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NASA NTRS1993

Non-invasive optical detection of glucose in cell culture nutrient medium

The objective of the proposed research was to begin the development of a non-invasive optical sensor for measuring glucose concentration in the output medium of cell cultures grown in a unique NASA bioreactor referred to as an integrated rotating-wall vessel (IRWV). The input, a bovine serum based nutrient media, has a known glucose concentration. The cells within the bioreactor digest a portion of the glucose. Thus, the non-invasive optical sensor is needed to monitor the decrease in glucose due to cellular consumption since the critical parameters for sustained cellular productivity are glucose and pH. Previous glucose sensing techniques have used chemical reactions to quantify the glucose concentration. Chemical reactions, however, cannot provide for continuous, real time, non-invasive measurement as is required in this application. Our effort while in the fellowship program was focused on the design, optical setup, and testing of one bench top prototype non-invasive optical sensor using a mid-infrared absorption spectroscopy technique. Glucose has a fundamental vibrational absorption peak in the mid-infrared wavelength range at 9.6 micron. Preliminary absorption data using a CO2 laser were collected at this wavelength for water based glucose solutions at different concentrations and one bovine serum based nutrient medium (GTSF) with added glucose. The results showed near linear absorption responses for the glucose-in-water data with resolutions as high at 108 mg/dl and as low as 10 mg/dl. The nutrient medium had a resolution of 291 mg/dl. The variability of the results was due mainly to thermal and polarization drifts of the laser while the decrease in sensitivity to glucose in the nutrient medium was expected due to the increase in the number of confounders present in the nutrient medium. A multispectral approach needs to be used to compensate for these confounders. The CO2 laser used for these studies was wavelength tunable (9.2 to 10.8 micrometers), however, it was to unstable across wavelengths to test the multispectral approach. From this research, further NASA support was obtained to continue the work throughout the year in which a more stable light source will be used at smaller, near-infrared, wavelengths. It is anticipated that a more compact, non-invasive, optical glucose sensor will be realized which can be used with a bioreactor on future space shuttle missions. It is also anticipated that a multispectral optical sensor may be used to determine the concentration of other molecules needed within the NASA bioreactor, such as fructose and galactose.

Cote, Gerald L.↗

DOE OSTI2022

CO2 pipeline data catalog

This "Data Catalog" is an excel spreadsheet of collected and catalogued spatial and non-spatial public datasets in relevance to and support of CO2 transport (pipelines) infrastructure development and risk modeling. Includes data associated with CO2 sources, sinks, and transportation.

CO2↗

DOE OSTI2020

Subtask 1.5 – CO2 Injection Monitoring with an Optimized Scalable, Automated, Semipermanent Seismic Array

The scalable, automated, semipermanent seismic array (SASSA) method is a flexible and relatively cost-effective surface geophysical method for regular time-lapse monitoring of the movement of injected carbon dioxide (CO2) in a reservoir for CO2 enhanced oil recovery (EOR) or geologic CO2 storage operations. It has the advantages of a low-environmental-footprint while monitoring regions of a reservoir from the surface without the need for a regular grid distribution of receivers. Automated data collection is possible. As only time-lapse amplitude changes at the reservoir level due to CO2 movement within the reservoir are monitored, the turnaround time to deliver results from the SASSA method can be short, without the need for long, time-consuming data-processing workflows. As data is collected and processed, incremental information can be provided to the field operator. The Energy & Environmental Research Center (EERC) conducted a SASSA field test from September 2018 to November 2020 in a portion of the Bell Creek Field in Montana, which implemented new CO2 EOR field activities during the study period. Lessons learned from a proof-of-concept study were incorporated to improve the data quality of the SASSA method and demonstrate the viability of the technology. The EERC implemented several enhancements to improve data quality, including 1) an iterative survey design, which allowed placing the receivers in strategic locations where the movement of the CO2 in the reservoir could be tracked with minimum interference by the cultural noise in the study area; 2) the use of powerful seismic sources in the form of surface orbital vibrators, and 3) data acquisition during optimal periods. History-matched reservoir simulation was performed to predict gas saturation and pressure response induced by CO2 injection in the study area. The results were compared with the SASSA-measured responses to CO2 injection as a partial validation technique. A match between the two methods was observed for most of the SASSA points predicted to have intersected a CO2 saturation change. The validated results provide confidence that the SASSA method can be used independently as a CO2 saturation monitoring technique. As data are collected and processed, incremental information can be provided to the field operator. The critical components of the SASSA workflow for a successful application of the method are the following: Iterative survey design with information about CO2 injection activities from the oilfield operator. A detailed CO2 injection plan is the key driver to select the strategic monitoring location of the SASSA sensors. After this information is incorporated in the initial distribution of sources and receivers in the study area, high-resolution satellite images are used to identify ground locations not affected by cultural noise sources, such as power lines, pipelines/flow lines, or roadways. In the next iteration of the survey design, a scouting trip to the study area is needed to understand more details of the noise sources identified in the previous step and the intensity of the field activities that can also generate noise during the monitoring. Integrating the information from the scouting trip into the survey design to select the optimum source and receiver locations is the final step. Noise attenuation. The variety of noise types during seismic monitoring of an oil field is enormous. Tailored noise characterization and processing at a node-by-node level can enhance the performance and sensitivity of the SASSA technique. Future advancements that could improve the efficiency and application of the SASSA technology include: Gaining a better understanding of the noise field produced by the seismic source to aid the choice of receiver location. Surface noise from the source can overwhelm the small signal changes due to CO2 that the SASSA method measures. Improved data-processing workflow to automatically analyze and adapt to dynamic noise conditions associated with industrial settings. This subtask was funded through the EERC–DOE Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE- FE0024233.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Moisture Effect on Chitin Decomposition Biogeochemistry

This dataset contains data files for multiple measurements of sample biogeochemistry and function collected for the Soils SFA Chitin Decomposition project in task 2.2. Samples were generated from soil incubated under different moisture levels, with and without chitin. Each sheet in the file refers to the preprocessed data collected. Sheet 1 "Respiration" measures CO2 production daily for the course of the incubation. Sheet 2 "Biomass" contains the microbial biomass and salt extractable measurements for carbon and nitrogen. Sheet 3 "Chitin" is for HPLC measured chitin from each sample. Sheet 4 "Extracellular Enzyme Assays" records the level of activity for several enzyme assays. Sheet 5 "Enzyme Kinetics" measures degradation of substrate over time for all samples.

Reichart, Nicholas J [Pacific Northwest National L↗

DOE OSTI2024

SPRUCE Xylem Native Embolism and Leaf Traits of Picea mariana and Larix laricina, 2019

This data set contains measurements of native embolism in branch xylem and associated branch and leaf traits from Picea mariana (Black Spruce) and Larix laricina (Tamarack) from September-October 2019 at the SPRUCE experiment (Hanson et al. 2017). Data are presented in one comma-separated (*.csv) file. Native embolism, a measurement of in-situ embolism in the xylem tissue that blocks water movement, measurements were conducted at the end of the growing season on cut branches using the hydraulic pipette method (see Peters et al. 2023 for full method). In short, branch segments were connected to hydraulic apprentice and flow rates of perfusion liquid were measured using graduated pipettes and stopwatch. After initial conductance measurements, branch segments were flushed using vacuum infiltration and hydraulic conductance was remeasured to calculate the percent loss in conductance due to embolism (PLC). Three branch segments (distal, middle, and proximal) were measured from each branch representing different diameters size classes. This dataset also contains leaf area associated with each measured branch segment, calculate leaf mass per area (LMA), sapwood specific conductivity (Ks), leaf area specific conductivity (Kl) and the sapwood area to leaf area ratio (Huber value). Measurements were made on mature trees from all ten treatment enclosures. One branch from each of five trees per species were used from each enclosure where available. Some plots do not contain five individual Larix laricina, in which case all available trees were sampled. All measurements were conducted in late September/early October 2019, at the end of growing season but before Larix laricina needle senescence. There are 10 experimental plots at SPRUCE: five temperature treatments (+0, +2.25, +4.5, +6.75, +9°C) at ambient CO2, and the same five temperature treatments at elevated CO2 (+500 ppm). These data were collected after the treatments had been running in full for three years, meaning much of the material measured was grown under treatment conditions.

Huber value↗

DOE OSTI2023

Duke Forest FACE (FACTS-I): Plant and Soil Response Data

This dataset describing the responses of plant and soil pools and fluxes to elevated atmospheric CO2 concentration and increased nitrogen supply was collected from Duke Forest Free Air CO2 Enrichment (FACE) – Forest-Atmosphere Carbon Transfer and Storage (FACTS-I) experiment from 1996 to 2012. The dataset includes data files for allometry (diameter at breast height, tree height, and height to live crown base), leaf area index, biomass (stem, branch, foliage, and root biomass, tree density, and basal area), net primary productivity (stem, branch, foliage, reproductive, and coarse root NPP), sap flux density, soil CO2 efflux, and stem temperature. Data files were formatted as .csv (Microsoft Excel or other spreadsheet programs can be used to read the format) and file descriptions, including variable name, unit, and data range, can be found in ‘FileDescription_[data_name].txt’ files. The Duke FACE experiment was in a loblolly pine (Pinus taeda L.) plantation established in 1983. Naturally regenerated broadleaved species including sweetgum (Liquidambar styraciflua L.) and tulip poplar (Liriodendron tulipifera L.), mostly in the overstory, and winged elm (Ulmus alata Michx.) and red maple (Acer rubrum L.) were common in the understory. The FACE experiment commenced with two plots (plots 7-8) in 1994 (Oren et al. 2001), with six additional plots (plots 1-6) coming online on 27 August 1996. CO2 enrichment was terminated on 31 October 2010 and post-enrichment data collection continued through 2012. Complete fertilization was applied annually to half of plots 7-8 from 1998 to 2004. The nutrient addition experiment expanded to half of plots 1-6 with a common protocol of N-fertilization in 2005 and continued until 2012. The levels of treatment in this dataset were expressed as ambient CO2 (AMB) or elevated CO2 (ELE) for CO2 treatment and control soil (CONT) or fertilized soil (FERT) for N treatment, respectively.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

BOREAS TE-5 CO2 Concentration and Stable Isotope Composition

The BOREAS TE-5 team collected measurements in the NSA and SSA on gas exchange, gas composition, and tree growth. This data set contains measurements of the concentration and stable carbon (C-13/C-12 and oxygen (O-18/O-16) isotope ratios of atmospheric CO2 in air samples collected at different heights within forest canopies. The data were collected to determine the influence of photosynthesis and respiration by the forest ecosystems on the concentration and stable isotope ratio of atmospheric CO2 These measurements were collected at the SSA during each 1994 IFC at OJP, OBS, and OA sites. Measurements were also collected at the NSA during each 1994 IFC at the OJP, T6R5S TE UBS, and T2Q6A TE OA sites. The stable isotope ratios are expressed using standard delta notation and in units of per mil. The isotope ratios are expressed relative to the international standard, PDB, for both carbon and oxygen samples. The data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2000

BOREAS TGB-1/TGB-3 NEE Data over the NSA Fen

The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-1) and TGB-3 teams collected several data sets that contributed to understanding the measured trace gas fluxes over sites in the Northern Study Area (NSA). This data set contains Net Ecosystem Exchange of CO2 (NEE) measurements collected with chambers at the NSA fen in 1994 and 1996. Gas samples were extracted approximately every 7 days from chambers and analyzed at the NSA lab facility. The data are provided in tabular ASCII files.

Bellisario, Lianne↗

NASA NTRS2000

BOREAS TE-5 Tree Ring and Carbon Isotope Ratio Data

The BOREAS TE-5 team collected several data sets to investigate the vegetation-atmosphere CO2 and H2O exchange processes. These data include tree ring widths and cellulose carbon isotope data from coniferous trees collected at the BOREAS NSA and SSA in 1993 and 1994 by the BOREAS TE-5 team. Ring width data are provided for both Picea mariana and Pinus banksiana. The carbon isotope data are provided only for Pinus banksiana. The data are provided in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS2000

BOREAS TGB-12 Rn-222 Activity Data over the NSA

The BOREAS TGB-12 team made measurements of soil carbon inventories, carbon concentration in soil gases, and rates of soil respiration at several sites to estimate the rates of carbon accumulation and turnover in each of the major vegetation types. Sampling strategies for soils were designed to take advantage of local fire chronosequences, so that the accumulation of carbon in regrowing mosses could be determined. All the data are used to: (1) calculate the inventory of carbon and nitrogen in moss and mineral soil layers at NSA sites, (2) determine the rates of input and turnover (using both accumulation since the last stand-killing fire and radiocarbon data), and (3) link changes in soil respiration rate to shifts in the C-14 content of soil CO2 to determine the average "age" respired CO2 . These Rn-222 activity data were collected from 15-Nov-1993 to 16-Aug-1994 over the NSA sites. They are useful for determining the rate of gas exchange between soil and the overlying atmosphere. The data in this data set are stored in tabular ASCII files.

Trumbore, Susan↗

NASA NTRS2000

BOREAS TGB-12 Rn-222 Flux Data over the NSA

The BOREAS TGB-12 team made measurements of soil carbon inventories, carbon concentration in soil gases, and rates of soil respiration at several sites to estimate the rates of carbon accumulation and turnover in each of the major vegetation types. Sampling strategies for soils were designed to take advantage of local fire chronosequences, so that the accumulation of carbon in new moss growth could be determined. All the data are used to 1) calculate the inventory of carbon and nitrogen in moss and mineral soil layers at NSA sites, 2) determine the rates of input and turnover (using both accumulation since the last stand-killing fire and radiocarbon data), and 3) link changes in soil respiration rate to shifts in the C-14 content of soil CO2 to determine the average "age" respired CO2. These Rn-222 flux data were collected from 15-Nov-1993 to 16-Aug-1994 over the NSA sites. The data in this data set are stored in tabular ASCII files.

Hall, Forrest G.↗

NASA NTRS2011

Evaluation of Convective Transport in the GEOS-5 Chemistry and Climate Model

The NASA Goddard Earth Observing System (GEOS-5) Chemistry and Climate Model (CCM) consists of a global atmospheric general circulation model and the combined stratospheric and tropospheric chemistry package from the NASA Global Modeling Initiative (GMI) chemical transport model. The subgrid process of convective tracer transport is represented through the Relaxed Arakawa-Schubert parameterization in the GEOS-5 CCM. However, substantial uncertainty for tracer transport is associated with this parameterization, as is the case with all global and regional models. We have designed a project to comprehensively evaluate this parameterization from the point of view of tracer transport, and determine the most appropriate improvements that can be made to the GEOS-5 convection algorithm, allowing improvement in our understanding of the role of convective processes in determining atmospheric composition. We first simulate tracer transport in individual observed convective events with a cloud-resolving model (WRF). Initial condition tracer profiles (CO, CO2, O3) are constructed from aircraft data collected in undisturbed air, and the simulations are evaluated using aircraft data taken in the convective anvils. A single-column (SCM) version of the GEOS-5 GCM with online tracers is then run for the same convective events. SCM output is evaluated based on averaged tracer fields from the cloud-resolving model. Sensitivity simulations with adjusted parameters will be run in the SCM to determine improvements in the representation of convective transport. The focus of the work to date is on tropical continental convective events from the African Monsoon Multidisciplinary Analyses (AMMA) field mission in August 2006 that were extensively sampled by multiple research aircraft.

Pickering, Kenneth E.↗

NASA NTRS2019

Potential Improvements in Global Carbon Flux Estimates from a Network of Laser Heterodyne Radiometer Measurements of Column Carbon Dioxide

We present observing system simulation experiments (OSSEs) to evaluate the impact of a proposed network of ground-based miniaturized laser heterodyne radiometer (mini-LHR) instruments that measure atmospheric column-averaged carbon dioxide (XCO2) with a 1 ppm precision. A particular strength of this passive measurement approach is its insensitivity to clouds and aerosols due to its direct sun pointing and narrow field of view (0.2°). Developed at the NASA Goddard Space Flight Center (GSFC), these portable, low-cost mini-LHR instruments were designed to operate in tandem with the sun photometers used by the AErosol RObotic NETwork (AERONET). This partnership allows us to leverage the existing framework of AERONET's global ground network of more than 500 sites as well as providing simultaneous measurements of aerosols that are known to be a major source of error in retrievals of XCO2 from passive nadir-viewing satellite observations. We show, using the global 3-D GEOS-Chem chemistry transport model, that a deployment of 50 mini-LHRs at strategic (but not optimized) AERONET sites significantly improves our knowledge of global and regional land-based CO2 fluxes. This improvement varies seasonally and ranges 58%–81% over southern lands, 47%–76% over tropical lands, 71%–92% over northern lands, and 64%–91% globally. We also show significant added value from combining mini-LHR instruments with the existing ground-based NOAA flask network. Collectively, these data result in improved a posteriori CO2 flux estimates on spatial scales of ∼10 km2, especially over North America and Europe, where the ground-based networks are densest. Our studies suggest that the mini-LHR network could also play a substantive role in reducing carbon flux uncertainty in Arctic and tropical systems by filling in geographical gaps in measurements left by ground-based networks and space-based observations. A realized network would also provide necessary data for the quinquennial global stock takes that form part of the Paris Agreement.

Palmer, Paul I.↗

NASA NTRS1992

Spatial and temporal variations of the fluxes of carbon dioxide and sensible and latent heat over the FIFE site

Airborne measurements of flux densities of carbon dioxide CO2, sensible heat, and latent heat (H2O) obtained over the First ISLSCP Field Experiment (FIFE) site during three intensive field campaigns in 1987 and one in 1989 are examined to characterize the spatial and temporal variations of CO2 and energy transfer processes. These data were collected by the National Research Council Twin Otter using low-level flight patterns, all flown at constant pressure altitude during relatively clear days. The spatial variations are larger in 1989 than in 1987 and a higher correlation is observed between the fluxes and the surface features. The temporal patterns are easier to characterize with the relatively homogeneous situation of 1987. Functional relationships obtained between fluxes of CO2 and latent heat, CO2 fluxes and greenness index, latent heat fluxes and greenness index, and between sensible heat fluxes and surface air temperature differences are presented for one day in 1987 and one in 1989 as an example of the kind of information that can be obtained from grid flights at constant pressure altitude.

Desjardins, R. L.↗

DOE OSTI2021

Learning-based CO 2 concentration prediction: Application to indoor air quality control using demand-controlled ventilation

There have been increasing concerns over the air quality inside buildings as high levels of bio-effluents can cause nausea, dizziness, headaches, and fatigue to the people working in those spaces. First published in 2004 as Standard 62.1, ASHRAE Standard 62.2-2019 requires highly occupied spaces to implement heating, ventilation, and air conditioning (HVAC) that can dilute contaminants produced by occupants. In this regard, occupant-centric ventilation control has been regarded as an effective practice to maintain a satisfactory indoor air quality (IAQ) when dealing with highly variable occupancy environments. However, few established models in current literature and practice consider dynamic occupancy behavior and adaptive IAQ control. To address this gap, a dynamic indoor CO2 model is constructed using machine learning algorithms to forecast CO2concentrations across a range of forecasting horizons. Herein, we tuned and compared six state-of-the-algorithms—including Support Vector Machine, Ada Boost, Random Forest, Gradient Boosting, Logistic Regression, and Multilayer Perceptron. The algorithms’ performances are validated using CO 2 and historical meteorological data collected from a campus classroom with a variable occupancy rate. Simulation results showed that Multilayer Perceptron can strongly predict the volatile CO 2 behavior and also outperforms other algorithms in terms of accuracy. Furthermore, a control strategy capable of modeling and detecting dynamic patterns of CO 2 level is utilized to modulate the ventilation rate in real-time and also reduce the energy consumption. The proposed controller reduced the HVAC fan’s energy consumption by 51.4% and provide ventilation as needed per the ASHRAE standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2000

BOREAS TGB-3 CH4 and CO2 Chamber Flux Data over NSA Upland Sites

The BOReal Ecosystem-Atmosphere Study Trace Gas Biogeochemistry (BOREAS TGB-3) team collected methane and carbon dioxide (CH4, CO2) chamber flux measurements at the Northern Study Area (NSA) Fen, Old Black Spruce (OBS), Young Jack Pine (YJP), and auxiliary sites along Gillam Road and the 1989 burn site. Gas samples were extracted from chambers and analyzed at the NSA lab facility approximately every 7 days during May to September 1994 and June to October 1996. The data are provided in tabular ASCII files.

Savage, Kathleen↗

DOE OSTI2025

Greenhouse Rhizobox Experiment with Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry data, Seward Peninsula, Alaska, 2024

Data collected from a greenhouse rhizobox experiment (2024) using soils and plants collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by porewater samplers (rhizons). Gas data consists of CO2 and CH4 surface soil fluxes measured with an FTIR (Fourier-transformed infrared red) analyzer. Plant and root data consists of biomass, root length. This study is a part of 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).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2 and CH4?Description of the contents of this data package: Rhizobox2024_Data.csv: This dataset contains plant, water and gas data. No software is needed to utilize them.nga535_flmd.csv: The file contains file level metadatanga535.dd.csv: This file contains the data dictionaryMethods.pdf: This file contains the data collection methods

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Exploration Extravehicular Mobility Unit (xEMU) 11 Foot Vacuum Chamber Upgrades Test Results

The Exploration Extravehicular Mobility Unit (xEMU) uncrewed 11 foot vacuum chamber testing evaluated the capabilities of the 11 foot vacuum chamber facility to support advanced spacesuit testing. The government reference design xEMU spacesuit provided a high-fidelity test article to demonstrate 11 foot vacuum chamber capabilities which included: gas loading of the chamber at varying simulated metabolic rates and open loop suit abort operations, Intravehicular Activity (IVA) vacuum access, consumables recharge, IVA vehicle-provided thermal loop cooling, and IVA vehicle-provided power. To demonstrate the xEMU airlock operations transitioning from IVA to EVA conditions without a test subject in the suit, test support equipment was developed to remotely actuate both the Exploration, Servicing, and Cooling Umbilical (ESCU) and the vacuum access umbilical. This test also evaluated the performance of the Exploration Portable Life Support System (xPLSS) at vacuum conditions. Data was collected and analyzed for carbon dioxide (CO2) scrubbing performance of the Rapid Cycle Amine (RCA) swingbed, for thermal regulation performance of the Suit Water Membrane Evaporator (SWME), and for sensor performance across the xPLSS. This paper will detail the findings of the testing performed with these upgrades which discussed previously laid out in ICES-2025-342.

Robert F Marsch↗