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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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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Impact of electric vehicle battery recycling on reducing raw material demand and battery life-cycle carbon emissions in China

The rapid growth of electric vehicles (EVs) in China challenges raw material demand. This study evaluates the impact of recycling and reusing EV batteries on reducing material demand and carbon emissions. Integrating a national-level vehicle stock turnover model with life-cycle carbon emission assessment, we found that replacing nickel-cobalt-manganese batteries with lithium iron phosphate batteries with battery recycling can reduce lithium, cobalt, and nickel demand between 2021 and 2060 by up to 7.8 million tons (Mt) (67%), 12.4 Mt (96%), and 37.2 Mt (93%), respectively, significantly decreasing reliance on import. Moreover, battery recycling coupled with reuse can reduce carbon emissions by up to 6,532-6,864 Mt (36.0-37.9%), depending on four recycling methods employed. However, this reuse strategy delays battery recycling and risks lithium supply shortage, necessitating trade-offs between carbon reduction and material supply. Future technologies, such as lithium-sulfur and all-solid-state batteries, despite their energy efficiency, might exacerbate lithium shortage, underscoring the crucial need for increased lithium supply.

25 ENERGY STORAGE↗
DOE OSTI2021

Environmental life cycle impacts of small wastewater treatment plants: Design recommendations for impact mitigation

The objective of this study was to quantify potential mitigation of environmental impacts from the operation and construction of wastewater treatment plants (WWTP) from implementing specific design recommendations. The study investigated small WWTPs, many of which are serving slow growing or declining populations. Life Cycle Assessment methodology was used to evaluate and compare the inventory and environmental impacts of nine small WWTP case studies. Detailed inventory data was collected from the facilities’ engineering design plans and utility bills. One recommended practice was to avoid significant overdesign by planning for no lower than a 75% capacity utilization by the facilities’ end-of-life. A theoretical correction to a 75% capacity utilization was estimated to mitigate 0.4% of lifetime electricity usage and 1% of secondary process concrete for every 1% reduction in design average flow rate. Relatedly, a 0.4% mitigation in the Carcinogenic and Global Warming impacts could be achieved for every 1% reduction in design average flow toward a 75% capacity utilization. Other suggested practices were focused on conveyance, namely, to minimize non-process facility area and to use polyvinyl chloride pipe instead of ductile iron pipe where possible. Furthermore, the latter practice was estimated to mitigate between 1.1 and 4.8% of the Carcinogenic impact in the nine case studies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Finally, findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A Life Cycle Decarbonization of Modular Building Solutions: Preprint

Off-site construction methods offer the opportunity to compress costs of net zero energy housing using the advantages of mass production. Blokable, LLC, a vertically integrated modular builder, wanted to know how the learning curves of mass production would help them decarbonize their existing modular housing prototype at a relative cost advantage. The method developed for this question looked at the life cycle assessment of an individual apartment and used learning curve efficiencies to approximate the relative advantage of construction-at-scale. Greenhouse gas emissions were quantified by a learning-affected, whole life carbon emissions model and demonstrated a path to a 60% reduction of whole life CO2-equivalent in the 2030 production year. The resultant roadmap considers a best-first approach to decarbonizing a modular building product line, and the method can be replicated for other modular builders.

decarbonization↗
DOE OSTI2026

Cradle-to-gate life cycle assessment of advanced composite panels incorporating CO 2 -derived multi-walled carbon nanotubes and hemp fiber for sustainable building applications

Advanced composite panels represent a promising pathway to reducing carbon emissions in the construction industry, yet comprehensive environmental impact assessments remain limited. Here, in this study, we conduct a life cycle assessment (LCA) to evaluate the environmental impacts of innovative composite panels produced from multi-walled carbon nanotubes (MWCNTs), hemp fiber (HF), recycled carbon fiber (rCF), and recycled polypropylene (PP), exploring their potential as baseline structural equivalents to conventional gypsum board. MWCNTs and HF play a critical role in sequestering carbon during raw material production, while the recycling processes for CF and PP generally require less energy compared to virgin material production. The LCA evaluates environmental performance using the TRACI 2.1 method, covering global warming potential (GWP), ozone depletion, smog formation, acidification, eutrophication, carcinogenic and non-carcinogenic effects, respiratory impacts, ecotoxicity, and fossil fuel depletion. Compositional variations—resin type (virgin vs. recycled), rCF content (9–29 wt%), and HF content (10–30 wt%)—are introduced for sensitivity and hotspot analyses. Results demonstrate that, when compared on the basis of preliminary structural equivalence, increasing recycled PP, rCF, and HF content can significantly reduce global warming potential compared to gypsum board. Beyond carbon reduction, the composite panels show trade-offs across other environmental categories. With the growing demand for composite materials in interior panels, ceiling systems, and exterior claddings, these findings highlight the environmental benefits and potential trade-offs of the proposed composites, establishing a foundational framework to support their continued development toward full building-system integration.

Advanced composite manufacturing↗
DOE OSTI2023

Global Life Cycle and Techno-Economic Assessment of Algal-Based Biofuels

Techno-economic analyses (TEAs) and life cycle assessments (LCAs) of algal biofuels often focus on locations in suboptimal latitudes for algal cultivation, which can under-represent the sustainability potential of the technology. This study identifies the optimal global productivity potential, environmental impacts, and economic viability of algal biofuels by using validated biophysical and sustainability modeling. The biophysical model simulates growth rates of Scenedesmus obliquusbased on temperature, photoinhibition, and respiration effects at 6685 global locations. Region-specific labor costs, construction factors, and tax rates allow for spatially resolved TEA, while the LCA includes regional impacts of electricity, hydrogen, and nutrient markets across ten environmental categories. The analysis identifies optimal locations for algal biofuel production in terms of environmental impacts and economic viability which are shown to follow biomass yields. Modeling results highlight the global variability of productivity with maximum yields ranging between 24.8 and 27.5 g m -2 d -1 in equatorial regions. Environmental impact results show favorable locations tracked with low-carbon electricity grids, with the well-to-wheels global warming potential (GWP) ranging from 31 to 45 g CO 2eq MJ -1 in South America and Central Africa. When including direct land use change impacts, the GWP ranged between 44 and 55 g CO 2eq MJ -1 in these high-productivity regions. Low-carbon electricity also favors air quality and eutrophication impacts. The TEA shows that minimum algal fuel prices of $\$1.89$-$\$2.15$ per liter of gasoline-equivalent are possible in southeast Asia and Venezuela. Furthermore, this discussion focuses on the challenges and opportunities to reduce fuel prices and the environmental impacts of algal biofuels in various global regions.

09 BIOMASS FUELS↗
NASA NTRS1989

Product specification documentation standard and Data Item Descriptions (DID). Volume of the information system life-cycle and documentation standards, volume 3

This is the third of five volumes on Information System Life-Cycle and Documentation Standards which present a well organized, easily used standard for providing technical information needed for developing information systems, components, and related processes. This volume states the Software Management and Assurance Program documentation standard for a product specification document and for data item descriptions. The framework can be applied to any NASA information system, software, hardware, operational procedures components, and related processes.

Callender, E. David↗
NASA NTRS1989

Assurance specification documentation standard and Data Item Descriptions (DID). Volume of the information system life-cycle and documentation standards, volume 4

This is the fourth of five volumes on Information System Life-Cycle and Documentation Standards. This volume provides a well organized, easily used standard for assurance documentation for information systems and software, hardware, and operational procedures components, and related processes. The specifications are developed in conjunction with the corresponding management plans specifying the assurance activities to be performed.

Callender, E. David↗
NASA NTRS1989

Management control and status reports documentation standard and Data Item Descriptions (DID). Volume of the information system life-cycle and documentation standards, volume 5

This is the fifth of five volumes on Information System Life-Cycle and Documentation Standards. This volume provides a well organized, easily used standard for management control and status reports used in monitoring and controlling the management, development, and assurance of informations systems and software, hardware, and operational procedures components, and related processes.

Callender, E. David↗
DOE OSTI2021

Technoeconomic and Life Cycle Analysis of Synthetic Methanol Production from Hydrogen and Industrial Byproduct CO 2

Here CO 2 capture and utilization provides an alternative pathway for low-carbon hydrocarbon production. Given the ample supply of high-purity CO 2 emitted from ethanol and ammonia plants, this study conducted technoeconomic analysis and environmental life cycle analysis of several systems: integrated methanol-ethanol coproduction, integrated methanol-ammonia coproduction, and stand-alone methanol production systems, using CO 2 feedstock from ethanol plants, ammonia plants, and general market CO 2 supply. The cradle-to-grave greenhouse gas emissions of methanol produced from the stand-alone methanol, integrated methanol-ethanol, and integrated methanol-ammonia systems are 13.6, 37.9, and 84.6 g CO 2 -equiv/MJ, respectively, compared to 91.5 g CO 2 -equiv/MJ of conventional methanol produced from natural gas. The minimum fuel selling price (MFSP) of methanol ($\$0.61-0.64$/kg) is 61-68% higher than the average market methanol price of $\$0.38$/kg, when using a Department of Energy target renewable hydrogen production price of $\$2.0$/kg. The methanol price increases to $\$1.24-1.28$/kg when the hydrogen price is $\$5.0$/kg. Without CO 2 abatement credits, the H 2 price needs to be within $\$0.77-0.95$/kg for the MFSP of methanol to equal the average methanol market price. With a CO 2 credit of $\$35$/MT according to tax credit per metric ton of CO 2 captured and used, the methanol price is reduced to $\$0.56-0.59$/kg.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Life-cycle analysis of recycling of post-use plastic to plastic via pyrolysis

Advanced recycling enables the application of post-use plastics (PUP) to produce valuable industrial chemicals and develop markets for recycled feedstocks. Pyrolysis is one of the most common advanced recycling technologies undergoing industrial-scale implementation for converting PUP. This paper presents a life cycle analysis (LCA) to assess greenhouse gas (GHG) emissions, fossil energy, water consumption, and solid waste impacts of converting PUP into new plastics such as high-density and low-density polyethylene (HDPE and LDPE, respectively). Data was collected from eight plastic pyrolysis companies. This study addresses the impacts of pyrolysis plant size and maturity; two substitution rate (SR) cases of pyrolysis oil with fossil-derived feedstocks in steam crackers (5% and a 20% of pyrolysis oil SR); and potentially avoided emissions from traditional end-of-life (EOL) management. Because the conventional feedstock slate of steam crackers in the Unites States is comprised of 94% gases (a mix of ethane, propane, and butane) and 6% naphtha, the 5% SR case looked at polyethylene (PE) derived from 5% pyrolysis oil, 1% naphtha, and 94% gases; while the 20% SR looked at PE derived from 20% pyrolysis oil and 80% gases. Moreover, the results are presented from two perspectives: 1) steam crackers' and 2) plastic recyclers'. In the recyclers' perspective, the results for the 5% SR showed for each kg of PUP used there was a 23% and 18% decrease in GHG emissions for HDPE and LDPE respectively, while the 20% SR showed a 4% and 3% reduction in GHG emissions for HDPE and LDPE respectively compared to virgin plastic. The 20% SR has lower GHG emissions reductions because there is an added step of hydrotreating the pyrolysis oil to remove chlorine concentrations that is not included in the 5% SR scenario. Furthermore, the 5% SR removes most of the naphtha, a more carbon intense feedstock, and replaces it with PUP-based pyrolysis oil, a less carbon intense feedstock. GHG emissions for PUP pyrolysis could be further reduced by 50% and 131% in the United States and European Union respectively if the GHG emissions of current PUP incineration practices were considered as emission reductions credits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Techno-Economic and life cycle assessment of standalone Single-Stream material recovery facilities in the United states

Material Recovery Facilities (MRFs) are crucial players in achieving a circular economy. MRFs receive complex waste streams and separate valuable recyclables from these mixtures. This study conducts techno-economic analysis (TEA) to estimate the net present value (NPV) and life cycle assessment (LCA) to estimate different environmental impacts of a commercial scale standalone, single-stream MRF to assess the economic feasibility and environmental impacts of recovering valuable recyclables from an MRF processing 120,000 tonnes per year (t/y). The TEA employs a discounted cash flow rate of return (DCFROR) analysis over a 20-year facility lifetime, along with a sensitivity analysis on the impact of different operating and economic parameters. Results show that the total fixed cost of building the MRF facility is $\$ $23 MM, and the operating cost is $\$ $45.48/tonne. Further the NPV of the MRF can vary from $\$ $3.57 MM to $\$ $60 MM, while 100-year global warming potential can range from 5.98 to 8.53 kg carbon dioxide equivalents (CO2-eq) per tonne of MSW. We have also found that MSW composition (arising from regional effects) significantly impacts costs, 100-year global warming potential, and other impact categories such as acidification potential, eutrophication potential, ecotoxicity, ozone depletion, photochemical oxidation, carcinogenic effects, and non-carcinogenic effects. Sensitivity and uncertainty analysis indicate that waste composition and market prices significantly impact the profitability of the MRF, and the waste composition mostly impacts global warming potential. Our analysis also indicates that facility capacity, fixed capital cost, and waste tipping fees are vital parameters that affect the economic viability of MRF operations.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Comparative life cycle assessment of woody biomass processing: air classification, drying, and size reduction powered by bioelectricity versus grid electricity

Sulfur accumulation during biofuel production is pollutive and toxic to conversion catalysts and causes the premature breakdown of processing equipment. Air classification is an effective preprocessing technology for ash and sulfur reduction from biomass feedstocks. Here, a life cycle assessment (LCA) sought to understand the environmental impact of implementing air classification as a sulfur-mitigation technique to improve feedstock quality for pine residues using a grid electricity scenario (GES) versus a bioelectricity scenario (BES). Global warming potential (GWP) for preprocessing was simulated using inventory databases embedded in SimaPro and the Argonne National Laboratory’s GREET model, specifically focusing on comparing the GWP of a GES versus a BES. Overall, the GES had a GWP impact over seven times that of the BES (136 versus 18 kg CO 2 equivalent per tonne of usable feedstock), with steam generation during rotary drying accounting for 57% of the GES’s GWP. Air classification represents 0.4% and 1.6% of the total GWP impact for the GES and BES, respectively. Therefore, air classification can facilitate a 30% reduction in feedstock sulfur content to improve feedstock quality for biofuel conversion and lessen corrosion of equipment while contributing minimal GWP impact during preprocessing.

Air classification↗
DOE OSTI2022

Incremental approach for the life-cycle greenhouse gas analysis of carbon capture and utilization

Electro-fuels (e-fuels) are examples of carbon capture and utilization (CCU) hydrocarbon products that are derived from captured carbon dioxide (CO 2 ), while using renewable electricity as the energy feedstock. The environmental impacts of CCU products (e.g., e-fuel) are systematically quantified through life-cycle analysis (LCA). Previous studies evaluating LCA of e-fuels proposed frameworks with an expanded system boundary approach that included the entire supply chain of the production process generating the CO 2 for CCU, in addition to the supply chain of the CCU product. This expanded system boundary approach evaluates two system boundaries, and uses deduction methods to calculate the carbon intensity (CI) of the CCU product (e-fuel). This paper proposes a simpler system boundary using an incremental approach that can calculate identical CI of the CCU product (e-fuel), while avoiding the extensive calculations in the expanded system boundary framework. The proposed incremental approach allocates the burdens of the CO 2 capturing process to the CO 2 feedstock supplying the CCU production process (e.g., e-fuel production). The CI of the captured CO 2 supplied to CCU process is determined by the energy and material requirements for the CO 2 capturing process and transportation to the CCU plant. Thus, the CI of CO 2 supplied to CCU process can be directly linked to the CI of e-fuel without the need to conduct LCA of the preceding process that generates the CO 2 for CCU.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Cost and Life Cycle Analysis for Deep CO 2 Emissions Reduction for Steel Making: Direct Reduced Iron Technologies

Among heavy industrial sectors worldwide, the steel industry ranks first in carbon dioxide (CO 2 ) emissions. Technologies that produce direct reduced iron (DRI) enable the industry to reduce emissions or even approach net‐zero CO 2 emissions for steel production. Herein, comprehensive cradle‐to‐gate (CTG) life cycle analysis (LCA) and techno‐economic analysis (TEA) are used to evaluate the CO 2 emissions of three DRI technologies. Compared to the baseline of blast furnace and basic oxygen furnace (BF–BOF) technology for steel making, using natural gas (NG) to produce DRI has the potential to reduce CTG CO 2 emissions by 33%. When 83% or 100% renewable H 2 is used for DRI production, DRI technologies can potentially reduce CO 2 emissions by 57% and 67%, respectively, compared to baseline BF–BOF technology. However, the renewable H 2 application for DRI increases the levelized cost of steel (LCOS). When renewable natural gas (RNG) and clean electricity are used for steel production, the CTG CO 2 emissions of all the DRI technologies can potentially be reduced by more than 90% compared to the baseline BF–BOF technology, although the LCOS depends largely on the cost of RNG and clean electricity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗