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At least 253 records · Page 14

Modeling Atmospheric CO2 Processes to Constrain the Missing Sink

We report on a NASA supported modeling effort to reduce uncertainty in carbon cycle processes that create the so-called missing sink of atmospheric CO2. Our overall objective is to improve characterization of CO2 source/sink processes globally with improved formulations for atmospheric transport, terrestrial uptake and release, biomass and fossil fuel burning, and observational data analysis. The motivation for this study follows from the perspective that progress in determining CO2 sources and sinks beyond the current state of the art will rely on utilization of more extensive and intensive CO2 and related observations including those from satellite remote sensing. The major components of this effort are: 1) Continued development of the chemistry and transport model using analyzed meteorological fields from the Goddard Global Modeling and Assimilation Office, with comparison to real time data in both forward and inverse modes; 2) An advanced biosphere model, constrained by remote sensing data, coupled to the global transport model to produce distributions of CO2 fluxes and concentrations that are consistent with actual meteorological variability; 3) Improved remote sensing estimates for biomass burning emission fluxes to better characterize interannual variability in the atmospheric CO2 budget and to better constrain the land use change source; 4) Evaluating the impact of temporally resolved fossil fuel emission distributions on atmospheric CO2 gradients and variability. 5) Testing the impact of existing and planned remote sensing data sources (e.g., AIRS, MODIS, OCO) on inference of CO2 sources and sinks, and use the model to help establish measurement requirements for future remote sensing instruments. The results will help to prepare for the use of OCO and other satellite data in a multi-disciplinary carbon data assimilation system for analysis and prediction of carbon cycle changes and carbodclimate interactions.

Kawa, S. R.↗

Enhanced Menshutkin S N 2 Reactivity in Mesoporous Silica: The Influence of Surface Catalysis and Confinement

A significant enhancement in the Menshutkin S N 2 reaction between 1-methylimidazole (MeIm) and methyl thiocyanate (MeSCN) is observed when the reaction is confined in the nanoscale silica pores of MCM41 and SBA15. The experiments in the silica pores are conducted without surrounding bulk reaction mixture. The influences of temperature, pore radius, and surface chemistry on the kinetics of the confined reaction are analyzed with time-dependent infrared spectroscopy, molecular dynamics simulations, and ab initio calculations. The rate constant of the pseudo-first order reaction increases with decreasing pore size, and the activation energy is found to decrease by 5.6 kJ/mol in the smallest pore studied (2.8 nm) relative to the bulk reaction. The rate constant dependence on pore size is accurately described by a two-state model in which molecules within the 4.6 Å interfacial layer experience a 2.4-fold rate constant increase relative to those reacting at the bulk rate further away from the interface. The removal of polar silanol groups from the silica surface via passivation with trimethylsilyl chloride results in bulk-like kinetics despite a reduction in the pore diameter, demonstrating the role of silanols as catalytic sites. Here, electronic structure calculations of the energy profile on a model silica surface confirm that silanol groups, particularly those of the vicinal type, can reduce the activation energy and reaction endothermicity through the donation of hydrogen bonds to the reactant, transition state, and product complexes.

36 MATERIALS SCIENCE↗

Theoretical insights into the surface physics and chemistry of redox-active oxides

Redox active oxides are ubiquitous in materials applications, including catalysis, photovoltaics, self-cleaning glasses, chemical sensors, and electronic components. Their utility derives from their unique ability to access multiple metal charge states within a finite energy window. However, this property also confounds our ability to study reducible oxides, because it leads to structural, compositional, and electronic complexities that elude simplistic models of materials structure and function. Oxygen vacancies play a critical role in shaping the functional properties of such oxides; most notably, they lead to mobile charge imbalances that impact surface processes at significant distances from the originating defect. Atomistic simulations are inherently equipped to illuminate these phenomena at a fundamental level; however, reducible oxides pose great challenges due to the high level of electron correlation needed to correctly describe them. Knowing how defects form, couple, propagate, agglomerate, or repel each other and influence the surface properties of reducible oxides is only now coming into the grasp of modern theory and simulation capabilities. This knowledge is also key to discovering and controlling emergent materials processes at nanometer scale and beyond. The manuscript was written with support of all three authors from U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. Work by RR and VG was performed at Pacific Northwest National Laboratory (PNNL), which is a multi-program laboratory operated by Battelle for DOE under Contract DE AC05 76RL01830. AS was supported under Award DE-SC0007347.

Rousseau, Roger J.↗

Quick-and-Easy Validation of Protein–Ligand Binding Models Using Fragment-Based Semiempirical Quantum Chemistry

Electronic structure calculations in enzymes converge very slowly with respect to the size of the model region that is described using quantum mechanics (QM), requiring hundreds of atoms to obtain converged results and exhibiting substantial sensitivity (at least in smaller models) to which amino acids are included in the QM region. As such, there is considerable interest in developing automated procedures to construct a QM model region based on well-defined criteria. However, testing such procedures is burdensome due to the cost of large-scale electronic structure calculations. Here, we show that semiempirical methods can be used as alternatives to density functional theory (DFT) to assess convergence in sequences of models generated by various automated protocols. The cost of these convergence tests is reduced even further by means of a many-body expansion. We use this approach to examine convergence (with respect to model size) of protein–ligand binding energies. Fragment-based semiempirical calculations afford well-converged interaction energies in a tiny fraction of the cost required for DFT calculations. Two-body interactions between the ligand and single-residue amino acid fragments afford a low-cost way to construct a “QM-informed” enzyme model of reduced size, furnishing an automatable active-site model-building procedure. This provides a streamlined, user-friendly approach for constructing ligand binding-site models that needs neither a priori information nor manual adjustments. Extension to model-building for thermochemical calculations should be straightforward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Source sector and fuel contributions to ambient PM 2.5 and attributable mortality across multiple spatial scales

Ambient fine particulate matter (PM 2.5 ) is the world’s leading environmental health risk factor. Reducing the PM 2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM 2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74–1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM 2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52–0.95] million deaths; 19.2%), industrial (0.45 [0.32–0.58] million deaths; 11.7%), and energy (0.39 [0.28–0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.

54 ENVIRONMENTAL SCIENCES↗

Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model

Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.

33 ADVANCED PROPULSION SYSTEMS↗

Effect of Processing on Precipitation Kinetics in Nano Polycrystalline 7075 Aluminum Alloy

Fairmount Technologies (FT) seeks to optimize the thermomechanical processing of Aluminum Alloy 7075. The target yield strength is 20% higher than commercially available 7075-T6 temper sheet which will enable structural light weighting by a similar magnitude and reduce the carbon footprint of the transportation sector. To reduce processing cost and make this commercially viable, it is important to understand physical mechanisms driving microstructural changes. A mesoscale phase-field model seeded with experimentally measured microstructures and assessed thermodynamic and kinetic properties will be developed and exercised using HPC at PNNL. It will account for the effect of deformation, temperature, and chemistry on precipitation kinetics in nanocrystalline microstructures. Our objective is to understand this “stress-aging” coupling by performing parametric simulations with mesoscale models for a better understanding of GP zone and η' formation in nanocrystalline 7075 Al. This will help FT optimize processing schedules to achieve desired microstructures that increase both strength and ductility.

36 MATERIALS SCIENCE↗

Dimethylsulfide oxidation over the tropical South Atlantic: OH and other oxidants

The general course of events in the formation of a marine cloud begins with the emission of species which can eventually serve as nuclei around which water can condense to form a cloud droplet. In remote marine regions, cloud condensation nuclei (CCN) are primarily composed of sulfate, in either its acid or ammonium salt form. Most sulfate in these regions is the product of atmospheric oxidation of dimethyl sulfide (DMS), a reduced sulfur gas that is released by phytoplankton at the ocean surface. Therefore, in order to effectively quantify the links in the cloud-formation cycle, one must begin with a well-defined description of the atmospheric chemistry of DMS. The intent of this project has been to initiate development of a comprehensive model of the chemistry and dynamics responsible for the formation of clouds in the remote marine boundary layer. The primary tool in this work has been the Global/Regional Atmospheric Chemistry Event Simulator (GRACES), a global atmospheric chemistry model, which is under development within the Atmospheric Chemistry and Dynamics Branch of NASA-Ames Research Center. In this effort, GRACES was used to explore the first chemical link between DMS and sulfate by modeling the diurnal variation of DMS.

Hemming, Brooke L.↗

Volatile chemical product emissions enhance ozone and modulate urban chemistry

Decades of air quality improvements have substantially reduced the motor vehicle emissions of volatile organic compounds (VOCs). Today, volatile chemical products (VCPs) are responsible for half of the petrochemical VOCs emitted in major urban areas. We show that VCP emissions are ubiquitous in US and European cities and scale with population density. We report significant VCP emissions for New York City (NYC), including a monoterpene flux of 14.7 to 24.4 kg ⋅ d−1 ⋅ km−2 from fragranced VCPs and other anthropogenic sources, which is comparable to that of a summertime forest. Photochemical modeling of an extreme heat event, with ozone well in excess of US standards, illustrates the significant impact of VCPs on air quality. In the most populated regions of NYC, ozone was sensitive to anthropogenic VOCs (AVOCs), even in the presence of biogenic sources. Within this VOC-sensitive regime, AVOCs contributed upwards of ∼20 ppb to maximum 8-h average ozone. VCPs accounted for more than 50% of this total AVOC contribution. Emissions from fragranced VCPs, including personal care and cleaning products, account for at least 50% of the ozone attributed to VCPs. We show that model simulations of ozone depend foremost on the magnitude of VCP emissions and that the addition of oxygenated VCP chemistry impacts simulations of key atmospheric oxidation products. NYC is a case study for developed megacities, and the impacts of VCPs on local ozone are likely similar for other major urban regions across North America or Europe.

Matthew M. Coggon↗

Solar nebula condensates and the composition of comets

Interpretation of the volatile abundances in Halley's comet in terms of models for chemical and physical processes in the solar nebula are discussed. Key ratios of the oxidized and reduced species of nitrogen and carbon are identified which tell something of the chemical history of the environment in which cometary grains accreted to form the nucleus. Isotopic abundances are also applied to this problem. It will be shown that the abundances of methane and carbon monoxide are consistent both with models of solar nebula chemistry and chemical processing on grains in star-forming regions. Ultimately, limitations of the current data set on molecular abundances in comets and star-forming regions prevent a definitive choice between the two. Processes important to the composition of outer solar system bodies are: (1) gas phase chemistry in the solar nebula; (2) imperfect mixing in the solar nebula; (3) condensation; (4) clathration; (5) adsorption; and (6) processing of interstellar material.

Lunine, J. I.↗

Multi-Zone Liquid Thrust Chamber Performance Code with Domain Decomposition for Parallel Processing

Computational Fluid Dynamics (CFD) has considerably evolved in the last decade. There are many computer programs that can perform computations on viscous internal or external flows with chemical reactions. CFD has become a commonly used tool in the design and analysis of gas turbines, ramjet combustors, turbo-machinery, inlet ducts, rocket engines, jet interaction, missile, and ramjet nozzles. One of the problems of interest to NASA has always been the performance prediction for rocket and air-breathing engines. Due to the complexity of flow in these engines it is necessary to resolve the flowfield into a fine mesh to capture quantities like turbulence and heat transfer. However, calculation on a high-resolution grid is associated with a prohibitively increasing computational time that can downgrade the value of the CFD for practical engineering calculations. The Liquid Thrust Chamber Performance (LTCP) code was developed for NASA/MSFC (Marshall Space Flight Center) to perform liquid rocket engine performance calculations. This code is a 2D/axisymmetric full Navier-Stokes (NS) solver with fully coupled finite rate chemistry and Eulerian treatment of liquid fuel and/or oxidizer droplets. One of the advantages of this code has been the resemblance of its input file to the JANNAF (Joint Army Navy NASA Air Force Interagency Propulsion Committee) standard TDK code, and its automatic grid generation for JANNAF defined combustion chamber wall geometry. These options minimize the learning effort for TDK users, and make the code a good candidate for performing engineering calculations. Although the LTCP code was developed for liquid rocket engines, it is a general-purpose code and has been used for solving many engineering problems. However, the single zone formulation of the LTCP has limited the code to be applicable to problems with complex geometry. Furthermore, the computational time becomes prohibitively large for high-resolution problems with chemistry, two-equation turbulence model, and two-phase flow. To overcome these limitations, the LTCP code is rewritten to include the multi-zone capability with domain decomposition that makes it suitable for parallel processing, i.e., enabling the code to run every zone or sub-domain on a separate processor. This can reduce the run time by a factor of 6 to 8, depending on the problem.

Homayun K. Navaz↗

Conceptual model of turbulent flameholding for scramjet combustors

New concepts and approaches to scramjet combustor design are presented. Blowoff was from failure of the recirculation-zone (RZ) flame to reach the dividing streamline (DS) at the rear stagnation zone. Increased turbulent exchange across the DS helped flameholding due to forward movement of the flame anchor point inside the RZ. Modeling of the blowoff phenomenon was based on a mass conservation concept involving the traverse of a flame element across the RZ and a flow element along the DS. The scale required to achieve flameholding, predicted by the model, showed a strong adverse effect of low pressure and low fuel equivalence ratio, moderate effect of flight Mach number, and little effect of temperature recovery factor. Possible effects of finite rate chemistry on flameholding and flamespreading in scramjets are discussed and recommendations for approaches to engine combustor design as well as for needed research to reduce uncertainties in the concepts are made.

Huber, P. W.↗

Joint Assimilation of the Aura Microwave Limb Sounder and Ozone Mapping and Profiler Suite Limb Profiler Data: Towards a Reanalysis of Stratospheric Ozone for Trend Studies

The future trajectory of the stratospheric ozone recovery will be sensitive to greenhouse gas concentrations through thermal control of chemical loss and via stratospheric circulation changes. The latter in particular is subject to considerable uncertainty meriting continuing monitoring of the evolution of ozone throughout the depth of the stratosphere. Atmospheric reanalyses utilize the data assimilation methodology to obtain comprehensive representations of the state of the atmosphere, including its composition, on multidecadal scales by combining diverse measurements from satellite-borne and conventional data sources. Systematic biases among these various data types pose a challenge for assimilation by introducing spurious discontinuities that affect the utility of reanalyses for studies of long-term variability and trends.In this presentation we will outline an approach, developed at NASA's Global Modeling and Assimilation Office (GMAO), that allows joint assimilation of stratospheric ozone profiles from the Microwave Limb Sounder (MLS) on EOS Aura and the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) currently flying on the Suomi-NPP satellite with future missions projected into the 2030s. We will demonstrate that a simple offline correction significantly reduces biases between MLS and OMPS-LP ozone data providing a strategy for generating a long-term vertically resolved homogenized representation of stratospheric ozone in future reanalyses. One novel element of our approach compared to previous GMAO reanalysis is the use of a version of the Goddard Earth Observing System model with full stratospheric chemistry. We will show selected comparisons of MLS and OMPS-LP assimilation experiments with independent ozonesonde and satellite data as well as two examples of process-based evaluation focused on the 2016 QBO disruption and Arctic winter ozone loss focusing on the relative performance of the MLS and OMPS-LP analyses.

Wargan, K.↗

Nearest-Neighbor Machine Learning Feature Selection for Interpretation of Microbial Molecular Signatures from Isotope Ratio Mass Spectrometry Data

Mass spectrometry (MS) promises to be a powerful tool for potential biosignature detection during astrobiological missions on ocean worlds in our solar system. Accurate and generalizable machine learning methods could enhance science return on investment by predicting seawater chemistry and classifying isotopic biosignatures, either as a signature consistent with microbial life (biotic) or as a novelty (unclassified/unique). However, machine learning models are likely to be complex and involve interactions between MS features, making biosignatures difficult to interpret. Feature selection methods provide biological and chemical context that help interpret the mechanisms of machine learning models, but these methods also need the ability to detect complex interactions. Previously, we developed a machine learning feature selection algorithm called nearest-neighbor projected distance regression (NPDR) that has the ability to identify important model features that involve complex interactions and automatically reduce correlation and the dimensionality in a high-dimensional variable space. The standard distance metrics used in NPDR – Manhattan and Euclidean – assume the multivariate data are isotropic, which is often violated in real data due to differences in the covariance between variables. Thus, we extend NPDR to include a random forest distance, and other anisotropic distance metrics, for computing nearest neighbors. We also augment the isotope-ratio MS data with time-series features from the raw MS signal to improve biotic classification. We test NPDR on our novel experimental ocean world seawater analog MS data. We measure isotope fractionations of volatile CO 2 that could be measured in exospheres or plumes. Samples include baseline abiotic conditions using a range of possible seawater chemistry consistent with Europa and Enceladus, and biotic samples that include microbes in these seawaters. We use penalized NPDR with random forest proximity to identify interpretable microbial molecular signatures. We compare features with random forest importance, and we train a classifier that discriminates between biotic and abiotic samples with high accuracy. These ML-trained ocean-world analog MS data could be used to assist in identifying biosignatures during future missions.

geochemistry↗

Predicting secondary organic aerosol phase state and viscosity and its effect on multiphase chemistry in a regional-scale air quality model

Atmospheric aerosols are a significant public health hazard and have substantial impacts on the climate. Secondary organic aerosols (SOAs) have been shown to phase separate into a highly viscous organic outer layer surrounding an aqueous core. This phase separation can decrease the partitioning of semi-volatile and low-volatile species to the organic phase and alter the extent of acid-catalyzed reactions in the aqueous core. A new algorithm that can determine SOA phase separation based on their glass transition temperature (T g ), oxygen to carbon (O:C) ratio and organic mass to sulfate ratio, and meteorological conditions was implemented into the Community Multiscale Air Quality Modeling (CMAQ) system version 5.2.1 and was used to simulate the conditions in the continental United States for the summer of 2013. SOA formed at the ground/surface level was predicted to be phase separated with core–shell morphology, i.e., aqueous inorganic core surrounded by organic coating 65.4 % of the time during the 2013 Southern Oxidant and Aerosol Study (SOAS) on average in the isoprene-rich southeastern United States. Our estimate is in proximity to the previously reported ~70 % in literature. The phase states of organic coatings switched between semi-solid and liquid states, depending on the environmental conditions. The semi-solid shell occurring with lower aerosol liquid water content (western United States and at higher altitudes) has a viscosity that was predicted to be 10 2 –10 12 Pa s, which resulted in organic mass being decreased due to diffusion limitation. Organic aerosol was primarily liquid where aerosol liquid water was dominant (eastern United States and at the surface), with a viscosity <10 2 Pa s. Phase separation while in a liquid phase state, i.e., liquid–liquid phase separation (LLPS), also reduces reactive uptake rates relative to homogeneous internally mixed liquid morphology but was lower than aerosols with a thick viscous organic shell. The sensitivity cases performed with different phase-separation parameterization and dissolution rate of isoprene epoxydiol (IEPOX) into the particle phase in CMAQ can have varying impact on fine particulate matter (PM 2.5 ) organic mass, in terms of bias and error compared to field data collected during the 2013 SOAS. This highlights the need to better constrain the parameters that govern phase state and morphology of SOA, as well as expand mechanistic representation of multiphase chemistry for non-IEPOX SOA formation in models aided by novel experimental insights.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Continuous recovery of phosphoric acid and Rare-Earths containing particles from phosphoric acid sludge using a decanter centrifuge

Recovery of rare earth elements (REEs) from various industrial and natural streams currently draws significant attention in efforts to meet the demands of the manufacturing industry. Among many industrial byproducts and waste streams, phosphoric acid sludge could be one of the most economically feasible resources for the recovery of REEs because solid particles in the sludge contain relatively concentrated REEs, up to 3,000 ppm, while the liquid component of the sludge is valuable phosphoric acid (P 2 O 5 ) that can be recovered and returned to the main product. Due to high viscosity and large solids content (e.g., 30–40 %), however, this byproduct stream requires multistep separation and purification processes. In this study, a single-step process involving a continuous-flow decanter centrifuge (CFDC) was employed to investigate its feasibility for continuous solid/liquid separation from real phosphoric acid sludge. High centrifugal forces generated from up to 1500 G gravity acceleration separate solid particles from the sludge, generating a liquid-rich stream and a solids-rich stream at the exit of the CFDC. A single pass of phosphoric-acid sludge through the CFDC yielded 95 % liquid recovery and 90 % recovery of REEs-containing solids from 20 to 34 wt% solids-containing sludge. Finally, a reduced order model developed for the CFDC operation showed good agreement with experimental data, and preliminary technoeconomic analysis revealed potential process feasibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The impact of temperature dependent CO2 cross section measurements: A role for heterogeneous chemistry in the atmosphere of Mars?

Carbon dioxide comprises over 95 percent of the Mars atmosphere, despite continuous photolysis of CO2 by solar ultraviolet (UV) radiation. Since the direct recombination of CO and O is spinforbidden, the chemical stability of CO2 in the Martian atmosphere is thought to be the result of a HO(x)-catalyzed recombination scheme. Thus the rate of CO oxidation is sensitive to the abundance and altitude distribution of OH, H, and HO2. Most Martian atmospheric models assume that HO(x) abundances are governed purely by gas phase chemistry. However, it is well established that reactive HO(x) radical are adsorbed by a wide variety of surfaces. The authors have combined laboratory studies of H, OH, and HO2 adsorption on inorganic surfaces, observational data of aerosol distributions, and an updated photochemical model to demonstrate that adsorption on either dust or ice aerosols is capable of reducing HO(x) abundances significantly, thereby retarding the rate of CO oxidation.

Anbar, A. D.↗