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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Sensitive Resources Assessment and Forest Analysis for the Proposed Versatile Test Reactor, Oak Ridge, Tennessee

The US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) is a leading institution in advanced materials, supercomputing, neutrons, and nuclear science. As a research laboratory managed by UT-Battelle, LLC for DOE, ORNL has national priorities in energy, security, and scientific discovery that necessitate facility improvements and expansions. DOE is also committed to environmental stewardship. The laboratory is located on the ~32,000-acre (~13,000-ha) Oak Ridge Reservation (ORR), much of which is categorized as a National Environmental Research Park (NERP) and a state Wildlife Management Area. DOE works with the Tennessee Wildlife Resources Agency (TWRA), Tennessee Department of Environment and Conservation (TDEC), US Fish and Wildlife Service (USFWS), US Department of Agriculture, and other agencies to serve as an effective steward of the ORR. Accordingly, project managers must conform to environmental regulations, agreements, and policies at the federal, state, and institutional levels. Per 40 CFR (Code of Federal Regulations) 1508.14, potential effects on research and science education also represent potential effects of federal actions on the NERP, and impacts on, e.g., deer harvest, must be considered on the Oak Ridge Wildlife Management Area when other aspects of the human environment are affected. The United States currently has no fast neutron testing capability to support advanced nuclear research and development. The proposed Versatile Test Reactor (VTR) will take advantage of current investments by the US government and private industry in nuclear reactors to expedite the design and construction process, using proven technology to create a world-class scientific infrastructure. The VTR will take advantage of fast neutrons provided by this proven technology, along with a capability to rapidly insert, conduct, and remove state-of-the-art experiments. An advantage of the VTR is that it can support future innovations in experimental capabilities without modifying the facility. The VTR will support progress in a variety of science and technology areas, including testing and qualification of advanced reactor fuels; testing and qualification of innovative structural materials; testing of innovative components and instruments; validation of advanced modeling and simulation tools; and versatility for future technical missions. Through proven technology, the VTR can take advantage of existing reactor designs and operating experience to reduce the risk, cost, and time for design and construction. The top available resources of DOE laboratories, industry, and universities will be used to expedite reactor design and construction toward developing the scientific infrastructure that affords a strong testing capability that can be sustained over many years. This report summarizes current knowledge of natural and cultural resources primarily within the VTR construction area. At the time of this report, the proposed VTR site design includes a construction area of ~150.4 acres (~69.9 ha), which contains an ~51.3-acre (~20.8-ha) operations area, located within forested natural areas of the ORR. The primary goal of the work presented here was to evaluate potential effects on sensitive resources that might result from development and construction activities associated with VTR. In addition to on-the-ground surveys during spring and summer 2020 by the ORNL Natural Resources Management Program and Aquatic Ecology Group staff, this report makes use of historical (pre-1995) and contemporary (1995 to present) data from additional confirmed sources (e.g., TDEC). Likewise, forest conditions were compiled from a 2011 forest inventory and supplemented with limited ground observations in 2020. The individuals who obtained and compiled the data presented here are familiar with and routinely assess sensitive resources on the ORR. Anyone who references this report must consider that the timing of surveys did not permit a complete delineation of the resources that will be affected. If the VTR project proceeds, additional surveys will be required to account for the seasonal patterns of various threatened and endangered species. Data deficiencies and potential resources that likely went undetected are indicated where possible. Accordingly, this report should facilitate more environmentally sound decisions during planning and 2 development of the VTR site, provide a foundation for further assessment of sensitive and cultural resources, and help project managers better address regulatory guidance and DOE policies on sustainable development in compliance with, for example, the US Endangered Species Act (ESA), Migratory Bird Treaty Act (MBTA), Tennessee Rare Plant Protection and Conservation Act of 1985, Tennessee Nongame and Endangered or Threatened Wildlife Species Conservation Act of 1974, several federal and state regulations regarding aquatic resource protection, and site-specific policies as outlined in various ORR management plans developed by ORNL and TWRA for DOE.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Enhancing Distribution System Resilience: A First-Order Meta-RL Algorithm for Critical Load Restoration

The increasing frequency of extreme events and the integration of distributed energy resources (DERs) into modern grids have elevated the need for resilient and efficient critical load restoration strategies in distribution systems. However, the stochastic nature of renewable DERs, limited energy resource availability and the intricate nonlinearities inherent in complex grid control problem make the problem challenging. Although reinforcement learning (RL) and warm-start RL methods have shown promising results, their performance often falls short in rapidly adapting to new, unseen situations and typically requires exhaustive problem-specific tuning. To address these gaps, we propose a First-Order Meta-based RL (FOM-RL) algorithm within an online framework for adaptive and robust critical load restoration. By harnessing local DERs as the enabling technology, FOM-RL allows the RL agent to swiftly adapt to new unseen scenarios by leveraging previously acquired knowledge of different tasks. Experimental results provide evidence that proposed algorithm learns more efficiently and showcases generalization capabilities across diverse set of operational scenarios. Moreover, a rigorous theoretical analysis yields a tight sublinear regret bound, sensitive to temporal variability, with a task-averaged optimality gap bounded by O(VM+D*/(Tsquare root(M))). These results suggest that optimality improves with task similarity and an increased number of tasks M, reaffirming the efficacy and scalability of the proposed approach in addressing the complexities of critical load restoration in distribution systems.

complexity theory↗
DOE OSTI2018

Optimal blending management of biomass resources used for biochemical conversion

This research develops an optimization model to describe the tradeoff among blend components in the least-cost biomass blend, based on resource availability, quality requirements, and logistics cost for a biochemical conversion. A mixed-integer linear programming model is developed to determine the least-cost blend from a set of candidate feedstocks. A case study – based on a biorefinery located in western Kansas that uses three-pass corn stover, two-pass corn stover, switchgrass, miscanthus, and municipal solid waste fractions to meet biochemical conversion specifications and feedstock demand – shows that the delivered cost of an optimal blend that meets carbohydrate and ash specifications is 12.12% higher than the delivered cost of optimal blend that meets a carbohydrate specification only. The results indicate that a least-cost blend that meets both carbohydrate and ash specifications consists of miscanthus (48.2%) and switchgrass (29.4%) whereas the least-cost blend meeting carbohydrate specification only comprises three-pass corn stover (55.4%) and two-pass corn stover (20.4%). Here an optimal blend uses a low-cost municipal solid waste fraction in all cases, implying that blending could be a potential strategy to reduce delivered feedstock cost.

09 BIOMASS FUELS↗
DOE OSTI2025

Air‐Stable High‐Voltage Li‐Ion Organic Cathode Enabled by Localized High‐Concentration Electrolyte

While lithium‐ion batteries have revolutionized the field of energy storage, their reliance on critical minerals such as cobalt and nickel raises significant concerns over resource availability and supply chain uncertainty. In this study, we revisit dithiin‐fused dilithium naphthazarin (5,8‐dihydroxy‐1,4‐naphthoquinone) (DNP‐Li) as a high‐voltage Li‐ion organic cathode and evaluate its performance in conjunction with localized high‐concentration electrolyte (LHCE). DNP‐Li exhibits remarkable air and thermal stability, a high operating potential of 3.55 V vs. Li + /Li, and a specific capacity of 232 mAh g −1 , positioning it as one of the most promising candidates among Li‐ion organic cathodes. Furthermore, the electrochemical behavior of DNP‐Li is strongly influenced by the electrolyte composition, giving distinct two‐plateau or four‐plateau voltage profiles accompanied by reversible or irreversible phase transitions in carbonate‐based or LHCE electrolyte formulations, respectively. The reduced solubility of DNP‐Li‐based redox intermediates in LHCE enhances cycling stability, achieving a capacity retention of 85% after 50 cycles at 0.1C and 75% after 160 cycles at 0.5C, demonstrating a significant improvement compared to the carbonate‐based electrolyte. This work highlights the critical role of solute–electrolyte interactions in modulating the electrochemical performance of multielectron small‐molecule organic cathodes, offering new pathways for advancing sustainable and high‐efficiency energy storage technologies.

Lakraychi, Alae Eddine [Department of Electrical a↗
DOE OSTI2014

Predicting future coexistence in a North American ant community

Global climate change will remodel ecological communities worldwide. However, as a consequence of biotic interactions, communities may respond to climate change in idiosyncratic ways. This makes predictive models that incorporate biotic interactions necessary. We show how such models can be constructed based on empirical studies in combination with predictions or assumptions regarding the abiotic consequences of climate change. Specifically, we consider a well-studied ant community in North America. First, we use historical data to parameterize a basic model for species coexistence. Using this model, we determine the importance of various factors, including thermal niches, food discovery rates, and food removal rates, to historical species coexistence. We then extend the model to predict how the community will restructure in response to several climate-related changes, such as increased temperature, shifts in species phenology, and altered resource availability. Interestingly, our mechanistic model suggests that increased temperature and shifts in species phenology can have contrasting effects. Nevertheless, for almost all scenarios considered, we find that the most subordinate ant species suffers most as a result of climate change. More generally, our analysis shows that community composition can respond to climate warming in nonintuitive ways. For example, in the context of a community, it is not necessarily the most heatsensitive species that are most at risk. Our results demonstrate how models that account for niche partitioning and interspecific trade-offs among species can be used to predict the likely idiosyncratic responses of local communities to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Distribution of genetic variation underlying adult migration timing in steelhead of the Columbia River basin

Abstract Fish migrations are energetically costly, especially when moving between freshwater and saltwater, but are a viable strategy for Pacific salmon and trout ( Oncorhynchus spp.) due to the advantageous resources available at various life stages. Anadromous steelhead ( O. mykiss ) migrate vast distances and exhibit variation for adult migration phenotypes that have a genetic basis at candidate genes known as greb1L and rock1 . We examined the distribution of genetic variation at 13 candidate markers spanning greb1L , intergenic, and rock1 regions versus 226 neutral markers for 113 populations ( n = 9,471) of steelhead from inland and coastal lineages in the Columbia River. Patterns of population structure with neutral markers reflected genetic similarity by geographic region as demonstrated in previous studies, but candidate markers clustered populations by genetic variation associated with adult migration timing. Mature alleles for late migration had the highest frequency overall in steelhead populations throughout the Columbia River, with only 9 of 113 populations that had a higher frequency of premature alleles for early migration. While a single haplotype block was evident for the coastal lineage, we identified multiple haplotype blocks for the inland lineage. The inland lineage had one haplotype block that corresponded to candidate markers within the greb1L gene and immediately upstream in the intergenic region, and the second block only contained candidate markers from the intergenic region. Haplotype frequencies had similar patterns of geographic distribution as single markers, but there were distinct differences in frequency between the two haplotype blocks for the inland lineage. This may represent multiple recombination events that differed between lineages where phenotypic differences exist between freshwater entry versus arrival timing as indicated by Micheletti et al. (2018a). Redundancy analyses were used to model environmental effects on allelic frequencies of candidate markers, and significant variables were migration distance, temperature, isothermality, and annual precipitation. This study improves our understanding of the spatial distribution of genetic variation underlying adult migration timing in steelhead as well as associated environmental factors and has direct conservation and management implications.

Collins, Erin E.↗
DOE OSTI2023

Engineering Nannochloropsis oceanica for the production of diterpenoid compounds

Abstract Photosynthetic microalgae like Nannochloropsis hold enormous potential as sustainable, light‐driven biofactories for the production of high‐value natural products such as terpenoids. Nannochloropsis oceanica is distinguished as a particularly robust host with extensive genomic and transgenic resources available. Its capacity to grow in wastewater, brackish, and sea waters, coupled with advances in microalgal metabolic engineering, genome editing, and synthetic biology, provides an excellent opportunity. In the present work, we demonstrate how N. oceanica can be engineered to produce the diterpene casbene—an important intermediate in the biosynthesis of pharmacologically relevant macrocyclic diterpenoids. Casbene accumulated after stably expressing and targeting the casbene synthase from Daphne genkwa (DgTPS1) to the algal chloroplast. The engineered strains yielded production titers of up to 0.12 mg g −1 total dry cell weight (DCW) casbene. Heterologous overexpression and chloroplast targeting of two upstream rate‐limiting enzymes in the 2‐C‐methyl‐ d ‐erythritol 4‐phosphate pathway, Coleus forskohlii 1‐deoxy‐ d ‐xylulose‐5‐phosphate synthase and geranylgeranyl diphosphate synthase genes, further enhanced the yield of casbene to a titer up to 1.80 mg g −1 DCW. The results presented here form a basis for further development and production of complex plant diterpenoids in microalgae.

Du, Zhi‐Yan↗
DOE OSTI2016

Reimagining watershed restoration: a call for new investment and support structures for greater resiliency and long‐term impact

Hundreds of locally based watershed initiatives have mobilized stakeholders to take voluntary action to restore the ecological conditions of North America's watersheds. Lead organizations rely on project‐based grant funding, alignment with government programs, and volunteerism to incrementally restore what is ultimately a vast and complex ecosystem. Structurally, the vision and goals of these initiatives often exceed available resources and capacity. In 1999, the Bonneville Environmental Foundation began to test ways by which a funder might increase the capacity of local watershed organizations to achieve long‐term watershed restoration goals through a 10‐year commitment of funding and technical support. We partnered with other funders, collectively seeking solutions to increase the impact of this work. Reflecting on 13 years experience across 21 watersheds in 7 western states ( USA ), we have concluded that the scale of ecological change desired requires a time frame for planning, implementation, and public engagement that is inconsistent with present‐day approaches. This has left us asking how can the capacity and impact of a watershed initiative be sustained over many decades—a time frame that exceeds the tenure of any individual leader, the proven life cycles of many nonprofit organizations, and the commitment of most funders? Clear themes have emerged: (1) engaging diverse stakeholders in planning, (2) orienting the work around broader goals, (3) emphasizing human well‐being, and (4) developing resilient partnerships. Reimagining watershed restoration in this context, we suggest a new agenda for action and research that emphasizes a multidecadal planning horizon integrating climate change projections and changing demographics and social values. WIREs Water 2017, 4:e1174. doi: 10.1002/wat2.1174 This article is categorized under: Water and Life > Conservation, Management, and Awareness Engineering Water > Planning Water Human Water > Water Governance

Warren, Robert F.↗
DOE OSTI2018

Porting DMRG++ Scientific Application to OpenPOWER

With the rapidly changing microprocessor designs and architectural diversity (multi-cores, many-cores, accelerators) for the next generation HPC systems, scientific applications must adapt to the hardware, to exploit the different types of parallelism and resources available in the architecture. To get the benefit of all the in-node hardware threads, it is important to use a single programming model to map and coordinate the available work to the different heterogeneous execution units in the node (e.g., multi-core hardware threads (latency optimized), accelerators (bandwidth optimized), etc.).Our goal is to show that we can manage the node complexity of these systems by using OpenMP for in-node parallelization by exploiting different “programming styles” supported by OpenMP 4.5 to program CPU cores and accelerators. Finding out the suitable programming-style (e.g., SPMD style, multi-level tasks, accelerator programming, nested parallelism, or a combination of these) using the latest features of OpenMP to maximize performance and achieve performance portability across heterogeneous and homogeneous systems is still an open research problem.We developed a mini-application, Kronecker Product (KP), from the original DMRG++ application (sparse matrix algebra) computational motif to experiment with different OpenMP programming styles on an OpenPOWER architecture and present their results in this paper.

Chatterjee, Ronnie↗
DOE OSTI2024

IRIS Reimagined: Advancements in Intelligent Runtime System for Task-Based Programming

Task-based programming models are gaining traction in scientific computing. IRIS is a portable runtime system that exploits multiple heterogeneous programming systems and can discover available resources and manage multiple diverse programming systems (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, and OpenMP) simultaneously. It accounts for the constraints of task dependencies and provides customizable scheduling policies to map those tasks to heterogeneous devices. In this paper, we present new capabilities added to IRIS to improve its portability for heterogeneous programming, build-friendliness, and performance efficiency. The new additions include vendor-specific kernel support, a runtime system with a foreign function interface to eliminate writing wrapper or boilerplate code for heterogeneous kernels, an easy-to-use and configurable CMake-based build environment, automatic and efficient data transfers and orchestration, and the Hunter and DAGGER toolchains to evaluate IRIS’s task scheduling algorithms.

Miniskar, Narasinga Rao↗
DOE OSTI2018

Camelina sativa , an oilseed at the nexus between model system and commercial crop

The rapid assessment of metabolic engineering strategies in plants is aided by crops that provide simple, high throughput transformation systems, a sequenced genome, and the ability to evaluate the resulting plants in field trials. Camelina sativa provides all of these attributes in a robust oilseed platform. The ability to perform field evaluation of Camelina is a useful, and in some studies essential benefit that allows researchers to evaluate how traits perform outside the strictly controlled conditions of a greenhouse. In the field the plants are subjected to higher light intensities, seasonal diurnal variations in temperature and light, competition for nutrients, and watering regimes dictated by natural weather patterns, all which may affect trait performance. There are difficulties associated with the use of Camelina . The current genetic resources available for Camelina pale in comparison to those developed for the model plant Arabidopsis thaliana; however, the sequence similarity of the Arabidopsis and Camelina genomes often allows the use of Arabidopsis as a reference when additional information is needed. Camelina ’s genome, an allohexaploid, is more complex than other model crops, but the diploid inheritance of its three subgenomes is straightforward. The need to navigate three copies of each gene in genome editing or mutagenesis experiments adds some complexity but also provides advantages for gene dosage experiments. In conclusion, the ability to quickly engineer Camelina with novel traits, advance generations, and bulk up homozygous lines for small-scale field tests in less than a year, in our opinion, far outweighs the complexities associated with the crop.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Plant-mediated partner discrimination in ectomycorrhizal mutualisms

Although ectomycorrhizal fungi have well recognized effects on ecological processes ranging from plant community dynamics to carbon cycling rates, it is unclear how actively plants are able to influence the structure of these fungal communities. To address this knowledge gap, we performed two complementary experiments to determine 1) whether ectomycorrhizal plants can discriminate among potential fungal partners, and 2) to what extent the plants might reward better mutualists. In experiment 1, split-root Larix occidentalis seedlings were inoculated with spores from three Suillus species (S. clintonianus, S. grisellus, and S. spectabilis). In experiment 2, we manipulated the symbiotic quality of Suillus brevipes isolates on split-root Pinus muricata seedlings by changing the nitrogen resources available, and used carbon-13 labeling to track host investment in fungi. In experiment 1, we found that hosts can discriminate in multi-species settings. The split-root seedlings inhibited colonization by S. spectabilis whenever another fungus was available, despite similar benefits from all three fungi. In experiment 2, we found that roots and fungi with greater nitrogen supplies received more plant carbon. Furthermore, our results suggest that plants may be able to regulate this symbiosis at a relatively fine scale, and that this regulation can be integrated across spatially separated portions of a root system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Root Characteristics Vary with Depth Across Four Lowland Seasonal Tropical Forests

Fine roots are key to ecosystem-scale nutrient, carbon (C), and water cycling, yet our understanding of fine root trait variation within and among tropical forests, one of Earth’s most C-rich ecosystems, is limited. We characterized root biomass, morphology, nutrient content, and arbuscular mycorrhizal fungal (AMF) colonization to 1.2 m depths across four distinct lowland Panamanian forests, and related root characteristics to soil C stocks. We hypothesized that: (H1) Fine root characteristics vary consistently with depth across seasonal tropical forests, with deeper roots exhibiting more exploratory traits, such as for deep water acquisition; (H2) fine root characteristics vary among tropical forests mainly in surface soils, where resource availability also varies. Here we found consistent variation with depth across the four forests, including decreased root biomass, root tissue density, and AMF, and increased specific root length. Among the forests, there was variation in some fine root characteristics, including greater surface root biomass and lower SRL in the wettest forest, and smaller fine root diameter in the driest forest. We also found that root characteristics were related to total soil C stocks, which were positively related to root biomass and negatively related to specific root length. These results indicate emergent properties of root variation with depth across tropical forests, and show site-scale variation in surface root characteristics. Future work could explore the flexibility in root characteristics under changing conditions such as drought.

13C NMR↗
DOE OSTI2019

Discrete game-theoretic analysis of defense in correlated cyber-physical systems

A cyber-physical system (CPS) is composed of a discrete number of cyber and physical components and subject to internal failures and external disruptions. The functionality of CPS therefore is determined not only by cyber and physical components but the adversary’s attacker strategy. We characterize the effect of cyber-physical interdependency on the CPS survival probability using a product-form function with cyber and physical exponential correlation coefficients. We model simultaneous and sequential discrete games between the provider and attacker on a CPS infrastructure to analyze its survivability and reinforcement strategy at Nash equilibrium. Our results show that the cyber and physical correlation coefficients can significantly affect CPS survival probability. In general, the provider’s cyber- (or physical-) reinforcement level increases as the cyber- (or physical-) attack level increases. In each of cyber and physical domains, the reinforcement level first increases then decreases in its own correlation coefficient, probability of successful component attacks, and maximum level of available resources, but decreases in the correlation coefficient of the other domain. We apply this game-theoretic analysis to a cloud computing infrastructure, and show that its residual capacity is relatively high when the attacker has no information about the distribution of servers. Finally, a high level of survival probability does not necessarily lead to high utility.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Geophysical Constraints on Decarbonized Systems—Building Spatio-Temporal Uncertainties into Future Electricity Grid Planning

Future electricity grids will be characterized by the high penetration of renewables to support the decarbonization process. Yet, this transition will further expose grids to a broad spectrum of geophysical forces, such as weather and climate, land and space, minerals and materials. Understanding their role is thus important to support the grid decarbonization process. Here, we synthesize the current body of knowledge on the relationship between geophysical constraints and electricity grid planning. Additionally, we show that there have been promising advances in the data, methods, and modelling tools needed to incorporate the effect of geophysical constraints on demand, resource availability, and grid operations. There are, however, multiple research avenues that deserve further attention. More system-specific and finer-scale analyses are necessary to better understand how spatio-temporal variability---and associated uncertainty---in geophysical forces affect grid planning. Moreover, we need a broader focus on the multi-sectoral implications of grid decarbonization efforts, so as to limit the risk of unintended consequences. Importantly, all these efforts are challenged by the computational requirements of existing power system models, which often limit our ability to characterize uncertainty, scale analyses across larger domains, or study the multi-sector implications of grid expansion decisions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Gaussian interferometric power and Black box estimation of Unruh temperature

We present a black box estimation paradigm of Unruh temperature in a relativistic bosonic continuous-variable setting. It is shown that the guaranteed precision for the estimation of Unruh temperature can be evaluated by the Gaussian interferometric power for a given probe state. We demonstrate that the amount of interferometric power is always beyond the entanglement type quantum correlations in a relativistic setting. It is found that due to the fact that Unruh radiation acts as a thermal bath on the probe system, it destroys available resources of the probe system and reduces the guaranteed precision of the estimation of Unruh temperature. We also find that the thermal noise induced by Unruh effect will generate interferometric power between accelerated Bob and his auxiliary partner anti-Bob, while it does not generate any correlation between inertial Alice and anti-Bob.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Decarbonization scenarios of the U.S. Electricity system and their costs

Decarbonizing the electricity system to zero-carbon emission is crucial for climate change mitigation. Previous studies have shown that such a transition in the United States (U.S.) may lead to higher system cost compared to a business-as-usual case, but it is not well-known how the cost of electricity generation varies at sub-regional level under the transition, and studies have rarely evaluated the trade-off between the cost and avoided climate damages, as well as the potential roles of negative emission technologies (NETs) in the electricity decarbonization. In this work, we present a regionally resolved national model to quantify the cost of decarbonizing the U.S. electricity system under a set of possible scenarios. The results show that, compared to the reference scenario without a decarbonization policy, reaching zero CO 2 emission by 2050 would incur, depending on the scenarios, 335-494 billion USD additional cost to the U.S. electric power sector during 2020-2050. The regional costs of electricity generation ranges from 2.4 to 4.7 cent/kWh, largely due to the generation profiles and renewable resources availability of those regions. The additional costs can be translated to an average CO 2 abatement cost of 29-59 USD/metric ton CO 2 (with 2%-7% discount rates), which are comparable to the social cost of carbon in the literature at around 4% discount rate. The results also show that the cost of mitigating the last few percent CO 2 emission from the U.S. electricity system may exceed the costs of NETs, indicating an opportunity for NETs to contribute to electricity decarbonization.

24 POWER TRANSMISSION AND DISTRIBUTION↗