Deviations from the Henry's law equilibrium during cloud events: a numerical approach of the mass transfer between phases and its specific numerical effects

Audiffren, Nicole; Renard, M. L.; Buisson, Emmanuel; Chaumerliac, Nadine

doi:10.1016/s0169-8095(98)00072-6

Cited by 51 publications

(33 citation statements)

References 23 publications

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“…For gas-phase chemistry, the mechanism includes 29 species with 65 reactions that represent the reactivity of ozone, NO y and VOC including isoprene chemistry (Arteta et al, 2006;Taghavi et al, 2004). For aqueous-phase chemistry, the mechanism includes 10 species with 18 reactions that represent the HO x chemistry and the formation of nitrate, sulfate and formic acid (Audiffren et al, 1998). For the exchange of chemical species between gas phase and liquid hydrometeors, the mass transfer kinetic formulation of Schwartz (1986) is used taking into account the possible deviation from Henry's law equilibrium.…”

Section: Rams (M Leriche and S Cautenet)mentioning

confidence: 99%

Cloud-scale model intercomparison of chemical constituent transport in deep convection

et al. 2007

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Abstract. Transport and scavenging of chemical constituents in deep convection is important to understanding the composition of the troposphere and therefore chemistryclimate and air quality issues. High resolution cloud chemistry models have been shown to represent convective processing of trace gases quite well. To improve the representation of sub-grid convective transport and wet deposition in large-scale models, general characteristics, such as species mass flux, from the high resolution cloud chemistry models can be used. However, it is important to understand how these models behave when simulating the same storm. The intercomparison described here examines transport of six species. CO and O 3 , which are primarily transported, show good agreement among models and compare well with observations. Models that included lightning production of NO x reasonably predict NO x mixing ratios in the anvil compared with observations, but the NO x variability is much larger than that seen for CO and O 3 . Predicted anvil mixing ratios of the soluble species, HNO 3 , H 2 O 2 , and CH 2 O, exhibit significant differences among models, attributed to different schemes in these models of cloud processing including the role of the Correspondence to: M. C. Barth (barthm@ucar.edu) ice phase, the impact of cloud-modified photolysis rates on the chemistry, and the representation of the species chemical reactivity. The lack of measurements of these species in the convective outflow region does not allow us to evaluate the model results with observations.

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Section: Rams (M Leriche and S Cautenet)mentioning

confidence: 99%

Cloud-scale model intercomparison of chemical constituent transport in deep convection

et al. 2007

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“…It can be represented by a partitioning coefficient q defined by Audiffren et al (1998) based upon the phase ratio introduced by Chameides (1984) and Lelieveld and Crutzen (1991):…”

Section: Partitioning Among Gas-aqueous Cloud Phasesmentioning

confidence: 99%

Modeling the partitioning of organic chemical species in cloud phases with CLEPS (1.1)

Chaumerliac¹,

Deguillaume²,

Perroux³

et al. 2018

Atmos. Chem. Phys.

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Abstract. The new detailed aqueous-phase mechanism Cloud Explicit Physico-chemical Scheme (CLEPS 1.0), which describes the oxidation of isoprene-derived watersoluble organic compounds, is coupled with a warm microphysical module simulating the activation of aerosol particles into cloud droplets. CLEPS 1.0 was then extended to CLEPS 1.1 to include the chemistry of the newly added dicarboxylic acids dissolved from the particulate phase. The resulting coupled model allows the prediction of the aqueousphase concentrations of chemical compounds originating from particle scavenging, mass transfer from the gas-phase and in-cloud aqueous chemical reactivity. The aim of the present study was more particularly to investigate the effect of particle scavenging on cloud chemistry. Several simulations were performed to assess the influence of various parameters on model predictions and to interpret long-term measurements conducted at the top of Puy de Dôme (PUY, France) in marine air masses. Specific attention was paid to carboxylic acids, whose predicted concentrations are on average in the lower range of the observations, with the exception of formic acid, which is rather overestimated in the model. The different sensitivity runs highlight the fact that formic and acetic acids mainly originate from the gas phase and have highly variable aqueous-phase reactivity depending on the cloud acidity, whereas C 3 -C 4 carboxylic acids mainly originate from the particulate phase and are supersaturated in the cloud.

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“…In such cases, a kinetic mass transfer treatment may be necessary to accurately describe the phase distribution between gas and cloud or fog droplets and subsequent chemistry (Djouad et al, 2003;Audiffren et al, 1998Audiffren et al, , 1996Chaumerliac et al, 2000;Ervens et al, 2003). Here, we treat mass transfer kinetically as a default in AQCHEM − KMT in an effort to assess how deviations from instantaneous Henry's law equilibrium impact predicted concentrations for short-and long-term averaging periods which may be of interest in different applications.…”

Section: Impacts Of Mass Transfer Assumptions and Solver On Box Modelmentioning

confidence: 99%

“…(1) and (2) represent the concentration changes due to mass transfer between the gas and aqueous phases. While instantaneous Henry's law equilibrium is assumed for all species in AQCHEM, in actuality, the distribution of a species between the gas and aqueous phases may deviate significantly from equilibrium (Audiffren et al, 1998;Sander, 1999;Gong et al, 2011). As in Schwartz (1986), the combined impacts of gas-phase diffusion and interfacial mass transport limitations are incorporated into a single mass transfer coefficient (k mt ), the expression for which is given in Table 2.…”

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confidence: 99%

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

et al. 2017

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Abstract. This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosenbrock solver (Rodas3) to integrate the stiff system of ordinary differential equations (ODEs) that describe the mass transfer, chemical kinetics, and scavenging processes of CMAQ clouds. CMAQ's standard cloud chemistry module (AQCHEM) is structurally limited to the treatment of a simple chemical mechanism. This work advances our ability to test and implement more sophisticated aqueous chemical mechanisms in CMAQ and further investigate the impacts of microphysical parameters on cloud chemistry.Box model cloud chemistry simulations were performed to choose efficient solver and tolerance settings, evaluate the implementation of the KPP solver, and assess the direct impacts of alternative solver and kinetic mass transfer on predicted concentrations for a range of scenarios. Month-long CMAQ simulations for winter and summer periods over the US reveal the changes in model predictions due to these cloud module updates within the full chemical transport model. While monthly average CMAQ predictions are not drastically altered between AQCHEM and AQCHEM − KMT, hourly concentration differences can be significant. With added in-cloud secondary organic aerosol (SOA) formation from biogenic epoxides (AQCHEM − KMTI), normalized mean error and bias statistics are slightly improved for 2-methyltetrols and 2-methylglyceric acid at the Research Triangle Park measurement site in North Carolina during the Southern Oxidant and Aerosol Study (SOAS) period. The added in-cloud chemistry leads to a monthly average increase of 11-18 % in "cloud" SOA at the surface in the eastern United States for June 2013.

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Deviations from the Henry's law equilibrium during cloud events: a numerical approach of the mass transfer between phases and its specific numerical effects

Cited by 51 publications

References 23 publications

Cloud-scale model intercomparison of chemical constituent transport in deep convection

Cloud-scale model intercomparison of chemical constituent transport in deep convection

Modeling the partitioning of organic chemical species in cloud phases with CLEPS (1.1)

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

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