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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Wasatch Fault Structure from Machine Learning Arrival Times and High-Precision Earthquake Locations

Abstract On 18 March 2020, a magnitude 5.7 earthquake hit the Salt Lake valley in the state of Utah, United States. Using a dense geophone deployment and machine learning (ML), an additional several thousand events were detected and located. Currently, both the mainshock and the majority of the aftershocks are suspected to have occurred on or near a deeper portion of the Salt Lake segment of the Wasatch fault—part of a large range-bounding fault system thought to be capable of generating an Mw 7.2 earthquake. However, a small subset of aftershocks may have occurred on a portion of the more steeply, eastward dipping, and poorly understood West Valley fault. Unfortunately, the catalog locations and lack of focal mechanisms for this subset of aftershocks provide only a crude constraint on the true fault structure. To better illuminate fault structure, we relocate the ML-generated catalog with a range of magnitudes from −2 to 4.6, using: (1) NonLinLoc, a nonlinear location algorithm, (2) source-specific station terms, and (3) waveform coherence. We further compute first-motion focal mechanisms for 68 events. Results of the relocation suggest a simpler, minimally listric Wasatch fault geometry, contrary to what has been previously proposed. We also find that analysis of the focal mechanisms and waveform similarity indicates minimal event similarity throughout the Magna sequence, suggesting a highly complex and heterogeneous rupture zone, as opposed to rupture on a single plane. These findings suggest an increased seismic hazard due to the overall shallowness of the earthquake sequence and highly varied rupture mechanisms.

Geochemistry & Geophysics↗
DOE OSTI2020

Research Introduction [Slides]

In the topic of Reverse Time Imaging, we proposed a new IC to reduce computation cost but reserve image resolution for distributed sensor networks. For Induced Seismicity in Oklahoma, we analyzed fault stress state analysis at state scale, and we applied machine learning techniques to polarity picking and seismicity rate forecasting. The results provide better understanding of fault properties, stress field, and the relationships among fault, stress state, injections, and potential seismic hazards. Lastly, for Microseismic Monitoring, we detected and located 770 low-frequency events (5-50 Hz): (1) Shallow events are highly clustered, consistent with the pathway from injection well 13-10A to monitoring well; moment tensor inversion shows dominant tensile cracking; (2) Deep events are scattered and show migration pattern to the basement; moment tensors show that most events are shear cracks.

58 GEOSCIENCES↗
DOE OSTI2026

Techno Economic Analysis for Production of Renewable Natural Gas and Value-Added Chemicals from Forest Biomass Residues (CRADA Final Report)

West Biofuels - in collaboration with the University of California San Diego, the University of California Davis, the National Laboratory of the Rockies (NLR), the Colorado School of Mines’ Center for Hydrate Research, Placer County Air Pollution Control District, the Sierra Business Council, and the Southern California Gas Company (SoCalGas)-will demonstrate an innovative pathway to convert forest biomass to renewable gas (RG). The project, Production of Pipeline Grade Renewable Natural Gas and Value-Added Chemicals from Forest Biomass Residues, will utilize an existing pilot-scale gasification system and data and lessons learned from a lab-scale catalytic reactor design, develop, and demonstrate an integrated pilot-scale RG process with a scaled-up catalytic reactor and hydrate-based gas separation process. This robust and simple process uses a commercial proven gasifier, a commercially available catalyst that can tolerate gas contaminants, and a gas separation process that simplifies the downstream processing. Current testing has shown that the process can yield a large amount of methane rich renewable gas in addition to a mixture of propanol, ethanol and other higher alcohols and the relative amounts can be controlled by shifting the process conditions. This process is novel and groundbreaking because the product mixture of RG and valuable alcohols byproducts makes RG production economically feasible at $\$$12 per million British thermal units (MMBtu) or less using forest biomass from high hazard zones.

09 BIOMASS FUELS↗
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Chemical and Radiological Compatibility Testing of 3D Printed Materials

To dramatically increase the adaptability, performance, and safety of processes in support of the Defense Waste Processing Facility (DWPF), Savannah River National Lab (SRNL) plans to perform chemical and radiological compatibility testing on a wide variety of 3D printed materials of interest. The 3D printing process provides numerous strategic operational benefits such as rapid prototyping of complex designs and geometry specific to the needs of the nuclear waste disposition process, as well as on-demand rapid prototyping and iteration with materials that aren’t as accessible through traditional manufacturing methods. Reaction chemistry in simulated waste batches can be matched closely to its radioactive counterpart, but glass reactor vessels have limitations. Vessel geometry can play a big factor in mixing transport limitations, process chemistry, and degradation reaction kinetics. In addition, additive manufacturing allows for much more detailed vessel design than traditional alternatives. Waste processing techniques in DWPF also encounter extreme chemical environments including high pH, strong acids, abrasive slurries, and significant irradiation. To meet these challenges, a matrix of various polymer, ceramic, and metal additive manufacturing materials have been exposed to a suite of chemical environments of interest as well as radioactive dose (such as gamma radiation from 60 Co) to properly test their durability under these conditions. Mass change has been monitored over a period of up to a week in these conditions, as well as added characterization for surface modification through Scanning Electron Microscopy/Electron Dispersive X-ray analysis (SEM/EDX). Further chemical characterization has been monitored through Fourier-Transform InfraRed Spectroscopy (FTIR), with planned investigation via thermal and tensile strength degradation. While the direct product of this research is identification of material(s) that can withstand specific hazardous environments encountered by the mercury water wash tank in DWPF process simulation experiments, the reference base of materials will be used for many other nuclear processes in the pursuit of rapidly developed, cost-efficient, and highly specific devices for environmental remediation and much more.

Wilson, Nathan W. [Savannah River National Laborat↗
DOE OSTI2023

A mechanistic model of a PWR-based nuclear power plant in response to external hazard-induced station blackout accidents

Natural hazard-induced nuclear accidents, such as the Fukushima Daiichi Accident that occurred in Japan in 2011, have significantly increased reactor safety studies in understanding nuclear power plant (NPP) responses to external hazard events such as earthquakes and floods. Natural hazards could cause the loss of offsite power in nuclear power plants, potentially leading to a Station Blackout (SBO) accident that significantly contributes to the overall risk of nuclear power plant accidents. Despite the fact that extensive research has been conducted on the station blackout accident for nuclear power plant, further understanding of these events is needed, particularly in the context of the dynamic nature of external hazards such as external flooding. This paper estimates the progression of station blackout events for a generic pressurized water reactor (PWR) in response to external flooding events. The original RELAP5-3D model of the Westinghouse four-loop design pressurized water reactor was adopted and modified to simulate the external flood-induced station blackout accident, including the short-term and long-term station blackout scenarios. A sensitivity analysis of long-term station blackout, examining reactor operation times and analyzing key parameters over time, was also conducted in this work. The results of the analyses, especially the critical timing parameters of key event sequences, provide useful insights about the time during the external flooding event, which is important for plant operators to make timely decisions to prevent potential core damage. This paper represents significant progress toward developing an integrated risk assessment framework for further identifying and assessing the effects of the critical sources of uncertainties of nuclear power plant under external hazard-induced events.

Liu, Tao↗
DOE OSTI2021

Uranium Prototype Glovebox and Furnace Design and Build (SPC-2954)

This specification contains the requirements for design, analysis, fabrication, testing and delivery of the Uranium Prototype Glovebox (UPG) and Furnace, and the associated equipment as described herein. The UPG will be primarily used for the containment of uranium and the prototyping of equipment to be used in higher hazard category gloveboxes. This will allow complex pieces of equipment to be tested in a less hazardous environment prior to fabrication and installation in other gloveboxes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

AI-Enabled Robots for Automated Nondestructive Evaluation and Repair of Power Plant Boilers. Final Report

Boiler failure could cause loss of life and safety issues, cost hundreds of thousands of dollars in equipment repairs, property damage and production losses, and drive up the cost of electric power. Boiler maintenance is challenging and risky for inspectors working on scaffolding in confined hazardous spaces inside of a boiler and sometimes the space is hard to access. The operation is also time-consuming due to the large area of vertical structures for inspection and the tremendous effort needed for scaffolding. Recently, the use of robotics (e.g., drones and crawlers) in power plants for maintenance is growing rapidly. However, the existing robotics solutions show two notable technological gaps: no live repair capability, and no Artificial Intelligence (AI) for smart autonomy. The objective of this project is to develop an integrated autonomous robotic platform that is equipped with compact non-destructive evaluation (NDE) sensors to perform live inspection, operates onboard repair devices to perform live repair, and uses AI for intelligent data fusion and predictive analysis for automated and smart spatiotemporal inspection, analysis and repair of the furnace walls in coal-fired boilers. The approach to achieve the objective includes developing NDE sensors with signal processing techniques, designing and evaluating repair devices for robots based on fusion and solid-state technologies, and an autonomous robotic platform that can attach to and navigate on boiler furnace walls using magnetic drive tracks. The robot is also powered by AI to automate data gathering (e.g., 3D mapping and damage localization) and predictive analysis. This project has advanced the state-of-the-art by providing technological breakthroughs including compact NDE and repair tools for robots, AI capabilities for smart autonomy, and a robotic platform for automated boiler maintenance. This project has great potential to result in significant benefits including limiting or eliminating the need to send operators to assess difficult-to-access or hazardous areas, enabling automated live inspection and repair, avoiding time consuming scaffolding (especially for partial maintenance during unplanned outage), collecting comprehensive and well-organized data smartly, and avoiding or limiting the need for onsite or remote piloting technicians. The impacts can be tremendous in terms of the time and cost savings, reducing the risk for human operators, and increasing boiler reliability, usability, and efficiency. In addition, by developing the new technologies on the autonomous inspection and repair robot, by involving multiple undergraduate and graduate students working together with the faculty members on this project, and by generating knowledge and building up collaborations with industrial partners, this effort will significantly update the education capabilities, support long-term fundamental research, and maintain the leadership of Colorado School of Mines and Michigan State University in energy fields.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

A database of global storm surge reconstructions

Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use a data-driven modeling framework to simulate daily maximum surge values at 882 tide gauge locations across the globe. We use five different atmospheric reanalysis products for the storm surge reconstruction, the longest one going as far back as 1836. The data that we generate can be used, for example, for long-term trend analyses of the storm surge climate and identification of regions where changes in the intensity and/or frequency of storms surges have occurred in the past. It also provides a better basis for robust extreme value analysis, especially for tide gauges where observational records are short. The data are made available for public use through an interactive web-map as well as a public data repository.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Mitigation of safety and environmental challenges posed by refrigerants

The abatement of safety and environmental burden associated with low and ultra-low Global Warming Potential (GWP) refrigerants is a critical undertaking. As the industry shifts towards more environmentally friendly alternatives, mitigating the potential risks and ensuring safety standards becomes paramount. The adoption of mildly and highly flammable refrigerants contributes significantly to minimizing the greenhouse gas impact on the environment, aligning with global climate and sustainability goals. However, it is essential to address safety concerns and potential environmental implications associated with the end use of these refrigerants. A method to mitigate the safety risk in a flammable refrigerant based heating, ventilation, air-conditioning, and refrigeration (HVACR) system is the primary focus of this paper. Advent of A2L and A3 refrigerants as replacements to high GWP refrigerants requires careful handling of leak episodes to lower or eliminate the risk associated with creating flammable mixtures capable of fire/explosion hazard. Solid materials tailored to target the molecule of interest (i.e., refrigerant.) by engineering the microporous structure as well as chemically functionalizing the surface to attract and hold on to the chemical compound being removed from the gas stream was realized. Quantitative analysis reveals the adsorbent's effectiveness in reducing leak potential in the range of 40 %–100 % for various refrigerants. Strategic placement and active leak management with negative pressure offer promising avenues for capturing leaked refrigerants, enhancing overall safety.

42 ENGINEERING↗
DOE OSTI2022

A Method for Measuring Coupled Individual and Social Vulnerability to Environmental Hazards

Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they reside. The backbone of our model is the Public-Use Microdata Sample (PUMS), a product of the U.S. Census Bureau that preserves a representative sample of completed responses to the American Community Survey (ACS). The PUMS enables us to understand the full range of individual protective capacities against a hazard in an exposed area, which we term individual vulnerability profiles (IVPs). In this case, we examine IVPs in the Coney Island-Brighton Beach section of New York City, which suffered severe impacts during Hurricane Sandy in 2012. To manage the large number of unique IVPs in Coney Island-Brighton Beach, we perform a segmentation analysis to generalize them into thematic cohort vulnerability profiles (CVPs) representing a typology of vulnerable people in Coney Island-Brighton Beach during Sandy. From synthetic populations of CVPs, we then estimate how individuals in varying housing types were coexposed to Sandy at the census tract level by classifying these areas into community social vulnerability profiles (SVPs). Our results provide a topology of social vulnerability that simultaneously links individual, community, and population-wide concerns, enabling a more holistic understanding of resources and interventions beneficial to human security during events like Sandy than is attainable with area-level metrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Mechanical behavior of carbonated MgO-based Engineered Cementitious Composite (ECC) after high temperatures exposure

Carbonated MgO-based Engineered Cementitious Composite (ECC) has ultrahigh tensile ductility and tight crack width control behavior. However, the expectation of improved fire-resistant has not been confirmed. This study explored the alterations to mechanical and microstructure characteristics of this material after exposure to temperatures up to 500 °C. Material mass loss, compressive strength, tensile strength, strain capacity, and matrix fracture toughness were measured. Scanning electron microscopy, mercury intrusion porosimetry, thermogravimetric analysis, and X-ray diffraction were used to probe the degradation of the cement matrix and fibers. The effect of elevated temperature on carbonated MgO-based ECC was further assessed via examination of the micromechanical behavior of the fiber-matrix. The objective of this research was to assess the performance of carbonated MgO-based ECC exposed to fire hazards. The tensile ductility of carbonated MgO-based ECC was found to be enhanced when exposed to ~100 °C as compared with those at room temperature ~20 °C. Further increase in exposure temperature, however, posed a negative impact on the composite compressive strength, ultimate tensile strength, and ability to control crack width. Here the results provide a useful database for further investigations into carbonated MgO-based ECC for fire safety enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimization of laser-induced breakdown spectroscopy for liquid sodium analysis

Next-generation nuclear power reactors based on liquid sodium coolant are in development to improve efficiency and safety. Fast breeder reactors could potentially achieve considerably higher fuel burn-up while producing less nuclear waste compared with current commercial technology. Monitoring of impurities in these types of reactors is important in order to prevent blockage of the cooling system or hazardous reactions due to the high reactivity of sodium with water. In this work, laser-induced breakdown spectroscopy is performed on a liquid sodium sample using a custom-built immersion probe system. The probe provides direct line of sight to the sample vessel in argon atmosphere for laser delivery and signal collection. Signatures of sodium, and impurities such as potassium and oxygen have been obtained. The probe height and immersion have a strong influence on the signal level and stability. Argon flow rates of 2 to 5 liters per minute produce no substantial change in signal, suggesting a steady laminar flowing regime. A high signal-to-noise ratio for impurity elements confirms the suitability of this technique for reliable impurity detection and monitoring in the reactor environment.

Gardette, V. [University of Michigan, Ann Arbor, M↗
DOE OSTI2022

Efficient transfer hydrodehalogenation of halophenols catalyzed by Pd supported on ceria

We report the transfer hydrodehalogenation (THD) of halophenols is efficiently catalyzed by palladium supported on high surface area ceria (Pd/CeO 2 ) under mild conditions (65 °C) using isopropanol (iPrOH) as hydrogen source. The reactivity of 4-halophenols (4-X-PhOH) varies in the order 4-F-PhOH > 4-Cl-PhOH > 4-Br-PhOH > > 4-I-PhOH and appears to be controlled by the desorption of halides from the catalyst surface. Kinetic analysis of the reactions and temperature programmed surface reaction (TPSR) experiments indicate that oxidative addition of C-X bonds and H-abstraction from isopropoxide compete for the same active sites on Pd. The catalyst was able to conduct the THD of various hazardous pollutants and emerging contaminants (dichlorodiphenyltrichloroethane (DDT), pentachlorophenol, pentafluorophenol and triclosan).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Simulation of Physics-Based 0-10Hz Strong Motion Using High Performance Computing Supporting Refinements to Regional Ground Motion Models for the Central Eastern US

In collaboration with the U.S. Nuclear Regulatory Commission (NRC) the LLNL has developed a computationally efficient simulation platform designed to perform physics-based ground motion simulations for crustal earthquakes in the Stable Continental Regions of Central and Eastern US (CEUS), using high-performance computing. The main objective of the earthquake simulations was to use synthetic ground motion to provide constrains to refinements of existing ergodic Ground Motion Models (GMMs), for large magnitude earthquakes and near-fault distances, for which these models are less reliable. Physics-based broadband (0-10Hz) ground motion simulations were used to estimate the near-fault ground motion amplitudes and within event and between-event variabilities associated with fault rupture characteristics. In our simulations we used a 3D regional velocity model that was based on Saikia’s 1D velocity model (1994). In simulations performed during the first stage of this project the Saikia’s velocity model demonstrated better performance in modelling high frequency regional wave propagation for the CEUS region recorded during the Mw5.0 November 7, 2016, Cushing Oklahoma (Taylor et al., 2017), and Mw5.8 September 3, 2016, Pawnee Oklahoma earthquakes. The proposed regional 3D model includes random perturbations to the 1D background model using the stochastic scheme of Pitarka and Mellors (2021). In addition, validation analysis of the rupture generator and regional wave propagation models, using comparisons with different GMMs for Mw6.5 and Mw7.0 scenario earthquakes in the CEUS region resulted in a very good match between the simulated and empirical ground motion models. For the purposes of seismic hazard assessment at the existing and planned nuclear power plants, NRC is interested in studies aimed at improving the current ground motion models (GMM) for both Stable Continental Regions (SCR) in the Central and Eastern US and Active Crustal Regions (ACR) in the Western US. Due to lack of recorded data, these improvements require synthetic data for short fault distances and large magnitude earthquakes for which the existing recorded data is not enough to uniquely constrain the GMMs. The need for simulations and strong motion data is especially critical for the CEUS region where we do not have recorded data from potentially large damaging earthquakes with moment magnitudes 6.0 and higher. In this the project, we focused on 10Hz simulations of Mw7.0 scenario earthquakes with strike slip and thrust faulting mechanisms. We used more than 50 Mw7.0 earthquake rupture scenarios to investigate the ground motion uncertainty due to unknown earthquake rupture parameters, in particular, the slip distribution, rupture velocity, and faulting mechanism, and their implication on ground motion amplification due to forward rupture directivity effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Mechanically induced thermal runaway severity analysis for Li-ion batteries

Thermal runaway is one of the most important safety concerns in the deployment of Li-ion batteries. For this study, we developed a standardized single-side indentation test protocol to induce an internal short-circuit. Cell voltage, temperature, and applied compressive force are monitored as a function of time. Each cell is given an observed hazard severity (OHS in five categories) modified from the EUCAR table. Meanwhile a calculated hazard severity (CHS) is obtained solely based on temperature and voltage curves. The calculation formula considers the cell temperature, rate of temperature increase, cell capacity, state of charge (SOC), voltage drop, and voltage drop rate. Each term is assigned with an appropriate weight to scale the calculated score from 0 to100. This method was applied to >100 Li-ion batteries with various SOCs and chemistries, and their OHS and CHS were displayed against SOC. The purpose is to provide battery designers, manufacturers, and end-users a clear comparison of thermal runaway severity of different batteries.

25 ENERGY STORAGE↗
DOE OSTI2026

Contrasting effects of glutamate and branched-chain amino acid metabolism on acid tolerance in a Castellaniella isolate from acidic groundwater

Groundwater acidification co-occurring with nitrate pollution is a common, global environmental health hazard. Denitrifying bacteria have been leveraged for the in situ removal of nitrate in groundwater. However, co-existing stressors—such as low pH—reduce the efficacy of biological removal processes. Castellaniella sp. str. MT123 is a complete denitrifier that was isolated from acidic, nitrate-contaminated groundwater. The strain grows robustly by nitrate respiration at pH < 6.0, completely reducing nitrate to dinitrogen gas. Genomic analyses of MT123 revealed few previously characterized acid tolerance genes. Thus, we utilized a combination of proteomics, metabolomics, and competitive mutant fitness to characterize the genetic mechanisms of MT123 acclimation to growth under mildly acidic conditions. We found that glutamate accumulation is critical in the acid acclimation of MT123, possibly through consumption of intracellular protons via glutamate decarboxylation to GABA. This is despite the fact that MT123 lacks the canonical glutamate decarboxylase-glutamate/GABA antiporter system implicated in acid tolerance in other bacteria. In contrast, branched-chain amino acid (BCAA) accumulation was detrimental to cell growth at lower pHs, possibly through indirect mechanisms impacting the cellular glutamate pool. Genetic analysis previously linked MT123 to a population of Castellaniella that bloomed—concurrent to nitrate removal—during a biostimulation effort to reduce groundwater nitrate concentrations at MT123’s location of origin. Thus, our analyses provide novel insight into mechanisms of acclimation to acidic conditions in a strain with significant potential for nitrate bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗