This data release provides several data files representing groundwater levels reported through driller's reports for the State of Louisiana Department of Natural Resources (Louisiana Department of Natural Resources, 2023) within or near the Mississippi Alluvial Plain (MAP) and (or) associated with the Mississippi River Valley alluvial aquifer (MRVA). First, a retrieval of data from the State of Louisiana was made and manual preparatory filtering including complete information of location, date, water level (depth below land surface) and water level altitude in feet, and general association with the MAP or MRVA. Further manual and digitally-assisted inspection was made to confirm that the data were not already within the U.S. Geological Survey (USGS) National Water Information System (NWIS) (U.S. Geological Survey, 2023). The agency code for the water levels has been assigned "LA018" (Louisiana Department of Natural Resources) in accordance with the https://help.waterdata.usgs.gov/codes-and-parameters/code/agency_cd_query?fmt=html (accessed February 28, 2023). Use of the LA018 agency code is consistent with historical and current USGS storage practices in NWIS when in collaboration with the State of Louisiana. This first data file is titled "LADNR_drillers_working.csv" (6,374 records). Second, that data file was processed through data structure conversion software (infoGW2visGWDB) (Asquith and Seanor, 2019) and in particular removal of well locations plotting outside the MAP boundary (Painter and Westerman, 2023) was made. The resultant but transient data structure of 4,855 of the original 6,374 records was given over to quality-control and assurance using statistical modeling (visGWDBmrva software) (Asquith and others, 2019, 2020). The statistical analyses result in formation of a regional statistical time series models using generalized additive models (GAMs) and support vector machines (SVMs). Some 18 records by horizontal position having a missing altitude of the bottom of the MRVA and zero records having water-level altitudes below the bottom of the MRVA when digitally working with the Torak and Painter (2019) surface of the MRVA bottom. These 18 records are retained through the workflow described herein to avoid potential scientific interpretation of hydrogeologic framework. In summary, for each of the 4,855 well-water-level records (or rather in detail, each unique well identifier), the visGWDBmrva software isolated all water levels for the MAP/MRVA from USGS (2023) within 16 kilometers radial distance. This means that the driller's dataset is being internally compared to itself and USGS MAP/MRVA data. The visGWDBmrva software computed a "pseudo water level" from a blending of GAM and SVM model predictions for the date of the driller's recorded water level. These computations are all created on-the-fly. A residual was computed from the pseudo water level (as altitude) to that water-level altitude reported for the well-water-level record of the driller's dataset. These statistical results are listed the file titled "LADNR_retained_levels.csv" (4,744 records) for which records were retained LADNR_drillers_working.csv if the absolute value of the residual of the well-water-level record and the pseudo water level was less than or equal to 20 feet. This threshold resulted from exploratory review of the statistical computations and is consistent with Smith and others (2020) and Weber and others (2021) for a similar driller's reported dataset for the Missouri part of the MAP/MRVA. The results listed in file LADNR_retained_levels.csv are deemed especially suitable for greater statistical modeling of groundwater levels in the MRVA (Asquith and Killian, 2022).

During the spring and summer of 2020, the U.S. Geological Survey, Lower Mississippi – Gulf Water Science Center, conducted single well slug tests on selected wells within the Mississippi Alluvial Plain of Arkansas and Mississippi to estimate hydraulic conductivity (K) and transmissivity (T) values for the aquifers in which the wells are screened. A total of 324 test were conducted on 48 wells. The computer software AQTESOLV for Windows (Duffield, 2007) was used to interpretate the slug test data to estimate K and T values. Mean estimates of K for the 44 wells completed in the Mississippi River Valley alluvial aquifer ranged from 3 to 401 feet per day (ft/day) and mean estimates of T ranged from 285 to 80,559 square feet per day (ft2/day). Mean estimates of K for the 4 wells completed in the Sparta Sand or 500-foot Sand (Memphis Aquifer) that make up part of the middle Claiborne aquifer of the Mississippi embayment aquifer system ranged from 0.14 to 183 ft/day and mean estimates of T ranged from 55 to 67,913 ft2/day. This Data Release contains the following data and supporting metadata: 1. A PDF document with calibration information for the mechanical slugs used for testing. 2. A zipped file of the 48-site files folders containing: 1. The site’s slug test field form (pdf). 2. Digital images of the site (jpg). 3. Water-level pressure transducer log files (csv), 4. Excel files(s) of transducer data with Time vs. Water Depth plots and the selected Time – Displacement data used for analysis. 5. The AQTESOLV solution report files (aqt) for each slug test. 3. A summary data file in two formats (csv & GIS shape file) including the following information for each site: 1. Site information [site name, agency code, USGS National Water Information System (NWIS) site number] 2. Location information (latitude, longitude, state, county). 3. Well construction information [well depth and diameter, casing diameter, top and bottom of opening (screen), and opening (screen) length]. 4. Aquifer information (local and national aquifer codes, and aquifer thickness). 5. Slug test information (test date and static water-level). 6. Estimates information (minimum, mean, median, and maximum K and T values and the solution method). 4. An equipment documentation file (csv) listing the water-level tape, transducer, and slug used at each site. 5. A water-level documentation file (csv) listing the before and after testing water-level measurements for each site. 6. A model input file (csv) listing the values input into the model for each test. 7. A model solutions file (csv) listing both the “Visual” and “Auto” match solution estimates for the slug tests at each site. Additional information, including discussions of the hydrogeologic setting, well descriptions, slug testing and analysis methods, and a summary of the slug test results are available in the Open File Report associated with this Data Release (Pugh, 2021). This dataset was collected and analyzed as part of the U.S. Geological Survey, Mississippi Alluvial Plain Regional Water-Availability Study.

This dataset contains all data and code required to reproduce the time-to-event analysis in the associated manuscript. More detail is found in the associated README.md file.Contents of repositoryYaeger_ReservoirDataset_Oct2022.csv: comma-separated data file with reservoir characteristics, construction times, and water table depths and percent saturation at 5-year intervals from 1975-2015.CGA_reservoir_analysis.Rmd: RMarkdown notebook with all code required to reproduce the time-to-event analysis in the manuscript and generate the associated plots.CGA_reservoir_analysis.html: HTML file rendered from the .Rmd notebook.README.md: additional details, including column descriptions from the CSV file.Software versions usedR version 4.1.2 (https://cran.r-project.org/bin/windows/base/old/4.1.2)R packages:data.table v1.14.8 (https://rdatatable.gitlab.io/data.table/)ggplot2 v3.4.4 (https://ggplot2.tidyverse.org/)sf v1.0-14 (https://r-spatial.github.io/sf/)survival v3.5-5 (https://cran.r-project.org/package=survival)icenReg v2.0.15 (https://cran.r-project.org/package=icenReg)

This dataset contains in situ water level measurements collected at 49 different locations across the Atchafalaya and Terrebonne basins in the Mississippi River Delta (MRD) floodplain, and 49 files with the in situ measurements from raw water level converted to absolute water surface elevation with respect to NAVD88 (GEOID12B). There were 65 sites included in the study, however, data from 16 of the sites were corrupted, unretrievable from the instrument or the instrument was lost during deployment. Additionally, it contains water surface elevations collected by GNSS mounted to a boat while underway, and a summary file with site information for all 65 sites. Relative water level measurements were recorded every 15-20 minutes using commercial pressure transducers (Levelogger, Solinst) to measure water depth. Water surface elevation was determined by measuring an absolute height conversion at each sensor location using AirSWOT or a survey-grade global navigation satellite system (GNSS). These water level measurements calibrate and validate the Delta-X campaign's remote sensing observations and hydrodynamic models. The data are provided in comma separated values (CSV) and JPEG image formats.

This dataset captures in digital form the results of previously published U.S. Geological Survey (USGS) Water Mission Area studies related to water resource assessment of Cenozoic strata and unconsolidated deposits within the Mississippi Embayment and the Gulf Coastal Plain of the south-central United States. The data are from reports published from the late 1980s to the mid-1990s by the Gulf Coast Regional Aquifer-System Analysis (RASA) studies and in 2008 by the Mississippi Embayment Regional Aquifer Study (MERAS). These studies, and the data presented here, describe the geologic and hydrogeologic units of the Mississippi embayment, Texas coastal uplands, and the coastal lowlands aquifer systems, south-central United States. The Mississippi embayment, Texas coastal uplands, and coastal lowlands aquifer systems underlie about 487,000 km2 in parts of Alabama, Arkansas, Florida, Illinois, Kentucky, Louisiana, Mississippi, Missouri, Tennessee, and Texas from the Rio Grande on the west to the western part of Florida on the east. The previously published investigations divided the Cenozoic strata and unconsolidated deposits within the Mississippi Embayment and the Gulf Coastal Plain into 11 major geologic units, typically mapped at the group level, with several additional units at the formational level, which were aggregated into six hydrogeologic units within the Mississippi embayment and Texas coastal uplands and into five hydrogeologic units within the Coastal Lowlands aquifer system. These units include the Mississippi River Valley alluvial aquifer, Vicksburg-Jackson confining unit (contained within the Jackson Group), the upper Claiborne aquifer (contained within the Claiborne Group), the middle Claiborne confining unit (contained within the Claiborne Group), the middle Claiborne aquifer (contained within the Claiborne Group), the lower Claiborne confining unit (contained within the Claiborne Group), the lower Claiborne aquifer (contained within the Claiborne Group), the middle Wilcox aquifer (contained within the Wilcox Group), the lower Wilcox aquifer (contained within the Wilcox Group), and the Midway confining unit (contained within the Midway Group). This dataset includes structure contour and thickness data digitized from plates in two reports, borehole data compiled from two reports, and a geologic map digitized from a report plate. Structure contour and thickness maps of hydrogeologic units in the Mississippi Embayment and Texas coastal uplands had been previously digitized by a USGS study from georeferenced images of altitude and thickness contours in USGS Professional Paper 1416-B (Hosman and Weiss, 1991). These data, which were stored on the USGS Water Mission Area’s NSDI node, were downloaded, reformatted, and attributed for present dataset. Structure contour maps of geologic units in the Mississippi Embayment and Texas coastal uplands were digitized and attributed from georeferenced images of altitude and thickness contours in USGS Professional Paper 1416-G (Hosman, 1996) for this data release. Borehole data in this data release include data compiled for USGS Gulf Coast RASA studies in which a scanned version of a USGS report (Wilson and Hosman, 1987) was converted through optical character recognition and then manipulated to form a data table, and from borehole data compiled for the subsequent MERAS study (Hart and Clark, 2008) where an Excel workbook was downloaded and manipulated for use in a GIS and as part of this dataset. The digital geologic map was digitized from Plate 4 of USGS Professional Paper 1416-G (Hosman, 1996) and then attributed according to the USGS National Cooperative Geologic Mapping Program’s GeMS digital geologic map schema. The digital dataset a digital geologic map with contacts and faults and geologic map polygons distributed as separate feature classes within a geographic information system geodatabase. The geologic map database is a digital representation of the geologic compilation of the Guld Coast region originally published as Plate 4 of USGS Professional Paper 1416-G (Hosman, 1996). The dataset includes a second geographic information system geodatabase that contain digital structure contour and thickness data as polyline feature classes for all of the hydrogeologic units contoured in USGS Professional Paper 1416-B (Hosman and Weiss, 1991) and all of the geologic units contoured in USGS Professional Paper 1416-G (Hosman, 1996). The geodatabase also contains separate point feature classes that portray borehole location and the depth to hydrogeologic units penetrated downhole for all boreholes compiled for the USGS RASA sturdies by Wilson and Hosman (1987) and for the subsequent USGS MERAS study (Hart and Clark, 2008). Borehole data are provided in Microsoft Excel spreadsheet that includes separate TABs for well location and tabulation of the depths to top and base of hydrogeologic units intercepted downhole, in a format suitable for import into a relational database. Each of the geographic information system geodatabases include non-spatial tables that describe the sources of geologic or hydrogeologic information, a glossary of terms, and a description of units. Also included is a Data Dictionary that duplicates the Entity and Attribute information contained in the metadata file. To maximize usability, spatial data are also distributed as shapefiles and tabular data are distributed as ascii text files in comma separated values (CSV) format.

This data package is associated with the publication “Riverine dissolved organic matter transformations increase with watershed area, water residence time, and Damköhler numbers in nested watersheds” submitted to Biogeochemistry by Ryan et al., 2024 (DOI: https://doi.org/10.1007/s10533-024-01169-5). This study aims to investigate fundamental and transferable drivers of dissolved organic matter (DOM) diversity across five nested watersheds within the contiguous United States. DOM diversity was explored using ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The samples and the unprocessed FTICR-MS data used in this study are publicly available on the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) data repository (see DOIs below). The data for the Willamette, Gunnison, Connecticut, and Deschutes basins were collected as part of a collaboration between the Watershed Rules of Life (WROL) project and Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS). The data for the Yakima River basin (YRB) was collected by the PNNL River Corridor SFA. The raw, unprocessed FTICR-MS data with additional (meta)data can be found at doi:10.15485/1895159 for WROL samples and doi:10.15485/1898912 for YRB samples. This data package contains the processed data used in the associated manuscript. This package also contains ancillary geospatial, hydrological, and geochemical information that supports the interpretation of the FTICR-MS data within Ryan et al., 2024. This data package is associated with the GitHub repository found at https://github.com/WHONDRS-Hub/rcsfa-RC4-WROL-YRB_DOM_Diversity. At the directory level, the data package is comprised of three folders: (1) data, (2) output, and (3) src; and five additional files including the data dictionary (file ending in "_dd.csv”) and file-level metadata (file ending in “_flmd.csv”). The “src” folder contains the scripts used to process the FTICR data, conduct the analyses, and produce the manuscript figures. The inputs for these scripts are in the “data” folder and the returned outputs in the “output” folder. Inputs include temporal and spatial metadata associated with the sampling efforts, processed FTICR data, and total and normalized putative biochemical transformations per sample. Outputs include cleaned and combined data presented as tables, descriptive statistics, and plots. The file-level metadata file lists all files contained in this data package and descriptions for each. The data dictionary describes the units and definitions for each tabular data column or row header.

This dataset includes estimates of total suspended solids (TSS) concentration and turbidity for waters of the Atchafalaya River and Terrebonne Basins of the Mississippi River Delta (MRD) in coastal Louisiana. Estimates were derived from Level 2 (L2) BRDF-corrected imagery from NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). AVIRIS-NG imagery was collected from March 27-April 6 (spring) and August 20-25 (fall), 2021, as part of the 2021 Delta-X campaign. Algorithms for TSS and turbidity estimation were developed using in-situ remote-sensing reflectance measured at field sampling stations paired with in-situ measures of turbidity from a water quality probe and TSS from water samples. Using the in-situ data, a partial least squares regression (PLSR) model was developed for each AVIRIS-NG wavelength. A subset of the in-situ data, collected during relatively clear AVIRIS-NG overflights, was held out to validate the PLSR model. The PLSR algorithm was then applied to AVIRIS-NG imagery to retrieve TSS and turbidity across the study area. The measurement units for TSS and turbidity estimates are mg L-1 and Formazin Nephelometric Units (FNU), respectively, and the spatial resolution is 3.8 to 5.4 m as determined by the AVIRIS-NG imagery. The dataset includes binary cloud and water masks. These data quantify the mesoscale (i.e., on the order of 1 ha) patterns of soil accretion that control land loss and gain and predict the resilience of deltaic floodplains under projected relative sea-level rise. Gridded estimates are provided in netCDF format, and regression coefficients are included in a comma-separated values (CSV) file. This is Version 3 of this dataset. All previously released data were updated to the latest available versions.

This data package is associated with the publication "Organic Matter Transformations are Disconnected Between Surface Water and the Hyporheic Zone" submitted to Biogeosciences (Stegen et al., 2022). The study aims to understand how the diversity of OM transformations varies across surface and subsurface components of river corridors using inland surface water and sediments collected along river corridors across the contiguous United States. Sediment extracts and water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). This dataset is comprised of one folder (WHONDR_S19S) which contains (1) a subfolder with R scripts used to process the data and to calculate biochemical transformations, (2) processed FTICR-MS data as csv files, sample collection metadata and climate data as csv files, (3) biochemical transformations profile, classifications and database as csv files, and (4) a readme file with more information regarding WHONDRS raw FTICR-MS data and processing scripts. Outside of the main folders there is a csv containing file-level metadata and a csv data dictionary defining column headers for all csv files contained in the data package. The samples were part of a WHONDRS (https://whondrs.pnnl.gov) study. The raw, unprocessed FTICR-MS data with additional data can be found at doi:10.15485/1729719 formore » sediments and doi:10.15485/1603775 for water. This data package contains the processed data used in the associated manuscript.« less

Dissolved oxygen (DO), total organic carbon (TOC), total nitrogen (TN), molecular data for organic matter, and biochemical reactions for surface water and porewater (i.e., hyporheic zone) collected from a water recirculating flume located at the University of Texas, Austin. The flume contained real river water from Lower Colorado River(Austin, TX) and clean sand. Hyporheic exchange in the flume was induced through The study aims to understand relationships between aerobic metabolism of organic matter and molecular characteristics of organic matter, such as thermodynamic signature and nitrogen content, through the extent of the hyporheic zone at 10 cm- resolution, and through time. During the experiment, organic matter (dry leaves) was added to the flume and removed after 24 hours. The water samples were collected before the addition of leaves, at the time of removal of leaves, and at hour 72. The water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and total organic carbon (TOC) and total nitrogen (TN) analysis. Dissolved oxygen content throughout the surface water and the hyporheic zone of the flume was measured with a large planar optode. This data package is associated with the publication ’ Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry’ published in Environmental Science and Technology (Turețcaia et al., 2023 https://doi.org/10.1021/acs.est.3c04765). The dataset is comprised of five folders (1) Diss_O2_pic, (2) input_files (3) output_files; (4) python_code; and (5) R_code . Diss_O2_pic contains siximages of dissolved oxygen distribution in a bedform at hours 0, 24, and 72 of the experiment conducted in a large recirculation flume. Images are in separate R and G channels (i.e., RGB). The input_files contains (1) a csv file with FTICR peaks identified within each sample, (2) a csv file with molecular information pertinent to FTICR data with Gibbs free energy calculations adjusted for environmental temperature, (3) a csv file containing concentrations of non-purgeable organic carbon measured throughout the experiment , (4) a csv file containing concentrations of total nitrogen measured throughout the experiment, (5) a csv file containing total biochemical reactions (i.e., transformations) identified in the dataset, (6) a csv containing transformation profiles, and (7) a csv file containing transformations with formulas, and (8) a jpg file with schematic representation of locations for sample collection. The output_files contains (1) and xlsx file containing percent biochemical reactions containing nitrogen identified across all 39 sample, (2) a csv file of merged FTICR data and molecular information files, (3) a csv files containing average Gibbs free energy within sampling domains and at each sampling location, (4) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 0, (5) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 24, (6) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 72, (7) a csv file with percent chemical classes identified across sampling locations at hour 0, (8) a csv file with percent chemical classes identified across sampling locations at hour 24, (9) a csv file with percent chemical classes identified across sampling locations at hour 72, and (10) a csv file containing percent nitrogen containing biochemical reactions identified across sampling locations at hours 0, 24, and 72. The python_code contains seven ipynb files which are Jupyter Notebooks used for data analysis and figures generation. The R_code contains 3 R files with R code used for data analysis and figures generation. This data package contains the processed data used in the associated manuscript. This data has not been previously published.

This data package provides scripts and geochemical data for a manuscript titled “Linkages between mineral element composition of soils and sediments with hyporheic zone dissolved organic matter chemistry across the contiguous United States” (preprint: doi: 10.22541/essoar.169447343.31694990/v1). This data is associated with the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS, https://whondrs.pnnl.gov) and is an extension of the Summer 2019 Sampling campaign which crowdsourced samples from rivers and sediment across the continental United States. Data from this study can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719. The main objective of this manuscript was to couple sediment water extractable dissolved organic matter chemistry, defined by ultra-high resolution mass spectrometry, with localized sediment elemental composition and watershed scale soil elemental characteristics. This data package contains one main folder with four subfolders. The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) an R markdown to reproduce manuscript figures and analyses; (5) a pdf of instructions to reproduce NGS interpolations with ArcGIS software; and (6) a python script to reproduce NGS extrapolations with python. The four subfolders contain files required to reproduce NGS extrapolations include (1) ‘CONUS_boundaries’ containing boundary layers (.shp) for the Continental United States; (2) ‘ngs_project’ containing files (.shp) with point level NGS soil elemental data (Grossman et al., 2004); (3) ‘raster_outputs’ containing the interpolated raster output files for various soil elements; and (4) ‘NGS_Chemistry_Final’ contain final extracted soil elemental data.

This dataset includes processed organic matter chemistry data from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and vegetation materials representative of major land cover types of the Pacific Northwest, USA. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. Source data and associated metadata (including methods and geospatial information) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1894135 (Grieger et al. 2022). This dataset provides processing scripts and processed data for both solid and dissolved phase organic matter characterization data from experimentally generated chars. These processed data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. The processed data were subsequently analyzed; and the results and ecological implications of the findings were published in peer-reviewed manuscripts. The scripts and workflows used to develop the manuscripts are also included in this data package. This data package was originally published June 2024. It was updated September 2024 (new and modified files) and in January 2025 (modified files). See the change history section in the readme for more details. This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), and folders containing (A) processed data; (B) general processing scripts; and (C) additional folders with specific manuscript analysis scripts and processed data. Step-by-step instructions to assist the user in recreating the workflow used to generate the results in the manuscripts is also provided. The processed data folder includes (1) a folder of processed Parallel Factor Analysis (PARAFAC) and spectra indices outputs from excitation emissions matrix (EEM) fluorescence and absorbance data; (2) a folder of processed solid state carbon-13 (13-C NMR) integrals; (3) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) processed data outputs from Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude), blank corrections and data aggregation, and calculated molecular indices. All files are .pdf, .csv, .html, .Rmd, .R, or .RData.

This dataset supports the broader Watershed Rules of Life (WROL) study examining spatial and temporal biogeochemical and microbial relationships across the Connecticut River, Deschutes River, Gunnison River, and Willamette River watersheds. The dataset provides geochemistry and organic matter characterization data generated from surface water collected from August 2019 to September 2020 in Colorado, Connecticut, Oregon, and Vermont. Related data were collected and will be published separately in collaboration with Raymond and Crump as part of WROL. This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) field metadata; (5) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (6) surface water sampling protocol; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; and (9) folder of high resolution characterization of organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml.