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At least 1,423 records · Page 79

DAISY Acoustic Measurements in Agate Pass, WA

Acoustic data and metadata from Drifting Acoustic Instrumentation SYstem (DAISY) testing in Agate Pass (separating the north end of Bainbridge Island and the Kitsap Peninsula in Puget Sound), WA in April 2022. The goal was to characterize radiated noise from a cross-flow turbine deployed from a moored vessel. As discussed in the accompanying report, sound produced by the turbine was below the ambient nose floor at the surveyed ranges.

16 TIDAL AND WAVE POWER↗

Hawaii Wave Surge Energy Converter (HAWSEC) OSU O.H. Hinsdale Basin

The following information and metadata applies to both the Phase I (Hydrodynamics) and Phase II (Full System Power Take-Off) zip folders which contain testing data from the OSU (Oregon State University) O.H. Hinsdale Wave Research Laboratory, from both OSU and the University of Hawaii at Manoa (UH). See zip folders provided further below in the downloads section. For experimental data of the full system, including PTO, see Phase II dataset. There are two main directories in each Phases's zip folder: "OSU_data" and "UH_data". The "OSU_data" directory contains data collected from their DAQ (data acquisition system), which includes all wave gauge observations, as well as body motions derived from their Qualisys motion tracking system. The organization of the directory follows OSU's convention. Detailed information on the instrument setup can be found under "OSU_data/docs/setup/instm_locations". The experiments conducted are documented in the "OSU_data/docs/daq_logs", which provides the trial number to the corresponding data located under "OSU_data/data" in several formats (e.g., ".mat" and ".txt"). Inside the trial directory, data is provided for each of the instruments defined in "OSU_data/docs/setup/instm_locations". The "UH_data" directory contains data collected from their DAQ. The data is stored in a ".tdms" file format. There are free plug-ins for Microsoft Excel and MathWorks MATLAB to read the ".tdms" format. Below are a few links providing methods to read in the data, but a Google search should identify alternatives sources if these no longer exist (valid as of January 2024): Excel: http://www.ni.com/example/27944/en/ MATLAB: https://www.mathworks.com/matlabcentral/fileexchange/30023-tdms-reader The Excel plugin is recommend to get a quick overview of the data. The UH data is organized by directory name, in which the sub-directories for each experiment contains a directory whose name defines the wave height and period for the experimental data within. For example, a directory name "H02_T0275" corresponds to an experiment with wave height 0.1m and a period of 2.75s. For random wave data, the gamma value is also included in the directory name. For example, a directory name "H02_T0225_G18" corresponds to an experiment with a significant wave height of 0.2m, a peak period of 2.25s, and a gamma value of 1.8, with each spectra being a TMA spectrum. For the free decay experiments, the directory name is defined by the initial angular displacement. For example, a directory name "ang05_run01" corresponds to an experiment with an initial angular displacement of 5 degrees. There is a dataset in the UH data for each corresponding experiment defined in the OSU DAQ logs. The ".tdms" data is output from the DAQ at fixed intervals. Therefore, if multiple files are contained within the folder, the data will need to be stitched together. Within the UH dataset, there are two input channels from the OSU DAQ providing a random square wave signal for time synchronization ("ENV-WHT-0010") and a high/low signal ("ENV-WHT-0012") to identify when the wave maker is active (+5V). The UH data is logged as a collection of channel outputs. Channels not in use for the OSU testing (either Phase I or Phase II) are marked "nan" below. If the sensor is disconnected, it will record noise throughout the experiment. Below are the channel definitions in terms of what they measure: GPS Time = time CYL-POS-0001 = position between flap and fixed reference CYL-LCA-0001 = force between flap and hydraulic cylinder REC-LPT-0001 = nan REC-HPT-0001 = nan REC-HPT-0002 = nan REC-HPT-0003 = nan HHT-HPT-0001 = pressure at exhaust ("head" only) REC-FQC-0001 = nan REC-FQC-0002 = nan HHT-FQC-0001 = flow at exhaust ("head" only) ENV-WHT-0001 = nan ENV-WHT-0002 = nan ENV-WHT-0003 = nan ENV-WHT-0010 = random signal from OSU DAQ ENV-WHT-0012 = high/low signal from OSU DAQ Also included is a calibration curve to convert the string pot data to flap pi...

16 TIDAL AND WAVE POWER↗

Bench Testing Data and Report for an Early Prototype Pitch Resonator WEC

This dataset encompasses data and documentation from bench tests conducted on an early prototype of a "pitch resonator" wave energy converter (WEC). The testing aimed to validate numerical models and reduce risks associated with the pitch resonator concept, which is designed to convert the pitching and rolling motions of a buoy into electrical power. The project's goal is to provide supplementary power, in the range of 10-100 watts, to the National Science Foundation's Ocean Observatories Initiative Pioneer Array. Two distinct testing phases are documented: one using a single degree of freedom (1DOF) test rig, and another employing a six degree of freedom (6DOF) Stewart platform, known as the Large Amplitude Motion Platform (LAMP). These tests assessed various factors, such as system performance in different motion scenarios, the torque exerted by wave forces, and the impact of mounting configurations. The dataset includes raw test data in MATLAB (.mat) format, detailed metadata, and a report describing the experimental procedures and preliminary findings.

16 TIDAL AND WAVE POWER↗

Version 2 - Tidal Energy Resource Characterization, Velocity and Turbulence Measurements, Cook Inlet, AK, 2021

Version 2 of MHKDR submission #475, which also contains the metadata for these measurements. Files here are stored in netCDF4 format, which can be read in Python using the "netcdf4" or "xarray" packages or in MATLAB using the "ncread()" function. Changes are as follows: MWM1 (mid-water mooring 1) ADV - Time length of data now ends when bottom track data is lost - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved velocity, turbulent kinetic energy (TKE), Reynolds stress, time interval (TI), and dissipation rate estimations MWM1 Down-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified MWM1 Up-Looking ADCP - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified - Velocity unchanged MWM2 ADV - Removes data after instrument was hit by debris - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved velocity, TKE, Reynolds stress, TI, and dissipation rate estimations MWM2 Down-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified MWM2 Up-Looking ADCP - Improved filtering and quality control of bottom track measurements - improved motion correction of velocity - Improved Doppler noise subtraction - improved TI and dissipation rate estimations - Removed TKE calculations - accuracy could not be verified THEOM (bottom lander) ADV - Improved Doppler noise subtraction - improved TKE, Reynolds stress, TI, and dissipation rate estimations - Velocity unchanged THEOM ADCP (up-looking) - Improved Doppler noise subtraction - improved TKE, TI, and dissipation rate estimations - Removed vertical TKE component (w'w' bar) - Velocity unchanged

16 TIDAL AND WAVE POWER↗

EV Profile Capture

NextGen Profiles' EV profile capture efforts aimed to explore the variance in performance and evaluate how different operational conditions influence production EV charging behavior. Data were collected at a frequency of 10 Hz from both the EV and EVSE during each charge session. These charge session parameters were then entered into a time-series database for further analysis. The data were gathered under different operational conditions to examine the effects of various factors such as battery state of charge, battery temperature, vehicle condition, smart charge management, and EVSE limitations. The EV profile capture dataset includes extensive high-power charging data from 16 different EVs—comprising light-, medium-, and heavy-duty vehicles—along with EVSE from various suppliers. To protect confidentiality, the EV and EVSE metadata are anonymized, and the publicly released datasets are aggregated to 0.1-Hz frequency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

EVSE Characterization

NextGen Profiles' EVSE characterization efforts explored performance variability in production EVSE through the use of EV emulation equipment and assessed how different operational conditions influence charging behavior. Data were collected at a frequency of 10 Hz from both the EV emulator and EVSE during each charge session and stored in a time-series database for further analysis. As part of the NextGen Profiles project, characterization of high-power EVSE was performed on both conductive and wireless charging infrastructure; however, only conductive charging data are currently included in this repository. This EVSE characterization was performed over a range of DC output currents and voltages, covering both nominal and off-nominal test conditions. This EVSE characterization dataset includes high-power charging data from two types of 350-kW-capable EVSE using liquid-cooled Combined Charging System-1 (CCS1, North American version) cables and connectors. To protect confidentiality, all EVSE metadata are anonymized, and the publicly released datasets are metered at 10-Hz frequency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Fleet Utilization

A key goal of NextGen Profiles' fleet utilization study was to conduct a comprehensive, strategic, and standardized assessment of the operational behavior and utilization patterns across EV and EVSE production-ready fleets. These data-driven insights were intended to inform current fleet management strategies and support future infrastructure planning, ensuring the effective adoption and adaptation of the growing EV fleet market. The study applied a series of metrics defined in NextGen Profiles to evaluate diverse fleet operations across various use cases, emphasizing trends in charging, routing, and other critical behaviors. The fleet utilization dataset includes these three sets of metrics from 17 EV fleets, each consisting of a wide range of vehicle types and operational categories, as well as two EVSE fleets. Data were collected from a variety of sources and reformatted into a unified structure before metric computation, ensuring consistency and comparability across all fleets. To protect confidentiality, all fleet metadata are anonymized, and the publicly released metric datasets are aggregated to an hourly cadence.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Livewire Data Platform

The Livewire Data Platform makes it easy to search and share transportation and mobility-related data. The Livewire Data Platform supports the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy’s Energy Efficient Mobility Systems (EEMS) Program goal of providing an affordable, efficient, safe, and accessible transportation future where mobility is decoupled from energy consumption. The Livewire Data Platform will function as a repository for all EEMS data and will support the following objectives: (1) EEMS partners with relevant data can catalog, document, and share project datasets via file-based sharing or Application Programming Interface (API) and can provides access management and usage auditing for those resources. (2) EEMS partners can securely search, discover and access shared datasets, their metadata, and available API’s. (3) External partners and researchers can discover EEMS capabilities and collaborate with EEMS partners.

99 GENERAL AND MISCELLANEOUS↗

WHONDRS 48 Hour Diel Cycling Study at HJ Andrews Experimental Forest Watershed 1 (WS1)

This dataset is from a 48 hour sampling campaign at H.J. Andrews Experimental Forest, Oregon, USA. Filtered surface water and pore water samples were collected every three hours from the Watershed 1 (WS1) stream. Samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL) for high resolution carbon characterization via Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). In addition, basic geochemistry analyses (e.g., dissolved organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. All data types are provided in a standard format. In addition, the data package contains instructions to process the FTICR data based on the user’s specific needs. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. Please use the data package’s DOI to cite the data package. Note that the included hydrograph has a separate DOI that should also be cited. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your documents, presentations, etc. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗

WHONDRS 48 Hour Diel Cycling Study at the Nisqually River, WA

This dataset is from a sampling campaign completed over the course of 48 hours to investigate the effects of glacial freeze/thaw cycle-induced water level variation on aqueous chemistry, dissolved organic matter chemistry, and metabolic potential of microbial communities at the Nisqually River, WA, USA. Filtered surface water (SW) and pore water (PP) samples were collected every three hours in August 2018. This dataset is one of seven companion datasets that were part of the WHONDRS 48 Hour Diel Cycling Study of freshwater rivers. All seven datasets are available on ESS-DIVE; they can be found by searching for WHONDRS 48 Hour.This package contains a variety of chemical and hydrologic variables. All data types are provided in a standard format. Basic geochemistry analyses (e.g., non-purgeable organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. Aqueous chemistry variables include USGS codes in the first portion of the variable name (e.g., 00940_Cl_mg_per_L). These codes allow for interoperability with USGS water quality data. In addition, samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) for high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The data package contains instructions to process the FTICR data based on the user’s specific needs, and sample-level summary indices derived from the FTICR data will be added to the data package. Beyond the data in this data package, metagenomic data are being generated on associated microbial communities. When these data are available, the data package will be updated with information on accessing them. Please contact WHONDRS@pnnl.gov for more information. Please use the data package’s DOI to cite the data package. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your publications, proposals, presentations, etc. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. Note that the included hydrograph has a separate DOI that should also be cited. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗

WHONDRS 48 Hour Diel Cycling Study at the Erpe River, Germany

This dataset is from a sampling campaign completed over the course of 48 hours to investigate the effects of wastewater treatment plant effluent induced water level variation on aqueous chemistry, dissolved organic matter chemistry, and metabolic potential of microbial communities at the Erpe River, Germany. Filtered surface water (SW) and pore water (PP) samples were collected every three hours in September 2018. This dataset is one of seven companion datasets that were part of the WHONDRS 48 Hour Diel Cycling Study of freshwater rivers. All seven datasets are available on ESS-DIVE; they can be found by searching for WHONDRS 48 Hour.This package contains a variety of chemical and hydrologic variables. All data types are provided in a standard format. Basic geochemistry analyses (e.g., non-purgeable organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. Aqueous chemistry variables include USGS codes in the first portion of the variable name (e.g., 00940_Cl_mg_per_L). These codes allow for interoperability with USGS water quality data. In addition, samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) for high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The data package contains instructions to process the FTICR data based on the user’s specific needs, and sample-level summary indices derived from the FTICR data will be added to the data package. Beyond the data in this data package, metagenomic data are being generated on associated microbial communities. When these data are available, the data package will be updated with information on accessing them. Please contact WHONDRS@pnnl.gov for more information. Please use the data package’s DOI to cite the data package. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your publications, proposals, presentations, etc. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗

WHONDRS 48 Hour Diel Cycling Study at the Columbia River in Washington, USA

This dataset is from a sampling campaign completed over the course of 48 hours to investigate the effects of the upstream Priest Rapids Dam-induced water level variation on aqueous chemistry, dissolved organic matter chemistry, and metabolic potential of microbial communities at the Columbia River, WA, USA. Filtered surface water (SW) and pore water (PP) samples were collected every three hours in August 2018. This dataset is one of seven companion datasets that were part of the WHONDRS 48 Hour Diel Cycling Study of freshwater rivers. All seven datasets are available on ESS-DIVE; they can be found by searching for WHONDRS 48 Hour.This package contains a variety of chemical and hydrologic variables. All data types are provided in a standard format. Basic geochemistry analyses (e.g., non-purgeable organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. Aqueous chemistry variables include USGS codes in the first portion of the variable name (e.g., 00940_Cl_mg_per_L). These codes allow for interoperability with USGS water quality data. In addition, samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) for high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The data package contains instructions to process the FTICR data based on the user’s specific needs, and sample-level summary indices derived from the FTICR data will be added to the data package. Beyond the data in this data package, metagenomic data are being generated on associated microbial communities. When these data are available, the data package will be updated with information on accessing them. Please contact WHONDRS@pnnl.gov for more information. Please use the data package’s DOI to cite the data package. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your publications, proposals, presentations, etc. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗

WHONDRS 48 Hour Diel Cycling Study at the Jordan River, Israel

This dataset is from a sampling campaign completed over the course of 48 hours to investigate the effects of groundwater pumping induced water level variation on aqueous chemistry, dissolved organic matter chemistry, and metabolic potential of microbial communities at the Jordan River, Israel. Filtered surface water (SW) and pore water (PP) samples were collected every three hours in August 2018. This dataset is one of seven companion datasets that were part of the WHONDRS 48 Hour Diel Cycling Study of freshwater rivers. All seven datasets are available on ESS-DIVE; they can be found by searching for WHONDRS 48 Hour.This package contains a variety of chemical and hydrologic variables. All data types are provided in a standard format. Basic geochemistry analyses (e.g., non-purgeable organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. Aqueous chemistry variables include USGS codes in the first portion of the variable name (e.g., 00940_Cl_mg_per_L). These codes allow for interoperability with USGS water quality data. In addition, samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) for high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The data package contains instructions to process the FTICR data based on the user’s specific needs, and sample-level summary indices derived from the FTICR data will be added to the data package. Beyond the data in this data package, metagenomic data are being generated on associated microbial communities. When these data are available, the data package will be updated with information on accessing them. Please contact WHONDRS@pnnl.gov for more information. Please use the data package’s DOI to cite the data package. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your publications, proposals, presentations, etc. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗

WHONDRS 48 Hour Diel Cycling Study at the East Fork Poplar Creek in Tennessee, USA

This dataset is from a sampling campaign completed over the course of 48 hours to investigate the effects of wastewater treatment plant effluent induced water level variation on aqueous chemistry, dissolved organic matter chemistry, and metabolic potential of microbial communities at the East Fork Poplar Creek, TN, USA. Filtered surface water (SW) and pore water (PP) samples were collected every three hours in August 2018. This dataset is one of seven companion datasets that were part of the WHONDRS 48 Hour Diel Cycling Study of freshwater rivers. All seven datasets are available on ESS-DIVE; they can be found by searching for WHONDRS 48 Hour.This package contains a variety of chemical and hydrologic variables. All data types are provided in a standard format. Basic geochemistry analyses (e.g., non-purgeable organic carbon concentration, cations, anions, SpC, pH) were conducted, standardized photos were taken, surface water hydrographs were collated from existing instrumentation, and extensive metadata were captured. Aqueous chemistry variables include USGS codes in the first portion of the variable name (e.g., 00940_Cl_mg_per_L). These codes allow for interoperability with USGS water quality data. In addition, samples were delivered to the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) for high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The data package contains instructions to process the FTICR data based on the user’s specific needs, and sample-level summary indices derived from the FTICR data will be added to the data package. Beyond the data in this data package, metagenomic data are being generated on associated microbial communities. When these data are available, the data package will be updated with information on accessing them. Please contact WHONDRS@pnnl.gov for more information. Please use the data package’s DOI to cite the data package. We ask that you email us at WHONDRS@pnnl.gov to let us know that you're using the data and acknowledge WHONDRS and the U.S. Department of Energy's Subsurface Biogeochemical Research program—which generously provides funding to WHONDRS—in your publications, proposals, presentations, etc. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. Note that the included hydrograph has a separate DOI that should also be cited. There is no obligation to include WHONDRS members as co-authors.

54 ENVIRONMENTAL SCIENCES↗

Custom NEON AOP reflectance mosaics and maps of shade masks, canopy water content

This mosaic of visible to shortwave infrared (VSWIR) data was derived from the assignable asset NEON AOP radiance data that was collected by LBNL’s Watershed Function SFA during the summer of 2018 (DOI: 10.15485/1617204). This atmospheric correction was completed to take into account site-specific terrain variability in the 334 km2 survey area centered around Crested Butte, CO. The atmospheric correction was completed using ACORN atmospheric correction software executed on 200 x 200 pixel kernels rather than line by line in order to capture local flight altitude conditions. Manual cloud delineation removed any small shaded areas that occurred within the data collection areas. Mosaics were developed based on preference for days that were in close timing proximity to the coincident ground campaign and with mosaicing criteria that minimized the angle between the sun and the sensor to retrieve the most consistent reflectance (min_phase_refl_tiled). Finally, we generated shade masks based on the geometry between the sun angle at time of flight, the ground surface, and the sensor. Here we provide the orthomosaiced estimated reflectance data (min_phase_refl_tiled.tif), canopy water content (wtrl), estimated atmospheric water vapor (wtrv), the observational data (obs) for this particular mosaic, the estimated visibility (vis), shade masks derived from the digital surface elevation model (shade) and the digital terrain model (shade_tch) added to the canopy height model (DOI: 10.15485/1617203), and a wavelength metadata file. Each image file is provided as a GeoTiff with internal tiling and LZW compression. These data can also be found on Google Earth Engine for extraction, download, and analysis of smaller extents (Google Earth Engine data is linked in external link table).

2018 NEON and 2025 CHESS Campaigns↗

KCMP Minnesota Tall Tower Carbon Dioxide Data 2007-2019

This data set contains carbon dioxide concentration values and supporting metadata information measured at a tall tower (KCMP radio station, 244 meters) site near St. Paul, Minnesota, USA. The data package includes a text file containing hourly continuous carbon dioxide concentration measurements from 2007 to 2019, including raw, de-spiked, and gap filled data. Carbon dioxide concentrations were measured at approximately 100 meters using tunable diode laser spectroscopy. The instrumentation was maintained at the base of the tall tower in a temperature-controlled building. This data was collected to track and improve the understanding of carbon dioxide levels over a twelve year period for the region.

54 ENVIRONMENTAL SCIENCES↗

Soil moisture and temperature data along the northeast facing hillslope at the Lower Montane site in the East River Watershed, Colorado

Soil moisture, temperature and electrical conductivity have been monitored with 5TE sensors (Decagon Inc.) located at 10 and 50 cm depth at 4 different locations along the northeast-facing slope at the Lower Montane site in the East River Watershed, Colorado from Oct 2016 to Oct 2018. The purpose of this data is to inform hydrobiogeochemical analyses for the Watershed Function Scientific Focus Area (SFA). The data is reported in 4 csv files labeled their by location identifiers (ER-SMN1-5) and location metadata is provided in SM_loc.csv. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

54 ENVIRONMENTAL SCIENCES↗

Columbia River Surface Water and Pore Water Unaligned FTICR-MS Data Associated with “Using Community Assembly Metrics from Metacommunity Ecology to Understand Environmental Metabolomes”

Surface water and pore water samples were collected at five sites along a shoreline transect of the Columbia River, southeastern WA, USA in 2017. This dataset is comprised of (1) high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) and (2) a metadata csv file. The FTICR-MS files are .xml, and the data package includes 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. The data are associated with the publication “Using community assembly metrics from metacommunity ecology to understand environmental metabolomes” that will be published in Nature Communications (Danczak et al.). The study aimed to investigate gaps in understanding the spatiotemporal organization of environmental metabolomes to improve the ability to predict ecosystem function. Associated sequencing data will be published via NCBI. The access information for NCBI and the publication DOI will be added to this abstract when they are available. Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.

54 ENVIRONMENTAL SCIENCES↗