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Multiphase cloud chemistry modeling: gas versus particle phases

Multiphase cloud chemistry modeling: gas versus particle phases

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Multiphase cloud chemistry modeling: gas versus particle phases

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  1. Multiphase cloud chemistry modeling: gas versus particle phases Maud Leriche, Laurent Deguillaume, Nadine Chaumerliac, Wolfram Wobrock, Karine Sellegri

  2. INDIRECT EFFECT Incident solar radiation DIRECT EFFECT Vertical transport Evaporation Evaporation CCN Aerosols Chemical reactions Chemical reactions IR radiation Wet deposition Wet deposition Activation Precursors Activation Sources Aerosols/cloud/chemistry interactions

  3. Physico-chemical properties of aerosols Microphysical and chemical properties of clouds Puy de Dôme site, center of France Nucleation capacity Hygroscopicity Precipitating capacity Process model M2C2 Model of Multiphase Cloud Chemistry Strategy Classification according to air mass type and cloud type Typical scenarios Role of chemistry Physico-chemical properties of aerosols Microphysical properties of clouds

  4. M2C2 model: Model of Multiphase Cloud Chemistry GAS AEROSOLS rain cloud Collision/coalescence Nucleation Condensation/Evaporation Sedimentation Dynamical framework: air parcel Microphysics: quasi-spectral scheme, log-normal distributions Leriche et al., 2001 ; Curier, 2003

  5. dC k g = - - + t P D C Lk C C Mathematical formulation g g g t g aq dt RTH eff dC k aq = - + - t P D C Lk C C aq aq aq t g aq dt RTH eff M2C2 model: Model of Multiphase Cloud Chemistry Air/droplet exchange: mass transfer kinetic theory (Schwartz, 1986) Explicit chemical mechanism valid for any environment Aqueous phase: chemistry of HxOy, of chlorine, of carbonates, of NOy, of sulfur, oxidation of VOCs, chemistry of transition metals (iron, copper, manganese) pH : calculated at each time step by solving the electroneutrality equation Leriche et al., 2003 ; Deguillaume et al., 2004

  6. Beginning of air parcel ascension Case study: polluted wintertime air mass at Puy de Dôme site Dynamical initialization Dynamical trajectory 3D simulation of meteorological situation on Puy de Dôme area the 13th of December 1997 using meso-scale Clark model The air parcel follows the dynamical back-trajectory, which reaches the Puy de Dôme at 12.11 p.m. Gas phase: available measurements Aqueous phase: chemical soluble species coming from aerosol activation Chemical initialization

  7. chemical composition Mode 1 • microphysical parameters Mode 3 2 Mode 2 Sellegri et al., 2003 1 3 BC OC NO3 SO4 NH4 OI OA H2O nd Case study: polluted wintertime air mass at Puy de Dôme site Aerosol initialization

  8. Aerosol activation Important activation at the beginning: 700 cm-3 Evolution of DCmoy and LWC by condensation/evaporation following ascent and descent of the parcel No significant activation afterwards < 1 cm-3

  9. 6x10-10 1.6x10-12 Initial distribution t0 + 2 mns Distribution initiale Aerosol activation Evolution of aerosol mass distribution Most important activation at the beginning Largest particles activated Spectrum moves towards small diameters at the beginning

  10. 1st nucleation event Initialization of droplet chemical composition [NH4+] = 1,9 10-4 M [SO42-] = 4,3 10-4 M [NO3-] = 2,2 10-4 M origin aerosols chemistry species 65% 35% [NH4+] 10% [SO42-] 90% 50% [NO3-] 50% NH4+ SO42- 27% NO3- 23% Sources of chemical species in cloud Initialization of gas phase Chemical production in aqueous phase: HSO3- + HNO4 Initialization of gas phase Chemical production in aqueous phase : HSO3- + HNO4 Chemical production in gas phase : NO2 + OH

  11. Aerosol activation Significant at the beginning Initialization of the droplet chemical composition Aerosols most important source Others : scavenging of gas and chemical reactivity Sources of chemical species Classification of cloudy events at Puy de Dôme station Generalization of results Conclusion and Perspectives method adapted to the study of aerosols/cloud/chemistry interactions