Economic and sustainability prospects for wet waste valorization: The case for sustainable aviation fuel from arrested anaerobic digestion
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As a primary federal investigation of the utility of transmission to support offshore wind emergence in the Western Interconnect, the West Coast Offshore Wind Transmission study evaluates five distinct West Coast-wide transmission scenarios and trades the economic benefits and costs of six development pathways from 2035 to 2050. In this time, 33 GW of OSW generation and supporting transmission are explored within the context of 350 additional GW of generation to support 100% clean electricity. Geospatial analysis informed plausible transmission topologies and cost estimates. All pathways to intraregional or interregional coordination transmission builds showed more than $\$$14 billion in present value cost savings, with a maximum of $\$$25 billion of savings in the interregional case. These savings are primarily driven by fuel costs and increased availability of power flows enabled by new transmission networks. Key considerations of clean, dispatchable generation options, geographic disaggregation of costs, system reliability reinforcements, resilience, and community values are also presented and discussed.
The Standard Energy Efficiency Data (SEED) and Building Efficiency Targeting Tool for Energy Retrofits (BETTER) platforms are both developed by the Department of Energy and work better together. SEED is a database to manage building characteristics and performance data from a variety of sources. BETTER provides simple energy efficiency measure analyses based on high level data about the building or portfolio of buildings. A demonstration of each platform and their integration will be provided. The inputs for BETTER are building type, floor area, location, utility data, and whether PV shall be included in the analysis. The BETTER analysis can be manually set up through the web application or data can be uploaded with a BuildingSync XML file either directly or through the API. SEED can be the source of this data and the data can be sent to BETTER through the SEED application after the BETTER API token has been entered. The benefit of utilizing SEED is that it has connections to many other sources of data such as ENERGY STAR Portfolio Manager, Audit Template, and Salesforce. Therefore, it is likely that a user of SEED will already have the required inputs for BETTER in SEED already and can create BETTER analyses across their whole portfolio in a couple mouse clicks. This is a major time savings and enables decision makers an easy path to identify buildings that should undergo more detailed audits or retrofit pathways.
Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.
This presentation was given in response to an invitation to NREL to contribute to a conference session titled: "From Farm to Sky: Sustainable Aviation Fuel." I overview the basics of Sustainable Aviation Fuel, including reviewing the SAF Grand Challenge, feedstock availability (especially agriculture-relevant feedstocks), the importance of SAF for decarbonizing aviation, life cycle analysis and sustainability, necessary SAF properties, ASTM-approved pathways, SAF synthesis processes in current practice, and broader positive impacts of SAF.
Significance Photosynthesis metabolites are quickly labeled when 13 CO 2 is fed to leaves, but the time course of labeling reveals additional contributing processes involved in the metabolic dynamics of photosynthesis. The existence of three such processes is demonstrated, and a metabolic flux model is developed to explore and characterize them. The model is consistent with a slow return of carbon from cytosolic and vacuolar sugars into the Calvin–Benson cycle through the oxidative pentose phosphate pathway. Our results provide insight into how carbon assimilation is integrated into the metabolic network of photosynthetic cells with implications for global carbon fluxes.
Abstract Background The oleaginous yeast Rhodotorula toruloides is a promising chassis organism for the biomanufacturing of value-added bioproducts. It can accumulate lipids at a high fraction of biomass. However, metabolic engineering efforts in this organism have progressed at a slower pace than those in more extensively studied yeasts. Few studies have investigated the lipid accumulation phenotype exhibited by R. toruloides under nitrogen limitation conditions. Consequently, there have been only a few studies exploiting the lipid metabolism for higher product titers. Results We performed a multi-omic investigation of the lipid accumulation phenotype under nitrogen limitation. Specifically, we performed comparative transcriptomic and lipidomic analysis of the oleaginous yeast under nitrogen-sufficient and nitrogen deficient conditions. Clustering analysis of transcriptomic data was used to identify the growth phase where nitrogen-deficient cultures diverged from the baseline conditions. Independently, lipidomic data was used to identify that lipid fractions shifted from mostly phospholipids to mostly storage lipids under the nitrogen-deficient phenotype. Through an integrative lens of transcriptomic and lipidomic analysis, we discovered that R. toruloides undergoes lipid remodeling during nitrogen limitation, wherein the pool of phospholipids gets remodeled to mostly storage lipids. We identify specific mRNAs and pathways that are strongly correlated with an increase in lipid levels, thus identifying putative targets for engineering greater lipid accumulation in R. toruloides . One surprising pathway identified was related to inositol phosphate metabolism, suggesting further inquiry into its role in lipid accumulation. Conclusions Integrative analysis identified the specific biosynthetic pathways that are differentially regulated during lipid remodeling. This insight into the mechanisms of lipid accumulation can lead to the success of future metabolic engineering strategies for overproduction of oleochemicals.
Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determine cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA) that relies on the patterns of isotope labeling of metabolites in the network. For metabolic systems, typical for plants, where all potentially labeled atoms effectively have only one source atom pool, only isotopically nonstationary MFA can provide information about intracellular fluxes. There are several global approaches that implement MFA for an entire metabolic network and estimate, at once, a steady-state flux distribution for all reactions with identifiable fluxes in the network. In contrast, local approaches deal with estimation of fluxes for a subset of reactions, with smaller data demand for flux estimation. Here we present a systematic comparative review and benchmarking of the existing local approaches for isotopically nonstationary MFA. The comparison is conducted with respect to the required data and underlying computational problems solved on a synthetic network example. Furthermore, we benchmark the performance of these approaches in estimating fluxes for a subset of reactions using data obtained from the simulation of nitrogen fluxes in the Arabidopsis thaliana core metabolism. The findings pinpoint practical aspects that need to be considered when applying local approaches for flux estimation in large-scale plant metabolic networks.
We investigate the two- and three-body fragmentation of tribromomethane (bromoform, CHBr 3 ) resulting from multiple ionization by 28-femtosecond near-infrared laser pulses with a peak intensity of 6 × 10 14 W cm -2 . The analysis focuses on channels consisting exclusively of ionic fragments, which are measured by coincidence momentum imaging. The dominant two-body fragmentation channel is found to be Br + + CHBr 2 +. Weaker HBr + + CBr 2 +, CHBr + + Br 2 +, CHBr 2+ + Br 2 +, and Br + + CHBr 2 2+ channels, some of which require bond rearrangement prior to or during the fragmentation, are also observed. The dominant three-body fragmentation channel is found to be Br + + Br + + CHBr + . This channel includes both concerted and sequential fragmentation pathways, which we identify using the native frames analysis method. We compare the measured kinetic energy release and momentum correlations with the results of classical Coulomb explosion simulations and discuss the possible isomerization of CHBr 3 to BrCHBr–Br (iso-CHBr 3 ) prior to the fragmentation.
Background: Hypertrophic cardiomyopathy (HCM) is a complex disease partly explained by the effects of individual gene variants on sarcomeric protein biomechanics. At the cellular level, HCM mutations most commonly enhance force production, leading to higher energy demands. Despite significant advances in elucidating sarcomeric structure–function relationships, there is still much to be learned about the mechanisms that link altered cardiac energetics to HCM phenotypes. Here, we test the hypothesis that changes in cardiac energetics represent a common pathophysiologic pathway in HCM. Methods: We performed a comprehensive multiomics profile of the molecular (transcripts, metabolites, and complex lipids), ultrastructural, and functional components of HCM energetics using myocardial samples from 27 HCM patients and 13 normal controls (donor hearts). Results: Integrated omics analysis revealed alterations in a wide array of biochemical pathways with major dysregulation in fatty acid metabolism, reduction of acylcarnitines, and accumulation of free fatty acids. HCM hearts showed evidence of global energetic decompensation manifested by a decrease in high energy phosphate metabolites (ATP, ADP, and phosphocreatine) and a reduction in mitochondrial genes involved in creatine kinase and ATP synthesis. Accompanying these metabolic derangements, electron microscopy showed an increased fraction of severely damaged mitochondria with reduced cristae density, coinciding with reduced citrate synthase activity and mitochondrial oxidative respiration. These mitochondrial abnormalities were associated with elevated reactive oxygen species and reduced antioxidant defenses. However, despite significant mitochondrial injury, HCM hearts failed to upregulate mitophagic clearance. Conclusions: Overall, our findings suggest that perturbed metabolic signaling and mitochondrial dysfunction are common pathogenic mechanisms in patients with HCM. These results highlight potential new drug targets for attenuation of the clinical disease through improving metabolic function and reducing mitochondrial injury.
Spaceflight has several detrimental effects on the physiology of astronauts, many of which are recapitulated in rodent models. We analyzed liver transcriptomic and proteomic data from three mouse spaceflight experiments flown aboard the International Space Station (Rodent Research-1 NASA (RR-1 NASA), Rodent Research-1 CASIS (RR-1 CASIS), Rodent Research-3 (RR-3)), and one mouse experiment flown on the Space Shuttle (Commercial Biomedical Testing Module-3 (CBTM-3) aboard STS-135). Despite the differences in genetic background and time of exposure to microgravity it was shown through Oil Red staining and histology that increased lipid accumulation was occurring in the liver of all mice flown in space compared to the ground controls. This led to further pursue the existing GeneLab datasets related to liver omics data from these mice. We were able to discover key conserved pathways across all the mice independent of the flight conditions that were related to increased lipid metabolism, fatty acid metabolism, both lipid and fatty acid processing, lipid catabolic processing, and lipid localization. In addition, key upstream regulators were predicted to be commonly regulated across all conditions which include ESR1, GCG, and NR1I2 being inhibited and INS being activated. Interestingly, estrogen receptor alpha (ESR1) expression has been known to be heavily involved with lipoprotein metabolism. In addition, insulin (INS) is the primary driver for fat metabolism and increased INS has been associated with increased fatty acids in the liver. Through additional proteomic analysis we were able to identify the majority of the key proteins related to lipids for both the RR-1 and RR-3 rodents were being up-regulated in the livers when comparing flight to ground controls. This additional confirmation of the lipid associated activity also showed that the lipid related proteins are heavily involved with lipid metabolism, cholesterol binding, and cholesterol metabolism. Lastly, the analysis also revealed that the circadian clock related pathways in the liver are commonly being increased across all space flight conditions which has also been reported in the literature to potentially cause increased liver damage. The combination of the very strong lipid uptake in the liver and the transcriptomic/proteomic signatures (including the circadian clock pathways) following spaceflight are consistent with early onset of liver disease. Taken together, these data indicate that, activation of lipotoxic pathways could persist during longer duration spaceflight which might result in the development of liver disease
Datasets supporting findings and visualization behind Okoye and McManamay (2025) Extending Shared Socioeconomic Pathways to Future Water Supply Infrastructure Scenarios: A Case Study of San Antonio, TX. Environmental Research Communications, DOI: 10.57931/2563186 These datasets contains the results of a site selection analysis for municipal water supply planning across multiple Shared Socioeconomic Pathways (SSPs 1–5) and hard scenario classification of water systems in San Antonio, TX. It includes data at the resolution of individual surface water supply sources (COMIDs) and integrates a wide range of hydrologic, socioeconomic, infrastructural, and scenario-based planning variables. Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions: Dataset_SSP1_SSP4.xlsx - Contains data used for site selection optimization under SSP1 to SSP4. This dataset was generated based on multi-indicator computations (e.g., WAI, WQI, ERI, WTC, WIC), scenario demand projections, and resource and spatial constraints, excluding new reservoir values. Dataset_SSP5.xlsx - Used for site optimization under SSP5. Unlike Dataset_SSP1_SSP4, this dataset includes new reservoir features with updated calculations of WAI, WTC, and WIC to reflect the added infrastructure and supply potential. hard_classification.xlsx - Provides the scenario classification output for each site. Includes both the initial scenario classification based on Euclidean Distance and adjusted classifications based on 30% change reduction BAU.zip - Zipped folder of .shp files showing spatially optimized water supply sites per SSP under the Business-As-Usual (BAU) water demand strategy LowGW.zip - Zipped folder of .shp files showing optimized site selections under the Low Groundwater strategy
The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.
The 2021 state of technology (SOT) assessment for the indirect liquefaction (IDL) of lignocellulosic biomass to high-octane gasoline (HOG) via methanol and dimethyl ether (DME) intermediates details the techno-economic analysis (TEA) results and technical progress of the pathway since the 2020 SOT report. A detailed process description and collection of underlying assumptions is given the 2015 design report. In 2021, research efforts rigorously quantified the selectivity of DME to aromatic compounds. As a result, the overall carbon selectivity to hydrocarbon products was updated based upon new findings. Additionally, research conducted over the past few years resulted in successful lower temperature regeneration of NREL's Cu/BEA catalyst with favorable implications on catalyst longevity. Discussions with an engineering firm resulted in an update to the excess air requirement for process combustors (including the char combustor, tar reformer combustor, and catalyst regenerator) in which excess air was reduced from 20% excess to 10%. The cumulative effect of the above efforts was used to calculate a minimum fuel selling price for the modeled pathway. Sensitivity cases examining federal carbon tax credits from CO 2 capture, product selectivity and yield, catalyst lifetime, and other key financial and process parameters were also considered in this assessment.
This study presents a cradle-to-grave life cycle analysis (LCA) of the greenhouse gas (GHG) emissions of the electricity generated from forest biomass in different regions of the United States (U.S.), taking into consideration regional variations in biomass availabilities and logistics. The regional biomass supply for a 20 MW bioelectricity facility is estimated using the Land Use and Resource Allocation (LURA) model. Results from LURA and data on regional forest management, harvesting, and processing are incorporated into the GHGs, Regulated Emissions, and Energy Use in Technologies (GREET) model for LCA. The results suggest that GHG emissions of mill residues-based pathways can be 15-52% lower than those of pulpwood-based pathways, with logging residues falling in between. Nonetheless, our analysis suggests that screening bioenergy projects on specific feedstock types alone is not sufficient because GHG emissions of a pulpwood-based pathway in one state can be lower than those of a mill residue-based pathway in another state. Furthermore, the available biomass supply often consists of several woody feedstocks, and its composition is region-dependent. Forest biomass-derived electricity is associated with 86-93% lower life-cycle GHG emissions than the emissions of the average grid electricity in the U.S. Key factors driving bioelectricity GHG emissions include electricity generation efficiency, transportation distance, and energy use for biomass harvesting and processing.
Powder metallurgy (PM)–hot isostatic pressing (PM-HIP) has long been recognized as a powerful route for producing fully dense, near net shape metallic components. By consolidating powders under high temperature and pressure, HIP provides isotropic properties, uniform microstructures, and scalability to complex geometries that are vital for sectors such as aerospace, energy, and nuclear power. Yet despite these advantages, the technology has remained constrained by costly trial and error canister fabrication, limitations of conventional forging, and incomplete knowledge about how the canister design influences final part properties. Additive manufacturing (AM), by contrast, thrives on design freedom and geometric flexibility but struggles with speed, scalability, and cost when applied to very large structures. The research presented in this report investigated how a convergent manufacturing approach, combining AM with PM-HIP, can merge the strengths of both technologies, leveraging AM’s flexibility for canister design and HIP’s consolidation capability to deliver reliable, large, and complex parts. The work progressed through three case studies that built on one another in scale and complexity. Small cylindrical canisters fabricated by conventional methods, laser powder bed fusion, and directed energy deposition were filled with stainless steel powders and subjected to HIP. The resulting parts demonstrated near-full density and mechanical properties on par with wrought stainless steel, showing for the first time that AM canisters can be a direct substitute for conventional ones without sacrificing quality. The next step involved a medium-scale, noncentrosymmetric T-valve, which is an enclosed, multibranch geometry that tested the limits of AM + PM-HIP integration. The T-valve achieved predictable shrinkage and uniform densification, confirming feasibility for enclosed designs. However, this study also revealed oxide inclusions and interfacial challenges at the AM + HIP boundary, underscoring the critical importance of controlling interface chemistry and employing robust, in situ strategies, such as melt pool monitoring and thermal monitoring, coupled with nondestructive evaluation techniques such as x-ray computed tomography. Finally, the effort culminated in fabricating a large-scale impeller weighing nearly 2000 lb and spanning 5 ft in diameter. Produced via multirobot wire arc AM and hot isostatic pressed to near-full density, the impeller validated industrial-scale feasibility. Predictive models closely matched experimental shrinkage, tensile properties were spatially uniform across the component, and the AM + PM-HIP interface proved mechanically sound despite the presence of oxide-decorated prior particle boundaries. This large-scale demonstration is a major milestone, showing that hybrid AM + PM‑HIP can reliably deliver components at reactor-relevant scales. Collectively, these studies charted a logical pathway: small-scale work built scientific confidence, medium-scale work highlighted opportunities and challenges, and large-scale work proved industrial impact. The overarching conclusion of this report is that AM + PM-HIP should not be seen as a replacement for forging but as a complementary pathway that provides the US with flexibility, resilience, and new options for manufacturing nuclear-grade components. Looking ahead, several directions emerge as critical to sustaining progress. Predictive modeling must become faster, more accessible, and more accurate, with digital twins and machine learning reducing reliance on trial and error. Powders and alloys must be optimized for HIP, with improved cleanliness, reduced oxides, and tailored chemistries that enhance creep, fatigue, and irradiation resistance. Interfaces between AM and HIP regions must be better engineered through coatings, machining strategies, and surface treatments to mitigate oxide formation and ensure reliable bonding to explore opportunities for HIP of targeted compositional parts, as well as multimaterial HIP cladding applications. Monitoring and nondestructive evaluation need to expand, incorporating multimodal sensors, x-ray computed tomography, and real-time data integration through platforms such as Pelican. At the same time, the pathway to industrial adoption requires techno-economic analysis, machinability studies, and qualification frameworks aligned with industry and regulatory standards. Finally, workforce and academic engagement must be strengthened. Programs that train technicians and engineers for US Navy and US Department of Energy manufacturing challenges should be paired with academic partnerships to support fundamental research, with open sharing of non-export-controlled data to accelerate innovation and build the next generation of experts. In conclusion, this report demonstrates that hybrid AM + PM-HIP is scientifically viable and strategically important. By combining the design agility of AM with the consolidation strength of HIP and embedding modeling, monitoring, and workforce development, this approach provided a transformative new capability for US manufacturing. The path forward is clear: hybrid AM + PM-HIP is not just a promising research direction but is also potentially an industrially relevant pathway that can reshape how nuclear-grade components are designed, qualified, and deployed.
Energy system projections from analytic models inform actions ranging from short-term and local decisions, such as technology and infrastructure deployment, to global and long-term negotiations and targets. Computational limits require the designers of these models to trade off between coverage and resolution. Some models, such as the Global Change Analysis Model (GCAM), represent all energy sources and uses but at a relatively coarse level of resolution. GCAM balances global supply and demand of all energy carriers by endogenously projecting prices for energy sources and costs of greenhouse gas mitigation while capturing interlinkages between the energy system, water, agriculture and land use, the economy, and the climate. This global model was used to frame the Long-Term Strategy released by the White House in 2021 and has been used to inform national and global economy-wide decarbonization discussions and strategy development for decades. Other models instead focus on a portion of the energy sector with greater detail and resolution. The Regional Energy Deployment System (ReEDS) electricity-sector model, for example, projects capacity expansion with an emphasis on integration of variable renewable energy into the grid of the future. The Transportation Energy and Mobility Pathway Options (TEMPO) transportation-sector model enables analysis of household choices in adoption, charging, and use of electric vehicles. The Scout buildings-sector model supports detailed consideration of the policies and markets that can accelerate the adoption of energy conservation measures in buildings. Such sector-specific models are instrumental in informing technology research, sectoral planning strategies, and sector-specific aspects of greenhouse gas (GHG) mitigation strategies in the United States. These global and sector-specific modeling approaches can complement each other. The global approach ensures consistent, endogenous energy pricing and resource allocation, which can substantially diverge from current conditions in transformative scenarios, while the sector-specific approach facilitates representation of granular details across spatial, temporal, technological, and market dimensions that enable exploration of particular interactions and trade-offs. This report presents the results of recent work to explore the differences and tradeoffs between these approaches by comparing GCAM with the sector-specific ReEDS, TEMPO, and Scout models. The report compares both model structures and results, and discusses their potential relevance and applications.
The sustainable generation of biodegradable plastics represents an opportunity to capture atmospheric CO 2 while reducing plastic waste accumulation in the environment. This study implements an integrated platform for bioelectrocatalytic CO 2 conversion to medium-chain-length polyhydroxyalkanoates (mcl-PHAs). Immobilizing cobalt phthalocyanine electrocatalysts on a covalent-organic framework in a gas recirculation electrolyzer enabled CO 2 -to-methanol conversion with a carbon conversion efficiency of 98%. Integration of polymer biosynthesis pathways enabled Methylotuvimicrobium alcaliphilum 20Z R to produce ~20% mcl-PHA of the dry cell weight with a CO 2 -to-bioproducts carbon conversion efficiency of 50%. This cell line was adapted to high sodium bicarbonate media, eliminating costly intermediate separation steps while improving economic potential. Transcriptomic analysis revealed sulfate transporters and peptidoglycan biosynthesis as key pathways involved in sodium bicarbonate halotolerance. Altogether, this research presents a foundation for integrating divergent chemical and biological processes into a transformative electrobiomanufacturing platform, addressing the need for alternative pipelines for generating valuable plastics and chemicals.