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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Quantifying Methane Leak Emissions by Fused Airborne Imaging Spectroscopy with in Situ Surface Mobile and Airborne Observations of a California Producing Oil Field

Methane (CH4) emission budgets remain uncertain and are projected to grow as oil and gas production from short-lived wells increases and their subsequent transport through aging gas distribution networks. Orders-of-magnitude variations in temporal, spatial, and emission scales present a key challenge to leak detection and quantification. Also, the probability distributions for large and stochastic, leaky systems such as geological reservoirs (by natural migration-seeps) and petroleum production from those reservoirs remain largely unknown, needed to address current approach limitations. The scale of many petroleum systems favors remote sensing, but the sensitivity of such systems often precludes detection of weak emissions. Consequently, an accurate evaluation requires that the relative contribution from the emission "tails" of small leaks also be quantified, which is best carried out using high-sensitivity in situ methods. Fusion of remote sensing and in situ approaches leverages complementary capabilities to address these limitations. We show results from mobile surface (AMOG) and airborne in situ (AJAX) and thermal-infrared (TIR) hyperspectral imaging spectroscopy (Mako) data applied to a producing oil field in the California Central Valley near Bakersfield. AMOG is an automobile-based mobile lab that measures 13 trace gases, aerosol size distributions and vertical profiles, 3D winds and other meteorology, and atmospheric column measurements by solar spectroscopy at highway speeds. AJAX measures 5 trace gases and 3D winds at ~140 m/s. Mako is a broad-area TIR imaging spectrometer that can discriminate multiple gases present in each pixel acquired. In situ-derived, total field emissions were 31±16 Gg/yr CH4. This was compared with Mako-derived emissions from all plumes identified across the study site. We found that super-emitters were not the dominant emissions mode and the spatial pattern of plume locations from production infrastructure was correlated to geological structures.

Leifer, Ira↗
NASA NTRS2022

Gulf of Mexico Health and Air Quality: Using NASA Earth Observations to Identify Potential Methane Sources for Improved Monitoring of Offshore Oil & Gas Activity in the Gulf of Mexico

The extraction, production, and transportation of oil and gas is a leading contributor to anthropogenic methane emissions via activities such as flaring and venting. The Bureau of Ocean and Energy Management (BOEM) has air quality jurisdiction offshore in the Gulf of Mexico and drafts regulations for criteria pollutants, while the Bureau of Safety and Environmental Enforcement (BSEE) enforces these regulations. Additionally, the non-profit organization SkyTruth monitors natural resources, including methane. BOEM, BSEE, and SkyTruth have partnered with NASA DEVELOP to use Earth observations to identify potential offshore methane sources in the Gulf of Mexico and to validate reported flaring activity. This information will allow BOEM and BSEE to make informed regulations regarding air pollution. Here, we cross-referenced BOEM infrastructure data with Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Radiometer Suite (VIIRS) Nightfire data to validate operator-reported flaring. Sentinel-5p TROPOspheric Monitoring Instrument (TROPOMI) pollutant concentrations were used to validate VIIRS-detected flaring outside of the Gulf of Mexico where operator-reported data is unavailable. Using these methods, we identified the locations of offshore oil and gas infrastructure with known episodic flaring and venting in 2017 in the Gulf of Mexico, as well as offshore of South America and West Africa in 2021. Drawing upon retrieval methods used to detect onshore methane emissions, we proposed an analogous method utilizing sunglint to illuminate methane plumes over the ocean using Sentinel-2 Multispectral Imager (MSI) imagery. We detected two potential methane plumes – one at the Constitution complex in the Gulf of Mexico in July 2017 and one off the Coast of Lagos, West Africa, in July 2021.

Kate Howell↗
NASA NTRS1927

High-speed Oil Engines for Vehicles. Part II

Further progress toward the satisfactory solution of the difficult problem of the distribution and atomization of the injected fuel was made by extensive experimentation with various fuel valves, nozzles, and atomizing devices. Valuable information was also obtained through numerous experimental researches on the combustion of oils and the manner of introducing the combustion air into the cylinder, as well as on the physical processes of atomization, the determination of the size of drops, etc. These researches led to the conclusion that it is possible, even without producing great turbulence in the combustion chamber and at moderate pump pressure, if the degree of atomization and the penetrative power of the fuel jet are adapted to the shape of the combustion chamber and to the dimensions of the cylinder.

ENGINES, OIL↗
NASA NTRS1926

Experimental investigation of the physical properties of medium and heavy oils, their vaporization and use in explosion engines. Part IV

This report presents a theoretical treatment of the vaporization process of medium and heavy oils. The results of this investigation, which were mostly obtained from the lighter components of the heavy fuels, require a 10- or 16-fold vaporization in comparison with gasoline. We must attain a still finer degree of atomization, in order to include the heavier components.

OILS↗
NASA NTRS2014

Improved Satellite Retrievals of NO2 and SO2 over the Canadian Oil Sands and Comparisons with Surface Measurements

Satellite remote sensing is increasingly being used to monitor air quality over localized sources such as the Canadian oil sands. Following an initial study, significantly low biases have been identified in current NO2 and SO2 retrieval products from the Ozone Monitoring Instrument (OMI) satellite sensor over this location resulting from a combination of its rapid development and small spatial scale. Air mass factors (AMFs) used to convert line-of-sight "slant" columns to vertical columns were re-calculated for this region based on updated and higher resolution input information including absorber profiles from a regional-scale (15 km × 15 km resolution) air quality model, higher spatial and temporal resolution surface reflectivity, and an improved treatment of snow. The overall impact of these new Environment Canada (EC) AMFs led to substantial increases in the peak NO2 and SO2 average vertical column density (VCD), occurring over an area of intensive surface mining, by factors of 2 and 1.4, respectively, relative to estimates made with previous AMFs. Comparisons are made with long-term averages of NO2 and SO2 (2005-2011) from in situ surface monitors by using the air quality model to map the OMI VCDs to surface concentrations. This new OMI-EC product is able to capture the spatial distribution of the in situ instruments (slopes of 0.65 to 1.0, correlation coefficients of greater than 0.9). The concentration absolute values from surface network observations were in reasonable agreement, with OMI-EC NO2 and SO2 biased low by roughly 30%. Several complications were addressed including correction for the interference effect in the surface NO2 instruments and smoothing and clear-sky biases in the OMI measurements. Overall these results highlight the importance of using input information that accounts for the spatial and temporal variability of the location of interest when performing retrievals.

surface concentration↗
NASA NTRS2018

Modeling the Risk of U.S. Offshore Oil & Gas Exploration-Well Drilling, Commercial Nuclear Plants, and Human Spaceflight

Nuclear power, offshore oil & gas exploration, and human spaceflight all have high consequence potential if something goes wrong. Each has had at least one major incident that pointed to a need for improved risk assessment. Careful risk analysis is very important for technologies having complexity, uncertainty, and high consequence potential. All rely on multiple barriers/controls/redundancy to minimize risk. NRC (Nuclear Regulatory Commission) has moved towards risk informed regulation with Probabilistic Risk Assessment (PRA) as a major input.

PRA↗
NASA NTRS2021

Airborne and Ground-Based Measurements of Aerosol Optical Depth of Freshly Emitted Anthropogenic Plumes in the Athabasca Oil Sands Region

In this work we report the airborne aerosol optical depth (AOD) from measurements within freshly emitted anthropogenic plumes arising from mining and processing operations in the Athabasca Oil Sands Region (AOSR) in the context of ground-based AERONET climatological daily averaged AODs at Fort McMurray (Alberta, Canada). During two flights on 9 and 18 June 2018, the NASA airborne 4STAR (Spectrometers for Sky-Scanning, Sun-Tracking Atmospheric Research) Sun photometer registered high fine-mode (FM, <1 µm) in-plume AODs of up to 0.4 and 0.9, respectively, in the vicinity of the plume source (<20 km). Particle composition shows that the plumes were associated with elevated concentrations of sulfates and ammonium. These high AODs significantly exceed climatological averages for June and were not captured by the nearby AERONET instrument (mean daily AODs of 0.10±0.01 and 0.07±0.02, maximum AOD of 0.12) due possibly to horizontal inhomogeneity of the plumes, plume dilution and winds which in certain cases were carrying the plume away from the ground-based instrument. The average 4STAR out-of-plume (background) AODs deviated only marginally from AERONET daily averaged values. While 4STAR AOD peaks were generally well correlated in time with peaks in the in situ-measured particle concentrations, we show that differences in particle size are the dominant factor in determining the 4STAR-derived AOD. During the two flights of 24 June and 5 July 2018 when plumes likely travelled distances of 60 km or more, the average 4STAR FM AOD increased by 0.01–0.02 over ∼50 km of downwind particle evolution, which was supported by the increases in layer AODs calculated from the in situ extinction measurements. Based on these observations as well as the increases in organic mass, we attribute the observed AOD increase, at least in part, to secondary organic aerosol formation. The in-plume and out-of-plume AODs for this second pair of flights, in contrast to clear differences in in situ optical and other measurements, were practically indistinguishable and compared favourably to AERONET within 0.01–0.02 AOD. This means that AERONET was generally successful in capturing the background AODs, but missed some of the spatially constrained high-AOD plumes with sources as close as 30–50 km, which is important to note since the AERONET measurements are generally thought to be representative of the regional AOD loading. The fact that industrial plumes can be associated with significantly higher AODs in the vicinity of the emission sources than previously reported from AERONET can potentially have an effect on estimating the AOSR radiative impact.

AERONET↗
NASA NTRSDate not supplied

A Machine Learning Approach for the Remote Sensing Retrieval of Oil Spills from Polarimetric Measurements

The Fresnel laws of specular reflection directly connect remote sensing observations of light polarization within the sunglint region to the ocean surface refractive index. This parameter is instrumental to identify areas affected by oil, or any other floating substance capable of modifying the refractive index of pure seawater. In preparation for the NASA Plankton, Aerosol, ocean Ecosystem (PACE) mission, we are developing an advanced retrieval scheme that exploits such measurements to deliver the refractive index as an operational product. The original method was developed based on observations of the airborne Research Scanning Polarimeter. Here we present several aspects related to the extension of this technique to the PACE HARP-2 sensor (especially regarding the projected accuracy), and discuss preliminary results obtained by applying neural-network trainings to look-up tables produced with the forward radiative transfer code, with the goal of improving the computational performance. Success in the final implementation will guarantee a version of the retrieval algorithm suitable to fast-response needs and disaster management.

machine learning↗