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DOE OSTI2017

Process Design and Techno-economic Analysis for Materials to Treat Produced Waters

Significant quantities of water are produced during enhanced oil recovery making these “produced water” streams attractive candidates for treatment and reuse. However, high concentrations of dissolved silica raise the propensity for fouling. In this paper, we report the design and economic analysis for a new ion exchange process using calcined hydrotalcite (HTC) to remove silica from water. This process improves upon known technologies by minimizing sludge product, reducing process fouling, and lowering energy use. Process modeling outputs included raw material requirements, energy use, and the minimum water treatment price (MWTP). Monte Carlo simulations quantified the impact of uncertainty and variability in process inputs on MWTP. These analyses showed that cost can be significantly reduced if the HTC materials are optimized. Specifically, R&D improving HTC reusability, silica binding capacity, and raw material price can reduce MWTP by 40%, 13%, and 20%, respectively. Optimizing geographic deployment further improves cost competitiveness.

04 OIL SHALES AND TAR SANDS↗

DOE OSTI2020

Ethanol as a Renewable Building Block for Fuels and Chemicals

Three factors, i) the ethanol “blend wall”, which limits its market as a transportation fuel, ii) advances in production efficiency, and iii) feedstock diversification, could lead to excess ethanol at competitive prices. Those factors have already motivated a search for value-added derivatives (e.g., distillate fuels, olefins, and asymmetric amines). Siting small, low cost, flexible conversion facilities to process ethanol at or near the fermentation plant could encourage the growth of an enterprise. Decreasing the barriers to entry, matching supply and demand, and enhancing access to production incentives are enabling success factors. This review discusses the process chemistries that might be employed by such ethanol conversion facilities based on market prices. Finally, how these technologies might benefit from process intensification, and without the requirement of complex processing or large pressures or temperature gradients typically employed in conventional, large scale facilities.

09 BIOMASS FUELS↗

DOE OSTI2021

Evaluating the Case for Reduced Precious Metal Catalysts in Proton Exchange Membrane Electrolyzers

Proton exchange membrane (PEM) water electrolyzers are a key technology in decarbonizing hydrogen production. Though the market for PEM electrolyzer systems is growing, there are concerns that the cost and availability of precious metal catalysts utilized in today’s commercial systems can limit deployment. Herein, we show that while the availability of Ir should not impede deployment in the near term, the inelasticity of the Ir commodity price is cause for immediate concern. Here we emphasize that diversifying catalyst materials, even with other precious metals, can reduce system costs and mitigate supply chain risk. Furthermore, we analyze the trade-offs between catalyst capital cost and catalyst activity for a range of operating conditions (i.e., capacity factor, electricity price). The framework presented herein is a first step toward establishing performance targets (i.e., activity, stability, material cost) for reduced precious metal and non-precious metal catalysts as a function of PEM electrolyzer operating conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Characterizing the Potential for Sustainable Azelaic Acid Production from High-Oleic Vegetable Oil Using Two-Step Oxidative Cleavage

Azelaic acid is a renewable monomer conventionally produced via the energy-intensive ozonolysis of oleic acid. Recent advancements have enabled the use of high-oleic vegetable oils (rather than tallow-derived oleic acid) and replaced ozonolysis with two-step oxidative cleavage using hydrogen and oxygen. Although this shift would improve process safety, the financial viability and environmental implications remain uncertain. In this study, we characterized the sustainability of azelaic acid production from high-oleic vegetable oil using two-step oxidative cleavage. Process design, simulation, technoeconomic analysis (TEA), and life cycle assessment (LCA) were executed under uncertainty using BioSTEAM. The modeled system produces azelaic acid at a market-competitive minimum selling price (MSP) of 8.32 [4.93−13.34] $\$kg$ −1 (median 5th−95th percentiles), below the minimum estimated market price of 9.93 $\$kg$ −1 . Further, it has the potential to approach carbon neutrality (0.0 [−5.5 to 5.6] kg of CO 2 -eq kg −1 ) under displacement allocation. Improvements to dihydroxylation (86 to 99%) and oxidative cleavage conversions (93 to 99%) would reduce MSP to $\$5.24$ kg −1 and carbon intensity to −1.90 kg of CO 2 -eq kg −1 (displacement). Additionally, increasing the feedstock triolein content (75 to 85%) lowers MSP by $\$0.82$ kg −1 . Overall, this research demonstrates the potential for financially viable production of azelaic acid from vegetable oils and the utility of agile TEA/LCA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

High-Efficiency Conversion of Ionic Liquid-Pretreated Woody Biomass to Ethanol at the Pilot Scale

We report that with a diverse and widely distributed global resource base, woody biomass is a compelling organic feedstock for conversion to renewable liquid fuels. In California, woody biomass comprises the largest fraction of underutilized biomass available for biofuel production, but conversion to fuels is challenged both by recalcitrance to deconstruction and by toxicity toward downstream saccharification and fermentation due to organic acids and phenolic compounds generated during pretreatment. In this study, we optimize pretreatment and scale-up of an integrated one-pot process for deconstruction of California woody biomass using the ionic liquid (IL) cholinium lysinate [Ch][Lys] as a pretreatment solvent. By evaluating the impact of solid loading, solid removal, yeast acclimatization, fermentation temperature, fermentation pH, and nutrient supplementation on final ethanol yields and titers, we achieve nearly full conversion of both glucose and xylose to ethanol with commercial C5-utilizing Saccharomyces cerevisiae. We then demonstrate process scalability in 680 L pilot-scale fermentation, achieving >80% deconstruction efficiency, >90% fermentation efficiency, 27.7 g/L ethanol titer, and >80% ethanol distillation efficiency from the IL-containing hydrolysate post fermentation. This fully integrated process requires no intermediate separations and no intermediate detoxification of the hydrolysate. Using an integrated biorefinery model, current performance results in a minimum ethanol selling price of $\$$8.8/gge. Reducing enzyme loading along with other minor process improvements can reduce the ethanol selling price to $\$$3/gge. This study is the largest scale demonstration of IL pretreatment and biofuel conversion known to date, and the overall biomass-to-ethanol efficiencies are the highest reported to date for any IL-based biomass-to-biofuel conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Techno-Economic Basis for Coproduct Manufacturing To Enable Hydrocarbon Fuel Production from Lignocellulosic Biomass

Biorefinery process development relies on techno-economic analysis (TEA) to identify primary cost drivers, prioritize research directions, and mitigate technical risk for scale-up through development of detailed process designs. Here, we conduct TEA of a model 2000 dry metric ton-per-day lignocellulosic biorefinery that employs a two-step pretreatment and enzymatic hydrolysis to produce biomass-derived sugars, followed by biological lipid production, lipid recovery, and catalytic hydrotreating to produce renewable diesel blendstock (RDB). On the basis of projected near-term technical feasibility of these steps, we predict that RDB could be produced at a minimum fuel selling price (MFSP) of USD $9.55/gasoline-gallon-equivalent (GGE), predicated on the need for improvements in the lipid productivity and yield beyond current benchmark performance. This cost is significant given the limitations in scale and high costs for aerobic cultivation of oleaginous microbes and subsequent lipid extraction/recovery. In light of this predicted cost, we developed an alternative pathway which demonstrates that RDB costs could be substantially reduced in the near term if upgradeable fractions of biomass, in this case hemicellulose-derived sugars, are diverted to coproducts of sufficient value and market size; here, we use succinic acid as an example coproduct. The coproduction model predicts an MFSP of USD $5.28/GGE when leaving conversion and yield parameters unchanged for the fuel production pathway, leading to a change in biorefinery RDB capacity from 24 to 15 MM GGE/year and 0.13 MM tons of succinic acid per year. Additional analysis demonstrates that beyond the near-term projections assumed in the models here, further reductions in the MFSP toward $2-3/GGE (which would be competitive with fossil-based hydrocarbon fuels) are possible with additional transformational improvements in the fuel and coproduct trains, especially in terms of carbon efficiency to both fuels and coproducts, recovery and purification of fuels and coproducts, and coproduct selection and price. Overall, this analysis documents potential economics for both a hydrocarbon fuel and bioproduct process pathway and highlights prioritized research directions beyond the current benchmark to enable hydrocarbon fuel production via an oleaginous microbial platform with simultaneous coproduct manufacturing from lignocellulosic biomass.

09 BIOMASS FUELS↗

DOE OSTI2019

Strategies to Valorize the Hydrothermal Liquefaction-Derived Aqueous Phase into Fuels and Chemicals

Valorization options for the aqueous fraction produced by the hydrothermal liquefaction of terrestrial feedstocks were developed. The processes focused on carboxylic acids, which are abundant in the aqueous fraction. A clean up process for the aqueous phase based on activated carbon absorption followed by liquid-liquid extraction was demonstrated that significantly reduces color bodies and inorganic contaminants while simultaneously concentrating desirable organic constituents. Conversion of the cleaned aqueous phase was then demonstrated for both a ketonization reaction and steam reforming. Condensed phase ketonization over LaxZryOz catalyst was found to exhibit both excellent hydrothermal stability and ketonization activity. Necessity for feedstock cleanup was established and stable condensed phase ketonization operation was demonstrated for ~100 hours with HTL-process derived material. Steam reforming was also demonstrated by employing a dual-bed catalyst configuration whereby carboxylic acids first undergo ketonization over CeO2 in the vapor phase followed by steam reforming of the ketone intermediates over Co/CeO2. The dual-bed approach reduced coke deposition and thus catalyst stability improved. Techno-economic analysis was used to assess economic viability for producing fuel from the bio-oil fraction and either propene (formed via hydrogenation and dehydration of acetone, the primary ketonization product) or hydrogen from the aqueous stream. The ketonization and steam reforming cases were separately modeled and benchmarked to a process utilizing anaerobic digestion. Resulting minimum fuel selling prices of $3.7, $4.2, and $4.3/GGE were obtained for the production of olefins via ketonization, reduction and dehydration; steam reforming; and anaerobic digestion processes, respectively. Both the steam reforming and anaerobic digestion processes benefited by avoiding the need for natural gas by producing the hydrogen on-site required for biocrude hydrotreatment. However, the condensed ketonization process had the lowest minimum fuel selling price because of the co-product olefins generated for sale.

Biomass, hydrothermal liquefaction, techno economi↗

DOE OSTI2018

An Ensemble Optimization Framework for Coupled Design of Hydropower Contracts and Real-Time Reservoir Operating Rules

Often, revenues from hydropower generation depend on the operator's ability to provide firm power in the presence of uncertain inflows. The primary options available for optimizing revenue are negotiation of a firm power contract before operations begin and adjustment of the reservoir release during operations. Contract and release strategy optimization are closely coupled and most appropriately analyzed with stochastic real-time control methods. Here we use an ensemble-based approach to stochastic optimization that provides a convenient way to construct nonparametric revenue probability distributions to explore the implications of uncertainty. The firm power contract is a simplified bilateral fixed price agreement that partially insulates operator and buyer from price fluctuations. The release control laws and firm energy target are jointly optimized to maximize the operator's expected revenue. Revenue probability distributions and related spill performance statistics indicate that predictive operating strategies such as stochastic dynamic programming and model predictive control can give significantly better performance than standard deterministic operating rules. The performance obtained from batch optimization with perfect inflow information establishes a convenient upper bound on potential revenue and provides a baseline for assessing the significance of differences between real-time operating strategies. Sensitivity analysis indicates that the benefits of predictive operational strategies are greatest for reservoirs with medium nondimensional residence times and less important for reservoirs with large residence times. Overall, probabilistic analysis of the coupled hydropower contract-operations problem provides a realistic way to assess revenue and risk for reservoirs that must provide firm power when inflows are uncertain.

13 HYDRO ENERGY↗

DOE OSTI2022

Drivers of Future Physical Water Scarcity and Its Economic Impacts in Latin America and the Caribbean

Future water scarcity is a global concern with significant impacts on the energy, water, and land (EWL) sectors. Countries in Latin America and the Caribbean (LAC) are significant producers of agricultural goods consumed around the world, so disruptions resulting from land and water scarcity in LAC are a source of global supply chain risk. Understanding where water scarcity in LAC could occur and what could drive that scarcity to emerge is critical for strategic resource management and planning, both regionally and globally. Assessing future water scarcity impacts in LAC is challenging given the multisector dynamic interactions among the EWL sectors and the multiple uncertainties acting across different spatial scales. We use scenario discovery to explore the drivers of future water scarcity, considering assumptions related to climate, socioeconomics, and the EWL sectors. Understanding what factors drive uncertainty across outcomes can help stakeholders in targeting long-term solutions and future data collection efforts. To illuminate these dynamics, we use a database consisting of a large ensemble of scenarios representing diverse worlds simulated using the Global Change Analysis Model. We quantify future water scarcity and its economic impacts across the scenarios using three metrics: (1) physical water scarcity, (2) water price, and (3) crop profit. We find that physical water scarcity and water price are driven primarily by reservoir storage capacity assumptions, highlighting the importance of strategic water infrastructure development in maintaining future water availability and accessibility. Crop profit is driven by a combination of water supply and demand assumptions, which emphasizes the complex nature of EWL multisector dynamics. While most of LAC is poised to have abundant land and water resources available for development, water basins in Mexico and along the Pacific coast of South America experience high levels of severity and uncertainty across the future scenarios for at least one of the metrics. We find that the drivers of extreme scarcity vary spatially and across the metrics, further highlighting the heterogeneity of the region and the importance of considering multiple metrics to assess water scarcity vulnerability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

E3SM‐GCAM: A Synchronously Coupled Human Component in the E3SM Earth System Model Enables Novel Human‐Earth Feedback Research

Abstract Modeling human‐environment feedbacks is critical for assessing the effectiveness of climate change mitigation and adaptation strategies under a changing climate. The Energy Exascale Earth System Model (E3SM) now includes a human component, with the Global Change Analysis Model (GCAM) at its core, that is synchronously coupled with the land and atmosphere components through the E3SM coupling software. Terrestrial productivity is passed from E3SM to GCAM to make climate‐responsive land use and CO 2 emission projections for the next 5‐year period, which are interpolated and passed to E3SM annually. Key variables affected by the incorporation of these feedbacks include land use/cover change, crop prices, terrestrial carbon, local surface temperature, and climate extremes. Regional differences are more pronounced than global differences because the effects are driven primarily by differences in land use. This novel system enables a new type of scenario development and provides a powerful modeling framework that facilitates the addition of other feedbacks between these models. This system has the potential to explore how human responses to climate change impacts in a variety of sectors, including heating/cooling energy demand, water management, and energy production, may alter emissions trajectories and Earth system changes. Plain Language Summary Earth system models help us understand how humans are changing the climate. Currently, these models do not include human systems, so predetermined greenhouse gas, aerosol, and land use change data are input to these models. These data do not reflect human responses to changes projected by Earth system models. We have added a human component to an Earth system model to represent human responses to environmental change and calculate corresponding greenhouse gas and land use change data instead of using predetermined data. Including this human component changes projections of land use, land carbon storage, and regional climate. Key Points We have incorporated a novel, advanceable human component in an Earth system model to simulate human‐Earth feedbacks Including terrestrial productivity feedbacks from the Earth to the human systems affects land change, crop prices, carbon, and climate Regional effects of including terrestrial productivity feedbacks are greater than global effects because land change is the main driver

E3SM↗

DOE OSTI2021

Build solar-energy systems to last — save billions

Here, to withstand extreme weather, rapid innovation and rock-bottom prices, solar installations need tighter quality control, standards and testing. Solar energy is being adopted the world over. Prices have plunged 100-fold since 1980. By 2023, the installed capacity of photovoltaics globally is expected to surpass 1 terawatt — 30–100 TW will be required by 2050. Yet colliding trends mean that many of the technologies being installed today might not last until then if quality is not assured.

14 SOLAR ENERGY↗

DOE OSTI2017

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

Fossil fuel combustion and land-use change are the first and second largest contributors to industrial-era increases in atmospheric carbon dioxide concentration, which is itself the largest driver of present-day climate change1. Projections of fossil fuel consumption and land-use change are thus fundamental inputs for coupled Earth system models (ESM) used to estimate the physical and biological consequences of future climate system forcing2,3. While empirical datasets are available to inform historical analyses4,5, assessments of future climate change have relied on projections of energy and land use based on energy economic models, constrained using historical and present-day data and forced with assumptions about future policy, land-use patterns, and socio-economic development trajectories6. Here we show that the influence of biospheric change – the integrated effect of climatic, ecological, and geochemical processes – on land ecosystems has a significant impact on energy, agriculture, and land-use projections for the 21st century. Such feedbacks have been ignored in previous ESM studies of future climate. We find that synchronous exposure of land ecosystem productivity in the economic system to biospheric change as it develops in an ESM results in a 10% reduction of land area used for crop cultivation; increased managed forest area and land carbon; a 15-20% decrease in global crop price; and a 17% reduction in fossil fuel emissions for a low-mid range forcing scenario7. These simulation results demonstrate that biospheric change can significantly alter primary human system forcings to the climate system. This synchronous two-way coupling approach removes inconsistencies in description of climate change between human and biosphere components of the coupled model, mitigating a major source of uncertainty identified in assessments of future climate projections8-10.

climate change↗

DOE OSTI2021

Global roll-out of comprehensive policy measures may aid in bridging emissions gap

Closing the emissions gap between Nationally Determined Contributions (NDCs) and the global emissions levels needed to achieve the Paris Agreement’s climate goals will require a comprehensive package of policy measures. National and sectoral policies can help fill the gap, but success stories in one country cannot be automatically replicated in other countries. They need to be adapted to the local context. Here, we develop a new Bridge scenario based on nationally relevant, short-term measures informed by interactions with country experts. These good practice policies are rolled out globally between now and 2030 and combined with carbon pricing thereafter. We implement this scenario with an ensemble of global integrated assessment models. We show that the Bridge scenario closes two-thirds of the emissions gap between NDC and 2°C scenarios by 2030 and enables a pathway in line with the 2 °C goal when combined with the necessary long-term changes, i.e. more comprehensive pricing measures after 2030. The Bridge scenario leads to a scale-up of renewable energy (reaching 52%-88% of global electricity supply by 2050), electrification of end-uses, efficiency improvements in energy demand sectors, and enhanced afforestation and reforestation. Our analysis suggests that early action via good-practice policies is less costly than a delay in global climate cooperation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Non-linear relationships between daily temperature extremes and US agricultural yields uncovered by global gridded meteorological datasets

Global agricultural commodity markets are highly integrated among major producers. Prices are driven by aggregate supply rather than what happens in individual countries in isolation. Furthermore, estimating the effects of weather-induced shocks on production, trade patterns and prices hence requires a globally representative weather data set. Recently, two data sets that provide daily or hourly records, GMFD and ERA5-Land, became available. Starting with the US, a data rich region, we formally test whether these global data sets are as good as more fine-scaled country-specific data in explaining yields and whether they estimate similar response functions. While GMFD and ERA5-Land have lower predictive skill for US corn and soybeans yields than the fine-scaled PRISM data, they still correctly uncover the underlying non-linear temperature relationship. All specifications using daily temperature extremes under any of the weather data sets outperform models that use a quadratic in average temperature. Correctly capturing the effect of daily extremes has a larger effect than the choice of weather data. In a second step, focusing on Sub Saharan Africa, a data sparse region, we confirm that GMFD and ERA5-Land have superior predictive power to CRU, a global weather data set previously employed for modeling climate effects in the region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Primary material supply configurations and domestic recycling for cost-effective battery material production in the US

Battery cathode active material costs hinge on regionally concentrated, price-volatile metal supply. Here. we construct a regional facility-level cost model based on over 80 global lithium, cobalt, and nickel mines, refineries, and battery-grade material plants. Our model yields aggregated lithium, nickel, manganese, and cobalt production material costs from 392 region-based supply configurations for five different cathode active materials. Focusing on the United States, all-domestic supply is 9–34% costlier than global average, increasing by cobalt content, while these shortfalls can be overcome by selective low-cost material imports. Furthermore, we analyze costs of two U.S.-based recycling facilities from primary data and techno-economic modelling and compare resulting cathode active material-level costs to primary supply. Although it is still significantly higher on cathode active material cost-level, rising end-of-life flows and lowered black-mass prices will, however, make secondary supply cost-competitive to domestic and foreign primary supply cost floors. Facility-level benchmarks reveal targeted import, scaling, and production cost optimization as levers for a resilient, cost-effective U.S. battery-material supply chain.

Energy↗

DOE OSTI2026

Pathways to cost competitive and viable lithium production from Salton Sea geothermal brines

Lithium supply chains remain heavily concentrated in hard rock and brine resources, creating significant supply risks. Geothermal brines represent an underutilized alternative, yet commercial progress is hindered by the absence of facility-scale cost assessments. Here, we present a techno-economic analysis of large-scale lithium extraction from Salton Sea geothermal brines, drawing on primary company disclosures, process patents, and brine resource modeling. Caused by varying lithium and impurity concentrations, brine dilution over time, and process configurations (e.g., production via carbonation and conversion vs. electrolysis), we find that large-scale production costs may reach ~10,000 United States dollars per ton, but increase up to 22,000 United States dollars per ton with higher certainty of brine modeling, raising concerns about economic competitiveness to conventional low-cost sources. Finally, a project feasibility-focused scenario analyses shows that leveraging brine pre-treatment by-product sales could lower long-term lithium break-even prices by ~5,000 United States dollars per ton, whereas capital cost optimization of 20% could further reduce lithium break-even prices by 10%.

Wesselkaemper, Jannis↗

DOE OSTI2020

Food–energy–water implications of negative emissions technologies in a +1.5 °C future

Scenarios for meeting ambitious climate targets rely on large-scale deployment of negative emissions technologies (NETs), including direct air capture (DAC). However, the tradeoffs between food, water and energy created by deploying different NETs are unclear. Here we show that DAC could provide up to 3 GtCO 2 yr -1 of negative emissions by 2035—equivalent to 7% of 2019 global CO 2 emissions—based on current-day assumptions regarding price and performance. DAC in particular could exacerbate demand for energy and water, yet it would avoid the most severe market-mediated effects of land-use competition from bioenergy with carbon capture and storage and afforestation. This could result in staple food crop prices rising by approximately fivefold relative to 2010 levels in many parts of the Global South, raising equity concerns about the deployment of NETs. Overall, these results highlight that delays in aggressive global mitigation action greatly increase the requirement for DAC to meet climate targets, and correspondingly, energy and water impacts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Machine learning model to project the impact of COVID-19 on U.S. motor gasoline demand

Owing to the global lockdowns that resulted from the COVID-19 pandemic, fuel demand plummeted and the price of oil futures went negative in April 2020. Robust fuel demand projections are crucial to economic and energy planning and policy discussions. Here we incorporate pandemic projections and people's resulting travel and trip activities and fuel usage in a machine-learning-based model to project the US medium-term gasoline demand and study the impact of government intervention. We found that under the reference infection scenario, the US gasoline demand grows slowly after a quick rebound in May, and is unlikely to fully recover prior to October 2020. Under the reference and pessimistic scenario, continual lockdown (no reopening) could worsen the motor gasoline demand temporarily, but it helps the demand recover to a normal level quicker. Under the optimistic infection scenario, gasoline demand will recover close to the non-pandemic level by October 2020. The COVID 19 pandemic and consequent lockdown has had a substantial impact on mobility and therefore fuel demand and it is not clear when demand will recover. Ou et al. use a machine learning model that integrates health recovery scenarios to project the near-term future of gasoline demand.

COVID-19 pandemic↗