A zonally averaged chemical-dynamical model of the lower thermosphere
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An attempt is made to explain the fact that the large variation in Venus CO abundance with planetary phase using a combination of photochemical and kinematical models. Present knowledge about the Venus mesosphere is first summarized, emphasizing the more completely measured lower and upper atmosphere. The predictions of Dickinson and Ridley's (1977) hydrodynamic modeling are compared to the results of microwave observations of CO. It is noted that the nightside CO bulge above 90-95 km altitude indicated by microwave measurements is a primary characteristic of these models, whereas the opposite phase behavior of CO between 80 and 90 km is not predicted by them. The result of diurnal photochemical models for the Venus mesosphere are presented and an attempt is made to reproduce the phase behavior of CO between 80 and 90 km in the Venus mesosphere. Possible diurnal variations due to chemistry and vertical eddy diffusion are considered.
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In the present numerical prediction of the deposition rate of silicon from silane in a CVD process, the conservation equations for mass, momentum, energy, and chemical species are solved on a staggered grid using the SIMPLE algorithm, while the rate of chemical reactions in the gas phase and on the susceptor surface is obtained from an Arrhenius rate equation. Predicted deposition rates as a function of position along the susceptor with and without the gas phase chemical reaction are compared with the available experimental and numerical data; agreement is excellent except at the leading edge of the susceptor, where the deposition rate is overpredicted.
The paper investigates the feasibility of using an inverse method based on a linear Kalman filter in a three-dimensional atmospheric transport model, for the determination of regional surface fluxes with rapid convergence, using data from a finite number of observation sites. It was found that the inverse method used was capable to accurately determine regional surface fluxes using the present ALE/GALE sites, and to converge to the correct solution within a year or two, using initial conditions very different from the final solution.
Contamination control is a critical safety requirement imposed on experiments flying on board the Spacelab. The General Purpose Work Station, a Spacelab support facility used for life sciences space flight experiments, is designed to remove volatile compounds from its internal airpath and thereby minimize contamination of the Spacelab. This is accomplished through the use of a large, multi-stage filter known as the Trace Contaminant Control System. Many experiments planned for the Spacelab require the use of toxic, volatile fixatives in order to preserve specimens prior to postflight analysis. The NASA-Ames Research Center SLS-2 payload, in particular, necessitated the use of several toxic, volatile compounds in order to accomplish the many inflight experiment objectives of this mission. A model was developed based on earlier theories and calculations which provides conservative predictions of the resultant concentrations of these compounds given various spill scenarios. This paper describes the development and application of this model.
Subglacial volcanic activity on Iceland has led to the formation of a variety of silicate and iron oxide-rich alteration products that may ressemble chemical alteration on Mars. The spectral and chemical properties of Icelandic samples are presented. Additional information is contained in the original extended abstract.
The atmospheric distributions of the aerosol tracers Pb-210 and Be-7 are simulated with a global three-dimensional model driven by assimilated meteorological observations for 1991-1996 from the NASA Goddard Earth Observing System (GEOSl). The combination of terrigenic Pb-210 and cosmogenic Be-7 provides a sensitive test of wet deposition and vertical transport in the model. Our simulation of moist transport and removal includes scavenging in wet convective updrafts (40% scavenging efficiency per kilometer of updraft), midlevel entrainment and detrainment, first-order rainout and washout from both convective anvils and large-scale precipitation, and cirrus precipitation. Observations from surface sites in specific years are compared to model results for the corresponding meteorological years, and observations from aircraft missions over the Pacific are compared to model results for the days of the flights. Initial simulation of Be-7 showed that cross-tropopause transport in the GEOSl meteorological fields is too fast by a factor of 3-4. We adjusted the stratospheric Be-7 source to correct the tropospheric simulation. Including this correction, we find that the model gives a good simulation of observed Pb-210 and Be-7 concentrations and deposition fluxes at surface sites worldwide, with no significant global bias and with significant success in reproducing the observed latitudinal and seasonal distributions. We achieve several improvements over previous models; in particular, we reproduce the observed Be-7 minimum in the tropics and show that its simulation is sensitive to rainout from convective anvils. Comparisons with aircraft observations up to 12-km altitude suggest that cirrus precipitation could be important for explaining the low concentrations in the middle and upper troposphere.
The performance of a scalar PDF hydrogen-air combustion model in predicting a complex reacting flow is evaluated. In addition the results are compared to those obtained by running the same case with the so-called laminar chemistry model and also a new model based on the concept of mapping partially stirred reactor data onto perfectly stirred reactor data. The results show that the scalar PDF model produces significantly different results from the other two models, and at a significantly higher computational cost.
Lead-210 distribution and lifetime in the atmosphere are not sensitive to ice in-cloud scavenging in convective updraft. Ice in-cloud scavenging in stratiform clouds reduce tropospheric (210)Pb lifetime by approximately 1 day and results in better agreements with observed surface observations and aircraft measured profiles. However, the process results in significant underestimate of (210)Pb in UT/LS.
This work serves as the second of a two-part study to improve surface PM2.5 forecasts in the continental U.S. through the integrated use of multi satellite aerosol optical depth (AOD) products (MODIS Terra/Aqua and VIIRS DT/DB), multichemical transport model (CTM) (GEOS-Chem, WRF-Chem, and CMAQ) outputs, and ground observations. In Part I of the study, an ensemble Kalman filter (KF) technique using three CTM outputs and ground observations was developed to correct forecast bias and generate a single best forecast of PM2.5 for next day over non rural areas that have surface PM2.5 measurements in the proximity of 125 km. Here, with AOD data, we extended the bias correction into rural areas where the closest air quality monitoring station is at least 125–300 km away. First, we ensembled all of satellite AOD products to yield the single best AOD. Second, we corrected daily PM2.5 in rural areas from multiple models through the AOD spatial pattern between these areas and non rural areas, referred to as “extended ground truth” or EGT, for the present day. Lastly, we applied the KF technique to reduce the forecast bias for next day using the EGT. Our results find that the ensemble of bias-corrected daily PM2.5 from three CTMs for both today and next day show the best performance. Together, the two-part study develops a multimodel and multi-AOD bias-correction technique that has the potential to improve PM2.5 forecasts in both rural and non rural areas in near real time, and be readily implemented at state levels.
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Rapid and accurate prediction of the physicochemical properties of molecules given their structures remains a key challenge in cheminformatics. Machine learning approaches offer high-throughput options, but the optimality of inductive biases and data representations are up for debate. For example, BERT-based masked language models (MLMs) can be trained in a self-supervised way on hundreds of millions to billions of readily available SMILES strings. Another option is graph neural networks (GNNs), which can operate directly on molecular structures. Yet, generating accurate molecular geometry is computationally expensive, leading to a relative scarcity in data compared to SMILES strings. It is attractive to combine these two paradigms by pre-training an LM on a large corpus of SMILES strings and embedding these representation into a geometric graph neural network. Despite the promise of such an approach, and contrary to previous studies, we find mixed results with the combination of the LMs and GNNs on several molecule datasets. In particular, we found evidence for improvement on the FreeSolv and QM7 benchmarks, but degraded performance on the ESOL, LIPO and QM9 datasets compared to a GNN baseline.
A unified overview is presented for chemical kinetics and chemical modeling in planetary atmospheres. The recent major advances in the understanding of the chemistry of the terrestrial atmosphere make the study of planets more interesting and relevant. A deeper understanding suggests that the important chemical cycles have a universal character that connects the different planets and ultimately link together the origin and evolution of the solar system. The completeness (or incompleteness) of the data base for chemical kinetics in planetary atmospheres will always be judged by comparison with that for the terrestrial atmosphere. In the latter case, the chemistry of H, O, N, and Cl species is well understood. S chemistry is poorly understood. In the atmospheres of Jovian planets and Titan, the C-H chemistry of simple species (containing 2 or less C atoms) is fairly well understood. The chemistry of higher hydrocarbons and the C-N, P-N chemistry is much less understood. In the atmosphere of Venus, the dominant chemistry is that of chlorine and sulfur, and very little is known about C1-S coupled chemistry. A new frontier for chemical kinetics both in the Earth and planetary atmospheres is the study of heterogeneous reactions. The formation of the ozone hole on Earth, the ubiquitous photochemical haze on Venus and in the Jovian planets and Titan all testify to the importance of heterogeneous reactions. It remains a challenge to connect the gas phase chemistry to the production of aerosols.