Modeling of scavenging processes in clouds: some remaining questions about the partitioning of gases among gas and liquid phases
Introduction
More than 50% of the Earth's surface is covered by clouds and theoretical calculations of Ravishankara (1997) have shown that clouds can alter the chemical composition of the atmosphere on a global scale. Clouds interact in many ways with chemicals on a wide range of scales, from micrometers up to thousands of kilometers.
On a large scale (thousands of kilometers), clouds are organized in broad and complex systems that are responsible for the transport of species from the boundary layer to the free troposphere Renard et al., 1994, Edy et al., 1996. Tracer redistribution can be greatly changed in case of precipitating clouds systems due to their efficient scavenging. Photochemical processes can be modified through cloud/radiation interactions (Thompson, 1984). Within these systems, each individual cloud is the host of complex microphysical processes that influence the partitioning of species among the air, the cloud and the precipitation (Grégoire et al., 1994). Finally, on microscale level, gas absorption and chemical reactions greatly depend on the microstructure of the cloud such as the droplet spectrum. Therefore, one has to consider complex interfacial transfer between gaseous and liquid phases Wurzler et al., 1995, Ricci et al., 1997.
Moreover, these small scale features cannot be ignored at larger scales because removal processes and radiative properties of clouds that perturb photochemistry depend on the microphysical characteristics of the clouds (Madronich, 1987).
In order to simulate such complex interactions on the whole range of scales at which they are important, it is necessary to use several types of models from box chemical model, to mesoscale models.
In this paper, scavenging processes that occur in clouds and their dependency on the fine microphysical features, such as droplet size, liquid water content will be discussed for one particular chemical species, hydrogen peroxide, which is both a soluble and a reactive compound in clouds. The way clouds interact with this particular species will be described in details. In particular, deviations from Henry's law can occur in clouds for this species at the sudden apparition of the aqueous phase or in a cloud, presenting different types of granulometry (cloud droplets vs. raindrops).
Section snippets
Non equilibrium kinetics: mass-transfer of H2O2 between gas and liquid phases
The rate equation in gaseous phase for a particular species may be written as:where Pg and Lg are respectively the production and destruction terms and Cg the gaseous concentration of the species.
With the introduction of cloud water, this equation becomes:where kt describes the mass transfer between the gas and aqueous phases, L the liquid water content, Heff the Henry's law effective constant of the species (Schwartz, 1986) and Caq the aqueous
Deviations from Henry's law for hydrogen peroxide during a cloud lifetime
The evolution of hydrogen peroxide has been followed during a cloud event by means of a chemical box model (Madronich and Calvert, 1990), which interprets any chemical mechanism, including aqueous phase chemistry based upon Grégoire et al. (1994). The chemical system is a standard gas phase mechanism including methane and CO in the presence of NOx and sulfur dioxide. The pH is held constant, equal to 4. Table 1, Table 2, Table 3, Table 4, Table 5 list the reactions, the initial concentrations
Deviations from Henry's law for hydrogen peroxide in a polydisperse cloud
The same type of study (Audiffren et al., 1996) has been performed in the framework of a mesoscale model simulating orographic clouds formed from different air masses (continental vs. maritime). This mesoscale meteorological model is coupled with the chemical module described in Section 3, except that the chemical equation system is solved with a QSSA type solver more appropriate (see Audiffren et al., 1998 for more details). A complete description of the meteorological mountain wave scenario
Conclusion
In this study, several examples of liquid clouds have been simulated by two types of models: a process model and a mesoscale model, including the multiphase chemistry. Experimentally, it is still very difficult to isolate concentrations of chemical species in one particular phase. Moreover, most of the time, samplings of cloud chemistry are based on measurements from pluviometers or impactors that provide time-integrated results, or low-sensitivity airborne measurements. Within the models, it
Acknowledgements
The work reported in this paper was supported by the INSU/CNRS (Institut National des Sciences de l'Univers/Centre National de La Recherche Scientifique) Program PNCA (Programme National de Chimie Atmosphérique). The first authors are very grateful to ADEME and Electricité de France for their support. Computer resources were provided by I.D.R.I.S. (Institut du Développement et Des Ressources en Informatique Scientifique), project no. 187.
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