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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Distributed optimization and control for autonomous distributed energy resource power dispatch and frequency regulation considering communication failures

Distributed energy resources (DERs) can significantly enhance grid flexibility by supplying power and secondary frequency regulation (SFR) services. Yet, their large number and dispersed nature limit the effectiveness of traditional centralized power dispatch and frequency control schemes, and expose the system to single-point communication failures. This paper presents a unified distributed optimization and control framework for DER power dispatch and SFR provision. A transmission-loss-aware distributed direct current optimal power flow is first formulated to optimize DER power dispatch and reserve scheduling. On top of this, a fully distributed control scheme for DER autonomous SFR provision is developed to allocate automatic generation control signals cost-effectively while ensuring robustness to communication link disruptions. The framework is validated on IEEE 14-bus and 39-bus transmission systems with large-scale distribution feeders using transmission-distribution dynamic co-simulation, demonstrating reliable and autonomous DER power dispatch and SFR provision under diverse operating conditions and communication contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Could on-site fuel storage economically reduce power plant-gas grid dependence in pipeline constrained areas like New England?

In the Northeastern United States, natural gas supply constraints have led to periods when gas shortages have caused up to a quarter of all unscheduled power plant outages. Dual fuel oil/gas generators or local gas storage might mitigate gas supply shortages. We use historical power plant operational and availability data to develop a supply curve of the costs required for generators to mitigate fuel shortage failures in New England. Based on 2012–2018 data, we find that the historical fuel shortages at approximately 2 GW worth of gas-fired capacity could be mitigated using on-site fuel storage. For comparison, New England’s average reserve margin was 1.7–2.8 GW over our sample period. Oil dual fuel plants would recoup their investment if compensated with a reliability adder of $\$ 3-7$/MWh during their normal operations, while $\$ 7-16$/MWh would incentivize using onsite, compressed natural gas storage. We estimate that the capital expenses associated with the fuel storage options would be less expensive than installing battery backup for resource adequacy at current battery prices.

03 NATURAL GAS↗
DOE OSTI2026

Computational capacity in hydrodynamic real-time hybrid simulation applied to simulate the dynamic response of floating offshore wind turbines

Real-time hybrid simulation (RTHS) mitigates similitude distortions in model-scale tests of floating offshore wind turbines (FOWTs) by coupling physical experiments with numerical models in real time. The coupling requires faster-than-real-time numerical computations to satisfy temporal similitude with the physical experiment, presenting a bottleneck for using more complex numerical models in RTHS. This paper presents a hydrodynamic-RTHS (hydro-RTHS) framework for FOWTs that simulates the hydrodynamics physically and the aerodynamics numerically with sensor feedback from the physical testing. The framework adapts the three-loop hardware architecture to leverage greater computational resources and mitigate strict temporal requirements, enabling more computationally demanding numerical analyses in hydro-RTHS. The three-loop hardware architecture integrates multiple machines, each dedicated to either numerical analysis or RTHS controls, with a rate-transition algorithm to synchronize the tasks executed across the different machine processors. Virtual and physical tests verified and validated the hydro-RTHS framework, respectively. The ”virtual” tests, which approximates the physical domain numerically, verified the RTHS framework with respect to a numerical full-scale complete FOWT model simulated in the open-source software, OpenFAST. The virtual tests were able to maintain comparable control signals while enabling greater computational resources for the numerical calculations. Real-world physical tests demonstrated that the hydro-RTHS framework computes aerodynamic forces similar to the complete OpenFAST model, validating the hydro-RTHS framework using the three-loop hardware architecture. Findings show that the hydro-RTHS framework with the three-loop hardware architecture is computationally efficient, with reserve capacity to simulate more complex problems due to the customized software, hardware, and rate-transition algorithm.

17 WIND ENERGY↗
DOE OSTI2023

Bimetallic-Derived Catalytic Structures for CO 2 -Assisted Ethane Activation

In recent years, the simultaneous upgrading of CO 2 and ethane has emerged as a promising approach for generating valuable gaseous (CO, H 2 , and ethylene) and liquid (aromatics and C 3 oxygenates) chemicals from the greenhouse gas CO 2 and large-reserved shale gas. The key challenges for controlling product selectivity lie in the selective C-H and C-C bond cleavage of ethane with the assistance of CO 2 . Bimetallic-derived catalysts likely undergo alloying or oxygen-induced segregation under reaction conditions, thus providing diverse types of interfacial sites, e.g., metal/support (M/M'O x ) interface and metal oxide/metal (M'O x /M) inverse interface, that are beneficial for selective CO 2 -assisted ethane upgrading. The alloying extent can be initially predicted by cohesive energy and atomic radius (or Wigner-Seitz radius), while the preference for segregation to form the on-top suboxide can be approximated using the work function, electronegativity, and binding strength of adsorbed oxygen. Furthermore, bimetallic-derived catalysts are typically supported on high surface area oxides. Modifying the reducibility and acidity/basicity of the oxide supports and introducing surface defects facilitate CO 2 activation and oxygen supplies for ethane activation. Using in situ synchrotron characterization and density functional theory (DFT) calculations, we found that the electronic properties of oxygen species influence the selective cleavage of C-H/C-C bonds in ethane, with electron-deficient oxygen over the metal (or alloy) surface promoting nonselective bond scission to produce syngas and electron-enriched oxygen over the metal oxide/metal interface enhancing selective C-H scission to yield ethylene. Here, we further demonstrate that the preferred structures of the catalyst surfaces, either alloy surfaces or metal oxide/metal inverse interfaces, can be controlled through the appropriate choice of metal combinations and their atomic ratios. Through a comprehensive comparison of experimental results and DFT calculations, the selectivity of C-C/C-H bond scission is correlated with the thermodynamically favorable bimetallic-derived structures (i.e., alloy surfaces or metal oxide/metal inverse interfaces) under reaction conditions over a wide range of bimetallic catalysts. These findings not only offer structural and mechanistic insights into bimetallic-derived catalysts but also provide design principles for selective catalysts for CO 2 -assisted activation of ethane and other light alkanes. This Account concludes by discussing challenges and opportunities in designing advanced bimetallic-derived catalysts, incorporating new reaction chemistries for other products, employing precise synthesis strategies for well-defined structures with optimized site densities, and leveraging time/spatial/energy-resolved in situ spectroscopy/scattering/microscopy techniques for comprehensive structural analysis. The research methodologies established here are helpful for the investigation of dynamic alloy and interfacial structures and should inspire more efforts toward the simultaneous upgrading of CO 2 and shale gas.

03 NATURAL GAS↗
DOE OSTI2020

Effect of Cr(III) Adsorption on the Dissolution of Boehmite Nanoparticles in Caustic Solution

Incorporation of relatively minor impurity metals onto metal (oxy)hydroxides can strongly impact solubility. In complex highly alkaline multicomponent tank waste such as that at the Hanford Nuclear Reservation, tests indicate that the surface area-normalized dissolution rate of boehmite ($γ$-AlOOH) nanomaterials is at least an order of magnitude lower than that predicted for the pure phase. In this work we examine the dissolution kinetics of boehmite coated by adsorbed Cr(III), which adheres at saturation coverages as sparse chemisorbed monolayer clusters. Using 40 nm boehmite nanoplates as a model system, temperature-dependent dissolution rates of pure versus Cr(III)-adsorbed boehmite showed that the initial rate for the latter is consistently several times lower, with an apparent activation energy 16 kJ·mol -1 higher. Although the surface coverage is only around 50%, solution analytics coupled to multimethod solids characterization reveals a phyicochemical armoring effect by adsorbed Cr(III) that substantially reduces the number of dissolution-active sites on particle surfaces. Such findings could help improve kinetics models of boehmite and/or metal ion adsorbed boehmite nanomaterials, ultimately providing a stronger foundation for the development of more robust complex radioactive liquid waste processing strategies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Modeling Nanoconfinement Effects Using Active Learning

Predicting the spatial configuration of gas in nanopores of is relevant in applications such as fluid flow forecasting and hydrocarbon reserves estimation. For example, shale reservoirs have suffered from computationally intractable multiscale problems, since fluid properties such as viscosity, density, and adsorption must be calculated by using expensive molecular dynamics (MD) simulations within each nanopore, whereas flow through these connected nanopores must be simulated at the micrometer scale. We utilize machine learning techniques to quickly and accurately model nanoscale confinement effects as an important step toward bridging the nano and micro scales. Our workflow is based on building and training physics-based deep-neural-networks models by learning from a database of MD calculations. The model accounts for the adsorption phenomenon by predicting the statistical distribution of gas inside nanopores. Because large databases of MD calculations are expensive to create, we investigate active learning (AL) as a data set construction strategy. In this workflow, new data are selected based on the model uncertainty via the query-by-committee approach. We show that our workflow obtains accurate models that generalize to real scanning electron microscopy geometries with 1/10th of the number of MD calculations required vs random data set generation. Our method enables the possibility of modeling nanoconfinement effects at the mesoscale, where complex connected sets of nanopores affect flow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Mechanistic Understanding of Methane Combustion over Ni/CeO 2 : A Combined Experimental and Theoretical Approach

Catalytic oxidation of methane (CH 4 ) over nonprecious Ni/CeO 2 catalysts has received a lot of attention due to the large natural gas reserves found in North America and the prohibitive cost of palladium-based catalysts, commonly used for CH 4 oxidation. However, the catalytic mechanism of CH 4 oxidation over Ni/CeO 2 still remains unclear. Moreover, the parameters affecting the reaction rates, the interaction between nickel and CeO 2 , and the reaction intermediates are still not well understood. In this study, kinetic model fitting, CH 4 temperature-programmed reduction-mass spectroscopy (CH 4 TPR-MS), in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and density functional theory (DFT) calculations were combined to elucidate the mechanism of complete oxidation of CH 4 over Ni/CeO 2 . CH 4 TPR-MS showed that the complete oxidation of CH 4 over Ni/CeO 2 requires 55–120 °C lower compared to bare CeO 2 or Ni/quartz sand; complete oxidation of CH 4 took place when the surface oxygen species were abundant, while partial oxidation products (CO, H 2 ) were formed when the oxygen species were depleted. In situ DRIFTS showed that CH 3 , CH 2 , CO, and CO 2 were formed after CH 4 activation over Ni/CeO 2 , while CH 3 O species were not observed. Combining those findings with kinetic model fitting, a redox Mars–van Krevelen (MvK) mechanism showed the best description of the experimental observations. The MvK mechanism involves the reaction of dissociated oxygen species with gas-phase CH 4 while water inhibits the reaction rate by adsorbing on the oxidized sites. Moreover, CH 4 activation leads to the reduction of the active sites and oxygen vacancy formation followed by reoxidation of the active sites by gas-phase O 2 . A CH 4 oxidation reaction pathway over Ni/CeO 2 is proposed by DFT calculations. In summary, the findings shown here suggest that CH 4 oxidation over Ni/CeO 2 follows a redox MvK mechanism and provides guidance for the rational design of non-precious-metal catalysts for CH 4 oxidation reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Catalytic Tandem CO 2 –Ethane Reactions and Hydroformylation for C3 Oxygenate Production

The strategy of tandem hydroformylation reaction for C3 oxygenate production from CO 2 and ethane represents an opportunity of simultaneously upgrading greenhouse gas CO 2 and the large-reserved shale gas into value-added liquid products. One of the challenges is how to tune and achieve the appropriate ethylene/CO/H 2 ratios for the downstream hydroformylation. Herein, the desired ethylene/CO/H 2 ratios were analyzed and identified by considering different combinations of main and side-reactions of CO 2 and ethane, based on which the PtSn 3 /γ-Al 2 O 3 catalyst was identified as promising to enable the catalytic tandem hydroformylation reaction. Further, the combined studies of reactor evaluation, in situ and ex situ characterization and theoretical calculations revealed that the Pt cluster/SnO x interfacial structures dominated the simultaneous dehydrogenation and dry reforming of ethane, thereby allowing the co-formation of ethylene, CO and H 2 that were subsequently converted to C3 oxygenates in the tandem hydroformylation reactor. The current work not only demonstrates the design principles of suitable catalysts for the tandem-reactor strategy, but also highlights the utilization of CO 2 and shale gas to produce value-added oxygenate products.

03 NATURAL GAS↗
DOE OSTI2026

A Robust Methodology to Elucidate Kinetics of Room Temperature Electrochemical Propane Adsorption on Platinum

Electrocatalytic activation of alkanes can further decarbonize chemical manufacturing by leveraging affordable renewable electricity and readily available shale gas reserves in the United States. Earlier works have identified the unique role of Pt in adsorbing and activating alkanes, like propane, at room temperature in acidic, aqueous electrolytes, revealing spontaneous formation of deeply dehydrogenated propane-derived surface species with an intact C 3 - backbone. Although an adsorption mechanism was hypothesized, it has not been explicitly investigated to date, preventing the quantification of kinetic rate parameters. A robust methodology to investigate and benchmark propane adsorption kinetics on Pt is critical for the rational design of electrocatalysts that exhibit higher selectivity toward desired partially oxidized products. Herein, we analyze an oxidative current transience that appears during the adsorption of propane on Pt in aqueous electrochemical conditions and develop a methodology that elucidates the adsorption mechanism and enables quantification of rate parameters such as order dependences and apparent activation barriers. This method yields an expected first-order dependence with respect to propane concentration at low coverage and reveals a second-order dependence with respect to the concentration of surface active sites. Additionally, the apparent activation barrier for propane adsorption was calculated using an Arrhenius analysis of the current transience under temperature control. The experimentally measured activation barrier of 35 kJ mol –1 is in excellent agreement with the theoretical barrier calculated by density functional theory (DFT). The kinetic analysis was extended, via the use of transition state theory, to extract entropy and enthalpy of activation, yielding consistent results with the proposed two-step adsorption mechanism and DFT calculations. These results demonstrate reliable quantification of kinetic parameters for electrocatalytic activation of C–H bonds in alkanes that can be employed for rational catalyst development for a versatile range of electrocatalytic conditions.

alkane activation↗
DOE OSTI2021

Urban Forests as Main Regulator of the Evaporative Cooling Effect in Cities

Abstract Higher temperatures in urban areas expose a large fraction of the human population to potentially dangerous heat stress. Green spaces are promoted worldwide as local and city‐scale cooling strategies but the amount, type, and functioning of vegetation in cities lack quantification and their interaction with urban climate in different settings remains a matter of debate. Here we use state‐of‐the‐art remote sensing data from 145 city clusters to disentangle the drivers of surface urban heat islands (SUHI) intensity and quantify urban‐rural differences in vegetation cover, species composition, and evaporative cooling. We show that nighttime SUHIs are affected mostly by abiotic factors, while daytime SUHIs are highly correlated with vegetation characteristics and the wetness of the background climate. Magnitude and seasonality of daytime SUHIs are controlled by urban‐rural differences in plant transpiration and leaf area, which explain the dependence of SUHIs on wetness conditions. Leaf area differences are caused primarily by changes in vegetation type and a loss of in‐city forested areas, highlighting the importance of maintaining “natural reserves” as a sustainable heat mitigation policy.

Paschalis, Athanasios↗
DOE OSTI2020

The Shifting Scales of Western U.S. Landfalling Atmospheric Rivers Under Climate Change

Atmospheric rivers (ARs) can be a boon and bane to water resource managers as they have the ability to replenish water reserves, but they can also generate million-to-billion-dollar flood damages. To investigate how anthropogenic climate change may influence AR characteristics in the coastal western United States by end century, we employ a suite of novel tools such as variable resolution in the Community Earth System Model (VR-CESM), the TempestExtremes AR detection algorithm, and the Ralph, Rutz, et al. (2019, https://doi.org/10.1175/BAMS-D-18-0023.1) AR category scale.We show that end-century ARs primarily shift from being “mostly or primarily beneficial” to “mostly or primarily hazardous” with a concomitant sharpening and intensification of winter season precipitation totals. Changes in precipitation totals are due to a significant increase in AR (+260%) rather than non-AR (+7%) precipitation, largely through increases in the most intense category of AR events and a decrease in the interval between landfalling ARs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Slope-Aspect Induced Climate Differences Influence How Water Is Exchanged Between the Land and Atmosphere

Cross-slope climate differences in the midlatitudes are ecologically important, and impact vegetation-mediated water balance between the earth surface and the atmosphere. We made high-resolution in situ observations of air temperature, relative humidity, soil moisture, insolation, and sap velocity observations on 14 Pacific madrone trees (Arbutus menziesii) spanning adjacent north and south slopes at the University of California's Angelo Coast Range Reserve. To understand the cross-slope response of sap velocity, a proxy for transpiration, to microclimate, we modeled the sap velocity on each slope using a transpiration model driven by ambient environment and parameterized with a Markov Chain Monte Carlo parameter estimation process. The results show that trees on opposing slopes do not follow a shared pattern of physiological response to transpiration drivers. This means that the observed sap velocity differences are not due entirely to observed microclimate differences, but also due to population-level physiological differences, which indicates acclimation to inhabited microclimate. While our present data set and analytical tools do not identify mechanisms of acclimation, we speculate that differing proportions of sun-adapted and shade-adapted leaves, differences in stomatal regulation, and cross-slope root zone moisture differences could explain some of the observed and modeled differences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulated Precipitation Diurnal Variation With a Deep Convective Closure Subject to Shallow Convection in Community Atmosphere Model Version 5 Coupled With CLUBB

In order to improve the physical consistency between shallow and deep convection, we modify the deep convective closure in the Community Atmosphere Model version 5 (CAM5) coupled with a third-order turbulence closure parameterization (i.e., Cloud Layers Unified by Binormals; CLUBB). The revised closure reserves a portion of the total convective available potential energy for shallow convection via utilizing the heating and moistening profiles from CLUBB to distribute moisture and energy between shallow and deep convection. Simulations at two resolutions (i.e. 2° and 0.5°, respectively) are conducted to investigate the impacts of convective closure on the simulated precipitation diurnal variations. Results from low-resolution simulations show that the revised closure suppresses deep convection until the lower troposphere is sufficiently moistened by shallow convection, which improves the precipitation diurnal variation simulations compared to the default closure, with the precipitation diurnal peak over tropical lands delayed from 12LST to 19LST. The revised closure better simulates the diurnal variations for precipitation over the Asian monsoon region, such as the delayed precipitation onset, but still fails to well capture the nighttime peak for precipitation there. This deficiency is alleviated to some extent when applying the revised closure in highresolution simulations, but nighttime precipitation is still underestimated probably because key processes responsible for nighttime convection are missing. Altogether, our results indicate that establishing the consistency between shallow and deep convection is critical for the precipitation diurnal cycle simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improving CLM5.0 Biomass and Carbon Exchange Across the Western United States Using a Data Assimilation System

The Western United States is dominated by natural lands that play a critical role for carbon balance, water quality, and timber reserves. This region is also particularly vulnerable to forest mortality from drought, insect attack, and wildfires, thus requiring constant monitoring to assess ecosystem health. Carbon monitoring techniques are challenged by the complex mountainous terrain, thus there is an opportunity for data assimilation systems that combine land surface models and satellite-derived observations to provide improved carbon monitoring. Here, we use the Data Assimilation Research Testbed to adjust the Community Land Model (CLM5.0) with remotely sensed observations of leaf area and above-ground biomass. The adjusted simulation significantly reduced the above-ground biomass and leaf area, leading to a reduction in both photosynthesis and respiration fluxes. The reduction in the carbon fluxes mostly offset, thus both the adjusted and free simulation projected a weak carbon sink to the land. This result differed from a separate observation-constrained model (FLUXCOM) that projected strong carbon uptake to the land. Simulation diagnostics suggested water limitation had an important influence upon the magnitude and spatial pattern of carbon uptake through photosynthesis. We recommend that additional observations important for water cycling (e.g., snow water equivalent, land surface temperature) be included to improve the veracity of the spatial pattern in carbon uptake. Furthermore, the assimilation system should be enhanced to maximize the number of the simulated state variables that are adjusted, especially those related to the recommended observed quantities including water cycling and soil carbon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Atmospheric Structure Prediction for Infrasound Propagation Modeling Using Deep Learning

Abstract Infrasound is generated by a variety of natural and anthropogenic sources. Infrasonic waves travel through the dynamic atmosphere, which can change on the order of minutes to hours. Infrasound propagation largely depends on the wind and temperature structure of the atmosphere. Numerical weather prediction models are available to provide atmospheric specifications, but uncertainties in these models exist and they are computationally expensive to run. Machine learning has proven useful in predicting tropospheric weather using Long Short‐Term Memory (LSTM) networks. An LSTM network is utilized to make atmospheric specification predictions up to ∼30 km for three different training and testing scenarios: (a) the model is trained and tested using only radiosonde data from the Albuquerque, NM, USA station, (b) the model is trained on radiosonde stations across the contiguous US, excluding the Albuquerque, NM, USA station, which was reserved for testing, and (c) the model is trained and tested on radiosonde stations across the contiguous US. Long Short‐Term Memory predictions are compared to a state‐of‐the‐art reanalysis model and show cases where the LSTM outperforms, performs equally as well, or underperforms in comparison to the state‐of‐the‐art. Regional and temporal trends in model performance across the US are also discussed. Results suggest that the LSTM model is a viable tool for predicting atmospheric specifications for infrasound propagation modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Ambient Noise Attenuation Tomography Reveals an Asymmetric Damage Zone Across San Jacinto Fault Near Anza, California

Here, we perform seismic attenuation tomography of the shallow structure for the San Jacinto Fault in the Ramona Reservation of southern California. The study uses ambient seismic noise recorded by a linear array of 65 3-C sensors across the fault. We extract amplitude decay information, with uncertainty, from noise interferometry functions. To account for strong heterogeneities in the complex shallow fault zone structure, we apply a frequency-dependent amplitude correction for focusing/defocusing effects using inverted phase velocity maps obtained by solving the transport equation. We then estimate the attenuation structure based on the linear station-triplet method for both Love and Rayleigh waves. The attenuation tomography indicates strong attenuation correlated with known San Jacinto Fault surface traces. The Love wave attenuation tomography reveals an asymmetric damage zone that exists primarily on the fault side with faster seismic velocity, consistent with earthquake ruptures on a fault bimaterial interface with preferred propagation direction to the northwest.

58 GEOSCIENCES↗
DOE OSTI2023

Ensemble Estimation of Historical Evapotranspiration for the Conterminous U.S.

Abstract Evapotranspiration (ET) is the largest component of the water budget, accounting for the majority of the water available from precipitation. ET is challenging to quantify because of the uncertainties associated with the many ET equations currently in use, and because observations of ET are uncertain and sparse. In this study, we combine information provided by available ET data and equations to produce a new monthly data set for ET for the conterminous U.S. (CONUS). These maps are produced from 1895 to 2018 at an 800 m spatial scale, marking a finer resolution than currently available products over this time period. In our approach, the relative performance of a suite of ET equations is assessed using water balance, flux tower, and remotely sensed ET estimates. At the observation locations, we use error distributions to quantify relative weights for the equations and use these in a modified Bayesian model averaging weighted ensemble approach. The relative weights are spatially generalized using a random forest regression, which is applied to wall‐to‐wall explanatory variable maps to generate CONUS‐wide relative weight maps and ensemble estimates. We assess the performance of the ensemble using a reserved subset of the observations and compare this performance against other national‐scale map products for historical to modern ET. The ensemble ET maps are shown to provide an improved accuracy over the alternative comparison products. These ET maps could be useful for a variety of hydrologic modeling and assessment applications that benefit from a long record, such as the study of periods of water scarcity through time.

Environmental Sciences & Ecology↗
DOE OSTI2022

Mixed heavy metal stress induces global iron starvation response

Abstract Multiple heavy metal contamination is an increasingly common global problem. Heavy metals have the potential to disrupt microbially mediated biogeochemical cycling. However, systems-level studies on the effects of combinations of heavy metals on bacteria are lacking. For this study, we focused on the Oak Ridge Reservation (ORR; Oak Ridge, TN, USA) subsurface which is contaminated with several heavy metals and high concentrations of nitrate. Using a native Bacillus cereus isolate that represents a dominant species at this site, we assessed the combined impact of eight metal contaminants, all at site-relevant concentrations, on cell processes through an integrated multi-omics approach that included discovery proteomics, targeted metabolomics, and targeted gene-expression profiling. The combination of eight metals impacted cell physiology in a manner that could not have been predicted from summing phenotypic responses to the individual metals. Exposure to the metal mixture elicited a global iron starvation response not observed during individual metal exposures. This disruption of iron homeostasis resulted in decreased activity of the iron-cofactor-containing nitrate and nitrite reductases, both of which are important in biological nitrate removal at the site. We propose that the combinatorial effects of simultaneous exposure to multiple heavy metals is an underappreciated yet significant form of cell stress in the environment with the potential to disrupt global nutrient cycles and to impede bioremediation efforts at mixed waste sites. Our work underscores the need to shift from single- to multi-metal studies for assessing and predicting the impacts of complex contaminants on microbial systems.

59 BASIC BIOLOGICAL SCIENCES↗