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At least 91 records · Page 5

Contamination Analysis Tools

This talk presents 3 different tools developed recently for contamination analysis:HTML QCM analyzer: runs in a web browser, and allows for data analysis of QCM log filesJava RGA extractor: can load in multiple SRS.ana files and extract pressure vs. time dataC++ Contamination Simulation code: 3D particle tracing code for modeling transport of dust particulates and molecules. Uses residence time to determine if molecules stick. Particulates can be sampled from IEST-STD-1246 and be accelerated by aerodynamic forces.

Nongyrotropic Electrons in Guide Field Reconnection

We apply a scalar measure of nongyrotropy to the electron pressure tensor in a 2D particle-in-cell simulation of guide field reconnection and assess the corresponding electron distributions and the forces that account for the nongyrotropy. The scalar measure reveals that the nongyrotropy lies in bands that straddle the electron diffusion region and the separatrices, in the same regions where there are parallel electric fields. Analysis of electron distributions and fields shows that the nongyrotropy along the inflow and outflow separatrices emerges as a result of multiple populations of electrons influenced differently by large and small-scale parallel electric fields and by gradients in the electric field. The relevant parallel electric fields include large-scale potential ramps emanating from the x-line and sub-ion inertial scale bipolar electron holes. Gradients in the perpendicular electric field modify electrons differently depending on their phase, thus producing nongyrotropy. Magnetic flux violation occurs along portions of the separatrices that coincide with the parallel electric fields. An inductive electric field in the electron EB drift frame thus develops, which has the effect of enhancing nongyrotropies already produced by other mechanisms and under certain conditions producing their own nongyrotropy. Particle tracing of electrons from nongyrotropic populations along the inflows and outflows shows that the striated structure of nongyrotropy corresponds to electrons arriving from different source regions. We also show that the relevant parallel electric fields receive important contributions not only from the nongyrotropic portion of the electron pressure tensor but from electron spatial and temporal inertial terms as well.

Parallel Electric Fields↗

Structure and Composition of the Distant Lunar Exosphere: Constraints from ARTEMIS Observations of Ion Acceleration in Time-Varying Fields

By analyzing the trajectories of ionized constituents of the lunar exosphere in time-varying electromagnetic fields, we can place constraints on the composition, structure, and dynamics of the lunar exosphere. Heavy ions travel slower than light ions in the same fields, so by observing the lag between field rotations and the response of ions from the lunar exosphere, we can place constraints on the composition of the ions. Acceleration, Reconnection, Turbulence, and Electrodynamics of Moon's Interaction with the Sun (ARTEMIS) provides an ideal platform to utilize such an analysis, since its two-probe vantage allows precise timing of the propagation of field discontinuities in the solar wind, and its sensitive plasma instruments can detect the ion response. We demonstrate the utility of this technique by using fully time-dependent charged particle tracing to analyze several minutes of ion observations taken by the two ARTEMIS probes ~3000-5000 km above the dusk terminator on 25 January 2014. The observations from this time period allow us to reach several interesting conclusions. The ion production at altitudes of a few hundred kilometers above the sunlit surface of the Moon has an unexpectedly significant contribution from species with masses of 40 amu or greater. The inferred distribution of the neutral source population has a large scale height, suggesting that micrometeorite impact vaporization and/or sputtering play an important role in the production of neutrals from the surface. Our observations also suggest an asymmetry in ion production, consistent with either a compositional variation in neutral vapor production or a local reduction in solar wind sputtering in magnetic regions of the surface.

Moon↗

Inertial Centrifugal-Based Pre-filter for Spacecraft Life Support Systems

The intrusion of planetary dust inside space vehicles on future Lunar missions may lead to performance compromises of the cabin air-filtration system. The evasive character of the fine planetary dust, in particular lunar dust, could enable the dust to make its way through the seals and barriers of the EVA hatches and become airborne in the cabin. This can result in performance and capacity overload of the high efficiency filter media and particle separation systems. Adequate pre-filtration can substantially reduce the load on the higher efficiency components leading to smaller dust loads during surge and nominal dust loading conditions, thereby protecting and extending the life of these components. A particle separation concept, based on centrifugal separation, is being investigated for its application as a pre-filter. The concept has previously been proposed for application in the aircraft engine industry, as means of capturing corrosive dust and salt deposits that may harm the engine. The technique has the advantages of being passive, integrable to HVAC and space vehicle architecture, and has the potential for high degree of particle separation with proper fluid dynamic design. Computational Fluid Dynamics (CFD) and particle tracing modeling were used to arrive at an initial design for rapid prototyping and testing. If feasible, the concept can be integrated to the Scroll Filter System which is being developed by NASA to address the filtration demands on long during spaceflight and surface missions. This paper will describe the modeling results of this concept.

Life Support Systems↗

Inertial Centrifugal-Based Pre-filter for Spacecraft Life Support Systems

The intrusion of planetary dust inside space vehicles on future Lunar missions may lead to performance compromises of the cabin air-filtration system. The evasive character of the fine planetary dust, in particular lunar dust, could enable the dust to make its way through the seals and barriers of the EVA hatches and become airborne in the cabin. This can result in performance and capacity overload of the high efficiency filter media and particle separation systems. Adequate pre-filtration can substantially reduce the load on the higher efficiency components leading to smaller dust loads during surge and nominal dust loading conditions, thereby protecting and extending the life of these components. A particle separation concept, based on centrifugal separation, is being investigated for its application as a pre-filter. The concept has previously been proposed for application in the aircraft engine industry, as means of capturing corrosive dust and salt deposits that may harm the engine. The technique has the advantages of being passive, integrable to HVAC and space vehicle architecture, and has the potential for high degree of particle separation with proper fluid dynamic design. Computational Fluid Dynamics (CFD) and particle tracing modeling were used to arrive at an initial design for rapid prototyping and testing. If feasible, the concept can be integrated to the Scroll Filter System which is being developed by NASA to address the filtration demands on long during spaceflight and surface missions. This paper will describe the modeling results of this concept.

Life Support Systems↗

Lunar Gateway Charging and Effects on Low-Energy Electron Measurements

The Electron Electrostatic Analyzer (EEA) is part of the HERMES instrument suite on Lunar Gateway and is designed to measure electrons in the energy range from 1 eV to 18 keV. Electrons in this range can be deflected or blocked from entering a detector by electric fields from a charged spacecraft platform, so many heliophysics missions (MMS, Cluster, etc.) use active potential control to minimize stray electric fields which would corrupt low-energy plasma measurements. Gateway, however, does not have such capabilities so the surface charging effects will influence the electron data. Further, some elements of Gateway partially block the instrument’s field of view to space. The effects of the Gateway platform on the low-energy electron population must be understood to maximize the accuracy of the EEA data. To investigate the electrostatic environment near Gateway and its effects on the EEA measurements, we use Nascap-2K to model the expected charging of Gateway under representative solar wind, magnetosheathic, and magnetospheric conditions. Next, we use the potential and electric field outputs from Nascap-2K along with in-house particle tracing codes to investigate how low-energy electrons are perturbed, blocked, or deflected by the spacecraft. We discuss how these perturbations impact the plasma moments computed from the EEA data and possible approaches for correcting the charging effects including application of advanced methods such as neural networks. In addition to electrons from the space environment being influenced by the electrostatic environment around Gateway, photoelectrons generated on Gateway surfaces will also be measured by EEA. We are investigating how knowledge of the potentials of various Gateway surfaces can be extracted from these measured photoelectrons using advanced numerical modeling and analysis. Such information would be valuable for validating charging models and planning mission operations around the platform. Finally, we discuss how the specific workflow developed for Gateway can be extended to a generalized process that is applicable to other future missions. As the space industry prepares for human exploration beyond low-Earth orbit, the need to obtain accurate space weather data from rideshare science payloads is critical. Our process for removing platform effects from the science data serves as a pathfinder for leveraging advanced simulations to maximize science returns and ensure the safety and success of future crewed missions.

Miles Bengtson↗

Agricultural Fires in the Southeastern U.S. During SEAC4RS: Emissions of Trace Gases and Particles and Evolution of Ozone, Reactive Nitrogen, and Organic Aerosol

Emissions from 15 agricultural fires in the southeastern U.S. were measured from the NASA DC-8 research aircraft during the summer 2013 Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) campaign. This study reports a detailed set of emission factors (EFs) for 25 trace gases and 6 fine particle species. The chemical evolution of the primary emissions in seven plumes was examined in detail for ~1.2 h. A Lagrangian plume cross-section model was used to simulate the evolution of ozone (O3), reactive nitrogen species, and organic aerosol (OA). Observed EFs are generally consistent with previous measurements of crop residue burning, but the fires studied here emitted high amounts of SO2 and fine particles, especially primary OA and chloride. Filter-based measurements of aerosol light absorption implied that brown carbon (BrC) was ubiquitous in the plumes. In aged plumes, rapid production of O3, peroxyacetyl nitrate (PAN), and nitrate was observed with (Delta)O3/(Delta)CO, (Delta)PAN/(Delta)NOy, and (Delta)nitrate/(Delta)NOy reaching approx. 0.1, approx. 0.3, and approx.0.3. For five selected cases, the model reasonably simulated O3 formation but underestimated PAN formation. No significant evolution of OA mass or BrC absorption was observed. However, a consistent increase in oxygen-to-carbon (O/C) ratios of OA indicated that OA oxidation in the agricultural fire plumes was much faster than in urban and forest fire plumes. Finally, total annual SO2, NOx, and CO emissions from agricultural fires in Arkansas, Louisiana, Mississippi, and Missouri were estimated (within a factor of approx. 2) to be equivalent to approx. 2% SO2 from coal combustion and approx. 1% NOx and approx. 9% CO from mobile sources.

OA mass or BrC absorption↗

Aircraft measurements of trace gases and particles near the tropopause

Research activities which were performed using atmospheric constituent data obtained by the NASA Global Atmospheric Sampling Program are described. The characteristics of the particle size spectrum in various meteorological settings from a special collection of GASP data are surveyed. The relationship between humidity and cloud particles is analyzed. Climatological and case studies of tropical ozone distributions measured on a large number of flights are reported. Particle counter calibrations are discussed as well as the comparison of GASP particle data in the upper troposphere with other measurements at lower altitudes over the Pacific Ocean.

Falconer, P.↗

Emissions of Trace Gases and Particles from Two Ships in the Southern Atlantic Ocean

Measurements were made of the emissions of particles and gases from two diesel-powered ships in the southern Atlantic Ocean off the coast of Namibia. The measurements are used to derive emission factors from ships of three species not reported previously, namely, black carbon, accumulation-mode particles, and cloud condensation nuclei (CCN), as well as for carbon dioxide, carbon monoxide (CO), methane (CH4), non-methane hydrocarbons, sulfur dioxide (SO2), nitrogen oxides (NOx), and condensation nuclei. The effects of fuel grade and engine power on ship emissions are discussed. The emission factors are combined with fuel usage data to obtain estimates of global annual emissions of various particles and gases from ocean-going ships. Global emissions of black carbon, accumulation- mode particles, and CCN from ocean-going ships are estimated to be 19-26 Gg yr(sup -1), (4.4-6.1) x 10(exp 26) particles yr(sup -1), and (1.0-1.5) x l0(exp 26) particles yr(sup -1), respectively. Black carbon emissions from ocean-going ships are approximately 0.2% of total anthropogenic emissions. Emissions of NOx and SO2 from ocean-going ships are approximately 10-14% and approximately 3-4%, respectively, of the total emissions of these species from the burning of fossil fuels, and approximately 40% and approximately 70%, respectively, of the total emissions of these species from the burning of biomass. Global annual emissions of CO and CH4 from ocean-going ships are approximately 2% and approximately 2-5%, respectively, of natural oceanic emissions of these species.

Sinha, Parikhit↗

Emissions of Trace Gases and Particles from Savanna Fires in Southern Africa

Airborne measurements made on initial smoke from 10 savanna fires in southern Africa provide quantitative data on emissions of 50 gaseous and particulate species, including carbon dioxide, carbon monoxide, sulfur dioxide, nitrogen oxides, methane, ammonia, dimethyl sulfide, nonmethane organic compounds, halocarbons, gaseous organic acids, aerosol ionic components, carbonaceous aerosols, and condensation nuclei (CN). Measurements of several of the gaseous species by gas chromatography and Fourier transform infrared spectroscopy are compared. Emission ratios and emission factors are given for eight species that have not been reported previously for biomass burning of savanna in southern Africa (namely, dimethyl sulfide, methyl nitrate, five hydrocarbons, and particles with diameters from 0.1 to 3 microns). The emission factor that we measured for ammonia is lower by a factor of 4, and the emission factors for formaldehyde, hydrogen cyanide, and CN are greater by factors of about 3, 20, and 3 - 15, respectively, than previously reported values. The new emission factors are used to estimate annual emissions of these species from savanna fires in Africa and worldwide.

Sinha, Parikhit↗

Cosmic ray particle dosimetry and trajectory tracing

Five pocket mice (Perognathus longimembris) were flown on Apollo XVII, each with a solid-state (plastic) nuclear track detector implanted beneath its scalp. The subscalp detectors were sensitive to HZE cosmic ray particles with a LET greater than or approximately equal to 0.15 million electron volts per micrometer (MeV/micron). A critical aspect of the dosimetry of the experiment involved tracing individual particle trajectories through each mouse head from particle tracks registered in the individual subscalp detectors, thereby establishing a one-to-one correspondence between a trajectory location in the tissue and the presence or absence of a lesion. The other major aspect was the identification of each registered particle. An average of 16 particles with Z greater than or equal to 6 and 2.2 particles with Z greater than or equal to 20 were found per detector. The track density, 29 tracks/sq cm, when adjusted for detection volume, was in agreement with the photographic emulsion data from an area dosimeter located next to the flight package.

Cruty, M. R.↗

Water and acid soluble trace metals in atmospheric particles

Continental aerosols are collected above a deciduous forest in eastern Tennessee and subjected to selective extractions to determine the water-soluble and acid-leachable concentrations of Cd, Mn, Pb, and Zn. The combined contributions of these metals to the total aerosol mass is 0.5 percent, with approximately 70 percent of this attributable to Pb alone. A substantial fraction (approximately 50 percent or more) of the acid-leachable metals is soluble in distilled water. In general, this water-soluble fraction increases with decreasing particle size and with increasing frequency of atmospheric water vapor saturation during the sampling period. The pattern of relative solubilities (Zn being greater than Mn, which is approximately equal to Cd, which is greater than Pb) is found to be similar to the general order of the thermodynamic solubilities of the most probable salts of these elements in continental aerosols with mixed fossil fuel and soil sources.

Lindberg, S. E.↗

Interplanetary dust - Trace element analysis of individual particles by neutron activation

Although micrometeorites of cometary origin are thought to be the dominant component of interplanetary dust, it has never been possible to positively identify such micrometer-sized particles. Two such particles have been identified as definitely micrometeorites since their abundances of volatile and nonvolatile trace elements closely match those of primitive solar system material.

Ganapathy, R.↗

El Chichon - Composition of plume gases and particles

Aircraft measurements were made of trace gases, atmospheric particles, and condensed acid volatiles in the plume of El Chichon volcano, Chiapas, Mexico, in November 1982. Hydrogen sulfide was the primary gaseous sulfur species in the plume at the time of collection. Concentrations of 28 elements were determined by neutron activation analysis of particulate material from the plume. The volatile elements sulfur, chlorine, arsenic, selenium, bromine, antimony, iodine, tungsten, and mercury were enriched relative to bulk pyroclastic material by factors of 60 to 20,000. Arsenic, antimony, and selenium were associated predominantly with small (not greater than 3 micrometer) particles. Calcium and sodium were present almost exclusively on larger particles and aluminum and manganese were bimodally distributed. Ashladen particulate material injected into the stratosphere during the early violent eruptions was enriched by factors of 10 to 30 relative to ash in some of the same elements observed in the quiescent plume.

Kotra, J. P.↗

Visualizing turbulent mixing of gases and particles

A physical model and interactive computer graphics techniques have been developed for the visualization of the basic physical process of stochastic dispersion and mixing from steady-state CFD calculations. The mixing of massless particles and inertial particles is visualized by transforming the vector field from a traditionally Eulerian reference frame into a Lagrangian reference frame. Groups of particles are traced through the vector field for the mean path as well as their statistical dispersion about the mean position by using added scalar information about the root mean square value of the vector field and its Lagrangian time scale. In this way, clouds of particles in a turbulent environment are traced, not just mean paths. In combustion simulations of many industrial processes, good mixing is required to achieve a sufficient degree of combustion efficiency. The ability to visualize this multiphase mixing can not only help identify poor mixing but also explain the mechanism for poor mixing. The information gained from the visualization can be used to improve the overall combustion efficiency in utility boilers or propulsion devices. We have used this technique to visualize steady-state simulations of the combustion performance in several furnace designs.

Ma, Kwan-Liu↗

Emissions from Miombo Woodland and Dambo Grassland Savanna Fires

Airborne measurements of trace gases and particles over and downwind of two prescribed savanna fires in Zambia are described. The measurements include profiles through the smoke plumes of condensation nucleus concentrations and normalized excess mixing ratios of particles and gases, emission factors for 42 trace gases and seven particulate species, and vertical profiles of ambient conditions. The fires were ignited in plots of miombo woodland savanna, the most prevalent savanna type in southern Africa, and dambo grassland savanna, an important enclave of miombo woodland ecosystems. Emission factors for the two fires are combined with measurements of fuel loading, combustion factors, and burned area (derived from satellite burn scar retrievals) to estimate the emissions of trace gases and particles from woodland and grassland savanna fires in Zambia and southern Africa during the dry season (May-October) of 2000. It is estimated that the emissions of CO2, CO, total hydrocarbons, nitrogen oxides (NOx as NO), sulfur dioxide (SO2), formaldehyde, methyl bromide, total particulate matter, and black carbon from woodland and grassland savanna fires during the dry season of 2000 in southern Africa contributed 12.3%, 12.6%, 5.9%, 10.3%, 7.5%, 24.2%, 2.8%, 17.5%, and 11.1%, respectively, of the average annual emissions from all types of savanna fires worldwide. In 2000 the average annual emissions of methane, ethane, ethene, acetylene, propene, formaldehyde, methanol, and acetic acid from the use of biofuels in Zambia were comparable to or exceeded dry season emissions of these species from woodland and grassland savanna fires in Zambia.

Sinha, Parikhit↗

Automated Machine Learning to Evaluate the Information Content of Tropospheric Trace Gas Columns for Fine Particle Estimates Over India: A Modeling Testbed

India is largely devoid of high-quality and reliable on-the-ground measurements of fine particulate matter (PM 2.5 ). Ground-level PM 2.5 concentrations are estimated from publicly available satellite Aerosol Optical Depth (AOD) products combined with other information. Prior research has largely overlooked the possibility of gaining additional accuracy and insights into the sources of PM using satellite retrievals of tropospheric trace gas columns. We evaluate the information content of tropospheric trace gas columns for PM 2.5 estimates over India within a modeling testbed using an Automated Machine Learning (AutoML) approach, which selects from a menu of different machine learning tools based on the data set. We then quantify the relative information content of tropospheric trace gas columns, AOD, meteorological fields, and emissions for estimating PM 2.5 over four Indian sub-regions on daily and monthly time scales. Our findings suggest that, regardless of the specific machine learning model assumptions, incorporating trace gas modeled columns improves PM 2.5 estimates. We use the ranking scores produced from the AutoML algorithm and Spearman’s rank correlation to infer or link the possible relative importance of primary versus secondary sources of PM 2.5 as a first step toward estimating particle composition. Our comparison of AutoML-derived models to selected baseline machine learning models demonstrates that AutoML is at least as good as user-chosen models. The idealized pseudo-observations (chemical-transport model simulations) used in this work lay the groundwork for applying satellite retrievals of tropospheric trace gases to estimate fine particle concentrations in India and serve to illustrate the promise of AutoML applications in atmospheric and environmental research.

Machine learning↗