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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Integrated Monitoring Volume: A Summary of Monitoring Studies Conducted in Niagaran Carbonate Pinnacle Reefs During Enhanced Oil Recovery with CO2

This introductory report to the Integrated Monitoring Volume provides an executive summary style overview of each of the monitoring methods deployed during the MRCSP Phase III Program. Each method is discussed in detail in a separate report that together with this Executive Summary comprise the Integrated Monitoring Volume.

BHG,DAS,Monitoring,PNC,VSP,borehole gravity,distri↗
NASA NTRS2020

Constraining Fossil Fuel CO2 Emissions from Urban Area Using OCO-2 Observations of Total Column CO2

Satellite observations of the total column dry-air CO2(XCO2) are expected to support the quantification and monitoring of fossil fuel CO2 (ffCO2) emissions from urban areas. We evaluate the utility of the Orbiting Carbon Observatory 2 (OCO-2) XCO2 retrievals to optimize whole-city emissions, using a Bayesian inversion system and high-resolution transport modeling. The uncertainties of constrained emissions related to transport model, satellite measurements, and local biospheric fluxes are quantified. For the first two uncertainty sources, we examine cities of different landscapes: “plume city” located in relatively flat terrain, represented by Riyadh and Cairo; “basin city” located in basin terrain, represented by Los Angeles (LA). The retrieved scaling factors of emissions and their uncertainties show prominent variabilities from track to track, due to the varying meteorological conditions and relative locations of the tracks transecting plumes. To explore the performance of multiple tracks in retrieving emissions, pseudo data experiments are carried out. The estimated least number of tracks required to constrain the total emissions for Riyadh (<10% uncertainty), Cairo (<10%), and LA (<5%) are 5, 8, and 7, respectively. Additionally, to evaluate the impact of biospheric fluxes on derivation of the ffXCO2 enhancements, we conduct simulations for Pearl River Delta metropolitan area. Significant fractions of local XCO2 enhancements associated with local biospheric XCO2 variations are shown, which potentially lead to biased estimates of ffCO2 emissions. We demonstrate that satellite measurements can be used to improve urban ffCO2 emissions with a sufficient amount of measurements and appropriate representations of the uncertainty components.

Xinxin Ye↗
NASA NTRS2010

Assessing the Health and Performance Risks of Carbon Dioxide Exposures

Carbon dioxide (CO2) is an anthropogenic gas that accumulates in spacecraft to much higher levels than earth-normal levels. Controlling concentrations of this gas to acceptable levels to ensure crew health and optimal performance demands major commitment of resources. NASA has many decades of experience monitoring and controlling CO2, yet we are uncertain of the levels at which subtle performance decrements develop. There is limited evidence from ground-based studies that visual disturbances can occur during brief exposures and visual changes have been noted in spaceflight crews. These changes may be due to CO2 alone or in combination with other known spaceflight factors such as increased intracranial pressure due to fluid shifts. Discerning the comparative contribution of each to performance decrements is an urgent issue if we hope to optimize astronaut performance aboard the ISS. Long-term, we must know the appropriate control levels for exploration-class missions to ensure that crewmembers can remain cooperative and productive in a highly stressful environment. Furthermore, we must know the magnitude of interindividual variability in susceptibility to the adverse effects of CO2 so that the most tolerant crewmembers can be identified. Ground-based studies have been conducted for many years to set exposure limits for submariners; however, these studies are typically limited and incompletely reported. Nonetheless, NASA, in cooperation with the National Research Council, has set exposure limits for astronauts using this limited database. These studies do not consider the interactions of spaceflight-induced fluid shifts and CO2 exposures. In an attempt to discern whether CO2 levels affect the incidence of headache and visual disturbances in astronauts we performed a retrospective study comparing average CO2 levels and the prevalence of headache and visual disturbances. Our goal is to narrow gaps in the risk profile for in-flight CO2 exposures. Such studies can provide no more than partial answers to the questions of environmental interactions, interindividual variability, and optimal control levels. Future prospective studies should involve assessment of astronaut well being using sophisticated measures during exposures to levels of CO2 in the range from 2 to 8 mmHg.

James, John T.↗
DOE OSTI2024

Machine Learning-Driven Quantification of CO2 Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO2 plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO2 injection metrics, this work aims to predict the temporal evolution of subsurface CO2 saturation plumes. The findings illustrate that machine learning can predict plume dynamics, revealing vertical clustering of microseismic events over distinct time periods within certain proximities to the injection well, consistent with an invasion percolation model. The buoyant CO2 plume partially trapped within sandstone intervals periodically breaches localized barriers or baffles, which act as leaky seals and impede vertical migration until buoyancy overcomes gravity and capillary forces, leading to breakthroughs along vertical zones of weakness. Between different unsupervised clustering techniques, K-Means and DBSCAN were applied and analyzed in detail, where K-means outperformed DBSCAN in this specific study by indicating the combination of the highest Silhouette Score and the lowest Davies–Bouldin Index. The predictive capability of machine learning models in quantifying CO2 saturation plume extension is significant for real-time monitoring and management of CO2 sequestration sites. The models exhibit high accuracy, validated against physical models and injection data from the IBDP, reinforcing the viability of CO2 geological sequestration as a climate change mitigation strategy and enhancing advanced tools for safe management of these operations.

Iyegbekedo, Ikponmwosa↗
DOE OSTI2024

Advanced Sensors for In-Situ Amine Degradation Monitoring in Post-Combustion Carbon Capture

In order to improve the long-term performance of post-combustion carbon capture technologies, improvements to the detection of solvent degradation or reduction in CO2 capture efficiency are necessary. A pair of sensors were deployed to the National Carbon Capture Center’s (NCCC) to monitor CO2 capture and solvent degradation. The CO2 sensors were located to measure before capture and after capture concentrations of CO2 to measure the capture efficiency of the solvent system. Amine degradation sensors were located at four locations along the main solvent lines corresponding to CO2 loading and temperature: hot rich, cold rich, hot lean, and cold lean. Experimental results from laboratory tests using the sensors are shown, along with prototype designs that were deployed to the field site.

Brister, Matthew↗
NASA NTRS2011

Application of Commercial Non-Dispersive Infrared Spectroscopy Sensors for Sub-Ambient Carbon Dioxide Detection

Monitoring carbon dioxide (CO2) concentration within a spacecraft or spacesuit is critically important to ensuring the safety of the crew. Carbon dioxide uniquely absorbs light at wavelengths of 3.95 micrometers and 4.26 micrometers. As a result, non-dispersive infrared (NDIR) spectroscopy can be employed as a reliable and inexpensive method for the quantification of CO2 within the atmosphere. A multitude of commercial-off-the-shelf (COTS) NDIR sensors exist for CO2 quantification. The COTS sensors provide reasonable accuracy so long as the measurements are attained under conditions close to the calibration conditions of the sensor (typically 21.1 C and 1 atm). However, as pressure deviates from atmospheric to the pressures associated with a spacecraft (8.0-10.2 PSIA) or spacesuit (4.1-8.0 PSIA), the error in the measurement grows increasingly large. In addition to pressure and temperature dependencies, the infrared transmissivity through a volume of gas also depends on the composition of the gas. As the composition is not known a priori, accurate sub-ambient detection must rely on iterative sensor compensation techniques. This manuscript describes the development of recursive compensation algorithms for sub-ambient detection of CO2 with COTS NDIR sensors. In addition, the basis of the exponential loss in accuracy is developed theoretically considering thermal, Doppler, and Lorentz broadening effects which arise as a result of the temperature, pressure, and composition of the gas mixture under analysis. As a result, this manuscript provides an approach to employing COTS sensors at sub-ambient conditions and may also lend insight into designing future NDIR sensors for aerospace application.

Swickrath, Michael J.↗
NASA NTRS2012

Application of Commercial Non-Dispersive Infrared Spectroscopy Sensors for Sub-Ambient Carbon Dioxide Detection

Monitoring carbon dioxide (CO2) concentration within a spacecraft or spacesuit is critically important to ensuring the safety of the crew. Carbon dioxide uniquely absorbs light at wavelengths of 3.95 micrometers and 4.26 micrometers. As a result, non-dispersive infrared (NDIR) spectroscopy can be employed as a reliable and inexpensive method for the quantification of CO2 within the atmosphere. A multitude of commercial off-the-shelf (COTS) NDIR sensors exist for CO2 quantification. The COTS sensors provide reasonable accuracy as long as the measurements are attained under conditions close to the calibration conditions of the sensor (typically 21.1 C (70.0 F) and 1 atmosphere). However, as pressure deviates from atmospheric to the pressures associated with a spacecraft (8.0{10.2 pounds per square inch absolute (psia)) or spacesuit (4.1{8.0 psia), the error in the measurement grows increasingly large. In addition to pressure and temperature dependencies, the infrared transmissivity through a volume of gas also depends on the composition of the gas. As the composition is not known a priori, accurate sub-ambient detection must rely on iterative sensor compensation techniques. This manuscript describes the development of recursive compensation algorithms for sub-ambient detection of CO2 with COTS NDIR sensors. In addition, the source of the exponential loss in accuracy is developed theoretically. The basis of the loss can be explained through thermal, Doppler, and Lorentz broadening effects that arise as a result of the temperature, pressure, and composition of the gas mixture under analysis. This manuscript provides an approach to employing COTS sensors at sub-ambient conditions and may also lend insight into designing future NDIR sensors for aerospace application.

Swickrath, Michael J.↗
NASA NTRS2016

Consistent Evaluation of ACOS-GOSAT, BESD-SCIAMACHY, CarbonTracker, and MACC Through Comparisons to TCCON

Consistent validation of satellite CO2 estimates is a prerequisite for using multiple satellite CO2 measurements for joint flux inversion, and for establishing an accurate long-term atmospheric CO2 data record. Harmonizing satellite CO2 measurements is particularly important since the differences in instruments, observing geometries, sampling strategies, etc. imbue different measurement characteristics in the various satellite CO2 data products. We focus on validating model and satellite observation attributes that impact flux estimates and CO2 assimilation, including accurate error estimates, correlated and random errors, overall biases, biases by season and latitude, the impact of coincidence criteria, validation of seasonal cycle phase and amplitude, yearly growth, and daily variability. We evaluate dry-air mole fraction (X(sub CO2)) for Greenhouse gases Observing SATellite (GOSAT) (Atmospheric CO2 Observations from Space, ACOS b3.5) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) (Bremen Optimal Estimation DOAS, BESD v2.00.08) as well as the CarbonTracker (CT2013b) simulated CO2 mole fraction fields and the Monitoring Atmospheric Composition and Climate (MACC) CO2 inversion system (v13.1) and compare these to Total Carbon Column Observing Network (TCCON) observations (GGG2012/2014). We find standard deviations of 0.9, 0.9, 1.7, and 2.1 parts per million vs. TCCON for CT2013b, MACC, GOSAT, and SCIAMACHY, respectively, with the single observation errors 1.9 and 0.9 times the predicted errors for GOSAT and SCIAMACHY, respectively. We quantify how satellite error drops with data averaging by interpreting according to (error(sup 2) equals a(sup 2) plus b(sup 2) divided by n (with n being the number of observations averaged, a the systematic (correlated) errors, and b the random (uncorrelated) errors). a and b are estimated by satellites, coincidence criteria, and hemisphere. Biases at individual stations have year-to-year variability of 0.3 parts per million, with biases larger than the TCCON predicted bias uncertainty of 0.4 parts per million at many stations. We find that GOSAT and CT2013b under-predict the seasonal cycle amplitude in the Northern Hemisphere (NH) between 46 and 53 degrees North latitude, MACC over-predicts between 26 and 37 degrees North latitude, and CT2013b under-predicts the seasonal cycle amplitude in the Southern Hemisphere (SH). The seasonal cycle phase indicates whether a data set or model lags another data set in time. We find that the GOSAT measurements improve the seasonal cycle phase substantially over the prior while SCIAMACHY measurements improve the phase significantly for just two of seven sites. The models reproduce the measured seasonal cycle phase well except for at Lauder_125HR (CT2013b) and Darwin (MACC). We compare the variability within 1 day between TCCON and models in June-July-August; there is correlation between 0.2 and 0.8 in the NH, with models showing 10-50 percent the variability of TCCON at different stations and CT2013b showing more variability than MACC. This paper highlights findings that provide inputs to estimate flux errors in model assimilations, and places where models and satellites need further investigation, e.g., the SH for models and 45-67 degrees North latitude for GOSAT and CT2013b.

ACOS-GOSAT↗
NASA NTRS2014

Quantifying the Observability of CO2 Flux Uncertainty in Atmospheric CO2 Records Using Products from Nasa's Carbon Monitoring Flux Pilot Project

NASAs Carbon Monitoring System (CMS) Flux Pilot Project (FPP) was designed to better understand contemporary carbon fluxes by bringing together state-of-the art models with remote sensing datasets. Here we report on simulations using NASAs Goddard Earth Observing System Model, version 5 (GEOS-5) which was used to evaluate the consistency of two different sets of observationally constrained land and ocean fluxes with atmospheric CO2 records. Despite the strong data constraint, the average difference in annual terrestrial biosphere flux between the two land (NASA Ames CASA and CASA-GFED) models is 1.7 Pg C for 2009-2010. Ocean models (NOBM and ECCO2-Darwin) differ by 35 in their global estimates of carbon flux with particularly strong disagreement in high latitudes. Based upon combinations of terrestrial and ocean fluxes, GEOS-5 reasonably simulated the seasonal cycle observed at northern hemisphere surface sites and by the Greenhouse gases Observing SATellite (GOSAT) while the model struggled to simulate the seasonal cycle at southern hemisphere surface locations. Though GEOS-5 was able to reasonably reproduce the patterns of XCO2 observed by GOSAT, it struggled to reproduce these aspects of AIRS observations. Despite large differences between land and ocean flux estimates, resulting differences in atmospheric mixing ratio were small, typically less than 5 ppmv at the surface and 3 ppmv in the XCO2 column. A statistical analysis based on the variability of observations shows that flux differences of these magnitudes are difficult to distinguish from natural variability, regardless of measurement platform.

FPP↗
DOE OSTI2024

Multi-Parameter Optical Fiber for Distributed Sensing of Humidity, CH4, CO2, and Corrosion

This work describes the use of the optical fiber sensor (OFS) for successful monitoring of humidity, CH4, and CO2 based on the strain produced along the single-mode fiber (SMF) sensor. This is enabled by absorption of H2O/gases onto the commercially available polyacrylate coated jacketed portion of the fiber resulting in a change in strain. Under equilibrium, a differential microstrain was observed along the jacketed portion of the SMF with N2, CH4, and CO2 at different relative humidity (RH) conditions. The strain response of the SMF under various mixed gas composition and different RH conditions were also measured and made calibration curves accordingly. Linear regression and principal component analysis of the strain datasets provided deconvolution of the impact of strain from H2O, N2, CH4, and CO2. Additionally, modified OFS comprised of the Fe coated fiber section was employed to monitor corrosion based on the increase in backscattered intensity amplitude of the light being passed once corrosion of Fe occurs. Also, corrosion of Fe was studied under soil by installing the fiber in soil with protective measures which would prevent the sensor being mechanically disturbed or broken during installation. The corrosion rates were studied by monitoring the rate at which the intensity of backscattered light amplitude attains a steady state value when complete corrosion of Fe with a specific coating thickness occurs.

Mainali, Badri↗
NASA NTRS1995

Partitioning of ocean and land uptake of CO2 as inferred by delta C-13 measurements from the NOAA Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network

Using delta C-13 measurements in atmospheric CO2 from a cooperative global air sampling network, we determined the partitioning of the net uptake of CO2 between ocean and land as a function of latitude and time. The majority of delta C-13 measurements were made at the Institute of Arctic and Alpine Research (INSTAAR) of the University of Colorado. We perform an inverse deconvolution of both CO2 and delta C-13 observations, using a two-dimensional model of atmospheric transport. Also, the discrimination against C-13 by plant photosynthesis, as a function of latitude and time, is calculated from global runs of the simple biosphere (SiB) model. Uncertainty due to the longitudinal structure of the data, which is not represented by the model, is studied through a bootstrap analysis by adding and omitting measurement sites. The resulting error estimates for our inferred sources and sinks are of the order of 1 GTC (1 GTC = 10(exp 15) gC). Such error bars do not reflect potential systematic errors arising from our estimates of the isotopic disequilibria between the atmosphere and the oceans and biosphere, which are estimated in a separate sensitivity analysis. With respect to global totals for 1992 we found that 3.2 GTC of carbon dissolved into the ocean and that 1.5 GTC were sequestered by land ecosystems. Northern hemisphere ocean gyres north of 15 deg N absorbed 2.7 GTC. The equatorial oceans between 10 deg S and 10 deg N were a net source to the atmosphere of 0.9 GTC. We obtained a sink of 1.6 GTC in southern ocean gyres south of 20 deg S, although the deconvolution is poorly constrained by sparse data coverage at high southern latitudes. The seasonal uptake of CO2 in the northern gyres appears to be correlated with a bloom of phytoplankton in surface waters. On land, northern temperate and boreal ecosystems between 35 deg N and 65 deg N were found to be a major sink of CO2 in 1992, as large as 3.5 GTC. Northern tropical ecosystems (equator-30 deg N) appear to be a net source to the source to the atmosphere of 2 GTC which could reflect biomass burning. A small sink, 0.3 GTC, was inferred for southern tropical ecosystems (30 deg S-equator).

Ciais, Philippe↗
DOE OSTI2024

Multi-Parameter Optical Fiber Sensing of Humidity, CH4, CO2, and Corrosion

In this work, the previously demonstrated capability of the optical fiber sensor (OFS) for successful monitoring of humidity has been extended to monitor the humidity, CH4, and CO2 with different gas composition based on the strain produced along the single mode fiber (SMF) sensor. This is enabled by absorption of H2O/gases on to the commercially available polyacrylate coated jacketed portion of the fiber resulting a change in strain. Under equilibrium, a differential microstrain was observed along the jacketed portion of the SMF with N2, CH4, and CO2 at different humidity conditions, while the unjacketed portion of the fiber was used only for sensing pressure/temperature induced strain. In case of N2 at 800 psig pressure, the observed microstrain was approximately 80, 65, 50 and 35 µε at 100, 75.0, 46.8, and 23.4 RH% respectively. Comparatively, a microstrain of approximately 95 µε was observed with 100% RH CH4 which demonstrates that SMF produces a measurable CH4 response alongside water. Similarly, the observed microstrain with CO2 was approximately 105, 90, 85, 80, and 70 µε at 100, 75.0, 46.8, 23.4, and 0 RH% respectively. Linear regression and principal component analysis of these dataset provided deconvolution of the impact of strain from H2O, CH4, and CO2 enabling good cross sensitivity. Additionally, modified OFS comprising of Fe coated fiber section was employed to monitor corrosion, using Fe as corrosion proxy, under harsh corrosive environment.

Mainali, Badri↗
DOE OSTI2024

Multi-Parameter Optical Fiber Sensing of Humidity, CH4, CO2, and Corrosion

In this work, the previously demonstrated capability of the optical fiber sensor (OFS) for successful monitoring of humidity has been extended to monitor the humidity, CH4, and CO2 with different gas composition based on the strain produced along the single mode fiber (SMF) sensor. This is enabled by absorption of H2O/gases on to the commercially available polyacrylate coated jacketed portion of the fiber resulting a change in strain. Under equilibrium, a differential microstrain was observed along the jacketed portion of the SMF with N2, CH4, and CO2 at different humidity conditions, while the unjacketed portion of the fiber was used only for sensing pressure/temperature induced strain. In case of N2 at 800 psig pressure, the observed microstrain was ~80, ~65, ~50 and ~35 µε at 100, 75.0, 46.8, and 23.4 RH% respectively. Comparatively, a microstrain of ~95 µε was observed with 100% RH CH4 which demonstrates that SMF produces a measurable CH4 response alongside water. Similarly, the observed microstrain with CO2 was ~105, ~90, ~85, ~ 80, and ~70 µε at 100, 75.0, 46.8, 23.4, and 0 RH% respectively. Linear regression and principal component analysis of these dataset provided deconvolution of the impact of strain from H2O, CH4, and CO2 enabling good cross sensitivity. Additionally, modified OFS comprising of Fe coated fiber section was employed to monitor corrosion based on the increase in backscattered intensity amplitude of the light being passed once corrosion occurs.

Mainali, Badri↗
NASA NTRS1990

Identifying atmospheric monitoring needs for Space Station Freedom

The monitoring needs for Space Station Freedom were identified by examining: the experiences of past missions; ground based tests of proposed life support systems; a contaminant load model; metabolic production from an 8-person crew; and a fire scenario. Continuous monitoring is recommended for components critical for life support, and that intermittent analysis be provided for all agents that may exceed one-half the spacecraft maximum allowable concentration. The minimum monitoring effort recommended includes continuous monitoring for: N2, O2, CO2, CO, H2O, H2, CH4, nonmethane hydrocarbons, aromatic hydrocarbons, refrigerants, and halons. Information on over 70 compounds is presented on the rationale for monitoring the frequency of analysis, and concentration ranges.

Casserly, Dennis M.↗
DOE OSTI2020

A system to control CO2 in O2 concentrations in aqueous media (Year 2 Report)

Per the Statement of Work, the following tasks were outlined for completion in Year 2: 1). Testing, modification, and optimization of the system. 2). Addition of oxygen manipulation and monitoring. 3). Expansion of CO2 bubbling/pH reduction system to include oxygen addition/removal and temperature control. 4). Investigate alkalinity modification by the microbial cultures and its impact on the carbonate chemistry control of the system. 5).Deliverable: Seawater chemistry and temperature control and monitoring system for microbial culture studies under present and future ocean conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Evaluation of Improvements in Storage Efficiencies, Containment, Assurance, CO 2 Plume Movement, and Verification of Storage Technologies

This report summarizes some of the evolving improvements in key technical skills that are developing to support a large-scale commercial application of CCS as well as support rapidly increasing interest in carbon negative technologies. It does not attempt to review relatively well-known processes and procedures that are familiar to many CCS experts; rather focuses on novel concepts that have the potential to provide breakthroughs and add high benefit as projects evolve. Some elements described are in development or not yet proven ideas for which we provide an expression of status of confidence at the time of writing. Topics covered are evaluation of improvements in storage efficiency estimation, containment assurance methods, CO 2 plume movement and pressure prediction, and monitoring and verification of storage methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Accessing Fungal Contributions to the Birch Effect: Real-Time Respiration from Pore-Scale Microfluidics

Drying and rewetting of soil stimulates soil carbon emission. The Birch effect, driven by these cycles, leads to CO2 efflux, which can be monitored using real-time mass spectrometry (RTMS). Although soil fungi retain water during droughts, their contribution to CO2 release during drying–rewetting cycles remains unclear. In this study, we present the first demonstration of integrating micromodels with RTMS to monitor the Birch effect by simulating drought and rewetting. Micromodels were inoculated with axenic fungal culture and dried to assess moisture retention. After drying, RTMS quantified CO2 release upon rewetting with H218O mixtures. Our results showed that soil fungi released CO2 upon rehydration and immediately utilized the external water source at the pore scale by generating subsequent 46CO2. This work is the first to integrate RTMS with microsystems to investigate pore-scale biogeochemistry and the involvement of fungi in the Birch effect.

54 ENVIRONMENTAL SCIENCES↗