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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Machine learning and ligand binding predictions: A review of data, methods, and obstacles

We report that computational predictions of ligand binding is a difficult problem, with more accurate methods being extremely computationally expensive. The use of machine learning for drug binding predictions could possibly leverage the use of biomedical big data in exchange for time-intensive simulations. This paper reviews current trends in the use of machine learning for drug binding predictions, data sources to develop machine learning algorithms, and potential problems that may lead to overfitting and ungeneralizable models. A few popular datasets that can be used to develop virtual high-throughput screening models are characterized using spatial statistics to quantify potential biases. We can see from evaluating some common benchmarks that good performance correlates with models with high-predicted bias scores and models with low bias scores do not have much predictive power. A better understanding of the limits of available data sources and how to fix them will lead to more generalizable models that will lead to novel drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Experimental study on kinetic oxidation of graphite IG-110 by steam

Graphite is proposed for use in High-temperature Gas-cooled Reactors (HTGRs) as the fuel matrix, neutron moderator/reflector, and core structural material. One important property of nuclear grade graphite is their resistance to oxidation in high-temperature environment. Extensive investigation has been performed in the literature for graphite oxidation by air. However, available experimental data are still limited for graphite oxidation by steam under conditions comparable to a postulated steam ingress accident in HTGRs. In this study, the oxidation rate of graphite IG-110 by steam was measured at temperatures from 850 to 1100 °C with the steam partial pressure varying from 0.5 to 20.0 kPa and the hydrogen partial pressure varying from 0 to 2.0 kPa. Further analysis confirms the oxidation process in this present study is dominated by the chemical kinetics, which lends credit to the data for being used to develop numerical models. It was observed that the increase of the kinetic oxidation rate with the steam partial pressure tends to become less apparent if the steam partial pressure keeps increasing. In addition, it was found that the partitioning of hydrogen inhibits the graphite-steam reaction process even with the steam partial pressure up to 20.0 kPa. However, this inhibiting effect starts to become saturated when the hydrogen partial pressure exceeds 1.0 kPa. The oxidation rates were fitted to the conventional Langmuir-Hinshelwood (LH) and Boltzmann-enhanced Langmuir-Hinshelwood (BLH) models by a multivariable optimization algorithm. The BLH model exhibits a better accuracy than the LH model within the specified experimental conditions. The predicted oxidation rate using the BLH model shows a mean relative difference of about 24% with the maximum difference of about 55% when compared with our experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Reducing Cost of Chlorinated Volatile Organic Compound Remediation by Transitioning from Active to Passive Soil Vapor Extraction - 20157

Areas of high chlorinated volatile organic compound (cVOC) contamination at the Savannah River Site (SRS) have been undergoing remediation via soil vapor extraction, sometimes coupled with thermal treatments to enhance extraction rates. These active systems are effective in removing large amounts of contaminant mass from the subsurface and mitigating the impacts to groundwater. However, as extraction rates decline, costs must be evaluated with respect to the benefit of continued active operation. A decision framework for identifying conditions when a transition to a more passive remediation is appropriate has been developed with state and federal regulatory agencies. Two remediation areas have recently been transitioned from active soil vapor extraction (ASVE) to passive soil vapor extraction (PSVE) at the SRS. Performance evaluation goals including plume stabilization, overall mass removal trends, environmental sustainability and costs were considered in transitioning from active remediation to passive technologies at both sites. At the Dynamic Underground Stripping (DUS) project at the M-Area Settling Basin, ASVE was combined with steam injection to extract cVOCs during active operations. Steam injection occurred from September 2005 to September 2009. DUS utilized 63 steam injection wells, 34 active vapor extraction wells, and 3 active soil vapor extraction units (SVEUs). Two active SVEUs had 60 horsepower blowers; the third had a 25-horsepower blower. Mass removal was closely tracked during DUS operations; over 181,437 kilograms (400,000 pounds) of cVOCs were removed while active steam injection occurred. After steaming was stopped, ASVE continued. The 34 active wells were evaluated in 2012. The ASVE wells were grouped into categories of high, medium, and low extraction rates. High producing wells remained connected to a single active SVEU. Low producing wells were abandoned, and the medium producing wells were transitioned to PSVE (Microblowers{sup TM}). Microblowers{sup TM} utilize a dedicated blower per well and are solar powered. This passive technology provides energy, maintenance, and operation costs savings while still providing an efficient reduction in cVOC migration to groundwater. In 2018, the remaining ASVE wells were evaluated again. The purpose of this testing was to identify which wells removed the most mass. An optimal well configuration was determined. The criteria to discontinue ASVE was removal of less than 18 kilograms (40 pounds) per week of cVOCs. After 3 months of shutdown (rebound conditions), 2.7 kilograms (5.9 pounds) of cVOCs per week were being removed. Data from the rebound test justified ending ASVE and transitioning wells with higher extraction rates to PSVE. Wells that had depleted the cVOC mass within their zone of influence were abandoned. Performance data from existing PSVE wells justified ending PSVE at wells with depleted extraction rates. Currently the system has 16 PSVE wells operating. Another ASVE system was being used to treat cVOC contaminated soil at the A-Area Miscellaneous Rubble Pile (AMRP) at SRS. System operation began in 2004, with 7 ASVE wells connected to a 60- horsepower blower. Mass removal rates and contaminant concentrations remained consistently low over the ASVE lifespan at AMRP. This indicated that mass removal was diffusion limited. With this data, the 7 ASVE wells were transitioned to PSVE in 2017. Twelve pressure monitoring points were also transitioned to PSVE wells. AMRP currently has 19 PSVE wells operating. Both transitions from active to passive remediation had concurrence from the United States Environmental Protection Agency and the South Carolina Department of Health and Environmental Control. These transitions ensure that only the necessary amount of energy is being exerted to remediate the environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

An approach to combine neutron and ion irradiation data to accelerate material qualification for nuclear reactors

Next-generation nuclear power plants are generally characterized by higher operating temperatures, increased neutron fluences and energies, and distinct corrosive coolant environments versus the existing light water reactor fleet. Whether using existing materials in new environments, newly developed materials tailored for these environments, or new manufacturing methods, the traditional decades-long approach for materials qualification does not facilitate rapid deployment. Ion irradiation has demonstrated success in reproducing material microstructure and select property evolution resulting from neutron irradiation with three to four orders of magnitude reduction in time and cost, making it an ideal candidate for accelerated irradiation testing. Because microstructure has a large impact on bulk material properties, limited neutron irradiation data at lower damage levels can in principle be combined with accelerated ion testing results and modeling and simulation to form an accurate prediction of microstructure evolution and select properties under different neutron irradiation conditions and at higher damage levels. The objective of this work is to present a conceptual framework of specific steps to fulfill several technical challenges associated with qualifying materials for performance in radiation environments on an accelerated time frame. A brief review of the regulatory landscape for materials in nuclear environments is presented, followed by additional overviews to understand the current state of the art for correlation of materials properties across radiation environments using experimental and computational methodologies. Finally, the roles of academia, national laboratories, and industry in the advancement of this accelerated materials qualification framework are discussed as a path forward, with possible case studies presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1973

Satellite ocean color measurements

The application of pattern recognition to ocean color data analysis is considered. Due to weight, cost, and data transmission rate limitations, any mapping type remote sensor of ocean color must necessarily collect light from the sea in a finite number of channels. The optical properties of the sea are discussed together with the remote sensing of ocean color, an optical model of natural water, the microscopic optical model, the macroscopic optical model, multiple scattering theory, measurements of subsurface oceanographic parameters, measurements of bulk absorption and scattering properties, measurements of the up- and down-welling light field, and the techniques for ocean color data analysis.

Mccluney, W. R.↗
NASA NTRS2012

Constraints on the Galactic Halo Dark Matter from Fermi-LAT Diffuse Measurements

We have performed an analysis of the diffuse gamma-ray emission with the Fermi Large Area Telescope (LAT) in the Milky Way halo region, searching for a signal from dark matter annihilation or decay. In the absence of a robust dark matter signal, constraints are presented. We consider both gamma rays produced directly in the dark matter annihilation/decay and produced by inverse Compton scattering of the e+/e− produced in the annihilation/decay. Conservative limits are derived requiring that the dark matter signal does not exceed the observed diffuse gamma-ray emission. A second set of more stringent limits is derived based on modeling the foreground astrophysical diffuse emission using the GALPROP code. Uncertainties in the height of the diffusive cosmic-ray halo, the distribution of the cosmic-ray sources in the Galaxy, the index of the injection cosmic-ray electron spectrum, and the column density of the interstellar gas are taken into account using a profile likelihood formalism, while the parameters governing the cosmic-ray propagation have been derived from fits to local cosmic-ray data. The resulting limits impact the range of particle masses over which dark matter thermal production in the early universe is possible, and challenge the interpretation of the PAMELA/Fermi-LAT cosmic ray anomalies as the annihilation of dark matter.

DIFFUSE MEASUREMENTS↗
NASA NTRSDate not supplied

Effects of Mild Hypobaric Hypoxia on Response From Mild Exercise in NASA Exploration Atmosphere Tests

INTRODUCTION: The NASA Exploration Atmosphere study aims to validate a new prebreathe protocol incorporating an alternate habitat atmosphere of 56.5 kPa (8.2psia), 34% O 2 , and 66% N 2 to control and mitigate decompression sickness risk associated with spaceflight extravehicular activities. This alternate atmosphere results in a mild hypoxic environment (PIO 2 of 128 mmHg) that may influence inhabitant physiological responses to exercise. Therefore, the responses to light exercise in relation to the mild hypobaric hypoxic environment were investigated. METHODS: Eight participants (4M/4F; age=38.3±9.0 yr; weight=76.0±13.1 kg; peak aerobic capacity [VO 2 pk]= 3.1±0.7 L/min) were exposed to a mild hypobaric hypoxic environment for 11 days in NASA’s 20-foot hypobaric chamber at Johnson Space Center. Participants alternated test days between a habitat atmosphere of 56.5 kPA/34% O 2 and simulated 6-hour EVA environment, 29.6 kPa/85% O 2 . Participants completed pre-mission graded VO 2 pk tests on a LODE cycle ergometer with ParvoMedics metabolic analyzer. Submaximal aerobic tests were performed pre and during the mission (10-minutes of exercise at a workload of 40% VO 2 pk).Pre-mission, performed submaximal exercise exposed to a breathing air mixture of, 18% O 2 and balance N 2 , to simulate the mildly hypoxic environment within the 20-foot chamber. Linear mixed models (fixed effect: test day; random effects: subject, age) were performed to determine whether physiological responses (oxygen uptake [VO 2 ], carbon dioxide production [VCO 2 ], ventilation [VE], oxygen saturation [SPO 2 ], heart rate [HR], respiratory exchange ratio [RER]) to submaximal exercise performed within the 20-foot hypobaric chamber every 2 days differed from the pre-mission (18% O 2 ) testing. Results are presented as estimated marginal means with lower and upper confidence limits, with significance set to 0.05. RESULTS AND DISCUSSION: Seven of eight participants completed the chamber study. Mixed models for VO 2 , VCO 2 , SpO 2 , HR, and RER indicated negligible impact of the mild hypoxic chamber environment compared to pre-mission testing (all p>0.05).Results for VE indicated a minor impact of chamber environment compared to pre-mission testing (37.0 L/min [30.8, 43.2]), with increased VE at test day 10 (40.4 L/min [34.2, 46.6]; p= 0.029).The aerobic performance data collected suggests limited physiologic responses to mild exercise when performed at normobaric hypoxia and hypobaric hypoxia.

B Siders↗
DOE OSTI2023

Three-dimensional nanoscale reduced-angle ptycho-tomographic imaging with deep learning (RAPID)

X-ray ptychographic tomography is a nondestructive method for three dimensional (3D) imaging with nanometer-sized resolvable features. The size of the volume that can be imaged is almost arbitrary, limited only by the penetration depth and the available scanning time. Here we present a method that rapidly accelerates the imaging operation over a given volume through acquiring a limited set of data via large angular reduction and compensating for the resulting ill-posedness through deeply learned priors. The proposed 3D reconstruction method “RAPID” relies initially on a subset of the object measured with the nominal number of required illumination angles and treats the reconstructions from the conventional two-step approach as ground truth. It is then trained to reproduce equal fidelity from much fewer angles. After training, it performs with similar fidelity on the hitherto unexamined portions of the object, previously not shown during training, with a limited set of acquisitions. In our experimental demonstration, the nominal number of angles was 349 and the reduced number of angles was 21, resulting in a x140 aggregate speedup over a volume of 4.48 x 93.18 x 3.92 μm 3 and with (14nm) 3 feature size, i.e. ~ 10 8 voxels. RAPID’s key distinguishing feature over earlier attempts is the incorporation of atrous spatial pyramid pooling modules into the deep neural network framework in an anisotropic way. We found that adjusting the atrous rate improves reconstruction fidelity because it expands the convolutional kernels’ range to match the physics of multi-slice ptychography without significantly increasing the number of parameters.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Motion Magnification to Visualize the Modes of Space Structures

Traditional structural testing involves using accelerometers and strain gages to measure the motion. While this traditional instrumentation suite has proven accurate, it is limited to capture data only in the discrete locations where the transducers are placed. Additionally, applying the instrumentation can be a difficult and labor intensive task. By using video cameras, the motion of the test article – such as a launch vehicle or launch vehicle payload – can be easily captured at any location in the field of view and easily visualized using a post-processing technique called Motion Magnification. It is also much easier to place video cameras to measure motion rather than having to place contact sensors, especially when placement locations can be limited on final flight hardware. Recently, a team of MIT Lincoln Laboratory (MITLL) and NASA Marshall Space Flight Center (MSFC) have been collaborating to use Motion Magnification to measure the dynamics of large space structures. This presentation will detail some of the results of this collaboration.

Eric Colby Stewart↗
NASA NTRSDate not supplied

Motion Magnification to Visualize the Modes of Space Structures

Traditional structural testing involves using accelerometers and strain gages to measure the motion. While this traditional instrumentation suite has proven accurate, it is limited to capture data only in the discrete locations where the transducers are placed. Additionally, applying the instrumentation can be a difficult and labor intensive task. By using video cameras, the motion of the test article – such as a launch vehicle or launch vehicle payload – can be easily captured at any location in the field of view and easily visualized using a post-processing technique called Motion Magnification. It is also much easier to place video cameras to measure motion rather than having to place contact sensors, especially when placement locations can be limited on final flight hardware. Recently, a team of MIT Lincoln Laboratory (MITLL) and NASA Marshall Space Flight Center (MSFC) have been collaborating to use Motion Magnification to measure the dynamics of large space structures. This presentation will detail some of the results of this collaboration.

Eric Colby Stewart↗
NASA NTRS2000

Limits on Arcminute Scale Cosmic Microwave Background Anisotropy with the BIMA Array

We have used the Berkeley-Illinois-Maryland-Association (BIMA) millimeter array outfitted with sensitive cm-wave receivers to search for Cosmic Microwave Background (CMB) anisotropies on arcminute scales. The interferometer was placed in a compact configuration which produces high brightness sensitivity, while providing discrimination against point sources. Operating at a frequency of 28.5 GHz, the FWHM primary beam of the instrument is 6.6 arcminutes. We have made sensitive images of seven fields, five of which where chosen specifically to have low IR dust contrast and be free of bright radio sources. Additional observations with the Owens Valley Radio Observatory (OVRO) millimeter array were used to assist in the location and removal of radio point sources. Applying a Bayesian analysis to the raw visibility data, we place limits on CMB anisotropy flat-band power Q_flat = 5.6 (+3.0, -5.6) uK and Q_flat < 14.1 uK at 68% and 95% confidence. The sensitivity of this experiment to flat band power peaks at a multipole of l = 5470, which corresponds to an angular scale of approximately 2 arcminutes The most likely value of Q_flat is similar to the level of the expected secondary anisotropies.

Holzapfel, W. L.↗
NASA NTRS1992

Numerical methods for the simulation of complex multi-body flows with applications for the integrated Space Shuttle vehicle

This project forms part of the long term computational effort to simulate the time dependent flow over the integrated Space Shuttle vehicle (orbiter, solid rocket boosters (SRB's), external tank (ET), and attach hardware) during its ascent mode for various nominal and abort flight conditions. Due to the limitations of experimental data such as wind tunnel wall effects and the difficulty of safely obtaining valid flight data, numerical simulations are undertaken to supplement the existing data base. This data can then be used to predict the aerodynamic behavior over a wide range of flight conditions. Existing computational results show relatively good overall comparison with experiments but further refinement is required to reduce numerical errors and to obtain finer agreements over a larger parameter space. One of the important goals of this project is to obtain better comparisons between numerical simulations and experiments. In the simulations performed so far, the geometry has been simplified in various ways to reduce the complexity so that useful results can be obtained in a reasonable time frame due to limitations in computer resources. In this project, the finer details of the major components of the Space Shuttle are modeled better by including more complexity in the geometry definition. Smaller components not included in early Space Shuttle simulations will now be modeled and gridded.

Chan, William M.↗
NASA NTRS2000

Limits on Arcminute-Scale Cosmic Microwave Background Anisotropy at 28.5 GHz

We have used the Berkeley-Illinois-Maryland Association (BIMA) millimeter array outfitted with sensitive centimeter-wave receivers to search for cosmic microwave background (CMB) anisotropies on arcminute scales. The interferometer was placed in a compact configuration that produces high brightness sensitivity, while providing discrimination against point sources. Operating at a frequency of 28.5 GHz, the FWHM primary beam of the instrument is approximately 6'.6. We have made sensitive images of seven fields, four of which where chosen specifically to have low infrared dust contrast and to be free of bright radio sources. Additional observations with the Owens Valley Radio Observatory (OVRO) millimeter array were used to assist in the location and removal of radio point sources. Applying a Bayesian analysis to the raw visibility data, we place limits on CMB anisotropy flat-band power of Q(sub flat) = 5.6(sub -5.6)(exp 3.0) microK and Q(sub flat) < 14.1 microK at 68% and 95% confidence, respectively. The sensitivity of this experiment to flat-band power peaks at a multipole of I = 5470, which corresponds to an angular scale of approximately 2'. The most likely value of Q(sub flat) is similar to the level of the expected secondary anisotropies.

Holzapfel, W. L.↗
NASA NTRS1999

Visualization Co-Processing of a CFD Simulation

OVERFLOW, a widely used CFD simulation code, is combined with a visualization system, pV3, to experiment with an environment for simulation/visualization co-processing on a SGI Origin 2000 computer(O2K) system. The shared memory version of the solver is used with the O2K 'pfa' preprocessor invoked to automatically discover parallelism in the source code. No other explicit parallelism is enabled. In order to study the scaling and performance of the visualization co-processing system, sample runs are made with different processor groups in the range of 1 to 254 processors. The data exchange between the visualization system and the simulation system is rapid enough for user interactivity when the problem size is small. This shared memory version of OVERFLOW, with minimal parallelization, does not scale well to an increasing number of available processors. The visualization task takes about 18 to 30% of the total processing time and does not appear to be a major contributor to the poor scaling. Improper load balancing and inter-processor communication overhead are contributors to this poor performance. Work is in progress which is aimed at obtaining improved parallel performance of the solver and removing the limitations of serial data transfer to pV3 by examining various parallelization/communication strategies, including the use of the explicit message passing.

Vaziri, Arsi↗
NASA NTRS2007

Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences.

Adler, Robert↗
NASA NTRS2007

Application of Multi-Satellite Precipitation Analysis to Floods and Landslides

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences. However, difficulties in comparing landslide event information (mostly from news reports) with the satellite-based forecasts are analyzed.

Adler, Robert↗
DOE OSTI2023

IRA Energy Community Data Layers

Data, geospatial data resources, and the linked mapping tool and web services reflect data for two types of potentially qualifying energy communities: 1) Census tracts and directly adjoining tracts that have had coal mine closures since 1999 or coal-fired electric generating unit retirements since 2009. These census tracts qualify as energy communities. 2) Metropolitan statistical areas (MSAs) and non-metropolitan statistical areas (non-MSAs) that are energy communities for 2023 and 2024, along with their fossil fuel employment (FFE) status. Additional information on energy communities and related tax credits can be accessed on the Interagency Working Group on Coal & Power Plant Communities & Economic Revitalization Energy Communities website (https://energycommunities.gov/energy-community-tax-credit-bonus/). Use limitations: these spatial data and mapping tool may not be relied upon by taxpayers to substantiate a tax return position or for determining whether certain penalties apply and will not be used by the IRS for examination purposes. The mapping tool does not reflect the application of the law to a specific taxpayer’s situation, and the applicable Internal Revenue Code provisions ultimately control.

Census Tract↗
NASA NTRS2009

Mobile Instruments Measure Atmospheric Pollutants

As a part of NASA's active research of the Earth s atmosphere, which has included missions such as the Atmospheric Laboratory of Applications and Science (ATLAS, launched in 1992) and the Total Ozone Mapping Spectrometer (TOMS, launched on the Earth Probe satellite in 1996), the Agency also performs ground-based air pollution research. The ability to measure trace amounts of airborne pollutants precisely and quickly is important for determining natural patterns and human effects on global warming and air pollution, but until recent advances in field-grade spectroscopic instrumentation, this rapid, accurate data collection was limited and extremely difficult. In order to understand causes of climate change and airborne pollution, NASA has supported the development of compact, low power, rapid response instruments operating in the mid-infrared "molecular fingerprint" portion of the electromagnetic spectrum. These instruments, which measure atmospheric trace gases and airborne particles, can be deployed in mobile laboratories - customized ground vehicles, typically - to map distributions of pollutants in real time. The instruments must be rugged enough to operate rapidly and accurately, despite frequent jostling that can misalign, damage, or disconnect sensitive components. By measuring quickly while moving through an environment, a mobile laboratory can correlate data and geographic points, revealing patterns in the environment s pollutants. Rapid pollutant measurements also enable direct determination of pollutant sources and sinks (mechanisms that remove greenhouse gases and pollutants), providing information critical to understanding and managing atmospheric greenhouse gas and air pollutant concentrations.

Source record↗