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  1. Life Cycle Analysis of Dedicated Energy Crops for Fuel Production in the United States

    Dedicated energy crops are promising feedstocks to make biofuels including jet fuels. This study applies life cycle analysis (LCA) to estimate direct well-to-wake (WTW) greenhouse gas (GHG) emissions (g CO2e/MJ) for jet fuel derived from five energy crops-biomass sorghum, miscanthus, switchgrass, poplar, and willow-via Fischer-Tropsch-to-Jet (FTJ) and Ethanol-to-Jet (ETJ) pathways. The WTW boundary includes direct emissions from biomass production, fuel production, and fuel combustion. The R&D GREET model is expanded to conduct the LCA, using national average biomass yields and farming inputs from the 2023 Billion-Ton Study. In addition, this study estimates emissions from market-mediated effects, including induced land-use change,more » induced other crop (non-feedstock) production changes, and induced livestock production changes using global economic and emissions factor models. On a per-dry U.S. ton basis, cultivation and harvest emissions are lowest for willow (51,565 g CO2e) and highest for biomass sorghum (104,488 g CO2e). Per-acre results show similarly high emissions for sorghum and lowest values for poplar and willow. Direct WTW emissions are substantially lower for FTJ (biomass sorghum: 5.5; miscanthus: 10.3; switchgrass: 11.7; poplar: 11.9; and willow: 8.7 g CO2e/MJ) than ETJ (33.2; 33.8; 34.8; 36.2; and 31.7 g CO2e/MJ, respectively). When market-mediated emissions are included, miscanthus exhibits the lowest total emissions across energy crop pathways. Although results are sensitive to modeling assumptions, they indicate that high-yielding perennial and woody crops, particularly when planted on marginal land, could significantly reduce WTW emissions for bio-jet fuels by combining low direct emissions with soil carbon gains and favorable market-mediated effects.« less
  2. Life Cycle Analysis of Growing Canola for Biofuel Production in the United States

    This study quantifies and compares the life cycle greenhouse gas (GHG) emissions of renewable diesel (RD), sustainable aviation fuel (SAF), and biodiesel (BD) produced from two U.S. canola production systems: 1) emerging intermediate winter canola, typically grown in double- or relay-cropping systems between the growing seasons of main crops, and 2) main canola, mostly spring canola but also including winter canola, which are grown as primary crops occupying the field for a full growing season. Using the Research and Development version of the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model and the most up-to-date lifemore » cycle inventory data─field trial data for intermediate winter canola (>37,000 acres) and recent national survey data for spring canola─this life cycle analysis (LCA) estimates the direct emissions from canola cultivation and harvest, the conversion of canola into fuels, fuel transportation, and combustion. In addition, we account for market-mediated emissions associated with a scenario of 0.5 billion gallons per year of spring canola-based biofuels, including induced land use change (ILUC), induced other crop (nonfeedstock) production changes, and induced livestock production changes. For intermediate winter canola, these market-mediated effects were not modeled, as ILUC is expected to be negligible due to its integration into existing rotations, and data are currently insufficient to reliably quantify other market-mediated changes. The estimated life cycle direct emissions of RD/SAF derived from intermediate winter canola and main spring canola are about 32 and 33 g of CO2-equivalent per megajoule of fuel (g CO2e/MJ), respectively. Corresponding emissions for BD from intermediate winter canola and main spring canola are about 30 and 31 g of CO2e/MJ, respectively. Farming is the dominant emissions source for both canola systems, with intermediate winter canola and main spring canola emitting about 19 and 20 g of CO2e/MJ, respectively. ILUC and other induced changes increase emissions of main spring canola-derived RD/SAF and BD by about 18 and 17 g of CO2e/MJ, respectively. These results indicate that the GHG emissions of biofuels produced from the two canola systems may differ substantially due to the different land use dynamics of the systems.« less
  3. Life Cycle Analysis of Hydrogen Production via Methane Pyrolysis Using Plasma Arc

    Steam methane reforming of natural gas is the primary method of producing hydrogen in the United States, accounting for 95% of all hydrogen produced there. Methane pyrolysis, an alternative production pathway that decomposes natural gas into solid carbon and hydrogen, both eliminates CO 2 emissions associated with methane reforming and allows for additional income from carbon black. A life-cycle inventory of this process has been developed using ASPEN Plus to model the methane pyrolysis (plasma arc) process. From well to gate, hydrogen production via methane pyrolysis produces 2.78 kg CO 2 e/kg H 2 of greenhouse gas emissions using massmore » allocation of emissions between hydrogen and carbon black coproducts. The well-to-gate emissions are mainly driven by electricity consumption (∼38 kW h/kg H 2 ), which accounts for 81% of the emissions; if renewable electricity is used, well-to-gate emissions can be reduced to −0.448 kg CO 2 e/kg H 2 . • Methane pyrolysis is a viable alternative method of hydrogen production. • Mass allocation of emissions between hydrogen, carbon black, and coke. • Electricity is the main contributing factor to WTG emissions of hydrogen produced. • H 2 WTG emissions decrease from 2.72 to −0.437 kgCO 2 e/kgH 2 using renewable energy.« less
  4. Comparison of Ammonia with Methanol, Liquefied Natural Gas and Conventional Marine Transportation Fuels through Life Cycle Cost and Emissions Analysis

    This study evaluates ammonia as a potential marine fuel for a SUEZMAX tanker and compares it with methanol, liquefied natural gas, and conventional fuel oils. The motivation arises from the need to identify low-emission, cost-competitive fuel options that can reduce greenhouse gas emissions from international shipping. The central hypothesis is that ammonia produced from renewable energy sources can achieve lower well-to-wake greenhouse gas emissions with varying life cycle costs based on the region. Life cycle assessment and techno-economic analysis were performed for a thirty-year vessel lifetime on two representative trade routes: from Saudi Arabia to Japan and from Saudi Arabiamore » to the Netherlands. Four ammonia production pathways were assessed: natural gas, natural gas with carbon capture, natural gas pyrolysis, and renewable electricity–based synthesis. Results show that wind-based ammonia produced in Saudi Arabia achieved the lowest life cycle well-to-wake greenhouse gas emissions, between 0.58 and 0.64 million metric tons, among all fuels when using regional grid process electricity. With renewable process electricity, ammonia produced from natural gas pyrolysis in Saudi Arabia showed comparable emissions of 0.37 to 0.44 million metric tons with wind-based ammonia of 0.37 to 0.43 million metric tons. Liquefied natural gas exhibited the lowest life cycle cost, between 402 and 412 million United States dollars, and the only negative carbon abatement cost, ranging from −277 to –322 United States dollars per metric ton of greenhouse gas, compared with high sulfur fuel oil. The findings indicate that renewable ammonia offers a promising long-term pathway for reducing shipping emissions, while liquefied natural gas remains the most cost-effective option in the near term.« less
  5. Global Techno-Economic and Life Cycle Greenhouse Gas Emissions Assessment of Solar and Wind Based Renewable Hydrogen Production

    This study conducts a global assessment of renewable hydrogen production pathways, focusing on techno-economic performance and life cycle greenhouse gas (GHG) emissions. It evaluates standalone solar photovoltaic (PV), wind, and hybrid PV/wind systems, integrated with proton exchange membrane (PEM) electrolyzers, through multi-objective optimization and considering embodied emissions in manufacturing PV, wind and electrolyzers. Results identify optimal configurations to minimize levelized cost of hydrogen (LCOH) and carbon intensity (CI) of hydrogen, showing potential reductions of cost and CI by 2030. Standalone PV systems can achieve LCOH values smaller than 6.5 USD/kg H2 and CI less than 2.5 kg CO2eq/kg H2 inmore » regions with high solar irradiance, such as North Africa, the Middle East and Chile. Wind systems in regions such as Middle East, North Africa, Australia and Central United States achieve LCOH below 5 USD/kg H2 and CI under 1.5 kg CO2eq/kg H2. Hybrid systems emerge as the optimal solution for minimizing both the LCOH and CI by maximizing the use of renewable energy. Moreover, the results also indicate that, with the technological advancements, future reduction in the capital cost of renewable energy systems and the PEM electrolyzer as well as the trade of coproduct O2 could drive the LCOH of all the RES-based hydrogen systems below 1 USD/kg H2 and the CI below zero in different regions as Middle East, North Africa and Central United State« less
  6. Life Cycle Greenhouse Gas Emissions of Biogas Upgrading for Fuel Production

    Waste-to-Renewable Natural Gas (RNG) offers a promising solution to alleviate waste management challenges by converting waste into renewable fuels. This process can significantly reduce greenhouse gas (GHG) emissions, as demonstrated through a comprehensive life cycle analysis. Biogas upgrading is essential to enhance methane concentration, though it could be energy-intensive and susceptible to methane slippage. Four commonly adopted biogas upgrading technologies including pressure swing adsorption, membrane separation, chemical absorption, and water scrubbing are considered. Our study evaluates the life cycle GHG emissions of RNG production from major sources of waste in the U.S. including wastewater sludge, food waste, landfill gas, dairymore » cow manure, and swine manure. Meta-analysis was conducted to assess methane slippage and energy consumption of biogas upgrading and associated GHG emissions, while accounting for potential avoided emissions from conventional waste management, which vary widely (ranging from -481.0 to 101.8 g CO2-eq/MJ). Under default upstream assumptions, representative carbon intensity of RNG varies from about -125 g CO₂-eq/MJ (dairy cow manure) to about 41 g CO₂-eq/MJ (wastewater sludge). We also explored RNG applications in producing hydrogen, ammonia, and compressed/liquefied forms. These findings highlight the potential of RNG and RNG-derived fuels to reduce GHG emissions and bolster the U.S. energy supply.« less
  7. Life-cycle greenhouse gas emissions analysis of battery-grade lithium production in Finland

    Various countries are undertaking initiatives to domestically produce battery-related critical materials. Within Finland, Keliber Technology Oy is developing capabilities for battery-grade lithium hydroxide monohydrate (LHM) production from spodumene ores. A detailed life-cycle assessment (LCA) of this pathway is conducted to determine its life-cycle GHG impacts using Argonne's R&D GREET (Research and Development Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model. The analysis shows life-cycle GHG emissions of similar to 9.2 kg CO2-eq/kg LHM, dominated by contributions from three energy sources - diesel, natural gas, and electricity - and two material inputs - lime (CaO) and soda ash (Na2CO3).more » Sensitivity analyses highlight the potential to reduce these impacts using low-carbon electricity, sequestration of process CO2 emissions generated during CaO and Na2CO3 production, and bio-based energy for LHM production (by similar to 15 % each). A comparative analysis shows lower impacts for Keliber's LHM than for existing LHM production from Australian spodumene ores processed in China (by similar to 40 %).« less
  8. Renewable Hydrogen Horizon: Geospatial Techno-economic Feasibility and Life Cycle Greenhouse Gas Analysis in the Middle East and North Africa

    Renewable hydrogen is receiving increasing attention for its potential as a flexible energy carrier in sectors such as transportation and industry. Specific cost and carbon intensity (CI) of renewable hydrogen production vary largely based on the location, owing to differences in renewable energy resources, as well as the supply chain dynamics. This study maps the techno-economic and life cycle greenhouse gas emissions of renewable hydrogen production in the Middle East and North Africa region, leveraging abundant solar and wind resources. The work investigates the variability in hydrogen costs and CI, optimally sizing proton exchange membrane (PEM) electrolyzers to account formore » partial and cyclic loading, and explores standalone versus grid-connected systems. PEM capacity ratios of 52%-63% for photovoltaic (PV) systems and 28%-82% for wind systems were identified as optimal, with hydrogen production costs ranging from $3.8-$4.8/kg for PV and $2.0-$7.0/kg for wind. CIs span from 1.9-3.7 kg CO2,eq/kg H2 for PV and 0.4-7.7 kg CO2,eq/kg H2 for wind systems. The study highlights significant cost and CI reductions achievable with technological advancements and co-product revenue from oxygen and electricity sales.« less
  9. Machine Learning-Based Extreme Data Reduction for Prompt Supernova Pointing at DUNE

    One of the goals of the Deep Underground Neutrino Experiment (DUNE) is to use the massive underground liquid argon time projection chamber (LArTPC) detectors at its far site for multimessenger astronomy (MMA), in the detection of neutrinos from core-collapse supernovae (SNe). Its current baseline trigger strategy detects activity in the detector that is consistent with supernova (SN) neutrinos and saves the raw data for further offline analysis but provides no prompt pointing information crucial for optical follow-ups by other observatories. This approach is based on the assumption that prompt pointing determination using raw data is computationally prohibitive. In this article,more » we demonstrate a proof-of-concept based on applying extreme data reduction on the buffered SN data in the DUNE data acquisition (DAQ) system’s front-end computers using a machine learning (ML) workflow. This reduces the data by ~5 orders of magnitude, allowing a full track reconstruction to be carried out quickly on a single server. The total time to perform the ML-based data reduction and the full track reconstruction is less than the time to transfer the SN data back to Fermilab or a high-performance computing (HPC) center. This shows that prompt processing of raw SN data is possible and, in fact, trivial once the data have been reduced to reject radiological backgrounds, paving the way to a high-quality SN pointing trigger that is based on fully reconstructed data instead of trigger primitives (TPs).« less
  10. Shape-shifting Elephants: Multi-modal Transport for Integrated Research Infrastructure

    Data Acquisition (DAQ) workloads form an important class of scientific network traffic that by its nature (1) flows across different research infrastructure, including remote instruments and supercomputer clusters, (2) has ever-increasing throughput demands, and (3) has ever-increasing integration demands---for example, observations at one instrument could trigger a reconfiguration of another instrument. Today's DAQ transfers rely on UDP and (heavily tuned) TCP, but this is driven by convenience rather than suitability. The mismatch between Internet transport protocols and scientific workloads becomes more stark with the steady increase in link capacities, data generation, and integration across research infrastructure.This position paper argues themore » importance of developing specialized transport protocols for DAQ workloads. It proposes a new transport feature for this kind of elephant flow: multi-modality involves the network actively configuring the transport protocol to change how DAQ flows are processed across different underlying networks that connect scientific research infrastructure. Multi-modality is a layering violation that is proposed as a pragmatic technique for DAQ transport protocol design. It takes advantage of programmable network hardware that is increasingly being deployed in scientific research infrastructure. The paper presents an initial evaluation through a pilot study that includes a Tofino2 switch and Alveo FPGA cards, and using data from a particle detector.« less
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"Wang, Michael"

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