metal anode severely limiting the cycle life due to polarization at the solid/liquid interfaces causing safety, inferior capacity, energy density, rate, and cycle life issues. Creation of a fully functional economical ≤$80/kWh, high energy density LSBs is vital for enabling its widespread commercial deployment and use in current and next generation electric vehicles.

25 ENERGY STORAGE↗
DOE OSTI2022

Carbon Intensities of Refining Products in Petroleum Refineries with Co-Processed Biofeedstocks

Petroleum refineries increasingly seek to generate fuels with lower carbon intensities (CIs; a measure of life cycle greenhouse gas [GHG] emissions per unit of energy of fuel; well-to-wheel [WTW]) to meet growing demand. Co-processing refers to a process that adds biomass-derived feedstocks to the fossil-based feedstocks of existing petroleum refinery process units. With the use of biofeedstocks, it is expected that co-processed fuels would have lower CIs than their petroleum counterparts without requiring changes in the existing infrastructure for producing, transporting, and using fuels. To quantify the GHG emissions reduction benefits of co-processing, this study uses a linear programming model to simulate petroleum refinery conditions with and without co-processing. The co-processing cases include three biofeedstocks (soy oil, tallow, and used cooking oil or UCO) used as 10 vol.% of the feedstock to a hydrotreater or hydrocracker since these lipid-based feedstocks have favorable properties to be treated in a hydrotreater or hydrocracker. In addition, we considered pyrolysis oil used as 10 vol.% of the feedstock to a fluid catalytic cracking (FCC) unit in the modeled refinery due to its higher oxygen content compared to other lipid-based feedstocks. Life cycle analysis (LCA) using two distinct approaches—process-level energy allocation and a refinery-level marginal approach—has been conducted for each case. The LCA results using process-level allocation show that there are no noticeable changes in emissions or energy use impacts at the facility level. The life cycle GHG emission reductions of co-processing cases are mainly related to the fraction of biogenic carbon embedded in each fuel product. For example, co-processed jet fuels (a mixture of fossil and biogenic fuels) made via hydrotreating or hydrocracking have higher biogenic carbon, which results in jet fuel CI reductions of 3.9%–8.6% compared to the CI of baseline petroleum jet fuels on a WTW basis. However, analysis of co-processed pyrolysis oil in an FCC shows that a higher fraction of biofeedstocks (29%) becomes process emissions (i.e., CO and CO 2 ), mainly due to the oxygenates in pyrolysis oil, and so it generates less renewable fuel than biofeedstocks co-processed via hydrotreating or hydrocracking. Using the refinery-level marginal approach, the changes in energy use and emissions of co-processing cases compared to the petroleum-only baseline case are allocated to the changes in fuel production (assuming renewable fuels). This approach generates the life cycle GHG emission values of co-processed renewable fuels, which are comparable to the CIs of standalone biofuel production pathways. However, as this approach relies on a rough assumption that product yields and emissions from co-processing units on fossil feedstocks remain the same with and without biofeedstock inputs, co-processing cases like FCC pyrolysis oil may generate quite skewed results.

02 PETROLEUM↗
DOE OSTI2024

HIPSTER (Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics) [SWR-24-17]

Development of a prototype, code-based life cycle assessment framework, the Harmonized Impacts across Products, Scenarios, and Technologies for Environmental and Resource metrics (HIPSTER), to coherently assess outputs of prospective NREL models across environmental and resource use metrics. Eventually, HIPSTER is aimed to also cover socioeconomic and justice metrics. At present, NREL model scenario impact assessments are performed incoherently, as they as based on varying assumptions and inputs, specifically life cycle inventories, and cover different system boundaries. HIPSTER was created to align the assumptions and boundaries with those of cradle-to-grave life cycle assessment. In FY22, HIPSTER was successfully applied using scenarios from the ReEDS™ model, NREL's flagship capacity expansion model resulting in cradle-to-grace time-series life cycle impacts across LCA midpoints and resource use metrics.

Ghosh, Tapajyoti↗
DOE OSTI2020

Nitrogen derived from Combined Algal Processing supports algae cultivation for biofuels

Algae biomass, a biofuel feedstock with potential to reduce global CO 2 emissions, is currently too expensive Nitrogen, a significant input and life cycle cost, requires research on recycling and additional sources to reduce costs. Integral to nitrogen recycling is the knowledge of actual nitrogen requirements in outdoor ponds, thus data from the Unified Field Studies of the Algae Testbed Public-Private Partnership was analyzed. The data showed that Nannochloropsis oceanica used 14–24 mg/L NH 4 + per harvest cycle for robust growth. Nitrogen recycled directly from the algae conversion process will likely be the primary source of nitrogen for algae cultivation. Harvested algae can be fractionated via Combined Algal Processing (CAP), where algae are pretreated, fermented, and the fuel feedstocks (e. g. ethanol, lipids) are removed leaving a nitrogen rich slurry. Chlorella vulgaris grew robustly in nitrogen-free media supplemented with CAP residues through 4 harvest cycles with no inhibition. The amount of nitrogen as free ammonium available for recycling directly without further processing was insufficient (~4% of total needed), thus the nitrogen fixing bacteria, Azotobacter vinelandii, was investigated as a means for increasing ammonium concentration in CAP residues. This organism was shown to be proficient at growth on sugars liberated from algae biomass during pretreatment and sustained algae growth using A. vinelandii supernatants was also demonstrated. Using Azotobacter to increase ammonium concentrations on-site using an inexpensive biological process to generate the necessary ammonium for outdoor algae cultivation improves sustainability of algae biofuels by avoiding the energy intensive steps of typical ammonium production and transport. Furthermore, these results show that byproducts of algae conversion begin to close nitrogen demand and, with further supplementation by diazotrophic bacteria or protein hydrolysis, may completely replace current energyintensive and costly industrial nitrogen sources offering a path to increased economic feasibility and improved life cycle analysis of algae-based biofuels.

09 BIOMASS FUELS↗
DOE OSTI2021

Bayesian learning for rapid prediction of lithium-ion battery-cycling protocols

Advancing lithium-ion battery technology requires the optimization of cycling protocols. A new data-driven methodology is demonstrated for rapid, accurate prediction of the cycle life obtained by new cycling protocols using a single test lasting only 3 cycles, enabling rapid exploration of cycling protocol design spaces with orders of magnitude reduction in testing time. We achieve this by combining lifetime early prediction with a hierarchical Bayesian model (HBM) to rapidly predict performance distributions without the need for extensive repetitive testing. The methodology is applied to a comprehensive dataset of lithium-iron-phosphate/graphite comprising 29 different fast-charging protocols. HBM alone provides high protocol-lifetime prediction performance, with 6.5% of overall test average percent error, after cycling only one battery to failure. Here, by combining HBM with a battery lifetime prediction model, we achieve a test error of 8.8% using a single 3-cycle test. In addition, the generalizability of the HBM approach is demonstrated for lithium-manganese-cobalt-oxide/graphite cells.

25 ENERGY STORAGE↗
DOE OSTI2023

Quantifying Uncertainty of Deep Reinforcement Learning Based Decision Making for Operations and Maintenance of Nuclear Power Plant

This paper summarizes research that integrates condition monitoring and prognostics with decision making for nuclear power plant operations and maintenance. As part of this research, we have developed an online asset management tool to help reduce life-cycle maintenance and repair costs. Using the latest advancements in condition monitoring, supply chain analytics, and deep reinforcement learning, we have created a predictive maintenance tool that can optimize the maintenance and spare-part management of a repairable nuclear system. To demonstrate these methods, preliminary studies were conducted on a simple, representative maintenance system undergoing a stochastic degradation process that requires repairs or replacement to continue operation. Through Monte Carlo simulations, we were able to reduce maintenance spending by approximately 50% compared to optimized, time-based maintenance strategies. Not only does the decision maker reduce the average life-cycle costs, it also minimizes the chance of high cost scenarios, lowering the variance of the expected cost distributions, and reducing overall financial risk. Furthermore, this work also studies the ability of the decision maker to handle various levels of noise from observation uncertainty. By introducing uncertainty into the decision-making process, we have quantified the robustness and resiliency of the decision maker, as well as identified necessary levels of observability to demonstrate cost effectiveness.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Recent progress in understanding solid electrolyte interphase on lithium metal anode

Lithium (Li) metal batteries (LMBs) are among the most promising candidates of next-generation high-energy-density rechargeable batteries. Solid electrolyte interphase (SEI) on Li metal anode plays a significant role which influences the Li deposition morphology and the cycle life of LMBs. Although SEI is the most important part, a thorough understanding of SEI is inadequate. In this review, we focus on the progresses of understanding on structures, properties and influencing factors of SEI as well as efficient strategies of tailoring SEI. First, the compositions, models and recent progresses on characterizing atomic structure of SEI are summarized. Second, the properties of SEI, including electronic conduction, ionic conduction, stability and mechanical properties are elucidated. Structures and properties of SEI are greatly influenced by multiple factors such as solvent, salt, additive, solvation structure, impurity, current density, temperature, pressure and capacity utilization. Thus, interactions between these factors and SEI are comprehensively discussed. Correlations of SEI with Li deposition morphology, rate capability and cycle life are further summarized. Moreover, efficient strategies of tailoring SEI with desired properties, including in-situ SEI and ex-situ SEI are also reviewed. Despite the significant progresses that have been achieved in the researches of SEI, better understanding of SEI is still highly demand. Finally, future directions especially in-operando techniques, multi-modality approaches for characterization of SEI and artificial intelligence assisted understanding of correlation between electrolyte components and SEI properties are proposed.

Wu, Haiping↗
DOE OSTI2026

Accessing and Understanding REopt's Federal Assumptions

REopt is a techno-economic analysis platform accessible as a user-friendly web tool that facilitates life cycle cost analysis of distributed energy resources. It is typically used for preliminary assessments to identify the least-cost technology mix, system sizing, and operations strategies towards agency cost savings and resilience goals. This guide identifies and explains REopt inputs for federal life cycle cost analyses, modified from their commercial default values. These federal input defaults are based on statutory requirements for life cycle cost analyses of energy conservation measures at federal facilities per 10 CFR 436 Subpart A.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Risk Model for EM Decision Support Toolsets

The Government Office of Accountability (GAO) has published several reports identifying the need for the Department of Energy (DOE) Office of Environmental Management (EM) to address mounting costs for DoE's cleanup program. DOEEM could greatly benefit from independent decision tool-sets/models that would allow them to evaluate options and inform business decision at the enterprise level considering site-specific life cycle costs and system plans. Program goals: Develop a tool-set that enables EM to independently evaluate alternatives, assess outcomes from different contracting strategies, and inform critical decisions for the enterprise. Project goals: Adaption of a Risk Model for integration with complimentary tool-sets for project level decision making. Operational Events: Discrete event model that evaluates operational variables (e.g. capacity, throughput, maintenance constraints) and identify bottlenecks. Identifying and Bounding Project Risk: Identify risks that impact confidence in meeting goals (e.g. production). Life cycle Cost: Evaluate impacts of staffing levels, inventory, and capital investments on life cycle costs. Methods and approach: Monte Carlo Analysis is being executed to generate results: Input derives from Risk Register Data; Tied to Projected and Target Schedules; Incorporates float duration within the model. Assumes associated risk mitigation actions being completed within a timeline of five fiscal years. Metrics include: Confidence in Meeting Production Goal; Confidence in Safety Standards; Confidence in Continuous Operation; Other Metrics can be added as appropriate regarding specific site needs. The adapted risk model can be used as a stand alone decision tool or can be integrated complementary tool-sets (i.e. process and cost models) for project-specific decisions. These support tool-sets can then be integrated with others for site- and complex- level evaluations. Future work includes designing an adaptable and modular framework that would allow integration of multiple tool-sets for holistic and/or targeted evaluation of alternative strategies for decision making that could lead to risk and cost reduction across the enterprise.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Delineating the impact of Ti/Mg substitution in P2-type Na 2/3 Ni 1/3 Mn 2/3 O 2 with an advanced electrolyte for sodium-ion batteries

Sodium layered oxide cathodes are drawing interest globally as a potential alternative to lithium layered oxides, but they suffer from egregious capacity fade and have intrinsically lower capacity. P2-type Na 2/3 Ni 1/3 Mn 2/3 O 2 is a particularly relevant cathode material as it demonstrates an energy density of up to 550 W h kg −1 at high operating potentials, although this can only be maintained for a handful of cycles with industrial electrolytes. Here, a localized saturated electrolyte (LSE) is shown to significantly improve the cycle life of Na 2/3 Ni 1/3 Mn 2/3 O 2 by suppressing the surface reactivity, despite large volume changes during cycling. The demonstrated influence of surface stability on cycle life in this work challenges the prevailing notion of a popular capacity stabilization strategy with titanium/magnesium co-doping, which is primarily thought to improve cycle life via improved structural stability. Single crystals of Na 2/3 Ni 1/3−x Mg x Mn 2/3−2x Ti 2x O 2 (x = 0, 1/48, 1/24, 1/12) materials are cycled with a traditional electrolyte and the LSE to demonstrate that despite eliminating the phase transition with dopants in Na 2/3 Ni 1/4 Mg 1/12 Mn 1/2 Ti 1/6 O 2 , the predominant role of the dopants is in reducing the parasitic oxygen reactivity at the cathode surface. The different roles these dopants play are systematically disambiguated, and this work can guide future research to focus on reducing the parasitic cathode/electrolyte reactivity further.

25 ENERGY STORAGE↗
DOE OSTI2020

Closed-loop optimization of fast-charging protocols for batteries with machine learning

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years. Furthermore, both large parameter spaces and high sampling variability necessitate a large number of experiments. As such, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users. We combine two key elements to reduce the optimization cost: an early-prediction model, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.

25 ENERGY STORAGE↗
DOE OSTI2021

Techno-economic comparison of electrification for heavy-duty trucks in China by 2040

We show that electrification of heavy-duty trucks (HDTs) is critical of achieving sustainability and carbon neutrality in road freight. Based on the total cost of ownership and the life-cycle emissions, the study compared the traditional diesel internal combustion engine vehicle technologies with potential electrification options for HDTs in China, including battery electric vehicle, plug-in hybrid electric vehicle, hydrogen fuel cell vehicle, and battery electric catenary vehicle. Scenario and sensitivity analysis were explored the life-cycle effects of these electrification options in China from 2020 to 2040. It is found that green electricity and green hydrogen are the most important factors influencing the life-cycle emissions of CO 2 , NO X , and PM 2.5 for different HDTs’ electrification options. The plug-in hybrid electric vehicle of HDTs has shown good performance in terms of total cost and carbon emissions, mainly due to the reduced battery capacity and the current grid mix in China.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Complementary Electrolyte Design for Li Metal Batteries in Electric Vehicle Applications

In this report a complementary electrolyte system with 0.8 M lithium bis(fluorosulfonylimide) (LiFSI) salt and 2 wt % lithium perchlorate (LiCLO4) additive in fluoroethylene carbonate (FEC)/ethyl methyl carbonate (EMC) solution enables not only stable cycling of lithium metal batteries (LMBs) with practical loading (<30 μm lithium anode, cathode loading > 4 mAh/cm 2 ) but also outstanding degradation stability toward the end of cycle life when compared to the conventional electrolyte. Although the use of LiFSI salt can increase the electrolyte conductivity and lengthen the cycle life of LMBs, the aged lithium anode morphology formed by the sacrificial decomposition of LiFSI is highly porous, leading to an abrupt cell capacity drop toward the end of cycling. Moreover, the inability to stop aluminum corrosion by the LiFSI-based electrolyte also causes cracking of the cathode tab during prolonged cycling. It is observed that a highly porous aged lithium consumed electrolyte at a higher rate, leading to the dry-out of electrolyte solvents. On the contrary, dense aged lithium anode morphology increased the localized current applied on the lithium, causing the formation of lithium dendrite. Thus, porosity control is the key to enhance battery performance. In this complementary system, LiClO 4 was introduced as an advanced additive to not only improve the capacity retention rate but also mitigate the abrupt capacity drop toward the end of cycle life because LiClO 4 acted as a pore astringent reducing the porosity of the aged lithium metal anode to the desired level. Moreover, the addition of LiClO 4 can also suppress the AI corrosion, allowing stable high-voltage cycling of LMBs. The synergistic effect of combining LiFSI salt and a LiClO 4 additive leads to an electrolyte system that can facilitate the application of high-energy LMBs with practical electrode loading.

25 ENERGY STORAGE↗
DOE OSTI2024

NETL Natural Gas Lifecycle Model

This is the excel-based life cycle model that contains all the parameters and Monte Carlo simulation capabilities to model the techno-regions contained in the report: Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile.

conventional gas↗
DOE OSTI2020

On-Road Heavy-Duty Low-NOx Technology Cost Study

The National Renewable Energy Laboratory (NREL) conducted a cost analysis for emission control technologies under contract to the California Air Resources Board (CARB). CARB sought incremental cost analysis for emission control technologies for on-road heavy-duty (HD) engines, used in vehicle greater than 14,000 pounds (lbs) gross vehicle weight rating (GVWR) to achieve oxides of nitrogen (NOx) emissions rates significantly lower than those required by current emissions standards. Specifically, incremental costs (without any retail price mark-up) were estimated for representative diesel, natural gas, and gasoline engine and emission aftertreatment systems that were selected to represent potential technology packages that could achieve 0.02 grams per brake horsepower hour (g/bhp-hr) NOx on certification test cycles, including a proposed updated certification test cycle that includes additional low load operating conditions. NREL surveyed stakeholders including industry association groups, Tier 1 suppliers, and engine original equipment manufacturers (OEMs) to estimate incremental direct and indirect costs. Incremental costs were considered for current engine full useful life (FUL) definitions, as well as with proposed increased FUL and warranty period. The incremental costs were subsequently incorporated in life-cycle cost analyses examining the incremental engine and aftertreatment costs along with life-cycle costs over the various engine FUL scenarios. Life-cycle costs analysis included the incremental upfront cost, fuel consumption changes (changes in fuel economy), diesel exhaust fluid (DEF) consumption changes, and the maximum FUL of the aftertreatment package (major overhaul intervals).

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Well‐to‐wheels analysis of greenhouse gas emissions for passenger vehicles in Middle East and North Africa

Battery electric vehicles (BEVs) are widely considered a pathway to achieve low carbon mobility. BEVs emit zero emissions from the tailpipe, but their life cycle carbon reduction compared to gasoline vehicles varies based on primary energy sources, electricity generation, and use efficiency. The Middle East and North Africa (MENA) region is an area rich in fossil fuels, meriting a detailed comparison between the emissions from BEV and other powertrains. We developed a MENA‐specific life cycle model that estimates well‐to‐wheel (WTW) greenhouse gas (GHG) emissions from passenger transport with internal combustion engine vehicles (ICEVs), hybrid electric vehicles (HEVs), plug‐in hybrid electric vehicles, and BEVs. MENA's average WTW GHG emissions for all supply chain steps including combustion emissions from vehicle operation are 767 g/kWh and 84 g CO 2 eq/MJ for electricity and gasoline, respectively, but are highly variable due to heterogeneity in upstream supply chains. The use of hybrid gasoline ICEVs provides the largest emission reduction opportunity for existing vehicle fleets in 9 of the 16 MENA countries. For these nine countries, replacing gasoline ICEVs with HEVs could, on average, reduce country‐level life cycle GHG emissions by 47%. There is a similar emission reduction opportunity for 14 of the 16 MENA countries when normalizing vehicle efficiencies irrespective of the powertrain shares and other trends in existing vehicle fleets. Future scenario analysis shows that BEVs would have the lowest WTW GHG emissions among all powertrains in most MENA countries only if significantly reduced electricity transmission losses and cleaner grid mix are realized, although a high cost of infrastructure developments is expected.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗