Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “WATER”

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.

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

At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Tree water dynamics in a drying and warming world: Future tree water dynamics

Disentangling the relative impacts of precipitation reduction and vapour pressure deficit (VPD) on plant water dynamics and determining whether acclimation may influence these patterns in the future is an important challenge. Here, we report sap flux density (FD), stomatal conductance (Gs), hydraulic conductivity (KL) and xylem anatomy in piñon pine (Pinus edulis) and juniper (Juniperus monosperma) trees subjected to five years of precipitation reduction, atmospheric warming (elevated VPD) and their combined effects. No acclimation occurred under precipitation reduction: lower Gs and FD were found for both species compared to ambient conditions. Warming reduced the sensibility of stomata to VPD for both species but resulted in the maintenance of Gs and FD to ambient levels only for piñon. For juniper, reduced soil moisture under warming negated benefits of stomatal adjustments and resulted in reduced FD, Gs and KL. Although reduced stomatal sensitivity to VPD also occurred under combined stresses, reductions in Gs, FD and KL took place to similar levels as under single stresses for both species. Our results show that stomatal conductance adjustments to high VPD could minimize but not entirely prevent additive effects of warming and drying on water use and carbon acquisition of trees in semi-arid regions.

Grossiord, Charlotte↗
NASA NTRS1975

LANDSAT-1 data as it has been applied for land use and water quality data by the Virginia State Water Control Board. 1: The state project. 2: Monitoring water quality from LANDSAT

LANDSAT-1 imagery has been used for water quality and land use monitoring in and around the Swift Creek and Lake Chesdin Reservoirs in Virginia. This has proved useful by (1) helping determine valid reservoir sampling stations, (2) monitoring areas not accessible by land or water, (3) giving the State a viable means of measuring Secchi depth readings in these inaccessible areas, (4) giving an overview of trends in changing sedimentation loadings over a given time period and classifying these waters into various categories, (5) enabling the State to inventory all major lakes and reservoirs and computing their acreage, (6) monitoring land use changes in any specific area, (7) evaluating possible long-term environmental effects of nearby developments, and (8) monitoring and predicting population shifts with possible impact on water quality problems. The main problems in the long-term use of such imagery appear to be cost and lack of consistency due to cloud cover limitations.

Trexler, P. L.↗
DOE OSTI2019

Activation of Water by Thorium Cation: A Guided Ion Beam and Quantum Chemical Study

The reaction of atomic thorium cations with deuterated water as a function of kinetic energy from thermal to 10 eV was studied using guided ion beam tandem mass spectrometry. At thermal energies, both ThO{sup +} + D{sub 2} and DThO{sup +} + D are formed in barrierless exothermic processes and reproduce results in the literature obtained using ion cyclotron resonance mass spectrometry. As the energy is increased, the branching ratio between these two channels changes such that the dominant product changes from ThO{sup +} to DThO{sup +} and back to ThO{sup +}, until ThD{sup +} + OD is energetically available and is the dominant product channel. To help understand these experimental results, a variety of theoretical approaches were tried and used to establish a potential energy surface, which compares well with previous theoretical studies. Utilizing the theoretical results, the kinetic energy dependent branching ratio between the ThO{sup +} + D{sub 2} and DThO{sup +} + D channels was calculated using both RRKM and phase space theory (PST). The results indicate that consideration of angular momentum conservation (as in PST) and spin-orbit corrected energies are needed to reproduce experimental results quantitatively. The PST modeling also provides relative energies for the two competing transition states that lead to the primary products, for which theory provides reasonable agreement. .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Greenlighting Photoelectrochemical Oxidation of Water by Iron Oxide

Hematite (alpha-Fe2O3) is one of just a few candidate electrode materials that possess all of the following photocatalyst-essential properties for scalable application to water oxidation: excellent stability, earth-abundance, suitability positive valence-band-edge energy, and significant visible light absorptivity. Despite these merits, hematites modest oxygen evolution reaction kinetics and its poor efficiency in delivering photogenerated holes, especially holes generated by green photons, to the electrode/solution interface, render it ineffective as a practical water-splitting catalyst. Here we show that hole delivery and catalytic utilization can be substantially improved through Ti alloying, provided that the alloyed material is present in ultrathin-thin-film form. Notably, the effects are most pronounced for charges photogenerated by photons with energy comparable to the band gap for excitation of Fe(3d) -> Fe(3d) transitions (i.e., green photons). Additionally, at the optimum Ti substitution level the lifetimes of surface-localized holes, competent for water oxidation, are extended. Together these changes explain an overall improvement in photoelectrochemical performance, especially enhanced internal quantum efficiencies, observed upon Ti(IV) incorporation.

absorbed photon-to-current conversion efficiency (↗
DOE OSTI2017

Hotspots of soil N 2 O emission enhanced through water absorption by plant residue

N 2 O is a highly potent greenhouse gas and arable soils represent its major anthropogenic source. Field-scale assessments and predictions of soil N 2 O emission remain uncertain and imprecise due to the episodic and microscale nature of microbial N 2 O production, most of which occurs within very small discrete soil volumes. Such hotspots of N 2 O production are often associated with decomposing plant residue. Here we quantify physical and hydrological soil characteristics that lead to strikingly accelerated N 2 O emissions in plant residue-induced hotspots. Results reveal a mechanism for microscale N 2 O emissions: water absorption by plant residue that creates unique micro-environmental conditions, markedly different from those of the bulk soil. Moisture levels within plant residue exceeded those of bulk soil by 4–10-fold and led to accelerated N 2 O production via microbial denitrification. The presence of large (Ø >35 μm) pores was a prerequisite for maximized hotspot N 2 O production and for subsequent diffusion to the atmosphere. Understanding and modelling hotspot microscale physical and hydrologic characteristics is a promising route to predict N 2 O emissions and thus to develop effective mitigation strategies and estimate global fluxes in a changing environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Precursor Evolution and Stress Corrosion Cracking Initiation of Cold-Worked Alloy 690 in Simulated Pressurized Water Reactor Primary Water

Stress corrosion crack initiation of two thermally-treated, cold-worked (CW) alloy 690 (UNS N06690) materials was investigated in 360oC simulated PWR primary water using constant load tensile (CLT) tests and blunt notch compact tension (BNCT) tests equipped with direct current potential drop (DCPD) for in-situ detection of cracking. SCC initiation was not detected by DCPD for either the 21% or 31%CW CLT specimens loaded at their yield stress after ~9,220 hours, however intergranular (IG) precursor damage and isolated surface cracks were observed on the specimens. The two 31%CW BNCT specimens loaded at moderate stress intensity after several cyclic loading ramps showed DCPD-indicated crack initiation after 10,400 hours of exposure at constant stress intensity, which was resulted from significant growth of IG cracks. The 21%CW BNCT specimens only exhibited isolated small IG surface cracks and showed no apparent DCPD change throughout the test. Post-test cross-section examinations revealed many grain boundary (GB) nano-cavities in the bulk of all the CLT and BNCT specimens particularly for the 31%CW materials. Cavities were also found along GBs extending to the surface suggesting an important role in crack nucleation. This paper provides an overview of the evolution of GB cavities and discusses their effects on crack initiation in CW alloy 690.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2013

Life Cycle Water Consumption and Water Resource Assessment for Utility-Scale Geothermal Systems: An In-Depth Analysis of Historical and Forthcoming EGS Projects

This report is the third in a series of reports sponsored by the U.S. Department of Energy Geothermal Technologies Program in which a range of water-related issues surrounding geothermal power production are evaluated. The first report made an initial attempt at quantifying the life cycle fresh water requirements of geothermal power-generating systems and explored operational and environmental concerns related to the geochemical composition of geothermal fluids. The initial analysis of life cycle fresh water consumption of geothermal power-generating systems identified that operational water requirements consumed the vast majority of water across the life cycle. However, it relied upon limited operational water consumption data and did not account for belowground operational losses for enhanced geothermal systems (EGSs). A second report presented an initial assessment of fresh water demand for future growth in utility-scale geothermal power generation. The current analysis builds upon this work to improve life cycle fresh water consumption estimates and incorporates regional water availability into the resource assessment to improve the identification of areas where future growth in geothermal electricity generation may encounter water challenges. This report is divided into nine chapters. Chapter 1 gives the background of the project and its purpose, which is to assess the water consumption of geothermal technologies and identify areas where water availability may present a challenge to utility-scale geothermal development. Water consumption refers to the water that is withdrawn from a resource such as a river, lake, or nongeothermal aquifer that is not returned to that resource. The geothermal electricity generation technologies evaluated in this study include conventional hydrothermal flash and binary systems, as well as EGSs that rely on engineering a productive reservoir where heat exists, but where water availability or permeability may be limited. Chapter 2 describes the approach and methods for this work and identifies the four power plant scenarios evaluated: a 20-MW EGS binary plant, a 50-MW EGS binary plant, a 10-MW hydrothermal binary plant, and a 50-MW hydrothermal flash plant. The methods focus on (1) the collection of data to improve estimation of EGS stimulation volumes, aboveground operational consumption for all geothermal technologies, and belowground operational consumption for EGS; and (2) the mapping of the geothermal and water resources of the western United States to assist in the identification of potential water challenges to geothermal growth. Chapters 3 and 4 present the water requirements for the power plant life cycle. Chapter 3 presents the results of the current data collection effort, and Chapter 4 presents the normalized volume of fresh water consumed at each life cycle stage per lifetime energy output for the power plant scenarios evaluated. Over the life cycle of a geothermal power plant, from construction through 30 years of operation, the majority of water is consumed by plant operations. For the EGS binary scenarios, where dry cooling was assumed, belowground operational water loss is the greatest contributor depending upon the physical and operational conditions of the reservoir. Total life cycle water consumption requirements for air-cooled EGS binary scenarios vary between 0.22 and 1.85 gal/kWh, depending upon the extent of belowground operational water consumption. The air-cooled hydrothermal binary and flash plants experience far less fresh water consumption over the life cycle, at 0.04 gal/kWh. Fresh water requirements associated with air- cooled binary operations are primarily from aboveground water needs, including dust control, maintenance, and domestic use. Although wet-cooled hydrothermal flash systems require water for cooling, these plants generally rely upon the geofluid, fluid from the geothermal reservoir, which typically has high salinity and total dissolved solids concentration and is much warmer than normal groundwater sources, for their cooling water needs; thus, while there is considerable geofluid loss at 2.7 gal/kWh, fresh water consumption during operations is similar to that of aircooled binary systems. Chapter 5 presents the assessment of water demand for future growth in deployment of utility-scale geothermal power generation. The approach combines the life cycle analysis of geothermal water consumption with a geothermal supply curve according to resource type, levelized cost of electricity (LCOE), and potential growth scenarios. A total of 17 growth scenarios were evaluated. In general, the scenarios that assumed lower costs for EGSs as a result of learning and technological improvements resulted in greater geothermal potential, but also significantly greater water demand due to the higher water consumption by EGSs. It was shown, however, that this effect could be largely mitigated if nonpotable water sources were used for belowground operational water demands. The geographical areas that showed the highest water demand for most growth scenarios were southern and northern California, as well as most of Nevada. In addition to water demand by geothermal power production, Chapter 5 includes data on water availability for geothermal development areas. A qualitative analysis is included that identifies some of the basins where the limited availability of water is most likely to affect the development of geothermal resources. The data indicate that water availability is fairly limited, especially under drought conditions, in most of the areas with significant near- and medium-term geothermal potential. Southern California was found to have the greatest potential for water-related challenges with its combination of high geothermal potential and limited water availability. The results of this work are summarized in Chapter 6. Overall, this work highlights the importance of utilizing dry cooling systems for binary and EGS systems and minimizing fresh water consumption throughout the life cycle of geothermal power development. The large resource base for EGSs represents a major opportunity for the geothermal industry; however, depending upon geology, these systems can require large quantities of makeup water due to belowground reservoir losses. Identifying potential sources of compatible degraded or low-quality water for use for makeup injection for EGS and flash systems represents an important opportunity to reduce the impacts of geothermal development on fresh water resources. The importance of identifying alternative water sources for geothermal systems is heightened by the fact that a large fraction of the geothermal resource is located in areas already experiencing water stress. Chapter 7 is a glossary of the technical terms used in the report, and Chapters 8 and 9 provide references and a bibliography, respectively.

15 GEOTHERMAL ENERGY↗
NASA NTRS2018

Water Across Synthetic Aperture Radar Data (WASARD): SAR Water Body Classification for the Open Data Cube

The detection of inland water bodies from Synthetic Aperture Radar (SAR) data provides a great advantage over water detection with optical data, since SAR imaging is not impeded by cloud cover. Traditional methods of detecting water from SAR data involves using thresholding methods that can be labor intensive and imprecise. This paper describes Water Across Synthetic Aperture Radar Data (WASARD): a method of water detection from SAR data which automates and simplifies the thresholding process using machine learning on training data created from Geoscience Australia’s WOFS algorithm. Of the machine learning models tested, the Linear Support Vector Machine was determined to be optimal, with the option of training using solely the VH polarization or a combination of the VH and VV polarizations. WASARD was able to identify water in the target area with a correlation of 97% with WOFS. Sentinel-1, Open Data Cube, Earth Observations, Machine Learning, Water Detection 1. INTRODUCTION Water classification is an important function of Earth imaging satellites, as accurate remote classification of land and water can assist in land use analysis, flood prediction, climate change research, as well as a variety of agricultural applications [2]. The ability to identify bodies of water remotely via satellite is immensely cheaper than contracting surveys of the areas in question, meaning that an application that can accurately use satellite data towards this function can make valuable information available to nations which would not be able to afford it otherwise. Highly reliable applications for the remote detection of water currently exist for use with optical satellite data such as that provided by LANDSAT. One such application, Geoscience Australia’s Water Observations from Space (WOFS) has already been ported for use with the Open Data Cube [6]. However, water detection using optical data from Landsat is constrained by its relatively long revisit cycle of 16 days [5], and water detection using any optical data is constrained in that it lacks the ability to make accurate classifications through cloud cover [2]. The alternative solution which solves these problems is water detection using SAR data, which images the Earth using cloud-penetrating microwaves. Because of its advantages over optical data, much research has been done into water detection using SAR data. Traditionally, this has been done using the thresholding method, which involves picking a polarization band and labeling all pixels for which this band’s value is below a certain threshold as containing water. The thresholding method works since water tends to return a much lower backscatter value to the satellite than land [1]. However, this method can be flawed since estimating the proper threshold is often imprecise, complicated, and labor intensive for the end user. Thresholding also tends to use data from only one SAR polarization, when a combination of polarizations can provide insight into whether water is present. [2] In order to alleviate these problems, this paper presents an application for the Open Data Cube to detect water from SAR data using support vector machine (SVM) classification. 2. PLATFORM WASARD is an application for the Open Data Cube, a mechanism which provides a simple yet efficient means of ingesting, storing, and retrieving remote sensing data. Data can be ingested and made analysis ready according to whatever specifications the researcher chooses, and easily resampled to artificially alter a scene’s resolution. Currently WASARD supports water detection on scenes from ESA’s Sentinel-1 and JAXA’s ALOS. When testing WASARD, Sentinel-1 was most commonly used due to its relatively high spatial resolution and its rapid 6 day revisit cycle [5]. With minor alterations to the application's code, however, it could support data from other satellites. 3. METHODOLOGY Using supervised classification, WASARD compares SAR data to a dataset pre-classified by WOFS in order to train an SVM classifier. This classifier is then used to detect water in other SAR scenes outside the training set. Accuracy was measured according to the following metrics:  Precision: a measure of what percentage of the points WASARD labels as water are truly water  Recall: a measure of what percentage of the total water cover WASARD was able to identify.  F1 Score: a harmonic average of the precision and recall scores Both precision and recall are calculated at the end of the training phase, when the trained classifier is compared to a testing dataset. Because the WOFS algorithm’s classifications are used as the truth values when training a WASARD classifier, when precision and recall are mentioned in this paper, they are always with respect to the values produced by WOFS on a similar scene of Landsat data, which themselves have a classification accuracy of 97% [6]. Visual representations of water identified by WASARD in this paper were produced using the function wasard_plot(), which is included in WASARD. 3.1 Algorithm Selection The machine learning model used by WASARD is the Linear Support Vector Machine (SVM). This model uses a supervised learning algorithm to develop a classifier, meaning it creates a vector which can be multiplied by the vector formed by the relevant data bands to determine whether a pixel in a SAR scene contains water. This classifier is trained by comparing data points from selected bands in a SAR scene to their respective labels, which in this case are “water” or “not water” as given by the WOFS algorithm. The SVM was selected over the Random Forest model, which outperformed the SVM in training speed, but had a greater classification time and lower accuracy, and the Multilayer Perceptron Artificial Neural Network, which had a slightly higher average accuracy than the SVM, but much greater training and classification times. Figure 1: Visual representation of the SVM Classifier. Each white point represents a pixel in a SAR scene. In Figure 1, the diagonal line separating pixels determined to be water from those determined not to be water represents the actual classification vector produced by the SVM. It is worth noting that once the model has been trained, classification of pixels is done in a similar manner as in the thresholding method. This is especially true if only one band was used to train the model. 3.1 Feature Selection Sentinel-1 collects data from two bands: the Vertical/Vertical polarization (VV) and the Vertical/Horizontal polarization (VH). When 100 SVM classifiers were created for each polarization individually, and for the combination of the two, the following results were achieved: Figure 2: Accuracy of classifiers trained using different polarization bands. Precision and Recall were measured with respect to the values produced by WOFS. Figure 2 demonstrates that using both the VV and VH bands trades slightly lower recall for significantly greater precision when compared with the VH band alone, and that using the VV band alone is inferior in both metrics. WASARD therefore defaults to using both the VV and VH bands, and includes the option to use solely the VH band. The VV polarization’s lower precision compared to the VH polarization is in contrast to results from previous research and may merit further analysis [4]. 3.2 Training a Classifier The steps in training a classifier with WASARD are 1. Selecting two scenes (one SAR, one optical) with the same spatial extents, and acquired close to each other in time, with a preference that the scenes are taken on the same day. 2. Using the WOFS algorithm to produce an array of the detected water in the scene of optical data, to be used as the labels during supervised learning 3. Data points from the selected bands from the SAR acquisition are bundled together into an array with the corresponding labels gathered from WOFS. A random sample with an equal number of points labeled “Water” and “Not Water” is selected to be partitioned into a training and a testing dataset 4. Using Scikit-Learn’s LinearSVC object, the training dataset is used to produce a classifier, which is then tested against the testing dataset to determine its precision and recall The result is a wasard_classifier object, which has the following attributes: 1. f1, recall, and precision: 3 metrics used to determine the classifier’s accuracy 2. Coefficient: Vector which the SVM uses to make its predictions. The classifier detects water when the dot product of the coefficient and the vector formed by the SAR bands is positive 3. Save(): allows a user to save a classifier to the disk in order to use it without retraining 4. wasard_classify(): Classifies an entire xarray of SAR data using the SVM classifier All of the above steps are performed automatically when the user creates a wasard_classifier object. 3.3 Classifying a Dataset Once the classifier has been created, it can be used to detect water in an xarray of SAR data using wasard_classify(). By taking the dot product of the classifier’s coefficients and the vector formed by the selected bands of SAR data, an array of predictions is constructed. A classifier can effectively be used on the same spatial extents as the ones where it was trained, or on any area with a similar landscape. While

Kreiser, Zachary↗
DOE OSTI2014

Integrated assessment of global water scarcity over the 21st century under multiple climate change mitigation policies

Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change and climate mitigation policies, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5 o x 0.5o resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W/m2 (equivalent to the SRES A1Fi emission scenario) and three climate policy scenarios with increasing mitigation stringency of 7.7, 5.5, and 4.2 W/m2 (equivalent to the SRES A2, B2, and B1 emission scenarios, respectively), we investigate the effects of emission mitigation policies on water scarcity. Two carbon tax regimes (a universal carbon tax (UCT) which includes land use change emissions, and a fossil fuel and industrial emissions carbon tax (FFICT) which excludes land use change emissions) are analyzed. The baseline scenario results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Additionally, in years 2050 and 2095, 36% (28%) and 44% (39%) of the global population, respectively, is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). When comparing the climate policy scenarios to the baseline scenario while maintaining the same baseline socioeconomic assumptions, water scarcity declines under a UCT mitigation policy but increases with a FFICT mitigation scenario by the year 2095 particularly with more stringent climate mitigation targets. Under the FFICT scenario, water scarcity is projected to increase driven by higher water demands for bio-energy crops.

climate policy↗
DOE OSTI2019

Case Study: Integrate Nuclear Water Desalination - Regional Potable Water in Arizona

The present study analyzes the economic viability of an Integrated Energy System (IES) that couples a Reverse Osmosis (RO) water desalination facility with a Nuclear Power Plant (NPP). The case study is conducted in collaboration with Arizona Public Service (APS), the operating owner of the Palo Verde Generating Station (PVGS) NPP. Cooling water for the reactor steam cycle is derived from treated effluent from municipal wastewater treatment plants. APS has established a long-term water resources program to effect a substantial reduction in plant cooling costs through advanced treatment and cooling technologies, and through the use of alternative water sources to replace the increasingly expensive effluent. One possible option is to replace some amount of the annual volume of effluent with brackish groundwater from a local regional aquifer. Although much less expensive than the municipal effluent, the quantity of brackish groundwater that could be used for plant cooling is limited as a result of the salinity and its impact on plant operation. Consequently, supplemental treatment could be required such that a greater amount of brackish groundwater could be used to reduce the demand on effluent. A study was conducted in 2018 by Idaho National Laboratory (INL) to investigate the economics of a PVGS onsite RO desalination plant that would reduce the salinity of a municipal effluent and brackish water blend to an acceptable level. One of the main findings of that study was that the overall economics of water desalination can be greatly improved if, in addition to cooling water for PVGS, potable water could also be produced and sold for profit. In fact, the study concluded that only producing cooling water for PVGS via RO desalination is not economically viable. The present report investigates the economic impact of a large, regional RO desalination plant that could provide potable water for the region, considering the conclusions from the 2018 scoping study. The study looks in particular at the water-market situation for the developing municipalities in the west valley of Phoenix. In addition to providing potable water for the municipalities, the existing infrastructure that conveys effluent to the Palo Verde plant and onsite water treatment facilities could be used to manage the RO concentrate. The processed concentrate could lead to a cost reduction in plant cooling by replacing some amount of effluent. The analysis reported here considers two cases (for various scenarios). First, the Base Case considers that neither the regional nor the onsite RO is built. The 2018 INL study showed that some brackish water can be blended with the municipal effluent water without having to build the onsite RO. That correspond to the maximum economically profitable option. The Base Case is where APS pumps the maximum volume of less-expensive brackish water (limited by water chemistry in the circulating water system), i.e. the case for which cooling water acquisition and treatment cost are lowest (without RO). Second, the proposed RO Case includes two RO plants, one onsite at PVGS and another larger, regional RO plant close to the brackish water wells. The regional RO produces potable water that is sold to the regional municipalities, while the PVGS onsite RO treats (part of) the regional ROs' concentrate and brackish water blend. The desalinated water from the PVGS RO is used in the circulating water system at PVGS. The analysis evaluates the difference in economics, using the Net Present Value (NPV) and Internal Rate of Return (IRR), between the cases. By comparing the two cases, in addition to evaluating the economics of the regional RO, we can also assess the impact of the regional RO on PVGS operational costs and, consequently, APS economics. The study shows that there exist combinations of regional RO and PVGS RO sizes for which the total blowdown and water chemistry limits at PVGS (including regional RO concentrate treatment at PVGS) are satisfied. However, such combinations only exist if no additional brackish water is directly mixed in the tertiary water system at PVGS. This leads to higher Levelized Costs of Potable Water (LCOPW) compared to cases where additional brackish water is injected (but violate the physical constraints). Additional studies are suggested to investigate the benefit of additional brackish water injection (lowers cooling water cost) versus the cost of lifting the physical constraints, e.g. building additional evaporation ponds. Staying in the case of no additional brackish water and satisfying the existing PVGS constraints, the lowest LCOPW (~0.5 $/m 3 ) can be achieved with a size of the regional RO of ~1.4e7 m 3 /yr (11000 AF/yr) capacity, which leads to ~8.63e6 m 3 /yr (7000 AF/yr) of potable water while no onsite RO at PVGS is built. Considering the vii residential water demand model developed for the Phoenix west valley, the NPV for this regional RO would be ~$100 million if all municipalities in the vicinity participate from the beginning of the project.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

A Modeling Framework for Evaluating the Drought Resilience of a Surface Water Supply System under Non-stationarity

The future resilience of water supply systems is unprecedentedly challenged by non-stationary processes, such as fast population growth and a changing climate. A thorough understanding of how these non-stationarities impact water supply resilience is vital to support sustainable decision making, particularly for large cities in arid and/or semi-arid regions. In this study, a novel modeling framework, which integrates hydrological processes and water management, was established over a representative water limited metropolitan area to evaluate the impacts of water availability and water demand on reservoir storage and water supply reliability. In this framework, climate change induced drought events were selected from statistically downscaled Coupled Model Intercomparison Project Phase 5 outputs under the Representative Concentration Pathway 8.5 scenario, while future water demand was estimated by the product of projected future population and per capita water use. Compared with the first half of the 21st century (2000–2049), reservoir storage and water supply reliability during the second half century (2050–2099) are projected to reduce by 16.1% and 14.2%, respectively. While both future multi-year droughts and population growth will lower water supply resilience, the uncertainty associated with future climate projection is larger than that associated with urbanization. To reduce the drought risks, a combination of mitigation strategies (e.g., additional conservation, integrating new water sources, and water use redistribution) was found to be the most efficient approach and can significantly improve water supply reliability by as much as 15.9%.

Zhao, Gang (ORCID:0000000327370530)↗
DOE OSTI2020

Continuous Monitoring and Partial Water Softening for Cooling Tower Water Treatment

Cooling towers are an integral component of many refrigeration systems, providing comfort or process cooling across a broad range of applications. They are the point in the system where heat is dissipated to the atmosphere through the evaporative cooling process. Cooling towers are commonly found in industrial applications and are also often used in water-cooled chilled water plants in medium to large commercial buildings. Continuous monitoring and partial water softening for cooling towers used in medium to large commercial buildings are the focus of this paper. Cooling towers consume large amounts of water. Cooling tower-related water consumption is one of largest potable water loads within buildings in the United States, with substantial building water use associated with heating and cooling. Regional water shortages have highlighted a need to reduce water consumption; the U.S. General Services Administration (GSA) and Executive Order 13834 place priority on reducing water consumption. This priority has fueled interest in the identification, investigation, and potential broad deployment of cost-effective opportunities to reduce water use, such as alternative water treatment (AWT) technologies for cooling towers. Traditional water treatment approaches use chemicals to extend the ability of the water to hold scaling minerals in suspension, minimize corrosion, and prevent biological growth. This treatment protects the chillers and cooling tower equipment; however, even when chemicals are used regularly, a certain percentage of condenser water must be drained and made up with fresh water to maintain system water quality parameters. In addition, the use of chemicals sometimes creates a waste disposal issue and can cause building owners to incur additional fees, such as disposal or wastewater charges. To manage cooling tower water treatment, GSA typically contracts with a company specializing in conventional chemical maintenance for a fixed fee. While there are many types and vendors of AWT systems, this project assesses the effectiveness of one technology provided by Aqualogix. This system is a chilled water plant monitoring and control system aimed at optimizing system performance by reducing the blowdown occurrences used to remove mineral build-up. The technology consists of two components – continuous programmable logic control (PLC) monitoring and side-stream filtration with partial water softening. PLC monitoring calculates cycles of concentration (CoC) and determines the optimum amount of blowdown water required to satisfy all water chemistry requirements. Side-stream filtration removes suspended matter and improves biocide efficacy while precisely dispensing softened water to achieve optimal makeup water hardness. Unlike other AWT systems evaluated by GSA to date, this system does not replace the legacy treatment system but is used in addition to chemical water treatment. The vendor claims their technology will reduce water consumption, water discharge, and maintenance costs. The AWT system evaluated in this demonstration is a commercialized technology. Given its commercialized state, the system evaluated in this report is at a Technology Readiness Level 9 according to National Aeronautics and Space Administration (NASA) definitions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Water-gas shift: Characterization and testing of nanoscale YSZ supported Pt catalysts

Nano-scale Y-doped zirconium oxide materials were prepared with high surface areas (150-200 m(2)/g) and small nano-crystallites (<8 nm). A combination of XANES and EXAFS was used to show that ZrO2 exhibited the tetragonal phase, while the Zr0.5Y0.5O1.75 support displayed the cubic phase. A comparison with undoped zirconia suggests that the Zr0.9Y0.1O1.95 support was tetragonal in structure. A slight increase in d-spacing observed in HR-TEM for the Zr0.9Y0.1O1.95 support relative to undoped ZrO2, along with a shift to lower 2 theta in XRD, provide evidence that Y-doping caused macrostrain. STEM imaging confirmed that the Pt clusters ranged from 0.5 to 2 nm over all three supports. Catalyst reducibility was explored by H-2-TPR, XANES at the Zr K-edge, and TPR-XANES at the Pt L-III edge. A higher concentration of surface defects for the 0.5%Pt/Zr0.9Y0.1O1.95 catalyst relative to 0.5%Pt/ZrO2 was confirmed by DRIFTS of adsorbed CO, while a greater surface mobility of surface formate was suggested based on forward formate decomposition experiments in steam. The Y-doped Pt promoted catalysts displayed higher water-gas-shift activity relative to the 0.5%Pt/ZrO2 catalyst when the Y content was at or below 50%, with the best catalyst being 0.5%Pt/Zr0.9Y0.1O1.95. (C) 2015 Elsevier B.V. All rights reserved.

Pt/YSZ↗