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The concentrations and the time development of chlorine and nitrogen trace gases in the Antarctic stratosphere before, during, and after the Airborne Antractic Ozone Experiment (AAOE) were simulated using photochemical models of the Antractic stratosphere during winter/spring. The initial conditions in the calculations were constrained using observations by the AAOE instrument. The comparison of calculated results with the AAOE measurements of HCl and ClO suggest that heterogeneous chemistry was maintained throughout the month of September 1987.
Our study is on the interaction of nitrogen oxides with organics as they are exported from their complex sources in Eastern North America. Both urban and specific industrial emissions contribute the nitrogen of the C-H-O-N compounds that affect the global atmosphere, helping determine both ozone and the self-cleaning radical chemistry of the troposphere mediated by the OH radical. Different industrial sources, urban, and natural emissions contribute the organic C. Peroxyacetyl nitrate, CH3C(double bonds O)OONO2 is the most interesting compound for which we can measure the outflow to the full depth of the Atlantic troposphere. As we adapt the 3-d chemical model to describe outflow for specific periods with sufficient accuracy, we are analyzing some valuable information in the NARE-97 complete airborne dataset. (NARE: North Atlantic Regional Experiment). Ames researchers find that there are substantial puzzles in the ratios of PAN/NO2. Peroxy acetyl nitrate provides one of the major long-distance export pathways for active nitrogen from Eastern North America. It should be closely linked with NO, (defined as the sum NO + NO2) by simple thermal association and decomposition reactions, at least when the ambient temperature is substantially above 5 C.
The mobility of rare earth elements (REE) in natural hydrothermal systems can be assessed using geochemical modeling, which requires reliable thermodynamic data of relevant aqueous species. In this study, we evaluate the controls of pH and temperature on La speciation and the role of hydroxyl complexes in REE transport at hydrothermal conditions. Batch-type hydrothermal solubility experiments were conducted using synthetic La hydroxide powders equilibrated in perchloric acid-based aqueous solutions at temperatures between 150 and 250 °C and starting pH of 2 to 5. The La hydroxide solubility is retrograde with temperature and displays a strong pH dependence with a decrease in La concentrations from acidic to mildly acidic pH spanning between 3 and 5 orders of magnitude (e.g. log La molality of –2.5 to –7.2 at 250 °C). Thermodynamic optimizations using GEMSFITS allow to retrieve the standard partial molal Gibbs energies for the La 3+ aqua ion and the formation constants for the La hydroxyl species (i.e., LaOH 2+ , La(OH) 2 + , La(OH) 3 0 ) between 25 and 250 °C. A comparison between the experimentally derived thermodynamic properties with the calculated values from the Helgeson-Kirkham-Flowers equation of state parameters indicates an increased divergence with temperature. Discrepancies in standard partial molal Gibbs energies range between ~ 1 – 12 kJ/mol and result in a predicted La hydroxide solubility differing by up to 3 orders of magnitude at 250 °C. Speciation calculations indicate a higher stability of La 3+ and LaOH 2+ over the other La hydroxyl species in the studied pH range of 3.4 to 6. Here, the optimized thermodynamic properties for La aqueous species have important implications for modeling the solubility of REE minerals such as monazite and the mobility of REE in hydrothermal systems.
A three-dimensional thermochemical nonequilibrium model has been developed and applied to the study of entry flows surrounding space vehicles. The model accounts for both chemical and vibrational nonequilibrium phenomena behind the bow shock. The thermodynamic state of a real gas is modeled with a translational-rotational temperature and a electron-vibrational temperature. Their internal energies are averaged to determine the temperature used in the reaction rates calculation. In order to establish the validity of the selected models, both one- and two-temperature models with seven and/or eleven species were investigated. Several numerical experiments that include a sphere, the RAMC vehicle and 3D AFE forebody flows were performed. Preliminary results were compared with RAMC-II experimental data. Good agreement was obtained after a two-temperature model with eleven species and thirty reactions was incorporated into the study.
A one-dimensional hybrid particle code is used to study the interactions between upflowing thermal ions from conjugate ionospheres. The simulation model allows for multiple species, convection of plasmaspheric flux tubes, and Coulomb self-collisions which conserve momentum and energy locally. The model incorporates a variable-flux boundary condition where the flux, at the boundaries, approaches zero as the plasmasphere fills and equilibrium conditions are reached. The effects of two important processes on plasmaspheric refilling have been considered. The first includes convection of the plasmaspheric flux tube. The second is the interaction of ionospheric thermal plasma and particle injection from an external source. Particle injection seems to play an important role in the evolution of the total particle distribution on the early timescales (t less than 1 hour); however, for late timescales (t larger than 8 days) the thermal plasma from the ionosphere dominates the particle distribution.
The only species that have been so far detected in the lunar exosphere are Na, K, Ar,and He. However, models for the production and loss of species derived from the lunarregolith through micrometeoroid impact vaporization, sputtering, and photon-stimulateddesorption, predict that a host of other species should exist in the lunar exosphere.Assuming that loss processes are limited to ballistic escape, photoionization, and recyclingto the surface, we have computed column abundances and compared them to publishedupper limits for the Moon. Only for Ca do modeled abundances clearly exceed theavailable measurements. This result suggests the relevance of some loss processes thatwere not included in the model, such as the possibility of gas-to-solid phasecondensation during micrometeoroid impacts or the formation of stable metallic oxides.Our simulations and the recalculation of efficiencies for resonant light scattering showthat models for other species studied are not well constrained by existingmeasurements. This fact underlines the need for improved remote and in situmeasurements of the lunar exosphere such as those planned by the Lunar Atmosphereand Dust Environment Explorer (LADEE) spacecraft. Our simulations of the LADEEneutral mass spectrometer and visibleultraviolet spectrometer indicate that LADEE measurements promise to provide definitive observations or set stringent upper limitsfor all regolith-driven exospheric species. We predict that observations by LADEE willconstrain assumed model parameters for the exosphere of the Moon.
The mixing of engine exhaust with the vortical wake of high speed aircraft operating in the stratosphere can play an important role in the formation of chemical products that deplete atmospheric ozone. An accurate analysis of this type of interaction is therefore necessary as a part of the assessment of the impact of proposed High Speed Civil Transport (HSCT) designs on atmospheric chemistry. This paper describes modifications to the parabolic Navier-Stokes flow field analysis in the UNIWAKE unified aircraft wake model to accommodate the computation of wake/exhaust mixing and the simulation of reacting flow. The present implementation uses a passive chemistry model in which the reacting species are convected and diffused by the fluid dynamic solution but in which the evolution of the species does not affect the flow field. The resulting analysis, UNIWAKE/PCHEM (Passive CHEMistry) has been applied to the analysis of wake/exhaust flows downstream of representative HSCT configurations. The major elements of the flow field model are described, as are the results of sample calculations illustrating the behavior of the thermal exhaust plume and the production of species important to the modeling of condensation in the wake. Appropriate steps for further development of the UNIWAKE/PCHEM model are also outlined.
Early results are presented from a program to model deep convective transport of chemical species by means of in situ data collection and numerical models. Data were acquired during the NASA GTE Amazon Boundary Layer Experiment in July-August 1985. Airborne instrumentation, including a UV-DIAL system, collected data on the O3, CO, NO, temperature and water vapor profiles from the surface to 400 mb altitude, while GOES imagery tracked convective clouds over the study area. A two-dimensional cloud model with small amplitude random temperature fluctuations at low levels, which simulated thermals, was used to describe the movements of the chemical species sensed in the convective atmosphere. The data was useful for evaluating the accuracy of the cloud model, which in turn was effective in describing the circulation of the chemical species.
Jet-A spray combustion has been evaluated in gas turbine combustion with the use of propane chemical kinetics as the first approximation for the chemical reactions. Here, the numerical solutions are obtained by using the KIVA-2 computer code. The KIVA-2 code is the most developed of the available multidimensional combustion computer programs for application of the in-cylinder combustion dynamics of internal combustion engines. The released version of KIVA-2 assumes that 12 chemical species are present; the code uses an Arrhenius kinetic-controlled combustion model governed by a four-step global chemical reaction and six equilibrium reactions. Researchers efforts involve the addition of Jet-A thermophysical properties and the implementation of detailed reaction mechanisms for propane oxidation. Three different detailed reaction mechanism models are considered. The first model consists of 131 reactions and 45 species. This is considered as the full mechanism which is developed through the study of chemical kinetics of propane combustion in an enclosed chamber. The full mechanism is evaluated by comparing calculated ignition delay times with available shock tube data. However, these detailed reactions occupy too much computer memory and CPU time for the computation. Therefore, it only serves as a benchmark case by which to evaluate other simplified models. Two possible simplified models were tested in the existing computer code KIVA-2 for the same conditions as used with the full mechanism. One model is obtained through a sensitivity analysis using LSENS, the general kinetics and sensitivity analysis program code of D. A. Bittker and K. Radhakrishnan. This model consists of 45 chemical reactions and 27 species. The other model is based on the work published by C. K. Westbrook and F. L. Dryer.
mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.
mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.
The hydrocarbon photochemistry in the upper atmosphere of Jupiter is investigated using a one-dimensional, photochemical-diffusive, and diurnally averaged model. The important chemical cycles and pathways among the major species are outlined and a standard model for the North Equatorial Belt region is examined in detail. It is found that several traditionally dominant chemical pathways among the C and C2 species are replaced in importance by cycles involving C-C4 species. The pressure and altitude profiles of mixing ratios for several observable hydrocarbon species are compared with available ultraviolet- and infrared-derived abundances. The results of sensitivity studies on the standard model with respect to variations in eddy diffusion profile, solar flux, atomic hydrogen influx, latitude, temperature, and important chemical reaction rates are presented. Measured and calculated airglow emissions of He at 584 angstroms and H at 1216 angstroms are also used to provide some constraints on the range of model parameters. The relevance of the model results to the upcoming Galileo mission is briefly discussed. The model is subject to considerable improvement; there is a great need for laboratory measurements of basic reaction rates and photodissociation quantum yields, even for such simple species as methylacetylene and allene. Until such laboratory measurements exist there will be considerable uncertainty in the understanding of the C3 and higher hydrocarbons in the atmospheres of the jovian planets.
Second generation feedstocks for bioethanol will likely include a sizable proportion of perennial C4 grasses, principally in the Panicoideae clade. The Panicoideae contain agronomically important annual grasses including Zea mays L. (maize), Sorghum bicolor (L.) Moench (sorghum), and Saccharum officinarum L. (sugar cane) as well as promising second generation perennial feedstocks including Miscanthus × giganteus and Panicum virgatum L. (switchgrass). The underlying complexity of these polyploid grass genomes is a major limitation for their direct manipulation and thus driving a need for rapidly cycling comparative model. Setaria viridis (green millet) is a rapid cycling C4 panicoid grass with a relatively small and sequenced diploid genome and abundant seed production. Stable, transient, and protoplast transformation technologies have also been developed for Setaria viridis making it a potentially excellent model for other C4 bioenergy grasses. Here, the lignocellulosic feedstock composition, cellulose biosynthesis inhibitor response and saccharification dynamics of Setaria viridis are compared with the annual sorghum and maize and the perennial switchgrass bioenergy crops as a baseline study into the applicability for translational research. A genome-wide systematic investigation of the cellulose synthase-A genes was performed identifying eight candidate sequences. Two developmental stages; (a) metabolically active young tissue and (b) metabolically plateaued (mature) material are examined to compare biomass performance metrics.
To enable complete closure of a Sabatier-based atmosphere revitalization system where oxygen recovery is predicated by carbon dioxide reduction to methane and water, there must be a means of recovering the hydrogen from the byproduct methane. Honeywell’s carbon vapor deposition (CVD) reactor is a potential technology that provides a thermochemical means by which methane decomposes at high temperatures (> 1,000 °C) into hydrogen, solid carbon, and a small percentage of hydrocarbons. This advanced methane pyrolysis reactor utilizes a carbon fiber substrate to capture and immobilize the solid pyrolytic carbon rather than allowing continuation toward undesirable soot. The CVD reactor is a highly dynamic system whose characteristic geometry changes while operating. The reactor model was developed to provide predictive performance assessment capabilities at different operating conditions, geometries, and configurations to aid in technology development. Modeling of the CVD reactor considered the multitude of simultaneous and interdependent physicochemical processes that are entailed, including: (1) the homogeneous gas-phase pyrolysis reactions, (2) the heterogeneous deposition reactions, and (3) the transport of gaseous species in the reactor domains. A 1-D CVD reactor model was developed based on a general packed-bed, axial-dispersion plug flow reactor model with a solid substrate balance to account for carbon deposition. The model includes 59 species and 243 reactions constituting the methane pyrolysis reaction network, carbon deposition, and interconversions of oxygenate species. The reactor model was compared to brassboard test data, where it was shown to be able to capture the pertinent physicochemical phenomena as evidenced by its agreement with short-duration run data (i.e., looking at different temperature and flow rate conditions), as well as trend agreement with the brassboard reactor’s long-duration test data. Recommendations are provided on further model development steps as well as its use cases.
Airborne measurements of a large number of oxygenated organic chemicals (Oxorgs) were carried out in the Pacific troposphere (0.1-12 km) in the Spring of 2001 (Feb. 24-April 10). Specifically these measuremen ts included acetone, methylethyl ketone (MEK), methanol, ethanol, ace taldehyde, propionaldehyde, PANS, and organic nitrates. Complementary measurements of formaldehyde, organic peroxides, and tracers were al so available. Ox-orgs were abundant in the clean troposphere and were greatly enhanced in the outflow regions from Asia. Their mixing ratios were typically highest in the lower troposphere and declined toward s the upper troposphere and the lowermost stratosphere. Their total a bundance (Ox-orgs) significantly exceeded that of NMHC (C2-C8 NMHC). A comparison of these data with observations collected some seven yea rs earlier (Feb.-March, 1994), did not reveal any significant changes . Throughout the troposphere mixing ratios of Ox-orgs were strongly c orrelated with each other as well as with tracers of fossil and bioma sshiof'uel combustion. Analysis of the relative enhancement of selected Oxorgs with respect to CH3Cl and CO in twelve sampled plumes, origi nating from fires, is used to assess their primary and secondary sour ces from biomass combustion. The composition of these plumes also ind icates a large shift of reactive nitrogen into the PAN reservoir ther eby limiting ozone formation. The Harvard 3-D photochemical model, th at uses state of the art chemistry and source information, is used to compare simulated and observed mixing ratios of selected species. A 1 -D model is used to explore the chemistry of aldehydes. These results will be presented.
Computer models of molecular electronic and vibrational emission intensities were developed. Known radiative emission rates (Einstein coefficients) permit the determination of relative excited state densities from spectral intensities. These codes were applied to the published spectra of glow above shuttle surface and to the Spacelab 1 results of Torr and Torr. The theoretical high-resolution spectra were convolved with the appropriate instrumental slit functions to allow accurate comparison with data. The published spacelab spectrum is complex but N2+ Meinel emission can be clearly identified in the ram spectrum. M2 First Positive emission does not correlate well with observed features, nor does the CN Red System. Spectral overlay comparisons are presented. The spectrum of glow above shuttle surfaces, in contrast to the ISO data, is not highly structured. Diatomic molecular emission was matched to the observed spectral shape. Source excitation mechanisms such as (oxygen atom)-(surface species) reaction product chemiluminescence, surface recombination, or resonance fluorescent re-emission will be discussed for each tentative assignment. These assignments are the necessary first analytical step toward mechanism identification. Different glow mechanisms will occur above surfaces under different orbital conditions.
Two models of vibrational energy exchange are compared at equilibrium to the elementary vibrational exchange reaction for a binary mixture. The first model, non-linear in the species vibrational energies, was derived by Schwartz, Slawsky, and Herzfeld (SSH) by considering the detailed kinetics of vibrational energy levels. This model recovers the result demanded at equilibrium by the elementary reaction. The second model is more recent, and is gaining use in certain areas of computational fluid dynamics. This model, linear in the species vibrational energies, is shown not to recover the required equilibrium result. Further, this more recent model is inconsistent with its suggested rate constants in that those rate constants were inferred from measurements by using the SSH model to reduce the data. The non-linear versus linear nature of these two models can lead to significant differences in vibrational energy coupling. Use of the contemporary model may lead to significant misconceptions, especially when integrated in computer codes considering multiple energy coupling mechanisms.