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The geochemical cycling of iron and carbon can couple in unique ways in the euphotic zone of aquatic systems.
In the method of X-ray footprinting mass spectrometry (XFMS), proteins at micromolar concentration in solution are irradiated with a broadband X-ray source, and the resulting hydroxyl radical modifications are characterized using liquid chromatography mass spectrometry to determine sites of solvent accessibility. These data are used to infer structural changes in proteins upon interaction with other proteins, folding, or ligand binding. XFMS is typically performed under aerobic conditions; dissolved molecular oxygen in solution is necessary in many, if not all, the hydroxyl radical modifications that are generally reported. In this study we investigated the result of X-ray induced modifications to three different proteins under aerobic versus low oxygen conditions, and correlated the extent of damage with dose calculations. We observed a concentration-dependent protecting effect at higher protein concentration for a given X-ray dose. For the typical doses used in XFMS experiments there was minimal X-ray induced aggregation and fragmentation, but for higher doses we observed formation of covalent higher molecular weight oligomers, as well as fragmentation, which was affected by the amount of dissolved oxygen in solution. The higher molecular weight products in the form of dimers, trimers, and tetramers were present in all sample preparations, and, upon X-ray irradiation, these oligomers became non-reducible as seen in SDS-PAGE. The results provide an important contribution to the large body of X-ray radiation damage literature in structural biology research, and will specifically help inform the future planning of XFMS, and well as X-ray crystallography and small-angle X-ray scattering experiments.
This data package is associated with the publication “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling” submitted to Geoscientific Model Development (Muller et al., 2024). In this manuscript, organic matter chemistry and thermodynamics are directly connected to reactive transport simulators through the newly developed Lambda-PFLOTRAN (Parallel Reactive Flow and Transport model) workflow tool that succinctly incorporates organic matter chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate aerobic respiration of the organic matter and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow, executed through a Jupyter Notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow, and transport code PFLOTRAN. This data package contains Jupyter Notebook based workflows for two test cases for running biogeochemical simulations of organic matter oxidation identified by FTICR-MS. It contains four primary folders (workflow, data, src, and analysis), a file-level metadata file (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_flmd.csv) that lists all the files contained in this data package with a short description of each, and a data dictionary (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_dd.csv) file that describes the tabular column headers. The ‘workflow’ folder contains the Jupyter Notebook based workflows for running the lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘data’ folder contains the FTICR-MS data, initial conditions, and incubation data for test cases 1 and 2 in folders titled ‘WHONDRS’ and ‘Colloids’, respectively. The data folder also has a ‘Database’ folder containing a reaction network for bulk organic matter (assumed to be CH2O) and a general database for PFLOTRAN (hanford_rxn_network). The CH2O reaction network defines bulk organic matter oxidation. Biogeochemical simulations are completed for both the lambda binned organic matter and bulk organic matter reaction networks. The ‘hanford_rxn_network’ database includes information required for PFLTORAN simulations including ion size, molar mass, and charge of the aqueous species, gases, and minerals phases. The ‘src’ folder contains python source codes for performing lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘analysis’ folder contains outputs from the test cases 1 and 2 including lambda analysis, PFLOTRAN runs and the calibration results.
Oxidative degradation in amine based post-combustion carbon capture (PCCC) leads to solvent losses and decreased solvent performance. Oxygen (O 2 ) in the flue gas is dissolved into the aqueous solvent and can reactively degrade the amine component. Advanced aqueous amine solvents are designed to contain additional surfactant and anti-foam additives as well as two types of corrosion inhibitors. These additives contribute to improve the solvent performance while reducing foaming and corrosion of expensive equipment. This work examines the impact of these additives on oxygen solubility (or dissolved oxygen - DO) in various aqueous amines used in PCCC including ethanolamine (MEA), 1-amino-2-propanol (A2P), 2-amino-1-propanol (2A1P), 2-(methylamino)-ethanol (NMEA), 2-(ethylamine)-ethanol (2EAE), diethanolamine (DEA), methyl-diethanolamine (MDEA), dimethylethanolamine (DMEA), piperazine (PZ), 1,2-ethyldiamine (EDA), and 1,6 hexadiamine (HDA). Further, the impact of carbon loading on oxygen solubility with and without these additives was also examined. The surfactant and anti-foam additives had minimal impact on DO for all the solvents investigated. The two anticorrosion additives had opposite effects in the measured DO, 2- mercaptobenzothiazole (MBT) decreased the DO concentration, and sodium metavanadate showed an increase. These results indicate that several of these common additives can be expected to minimally affect DO related oxidative degradation in these advance amine solvents.
In wastewater treatment plants, aeration plays a significant role as it encourages aerobic respiration of microbes, which are necessary to break down carbonaceous matter in the waste stream. This process can account for the majority of energy use in wastewater treatment plants. The aeration process is also necessary in odor control in lagoons and in the aquaculture industry. Generally, the aeration process is accomplished with compressors or blowers which can be of low efficiency due to ideal gas laws. This study introduces the idea of increasing aeration efficiency by looping water from a reservoir through a piping network which includes a venturi aspirator at its inlet. For this purpose, an experimental study has been conducted in a laboratory setup with a pump which pulls water from a tank, passes it through a Venturi aspirator and a helical piping network intended to increase bubble residence time, before depositing it back into the bulk fluid tank. This same process is modeled computationally, using a discrete bubble method (DBM), with good agreement with experiments. The overall purpose here is to determine the optimal configurations for standard aeration efficiency (SAE) and the standard oxygen transfer rate (SOTR). A parametric study has been implemented using the DBM based on different hydraulic and flow parameters. The model is also used to predict the SAE of a hypothetical aeration system. Results indicate that it is possible to achieve SAE values in the range of surface aerators or submersed jet aerators using the proposed aeration system with less complex components, thereby decreasing overall costs.
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Conceptual models of sedimentary basin groundwater flow systems typically assume that the crystalline basement acts as an impermeable boundary and can be neglected. In this study, we use hydrologic models constrained by isotopic and geochemical datasets to argue that the La Sal Mountains, Utah, USA, act as a hydrologic window into the Paradox Basin’s lower aquifer system and underlying crystalline basement. We conducted a sensitivity study in which we varied crystalline basement/laccolith permeability as well as fault zone connectivity along a cross-sectional transect from the La Sal Mountains to Lisbon Valley. When the crystalline basement/laccolith units are set at relatively permeable levels (10–14 m 2 ), simulated tracers that include total dissolved solids, oxygen isotopic composition of pore fluids (δ 18 O), and groundwater residence times are in closest agreement with field measurements. Model results indicate that pore fluids in the basal aquifer system underlying the Paradox Formation confining unit are a mixture of relatively young meteoric fluids and older Paradox Formation brines. The presence of faults did not significantly modify fluid exchange between the upper and lower aquifer systems. This was due, in part, to underpressuring within the Paradox Formation. Our study concludes that the Paradox Basin represents a regional recharge area for the Colorado Plateau, with groundwater discharge occurring along the Colorado River within the Grand Canyon some 375 km away to the southwest. This is only possible with a permeable crystalline basement. Our findings help explain the genesis of Mississippi Valley-type ore deposits of the US Midcontinent, where the presence of a permeable basement may be useful in addressing issues related to solute mass and energy balance.
Understanding the different sources of carbon subsurface microbes use is highly informative yet remains challenging. The goal of this work was to develop and test a cultivation-independent method that analyzes both the radiocarbon and ribosomal RNA (rRNA) signature of unamplified RNA from the same environmental sample, and that collectively characterizes community carbon utilization under in situ conditions. The method was applied to a filtered groundwater sample from a geochemically reduced zone of a shallow alluvial aquifer near Rife, Colorado (CO), where multiple potential carbon sources co-occur. The radiocarbon and RNA-Seq results, while addressing diverse sample properties, indicated a strikingly similar conclusion about the quantitative role of autotrophy in the subsurface microbial community.This data package provides (1) ribosomal RNA (rRNA) sequences for groundwater microbial populations, (2) the taxonomic identity and relative abundance of groundwater microbial populations based on these rRNA sequences, (3) radiocarbon signatures of the rRNA indicating the source of carbon used by the groundwater microbial populations (provided in both Word docx file and pdf file), (4) geochemical measurements for the monitoring well corresponding to these measurements.
This data package contains model input and output files for local and global sensitivity analysis (SA) of a reactive transport model simulating redox cycling within a floodplain aquifer. The reaction network is implemented in CrunchFlow and focuses on spatially and temporally heterogeneous Fe cycling, though it contains several other species and redox pathways (37 aqueous species and 7 minerals in total). The package contains data from 600 Monte Carlo simulations (for global SA) and 104 one-at-a-time simulations (for local SA). It includes all input files required to run the CrunchFlow model, as well as limited model output – .csv files containing time series of primary species concentrations at 21 grid cells within the domain. These time series files contain the following species: H+, CO32-, SO42-, Cl-, Ca2+, Mg2+, Na+, K+, Fe(II), Fe(III), HS-, CH3COO-, O2(aq), S(aq), and Br-.These data were used to demonstrate the application of a novel form of global SA, distance-based generalized sensitivity analysis (DGSA) to a reactive transport model. The 2D model simulates the export of reduced species from pockets of fine-grained, organic-rich sediments embedded in a coarse sand aquifer. Stochastic simulations jointly varied 17 key model input parameters across several orders of magnitude, including the spatial variability of each parameter. DGSA on the model results reveal that the amplitude and variability of exported Fe(II) are most sensitive to the interaction between sand permeability and individual reaction rates. By contrast, the propagation of reducing conditions downgradient from the fine-grained lenses depends most heavily on the rate of dissolved organic carbon and sulfate release from the fines.
This data package contains surface water chemistry measurements collected in 2025 to evaluate how beaver damming and low-tech process-based stream restoration influence water quality and metal mobility in mountainous headwater systems of the Upper Colorado River Basin. Sampling was conducted at Trail Creek (Taylor Park watershed, Colorado), a tributary undergoing restoration through installation of low-tech process-based structures (i.e., beaver dam analogs), and at off-channel beaver ponds within the East River floodplain (East River watershed, Colorado). Samples were collected along longitudinal transects spanning upstream control reaches, beaver-influenced ponded reaches, and downstream segments. Additional samples were collected from near-surface pore waters within a beaver dam seepage face. The dataset includes concentrations of major and trace elements measured by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES), major anions measured by ion chromatography (IC), and dissolved organic carbon (DOC; reported as non-purgeable organic carbon, NPOC). Samples were size-fractionated at 0.45 micrometers (µm), 0.22 µm, and 0.02 µm to distinguish particulate (>0.45 µm), colloidal (0.22–0.02 µm), and dissolved (<0.02 µm) fractions. The data package consists of comma-separated value (.csv) files containing tabulated chemical concentration data, sample metadata (site identifiers, geographic coordinates, sampling dates, fraction type), and quality control flags. All files are provided in open, non-proprietary formats that can be accessed using standard data analysis software such as Microsoft Excel, R, Python, MATLAB, or other programs capable of reading .csv files. Units, detection limits, and analytical methods are documented in accompanying metadata files. The dataset is designed to support analyses of (1) how beaver impoundment and restoration structures alter elemental partitioning and transport, (2) the role of iron and organic carbon in mediating trace metal mobility, and (3) reach-scale changes in water quality across restoration gradients. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.
Polygonal ground is a signature characteristic of the Arctic, and permafrost thaw can potentially generate substantial feedbacks to Arctic ecosystems and climate. This study describes the first comprehensive spatial examination of active layer biogeochemistry that extends across high- and low-centered polygons and their features, including depth. Water chemistry measurements were made on active layer water samples collected near Barrow, Alaska during summer, 2012. Several significant differences in chemistry were observed between high- and low-centered polygons suggesting polygon types may be useful for landscape-scale geochemical classification. However, differences were found for polygon features (centers and troughs) for analytes that were not significant for type, suggesting that finer scale features control biogeochemistry in a different way than polygon type. Depth variations were also significant, demonstrating important multi-dimensional aspects of polygonal ground biogeochemistry. These results have major implications for understanding how polygonal ground ecosystems function, and how they may respond to future change. This data package includes one *.csv data file and one *.pdf user guide. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
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This dataset supports a broader study examining the drivers of spatial variability in wildfire impacts across the Yakima River Basin. Data provided within this dataset were generated from sample collection across 17 total sites (8 sites affected by a recent wildfire, 9 sites unaffected by a recent wildfire) within multiple rivers throughout the Yakima River Basin in Washington, USA from May-July 2023. Fire affected sites are defined as those affected by the 2021 Schneider Springs Fire, based on the drainage area of the streams being within the 2021 Schneider Springs Fire burn perimeter or not (Figure 1, below). The contents include surface water geochemistry data (dissolved organic carbon; total dissolved nitrogen; total suspended solids); short-term sonde data (specific conductivity; turbidity; pH; chlorophyll A; temperature); stream depth data; stream velocity; manual chamber open channel respiration data; sensor time-series data (oxygen; water pressure; barometric pressure); field metadata (including qualitative information on in stream and river corridor characteristics); and environmental context photos taken in the field. The dataset also includes a summary file of the sensor data and plots of the sensor data. Sensors were only recovered at 15 out of the 17 sites, and not all sensors were recovered at all 15 sites (see Methods section for more details), therefore all data does not exist at all sites. Data from a 2022 study at the same sites, as well as additional sites, can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566. The data package was originally published in November 2023. It was updated in June 2025 (v2; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of one folder with field photos and one main data folder with two subfolders. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) field protocol; (5) readme; (6) international generic sample number (IGSN) mapping file; and (7) stream depth and averages. The sensor data subfolder consists of (1) sensor installation methods summary; (2) stream velocity; and (3) six subfolders. The BarotrollAtm (barometric pressure; temperature), DepthHOBO (water pressure; temperature), MantaRiver (specific conductivity; turbidity; pH; chlorophyll A; temperature), EXO (specific conductivity; pH; temperature), miniDOT (dissolved oxygen; temperature), and miniDOTManualChamber (dissolved oxygen; temperature) contain time-series data, plots, and summary files. The sample data subfolder consists of (1) total suspended solids (TSS) data; (2) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (3) total dissolved nitrogen (TN) data and averages; and (4) methods codes. All files are .csv, .pdf, .jpg, .jpeg, or .mov.
The effects of dissolved nickel on the oxygen reduction reaction (ORR) kinetics and oxygen transport properties of perfluorosulfonic acid (PFSA) thin films were investigated using rotating disk electrode (RDE) measurements of ORR on a PFSA-coated platinum electrode. The electrochemical characterization in 0.1 M perchloric acid (HClO 4 ) with and without added Ni 2+ quantitatively measured the impact of ionic interactions between the Ni 2+ cations and sulfonate (SO 3 - ) anions on oxygen transport through the PFSA thin film. Cyclic voltammetry (CV) curves in deaerated electrolyte showed that Ni 2+ cations diffusing through the PFSA thin film interact with the Pt surface altering the hydrogen underpotential deposition and stripping processes and decreasing ORR kinetics. The RDE limiting current results point to reduced permeability of oxygen through PFSA-Ni 2+ compared to PFSA-H + . Furthermore, the results indicate that transition metals leached from Pt alloy catalyst may be detrimental not only to the intrinsic ORR kinetics of the PEFC cathode catalyst through loss of the ORR-enhancing transition metal, but may also inhibit the diffusion of oxygen to the catalytic sites and poison the ORR.
Small-scale modular systems for oxygen generation offer clear benefits, including improved energy efficiency, reduced operating costs, and the flexibility to meet location-specific needs. We propose that a compact modular system could be developed using a solvent-based method for capturing and releasing oxygen, enabling “oxygen on demand” for various combustion technologies. In this project, we aim to develop and demonstrate a modular oxygen-selective approach based on Battelle IPID 31740. The use of designer solvents, which are reversible, single-component solvents capable of dissolving and separating oxygen from air, offers the advantage of unlimited chemical tunability to achieve desirable properties for efficient oxygen separation. We filed U.S. Patent (32845-E, iEdison No. 0685901-23-0184).
Monitoring water quality in sewers is challenging, particularly because state-of-the-art technologies require contact with the raw wastewater. The presence of fat, oil, grease, and solids makes automated grab sampling difficult and causes sensor fouling. To overcome these limitations, non-contact methods based on light reflectance, such as hyperspectral imaging (HSI), are gaining attention. However, HSI has never been tested for raw wastewater. To assess its accuracy for measuring pollution, we developed a laboratory setup and performed targeted experiments with a combination of raw and diluted wastewater, as well as synthetic turbidity stock solutions. We measured seven pollution variables: chemical oxygen demand, turbidity, dissolved organic compounds, ammonium, total nitrogen, phosphate, and sulphates. We used automated pixel selection and partial least squares regression to retrieve pollution information from the hyperspectral images. Our results, based on 144 samples, suggest that HSI can estimate pollution levels with a precision in the range of state-of-the-art absorbance spectrophotometric methods. Additionally, we found that the combination of pixel and wavelength selection, enabled by the hyperspectral data structure, significantly influences the performance of partial least square modelling. Overall, our findings indicate that HSI is a promising technology for non-contact monitoring of water quality in raw wastewater.
Coastal upland forests are exposed to intensifying precipitation regimes and sea level rise, increasing tree mortality and transforming these coastal forests into wetland ecosystems. Despite these well-known risks, the differing degrees to which hydrological, biogeochemical, and biological components of upland forests respond to novel salinity exposure is relatively unknown. The Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment decouples two distinct disturbances associated with hydrological extremes: (1) flooding from heavy precipitation and (2) exposure to saline conditions from storm surge. This dataset includes data reported in Myers-Pigg et al. (2025), which analyzed data from the first TEMPEST flooding treatment in 2022. This includes: - Colored dissolved organic matter in porewaters - Soil temperature and oxygen - Groundwater temperature and chemistry - Dissolved organic carbon concentrations in porewaters - Soil-to-atmosphere CH4 and CO2 fluxes - Soil temperature, water content, and electrical conductivity - Root-influenced CH4 and CO2 flux - Tree sap flow velocity - The R analytical code and documentation about the computational environmental in which it was run (the "sessionInfo.txt" file) All data files are plain-text comma separated value (CSV) and no special software is required to read them.
Manganese oxides are ubiquitous in soils and sediments, and their formation and transformation processes affect the migration and transformation of heavy metals and organic pollutants. Most previous work has been focused the oxidation of Mn(II) on Mn(IV) oxide surface, but it remains poorly understood how Mn(II) interacts with manganite under oxic conditions. Here, the interactions between manganite and dissolved Mn(II) within pH 5.0–9.0 under oxic conditions were systematically studied. The results indicated that adsorbed Mn(II) was directly oxidized to manganite on the surface, and the oxidation rate increased with increasing pH and oxygen partial pressure. Electrons are likely transferred in bulk manganite during the oxidation process of Mn(II). Although manganite induced Mn(II) oxidation and the epitaxial growth of bulk particles, there was no obvious change in mineral phase. Dissolved oxygen accelerated the growth of manganite in Mn(II) solution. Compared with the absence of manganite, the presence of manganite inhibited the formation of hausmannite from Mn(II) oxidation by oxygen in air. Furthermore, this study reveals the catalytic oxidation process and mechanism of Mn(II) on manganite surface, and improves the understanding of manganite crystal growth in supergene environments.