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Atmospheric modelling of HMs Sensitivity study

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1 Atmospheric modelling of HMs Sensitivity study
Oleg Travnikov EMEP/MSC-E TFMM 6th Meeting, Zagreb 2005

2 Outline Overview of the model formulation
Analysis of the model sensitivity and uncertainty TFMM 6th Meeting, Zagreb 2005

3 Computation domain Regional model (MSCE-HM) Coverage – EMEP region
Resolution – 50×50 km2 EMEP region EMEP region Hemispheric model (MSCE-HM-Hem) Coverage – Northern Hemisphere Resolution – 2.5°×2.5° TFMM 6th Meeting, Zagreb 2005

4 Computation domain Vertical structure: (s-p) coordinate system
15 layers up to 15 km First layer height ~ 70 m TFMM 6th Meeting, Zagreb 2005

5 Model scheme MSCE-HM Input Output Boundary conditions
Atmospheric transport Atmospheric chemistry Dry and wet deposition MSCE-HM Pb, Cd, … Hg TFMM 6th Meeting, Zagreb 2005

6 Atmospheric transport
Species continuity equation Horizontal transport: Monotone Bott scheme (fourth-order area-preserving polynomials) Vertical transport: Bott scheme adapted to irregular vertical grid Vertical eddy diffusion: Second-order implicit finite-difference scheme TFMM 6th Meeting, Zagreb 2005

7 Mass consistency Air continuity equation
Calculation of vertical transport velocities from the air continuity equation: Step I: Calculation of the air horizontal transport using the Bott advection scheme Step II: Calculation of vertical velocities using analytical inversion of the Bott scheme TFMM 6th Meeting, Zagreb 2005

8 Atmospheric transport
Basic tests “Rotational flow” Results: Low numerical diffusion Monotonicity Insignificant distortions Stability in strong deformational flows Low time-splitting error TFMM 6th Meeting, Zagreb 2005

9 Dry deposition Main characteristics: Ecosystem-dependent scheme
Resistance analogy approach Size-segregated deposition velocities of particles Deposited species: Particles (Pb, Cd, Hgpart, …) Gases (Hg2+gas, Hg0) Aqueous Hg species (fog) TFMM 6th Meeting, Zagreb 2005

10 Dry deposition Particles deposition to vegetation:
Theoretical formulation [Slinn, 1982] Empirically derived parameters [Ruijgrok et al., 1997; Wesely et. al., 1985] Ruijgrok Wesely TFMM 6th Meeting, Zagreb 2005

11 Dry deposition Particles deposition to water surface:
Based on the approach from [Williams, 1982] Effects of wave breaking and aerosol washout by seawater spray TFMM 6th Meeting, Zagreb 2005

12 Aerosol scavenging efficiency
Wet deposition Main characteristics: In-cloud and below-cloud scavenging Empirically derived approach: Aerosol scavenging efficiency [Kasper et al., 1998] Rp – precipitation rate A, B – empirical constants In-cloud scavenging efficiency of aerosol: Cw – cloud liquid water content TFMM 6th Meeting, Zagreb 2005

13 Atmospheric chemistry
(Hg) Gas-phase chemistry: Oxidation by ozone, chlorine and hydroxyl radical Aqueous-phase chemistry: Oxidation by dissolved ozone, chlorine and hydroxyl radical Reduction to elemental form Formation of chloride complexes Adsorption by soot particles TFMM 6th Meeting, Zagreb 2005

14 Boundary conditions Mercury
Monthly mean concentrations at the domain boundaries from hemispheric modelling Lead and cadmium Prescribed air concentrations based on measurements data TFMM 6th Meeting, Zagreb 2005

15 Sensitivity and uncertainty analysis
Model sensitivity to input parameters and processes Influence of meteorological variability The model uncertainty TFMM 6th Meeting, Zagreb 2005

16 Model sensitivity Metals: Lead and mercury Model input parameters:
Anthropogenic emission Pb, Hg Speciation of anthropogenic emission Hg Natural emission and re-emission Wet deposition coefficient Dry deposition velocity Boundary concentration Eddy diffusion coefficient Liquid water content Oxidation rate by O3 Oxidation rate by OH Oxidation rate by Cl2 Reduction rate in aqueous phase Hg ion-chloride equilibrium constant Adsorption equilibrium constant pH of cloud water Chloride ion concentration Aerosol solubility Henry’s low constants Metals: Lead and mercury Model input parameters: (Pb – 7, Hg – 25 parameters) Model outputs: Concentration in air Concentration in precipitation Total deposition flux TFMM 6th Meeting, Zagreb 2005

17 Relative deviation of Pb air concentration
Model sensitivity Relative deviation of Pb air concentration Vd x 2 Analysis procedure: Variation of input parameters: X = Xbase · K Relative deviation of the model output: TFMM 6th Meeting, Zagreb 2005

18 Relative deviation of Pb total deposition
Model sensitivity Relative deviation of Pb total deposition Vd x 2 Analysis procedure: Variation of input parameters: X = Xbase · K Relative deviation of the model output: Sensitivity coefficient: TFMM 6th Meeting, Zagreb 2005

19 Sensitivity coefficient
Pb air concentration Pb total deposition Intervals – 90% confidence range TFMM 6th Meeting, Zagreb 2005

20 Sensitivity coefficient
Hg air concentration Hg total deposition TFMM 6th Meeting, Zagreb 2005

21 Meteorological variability
Pb Hg Analysis procedure: Calculation period: The same emission data Relative deviation: Mean square relative error: TFMM 6th Meeting, Zagreb 2005

22 Meteorological variability
Variation of modelling results Intervals – 90% confidence range Pb: ±25-30% for all parameters Hg: ±10% for air concentration, ±20-30% for others TFMM 6th Meeting, Zagreb 2005

23 Model uncertainty Expert estimates of input uncertainties: (20%-90%)
Input parameters ex Anthropogenic emissions 50% Speciation of anthropogenic emission 40% Natural emission and re-emission 90% Wet deposition coefficient 75% Dry deposition velocity Boundary concentration GEM 20% Boundary concentration of Pb Eddy diffusion coefficient Liquid water content Oxidation rate by O3 Oxidation rate by OH Oxidation rate by Cl2 Reduction rate in aqueous phase Hg ion-chloride equilibrium constant Solution-adsorption equilibrium constant pH of cloud water Chloride ion concentration Aerosol solubility Expert estimates of input uncertainties: (20%-90%) 50% TFMM 6th Meeting, Zagreb 2005

24 Model uncertainty Expert estimates of input uncertainties: (20%-90%)
Hg air concentration Expert estimates of input uncertainties: (20%-90%) Uncertainty due to individual parameters: Overall model uncertainty: TFMM 6th Meeting, Zagreb 2005

25 Model uncertainty Lead Mercury
Model intrinsic uncertainty (without emissions) Overall model uncertainty (with emissions) Lead Mercury TFMM 6th Meeting, Zagreb 2005

26 Conclusions Detailed model description was prepared and distributed for the model review Sensitivity analysis has shown that the modelling results for particle bound metals (Pb, Cd, etc.) are the most sensitive to emission data Mercury modelling results are very sensitive to boundary conditions The model intrinsic uncertainty does not exceed 50% Evaluation of the overall model uncertainty requires realistic estimates of emission data uncertainty TFMM 6th Meeting, Zagreb 2005


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