High pressure and low temperature diffraction data of polycrystalline Pyrazine-d4
Raw data, and temperature correction file for pyrazine data.
36 MATERIALS SCIENCE↗
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Leaf temperature raw data, 2015 - 2017, at Manaus, Brazil
This data package contains raw leaf surface temperature data from the NGEE Tropics K34 tower site on a plateau near Manaus, Brazil, including automated and manually collected time series data on leaf surface temperature (thermocouples, IR radiometer, thermocamera). Leaf surface temperature (LST) was determined throughout diurnal periods using individual type T thermocouples (Omega Engineering) on 8 individual leaves of a single tree. Mature leaves at the same height and general area near the tower were selected. LST measurements were taken every 15 s and recorded on a field portable self-powered data logger (OM-CP-OCTTEMP-A, Omega Engineering). Measurements were stopped in the case of a storm or rain which can remove the attached thermocouple wires from the leaf due to large wind-driven branch movements. Included in the attached zip file are six folders: three with LST data in Excel and CSV file formats from both the K34 and B34 towers, one folder with data logger configuration programs that were used for data collection, a fifth folder with PDF files of manuals for instruments used and a final folder with two Excel metadata files. See dataset references for associated metadata package. This dataset replaces the leaf surface temperature data of two retired packages, http://dx.doi.org/10.15486/ngt/1507764 and http://dx.doi.org/10.15486/ngt/1507767
54 ENVIRONMENTAL SCIENCES↗
Data for: Patel et al. Carbon flux estimates are sensitive to data source: A comparison of field and lab temperature sensitivity data
This dataset contains data and code used for the paper "Carbon flux estimates are sensitive to data source: A comparison of field and lab temperature sensitivity data" [DOI COMING SOON]A large literature exists on mechanisms driving soil production of the greenhouse gases CO2 and CH4. Measurements of these gases’ fluxes are often performed using closed-chamber incubations in the laboratory or in situ, i.e., in the field. Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. It is crucial to understand the magnitude and reasons for any differences, as these data are used to parametrize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we specifically examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO2 and CH4 measurements. We use Q10 of greenhouse gas flux (temperature sensitivity) for our analyses, because of the ubiquity of this metric in biological and Earth system sciences and its importance to many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q10 values calculated from lab-based measurements of CO2 fluxes, because lab experiments explore extremes rarely seen in situ, and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q10, these values showed almost identical distributions across laboratory (n = 1110) and field (n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH4 Q10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata. This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/field_lab_q10 (DOI: 10.5281/zenodo.7106554).
54 ENVIRONMENTAL SCIENCES↗
JHU Baltimore iButton data
Temperature and Relative Humidity data from a low cost sensor ("iButton") network deployed in Baltimore in summer 2015, 2016, 2017, 2021, and 2022. Initial deployment described in Scott, A., Zaitchik, B., Waugh, D., O'Meara, K. 2017. Intra-Urban temperature variability in Baltimore. Journal of Applied Meteorology and Climatology, 56(1): 159-171. doi: 10.1175/JAMC-D-16-0232.1
applied meteorology↗
Soil Temperature Sensor Data, May - December 2024, Five sites in Knoxville, Tennessee
This dataset contains surface soil temperature measurements from five urban parks in Knoxville: Cumberland Estates Park (CE), Socially Equal Energy Efficient Development (SD), West View Park (WV), Victor Ashe Park (VA), and West Hills Park (WH). The dataset comprises 29 Excel (.xlsx) and Comma-Separated Values (.csv) files documenting soil temperature recorded by six HOBO Pendant MX Water Temperature Data Loggers at each site, except for CE, which has five sensors. Each logger was installed at a depth of 10 inches and positioned approximately 3 to 6 feet from the weather station at each site. To open both csv and xlsx files, users can utilize spreadsheet applications such as Microsoft Excel, Google Sheets, LibreOffice Calc, and Apple Numbers. This dataset is part of a broader study examining the effects of soil moisture and plant evapotranspiration on ambient temperature and relative humidity across multiple urban parks in Knoxville, Tennessee.
EARTH SCIENCE > LAND SURFACE > SOILS↗
Carbon flux estimates are sensitive to data source: a comparison of field and lab temperature sensitivity data
Abstract A large literature exists on mechanisms driving soil production of the greenhouse gases CO 2 and CH 4 . Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. These data are used to parameterize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO 2 and CH 4 measurements. We use Q 10 of greenhouse gas flux (temperature sensitivity) for our analyses because this metric is commonly used in biological and Earth system sciences and is an important parameter in many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q 10 values calculated from lab-based measurements of CO 2 fluxes, because lab experiments explore extremes rarely seen in situ , and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q 10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q 10 , these values showed almost identical distributions across laboratory ( n = 1110) and field ( n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH 4 Q 10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata.
54 ENVIRONMENTAL SCIENCES↗
Faraday: A High-temperature Electrolysis Data Explorer
Faraday is a high-temperature electrolysis data visualization tool, which reveals the performance of various button cells under test conditions. These tests and the resulting analytics on their data constitute a state of the industry as the US Department of Energy pushes for the production of hydrogen. Faraday leverages the Idaho National Laboratory's DeepLynx data warehouse to standardize and query button cell data. Faraday programmatically accesses this data in DeepLynx by traversing the schema, represented by a custom ontology. The user interface queries DeepLynx for timeseries data associated with specific button cells in the warehouse, and renders them using JavaScript charts. Additional charting and data analysis techniques are made possible by an auxiliary Python server.
Woodruff, Nathan↗
Advanced Model Development for Large Eddy Simulation of Oxy-Combustion and Supercritical Carbon Dioxide Power Cycles
A joint experimental and numerical study is performed to observe the characteristics of a supercritical carbon dioxide turbulent mixing layer in the presence of strong nonlinearities in the thermodynamic and transport properties. A bespoke experimental setup is designed and employed for this purpose and provides insight into macroscopic mixing behavior. The mixing is experimentally observed using two techniques: shadowgraphy and spontaneous Raman scattering. Qualitative and quantitative intensity fields obtained via these techniques yield instantaneous and mean density data. Spanwise temperature data is also collected using analogue resistance temperature detectors. These measurements are used to quantify the level of mixed material within the field. The experimental data are supplemented by a companion high-fidelity numerical study. The numerical results are obtained through fully resolved, three-dimensional direct numerical simulation. The numerical dataset permits observation of the near-field mixing characteristics, which are difficult to measure experimentally due to the rapid dynamics and sharp thermophysical gradients in this area. Qualitative field visualizations are presented, followed by quantitative mixed material results and observations regarding thermodynamic property trends at select locations within the field. One-dimensional spectra of the turbulent kinetic energy and solenoidal dissipation are provided to observe the spectral characteristics of the flow. Reynolds stress anisotropy is analyzed graphically through anisotropy invariance maps (Lumley triangles). The mixing quantification, spectral data and anisotropy analysis of a flow at these thermodynamic conditions represent the main outcomes of the work.
20 FOSSIL-FUELED POWER PLANTS↗
Using pyrometry to identify porosity in additively manufactured structures
A method and apparatus for identifying porosity in a structure made by an additive manufacturing process in which a laser is scanned across layers of material to form the structure. Pyrometry data comprising images of the layers acquired during additive manufacturing of the structure is received. The pyrometry data is used to generate temperature data comprising estimated temperatures of points in the layers in the images of the layers. The temperature data is used to identify shapes fit to high temperature areas in the images of the layers. Conditions of the shapes fit to the high temperature areas in the images of the layers are identified. Outlier shapes are identified in the shapes fit to the high temperature areas in the images of the layers using the conditions of the shapes.
Mitchell, John A.↗
2-D Surface Temperature Simulation Data and Matlab Scripts
SAND2023-07249O The 2-D Surface Temperature Simulation Data and Matlab software can estimate 2D temperature fields from electrical measurements along the edge of the 2D domain. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Sjoberg, Carl Magnus↗
Utah FORGE: Well 16B(78)-32 Distributed Temperature Sensing Data from April and May 2024
This dataset includes Neubrex Energy Services fiber optic distributed temperature sensing (DTS) data from well 16B(78)-32 during stimulation and circulation, including interaction with well 16A(78)-32, during April and May 2024. The DTS data are stored in HDF5 file format and are accompanied by a PowerPoint report on the study. All times in this dataset are in UTC. Depths are in MD relative to Kelly Bushing Height, and temperatures are in degrees Fahrenheit. All DTS measurements were made using a Yokogawa 3000DTSX Distributed Temperature Sensing Interrogator Unit, with a spatial sampling interval of 3.28 feet and a temporal sampling rate of 129 seconds. The third-party Pressure-Temperature Gauge data should be used with caution after April 20, 2024, as its performance is not considered reliable beyond this date.
15 GEOTHERMAL ENERGY↗
Distributed Thermal Response Multi-Source Modeling to Evaluate Heterogeneous Subsurface Properties
A thorough assessment of thermal properties in heterogeneous subsurface is necessary in design of low-temperature borehole heat exchangers (BHEs). For this study, a distributed thermal response test (DTRT), which combines distributed temperature sensing (DTS) with a conventional thermal response test (TRT), was conducted in a U-bend geothermal loop installed in an open borehole at the University of Illinois at Urbana-Champaign to estimate thermal properties by analyzing the thermal response of different geologic materials while applying a constant heat input rate. Fiber-optic cables in the DTRT were deployed both inside the U-bend geothermal loop and in the center of the borehole to improve the accuracy of calculated heat-loss rates and borehole temperature profile measurements. To assess the subsurface thermal conductivity during the heating phase of the DTRT, a single-source model and a multi-source model, both based on the infinite line source method, were developed using the borehole temperature data and temperatures inside and along the outside of the loop, separately. The two models returned similar thermal conductivity values. The multi-source modeling has the advantage of predicting the thermal conductivity of heterogeneous geologic materials from borehole temperature profiles during the DTRT heating phase. Additionally, based on the distributed thermal conductivity measured in the borehole, estimates were made for both radial thermal impacts and the rate of heat loss in the BHE.
58 GEOSCIENCES↗
AGR-5/6/7 Raw Thermocouple Data
This is temperature data from the AGR-5/6/7 experiment. This data will support a conference paper (INL/CON-20-60776) and needs to be shared with co-authors and other collaborators.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019
This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.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).
54 ENVIRONMENTAL SCIENCES↗
A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature: Supporting Data
This dataset was used to assess the potential of a Distributed Temperature Profiling System developed and presented in the article named "A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature" and submitted to Cryosphere. There are three comma-delimited data files (.csv). Each of them contains snow or soil temperature with times (UTC) in the first column and temperature at various vertical distance from the ground surface (positive means in air/snow) or below the ground surface (negative means in soil). The measurements were acquired every 15 minutes. Data collected at the East River, Colorado site with two probes: 1) measuring air/snow temperature from 1.1 m above the ground surface to the ground surface (with 5 or 10 cm spacing between sensors) and 2) measuring soil temperature from the ground surface to 0.7 m depth (with 5 or 10 cm spacing between sensors). Data collected at the Teller road (mile 27) site near Nome, Alaska with one probe: measuring soil temperature from 5 cm above the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors). Additional metadata included in *.csv and *.pdf files. NGEE Arctic Project Summary: 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).
54 ENVIRONMENTAL SCIENCES↗
Stomatal conductance and leaf temperature raw data from Aug 2016-Nov 2017 at the B34 tower in Manaus, Brazil
This data package contains raw data from stomatal conductance and leaf temperature measurements from the B34 tower in Manaus, Brazil. The attached zip file contains two data files and two metadata files. Additional metadata, such as site information and equipment manuals, are included in the data package listed under Dataset Reference(s). Contact israelmdt@gmail.com if you need to use this dataset for additional information.
54 ENVIRONMENTAL SCIENCES↗
Stomatal conductance and leaf temperature raw data from Aug 2016-Nov 2017 at the B34 tower in Manaus, Brazil
This data package contains raw data from stomatal conductance and leaf temperature measurements from the B34 tower in Manaus, Brazil. The attached zip file contains two data files and two metadata files. Additional metadata, such as site information and equipment manuals, are included in the data package listed under Dataset Reference(s). Contact israelmdt@gmail.com if you need to use this dataset for additional information.
54 ENVIRONMENTAL SCIENCES↗
Stomatal conductance and leaf temperature raw data from Aug 2016-Nov 2017 at the K34 tower in Manaus, Brazil
These are raw data from stomatal conductance and leaf temperature measurements from the NGEE-Tropics K34 tower in Manaus, Brazil. The attached zip file contains two data files and two metadata files. Related data packages, including additional metadata such as site information and equipment manuals, are included in the data package listed under Dataset Reference(s). Contact israelmdt@gmail.com if you need to use this dataset for additional information.
54 ENVIRONMENTAL SCIENCES↗