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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 55 records · Page 3

Solvent Transport in Disordered and Dynamic Membrane Pores: Implications for Reverse Osmosis and Nanofiltration Membranes

Pressure-driven separations with nanoporous membranes, such as reverse osmosis and nanofiltration, play a vital role in addressing water scarcity and enabling resource recovery. Understanding water or solvent transport in membrane pores is essential for advancing membrane separation technologies. A key question in transport modeling is to establish a relationship between solvent permeability and membrane porous structure properties, such as porosity or pore size. The nano- and subnanometer pores in polymeric membranes such as reverse osmosis and nanofiltration membranes are highly tortuous and dynamically connected, which challenges the conventional methods of transport modeling. This study addresses this challenge by developing a theoretical framework to describe solvent transport through membranes with dynamic and disordered porous structure. Specifically, we propose a lattice model to describe the pore network, while preserving the viscous nature of solvent permeation. We further establish a relationship between solvent permeability and membrane porosity or pore size, which is validated by molecular dynamics simulations and experimental data. By integrating this relationship into the solution-friction model, we define pore connectivity and local friction coefficient to quantify the impact of pore structure on solvent permeability. Our analysis highlights the dominant influence of pore connectivity on the permeability of reverse osmosis and nanofiltration membranes, particularly when the pore size approaches the dimensions of solvent molecules. Overall, this study provides critical insights into water and solvent transport mechanisms in nanoporous membranes, opening the door for strategies to substantially enhance membrane performance.

membranes↗

Impact of Non-Steady State Operation on Cooling Water Consumption at Coal- and Natural Gas-Fired Power Plants

Increased renewable energy penetration in the electricity grid in coming decades will result in more frequent cycling at thermal power plants. Simultaneously, thermal power plants may face water scarcity with declining availability of cooling water. Therefore, to enhance thermal power plants’ resiliency to water shortages it is important to understand how non-steady conditions due to cycling will impact cooling water consumption and withdrawal intensity. Non-steady operation at power plants has been previously shown to decrease power plant thermal efficiency. Energy balance models have also demonstrated that a decrease in thermal efficiency is expected to increase cooling water consumption intensity. Furthermore, past work has used operating hours data to show idling and cycling gaps where cooling systems operate more than corresponding generators. As a result, an increase in cycling behavior may impact cooling water consumption and withdrawal intensity. This study uses data from the Energy Information Administration (EIA) and Environmental Protection Agency (EPA) to quantify the impact of cycling cooling water consumption intensity for recirculating cooling systems and withdrawal intensity for once-through cooling systems using energy balance and statistical approaches. In a novel application of a fixed effects model to study the effect of temperature on cooling water consumption and withdrawal intensity, this study finds temperature was consistently expected to increase consumption intensity and withdrawal intensity. Non-steady state conditions do not increase cooling water consumption intensity with statistical significance across unit types. However, additional validation of cooling water data is required to confirm these observed trends due to the sensitivity of these findings to model form and concerns with data quality of the dependent variables, cooling water consumption and withdrawal.

20 FOSSIL-FUELED POWER PLANTS↗

Prediction of alkaline earth metal ion adsorption on goethite for various background electrolytes with the CD-MUSIC model

As water scarcity drives the use of more saline water sources, contaminant fate and transport models must capture the impact of high concentrations of alkaline earth metal ions (AEMs) and background electrolytes in these more complex waters. By utilizing macroscopic adsorption data from various electrolyte systems, a Charge Distribution – Multisite Complexation (CD-MUSIC) model, capable of incorporating electrolyte adsorption, was able to accurately simulate the adsorption behavior of alkaline earth metal ions onto goethite. The modeling effort was guided by previous spectroscopic and surface complexation modeling of alkaline earth metal adsorption and built on previous CD-MUSIC modeling that accounted for changes in crystal face contributions to the surface site density as a function of specific surface area. Further, the model was constrained to consider only two dominant surface complex species for each metal ion adsorption reaction. These two species were selected from 44 possible species through objective curve fitting of single-solute macroscopic adsorption data. While most of the alkaline earth metal surface complexes formed outer-sphere complexes at the goethite surface, an inner-sphere species was utilized for Mg 2+ . With the surface complex species and equilibrium constants obtained from this study, the calibrated model successfully predicted alkaline earth metal ion adsorption over a wide range of solution and surface conditions; the model predictions encompassed a wide range of pH (5–11), solute/solid ratio (1.37 × 10 -5 – 8.33 × 10 -4 mol -solute /g -solid ), ionic strengths (0.01 M – 0.7 M), and background electrolytes (Na + , Cs + , Rb + , Cl - , and NO 3 - ) using the same crystal face contribution methodology for site density, capacitance values, and surface acidity constants adopted for proton and cadmium adsorption in previous work (Han and Katz, 2019). Model simulations for a range of background water chemistries demonstrated the potential for Mg 2+ to reduce Cd 2+ adsorption to goethite in model seawater and oil- and gas-produced waters.

42 ENGINEERING↗

SIMPLE-G: A multiscale framework for integration of economic and biophysical determinants of sustainability

We introduce SIMPLE-G, a Simplified International Model of agricultural Prices, Land use, and the Environment- Gridded version, which is a novel tool for evaluating sustainability policies in a global context while factoring in local heterogeneity in land and water resources and natural ecosystem services. This multi-scale model can provide boundary conditions for local decision makers, as well as capturing feedback from local policies to national and global scales. Additionally, to illustrate its value in environmental analysis, we provide two applications of the model. First, we quantify the local stresses on land and water resources due to global changes in population, income, and productivity. Second, we quantify the global impacts of local policy responses and adaptations to water scarcity.

42 ENGINEERING↗

Evaluation of hybrid evaporative-vapor compression air conditioners for different global climates

Currently, a majority of global residential air-conditioning requirements are met using cooling systems based on the vapor compression cycle (VCC). To meet the future demand for space cooling and to reduce the corresponding environmental impact, there is a need for alternative cooling systems which require less resources and exhibit a higher coefficient of performance (COP). One of proposed alternatives is called the hybrid evaporative-vapor compression (HEVC) cycle, which utilizes adiabatic latent cooling in combination with the VCC. In this paper, we conducted a feasibility analysis of a HEVC system by comparing its performance to that of VCC for various global climates. To accomplish this, we developed and validated models to simulate the performance of residential VCC and HEVC systems. ASHRAE weather data and design conditions were then used to compare the performance of the two systems. In general, HEVC systems are best suited for hot arid climates with energy reduction greater than 20%. Conversely, humid climates are not suitable for HEVC adoption due to degraded performance of evaporative coolers in these climates. In addition to comparing the energy savings from HEVC systems, it is also critical to analyze their water consumption. Generally, climates that benefit the most from HEVC technology tend to also experience water scarcity issues. Thus, both the energy savings and water consumption of HEVC systems must be analyzed to guide the discussion on their adoption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Crop diversification improves water-use efficiency and regional water sustainability

As global water scarcity intensifies, identifying agricultural practices that enhance sustainable water management is critical. Temporal crop diversification-rotating multiple species over time-has been proposed to improve soil health and water retention based on field-scale experiments. However, widespread adoption remains limited on farms, in part due to unverified benefits at larger scales. Here, we assess the influence of crop diversification on agricultural water-use efficiency (WUE, ratio of gross primary productivity to evapotranspiration) along a spectrum of monoculture to complex species rotations in California. Leveraging new high-resolution remote sensing datasets, we show that crop diversification is a key driver of agricultural WUE, and increasing the number of species planted in the previous 6 years from two to four increases WUE by ∼20% after accounting for differences between crops. Our results provide spatially explicit, large-scale quantification of crop diversification’s improvements to WUE, with direct implications for climate adaptation. More broadly, our framework offers a tool to evaluate other sustainable practices and guide policy and farm-scale decision-making.

climate-resilient agriculture↗

Seeding Advanced Treated Wastewater for Purposes of Direct Potable Reuse

Direct potable reuse (DPR) is a promising solution to address water scarcity. However, a better understanding of how introducing advanced treated water (ATW) affects microbial communities present in distribution systems is needed. Here, in this study, we measured changes to the microbial water quality in simulated distribution systems that were conditioned using treated, unimpaired surface water (SW) and then transitioned to ATW. In addition, we investigated whether adding a biological filtration step would seed the microbial community of the ATW and whether the influence would persist in the simulated distribution systems. We found that the bulk water in the ATW-fed distribution systems had lower cell counts and ATP concentrations and a distinct microbial community (based on 16S amplicon sequencing) compared to the SW-fed or the seeded ATW-fed systems. However, biofilm community composition and biomass remained consistent regardless of the feedwater. Increased microbial biomass and diversity were present in the seeded ATW, with several amplicon sequence variants identified as being introduced by the biological filter. Our results suggest that directly introducing ATW to distribution systems could disturb the existing microbial community. Preparing ATW for distribution via biological filtration may deliver more predictable and stable microbial water quality than introducing unseeded ATW.

16S↗

Drivers of Water Use in the Agricultural Sector of the European Union 27

Population growth and the uncertain hazards that accompany climate change have put increasing pressure on the management and sustainability of water. It has a direct impact on agriculture and its domestic and international supply chain linkages. As one of the largest agricultural producers in the world, the European Union (EU) is particularly sensitive to changes in water availability. Therefore, here we perform a structural decomposition analysis based on the recently released EXIOBASE 3 database to examine in depth how changes in water input coefficients, in final demand and in technology have affected changes in water use across crops. Crop production consumes 99% of the direct water in agriculture. Our results show that the largest EU crop producers have experienced an increase in water use that is mostly driven by changes in technology. On the other hand, several Mediterranean countries, where water scarcity has been a problem for years, have decreased their water consumption mostly thanks to an improvement in their water intensity. Results by crop are consistent with those at the aggregated level except for vegetables of which water use changes have been primarily driven by changes in final demand and water intensity.

54 ENVIRONMENTAL SCIENCES↗

The future evolution of energy-water-agriculture interconnectivity across the US

Abstract Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the ‘Interconnectivity Magnitude Index’ and the ‘Interconnectivity Spread Index’. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Khan, Zarrar (ORCID:0000000281478553)↗

Opportunities for Using the Industrial Assessment Center Database for Industrial Water Use Analysis

The manufacturing sector accounted for approximately 5–6% of total U.S. water use in 2015. Of that amount, 75–80% is self supplied withdrawal from surface-water and groundwater sources and the remainder is from public water supplies. Although manufacturing facilities commonly locate in water-scarce areas, water scarcity still poses a great risk to the manufacturing sector. Reliable water is necessary for any facility that relies on it for process and comfort cooling, cleaning, employee use, and steam generation. One of these barriers to water efficiency is the lack of reliable data on overall U.S. industrial water use—how it is used and the quantities required for each sector. If a facility cannot be easily compared with a facility of similar size and sector, knowing if it is effectively using water conservation best practices is difficult. One potential source of industrial water use data is the U.S. Department of Energy (DOE)–sponsored Industrial Assessment Centers (IACs). IACs are university-based organizations that provide free audits to small- and medium-sized manufacturing facilities to identify productivity improvement and waste and energy reduction opportunities. The IACs also maintain a database of all the audits conducted, which currently holds more than 19,267 assessments and 145,000 recommendations (as of July 24, 2020). This database also contains energy utility (electricity, natural gas, and other fuels) and water utility data, making it a potential data source for industrial water use. This report attempts to create regression models to predict a small- or medium-sized industrial facility’s annual water use or cost based on its industrial subsector and several possible relevant variables. Using data collected by IAC assessments, models for several industrial subsectors were generated via stepwise regression techniques to determine which variables (annual sales, number of employees, facility/plant area, annual production hours, and a water stress metric) are relevant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Abbr. Final report: Self-assembled molecular containers as artificial water channels: towards biomimetic desalination membranes

Global water scarcity demands advances in desalination technologies that can deliver more fresh water with less energy. Current reverse osmosis membranes are fundamentally limited by a trade-off between how much water they can pass and how well they block salts. To address this challenge, we developed a bottom-up strategy to design and test artificial water channels that mimic the efficiency of biological proteins but are built from robust synthetic molecules. Over two years, we synthesized and evaluated more than twenty molecular channel candidates, including supramolecular macrocycles and nanographene pores with atomically precise structures. We showed that small chemical modifications allow direct control over pore size and chemistry, which in turn govern water permeability and salt rejection. In collaboration with university partners, we reported the first experimental demonstration of water transport through a nanographene pore, bridging a long-standing gap between simulation and experiment. Several of the artificial channels we developed achieved water–salt selectivity beyond conventional polymer membranes, highlighting their potential for next-generation desalination and precision separations.

36 MATERIALS SCIENCE↗

Characterizing the Effects of Irrigation in the Middle East and North Africa Using Remotely Sensed Vegetation and Water Cycle Observations

A majority of the countries in the Middle East and North Africa (MENA) region suffer from water scarcity due in part to widespread rainfall deficits, unprecedented levels of water demand, and the inefficient use of renewable freshwater resources. Since a majority of the water withdrawal in the MENA is used for irrigation, there is a desperate need for improved understanding of irrigation practices and agricultural water use in the region. Here, satellite-derived irrigation maps and crop-type agricultural data are applied to the Land Data Assimilation System for the MENA region (MENA LDAS), designed to provide regional, gridded fields of hydrological states and fluxes relevant for water resources assessments. Within MENA-LDAS, the Catchment Land Surface Model (CLSM) simulates the location, timing, and amount of water applied through agricultural irrigation practices over the region from 2002-2012. In addition to simulating the irrigation impact on evapotranspiration, soil moisture, and runoff, we also investigate regional changes in terrestrial water storage (TWS) observed from the Gravity Recovery and Climate Experiment (GRACE) and simulated by CLSM.

Bolten, John↗

Tethys Water Demand Data

U.S. water demand varies sharply by sector and region as land use, population, weather patterns, and economic activity co-evolve. High-resolution water demand data is required to capture these dynamics, support integrated energy-water-land modeling, and local-to-regional water scarcity assessments. This dataset contains gridded (1/8 degree), monthly, multi-sector water demand dataset for the contiguous United States (CONUS) covering 1980-2100 across eight future scenarios of human-Earth system change. The dataset covers irrigation, thermoelectric, municipal (public-supply and domestic), livestock, manufacturing, and mining demands, separately for withdrawals and consumption, and includes per-cell renewable vs. non-renewable water source attributions. The dataset is validated against the latest USGS 2010-2020 water-use data for the three largest water demand sectors (Domestic, Electricity, and Irrigation), with correlations ranging from 0.73-0.95 at the HUC6 scale. The two datasets largely agree on an aggregate basis with per-sector bias falling within +/-7%, but they disagree on the spatial allocation of water with individual HUC6 basins having normalized RMSE from 68-171% and median absolute percent difference from 37-86%. This dataset advances prior global products by combining state-resolved sectoral demands from GCAM-USA, future power-plant siting from the CERF model, and scenario-consistent high-resolution climate and population forcing data across the eight scenarios.

GCAM-USA↗

Estimating Fresh Water Needs to Meet Future Thermoelectric Generation Requirements and Program Water Saving Benefits (2022 Update)

Freshwater availability is operationally critical for thermoelectric power plants. Trends indicating a growing population, along with increasing threats stemming from the changing climate could possibly set off water scarcity issues for U.S. thermoelectric generation in scarcity-prone regions in the country. This report is an update to a previous water needs analysis which was conducted in 2020 by the Department of Energy’s National Energy Technology Laboratory (DOE/NETL).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Integrated energy-water-land nexus planning in the Colorado River Basin (Argentina)

Integrated energy-water-land (EWL) planning promotes synergies and avoids conflicts in ways that sector-specific planning approaches cannot. Many important decisions that influence emerging EWL nexus issues are implemented at regional (e.g., large river basin, electricity grid) and sub-regional (e.g., small river basin, irrigation district) scales. However, actual implementation of integrated planning at these scales has been limited. Simply collecting and visualizing data and interconnections across multiple sectors and sub-regions in a single modeling platform is a unique endeavor in many regions. This study introduces and applies a novel approach to linking together multiple sub-regions in a single platform to characterize and visualize EWL resource use, EWL system linkages within and among sub-regions, and the EWL nexus implications of future policies and investments. This integrated planning methodology is applied in the water-stressed Colorado River Basin in Argentina, which is facing increasing demands for agricultural and fossil fuel commodities. Guided by stakeholders, this study seeks to inform basin planning activities by characterizing and visualizing (1) the basin’s current state of EWL resources, (2) the linkages between sectors within and among basin sub-regions, and (3) the EWL nexus implications of planned future agricultural development activities. Results show that water scarcity, driven in part by human demands that have historically reached 60% of total surface water supply, poses a substantial constraint to economic development in the basin. The Colorado basin has the potential to serve as a testbed for crafting novel and generalizable sub-regional EWL planning approaches capable of informing the EWL planning dialogue globally.

54 ENVIRONMENTAL SCIENCES↗

Highly efficient, rapid, and concurrent removal of toxic heavy metals by the novel 2D hybrid LDH–[Sn 2 S 6 ]

According to a United Nations report, by 2050 nearly six billion people worldwide will suffer from clean water scarcity. This is mostly because of the exponential proliferation of world population, urbanization, industrialization, and water pollution. Heavy metals are common water pollutants that can pose grave public health consequences. Existing water purification systems are lack of materials that have the potential for quick, simultaneous, efficient, and cost-efficient removal of numerous toxic metals from wastewater. Here, in this work, we report the design and synthesis of an economically viable Layered Double Hydroxides - Stannic Sulfide, LDH–[Sn 2 S 6 ] that exhibits a rapid, efficient, selective, and concurrent removal of Cu 2+ , Ag + , Cd 2+ , Pb 2+ , and Hg 2+ from parts per million (ppm) level to below 5 parts per billion (ppb) satisfying World Health Organization’s (WHO) safe drinking water limit. Moreover, LDH–[Sn 2 S 6 ] shows exceptionally high removal efficiencies of the above metals in acidic, neutral, and basic conditions. LDH–[Sn 2 S 6 ] also demonstrates enormous sorption capacities of 378, 978, 332, 579, and 666 mg/g for Cu 2+ , Ag + , Cd 2+ , Pb 2+ , and Hg 2+ , respectively. Remarkably, LDH–[Sn 2 S 6 ] displays extraordinary tolerance to the concentrations of Na + , Ca 2+ , Mg 2+ , Cl - , CO 3 2– , NO 3 – ,and SO 4 2- , and other constituents in tap and river water, it efficiently sequestrates Cu 2+ , Ag + , Cd 2+ , Pb 2+ , and Hg 2+ from ppm to safe drinking water levels in minutes. LDH–[Sn 2 S 6 ] shows pseudo-second-order sorption kinetics suggesting chemisorption adsorption mechanism involving M–S bonding. Altogether, the regeneratable LDH–[Sn 2 S 6 ] becomes an exceptional material that shows ultrahigh removal, unprecedented selectivity, rapid adsorption kinetics, wide pH stability, and a massive adsorption capacity. The integration of these features places LDH–[Sn 2 S 6 ] at the top of all adsorbents known to date and thus could be used for wastewater purifications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterizing Drought Behavior in the Colorado River Basin Using Unsupervised Machine Learning

Drought is a pressing issue for the Colorado River Basin (CRB) due to the social and economic value of water resources in the region and the significant uncertainty of future drought under climate change. Here, we use climate simulations from various Earth System Models (ESMs) to force the Variable Infiltration Capacity hydrologic model and project multiple drought indicators for the sub-watersheds within the CRB. We apply an unsupervised machine learning (ML) based on Non-Negative Matrix Factorization using K-means clustering (NMFk) to synthesize the simulated historical, future, and change in drought indicators. The unsupervised ML approach can identify sub-watersheds where key changes to drought indicator behavior occur, including shifts in snowpack, snowmelt timing, precipitation, and evapotranspiration. While changes in future precipitation vary across ESMs, the results indicate that the Upper CRB will experience increasing evaporative demand and surface-water scarcity, with some locations experiencing a shift from a radiation-limited to a water-limited evaporation regime in the summer. Large shifts in peak runoff are observed in snowmelt-dominant sub-watersheds, with complete disappearance of the snowmelt signal for some sub-watersheds. The work demonstrates the utility of the NMFk algorithm to efficiently identify behavioral changes of drought indicators across space and time and to quickly analyze and interpret hydro climate model results.

54 ENVIRONMENTAL SCIENCES↗

Linking Stream Chemistry to Subsurface Redox Architecture

As drinking-water scarcity grows worldwide, we need to improve predictions of the quantity and quality of our water resources. An overarching problem for model improvement is that we do not know the geological structure of aquifers in sufficient detail. In this work, we demonstrate that mineral-water reactions imprint structure in the subsurface that impacts the flow and transport of some chemical species. Specifically, pyrite, a ubiquitous mineral, commonly oxidizes and depletes in the upper layers of the weathering profile in most humid watersheds, only remaining at depths of meters. We hypothesize that variations in concentrations (C) of pyrite-derived sulfate released into rivers as a function of discharge (q) reflect the rate-limiting step and depth of pyrite-oxidizing layers. We found that log C - log q behaviors thus differ in small and large watersheds in the Susquehanna River Basin as well as in selected watersheds in the Western United States. Although coal mining changes pyrite oxidation from closed to open system with respect to O 2 , patterns in stream chemistry as a function of discharge are consistent with deep and shallow pyrite oxidation zones in small and large watersheds respectively. Therefore, understanding the subsurface patterns of mineral reactions and how they affect the architecture of aquifers will elucidate patterns of changing river chemistry and our ability to manage water resources in the future under accelerated land use and climate change.

54 ENVIRONMENTAL SCIENCES↗