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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Anthropogenic effects on flood hazards in a hyper-arid watershed: The 2015 Atacama floods

An unprecedented precipitation event in the hyper-arid Atacama Desert of Northern Chile occurred in March 2015. Geomorphic alterations to the river channel and the coastal zone, coupled with the exceptional magnitude of the rainfall, caused catastrophic damage and loss of life. On the coast of the El Salado watershed, legacy mine tailings infilled the watershed-ocean connection, while the river channel was altered both by tailings and urbanization. The consequences of this event resulted from the coupling of anthropogenic geomorphic changes with an unusual climate event. Lack of field data, complex geomorphology and sediment loads influenced by human activity make analysing floods in these regions especially challenging. The objective of this work is to improve our understanding of the factors that control flood hazards by using numerical simulations to reconstruct the 2015 flood in El Salado. We carry out unsteady two-dimensional simulations fully coupled with the sediment concentration to identify the influence of tailing deposits, considering high-resolution data of the pre- and post-2015 flood topography. In conclusion, the results highlight the importance of specific event-based studies, using models that can help designing better strategies for climate change adaptation and risk mitigation, while providing information for risk reduction and channel restoration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Evaluating the regional risks to food availability and access from land-based climate policies in an Integrated Assessment Model

Mitigating greenhouse gas (GHG) emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production. However, certain mitigation measures may generate unintended consequences to food availability and food access due to both land use competition and economic burden of mitigation. Integrated assessment models (IAM) are generally used to evaluate these policies; however, currently these models may not capture the importance of income and food prices for hunger and overall economic wellbeing. Here, we implement a measure of food security that captures the nutritional and economic aspects as the total expenditures on staple foods divided by income and weighted by total caloric consumption in an IAM, the Global Change Analysis Model (GCAM4.0). We then project consumer prices and our measure of food security along the Shared Socioeconomic Pathways (SSPs). Sustained economic growth underpins increases in caloric consumption and lowering expenditures on staple foods. Strict conservation policies affect food accessibility in a larger number of developing countries, whereas the negative effects of pricing terrestrial emissions is more concentrated on the poor in Sub-Saharan Africa, by substantially replacing their cropland with forests and affecting the production of key staples.

Cui, Ryna↗
DOE OSTI2025

Evaluation and calibration of MERRA-2 and CAMS reanalysis for PM 2.5 in a semi-urbanized area in the south of the Amazon

Air pollution has significant implications for the climate and poses irreversible risks to human health. The Amazon region of Brazil is severely affected by biomass burning (BB) emissions, yet air quality monitoring remains highly inadequate. Given the scarcity of surface-based observations, reanalysis models have become essential tools for assessing air pollution. Although MERRA-2 and CAMS PM 2.5 products are widely utilized, their validation and comprehensive evaluation for the Amazon Basin remain limited. Here, this study assesses the performance of these products in a semi-urbanized region in the southern Amazon. The calibrated time series was employed to analyze PM 2.5 concentrations from 2003 to 2023. Our results showed satisfactory performance of both products for the 24-h averages of PM 2.5 , with linear correlations above 0.76. However, it was found that both products overestimate surface concentrations. MERRA-2 performed better, with approximately 30% lower bias than CAMS. Time series analysis showed that the study area is strongly impacted by emissions BB in the dry period, mainly in August and September. Furthermore, our findings indicate a positive trend in increasing PM 2.5 concentrations, with a notable rise observed since 2014. The average PM 2.5 levels frequently exceed the daily air quality guidelines established by the WHO in 2021. It has been estimated that the population of this region is exposed to concentrations above 15 μg.m -3 , on average, more than 30 days per year. Our results contribute to the evaluation of MERRA-2 and CAMS products for Amazon and provide a corrected estimate for surface PM 2.5 . Recent concerns about air quality and the implementation of new surface monitoring networks may improve the evaluation of reanalysis products. In the short term, the need for this information makes our assessments indispensable.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

LCC-based framework for building envelope and structure co-design considering energy efficiency and natural hazard performance

Herein, this paper presents a life-cycle cost (LCC) informed co-design framework for building structures and envelope systems, holistically considering the influences of energy and natural hazard performance. The proposed method is consisted of a two-stage design and decision-making process, aiming to provide a quantitative guideline for building's structural and envelope co-design based on the its geographic locations. First, the building's structural configuration and envelope type are selected based on the life cycle cost. Then, the long-term cost effectiveness of various energy-saving building envelope options (e.g., high-performance glazing and insulation) is evaluated to refine the envelope design. The proposed co-design framework was demonstrated through the case study of a medium-size office building archetype in three locations with distinct climate conditions and seismic activities (i.e., Los Angeles, Memphis, and Boston). The results highlighted the interplay between building's structural (seismic) performance and the cost-effectiveness of energy-saving design options – e.g., for buildings located in high-seismic regions, seismic enhancing designs greatly reduce the paybak period of high performance building envelope by reducing the seismic loss; whereas for buildings located in regions with cold climate and low seismic risk such as Boston, spatial frame with high insulation building envelope shows the lowest LCC.

42 ENGINEERING↗
DOE OSTI2025

Probabilistic Diffusion Models Advance Extreme Flood Forecasting

Extreme floods pose escalating risks in a changing climate, yet forecasting remains challenging due to peak flow underestimation and high uncertainty. We introduce diffusion-based runoff model (DRUM), a probabilistic deep learning (DL) approach that advances extreme flood forecasting across representative basins in the contiguous United States. DRUM outperforms state-of-the-art benchmarks, enhancing nowcasting skill for the top 1‰ of flows in 72.3% of studied basins. Under operational scenarios, DRUM extends reliable lead times by nearly a full day for 20- and 50-year floods. When evaluated with measured precipitation, an ideal condition, recall improves by 0.3–0.4 and the early warning window extends by 2.3 days for 50-year floods. The enhancement potential varies regionally, with precipitation-driven flood zones in the eastern and northwestern US benefiting most, gaining 3–7 days in lead time. These findings highlight the transformative potential of diffusion models as a cutting-edge generative AI technique for advancing hydrology and broader Earth system sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Social inequalities in climate change-attributed impacts of Hurricane Harvey

Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But little research to date investigates if, and to what extent, there are social inequalities in climate change-attributed extreme weather event impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. Using detailed land-parcel and census tract socio-economic data, we then describe the socio-spatial characteristics associated with these climate change-induced impacts. We show that 30 to 50% of the flooded properties would not have flooded without climate change. Climate change-attributed impacts were particularly felt in Latina/x/o neighborhoods, and especially so in Latina/x/o neighborhoods that were low-income and among those located outside of FEMA’s 100-year floodplain. Our focus is thus on climate justice challenges that not only concern future climate change-induced risks, but are already affecting vulnerable populations disproportionately now.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Scenarios in IPCC assessments: lessons from AR6 and opportunities for AR7

Scenarios have been an important integrating element in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) in the understanding of possible climate outcomes, impacts and risks, and mitigation futures. Integration supports a consistent, coherent assessment, new insights and the opportunity to address policy-relevant questions that would not be possible otherwise, for example, which impacts are unavoidable, which are reversible, what is a consistent remaining carbon budget to keep temperatures below a level and what would be a consistent route of action to achieve that goal. The AR6 builds on community frameworks that are developed to support a coherent use of scenarios across the assessment, yet their use in the assessment and the related timelines presented coordination challenges. From lessons within each Working Group (WG) assessment and the cross-WG experience, we present insights into the role of scenarios in future assessments, including the enhanced integration of impacts into scenarios, near-term information and community coordination efforts. Recommendations and opportunities are discussed for how scenarios can support strengthened consistency and policy relevance in the next IPCC assessment cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling and observations of North Atlantic cyclones: Implications for U.S. Offshore wind energy

To meet the Biden-Harris administration's goal of deploying 30 GW of offshore wind power by 2030 and 110 GW by 2050, expansion of wind energy into U.S. territorial waters prone to tropical cyclones (TCs) and extratropical cyclones (ETCs) is essential. This requires a deeper understanding of cyclone-related risks and the development of robust, resilient offshore wind energy systems. Here, this paper provides a comprehensive review of state-of-the-science measurement and modeling capabilities for studying TCs and ETCs, and their impacts across various spatial and temporal scales. We explore measurement capabilities for environments influenced by TCs and ETCs, including near-surface and vertical profiles of critical variables that characterize these cyclones. The capabilities and limitations of Earth system and mesoscale models are assessed for their effectiveness in capturing atmosphere–ocean–wave interactions that influence TC/ETC-induced risks under a changing climate. Additionally, we discuss microscale modeling capabilities designed to bridge scale gaps from the weather scale (a few kilometers) to the turbine scale (dozens to a few meters). We also review machine learning (ML)-based, data-driven models for simulating TC/ETC events at both weather and wind turbine scales. Special attention is given to extreme metocean conditions like extreme wind gusts, rapid wind direction changes, and high waves, which pose threats to offshore wind energy infrastructure. Finally, the paper outlines the research challenges and future directions needed to enhance the resilience and design of next-generation offshore wind turbines against extreme weather conditions.

17 WIND ENERGY↗
DOE OSTI2022

Lifecycle Assessment and Techno-Economic Analysis of Biochar Pellet Production from Forest Residues and Field Application

Biochar produced from low-value forest biomass can provide substantial benefits to ecosystems and mitigate climate change-induced risks such as forest fires. Forest residues from restoration activities and timber harvest and biochar itself are bulky and thus incur high logistic costs, so are considered major bottlenecks for the commercialization of the biochar industry. The objectives of this study were to assess the environmental footprints and techno-economic feasibility of converting forest residues in Pacific Northwest United States into biochar pellets using portable systems followed by delivery of the final product to end-users for land application (dispersion). Two portable systems (Biochar Solutions Incorporated (BSI) and Air Curtain Burner (ACB)) were considered for biochar production. A cradle-to-grave lifecycle assessment (LCA) and a discounted cash flow analysis method were used to quantify the environmental impacts and minimum selling price (MSP) of biochar. The global warming (GW) impact of biochar production through BSI and ACB was estimated to be 306–444, and 750–1016 kgCO₂eq/tonne biochar applied to the field, respectively. The MSP of biochar produced through BSI and ACB was 1674–1909 and 528–1051 USD/tonne biochar applied to the field, respectively. Pelletizing of biochar reduced GW impacts during outbound logistics (~8–20%) but increased emissions during pelletizing (~1–9%). Results show the BSI system was a more viable option in terms of GW impact, whereas the ACB system can produce biochar with lower MSP. The results of the study conclude that the production of biochar pellets through the two portable systems and applied to fields can be both an environmentally beneficial and economically viable option.

09 BIOMASS FUELS↗
DOE OSTI2025

Divergent responses of historic rain-on-snow flood extremes to a warmer climate

Global warming is altering flood risks induced by rain-on-snow events. However, decision-makers lack guidance on how rain-on-snow induced extreme floods could be altered with warming. Here, storyline analyses using a kilometer-scale land surface model reveal diverse responses of four historically-impactful, decision-relevant rain-on-snow induced extreme flood events over the contiguous U.S. to warming, due to alterations in their water budgets. For the 2017-Feb California floods, runoff first increases and then decreases with warming, peaking under the +3 K scenario, while runoff of the 2017-Jan California floods increases monotonically by ~53%/K. Contrastingly, runoff of the 1996-Jan Mid-Atlantic floods decreases gradually with warming. Despite these differences, warming generally shifts flood-generating regimes along elevation profiles. High elevations could experience notably increased runoff, while low elevations encounter a shift from rain-on-snow-driven to rainfall-dominated runoff. These findings underscore the need for flood control planning to quantify region- and elevation-specific changes in rain-on-snow events in a warmer climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exploring Water System Vulnerabilities in California's Central Valley Under the Late Renaissance Megadrought and Climate Change

Abstract California faces cycles of drought and flooding that are projected to intensify, but these extremes may impact water users across the state differently due to the region's natural hydroclimate variability and complex institutional framework governing water deliveries. To assess these risks, this study introduces a novel exploratory modeling framework informed by paleo and climate‐change based scenarios to better understand how impacts propagate through the Central Valley's complex water system. A stochastic weather generator, conditioned on tree‐ring data, produces a large ensemble of daily weather sequences conditioned on drought and flood conditions under the Late Renaissance Megadrought period (1550–1580 CE). Regional climate changes are applied to this weather data and drive hydrologic projections for the Sacramento, San Joaquin, and Tulare Basins. The resulting streamflow ensembles are used in an exploratory stress test using the California Food‐Energy‐Water System model, a highly resolved, daily model of water storage and conveyance throughout California's Central Valley. Results show that megadrought conditions lead to unprecedented reductions in inflows and storage at major California reservoirs. Both junior and senior water rights holders experience multi‐year periods of curtailed water deliveries and complete drawdowns of groundwater assets. When megadrought dynamics are combined with climate change, risks for unprecedented depletion of reservoir storage and sustained curtailment of water deliveries across multiple years increase. Asymmetries in risk emerge depending on water source, rights, and access to groundwater banks.

Gupta, Rohini S. [School of Civil and Environmenta↗
DOE OSTI2023

A Large Ensemble Global Dataset for Climate Impact Assessments

We present a self-consistent, large ensemble, high-resolution global dataset of long-term future climate, which accounts for the uncertainty in climate system response to anthropogenic emissions of greenhouse gases and in geographical patterns of climate change. The dataset is developed by applying an integrated spatial disaggregation (SD) - bias-correction (BC) method to climate projections from the MIT Integrated Global System Model (IGSM). Four emission scenarios are considered that represent energy and environmental policies and commitments of potential future pathways, namely, Reference, Paris Forever, Paris 2 °C and Paris 1.5 °C. The dataset contains nine key meteorological variables on a monthly scale from 2021 to 2100 at a spatial resolution of 0.5°x 0.5°, including precipitation, air temperature (mean, minimum and maximum), near-surface wind speed, shortwave and longwave radiation, specific humidity, and relative humidity. We demonstrate the dataset’s ability to represent climate-change responses across various regions of the globe. This dataset can be used to support regional-scale climate-related impact assessments of risk across different applications that include hydropower, water resources, ecosystem, agriculture, and sustainable development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Next-Generation Intensity-Duration-Frequency Curves for Climate-Resilient Infrastructure Design: Advances and Opportunities

National and international security communities (e.g., U.S. Department of Defense) have shown increasing attention for innovating critical infrastructure and installations due to recurring high-profile flooding events in recent years. The standard infrastructure design approach relies on local precipitation-based intensity-duration-frequency (PREC-IDF) curves that do not account for snow process and assume stationary climate, leading to high failure risk and increased maintenance costs. This paper reviews the recently developed next-generation IDF (NG-IDF) curves that explicitly account for the mechanisms of extreme water available for runoff including rainfall, snowmelt, and rain-on-snow under nonstationary climate. The NG-IDF curve is an enhancement to the PREC-IDF curve and provides a consistent design approach across rain- to snow-dominated regions, which can benefit engineers and planners responsible for designing climate-resilient facilities, federal emergency agencies responsible for the flood insurance program, and local jurisdictions responsible for developing design manuals and approving subsequent infrastructure designs. Further, we discuss the recent advances in climate and hydrologic science communities that have not been translated into actional information in the engineering community. To bridge the gap, we advocate that building climate-resilient infrastructure goes beyond the traditional local design scale where engineers rely on recipe-based methods only; the future hydrologic design is a multi-scale problem and requires closer collaboration between climate scientists, hydrologists, and civil engineers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Computational Tools and Workflows for Quantitative Risk Assessment and Decision Support for Geologic Carbon Storage Sites: Progress and Insights from the U.S. DOE’s National Risk Assessment Partnership

The 2005 Intergovernmental Panel on Climate Change (IPCC) Special Report on CCS raised the profile of CO2 capture and storage (CCS) as an important technology for reducing greenhouse gas (GHG) emissions. CCS is now recognized as a key component of most climate change mitigation scenarios. Since publication of that report the international research, development, and deployment (RD&D) community has advanced key technical aspects, clarified regulatory requirements, explored value chain and infrastructure solutions, and developed incentive paradigms to enable and promote large-scale deployment of CCS. These efforts have included research to better characterize geologic storage resources, to improve injection performance and storage efficiency, to assess and manage subsurface environmental risks, and to advance monitoring technologies to assure system conformance. These efforts have helped to build confidence in the viability of geologic carbon storage (GCS), but stakeholder concerns about long-term risks and liability associated with GCS remain a hurdle to broad acceptance and large-scale deployment of CCS. Since 2010, the U.S. DOE’s National Risk Assessment Partnership (NRAP) – a research collaboration between five contributing national laboratories – has worked to establish and demonstrate methods and tools to quantify and manage the subsurface environmental risks associated with GCS, amidst uncertainty. This work supports the Office of Fossil Energy and Carbon Management Carbon Transport and Storage Program’s goal of advancing safe and secure commercial-scale GCS deployment. To address the technical challenge of simulating the physical response of the GCS site to large-scale CO2 injection, NRAP has adopted an approach that relies on coupling computationally efficient reduced-order and/or data-driven proxy models of important system components (i.e., storage reservoir, sealing caprock, leakage pathways, intermediate formations, overlying groundwater aquifers, and the atmosphere) in integrated assessment framework. That integrated model of the physical system is complemented with fit-for purpose functionality to support site characterization and risk-related decisions. The recently released NRAP Phase II toolset includes the Open-Source Integrated Assessment Model (NRAP-Open-IAM) for evaluation of trends in leakage risk and potential impact, tools to support monitoring design optimization (Designs for Risk Evaluation and Management – DREAM v3.0 and Passive Seismic Monitoring Tool - PSMT), and tools for state of stress evaluation (State-of-Stress Analysis Tool - SOSAT) and forecasting induced seismicity risk. The NRAP team has also released a pair of reports describing conceptual workflows to incorporate physics-based, quantitative risk assessment into many of the design, planning, operation, and closure decisions for GCS projects. An online catalogue highlights published studies where these tools and methods are demonstrated. In this presentation, the utility of these products to assess risks and address key stakeholder questions will be highlighted through examples, and related insights about the safety and security of geologic carbon storage in qualified storage sites will be discussed. The prospect of rapid, large-scale deployment of GCS technology to aggressively reduce anthropogenic CO2 emissions requires careful consideration of interference between multiple commercial-scale storage projects within a basin. Going forward, NRAP is expanding and adapting site-scale risk quantification tools and methods to enable assessment of risks and inform management decisions for basin-scale deployment. Increasingly, this work will leverage next-generation approaches for surrogate modelling, fast prediction, and advanced visualization enabled by machine learning and artificial intelligence to promote virtual learning, scenario evaluation, and augment risk-based decision making.

quantitative risk assessment, geologic carbon stor↗
DOE OSTI2023

Projections of wildfire risk and activities under 1.5 °C and 2.0 °C global warming scenarios

Wildfires are important ecosystem processes that have a significant impact on terrestrial vegetation, environment, and climate. This study investigates how future wildfire risk and activities could change under 1.5 °C and 2.0 °C warming scenarios relative to pre-industrial levels using a modified McArthur Forest Fire Danger Index (FFDIn) and the CLM4.5-BGC land surface model. Sixteen Earth System Models (ESMs) from CMIP5 and CMIP6 were employed to supply the variables of climate change under low, middle, and high greenhouse emission scenarios in the 1.5 °C and 2.0 °C scenarios. The ensemble means from the FFDIn and results from the CLM4.5-BGC with multiple forcings show that the dry areas in the southwestern US, Brazilian Highlands, and Arabian islands are projected to face higher wildfire risk with larger burned areas and more carbon emissions under a warmer climate. The Congo Basin and part of the Amazon could have a lower wildfire risk with smaller burned areas and less carbon emissions. The absolute changes in the projected FFDIn are small, although large increases are observed in boreal areas, particularly in the winter and spring. Burned area and carbon emissions are projected to increase in general in the boreal area but decrease in northeastern Asia. Compared to the 1.5 °C scenario, the wildfire risk and burned area levels are projected to increase under the 2.0 °C scenario except in the western Amazon. However, fire carbon emissions are projected to decrease more in tropical areas under the 2.0 °C scenario. The different change directions in eastern North America and eastern China produced by the FFDIn and CLM4.5-BGC suggest the potential effect of non-meteorological elements on fire activities.

1.5 °C and 2.0 °C warming↗
DOE OSTI2024

Evidence of human influence on Northern Hemisphere snow loss

Documenting the rate, magnitude and causes of snow loss is essential to benchmark the pace of climate change and to manage the differential water security risks of snowpack declines. So far, however, observational uncertainties in snow mass have made the detection and attribution of human-forced snow losses elusive, undermining societal preparedness. Here we show that human-caused warming has caused declines in Northern Hemisphere-scale March snowpack over the 1981–2020 period. Using an ensemble of snowpack reconstructions, we identify robust snow trends in 82 out of 169 major Northern Hemisphere river basins, 31 of which we can confidently attribute to human influence. Most crucially, we show a generalizable and highly nonlinear temperature sensitivity of snowpack, in which snow becomes marginally more sensitive to one degree Celsius of warming as climatological winter temperatures exceed minus eight degrees Celsius. Such nonlinearity explains the lack of widespread snow loss so far and augurs much sharper declines and water security risks in the most populous basins. Together, our results emphasize that human-forced snow losses and their water consequences are attributable—even absent their clear detection in individual snow products—and will accelerate and homogenize with near-term warming, posing risks to water resources in the absence of substantial climate mitigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Yesterday’s extremes, today’s new normal: flood risk in the Kathmandu Valley, Nepal

Unplanned urban growth has left many cities increasingly vulnerable to extreme rainfall events, particularly in regions with inadequate drainage infrastructures and development encroaching on natural floodplains. Here, in this perspective paper, we examine the September 2024 floods that struck Central Nepal, triggered by a persistent low-pressure system and enhanced by converging moisture flows from the Arabian Sea and the Bay of Bengal which led to widespread catastrophic damage. In the Kathmandu Valley, floodwaters expanded to more than 2.5 times the bankfull water extent, causing significant damage to housing, transportation network, and critical infrastructure, displacing thousands of residents, and severely disrupting urban services. This event highlights the urgent need for improved flood management strategies that integrate both structural and non-structural measures into the infrastructure development. While early warning systems provided critical lead time, challenges remain in reducing forecasting uncertainties and improving communication across government agencies and with local communities. A forward-looking approach is essential, including probabilistic flood forecasting systems, sustainable floodplain management, risk-sensitive land use planning, climate- and disaster- resilient infrastructure development, and the integration of nature-based solutions like urban green and blue spaces to mitigate flood impacts. By involving local communities in planning and preparedness efforts, particularly through citizen science initiatives, and engagement with underserved and disadvantaged communities, Nepal can better adapt to the growing risks posed by extreme rainfall and urban flooding and enhance long-term disaster resilience in rapidly urbanizing areas like Kathmandu Valley.

Kathmandu Valley↗
DOE OSTI2021

U.S. Manufacturing Water Use Data and Estimates: Current State, Limitations, and Future Needs for Supporting Manufacturing Research and Development

Water is essential to manufacturing operations; without it, many facilities could not operate or meet production demands. Physical, reputational, and regulatory risks to water supplies compounded by climate change-induced impacts on hydrological conditions threaten the adequacy of water supplies for manufacturing. Manufacturing water use has not been a major focus of either water or manufacturing-related research. Research and development (R&D) aimed at helping manufacturers use water more sustainably and adapt to changing water conditions is needed to ensure a thriving sector and economy. However, the ability to identify R&D needs is severely limited due to a lack of current, statistically representative data on manufacturing water use and its environmental implications. In this Perspective, we outline four key questions to inform R&D on manufacturing use and highlight how the current state of water data in the United States does not support the adequate investigation of these questions. We make recommendations for the water data characteristics needed to explore the research questions and knowledgeably inform R&D on manufacturing water use.

McCall, James↗