Effect of Hydrogen Leakage on the Life Cycle Climate Impacts of Hydrogen Supply Chains

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Beagle, Ansh N. Nasta, Derek L. Wissmiller, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4825556/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Feb, 2025 Read the published version in Communications Earth & Environment → Version 1 posted You are reading this latest preprint version Abstract Hydrogen is of interest for decarbonizing hard-to-abate sectors because it does not produce carbon dioxide when combusted. However, hydrogen has indirect warming effects. In this work, we conducted a life cycle assessment of electrolysis and steam methane reforming to assess their emissions while considering hydrogen’s indirect warming effects. We find that the primary factors influencing life cycle emissions are the production method and related feedstock emissions, rather than the hydrogen leakage and the indirect warming potential of hydrogen. A comparison between fossil fuel-based and hydrogen-based steel production and heavy-duty transportation showed a reduction in greenhouse gas emissions, of approximately 800 to more than 1400 kgCO 2 e per tonne of steel and 0.1 to 0.17 kgCO 2 e per tonne-km of cargo. While any hydrogen production pathway reduces greenhouse gas emissions for steel, this is not the case for heavy-duty transportation. Therefore, we recommend a nuanced approach in choosing application areas for hydrogen. Earth and environmental sciences/Climate sciences/Climate change Earth and environmental sciences/Environmental sciences/Environmental impact Scientific community and society/Energy and society/Energy policy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 INTRODUCTION Hydrogen is a promising low-carbon and scalable option to decarbonize hard-to-abate industries such as iron and steel production, heavy manufacturing, and heavy-duty transportation [ 1 , 2 , 3 , 4 ]. As of August 2024, 61 countries including the United States (US) have official national hydrogen strategies [ 5 ]. Other countries, including China, have included hydrogen in their decarbonization and energy plans [ 6 ]. Recent energy policies in the US, such as the regional clean hydrogen hubs and the Clean Hydrogen Production Tax Credit in the Inflation Reduction Act (IRA), are set to dramatically increase the production and use of clean hydrogen [ 7 ]. Thus, various analyses have projected that hydrogen production and consumption volumes could increase from under 100 Megatonnes (Mt) in 2022 to 530Mt650Mt by 2050 [ 8 , 9 , 10 , 11 ]. As governments worldwide have pledged billions in investments toward hydrogen development and expansion quantifying hydrogen greenhouse gas emissions would be beneficial to understanding life cycle climate impacts. For the IRA’s Clean Hydrogen Production Tax Credit, the tax credits issued are dependent on the life cycle greenhouse gas emission intensity of the hydrogen production process in kilograms pf CO 2 - equivalent per kilogram of hydrogen (kgCO 2 e/kgH 2 ). Supply chains with lifecycle emissions below 4 kgCO 2 e/kgH 2 will qualify for the most generous support [ 7 ]. The tax credit requires a well-to-gate lifecycle analysis including emissions associated with feedstock growth, gathering, extraction, processing, and delivery to a hydrogen production facility and emissions associated with the hydrogen production process itself. The hydrogen focused Greenhouse gases, Regulated Emissions, and Energy use in Transportation model (45VH2-GREET) developed by Argonne National Laboratory was designated as the official tool to quantify emissions for tax credit applicants. The 45VH2-GREET model, however, does not account for hydrogen fugitive emissions and leakage nor does it include all hydrogen production methods that may be economically viable. This absence can unintentionally impede innovations that are not currently encompassed within the established repertoire of 45VH2-GREET. Furthermore, the 45VH2-GREET model and, subsequently, the clean hydrogen tax credit assessments do not consider downstream emissions and, therefore, omit a crucial aspect of hydrogen's emission reduction capability through the displacement of current fossil fuels. Though hydrogen itself is not a greenhouse gas, it interacts with the hydroxyl radical, which is the primary sink for methane. This interaction, increases the atmospheric lifetime of methane, a potent greenhouse gas, and thus, hydrogen indirectly increases radiative forcing [ 12 , 13 , 14 ]. In the troposphere, methane oxidation leads to the production of formaldehyde, which produces hydrogen through photolysis. The natural presence accompanied by increased anthropogenic injection of hydrogen in the atmosphere that can occur through leakage may accentuate this adverse atmospheric interaction. Furthermore, certain hydrogen production pathways such as pyrolysis and steam methane reforming (SMR) rely on a methane feedstock, which can also be leaked, effectively increasing the overall stockpile of atmospheric methane. Moreover, through its interaction with hydroxyl, hydrogen increases tropospheric ozone and produces water vapor which also acts as a greenhouse gas through radiative trapping in the stratosphere [ 15 ]. There are uncertainties across the literature concerning the quantification of hydrogen sinks and global hydrogen leakage rates. Gaseous hydrogen is more reactive and has a smaller molecular cross-section than methane and is therefore prone to leak [ 16 ]. The leakage rates available in previous studies are obtained from assumptions, calculations, lab experiments, and simulations [ 17 ]. These estimates are not uniform across hydrogen production technologies or supply chains. Most studies utilize hydrogen leakage rates ranging from 1–10% to produce estimates of its climate implications. A recent study synthesizing known hydrogen emission rates reported present and future value chain emissions varying between 0.2–20% [ 17 ]. In the effort to obtain more accurate hydrogen leakage rates the US Department of Energy (DOE) recently announced a $ 20 million detection and quantification development initiative [ 18 ]. Furthermore, there is a lack of consensus on hydrogen’s global warming potential due to its relatively shorter lifespan of 2.5 years compared to other greenhouse gases [ 19 ]. The commonly encountered metrics are global warming potential over 100 years and 20 years (GWP 100 , GWP 20 ), and global temperature potential over 100 years and 20 years (GTP 100 , GTP 20 ). The values reported for hydrogen are 13 ± 5 for GWP 100 , 40 ± 24 for GWP 20 , 2 ± 1.5 for GTP 100 , and 18 ± 23 for GTP 20 [ 19 ]. The Hydrogen Council conducted a life cycle assessment (LCA) that considered various pathways envisioned for future hydrogen value chains for 2030 and 2050 [ 20 ]. The pathways in the study consist of four autothermal reforming (ATR) plants coupled with 98% capture of total emitted carbon and four electrolysis pathways with onshore or offshore wind and/or solar energy [ 20 ]. The end-use applications in their analysis include light-duty vehicle transport, shipping, industrial heat, power generation, fertilizer manufacturing, public transport, and steel production. The analysis includes a comparison between the various hydrogen pathways used and alternative fossil fuel-based or electric-based pathways as appropriate. The results of the study indicated that the effects of using hydrogen range from 60–100% reduction in warming for the respective supply chains relative to current methods, assuming a carbon intensity reduction of the global grid mix [ 20 ]. Although this analysis included operational hydrogen venting at production, it omitted fugitive emissions along the supply chain and the indirect warming effects of hydrogen. Recently, researchers from the Environmental Defense Fund (EDF) conducted a study on the life cycle of hydrogen deployment pathways in which hydrogen leakage and warming effect were taken into consideration [ 21 ]. The study was based on the LCA completed by the Hydrogen Council in 2021 [ 20 ], but only considered four end uses, notably light-duty vehicle transport, shipping, industrial heat, and power generation, and focused on impacts in 2050. Additionally, carbon capture on ATR hydrogen production was assumed to range from 60–98%. A hydrogen leakage range of 1–10% was assumed across the value chain, and five levels of methane leakage were considered: —extreme low (0.01%), low (0.6%), medium (0.9%), high (2.1%), and extreme high (5.4%). The comparisons between the hydrogen pathways and fossil fuel alternatives were completed using the technology warming potential (over 10, 20, 50 years), which measures the effect of switching from one technology to another, and GWP (over 20 and 100 years). Under extreme cases, the use of hydrogen can produce a 46% increase or a 93% decrease in warming, respectively. This range suggests that better understanding of hydrogen life cycle emissions and warming impacts and appropriate supply chain and end use selection is critical for hydrogen use to yield meaningful climate benefits. Furthermore, electrolysis production pathways appear to be the most consistent in emission reduction (> 60%) regardless of hydrogen leakage and warming effects over different time scales [ 21 ]. Despite its thoroughness in terms of hydrogen emissions consideration this study omits two main end uses for hydrogen, notably steel production and heavy-duty transport, which are examined in this work. Current steel production is responsible for 9% of worldwide carbon dioxide emissions, averaging 1.85 tonne (1850 kg) of CO 2 per tonne of steel produced [ 22 ]. Proposed decarbonization strategies for the steel industry include substituting hydrogen and direct reduction for coal used in blast furnaces. Additionally, renewable energy or hydrogen combustion could be used for process heat to reduce or eliminate emissions. Similarly, hydrogen has been proposed as an alternative fuel to reduce heavy duty trucking emissions that currently range from approximately 0.1 to 0.3 kgCO 2 e per tonne-km for conventional vehicles operating with diesel [ 23 ]. In this work, we aim to fill the existing knowledge gap by including leakage rates and global warming potential to quantify the life cycle climate effects from 1) different hydrogen production pathways then 2) using that hydrogen as an alternative to traditional energy sources for end uses previously omitted in literature. Given the projected growth of hydrogen in the energy mix to meet 2050 decarbonization goals and the concerns that hydrogen might indirectly cause warming that undermines progress towards mitigating climate change, it is valuable to comprehensively assess the impacts of the full life cycle emissions and indirect warming effects of hydrogen. This approach will be demonstrated with novel LCAs of a few sample hydrogen production pathways (electrolysis with grid-tied electricity, electrolysis with carbon-free electricity, SMR, and SMR with CCS) and product manufacturing of steel and heavy-duty transport. RESULTS Production: This study used hydrogen global warming potentials from Hauglustaine., et al [ 19 ]. An initial 2% hydrogen leakage was applied to all the production methods to assess the effects of the other variables. Figure 1 shows the results of this standardized leakage reported in kgCO 2 e / kgH 2 using GWP 100 of hydrogen. The difference between the overall greenhouse gas intensity of hydrogen production with and without indirect warming from hydrogen leakage is < 0.5 kgCO 2 e /kgH 2 for all pathways considered, which represents less than a 15% increase for electrolysis with grid-tied electricity, steam methane reforming (SMR), and SMR with carbon capture and sequestration (CCS). Consequently, though there is a slight increase in CO 2 e emissions when hydrogen’s indirect warming effects are introduced into the model, the carbon intensity of the electricity source and carbon intensity of the production process have a much greater bearing on overall warming potential of hydrogen production. Figure 2 shows an assessment of the sensitivity to different climate metrics of hydrogen indirect warming effects over time with uniform 2% leakage for all the production methods. The increase in carbon intensity introduced solely by hydrogen warming effects (as opposed to methane) over different time frames is presented through contrast between the base scenario and the inclusion of hydrogen GWP. On average, there is a 0.5 kgCO 2 e /kgH 2 difference between GWP 100 and GWP 20 values. With the relatively shorter lifetime of hydrogen, such results align with previous studies that concluded the climate effects of hydrogen are slightly attenuated over time [ 17 , 24 ]. An assessment of current reported leakage rate projections for 2050 by Esquivel-Elizondo S., et al [ 17 ], revealed considerable variation. Electrolysis with renewables has the highest reported leakage rates varying between 2.0% and 9.2%. These relatively high values are due to venting and purging that occur for safety reasons during the electrolysis process. Unabated SMR and SMR coupled with CCS have leakage rates that vary between 0.5% and 1.0%. The detailed leakage rates used for this analysis are outlined in the methods section. Figure 3 shows that despite relatively high leakage rates, electrolysis had the lowest emissions for the lower and average scenarios and remained comparable in emissions to SMR with CCS even with an upper limit leakage rate. On the other hand, unabated SMR, even with lower hydrogen leakage rates, has the highest overall emissions (partly because of fugitive methane emissions in its supply chain) and fails to meet the DOE clean hydrogen standard of 4.0 kgCO 2 e /kgH 2 for well-to-gate life cycle greenhouse emissions. It must be noted our analysis includes a greater scope of emissions then outlined in the 45V guidance (view methods). Steel Production and Heavy-Duty Transport Case Studies: Figure 4 A and 4 B show the decrease in emissions observed with the use of hydrogen for steel production and heavy-duty transport respectively. The results from the steel supply chain LCA include hydrogen leakage and associated indirect warming effects at each stage of the supply chain (production, transportation, and end use). The assessment reveals a minimum 800 kgCO 2 e per tonne of steel production (t steel decrease in the carbon intensity of steel production using hydrogen compared to current fossil fuel-based methods with an average carbon intensity of 1850 kgCO 2 e/t steel [ 22 ]. Further reduction is observed with decreased carbon intensity of the hydrogen production method. A decrease in emissions ranging from 0.1– 0.17 kgCO 2 e per tonne-kilometer (t-km) is observed with hydrogen based heavy duty trucking when using electrolysis powered by wind or solar energy. An increase in emissions (0.79 kgCO 2 e /t-km) for heavy duty transportation is observed when using hydrogen from unabated SMR. DISCUSSION Including hydrogen leakage and its associated impact in LCA models only increases the total climate impact of hydrogen production by 0.5 kgCO 2 e / kgH 2 . These findings suggest that while hydrogen does act as an indirect greenhouse gas, other sources of emissions along the supply chain, including electricity production, fugitive methane emissions, and process emissions, are more significant in the overall climate impact of hydrogen production. Furthermore, even with high hydrogen leakage rates, electrolysis powered by renewables meets the U.S. federal standard of clean hydrogen production with lifecycle emissions intensity below 4 kgCO 2 e /kgH 2 . Moreover, by incorporating median leakage values and hydrogen GWP into an existing steel production process it was evident that there is a significant decrease in emissions per tonne of steel produced when shifting from conventional fossil fuel to hydrogen-based steel production, regardless of the production pathway for the hydrogen. In heavy-duty transportation, hydrogen in place of diesel can reduce or exacerbate climate impacts depending on the production pathway. Hydrogen produced via electrolysis with renewables (wind or solar) has lower climate impact while hydrogen produced via SMR and SMR with CCS has a similar or higher carbon intensity compared to current heavy-duty fuels. Our finding is a need for a nuanced approach in evaluating hydrogen's role in mitigating climate change effects. While hydrogen holds promise as a cleaner energy source, careful consideration of its supply chain, leakage, and indirect climate effects is crucial to ensure meaningful contributions to global decarbonization goals. METHODS The goal of this assessment is to quantify the impact of hydrogen's indirect climate effects and leakage rates on the life cycle emissions of different hydrogen production methods and end uses. We use a life cycle assessment (LCA) model constructed through the Open LCA software and the IPCC 2021 impact assessment method to estimate greenhouse gas emissions intensity of various hydrogen production pathways [ 26 ]. The functional unit is the product of concern, which in this case is hydrogen or the concerned end use (highlighted in red in the data tables). Every phase of the life cycle is divided into processes, which are subsequently interconnected through intermediate flows, thereby forming a product system. The data used to conduct this analysis was obtained from the Ecoinvent database [ 27 ], a sustainability assessment life cycle inventory, in addition to available hydrogen leakage rates obtained from a study conducted by Esquivel-Elizondo S., et al [ 17 ]. The GWP 100 , and GWP 20 of hydrogen obtained from a study conducted by Hauglustaine., et al [ 19 ] reported in Table 1 were incorporated in the assessment. These values were used in order to understand the warming potential of each production pathway with associated leakage and indirect hydrogen climate impact over time. Table 1 GWP values for hydrogen from Hauglustaine., et al [ 19 ] in this table were added to the IPCC 2021 impact assessment method and used in this study. Climate Change Metric Value GWP 100 13 GWP 20 40 Production: The production methods taken into consideration in this analysis are unabated SMR (SMR without CCS), SMR coupled with 96% CCS, electrolysis using a grid mix supply of electricity, electrolysis using solar (equivalent kWh not hourly matched), and electrolysis using wind energy (equivalent kWh not hourly matched). Figures 5 , 6 , and 7 display the system boundaries of the production methods used. The system boundary for the SMR pathways begins with the raw material production and transport of natural gas, deionized water, metallurgical aluminum oxide, magnesium oxide, copper oxide, quicklime, chromium oxide, zinc oxide, zeolite powder, molybdenum trioxide, silica sand, and portafer. Additionally, the embedded emissions of the chemical factory and storage tank are included. The natural gas is sourced from markets in the United States (U.S.), and the remaining inputs are sourced from the global market. The system boundary for the electrolysis pathways begins with deionized water, the designated electricity supplier (grid, solar, wind, or renewable mix) and their capital expenditure (CAPEX) emissions. The electricity for electrolysis is sourced from the Texas Regional Entity (TRE) for grid mix and wind electrolysis and from the Western Electricity Coordinating Council (WECC) for solar (photovoltaic) electrolysis. For all the production processes, the system boundaries stop after the production of hydrogen (that is, at the system gate). Tables 2 – 5 detail the inputs and outputs of each production process considered in this study. Table 2 Input parameters for SMR and SMR + CCS production pathways with corresponding units. Oxides: Aluminum oxide, Chromium oxide, Copper oxide, Magnesium oxide, Molybdenum trioxide, Zinc oxide. Natural gas, water oxides, nickel, portafer, quisklime, silica, and zeolite powder data sourced from Ecoinvent. Electricity input for CCS was obtained from NETL [ 28 ]. Input Parameters Values Units/kg H2 Natural Gas 4.6 m 3 Water (cooling) 0.4 m 3 Deionized water 4.4 kg Oxides 1.40E-03 kg Nickel 2.00E-04 kg Portafer 3.00E-04 kg Quicklime 4.80E-05 kg Silica 1.20E-05 kg Zeolite powder 9.00E-04 kg Electricity (CCS only) 1.15 kWh Table 3: Output parameters for SMR and SMR+CCS production pathways with corresponding units. Hydrogen leakage data is detailed in Table 7. The remaining data is sourced from Ecoinvent. The hydrogen leakage is emitted to the atmosphere. Stack emissions include acetaldehyde, acetic acid, benzene, benzoapyrene, butane, carbon dioxide, carbon monoxide, dinitrogen monoxide, formaldehyde, mercury, methane, nitrogen oxides, polycyclic aromatic hydrocarbons (PAH), particulate matter, pentane, propane, propionic oxide, sulfur dioxide, and toluene. Output Parameters Values Units Stack emissions 5.7E-04 kg Hydrogen 1 kg Carbon dioxide 9 kg Carbon dioxide (with CCS) 0.34 kg Hydrogen Leakage varies kg Table 4 Input parameters for electrolysis production pathways with corresponding units. The electricity input is obtained from the National Energy Technology Laboratory [ 29 ] and the deionized water input is obtained from WaterSMART Ltd [ 30 ]. Input Parameters Values Units Electricity 40 kWh Deionized water 9 kg Table 5: Output parameters for electrolysis production pathways with corresponding units. Output Parameters Values Units Hydrogen 1 kg Hydrogen Leakage varies kg The data for the SMR production processes (Tables 2 and 3 ) are based on an SMR plant assessed by Antonini., et al. [ 31 ]. The natural gas is pressurized at 200 bars. The hydrogen yield of the process is enhanced with a water gas shift reaction. In the unabated SMR process, the carbon dioxide exits the plant with the flue gas from the furnace. A separate model for CCS was not built for this LCA, rather a 96.2% capture rate was applied to the total amount of carbon dioxide emitted from the base unabated SMR process, and the subsequent electricity requirements were added as additional input. The electricity input value calculations were based on findings from the National Energy Technology Laboratory [ 28 ]. The electricity and water input values for electrolysis were obtained from reports published by the National Renewable Energy Laboratory [ 29 , 32 , 33 ]. This analysis does not take into account specific variations between PEM and alkaline electrolyzers, as the differences are small. An upper limit, lower limit, and average leakage rates were assessed for each production method to gauge the sensitivity of supply chain greenhouse gas emissions intensity to leakage rates. These leakage rates are detailed in Table 6 . An assessment of current reported hydrogen leakage rate projections for 2050 by Esquivel-Elizondo S., et al [ 17 ], revealed considerable variation. Electrolysis with renewables has the highest reported leakage rates varying between 2.0% (lower limit) and 9.2% (upper limit). These relatively high values are due to venting and purging that occur for safety reasons as a result of oxygen build up during the electrolysis process. Unabated SMR and SMR with CCS have leakage rates that vary between 0.5% and 1.0%. There are limitations in the leakage values used as they are obtained from simulations or models. There is little to no direct measurement data available on hydrogen leakage. Methane leakage during the SMR processes is < 1% (default in the Ecoinvent database). Table 6 Hydrogen leakage rates used for the sensitivity analysis. Data obtained from Esquivel-Elizondo S. et al. [ 17 ]. Average value represents value calculated for taking the average of 2050 leakage rate predictions. Leakage rate Percentage (%) SMR Upper limit 1 Average 0.8 Lower limit 0.5 SMR + CCS Upper limit 1.5 Average 0.8 Lower limit 0.6 Electrolysis Upper limit 9.2 Average 4.6 Lower limit 2 Production Model Validation: A validation was conducted by comparing the results from the models in this study to the Hydrogen Production Emissions Calculator (HyPEC) tool version 1.0, which is based on the GREET model version 2021 [ 34 , 35 ]. Figure 8 shows the results of this validation, excluding the indirect warming effect of hydrogen. At the time of this analysis, the 45V-GREET had yet to be made available. The difference between the models for all the production pathways considered is less than 2 kgCO 2 e / kgH 2 . In both models, upstream methane emissions are less than 1%. Steel Case and Heavy-Duty Transport Case Studies: The steel and heavy-duty transport pathways selected are based in Texas to mimic future scenarios as one of the DOE hydrogen hubs, Gulf Coast Hydrogen Hub (HyVelocity), is expected to be constructed in Houston. A hydrogen pipeline transportation distance of 400km is assumed with the scenario that the hydrogen would be produced in Houston and used at some location within or on the outskirts of the Texas Triangle. The Texas triangle is defined as the area encompassing Austin, Dallas-Fort Worth, Houston, and San Antonio with the latter three as the corners connected by Interstate 45, Interstate 10, and Interstate 35. The distance chosen for pipeline transport represents the average of the three sides of the Texas triangle rounded up to the nearest hundred. The percentages of hydrogen leaked during pipeline transport and end use consumption used in the model are specified in Table 7 . An average leakage rate of 0.3% is assumed during hydrogen pipeline transport [ 17 ]. Tables 8 and 9 detail the input and outputs of these end uses, and Figs. 9 , and 10 illustrate the system boundaries for the end uses applied in the two supply chains. The gas power plant stack emissions in the electricity supply chain include acenaphthene, acetaldehyde, acetic acid, arsenic ion, benzene, benzo(a)pyrene, beryllium II, butane, cadmium II, carbon monoxide, chromium III, cobalt II. dinitrogen monoxide, dioxins measured as 2,3,7,8-tetrachlorodibenzo-p-dioxin, ethane, formaldehyde, hexane, lead II, manganese II, mercury II, methane, nickel II, nitrogen oxides, PAH, particulate matter, pentane, propane, propionic acid, selenium IV, sulfur dioxide, and toluene [ 27 ]. Hydrogen fuel cell trucks have varying characteristics such as on-board hydrogen storage, battery size, fuel cell power, and range which present difficulties in systems level modeling for hydrogen based heavy-duty trucking. For example, the Xcient fuel cell truck with range of 400 km developed by Hyundai has a 72-kWh battery, 190 kW fuel cell power, and can carry 31 kg of hydrogen compressed at 350 bars. The Daimler truck, which was developed by Mercedes Benz and has a range of 1000 km, demonstrated the use of liquid hydrogen (80 kg maximum capacity) with 70 kWh battery size and 300 kW fuel cell power [ 25 ]. Consequently, this study only assesses the necessary hydrogen input for transporting 1 tonne over a km obtained with the characteristics of Xcient fuel cell truck. Table 7 Supply chain hydrogen leakage rates used in the assessment. Data obtained from Esquivel-Elizondo S., et al [ 17 ]. Percentage Pipeline 0.30% Steel 0.36% Heavy Duty Transport 1.60% Table 8 Inputs for the supply chain end uses assessed in this study and corresponding units. All upstream processes are auto linked by open LCA. Input Parameters Values Units/kg H2 Steel Manufacturing Hydrogen 50 kg Iron ore concentrate 1.6 tonne Limestone 0.2 tonne Water 58 m 3 Electricity (grid mix) 556 kWh Pipeline Transportation 400 km Heavy Duty Transport Hydrogen 0.09 kg Pipeline transportation 400 km Table 9: Supply chain outputs and corresponding units. The unit products are highlighted in red. Output Parameters Values Units Steel Manufacturing Steel 1 tonne Hydrogen leakage 0.33 kg Heavy Duty Transport Heavy duty transport 1 tonne-km Hydrogen leakage 0.0017 kg Declarations Acknowledgments This work was sponsored by GTI Energy and the Cynthia and George Mitchell Foundation. We thank Michael Lewis (The University of Texas at Austin, Center for Electromechanics) for his contributions to the project. Dr. Webber is on the board of GTI Energy and cofounder and Chairman of Idea Smiths LLC, an engineering consulting firm. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors, GTI Energy, Cynthia and George Mitchell Foundation, The University of Texas at Austin, or Idea Smiths LLC. The terms of this arrangement have been reviewed and approved by the University of Texas at Austin in accordance with its policy on objectivity in research. References International Energy Agency (2019), The Future of Hydrogen, IEA, Paris https://www.iea.org/reports/the-future-of-hydrogen, License: CC BY 4.0 The Hydrogen Council (Oct 2023), Hydrogen in Decarbonized Energy Systems, https://hydrogencouncil.com/wp-content/uploads/2023/12/Hydrogen-in-Decarbonized-Energy-Systems.pdf U.S. Department of Energy (Jan 2021), Road Map to a US Hydrogen Economy, https://www.fchea.org/us-hydrogen-study National Petroleum Council (2024). Harnessing Hydrogen A Key Element of the U.S. Energy Future. 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Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-2023-29 Basma, H., Rodriguez, F., (2022). Fuel cell electric tractor-trailers: Technology overview and fuel economy. International Council on Clean Transportation (ICCT). https://theicct.org/wp-content/uploads/2022/07/fuel-cell-tractor-trailer-tech-fuel-1-jul22.pdf Green Delta Life Cycle and Sustainability Modeling Suite. openLCA. https://www.openlca.org/openlca/ (2022). Ecoinvent database v.3.10. https://ecoinvent.org/the-ecoinvent-database/ Lewis, E., McNaul, S., Jamieson, M., Henriksen, M.S., Matthews, H. S., Walsh, L., Grove, J., Shultz, T., Skone, T. J., Stevens, R. (2022). Comparison of Commercial, State-of-the-Art, Fossil-Based Hydrogen Production Technologies. National Energy Technology Laboratory. https://doi.org/10.2172/1862910 Kroposki, B., Levene, J., Harrison, K., Sen, P.K., and Novachek, F. (2006). Electrolysis: Information and Opportunities for Electric Power Utilities. https://www.nrel.gov/docs/fy06osti/40605.pdf Saulnier, R., Minnich, K., Strugess, P.K., (2020). Water for the Hydrogen Economy. Water Smart Solutions Ltd. https://watersmartsolutions.ca/wp-content/uploads/2020/12/Water-for-the-Hydrogen-Economy_WaterSMART-Whitepaper_November-2020.pdf Antonini, C., Treyer, K., Streb A., van der Spek, M., Bauer, C., Mazzotti, M. (2020). Hydrogen production from natural gas and biomethane with carbon capture and storage – A techno-environmental analysis. Sustainable Energy Fuels, v4, 2967-2986. https://pubs.rsc.org/en/content/articlelanding/2020/se/d0se00222d Harrison, K W, Remick, R, Hoskin, A, and Martin, G D. (2010). Hydrogen Production: Fundamentals and Case Study Summaries; Preprint. United States: N. p., 2010. Web. Ivy, J. (2004). Summary of Electrolytic Hydrogen Production: Milestone Completion Report. https://www.nrel.gov/docs/fy04osti/36734.pdf GTI Energy. (2021). Hydrogen Production Emissions Calculator. https://hypec.gti.energy Argonne National Laboratory. (2022). Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model. https://greet.anl.gov Additional Declarations There is NO Competing Interest. Cite Share Download PDF Status: Published Journal Publication published 28 Feb, 2025 Read the published version in Communications Earth & Environment → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4825556","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Analysis","associatedPublications":[],"authors":[{"id":335923146,"identity":"2983b557-b9ab-43be-8685-a770dea627c7","order_by":0,"name":"Esther Goita","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYJCCAwwMNgwMzCRpOcCQxsBDkhagNYcZeIhWzc+/+ODhDzXn7fazMzA+Lqi4Z7fhAAEtkjOeJRw4cOx2cg8zA7PxjDPFyQS1GNw4Y3DgANvtZKBf2KR52xKSDQhpsQdr+XcOpIX9N+8/IrQY8PcYHDjYdsAOZAszb0OCHUEtEjfYEg6c7UtO4DnM2CzNcywhQZKQFv7+w4c/VHyzs2fvP3zwM09Ngj0fIS0MEglgKrGBgbEBzFhAUAs/RIU9jG8v30BIyygYBaNgFIw0AAA9IUbhyvHovAAAAABJRU5ErkJggg==","orcid":"","institution":"GTI Energy","correspondingAuthor":true,"prefix":"","firstName":"Esther","middleName":"","lastName":"Goita","suffix":""},{"id":335923147,"identity":"75f50d3b-b274-4090-b794-269039690e73","order_by":1,"name":"Emily A. Beagle","email":"","orcid":"","institution":"The University of Texas at Autin","correspondingAuthor":false,"prefix":"","firstName":"Emily","middleName":"A.","lastName":"Beagle","suffix":""},{"id":335923148,"identity":"22498066-5b9d-46fe-aea8-a12e9b055415","order_by":2,"name":"Ansh N. Nasta","email":"","orcid":"","institution":"GTI Energy","correspondingAuthor":false,"prefix":"","firstName":"Ansh","middleName":"N.","lastName":"Nasta","suffix":""},{"id":335923149,"identity":"34e1fba1-95b4-4ac9-b32b-03774d22a396","order_by":3,"name":"Derek L. Wissmiller","email":"","orcid":"","institution":"GTI Energy","correspondingAuthor":false,"prefix":"","firstName":"Derek","middleName":"L.","lastName":"Wissmiller","suffix":""},{"id":335923150,"identity":"ea7a0bb6-b1ce-4d56-a8b0-aebf7d7c8b78","order_by":4,"name":"Arvind Ravikumar","email":"","orcid":"https://orcid.org/0000-0001-8385-6573","institution":"The University of Texas at Austin","correspondingAuthor":false,"prefix":"","firstName":"Arvind","middleName":"","lastName":"Ravikumar","suffix":""},{"id":335923151,"identity":"f6f84773-4ff3-42be-a9cd-7e4286ae48d7","order_by":5,"name":"Michael E. Webber","email":"","orcid":"","institution":"University of Texas at Austin","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"E.","lastName":"Webber","suffix":""}],"badges":[],"createdAt":"2024-07-30 04:25:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4825556/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4825556/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s43247-025-02141-3","type":"published","date":"2025-02-28T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66677296,"identity":"00700b35-8b10-4848-adc2-13e6026f81f9","added_by":"auto","created_at":"2024-10-15 11:27:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":33659,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLife-cycle greenhouse gas emissions intensity of various hydrogen production pathways with (left) and without (right) hydrogen indirect warming effect from atmospheric releases. \u003c/strong\u003eThe inclusion of the indirect warming impacts of hydrogen increases equivalent greenhouse gas emissions intensity by less than 15% in most cases, depending on the production pathway. Results presented use GWP\u003csub\u003e100\u003c/sub\u003e. [ SMR= steam ethane Reforming; CCS= carbon\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/9bb28c8e0d92028f3ee0c79c.jpg"},{"id":66675002,"identity":"b239573b-267c-4c3f-b579-c3cee0acb504","added_by":"auto","created_at":"2024-10-15 11:03:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50215,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLife cycle carbon intensity of hydrogen production over various time frames using electrolysis production from wind, solar, or a grid mix, SMR and SMR with CCS production respectively.\u003c/strong\u003e Results shown for four climate metrics notably, GWP\u003csub\u003e20\u003c/sub\u003e (cross hatched), GWP\u003csub\u003e20\u003c/sub\u003e with hydrogen indirect impacts (solid gray), GWP\u003csub\u003e100\u003c/sub\u003e (solid white), and GWP\u003csub\u003e100\u003c/sub\u003e with hydrogen indirect impacts (solid black).\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/616d710a743192aacdc21ba2.jpg"},{"id":66675000,"identity":"1360b397-a37c-4b5e-a341-e72cc70038a8","added_by":"auto","created_at":"2024-10-15 11:03:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56732,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHydrogen leakage rate sensitivity analysis on different hydrogen production methods using high, average, and low leakage estimates\u003c/strong\u003e. The respective high, average, and low leakage rates used are as flows Electrolysis (left):9.2%, 4.6%, and 2%; SMR (center) 1%, 0.8%, and 0.5%; SMR+CCS (right): 1.5%, 0.8%, and 0.6%. The threshold below which tax credits are potentially available from the U.S. Inflation Reduction Act is indicated by the red dashed line. Results presented using GWP\u003csub\u003e100\u003c/sub\u003e.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/f8fc071131b8e17e9a31886c.jpg"},{"id":66676490,"identity":"1f934b6e-dc5d-4b2e-b61d-73b9f6ab316c","added_by":"auto","created_at":"2024-10-15 11:19:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":65527,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLife cycle emissions of hydrogen in steel manufacturing (A) and heavy-duty transport (B). \u003c/strong\u003eThe results with (dark gray) and without (light gray) considering the indirect warming impacts of hydrogen indicate a net decrease in greenhouse gas emission when using hydrogen for steel production and heavy-duty transport. The blue horizontal line represents the current average carbon intensity for each end use [22, 23,25]\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/5615d7d9b21ae3ff07634749.jpg"},{"id":66676491,"identity":"71ead0b2-6989-4568-92fb-00c44b64a821","added_by":"auto","created_at":"2024-10-15 11:19:22","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":54179,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupply chain for hydrogen production from natural gas through SMR used in this study\u003c/strong\u003e. The system boundary is shown as a red dashed line.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/856f01706260f0e4c518210b.jpg"},{"id":66675008,"identity":"4bb685ca-2fa3-4d61-9fac-2fb1a6a2248b","added_by":"auto","created_at":"2024-10-15 11:03:23","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":67398,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupply chain for hydrogen production from natural gas through SMR+CCS used in this study.\u003c/strong\u003e The system boundary is shown as a red dashed line.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/1b9ae5aaaf951a9d8d5aade4.jpg"},{"id":66676038,"identity":"f01b736a-9c11-4558-8ecc-27ec0cbf77b3","added_by":"auto","created_at":"2024-10-15 11:11:22","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":54472,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupply chain for hydrogen production through electrolysis used in this study.\u003c/strong\u003e The system boundary (shown as a red dashed line) includes upstream CAPEX emissions for electricity production.\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/b90ca27215a7a7613dc9fed7.jpg"},{"id":66675007,"identity":"d7cb9818-0a2c-4462-a478-8d45f39b7197","added_by":"auto","created_at":"2024-10-15 11:03:23","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":49421,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA comparison of life-cycle greenhouse gas emissions intensity of various hydrogen production pathways emissions. \u003c/strong\u003eComparison between\u003cstrong\u003e \u003c/strong\u003eLCA model conducted with Open LCA and the Ecoinvent database in this study (right) with existing GTI HyPEC tool based on the GREET model (left) validates the model.\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/35705e28f7a955398ba6232d.jpg"},{"id":66675006,"identity":"997f3837-ed5d-4219-a315-9b589e338b98","added_by":"auto","created_at":"2024-10-15 11:03:23","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":50129,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSteel manufacturing end use parameters and system boundary \u003c/strong\u003e(red dashed line).\u003c/p\u003e","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/ce734bed22864f9e038c9b6a.jpg"},{"id":66676041,"identity":"d69ae7d0-d471-4ba3-adb6-9e138be52d7e","added_by":"auto","created_at":"2024-10-15 11:11:23","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":31451,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeavy duty transport end use parameters and system boundary\u003c/strong\u003e (red dashed line)\u003c/p\u003e","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/dfc0df216615d799da1e8bd9.jpg"},{"id":77398269,"identity":"94cbe378-c81e-49ca-b221-a4a68b33ea15","added_by":"auto","created_at":"2025-02-28 08:06:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1659599,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4825556/v1/6d48f633-3456-4a21-9243-e1d42f0262dc.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Effect of Hydrogen Leakage on the Life Cycle Climate Impacts of Hydrogen Supply Chains","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eHydrogen is a promising low-carbon and scalable option to decarbonize hard-to-abate industries such as iron and steel production, heavy manufacturing, and heavy-duty transportation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As of August 2024, 61 countries including the United States (US) have official national hydrogen strategies [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Other countries, including China, have included hydrogen in their decarbonization and energy plans [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Recent energy policies in the US, such as the regional clean hydrogen hubs and the Clean Hydrogen Production Tax Credit in the \u003cem\u003eInflation Reduction Act\u003c/em\u003e (IRA), are set to dramatically increase the production and use of clean hydrogen [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Thus, various analyses have projected that hydrogen production and consumption volumes could increase from under 100 Megatonnes (Mt) in 2022 to 530Mt650Mt by 2050 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. As governments worldwide have pledged billions in investments toward hydrogen development and expansion quantifying hydrogen greenhouse gas emissions would be beneficial to understanding life cycle climate impacts. For the IRA\u0026rsquo;s Clean Hydrogen Production Tax Credit, the tax credits issued are dependent on the life cycle greenhouse gas emission intensity of the hydrogen production process in kilograms pf CO\u003csub\u003e2\u003c/sub\u003e- equivalent per kilogram of hydrogen (kgCO\u003csub\u003e2\u003c/sub\u003ee/kgH\u003csub\u003e2\u003c/sub\u003e). Supply chains with lifecycle emissions below 4 kgCO\u003csub\u003e2\u003c/sub\u003ee/kgH\u003csub\u003e2\u003c/sub\u003e will qualify for the most generous support [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The tax credit requires a well-to-gate lifecycle analysis including emissions associated with feedstock growth, gathering, extraction, processing, and delivery to a hydrogen production facility and emissions associated with the hydrogen production process itself. The hydrogen focused Greenhouse gases, Regulated Emissions, and Energy use in Transportation model (45VH2-GREET) developed by Argonne National Laboratory was designated as the official tool to quantify emissions for tax credit applicants. The 45VH2-GREET model, however, does not account for hydrogen fugitive emissions and leakage nor does it include all hydrogen production methods that may be economically viable. This absence can unintentionally impede innovations that are not currently encompassed within the established repertoire of 45VH2-GREET. Furthermore, the 45VH2-GREET model and, subsequently, the clean hydrogen tax credit assessments do not consider downstream emissions and, therefore, omit a crucial aspect of hydrogen's emission reduction capability through the displacement of current fossil fuels.\u003c/p\u003e \u003cp\u003eThough hydrogen itself is not a greenhouse gas, it interacts with the hydroxyl radical, which is the primary sink for methane. This interaction, increases the atmospheric lifetime of methane, a potent greenhouse gas, and thus, hydrogen indirectly increases radiative forcing [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In the troposphere, methane oxidation leads to the production of formaldehyde, which produces hydrogen through photolysis. The natural presence accompanied by increased anthropogenic injection of hydrogen in the atmosphere that can occur through leakage may accentuate this adverse atmospheric interaction. Furthermore, certain hydrogen production pathways such as pyrolysis and steam methane reforming (SMR) rely on a methane feedstock, which can also be leaked, effectively increasing the overall stockpile of atmospheric methane. Moreover, through its interaction with hydroxyl, hydrogen increases tropospheric ozone and produces water vapor which also acts as a greenhouse gas through radiative trapping in the stratosphere [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThere are uncertainties across the literature concerning the quantification of hydrogen sinks and global hydrogen leakage rates. Gaseous hydrogen is more reactive and has a smaller molecular cross-section than methane and is therefore prone to leak [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The leakage rates available in previous studies are obtained from assumptions, calculations, lab experiments, and simulations [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These estimates are not uniform across hydrogen production technologies or supply chains. Most studies utilize hydrogen leakage rates ranging from 1\u0026ndash;10% to produce estimates of its climate implications. A recent study synthesizing known hydrogen emission rates reported present and future value chain emissions varying between 0.2\u0026ndash;20% [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In the effort to obtain more accurate hydrogen leakage rates the US Department of Energy (DOE) recently announced a \u003cspan\u003e$\u003c/span\u003e20\u0026nbsp;million detection and quantification development initiative [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Furthermore, there is a lack of consensus on hydrogen\u0026rsquo;s global warming potential due to its relatively shorter lifespan of 2.5 years compared to other greenhouse gases [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The commonly encountered metrics are global warming potential over 100 years and 20 years (GWP\u003csub\u003e100\u003c/sub\u003e, GWP\u003csub\u003e20\u003c/sub\u003e), and global temperature potential over 100 years and 20 years (GTP\u003csub\u003e100\u003c/sub\u003e, GTP\u003csub\u003e20\u003c/sub\u003e). The values reported for hydrogen are 13\u0026thinsp;\u0026plusmn;\u0026thinsp;5 for GWP\u003csub\u003e100\u003c/sub\u003e, 40\u0026thinsp;\u0026plusmn;\u0026thinsp;24 for GWP\u003csub\u003e20\u003c/sub\u003e, 2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 for GTP\u003csub\u003e100\u003c/sub\u003e, and 18\u0026thinsp;\u0026plusmn;\u0026thinsp;23 for GTP\u003csub\u003e20\u003c/sub\u003e [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Hydrogen Council conducted a life cycle assessment (LCA) that considered various pathways envisioned for future hydrogen value chains for 2030 and 2050 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The pathways in the study consist of four autothermal reforming (ATR) plants coupled with 98% capture of total emitted carbon and four electrolysis pathways with onshore or offshore wind and/or solar energy [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The end-use applications in their analysis include light-duty vehicle transport, shipping, industrial heat, power generation, fertilizer manufacturing, public transport, and steel production. The analysis includes a comparison between the various hydrogen pathways used and alternative fossil fuel-based or electric-based pathways as appropriate. The results of the study indicated that the effects of using hydrogen range from 60\u0026ndash;100% reduction in warming for the respective supply chains relative to current methods, assuming a carbon intensity reduction of the global grid mix [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Although this analysis included operational hydrogen venting at production, it omitted fugitive emissions along the supply chain and the indirect warming effects of hydrogen.\u003c/p\u003e \u003cp\u003eRecently, researchers from the Environmental Defense Fund (EDF) conducted a study on the life cycle of hydrogen deployment pathways in which hydrogen leakage and warming effect were taken into consideration [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The study was based on the LCA completed by the Hydrogen Council in 2021 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], but only considered four end uses, notably light-duty vehicle transport, shipping, industrial heat, and power generation, and focused on impacts in 2050. Additionally, carbon capture on ATR hydrogen production was assumed to range from 60\u0026ndash;98%. A hydrogen leakage range of 1\u0026ndash;10% was assumed across the value chain, and five levels of methane leakage were considered: \u0026mdash;extreme low (0.01%), low (0.6%), medium (0.9%), high (2.1%), and extreme high (5.4%). The comparisons between the hydrogen pathways and fossil fuel alternatives were completed using the technology warming potential (over 10, 20, 50 years), which measures the effect of switching from one technology to another, and GWP (over 20 and 100 years). Under extreme cases, the use of hydrogen can produce a 46% increase or a 93% decrease in warming, respectively. This range suggests that better understanding of hydrogen life cycle emissions and warming impacts and appropriate supply chain and end use selection is critical for hydrogen use to yield meaningful climate benefits. Furthermore, electrolysis production pathways appear to be the most consistent in emission reduction (\u0026gt;\u0026thinsp;60%) regardless of hydrogen leakage and warming effects over different time scales [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Despite its thoroughness in terms of hydrogen emissions consideration this study omits two main end uses for hydrogen, notably steel production and heavy-duty transport, which are examined in this work.\u003c/p\u003e \u003cp\u003eCurrent steel production is responsible for 9% of worldwide carbon dioxide emissions, averaging 1.85 tonne (1850 kg) of CO\u003csub\u003e2\u003c/sub\u003e per tonne of steel produced [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Proposed decarbonization strategies for the steel industry include substituting hydrogen and direct reduction for coal used in blast furnaces. Additionally, renewable energy or hydrogen combustion could be used for process heat to reduce or eliminate emissions. Similarly, hydrogen has been proposed as an alternative fuel to reduce heavy duty trucking emissions that currently range from approximately 0.1 to 0.3 kgCO\u003csub\u003e2\u003c/sub\u003ee per tonne-km for conventional vehicles operating with diesel [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this work, we aim to fill the existing knowledge gap by including leakage rates and global warming potential to quantify the life cycle climate effects from 1) different hydrogen production pathways then 2) using that hydrogen as an alternative to traditional energy sources for end uses previously omitted in literature. Given the projected growth of hydrogen in the energy mix to meet 2050 decarbonization goals and the concerns that hydrogen might indirectly cause warming that undermines progress towards mitigating climate change, it is valuable to comprehensively assess the impacts of the full life cycle emissions and indirect warming effects of hydrogen. This approach will be demonstrated with novel LCAs of a few sample hydrogen production pathways (electrolysis with grid-tied electricity, electrolysis with carbon-free electricity, SMR, and SMR with CCS) and product manufacturing of steel and heavy-duty transport.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eProduction:\u003c/h2\u003e \u003cp\u003eThis study used hydrogen global warming potentials from Hauglustaine., et al [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. An initial 2% hydrogen leakage was applied to all the production methods to assess the effects of the other variables. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the results of this standardized leakage reported in kgCO\u003csub\u003e2\u003c/sub\u003ee / kgH\u003csub\u003e2\u003c/sub\u003e using GWP\u003csub\u003e100\u003c/sub\u003e of hydrogen. The difference between the overall greenhouse gas intensity of hydrogen production with and without indirect warming from hydrogen leakage is \u0026lt;\u0026thinsp;0.5 kgCO\u003csub\u003e2\u003c/sub\u003ee /kgH\u003csub\u003e2\u003c/sub\u003e for all pathways considered, which represents less than a 15% increase for electrolysis with grid-tied electricity, steam methane reforming (SMR), and SMR with carbon capture and sequestration (CCS). Consequently, though there is a slight increase in CO\u003csub\u003e2\u003c/sub\u003ee emissions when hydrogen\u0026rsquo;s indirect warming effects are introduced into the model, the carbon intensity of the electricity source and carbon intensity of the production process have a much greater bearing on overall warming potential of hydrogen production.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows an assessment of the sensitivity to different climate metrics of hydrogen indirect warming effects over time with uniform 2% leakage for all the production methods. The increase in carbon intensity introduced solely by hydrogen warming effects (as opposed to methane) over different time frames is presented through contrast between the base scenario and the inclusion of hydrogen GWP. On average, there is a 0.5 kgCO\u003csub\u003e2\u003c/sub\u003ee /kgH\u003csub\u003e2\u003c/sub\u003e difference between GWP\u003csub\u003e100\u003c/sub\u003e and GWP\u003csub\u003e20\u003c/sub\u003e values. With the relatively shorter lifetime of hydrogen, such results align with previous studies that concluded the climate effects of hydrogen are slightly attenuated over time [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAn assessment of current reported leakage rate projections for 2050 by Esquivel-Elizondo S., et al [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], revealed considerable variation. Electrolysis with renewables has the highest reported leakage rates varying between 2.0% and 9.2%. These relatively high values are due to venting and purging that occur for safety reasons during the electrolysis process. Unabated SMR and SMR coupled with CCS have leakage rates that vary between 0.5% and 1.0%. The detailed leakage rates used for this analysis are outlined in the \u003cspan refid=\"Sec6\" class=\"InternalRef\"\u003emethods\u003c/span\u003e section.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that despite relatively high leakage rates, electrolysis had the lowest emissions for the lower and average scenarios and remained comparable in emissions to SMR with CCS even with an upper limit leakage rate. On the other hand, unabated SMR, even with lower hydrogen leakage rates, has the highest overall emissions (partly because of fugitive methane emissions in its supply chain) and fails to meet the DOE clean hydrogen standard of 4.0 kgCO\u003csub\u003e2\u003c/sub\u003ee /kgH\u003csub\u003e2\u003c/sub\u003e for well-to-gate life cycle greenhouse emissions. It must be noted our analysis includes a greater scope of emissions then outlined in the 45V guidance (view methods).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSteel Production and Heavy-Duty Transport Case Studies:\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB show the decrease in emissions observed with the use of hydrogen for steel production and heavy-duty transport respectively. The results from the steel supply chain LCA include hydrogen leakage and associated indirect warming effects at each stage of the supply chain (production, transportation, and end use). The assessment reveals a minimum 800 kgCO\u003csub\u003e2\u003c/sub\u003ee per tonne of steel production (t\u003csub\u003esteel\u003c/sub\u003e decrease in the carbon intensity of steel production using hydrogen compared to current fossil fuel-based methods with an average carbon intensity of 1850 kgCO\u003csub\u003e2\u003c/sub\u003ee/t steel [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Further reduction is observed with decreased carbon intensity of the hydrogen production method. A decrease in emissions ranging from 0.1\u0026ndash; 0.17 kgCO\u003csub\u003e2\u003c/sub\u003ee per tonne-kilometer (t-km) is observed with hydrogen based heavy duty trucking when using electrolysis powered by wind or solar energy. An increase in emissions (0.79 kgCO\u003csub\u003e2\u003c/sub\u003ee /t-km) for heavy duty transportation is observed when using hydrogen from unabated SMR.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIncluding hydrogen leakage and its associated impact in LCA models only increases the total climate impact of hydrogen production by 0.5 kgCO\u003csub\u003e2\u003c/sub\u003ee / kgH\u003csub\u003e2\u003c/sub\u003e. These findings suggest that while hydrogen does act as an indirect greenhouse gas, other sources of emissions along the supply chain, including electricity production, fugitive methane emissions, and process emissions, are more significant in the overall climate impact of hydrogen production. Furthermore, even with high hydrogen leakage rates, electrolysis powered by renewables meets the U.S. federal standard of clean hydrogen production with lifecycle emissions intensity below 4 kgCO\u003csub\u003e2\u003c/sub\u003ee /kgH\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eMoreover, by incorporating median leakage values and hydrogen GWP into an existing steel production process it was evident that there is a significant decrease in emissions per tonne of steel produced when shifting from conventional fossil fuel to hydrogen-based steel production, regardless of the production pathway for the hydrogen. In heavy-duty transportation, hydrogen in place of diesel can reduce or exacerbate climate impacts depending on the production pathway. Hydrogen produced via electrolysis with renewables (wind or solar) has lower climate impact while hydrogen produced via SMR and SMR with CCS has a similar or higher carbon intensity compared to current heavy-duty fuels.\u003c/p\u003e \u003cp\u003eOur finding is a need for a nuanced approach in evaluating hydrogen's role in mitigating climate change effects. While hydrogen holds promise as a cleaner energy source, careful consideration of its supply chain, leakage, and indirect climate effects is crucial to ensure meaningful contributions to global decarbonization goals.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eThe goal of this assessment is to quantify the impact of hydrogen's indirect climate effects and leakage rates on the life cycle emissions of different hydrogen production methods and end uses. We use a life cycle assessment (LCA) model constructed through the Open LCA software and the IPCC 2021 impact assessment method to estimate greenhouse gas emissions intensity of various hydrogen production pathways [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The functional unit is the product of concern, which in this case is hydrogen or the concerned end use (highlighted in red in the data tables). Every phase of the life cycle is divided into processes, which are subsequently interconnected through intermediate flows, thereby forming a product system. The data used to conduct this analysis was obtained from the Ecoinvent database [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], a sustainability assessment life cycle inventory, in addition to available hydrogen leakage rates obtained from a study conducted by Esquivel-Elizondo S., et al [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The GWP\u003csub\u003e100\u003c/sub\u003e, and GWP\u003csub\u003e20\u003c/sub\u003e of hydrogen obtained from a study conducted by Hauglustaine., et al [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e were incorporated in the assessment. These values were used in order to understand the warming potential of each production pathway with associated leakage and indirect hydrogen climate impact over time.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGWP values for hydrogen from Hauglustaine., et al [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] in this table were added to the IPCC 2021 impact assessment method and used in this study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClimate Change Metric\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGWP\u003csub\u003e100\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGWP\u003csub\u003e20\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eProduction:\u003c/h3\u003e\n\u003cp\u003eThe production methods taken into consideration in this analysis are unabated SMR (SMR without CCS), SMR coupled with 96% CCS, electrolysis using a grid mix supply of electricity, electrolysis using solar (equivalent kWh not hourly matched), and electrolysis using wind energy (equivalent kWh not hourly matched). Figures\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, and \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e display the system boundaries of the production methods used. The system boundary for the SMR pathways begins with the raw material production and transport of natural gas, deionized water, metallurgical aluminum oxide, magnesium oxide, copper oxide, quicklime, chromium oxide, zinc oxide, zeolite powder, molybdenum trioxide, silica sand, and portafer. Additionally, the embedded emissions of the chemical factory and storage tank are included. The natural gas is sourced from markets in the United States (U.S.), and the remaining inputs are sourced from the global market. The system boundary for the electrolysis pathways begins with deionized water, the designated electricity supplier (grid, solar, wind, or renewable mix) and their capital expenditure (CAPEX) emissions. The electricity for electrolysis is sourced from the Texas Regional Entity (TRE) for grid mix and wind electrolysis and from the Western Electricity Coordinating Council (WECC) for solar (photovoltaic) electrolysis. For all the production processes, the system boundaries stop after the production of hydrogen (that is, at the system gate). Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e detail the inputs and outputs of each production process considered in this study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInput parameters for SMR and SMR\u0026thinsp;+\u0026thinsp;CCS production pathways with corresponding units. Oxides: Aluminum oxide, Chromium oxide, Copper oxide, Magnesium oxide, Molybdenum trioxide, Zinc oxide. Natural gas, water oxides, nickel, portafer, quisklime, silica, and zeolite powder data sourced from Ecoinvent. Electricity input for CCS was obtained from NETL [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInput Parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValues\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnits/kg\u003csub\u003eH2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNatural Gas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003em\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWater (cooling)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003em\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeionized water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOxides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.40E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNickel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePortafer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.00E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuicklime\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.80E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSilica\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.20E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZeolite powder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.00E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectricity (CCS only)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekWh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u003c/strong\u003e Output parameters for SMR and SMR+CCS production pathways with corresponding units. Hydrogen leakage data is detailed in Table 7. The remaining data is sourced from Ecoinvent. The hydrogen leakage is emitted to the atmosphere. Stack emissions include acetaldehyde, acetic acid, benzene, benzoapyrene, butane, carbon dioxide, carbon monoxide, dinitrogen monoxide, formaldehyde, mercury, methane, nitrogen oxides, polycyclic aromatic hydrocarbons (PAH), particulate matter, pentane, propane, propionic oxide, sulfur dioxide, and toluene.\u003c/p\u003e\n\u003ctable style=\"width:470.1pt;border-collapse:collapse;border:none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170.75pt;border: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eOutput Parameters\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142.65pt;border-top: 1pt solid black;border-right: 1pt solid black;border-bottom: 1pt solid black;border-image: initial;border-left: none;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eValues\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156.7pt;border-top: 1pt solid black;border-right: 1pt solid black;border-bottom: 1pt solid black;border-image: initial;border-left: none;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eUnits\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170.75pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003eStack emissions\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003e5.7E-04\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156.7pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003ekg\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170.75pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:red;\"\u003eHydrogen\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:red;\"\u003e1\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156.7pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:red;\"\u003ekg\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170.75pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003eCarbon dioxide\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003e9\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156.7pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003ekg\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170.75pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003eCarbon dioxide (with CCS)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003e0.34\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156.7pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003ekg\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 170.75pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003eHydrogen Leakage\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 142.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003evaries\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156.7pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16.65pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003ekg\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInput parameters for electrolysis production pathways with corresponding units. The electricity input is obtained from the National Energy Technology Laboratory [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and the deionized water input is obtained from WaterSMART Ltd [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInput Parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValues\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnits\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElectricity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekWh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeionized water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 5:\u003c/strong\u003e Output parameters for electrolysis production pathways with corresponding units.\u003c/p\u003e\n\u003ctable style=\"border-collapse:collapse;border:none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180.5pt;border: 1pt solid black;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eOutput Parameters\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183.3pt;border-top: 1pt solid black;border-right: 1pt solid black;border-bottom: 1pt solid black;border-image: initial;border-left: none;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eValues\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.95pt;border-top: 1pt solid black;border-right: 1pt solid black;border-bottom: 1pt solid black;border-image: initial;border-left: none;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eUnits\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180.5pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:red;\"\u003eHydrogen\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183.3pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:red;\"\u003e1\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.95pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cstrong\u003e\u003cspan style=\"color:red;\"\u003ekg\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 180.5pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003eHydrogen Leakage\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 183.3pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003evaries\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.95pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 18.05pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-indent:.25in;'\u003e\u003cspan style=\"color:black;\"\u003ekg\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e \u003cp\u003eThe data for the SMR production processes (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) are based on an SMR plant assessed by Antonini., et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The natural gas is pressurized at 200 bars. The hydrogen yield of the process is enhanced with a water gas shift reaction. In the unabated SMR process, the carbon dioxide exits the plant with the flue gas from the furnace. A separate model for CCS was not built for this LCA, rather a 96.2% capture rate was applied to the total amount of carbon dioxide emitted from the base unabated SMR process, and the subsequent electricity requirements were added as additional input. The electricity input value calculations were based on findings from the National Energy Technology Laboratory [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The electricity and water input values for electrolysis were obtained from reports published by the National Renewable Energy Laboratory [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This analysis does not take into account specific variations between PEM and alkaline electrolyzers, as the differences are small.\u003c/p\u003e \u003cp\u003eAn upper limit, lower limit, and average leakage rates were assessed for each production method to gauge the sensitivity of supply chain greenhouse gas emissions intensity to leakage rates. These leakage rates are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. An assessment of current reported hydrogen leakage rate projections for 2050 by Esquivel-Elizondo S., et al [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], revealed considerable variation. Electrolysis with renewables has the highest reported leakage rates varying between 2.0% (lower limit) and 9.2% (upper limit). These relatively high values are due to venting and purging that occur for safety reasons as a result of oxygen build up during the electrolysis process. Unabated SMR and SMR with CCS have leakage rates that vary between 0.5% and 1.0%. There are limitations in the leakage values used as they are obtained from simulations or models. There is little to no direct measurement data available on hydrogen leakage. Methane leakage during the SMR processes is \u0026lt;\u0026thinsp;1% (default in the Ecoinvent database).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHydrogen leakage rates used for the sensitivity analysis. Data obtained from Esquivel-Elizondo S. et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Average value represents value calculated for taking the average of 2050 leakage rate predictions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeakage rate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSMR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eSMR\u0026thinsp;+\u0026thinsp;CCS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eElectrolysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUpper limit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower limit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eProduction Model Validation:\u003c/h2\u003e \u003cp\u003eA validation was conducted by comparing the results from the models in this study to the Hydrogen Production Emissions Calculator (HyPEC) tool version 1.0, which is based on the GREET model version 2021 [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Figure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e shows the results of this validation, excluding the indirect warming effect of hydrogen. At the time of this analysis, the 45V-GREET had yet to be made available. The difference between the models for all the production pathways considered is less than 2 kgCO\u003csub\u003e2\u003c/sub\u003ee / kgH\u003csub\u003e2\u003c/sub\u003e. In both models, upstream methane emissions are less than 1%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSteel Case and Heavy-Duty Transport Case Studies:\u003c/h3\u003e\n\u003cp\u003eThe steel and heavy-duty transport pathways selected are based in Texas to mimic future scenarios as one of the DOE hydrogen hubs, Gulf Coast Hydrogen Hub (HyVelocity), is expected to be constructed in Houston. A hydrogen pipeline transportation distance of 400km is assumed with the scenario that the hydrogen would be produced in Houston and used at some location within or on the outskirts of the Texas Triangle. The Texas triangle is defined as the area encompassing Austin, Dallas-Fort Worth, Houston, and San Antonio with the latter three as the corners connected by Interstate 45, Interstate 10, and Interstate 35. The distance chosen for pipeline transport represents the average of the three sides of the Texas triangle rounded up to the nearest hundred. The percentages of hydrogen leaked during pipeline transport and end use consumption used in the model are specified in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. An average leakage rate of 0.3% is assumed during hydrogen pipeline transport [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Tables\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e detail the input and outputs of these end uses, and Figs.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, and \u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e illustrate the system boundaries for the end uses applied in the two supply chains. The gas power plant stack emissions in the electricity supply chain include acenaphthene, acetaldehyde, acetic acid, arsenic ion, benzene, benzo(a)pyrene, beryllium II, butane, cadmium II, carbon monoxide, chromium III, cobalt II. dinitrogen monoxide, dioxins measured as 2,3,7,8-tetrachlorodibenzo-p-dioxin, ethane, formaldehyde, hexane, lead II, manganese II, mercury II, methane, nickel II, nitrogen oxides, PAH, particulate matter, pentane, propane, propionic acid, selenium IV, sulfur dioxide, and toluene [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Hydrogen fuel cell trucks have varying characteristics such as on-board hydrogen storage, battery size, fuel cell power, and range which present difficulties in systems level modeling for hydrogen based heavy-duty trucking. For example, the Xcient fuel cell truck with range of 400 km developed by Hyundai has a 72-kWh battery, 190 kW fuel cell power, and can carry 31 kg of hydrogen compressed at 350 bars. The Daimler truck, which was developed by Mercedes Benz and has a range of 1000 km, demonstrated the use of liquid hydrogen (80 kg maximum capacity) with 70 kWh battery size and 300 kW fuel cell power [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Consequently, this study only assesses the necessary hydrogen input for transporting 1 tonne over a km obtained with the characteristics of Xcient fuel cell truck.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSupply chain hydrogen leakage rates used in the assessment. Data obtained from Esquivel-Elizondo S., et al [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePipeline\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.30%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSteel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.36%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHeavy Duty Transport\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eInputs for the supply chain end uses assessed in this study and corresponding units. All upstream processes are auto linked by open LCA.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInput Parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValues\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnits/kg\u003csub\u003eH2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eSteel Manufacturing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydrogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIron ore concentrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003etonne\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLimestone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003etonne\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWater\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003em\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElectricity (grid mix)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ekWh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePipeline Transportation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ekm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHeavy Duty Transport\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydrogen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ekg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePipeline transportation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ekm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \n\u003cp\u003e\u003cstrong\u003eTable 9:\u003c/strong\u003e Supply chain outputs and corresponding units. The unit products are highlighted in red.\u003c/p\u003e\n\u003ctable style=\"border-collapse:collapse;border:none;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 119.1pt;border: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115.55pt;border-top: 1pt solid black;border-right: 1pt solid black;border-bottom: 1pt solid black;border-image: initial;border-left: none;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eOutput Parameters\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114.65pt;border-top: 1pt solid black;border-right: 1pt solid black;border-bottom: 1pt solid black;border-image: initial;border-left: none;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eValues\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118.2pt;border-top: 1pt solid black;border-right: 1pt solid black;border-bottom: 1pt solid black;border-image: initial;border-left: none;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cstrong\u003e\u003cspan style=\"color:black;\"\u003eUnits\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 119.1pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;'\u003e\u003cspan style=\"color:black;\"\u003eSteel Manufacturing\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115.55pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:red;\"\u003eSteel\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:red;\"\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118.2pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:red;\"\u003etonne\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115.55pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:black;\"\u003eHydrogen leakage\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:black;\"\u003e0.33\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118.2pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:black;\"\u003ekg\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 119.1pt;border-right: 1pt solid black;border-bottom: 1pt solid black;border-left: 1pt solid black;border-image: initial;border-top: none;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;'\u003e\u003cspan style=\"color:black;\"\u003eHeavy Duty Transport\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115.55pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:red;\"\u003eHeavy duty transport\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:red;\"\u003e1\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118.2pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:red;\"\u003etonne-km\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 115.55pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:black;\"\u003eHydrogen leakage\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114.65pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:black;\"\u003e0.0017\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118.2pt;border-top: none;border-left: none;border-bottom: 1pt solid black;border-right: 1pt solid black;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin-right:0in;margin-left:0in;font-size:16px;font-family:\"Calibri\",sans-serif;margin:0in;text-align:center;'\u003e\u003cspan style=\"color:black;\"\u003ekg\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis work was sponsored by GTI Energy and the Cynthia and George Mitchell Foundation. We thank Michael Lewis (The University of Texas at Austin, Center for Electromechanics) for his contributions to the project. Dr. Webber is on the board of GTI Energy and cofounder and Chairman of Idea Smiths LLC, an engineering consulting firm. Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the sponsors, GTI Energy, Cynthia and George Mitchell Foundation, The University of Texas at Austin, or Idea Smiths LLC. The terms of this arrangement have been reviewed and approved by the University of Texas at Austin in accordance with its policy on objectivity in research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eInternational Energy Agency (2019), The Future of Hydrogen, IEA, Paris https://www.iea.org/reports/the-future-of-hydrogen, License: CC BY 4.0\u003c/li\u003e\n\u003cli\u003eThe Hydrogen Council (Oct 2023), Hydrogen in Decarbonized Energy Systems, https://hydrogencouncil.com/wp-content/uploads/2023/12/Hydrogen-in-Decarbonized-Energy-Systems.pdf \u003c/li\u003e\n\u003cli\u003eU.S. Department of Energy (Jan 2021), Road Map to a US Hydrogen Economy, https://www.fchea.org/us-hydrogen-study\u003c/li\u003e\n\u003cli\u003eNational Petroleum Council (2024). Harnessing Hydrogen A Key Element of the U.S. Energy Future. 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The Long-Term Strategy of the United States: Pathways to Net-Zero Greenhouse Gas Emissions by 2050(Nov 2021). https://www.whitehouse.gov/wp-content/uploads/2021/10/US-Long-Term-Strategy.pdf\u003c/li\u003e\n\u003cli\u003eBertagni, M. B., Pacala, S. W., Paulot, F., \u0026amp; Porporato, A. (2022). Risk of the hydrogen economy for atmospheric methane. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-35419-7\u003c/li\u003e\n\u003cli\u003eOcko, I., and Hamburg, S., (Feb 2022) Climate Consequences of Hydrogen Emissions, Atmospheric Chemistry and Physics, https://doi.org/10.5194/acp-22-9349-2022.\u003c/li\u003e\n\u003cli\u003eKirschke, S., Bousquet, P., Ciais, P., Saunois, M., Canadell, J. G., Dlugokencky, E. J., Bergamaschi, P., Bergmann, D., Blake, D. R., Bruhwiler, L., Cameron-Smith, P., Castaldi, S., Chevallier, F., Feng, L., Fraser, A., Heimann, M., Hodson, E. L., Houweling, S., Josse, B., \u0026hellip; Zeng, G. (2013). Three decades of global methane sources and sinks. Nature Geoscience, 6(10), 813\u0026ndash;823. https://doi.org/10.1038/ngeo1955.\u003c/li\u003e\n\u003cli\u003eShaddix, C. (2022). An Assessment of Current Understanding of the Greenhouse Gas Impacts from H2 Emissions. Retrieved from https://doi.org/10.2172/1884932 \u003c/li\u003e\n\u003cli\u003eThawani, B., Hazael, R., Critchley, R. (2024). Numerical modelling of hydrogen leakages in confined spaces for domestic applications. International Journal of Hydrogen Energy. https://doi.org/10.1016/j.ijhydene.2023.12.279 \u003c/li\u003e\n\u003cli\u003eEsquivel-Elizondo, S., Hormaza Mejia, A., Sun ,T., Shrestha, E., Hamburg, SP., \u0026amp; Ocko, IB. (2023). Wide range in estimates of hydrogen emissions from infrastructure, Front. Energy Res. 11:1207208. doi: 10.3389/fenrg.2023.1207208 \u003c/li\u003e\n\u003cli\u003eAdvanced Research Projects Agency-Energy (2024). U.S. Department of Energy Announces $20 Million to Develop Cost-Effective, Highly Accurate Hydrogen Detection and Quantification Technologies. Press Release. https://arpa-e.energy.gov/news-and-media/press-releases/us-department-energy-announces-20-million-develop-cost-effective\u003c/li\u003e\n\u003cli\u003eHauglustaine, D., Paulot, F., Collins, W., Derwent, R., Sand, M., \u0026amp; Boucher, O. (2022). Climate benefit of a future hydrogen economy. Communications Earth \u0026amp; Environment, 3(1). https://doi.org/10.1038/s43247-022-00626-z\u003c/li\u003e\n\u003cli\u003eThe Hydrogen Council. (2021). Hydrogen Decarbonization Pathways: A Life-Cycle Assessment. https://hydrogencouncil.com/wp-content/uploads/2021/04/Hydrogen-Council-Report_Decarbonization-Pathways_Part-1-Lifecycle-Assessment.pdf\u003c/li\u003e\n\u003cli\u003eSun, T., Sherestha, E., Hamburg, S. P., Kupers, R., Ocko, I. B. (2024). Climate Impacts of Hydrogen and Methane Emissions can Considerably Reduce the Climate Benefits across Key Hydrogen Use Cases and Time Scales. Environmental Science \u0026amp; Technology. https://doi.org/10.1021/acs.est.3c09030 \u003c/li\u003e\n\u003cli\u003eKurrer, C., (2020). European Parliament Briefing. The potential of hydrogen for decarbonizing steel production. https://www.europarl.europa.eu/RegData/etudes/BRIE/2020/641552/EPRS_BRI(2020)641552_EN.pdf \u003c/li\u003e\n\u003cli\u003eU.S. Environmental Protection Agency. (2023, September 12), Emission Factors for Greenhouse Gas Inventories. https://www.epa.gov/system/files/documents/2023-03/ghg_emission_factors_hub.pdf\u003c/li\u003e\n\u003cli\u003eWarwick, et al. (March 2023). Atmospheric composition and climate impacts of a future hydrogen economy. Atmospheric Chemistry and Physics. https://doi.org/10.5194/acp-2023-29 \u003c/li\u003e\n\u003cli\u003eBasma, H., Rodriguez, F., (2022). Fuel cell electric tractor-trailers: Technology overview and fuel economy. International Council on Clean Transportation (ICCT). https://theicct.org/wp-content/uploads/2022/07/fuel-cell-tractor-trailer-tech-fuel-1-jul22.pdf\u003c/li\u003e\n\u003cli\u003eGreen Delta Life Cycle and Sustainability Modeling Suite. openLCA. https://www.openlca.org/openlca/ (2022).\u003c/li\u003e\n\u003cli\u003eEcoinvent database v.3.10. https://ecoinvent.org/the-ecoinvent-database/ \u003c/li\u003e\n\u003cli\u003eLewis, E., McNaul, S., Jamieson, M., Henriksen, M.S., Matthews, H. S., Walsh, L., Grove, J., Shultz, T., Skone, T. J., Stevens, R. (2022). Comparison of Commercial, State-of-the-Art, Fossil-Based Hydrogen Production Technologies. National Energy Technology Laboratory. https://doi.org/10.2172/1862910\u003c/li\u003e\n\u003cli\u003eKroposki, B., Levene, J., Harrison, K., Sen, P.K., and Novachek, F. (2006). Electrolysis: Information and Opportunities for Electric Power Utilities. https://www.nrel.gov/docs/fy06osti/40605.pdf \u003c/li\u003e\n\u003cli\u003eSaulnier, R., Minnich, K., Strugess, P.K., (2020). Water for the Hydrogen Economy. Water Smart Solutions Ltd. https://watersmartsolutions.ca/wp-content/uploads/2020/12/Water-for-the-Hydrogen-Economy_WaterSMART-Whitepaper_November-2020.pdf\u003c/li\u003e\n\u003cli\u003eAntonini, C., Treyer, K., Streb A., van der Spek, M., Bauer, C., Mazzotti, M. (2020). Hydrogen production from natural gas and biomethane with carbon capture and storage \u0026ndash; A techno-environmental analysis. Sustainable Energy Fuels, v4, 2967-2986. https://pubs.rsc.org/en/content/articlelanding/2020/se/d0se00222d\u003c/li\u003e\n\u003cli\u003eHarrison, K W, Remick, R, Hoskin, A, and Martin, G D. (2010). Hydrogen Production: Fundamentals and Case Study Summaries; Preprint. United States: N. p., 2010. Web.\u003c/li\u003e\n\u003cli\u003eIvy, J. (2004). Summary of Electrolytic Hydrogen Production: Milestone Completion Report. https://www.nrel.gov/docs/fy04osti/36734.pdf \u003c/li\u003e\n\u003cli\u003eGTI Energy. (2021). Hydrogen Production Emissions Calculator. https://hypec.gti.energy \u003c/li\u003e\n\u003cli\u003eArgonne National Laboratory. (2022). Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model. https://greet.anl.gov \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4825556/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4825556/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHydrogen is of interest for decarbonizing hard-to-abate sectors because it does not produce carbon dioxide when combusted. However, hydrogen has indirect warming effects. In this work, we conducted a life cycle assessment of electrolysis and steam methane reforming to assess their emissions while considering hydrogen\u0026rsquo;s indirect warming effects. We find that the primary factors influencing life cycle emissions are the production method and related feedstock emissions, rather than the hydrogen leakage and the indirect warming potential of hydrogen. A comparison between fossil fuel-based and hydrogen-based steel production and heavy-duty transportation showed a reduction in greenhouse gas emissions, of approximately 800 to more than 1400 kgCO\u003csub\u003e2\u003c/sub\u003ee per tonne of steel and 0.1 to 0.17 kgCO\u003csub\u003e2\u003c/sub\u003ee per tonne-km of cargo. While any hydrogen production pathway reduces greenhouse gas emissions for steel, this is not the case for heavy-duty transportation. Therefore, we recommend a nuanced approach in choosing application areas for hydrogen.\u003c/p\u003e","manuscriptTitle":"Effect of Hydrogen Leakage on the Life Cycle Climate Impacts of Hydrogen Supply Chains","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-15 11:03:18","doi":"10.21203/rs.3.rs-4825556/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"communications-earth-and-environment","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"commsenv","sideBox":"Learn more about [Communications Earth and Environment](https://www.nature.com/commsenv/)","snPcode":"","submissionUrl":"","title":"Communications Earth \u0026 Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Communications Series","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"0641598b-4a2b-47e1-bd2b-b4c37ca08047","owner":[],"postedDate":"October 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":35574540,"name":"Earth and environmental sciences/Climate sciences/Climate change"},{"id":35574541,"name":"Earth and environmental sciences/Environmental sciences/Environmental impact"},{"id":35574542,"name":"Scientific community and society/Energy and society/Energy policy"}],"tags":[],"updatedAt":"2025-02-28T08:05:58+00:00","versionOfRecord":{"articleIdentity":"rs-4825556","link":"https://doi.org/10.1038/s43247-025-02141-3","journal":{"identity":"communications-earth-and-environment","isVorOnly":false,"title":"Communications Earth \u0026 Environment"},"publishedOn":"2025-02-28 05:00:00","publishedOnDateReadable":"February 28th, 2025"},"versionCreatedAt":"2024-10-15 11:03:18","video":"","vorDoi":"10.1038/s43247-025-02141-3","vorDoiUrl":"https://doi.org/10.1038/s43247-025-02141-3","workflowStages":[]},"version":"v1","identity":"rs-4825556","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4825556","identity":"rs-4825556","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}