SEARCH · Engineering Papers

Results for “LCA”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17

All sources NASA NTRS DOE OSTI

DOE OSTI2026

Forest residue harvest optimization: spanning the bridge between plant biology and biorefinery performance

Forestry residues have immense potential as alternative feedstocks to petroleum, yet their inherent complexity remains a major challenge to widespread use. Pairing the temporal rhythms of plant biology with biorefinery performance is critical to industrial-scale biorefinery development. Here, we provide the first report of a techno-economic analysis (TEA) and life cycle assessment (LCA) for a model integrated reductive catalytic fractionation (RCF)–molten salt hydrolysis process for forestry residues varying in tree part, species, and phenophase. All forestry residues resulted in net-negative greenhouse gas (GHG) emissions vs. comparable petroleum feedstocks, with GHG emissions potentially reduced >4.0× through composition-based feedstock selection (e.g., harvesting American beech bark in spring vs. summer). Moreover, American beech twigs/branchlets and bark in leafed and emergence phenophases, respectively, had 7.9× lower predicted phenolic minimum selling prices (MSPs) vs. other feedstocks and MSPs within the current global phenolic market range. Hemicellulose content and RCF yield emerged as key parameters impacting GHG emissions and biorefinery revenue, identifying hardwood twigs/branchlets in the leafed phenophase as optimal biofeedstocks. Biorefinery expenses were dominated by purchased equipment, raw materials, and utility costs, highlighting essential areas for future study. Notably, RCF reactor pressures drove 85–90% of equipment costs, but sensitivity analysis revealed that decreasing the pressure 20% could reduce the phenol MSP 4-fold. Structural carbohydrate dynamics were also investigated using a two-step acid hydrolysis method to resolve tissue- and species-level patterns in biomass composition throughout the year to enable harvest optimization based on TEA/LCA findings. Ultimately, elucidating the impact of biofeedstock dynamics on biorefinery performance enables harvest optimization, informed engineering design, and progress towards an expanded bioeconomy.

Shapiro, Alison J. [University of Delaware, Newark↗

DOE OSTI2021

Effects of Cement Changes and Aggregate System on Mechanical Properties of Concrete

In this paper, mechanical properties of concrete mixtures containing different cementitious combinations and two aggregate systems were investigated under plastic and drying conditions. Emphasis was laid on durability and shrinkage of concrete. Life Cycle Analysis was also conducted by using Green Concrete LCA Webtool. Results indicated that the presence of larger aggregate sizes tend to enhance durability of concrete. The presence of nanosilica also imparted superior mechanical properties to concrete. A cementitious combination containing Portland Limestone Cement and fly ash with larger aggregate sizes emerged as a better performing mixture in terms of mechanical properties and with minimum environmental impact.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Quantifying Energy Flows in PV Circularity Processes

As sustainable deployment and end-of-life management become a hot topic to timely address in the PV community, a dynamic comparative evaluation of the benefits of circular pathways such as reuse, and remanufacturing, recycling has not been performed holistically beyond material flows or LCA analysis. Energy flows are critical for evaluating energy generation technologies. Previously they have been used to compare renewables to fossil generation and then between PV technologies. This paper quantifies energy flows to evaluate circular pathways for PV. The energy flows tracking manufacturing, generation, and losses complementary to the mass flows of silicon are quantified leveraging the PV ICE framework.

circular economy↗

DOE OSTI2024

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Abstract This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass‐based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real‐world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Kim, Seungdo↗

DOE OSTI2026

Corn and Switchgrass Derived Sustainable Aviation Fuel Carbon Intensity

The production and use of sustainable aviation fuel (SAF) could lower aviation's carbon footprint. Feedstock agricultural management can optimize—or potentially determine—SAF sustainability and profitability, but long-term SAF feedstock comparisons are limited. Life cycle assessments (LCA) are commonly used to estimate the carbon intensity of producing SAF from emerging feedstocks due to the limited availability of long-term, primary field data. We quantified the agricultural phase and well-to-wake (WTWa) carbon intensities of producing SAF from no-till, continuous corn (Zea mays L.) under 120 kg N ha−1 year−1 (120 N corn) and switchgrass (Panicum virgatum L.) under 60 or 120 kg N ha−1 year−1 (60 N and 120 N SWG, respectively) via LCAs based on measured data from a long-term (1998-present) field experiment on marginally productive cropland located in Eastern NE, USA. Measured data included crop productivity, long-term changes in soil organic carbon (SOC) stocks (0–150 cm), annual soil N2O emissions, and field management practices. Both 120 N corn (2078 L ha−1) and 120 N SWG (1752 L ha−1) produced more SAF than 60 N SWG (1229 L ha−1) (p < 0.0001). However, making SAF from corn had greater life cycle GHG emissions (i.e., WTWa carbon intensity) than making SAF from 120 N and 60 N SWG (61.5 > −14.5 and −27.5 g CO2e MJ−1 SAF, respectively; p = 0.0007), primarily due to SOC accrual during crop production. Here, we demonstrate that agricultural management (e.g., crop type, fertilizer use) can determine the sustainably and productivity of producing SAF by using long-term, measured field data in LCAs.

carbon intensity↗

DOE OSTI2023

Comparative Life Cycle Assessment of Injection Molded and Big Area Additive Manufactured NdFeB Bonded Permanent Magnets

Permanent magnets are expected to play a crucial role in the realization of the clean economy. In particular, the neodymium-iron-boron (Nd2Fe14B or NdFeB) magnets, which have the highest energy density among rare earth permanent magnets, are needed for building more efficient windmill generators, electric vehicle motors, etc. Currently, near-net shape magnets can be either made through sintering and compression molding with extensive post machining or directly through injection molding. However, injection molding has a loading volume fraction limitation of 0.65 for nylon binders. A novel method of manufacturing bonded permanent magnets with loading fraction greater than 0.65 has been demonstrated using Big Area Additive Manufacturing (BAAM) printers. As energy density is directly proportional to the square of the magnet loading fraction, magnets produced using BAAM printers require less volume and magnetic material compared to that of injection molded magnets on average. A comparative LCA shows that this difference in magnetic powder consumption nearly constitutes the difference in the environmental impact categories. Even after assuming recycled magnetic input, the BAAM magnets perform better environmentally than injection molded magnets, especially in the ozone depletion category. Since BAAM printers can accommodate even higher loading fractions, at scale, BAAM printers possibly can bring about a significant decrease in rare earth mineral consumption and environmental emissions. So furthermore, single screw extrusion enables BAAM printers to have high print speeds and allow them to be economically competitive against injection molding. Therefore, BAAM printed magnets show promise in transitioning towards the clean economy.

36 MATERIALS SCIENCE↗

DOE OSTI2022

PV DMFA [SWR-21-105]

The Photovoltaic Dynamic Material Flow Assessment (PV DMFA) model (also referred to here as “The model”) is a computational framework written in Python based on utility-scale PV electricity generation to quantify time-series stocks and flows of PV materials primarily in crystalline silicon PV technologies. The model evaluates cradle-to-cradle life cycle of utility-scale solar PV systems in the United States in the period 2000-2100. PV DMFA serves as a sustainability analysis tool to assess the impacts of different material circularity practices (i.e., reduce, reuse/refurbish, remanufacture, and recycle), PV module design shifts and sensitivity of material processing and technology related parameters to material installations, waste creation and raw material depletion in PV material supply chains. This tool enables advanced planning for future material needs and informs sustainable pathways for PV material management in the circular economy. This tool could be helpful to a wide range of stakeholders; Particularly, researchers and manufacturers looking for technoeconomic and/or environmental life cycle analysis (LCA) feedback for renewable energy (RE) systems.

Khalifa, SherifA.↗

DOE OSTI2024

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

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

Ghosh, Tapajyoti↗

DOE OSTI2025

pnnl/Rooftop-Unit-LCI-Template

A content repository for the life cycle inventory (LCI) rooftop unit (RTU) data collection template, a data collection template for the linked openLCA model Life Cycle Assessment (LCA) for automated Environmental Product Declaration (EPD) results generation.

Unger, Scott [Pacific Northwest National Laborator↗

DOE OSTI2020

scyjth/biosteam_lca

An agile life cycle assessment (LCA) platform that simultaneously characterize the economic and environmental impacts of biofuels and bioproducts under uncertainty.

Shi, Lynn↗

DOE OSTI2023

Evaluation of Rail Decarbonization Alternatives: Framework and Application

The Northwestern University Freight Rail Infrastructure & Energy Network Decarbonization (NUFRIEND) framework is a comprehensive industry-oriented tool for simulating the deployment of new energy technologies including biofuels, e-fuels, battery-electric, and hydrogen locomotives. By classifying fuel types into two categories based on deployment requirements, the associated optimal charging/fueling facility location and sizing problem are solved with a five-step framework. Life-cycle analysis (LCA) and techno-economic analysis (TEA) are used to estimate carbon reduction, capital investments, cost of carbon reduction, and operational impacts, enabling sensitivity analysis with operational and technological parameters. Here, the framework is illustrated on lower-carbon drop-in fuels as well as battery-electric technology deployments for the US Eastern and Western Class I railroad networks. Drop-in fuel deployments are modeled as admixtures with diesel in existing locomotives, while battery-electric deployments are shown for varying technology penetration levels and locomotive ranges. When mixed in a 50% ratio with diesel, results show biodiesel’s capacity to reduce emissions at 36% with a cost of $\$$ 0.13 per kilogram of CO 2 reduced, while e-fuels offer a potential reduction of 50% of emissions at a cost of $\$$ 0.22 per kilogram of CO 2 reduced. Battery-electric results for 50% deployment over all ton-miles highlight the value of future innovations in battery energy densities as scenarios assuming 800-mi range locomotives show an estimated emissions reduction of 46% with a cost of $\$$ 0.06 per kilogram of CO 2 reduced, compared with 16% emissions reduction at a cost of $\$$ 0.11 per kilogram of CO 2 reduced for 400-mi range locomotives. The NUFRIEND framework provides a systematic method for comparing different alternative energy technologies and identifying potential challenges and benefits in their future deployments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Data for "Sustainable Potassium Sorbate Production from Triacetic Acid Lactone in Food-Grade Solvents"

This study advances the production of potassium sorbate (KS) from triacetic acid lactone (TAL) utilizing food-grade solvents, ethanol (EtOH) and isopropyl alcohol (IPA). We have previously demonstrated the route to produce KS from TAL in tetrahydrofuran (THF) as the main solvent, but the use of THF is associated with environmental and health risks especially for food applications. The process employs a catalytic approach in food-grade solvents and includes three main steps: hydrogenation, etherification and hydrolysis, and ring-opening hydrolysis to produce KS from TAL. In the synthesis of KS from TAL, the use of IPA leads to higher yields and reduced reaction times compared to EtOH. As a result, the overall reaction time in IPA was reduced to 35.7 h, compared to 42.1 h in our previous study using THF and EtOH, while achieving a comparable KS yield of 84% from TAL. The synthesized KS exhibits a trans-2, trans-4 geometrical configuration, identical to that of commercially available KS. Through techno-economic analysis (TEA) and life cycle assessment (LCA), we estimated full-scale production of KS from sugarcane with the developed process in IPA could achieve a minimum product selling price (MPSP) of $8.27 per kg with a range of $7.06–10.16 per kg [5th–95th percentiles from 6000 Monte Carlo simulations] and a carbon intensity (CI) of 13.7 [9.6–18.6] kg CO2-eq per kg. This study highlights the synthesis of KS from TAL using food-grade solvents, demonstrating improved economic viability and environmental sustainability compared to our previous research (MPSP of $9.68 per kg [$8.47–11.45 per kg] and CI of 16.2 [12.0–21.2] kg CO2-eq per kg), as the total required reaction decreases while achieving the comparable overall yield of KS from TAL.

bioproducts↗

DOE OSTI2022

Hawaii Wave Surge Energy Converter (HAWSEC) OSU O.H. Hinsdale Basin

The following information and metadata applies to both the Phase I (Hydrodynamics) and Phase II (Full System Power Take-Off) zip folders which contain testing data from the OSU (Oregon State University) O.H. Hinsdale Wave Research Laboratory, from both OSU and the University of Hawaii at Manoa (UH). See zip folders provided further below in the downloads section. For experimental data of the full system, including PTO, see Phase II dataset. There are two main directories in each Phases's zip folder: "OSU_data" and "UH_data". The "OSU_data" directory contains data collected from their DAQ (data acquisition system), which includes all wave gauge observations, as well as body motions derived from their Qualisys motion tracking system. The organization of the directory follows OSU's convention. Detailed information on the instrument setup can be found under "OSU_data/docs/setup/instm_locations". The experiments conducted are documented in the "OSU_data/docs/daq_logs", which provides the trial number to the corresponding data located under "OSU_data/data" in several formats (e.g., ".mat" and ".txt"). Inside the trial directory, data is provided for each of the instruments defined in "OSU_data/docs/setup/instm_locations". The "UH_data" directory contains data collected from their DAQ. The data is stored in a ".tdms" file format. There are free plug-ins for Microsoft Excel and MathWorks MATLAB to read the ".tdms" format. Below are a few links providing methods to read in the data, but a Google search should identify alternatives sources if these no longer exist (valid as of January 2024): Excel: http://www.ni.com/example/27944/en/ MATLAB: https://www.mathworks.com/matlabcentral/fileexchange/30023-tdms-reader The Excel plugin is recommend to get a quick overview of the data. The UH data is organized by directory name, in which the sub-directories for each experiment contains a directory whose name defines the wave height and period for the experimental data within. For example, a directory name "H02_T0275" corresponds to an experiment with wave height 0.1m and a period of 2.75s. For random wave data, the gamma value is also included in the directory name. For example, a directory name "H02_T0225_G18" corresponds to an experiment with a significant wave height of 0.2m, a peak period of 2.25s, and a gamma value of 1.8, with each spectra being a TMA spectrum. For the free decay experiments, the directory name is defined by the initial angular displacement. For example, a directory name "ang05_run01" corresponds to an experiment with an initial angular displacement of 5 degrees. There is a dataset in the UH data for each corresponding experiment defined in the OSU DAQ logs. The ".tdms" data is output from the DAQ at fixed intervals. Therefore, if multiple files are contained within the folder, the data will need to be stitched together. Within the UH dataset, there are two input channels from the OSU DAQ providing a random square wave signal for time synchronization ("ENV-WHT-0010") and a high/low signal ("ENV-WHT-0012") to identify when the wave maker is active (+5V). The UH data is logged as a collection of channel outputs. Channels not in use for the OSU testing (either Phase I or Phase II) are marked "nan" below. If the sensor is disconnected, it will record noise throughout the experiment. Below are the channel definitions in terms of what they measure: GPS Time = time CYL-POS-0001 = position between flap and fixed reference CYL-LCA-0001 = force between flap and hydraulic cylinder REC-LPT-0001 = nan REC-HPT-0001 = nan REC-HPT-0002 = nan REC-HPT-0003 = nan HHT-HPT-0001 = pressure at exhaust ("head" only) REC-FQC-0001 = nan REC-FQC-0002 = nan HHT-FQC-0001 = flow at exhaust ("head" only) ENV-WHT-0001 = nan ENV-WHT-0002 = nan ENV-WHT-0003 = nan ENV-WHT-0010 = random signal from OSU DAQ ENV-WHT-0012 = high/low signal from OSU DAQ Also included is a calibration curve to convert the string pot data to flap pi...

16 TIDAL AND WAVE POWER↗

DOE OSTI2024

End-of-Life Plastics Management: A Review: Mechanical recycling, pyrolysis and hydrocracking methods

End-of-life plastics present a significant challenge to achieving a sustainable economy. It is crucial to develop environmentally friendly technologies to process the waste streams beyond landfilling. This review provides a detailed overview of end-of-life plastics management, covering mechanical recycling, pyrolysis and hydrocracking methods. Mechanical recycling is the predominant technique employed on a large scale in recycling end-of-life plastics, and this review discusses the technoeconomic assessment and life cycle assessment (LCA) of mechanical recycling. This review also summarises key studies concentrating on chemical recycling techniques for handling end-of-life plastics. Among these, pyrolysis and hydrocracking are discussed in depth. Recent advancements and fundamentals of these two techniques are covered, highlighting their significance in tackling the plastic waste challenge. The prospects of scaling up pyrolysis and hydrocracking technologies are interpreted in terms of technical and economic feasibility. The discussion concludes with recommendations for future research to commercialise chemical recycling of end-of-life plastics.

Chemistry↗

DOE OSTI2022

Electrochemical CO2 conversion to formic acid through the Andora Process

Electrochemical utilization or conversion of CO2 can be used to convert waste CO2 into targeted high-value and cost-effective commercial products. Conventional processes for CO2 conversion to fuel sources are challenging and expensive due to their requirement for high temperatures and pressures. Electrochemically, a catalyst can be used at a fixed applied potential to reduce CO2 to form a desired product with less competition at modest operating conditions. Formic acid (FA) has recently become a product of interest for CO2 conversion due to its potential for hydrogen storage and fuel cell applications. Electrochemically, FA is produced through a direct two-electron transfer process involving CO2 with a proton source, requiring less energy input and fewer reaction steps than traditional processes. However, there remain significant obstacles for the broader-scale implementation of CO2 on the market, including competition with unwanted CO and H, the presence of molecular oxygen, and stability of the electrocatalyst. In order to overcome some of these challenges, a new continuous flow Andora Process was developed consisting of two separate cells to decouple electrochemical reduction of the charge carrier with the FA production via an engineered catalyst. Recent experimental results show that with appropriate design changes and operating conditions to the flow system, FA production above 500 mM can be achieved along with efficiencies above 80%. TEA and LCA assessments of the Andora Process show a potential for the reduction in the GWP potential and cost saving compared to the current comparative formic acid production process.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Carbon Capture from ArcelorMittal Hot Briquetted Iron Plant Using Air Liquide Cryocap™ FG Technology – FEED Study

The process of steel production is energy and carbon intensive with global average energy consumption of 5.5 MWh/tonne of steel and CO2 emission intensity of 1.83 tonne CO2/tonne of steel. The steel making process has inherent CO2 emissions from mineral conversion and is considered major contributors to the global carbon emissions. The steel industry is responsible for 8% of global carbon emissions. The main objective of this research project is to execute and complete a front-end engineering and design (FEED) study for a commercial-scale, carbon capture project that separates 95% of the total CO2 emissions at the ArcelorMittal’s Hot Briquetted Iron (HBI) plant in Portland, TX (Figure 1). The HBI is an ore-based metallic that is used as high-grade feedstock for high-quality steel via an Electric Arc Furnace (EAF) route. The HBI plant produces 2.0 million metric tonnes of high-quality HBI and emits approximately 1 million tonnes CO2/yr. The capture system is a Pressure Swing Adsorption (PSA) system assisted Cryocap™ FG technology (Figure 2). The captured CO2 will be pipeline grade and will be geologically stored in a facility within 10 miles of the CO2 source. The Host Site location in Corpus Christi, TX, is near hydrocarbon processing facilities and near Environmental Justice (EJ) and Qualified Opportunity Zone (QOZ) communities. Due to the location of the Host Site, the retrofit project offers the ability to demonstrate how a workforce focused on the fossil energy sector can be redirected to the clean- energy sector. The Air Liquide Cryocap™ capture technology is a proven technology and has been extensively examined for large industrial applications. It has been shown to be applicable to a variety of industrial applications including the steel industry. Cryocap™ FG (specific setup for Flue Gas application) consists of a Pressure Swing Adsorption (PSA) unit coupled with a Cryogenic System. The PSA pre-concentrates the CO2 from the flue gas, while the cryogenic unit enables the CO2 purity to be increased to the desired level. The scope of this study incorporates completing FEED study of the CO2 capture system which includes point-source CO2 capture and balance-of-plant; Business Case Analysis (BCA) outlining the current and projected volumes of the steel plant’s point sources of CO2 and the potential utilization of tax credits, including its projected revenue and duration; Life Cycle Analysis (LCA); Environmental Justice Analysis; Economic Revitalization and Job Creation Outcomes Analysis; and Workforce Readiness Plan. The plant design work was divided into two components: Inside Battery Limits (ISBL) and Outside Battery Limits (OSBL). The ISBL focuses on the capture system, while the OSBL focuses on the utility feeds and ducting from the plant to the capture system. Various design and engineering deliverables will be developed to define commodity quantities, equipment specifications, and labour effort required to execute the project. These FEED study deliverables will be prepared with the intent to develop an overall project capital cost estimate consistent with an AACE Class 3 estimate. The modular approach for the Cryocap™ FG that is being designed for this study integrates compression, PSA, and cryogenic “bricks” to achieve the desired CO2 capture rates. This carbon capture system integrates easily with the existing plant, thus reducing project costs and risks. It is also capable of managing impurities such as nitrogen oxides (NOx), sulfur oxides (SOx), mercury, hydrocarbons, and particulate matter. The capture system has a smaller footprint than amine-based systems. The two-step process uses PSA to preconcentrate the CO2 in the feedstream and then uses the cryogenic portion to purify and compress the resulting high purity CO2 product. This combination of purification and compression (i.e., process intensification) significantly reduces the CAPEX associated with use of a separate compressor commonly utilized for amine solvent-based systems. Successful completion of the FEED study will provide DOE with a detailed understanding of the costs for scaling up this proven capture technology for commercial applications at industrial facilities.

42 ENGINEERING↗

DOE OSTI2021

Industry Partnerships & Their Role In Reducing Natural Gas Supply Chain Greenhouse Gas Emissions – Phase 2

This analysis is the product of collaboration between Our Nation’s Energy Future (ONE Future) and the United States (U.S.) Department of Energy (DOE) National Energy Technology Laboratory (NETL). This analysis is an update to Phase 1 of the collaboration between ONE Future and NETL. Phase 1 had three objectives: 1. Calculate a greenhouse gas (GHG) emission profile representative of ONE Future’s supply chain, including methane (CH 4 ) emission rates. 2. Compare ONE Future’s emission profile to the emission profile for the U.S. natural gas supply chain. 3. Evaluate specific emission reduction opportunities. Phase 2 has two key enhancements over Phase 1: 1. The reporting year of the data is updated from 2016 to 2017. 2. The emission profiles and the specific emission reduction opportunities are regionalized for the ONE Future supply chain. The ONE Future supply chain is based on data provided by ONE Future members for all their U.S. onshore assets. ONE Future’s data are mostly representative of their participation in the Greenhouse Gas Reporting Program (GHGRP) administered by the Environmental Protection Agency (EPA) and is supplemented by ONE Future facilities that are not required to report to GHGRP. The U.S. scenario is based on NETL’s life cycle analysis (LCA) of natural gas extraction and power generation, which also uses data from the GHGRP (but does not include non-GHGRP facilities). In addition to the data from these sources, NETL accounted for uncertainty due to data variability, data limitations, and variability in liquids unloading frequency and event duration. This report is a re-issue of the 2020 study (published on July 28, 2020). It revises the device count in the mitigation strategy “pipeline pump-down before maintenance” in the Marginal Abatement Cost (MAC) Analysis section of the report (Section 7). Please see the addendum for more details on this revision and resultant changes. This revision does not change most of our conclusions and recommendations. It only changes the total methane reduced from all the mitigation opportunities (low cost and high cost) from 6.5 Bcf CH 4 /yr to 4.8 Bcf CH 4 /yr.

03 NATURAL GAS↗

DOE OSTI2020

Carbon Calculator for Land Use and Land Management Change from Biofuels Production (CCLUB)

The Carbon Calculator for Land Use and Land Management Change from Biofuels Production (CCLUB) has been developed as an integral part of Argonne National Laboratory’s Greenhouse Gases, Regulated Emissions, and Energy use in Technologies (GREET) model to analyze greenhouse gas (GHG) emissions from land use change (LUC) and land management change (LMC) in the context of overall biofuel life-cycle analysis (LCA).

09 BIOMASS FUELS↗