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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Fate and transport of hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) and its degradation products in sedimentary and volcanic rocks, Los Alamos, New Mexico

High-explosive compounds including hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) were used extensively in weapons research and testing at Los Alamos National Laboratory (LANL). Liquid effluents containing RDX were released to an outfall pond that flowed to Cañon de Valle at LANL's Technical Area 16 (TA-16), resulting in the contamination of the alluvial, intermediate and regional groundwater bodies. Monitoring of groundwater within Cañon de Valle has shown persistent RDX in the intermediate perched zone located between 225 and 311 m below ground surface. Monitoring data also show detectable levels of RDX putative anaerobic degradation products. Batch and column experiments were conducted to determine the extent of adsorption-desorption and transport of RDX and its degradation products (MNX, DNX, and TNX) in major rock types that are within the RDX plume. All experiments in this paper were performed in the dark using water obtained from a well located at the center of the plume, which is fairly oxic and has a neutral pH of 7.5. Retardation factors and partitioning coefficient (K d ) values for RDX were calculated from batch experiments. Additionally, retardation factors and K d values for RDX and its degradation products were calibrated from column experiments using a one-dimensional transport model with equilibrium sorption (linear isotherm). Results from the column and batch experiments showed little to no sorption of RDX to the aquifer materials tested, with retardation factors ranging from 1.0 to 1.8 and K d values varying from 0 to 0.70 L/kg. Finally, results also showed no measurable differences between the transport properties of RDX and its degradation products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Developing a robust geochemical and reactive transport model to evaluate possible sources of arsenic at the CO[subscript 2] sequestration natural analog site in Chimayo, New Mexico

Migration of carbon dioxide (CO{sub 2}) from deep storage formations into shallow drinking water aquifers is a possible system failure related to geologic CO{sub 2} sequestration. A CO{sub 2} leak may cause mineral precipitation/dissolution reactions, changes in aqueous speciation, and alteration of pH and redox conditions leading to potential increases of trace metal concentrations above EPA National Primary Drinking Water Standards. In this study, the Chimayo site (NM) was examined for site-specific impacts of shallow groundwater interacting with CO{sub 2} from deep storage formations. Major ion and trace element chemistry for the site have been previously studied. This work focuses on arsenic (As), which is regulated by the EPA under the Safe Drinking Water Act and for which some wells in the Chimayo area have concentrations higher than the maximum contaminant level (MCL). Statistical analysis of the existing Chimayo groundwater data indicates that As is strongly correlated with trace metals U and Pb indicating that their source may be from the same deep subsurface water. Batch experiments and materials characterization, such as: X-ray diffraction (XRD), scanning electron microscopy (SEM), and synchrotron micro X-ray fluorescence ({mu}-XRF), were used to identify As association with Fe-rich phases, such as clays or oxides, in the Chimayo sediments as the major factor controlling As fate in the subsurface. Batch laboratory experiments with Chimayo sediments and groundwater show that pH decreases as CO{sub 2} is introduced into the system and buffered by calcite. The introduction of CO{sub 2} causes an immediate increase in As solution concentration, which then decreases over time. A geochemical model was developed to simulate these batch experiments and successfully predicted the pH drop once CO{sub 2} was introduced into the experiment. In the model, sorption of As to illite, kaolinite and smectite through surface complexation proved to be the key reactions in simulating the drop in As concentration as a function of time in the batch experiments. Based on modeling, kaolinite precipitation is anticipated to occur during the experiment, which allows for additional sorption sites to form with time resulting in the slow decrease in As concentration. This mechanism can be viewed as trace metal 'scavenging' due to sorption caused secondary mineral precipitation. Since deep geologic transport of these trace metals to the shallow subsurface by brine or CO{sub 2} intrusion is critical to assessing environmental impacts, the effective retardation of trace metal transport is an important parameter to estimate and it is dependent on multiple coupled reactions. At the field scale, As mobility is retarded due to the influence of sorption reactions, which can affect environmental performance assessment studies of a sequestration site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Identifying recharge sources and their impacts on a North Central New Mexico shallow aquifer using unsupervised machine learning

In this article, shallow aquifers are important but highly variable resources in arid to semi-arid regions. Limited shallow aquifer volume results in high sensitivity to recharge fluctuations, which can impact the local fauna and flora, and transport of contaminants in the aquifer or vadose zone. Aquifer response to external forcing (e.g., precipitation) is usually solved by estimating aquifer parameters and running physics-based models to match known fluctuations of hydraulic head. However, this technique is time and computationally expensive. Furthermore, high aquifer complexity decreases precision in physics-based models. Alternatively supervised machine learning is used to predict aquifer dynamics. However, these techniques rely on input data and struggle to interpret aquifer response for missing sources (i.e., snowpack data). To counter these problems, we propose an unsupervised machine learning technique (NMFk) to estimate the impact of different sources on aquifer recharge. NMFk is used to understand the influence of external forcing on shallow aquifer recharge in the Pajarito Plateau (Los Alamos, NM, USA). The results show how NMFk can be used to reduce the data dimension in a complex field dataset to three recharge signals that cause fluctuations within the field data. Here, the source signals are interpreted as rainfall, snowmelt, and a delayed aquifer response to the previous two signals. These results evidence how heterogeneous aquifers delimited by canyons incised into the Pajarito Plateau respond in similar ways to the source signals identified by NMFk. Furthermore, results show the importance of the local geology where faults act as sinks, and anthropogenic disturbances can facilitate infiltration amplifying the interpreted signal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ponderosa pine hydraulic stress predicts more extreme wildfire behavior under future conditions in Bandelier National Monument, New Mexico

Background Live fuel moisture contributes to wildfire spread and reflects plant stress and physiological traits. The anticipated change in live fuel moisture under future conditions is likely non-linear, owing to physiological plant thresholds in water hydraulics. We constructed a mechanistic model of live fuel moisture’s response to water stress to understand the impact of future climate on live fuel moisture. We first gathered data on plant physiology and live fuel moisture for Pinus ponderosa at Bandelier National Monument, NM, USA, and modeled their relationship. We then parameterized a mechanistic plant hydrodynamics model (FATES-HYDRO) to simulate changes in plant stress and a statistical model to simulate the resulting impact on live fuel moisture. We then simulated FATES-HYDRO under future climate anomalies (SSP2-4.5 and SSP5-8.5: 2080–2100) to understand the change in plant stress and estimate its impact on live fuel moisture. Results We found that the number of days below crucial thresholds of live fuel moisture (100% and 79%) increased from contemporary levels (< 100%: 72 days, < 79%: 1.4 days) under SSP2-4.5 (< 100%: 185 days, < 79%: 10.2 day) and increased exponentially under SSP5-8.5 (< 100%: 215 days, < 79%: 65 days). We found that gross primary productivity decreased under both future climate scenarios (contemporary: 336 g C m −2 , SSP2-4.5: 203 g C m −2 , SSP5-8.5: 243 g C m −2 ); however, spring productivity increased under SSP5-8.5, potentially altering fuel loading. We additionally see a potentially lethal loss of conductivity in hydraulic P. ponderosa under SSP5-8.5. Conclusions The overall increase in plant water stress (as represented by loss of hydraulic conductivity and leaf water potential) and lower live fuel moisture appear to be driven by reduced precipitation during late summer monsoons typical of the region, extending the fire season later in the year. We predict increasing variability in the P. ponderosa wildfire regime under both climate projections driven by changing productivity, rising mortality, and an overall decrease in live fuel moisture.

54 ENVIRONMENTAL SCIENCES↗