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NASA NTRS1988

Effects of hemorrhagic hypotension on tyrosine concentrations in rat spinal cord and plasma

Tyrosine is the precursor for catecholamine neurotransmitters. When catecholamine-containing neurons are physiologically active (as sympathoadrenal cells are in hypotension), tyrosine administration increases catecholamine synthesis and release. Since hypotension can alter plasma amino acid composition, the effects of an acute hypotensive insult on tyrosine concentrations in plasma and spinal cord were examined. Rats were cannulated and bled until the systolic blood pressure was 50 mmHg, or were kept normotensive for 1 h. Tyrosine and other large neutral amino acids (LNAA) known to compete with tyrosine for brain uptake were assayed in plasma and spinal cord. The rate at which intra-arterial (H-3)tyrosine disappeared from the plasma was also estimated in hemorrhaged and control rats. In plasma of hemorrhaged animals, both the tyrosine concentration and the tyrosine/LNAA ratio was elevated; moreover, the disappearance of (H-3)tyrosine was slowed. Tyrosine concentrations also increased in spinal cords of hemorrhaged-hypotensive rats when compared to normotensive controls. Changes in plasma amino acid patterns may thus influence spinal cord concentrations of amino acid precursors for neurotransmitters during the stress of hemorrhagic shock.

Conlay, L. A.↗

NASA NTRS1994

The active titration method for measuring local hydroxyl radical concentration

We are developing a method for measuring ambient OH by monitoring its rate of reaction with a chemical species. Our technique involves the local, instantaneous release of a mixture of saturated cyclic hydrocarbons (titrants) and perfluorocarbons (dispersants). These species must not normally be present in ambient air above the part per trillion concentration. We then track the mixture downwind using a real-time portable ECD tracer instrument. We collect air samples in canisters every few minutes for roughly one hour. We then return to the laboratory and analyze our air samples to determine the ratios of the titrant to dispersant concentrations. The trends in these ratios give us the ambient OH concentration from the relation: dlnR/dt = -k(OH). A successful measurement of OH requires that the trends in these ratios be measureable. We must not perturb ambient OH concentrations. The titrant to dispersant ratio must be spatially invariant. Finally, heterogeneous reactions of our titrant and dispersant species must be negligible relative to the titrant reaction with OH. We have conducted laboratory studies of our ability to measure the titrant to dispersant ratios as a function of concentration down to the few part per trillion concentration. We have subsequently used these results in a gaussian puff model to estimate our expected uncertainty in a field measurement of OH. Our results indicate that under a range of atmospheric conditions we expect to be able to measure OH with a sensitivity of 3x10(exp 5) cm(exp -3). In our most optimistic scenarios, we obtain a sensitivity of 1x10(exp 5) cm(exp -3). These sensitivity values reflect our anticipated ability to measure the ratio trends. However, because we are also using a rate constant to obtain our (OH) from this ratio trend, our accuracy cannot be better than that of the rate constant, which we expect to be about 20 percent.

Sprengnether, Michele↗

DOE OSTI2022

Plasma diagnostics and modeling of lithium-containing plasmas

Thin-film deposition from chemically reactive multi-component plasmas is complex, and the lack of electron collision cross-sections for even the most common metalorganic precursors and their fragments complicates their modeling based on fundamental plasma physics. This study focuses on understanding the plasma physics and chemistry in argon (Ar) plasmas containing lithium bis (trimethylsilyl) amide used to deposit Li x Si y thin films. These films are emerging as potential solid electrolytes for lithium-ion batteries, and the Li-to-Si ratio is a crucial parameter to enhance their ionic conductivity. We deposited Li x Si y films in an axial flow-through plasma reactor and studied the factors that determine the variation of the Li-to-Si ratio in films deposited at various points on a substrate spanning the entire reactor axis. While the Li-to-Si ratio is 1:2 in the precursor, the Li-to-Si ratio is as high as 3:1 in films deposited near the plasma entrance and decreases to 1:1 for films deposited downstream. Optical emission from the plasma is dominated by Li emission near the entrance, but Li emission disappears downstream, which we attribute to the complete consumption of the precursor. We hypothesized that the axially decreasing precursor concentration affects the electron energy distribution function in a way that causes different dissociation efficiencies for the production of Li and Si. We used Li line intensities to estimate the local precursor concentration and Ar line ratios to estimate the local reduced electric field to test this hypothesis. This analysis suggests that the mean electron energy increases along the reactor axis with decreasing precursor concentration. As a result, the decreasing Li-to-Si ratio with axially decreasing precursor concentration may be explained by Li release from the precursor having lower threshold energy than Si release.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Aqueous phosphate detection using Eu(acac) 3

Currently, the majority of phosphate-sensitive phosphors reported in literature are metal-based complexes that require complicated and expensive synthesis to prepare. Here, in this study, we investigate the phosphate detecting capabilities of an inexpensive off-the-shelf phosphor: Eu(acac) 3 . We characterize its phosphate sensitivity as a function of sensor concentration and find that the quenching coefficient is inversely proportional to sensor concentration. This results in the limit-of-detection scaling linearly with sensor concentration. We determine its concentration-independent sensitivity to be 1.558 ± 0.012, which results in our lowest sensor concentration (44 μM) having a limit-of-detection of 3.39 ± 0.68 μM. We also find that for phosphate concentrations less than the sensor concentration, the fluorescence intensity ratio behaves linearly, but transitions to a non-linear functionality as the phosphate concentration exceeds the sensor concentration.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1986

Meal composition and plasma amino acid ratios: Effect of various proteins or carbohydrates, and of various protein concentrations

The effects of meals containing various proteins and carbohydrates, and of those containing various proportions of protein (0 percent to 20 percent of a meal, by weight) or of carbohydrate (0 percent to 75 percent), on plasma levels of certain large neutral amino acids (LNAA) in rats previously fasted for 19 hours were examined. Also the plasma tryptophan ratios (the ratio of the plasma trytophan concentration to the summed concentrations of the other large neutral amino acids) and other plasma amino acid ratios were calculated. (The plasma tryptophan ratio has been shown to determine brain tryptophan levels and, thereby, to affect the synthesis and release of the neurotransmitter serotonin). A meal containing 70 percent to 75 percent of an insulin-secreting carbohydrate (dextrose or dextrin) increased plasma insulin levels and the tryptophan ratio; those containing 0 percent or 25 percent carbohydrate failed to do so. Addition of as little as 5 percent casein to a 70 percent carbohydrate meal fully blocked the increase in the plasma tryptophan ratio without affecting the secretion of insulin - probably by contributing much larger quantities of the other LNAA than of tryptophan to the blood. Dietary proteins differed in their ability to suppress the carbohydrate-induced rise in the plasma tryptophan ratio. Addition of 10 percent casein, peanut meal, or gelatin fully blocked this increase, but lactalbumin failed to do so, and egg white did so only partially. (Consumption of the 10 percent gelatin meal also produced a major reduction in the plasma tyrosine ratio, and may thereby have affected brain tyrosine levels and catecholamine synthesis.) These observations suggest that serotonin-releasing neurons in brains of fasted rats are capable of distinguishing (by their metabolic effects) between meals poor in protein but rich in carbohydrates that elicit insulin secretion, and all other meals. The changes in brain serotonin caused by carbohydrate-rich, protein-poor meals may affect subsequent food choice and various serotonin-mediated behaviors.

Yokogoshi, Hidehiko↗

NASA NTRS1994

A double-moment multiple-phase four-class bulk ice scheme, Part 1: Description

A detailed ice-phase bulk microphysical scheme has been developed for simulating the hydrometeor distributions of convective and stratiform precipitation in different large-scale environmental conditions. The proposed scheme involves 90 distinct microphysical processes, which predict the mixing ratios and the number concentrations of small ice crystals, snow, graupel, and frozen drops/hail, as well as the mixing ratios of liquid water on wet precipitation ice (snow, graupel, frozen drops). The number of adjustable coefficients has been significantly reduced in comparison with other bulk schemes. Additional improvements have been made to the parameterization in the following areas: (1) representing small ice crystals with nonzero terminal fall velocities and dispersive size distributions, (2) accurate and computationally efficient calculations of precipitation collection processes, (3) reformulating the collection equation to prevent unrealistically large accretion rates, (4) more realistic conversion by riming between different classes of precipitation ice, (5) preventing unrealistically large rates of raindrop freezing and freezing of liquid water on ice, (6) detailed treatment of various rime-splintering ice multiplication mechanisms, (7) a simple representation of the Hobbs-Rangno ice enhancement process, (8) aggregation of small ice crystals and snow, and (9) allowing explicit competition between cloud water condensation and ice deposition rates rather than using saturation adjustment techniques. For the purposes of conserving the higher moments of the particle distributions, preserving the spectral widths (or slopes) of the particle spectra is shown to be more important than strict conservation of particle number concentration when parameterizing changes in ice-particle number concentrations due to melting, vapor transfer processes (sublimation of dry ice, evaporation from wet ice), and conversion between different hydrometeor species. The microphysical scheme is incorporated into a nonhydrostatic cloud model in Part 2 of this study. The model performed well in simulating the radar and microphysical structures of a midlatitude-continental squall lines and a tropical-maritime squall system with minimal tuning of the parameterization, even though the vertical profiles of radar reflectivity differed substantially between these storms.

Ferrier, Brad Shoenberg↗

DOE OSTI2023

Characterization of polysaccharide from Lonicera japonica Thunb leaves and its application in nano-emulsion

The polysaccharides in honeysuckle leaves (PHL) were separated and characterized for the first time. The nano-emulsion stabilized by PHL and whey protein isolate (WPI) were also fabricated based on the ultrasonic method. The results indicated that PHL was mainly composed of glucose (47.40 mol%), galactose (19.21 mol%) and arabinose (20.21 mol%) with the weight-average molecular weight of 137.97 ± 4.31 kDa. The emulsifier concentration, WPI-to-PHL ratio, ultrasound power and ultrasound time had significant influence on the droplet size of PHL-WPI nano-emulsion. The optimal preparation conditions were determined as following: emulsifier concentration, 1.7%; WPI/PHL ratio, 3:1; ultrasonic power, 700 W; ultrasonic time, 7 min. Under the above conditions, the median diameter of the obtained nano-emulsion was 317.70 ± 5.26 nm, close to the predicted value of 320.20 nm. The protective effect of PHL-WPI emulsion on β-carotene against UV irradiation was superior to that of WPI emulsion. Our results can provide reference for the development of honeysuckle leaves.

Li, Yongchao↗

NASA NTRS1987

Diverse eucritic pebbles in the Vaca Muerta mesosiderite

Seven 5-cm basaltic pebbles from the Vaca Muerta mesosiderite were studied by neutron activation and electron microprobe analysis, and three additional pebbles were studied petrographically. The cumulate pebbles had low REE concentrations and high Eu/Sm ratios, indicating the absence of intercumulus liquid. Siderophile interelement ratios were similar to those found in Vaca Muerta metal except for anomalously low Ir concentrations. The presence of 20 percent impact-melt breccias among the pebbles and 35-40 percent melt breccias among the mesosiderite whole-rocks suggests that the mesosiderites were more extensively impact melted than the howardites. Three alternative models to explain this greater proportion of impact-melted material among the mesosiderites are proposed.

Rubin, Alan E.↗

NASA NTRS1987

C-13/C-12 ratio in methane from the flooded Amazon forest

The C1-C4 hydrocarbon concentrations and the C-13/C-12 ratio in CH4 detected in air samples collected in the Amazon region (3.5 deg S latitude and 5.9 deg W longitude) are analyzed. It is observed that the CH4 concentrations of each sample are enhanced over the background concentration for remote locations, and the C-13/C-12 ratio in this biogenic methane is depleted in C-13 relative to atmospheric CH4. It is concluded, from the C2-C4 hydrocarbon data, that minor yields of C2-C4 hyrocarbons are released coincident with CH4; however, the minor yields do not contribute to the regionally enhanced concentrations of hydrocarbons found in Amazonia and the global atmosphere release of C2-C4 compounds.

Tyler, Stanley C.↗

NASA NTRS2005

Fabrication and Probabilistic Fracture Strength Prediction of High-Aspect-Ratio Single Crystal Silicon Carbide Microspecimens With Stress Concentration

Single crystal silicon carbide micro-sized tensile specimens were fabricated with deep reactive ion etching (DRIE) in order to investigate the effect of stress concentration on the room-temperature fracture strength. The fracture strength was defined as the level of stress at the highest stressed location in the structure at the instant of specimen rupture. Specimens with an elliptical hole, a circular hole, and without a hole (and hence with no stress concentration) were made. The average fracture strength of specimens with a higher stress concentration was larger than the average fracture strength of specimens with a lower stress concentration. Average strength of elliptical-hole, circular-hole, and without-hole specimens was 1.53, 1.26, and 0.66 GPa, respectively. Significant scatter in strength was observed with the Weibull modulus ranging between 2 and 6. No fractographic examination was performed but it was assumed that the strength controlling flaws originated from etching grooves along the specimen side-walls. The increase of observed fracture strength with increasing stress concentration was compared to predictions made with the Weibull stress-integral formulation by using the NASA CARES/Life code. In the analysis isotropic material and fracture behavior was assumed - hence it was not a completely rigorous analysis. However, even with these assumptions good correlation was achieved for the circular-hole specimen data when using the specimen data without stress concentration as a baseline. Strength was over predicted for the elliptical-hole specimen data. Significant specimen-to-specimen dimensional variation existed in the elliptical-hole specimens due to variations in the nickel mask used in the etching. To simulate the additional effect of the dimensional variability on the probabilistic strength response for the single crystal specimens the ANSYS Probabilistic Design System (PDS) was used with CARES/Life.

Nemeth, Noel N.↗

DOE OSTI2021

Measurement of material isotopics and atom number ratio with α-particle spectroscopy for a NIFFTE fission Time Projection Chamber actinide target

In this work, we present the results of a measurement of isotopic concentrations and atomic number ratio of a double-sided actinide target using α-spectroscopy and mass spectrometry. The double-sided actinide target, with predominantly 239 Pu on one side and 235 U on the other, was used in the fission Time Projection Chamber (fissionTPC) for a measurement of the neutron-induced fission cross-section ratio between the two isotopes. The measured atomic number ratio is needed to extract an absolute measurement fission cross-section ratio. The 239 Pu/ 235 U atom number ratio was measured with a combination of mass spectrometry and α-spectroscopy with a planar silicon detector achieving uncertainties of less than 1%. Different strategies for estimating isotopic concentration from the α-spectrum are presented to demonstrate the potential of these methods for non-destructive target assay. We found that a combination of fitting spectra with constraints from mass spectrometry, and summing counts in a region of the spectrum provided the most consistent results with the lowest uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Oxidation of Glycolate in the Defense Waste Processing Facility (DWPF) Recycle Collection Tank - 20305

The Savannah River Site's Defense Waste Processing Facility (DWPF) operations are being upgraded with the introduction of the Nitric-Glycolic Flowsheet. Glycolic acid has been shown superior to formic acid as the reducing acid used during chemical processing. The new flowsheet improves or maintains necessary parameters such as 1) reduction of mercury, 2) adjustment of feed rheology and 3) adjustment of melter oxidation/reduction potential. Further, the potential for catalytic hydrogen generation in DWPF processing is virtually eliminated. DWPF process condensates are collected and returned to the SRS Concentration, Storage and Transfer Facilities (CSTF). The Recycle Collection Tank (RCT) collects off-gas condensate during chemical processing, vitrification, and other unit operations performed in DWPF and is the singular return vessel delivering recycle effluent back to CSTF. Each batch of recycle may contain a small amount of glycolate from chemical processing and melter off-gas condensates. To avoid potential flammability issues due to thermolysis of glycolate in the CSTF, chemical oxidation within the RCT has been investigated as an option for mitigating the transfer of glycolate. Sodium permanganate has been down-selected as the best option for oxidation of glycolate. Testing was performed using both 2-L and 22-L reactors (16,800:1 and 1,530:1 scale by volume) with non-radioactive waste simulants to approximate the expected RCT compositions. RCT simulants were evaluated at various process pH and temperature conditions. Also, RCT operations, namely the sequence of addition of corrosion inhibitors (NaOH and NaNO{sub 2}) versus a permanganate strike, were evaluated. Glycolate was introduced via a sludge simulant to mimic both expected entrainment and abnormal process foam-over conditions - the range being between 68 and 5100 mg/kg glycolate. Glycolate destruction was monitored by ion chromatography (IC). The corresponding manganese behavior was monitored in real-time using in situ ultraviolet-visible (UV-Vis) spectroscopy. RCT glycolate content can be reduced to below the IC detection limit within 90 minutes for all concentrations investigated. Ion Chromatography analysis revealed that under alkaline conditions, glycolate is primarily oxidized to oxalate with no significant formation of CO{sub 2} or carbonate, and nitrite is not oxidized to nitrate. Initially, complete oxidation of organics species and nitrite was assumed. Determination of the mechanistic chemical reaction has allowed the required amount of permanganate to be more accurately predicted and the total addition to be significantly reduced. UV-Vis measurements reveal that permanganate (Mn{sup 7+}) is reduced to manganate (Mn{sup 6+}) in the RCT. The oxidant stoichiometry is defined by using the initial permanganate to glycolate (P/G) molar ratio. At low initial glycolate concentration (68 and 140 mg/kg), the minimum required initial permanganate to glycolate (P/G) molar ratio was found to be 5-6. With high initial glycolate concentrations (5100 mg/kg) a lower (P/G) molar ratio of ∼2.5 was needed. The final portion of this effort supporting the nitric/glycolic flowsheet will be to test actual (fully radioactive) RCT samples as per the above simulant tests. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1992

Stress concentrations for straight-shank and countersunk holes in plates subjected to tension, bending, and pin loading

A three dimensional stress concentration analysis was conducted on straight shank and countersunk (rivet) holes in a large plate subjected to various loading conditions. Three dimensional finite element analysis were performed with 20 node isoparametric elements. The plate material was assumed to be linear elastic and isotropic, with a Poisson ratio of 0.3. Stress concentration along the bore of the hole were computed for several ratios of hole radius to plate thickness (0.1 to 2.5) and ratios of countersink depth to plate thickness (0.25 to 1). The countersink angles were varied from 80 to 100 degrees in some typical cases, but the angle was held constant at 100 degrees for most cases. For straight shank holes, three types of loading were considered: remote tension, remote bending, and wedge loading in the hole. Results for remote tension and wedge loading were used to estimate stress concentration for simulated rivet in pin loading. For countersunk holes only remote tension and bending were considered. Based on the finite element results, stress concentration equations were developed. Whenever possible, the present results were compared with other numerical solutions and experimental results from the literature.

Shivakumar, K. N.↗

DOE OSTI2026

Unraveling In-Situ Formation of Surface Nickel Nitride Structures in Plasma-Assisted Catalytic Ammonia Synthesis

We report the in situ formation of Ni nitride for plasma-assisted ammonia synthesis. Both the surface nitrogen concentration and the ammonia formation rate exhibit dependence on the N 2 :H 2 feed ratio. The maximum surface nitrogen concentration occurs at a N 2 :H 2 ratio of 4:1, and the maximum catalytic activity occurs at 2:1. In contrast, the formation of gas phase radicals is less sensitive to feed composition, indicating that Ni nitride is more kinetically relevant to ammonia production than gas-phase radicals. The plasma-induced formation of Ni nitride is therefore proposed to be a critical contributor to the synergistic effects in plasma-assisted catalytic ammonia synthesis. Additionally, Ni nitride alters the surface reaction mechanism of plasma-assisted ammonia synthesis, with the rate-determining-step (RDS) shifting to surface-bound NH 3 formation rather than N 2 activation at temperatures below 373 K. These findings provide mechanistic insight that opens opportunities for optimizing the performance of plasma-assisted catalytic ammonia synthesis

Ammonia↗

NASA NTRS1975

The provenance of metal in anorthositic rocks

Calculated compositions for metal crystallized from anorthositic melt rocks or feldspathic basalts such as 14310, 68415, and 77017 are (1) meteoritic in the initial stages or if metal is the only phase crystallized, and (2) higher in Co than meteoritic metal as a result of fractional crystallization of metals and silicates. Metal in coarse anorthositic rocks 15415, 15455, 60015, 64435, and 78238 is not of meteoritic composition and has Co contents from 0 to 9% with a Ni/Co ratio of about 1. The formation of anorthosites and the composition of the earliest metal are discussed with attention to Ni concentrations and the Ni/Co ratio. It is shown that anorthositic hornfels and breccias contain metal of a composition not found in their source material, coarse anorthosite; it is suggested that the hornfels includes metal grains probably derived with little change in composition from ancient meteorites.

Hewins, R. H.↗

DOE OSTI2021

Alignment of Au nanorods along de novo designed protein nanofibers studied with automated image analysis

In this paper, we focus on exploring the directional assembly of anisotropic Au nanorods along de novo designed 1D protein nanofiber templates. Using machine learning and automated image processing, we analyze scanning electron microscopy (SEM) images to study how the attachment density and alignment fidelity are influenced by variables such as the aspect ratio of the Au nanorods, and the salt concentration of the solution. We find that the Au nanorods prefer to align parallel to the protein nanofibers. This preference decreases with increasing salt concentration, but is only weakly sensitive to the nanorod aspect ratio. While the overall specific Au nanorod attachment density to the protein fibers increases with increasing solution ionic strength, this increase is dominated primarily by non-specific binding to the substrate background, and we find that greater specific attachment (nanorods attached to the nanofiber template as compared to the substrates) occurs at the lower studied salt concentrations, with the maximum ratio of specific to non-specific binding occurring when the protein fiber solutions are prepared in 75 mM NaCl concentration.

36 MATERIALS SCIENCE↗

DOE OSTI2022

USE OF TWO-PISTON SPLAT QUENCHING TO INVESTIGATE & CHARACTERIZE THE IMPACT OF COMPOSITIONAL VARIATIONS ON RAPID SOLIDIFICATION MICROSTRUCTURES & SUB-MICROSCALE FEATURES IN STAINLESS STEEL ALLOY.

The objective of this dissertation was to use two-piston splat quenching (SQ) to investigate the impact of compositional modifications on the solidification and microstructure of rapidly solidified austenitic stainless steels (SS) and to demonstrate the ability of SQ to quickly and effectively simulate rapid solidification conditions similar to those found in powder bed fusion (PBF) additive techniques. PBF techniques like laser powder bed fusion (LPBF) are being implemented across a breadth of research and industrial applications to create parts with complex geometries and performance capabilities while pushing the current limits of processing conditions and understanding of material systems. In this work, SQ was used to experimentally produce rapid solidification in 20+ unique austenitic SS compositions with systematic variations of the chrome and nickel equivalency ratio (Cr/Nieq) through targeted compositional modifications. From the targeted change of Cr, Ni, and Mo concentrations in rapidly solidified SS alloys, the ferrite solidification mode was found to be the primary solidification mode at significantly lower Cr/Nieq than previously predicted for RS. Also, decreasing concentrations of Fe at a constant Cr/Nieq ratio (i.e., different Fe isopleths), or increased Mo concentrations at a constant Cr/Nieq ratio were found to suppress the ferrite to austenite massive transformation when compared to alloys with lower concentrations at the same Cr/Nieq. Using an established empirical relationship between cell size and cooling rate, the SQ technique was estimated to produce cooling rates between 106 and 108 K/s. Thermal gradients were extracted from 2-D heat transfer simulations of the SQ solidification event and used with these cooling rates to produce solidification rate estimates for SQ which were between 0.4-1.6m/s. The primary solidification mode was observed to be the determining factor in which elements segregated to the cell boundaries during RS, for which Cr and Mo were the main elements to segregate during primary austenite solidification and Ni during primary ferrite solidification. Finally, the solidification rates and conditions produced by SQ experiments resulted in similar microstructures, features, and microsegregation to what was found in LPBF samples of the same feedstock.

Hasenbusch, Zachary↗

NASA NTRSDate not supplied

Using Machine Learning to Estimate Surface-Level SO2 Concentrations from Satellite-Based Measurements

Sulfur dioxide (SO2) is a criteria air pollutant due to its contributions to aerosol formation, rainfall acidification, and harm to human health. The placement of air quality monitoring sites is typically biased towards urban areas, leaving large areas with very limited monitoring data. The Ozone Monitoring Instrument (OMI) has been used to provide estimates of SO2 vertical column densities (VCDs) globally at spatial resolution of 10s of kms once per day. OMI SO2 VCDs have been previously used to estimate surface SO2 concentrations using chemical transport model (CTM) simulations. The CTMs use estimated emissions and assimilated meteorological data, and simulate the chemical and physical processes that determine the vertical profile of SO2, which can be used to derive a ratio between the surface concentrations and VCDs. These models are complex, computationally expensive, and have large uncertainties in the simulated surface-to-VCD ratio due to biases in emissions and relatively coarse resolution. Machine learning techniques are comparatively easier to use, much less computationally expensive to use after training, and can produce more accurate estimations of surface concentrations than the CTM-based method. The interpretation of machine learning models often poses challenges, and in some cases, non-physical variables unrelated to SO2 are used as predictors. In this work, we create an artificial neural network (ANN) to relate OMI retrievals and archived GEOS-FP boundary layer heights to surface SO2 concentrations from the ChinaHighAirPollutants ChinaHighSO2 dataset (CHAP; Wei et al., 2023) on a seasonal average timescale from 2013-2018. Our model only utilizes five variables that are directly relevant to the satellite retrieval, lifetime, and spatial distribution of SO2. The model was trained on 16 seasons (four of each) with independent validation (one of each season) and testing datasets (one of each season) to avoid overfitting. Our ANN generates surface SO2 concentrations that are sensitive (slope = 0.51) and consistent (r = 0.74) with the CHAP data, but are underpredicted by an average of 1.2 ppbv with a mean absolute error of 2.2 ppbv. These results are better than recent studies utilizing the CTM method. To our knowledge, this is the best performing machine learning model that only uses physical variables to predict surface SO2. Our work demonstrates that a carefully constructed, simple ML model can accurately estimate surface-based SO2 concentrations from satellite VCD measurements, and this technique has future promise to expend to newer, higher resolution satellites and other air pollutants.

SO2, air quality, OMI, machine learning↗