Impact of particles on photolysis rates and Results Impact on - PowerPoint PPT Presentation

Introduction Model description Impact of particles on photolysis rates and Results Impact on photolysis air quality rates Impact on concentrations Impact on air quality monitoring Elsa Real a and Karine Sartelet a Conclusions 3 juin 2010 a CEREA (joint laboratory ENPC - EDF R&D) Université Paris-Est, Marne la Vallée, France

How aerosols impact photolysis rates and gas concentrations ? Clear sky conditions With clouds and aerosols Introduction Optical Properties and Model Optical Depth: Φ description = solar flux - aerosol numbers - size distribution Results - chemical composition Impact on photolysis rates Impact on σ gaz = cross section concentrations Impact on air quality monitoring J(λ)=∫ σ gaz (λ) * Φ (λ) Conclusions photolysis rates

How aerosols impact photolysis rates and gas concentrations ? Clear sky conditions With clouds and aerosols Introduction Optical Properties and Model Optical Depth: Φ description = solar flux - aerosol numbers - size distribution Results - chemical composition Impact on photolysis rates Impact on σ gaz = cross section concentrations Impact on air quality monitoring J(λ)=∫ σ gaz (λ) * Φ (λ) Conclusions photolysis rates

How aerosols impact photolysis rates and gas concentrations ? Clear sky conditions With clouds and aerosols Introduction Optical Properties and Model Optical Depth: Φ = solar flux description - aerosol numbers - size distribution Results - chemical composition Impact on photolysis rates σ gaz = cross section Impact on concentrations Impact on air quality J(λ)=∫ σ gaz (λ) * Φ (λ) monitoring Conclusions photolysis rates Main photolysis reactions Ozone production Ozone loss and OH production JNO 2 JO 3 NO 2 + h ν → NO + O( 3 P) O 3 + h ν → O 1 D + O 2 − − − − − O( 3 P) + O 2 + M − → O 3 + M O 2 + H 2 O − → 2 OH − − − −

Coupling a regional CTM with a photolysis scheme Polyphemus Polyphemus Regional Aerosols Polair3D Polair3D concentrations, size, chemical Gases Introduction composition CTM Chemical scheme : RACM, Model Aerosol scheme : SIREAM description (16 aerosol species) Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions Radiative FAST-J FAST-J model Photolysis rates photolysis rate scheme

Coupling a regional CTM with a photolysis scheme Polyphemus Polyphemus Regional Aerosols Polair3D Polair3D concentrations, size, chemical Gases Introduction composition CTM Chemical scheme : RACM, Model Aerosol scheme : SIREAM description (16 aerosol species) Results Impact on photolysis rates Impact on concentrations OPAC OPAC Impact on air quality Optical properties and depth monitoring (refractive index (ω, Q, φ) database) Conclusions + Mie code Mie code Radiative FAST-J FAST-J model Photolysis rates photolysis rate scheme (each hour of the simulation)

Setting of the simulations Run : 2 simulations, with and without taking into account Introduction photolysis rate modifications by aerosols R-AERO and Model description R-NOAERO Results Impact on photolysis rates Domain : Europe (0.5˚ × 0.5˚) and 13 vertical levels up to 10 Impact on concentrations km. Impact on air quality monitoring Conclusions Meteorological data : ECMWF (0.36˚ × 0.36˚). Boundary conditions : MOZART for gas and GOCART for aerosols Time : 1 summer month (15 July-15 August) of 2001

Description of the aerosols simulation Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring F IG .: Monthly mean tropospheric AOD F IG .: AOD vertical profile averaged over Europe. Conclusions Contributions of individual species to the total AOD are shown.

Description of the aerosols simulation Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring F IG .: Monthly mean tropospheric AOD F IG .: AOD vertical profile averaged over Europe. Conclusions Contributions of individual species to the total AOD are shown. AOD comparaison with AERONET data Mean correlation RMSE NMB NME Measurement 0.2 Simulation 0.3 78% 0.2 20% 39% Acording to these statistics AOD simulated by the model are realistic.

Impact on photolysis rates Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions F IG .: JNO 2 monthly mean ground relative F IG .: Vertical profiles of relative difference between differences between R-AERO and R-NOAERO R-AERO and R-NOAERO for JNO 2 and JO 3 Strong decrease of photolysis rates are spatially correlated with strong OD Larger impact at the ground

Impact on gas concentrations Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions F IG .: Vertical profiles of relative difference between O 3 , NO, NO 2 and OH concentrations simulated with R-AERO and R-NOAERO Main photolysis reactions JNO 2 JO 3 NO 2 + h ν → NO + O( 3 P) O 3 + h ν → O 1 D + O 2 − − − − − O( 3 P) + O 2 + M − → O 3 + M O 2 + H 2 O − → 2 OH − − − −

Impact on gas concentrations Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions F IG .: Vertical profiles of relative difference between O 3 , NO, NO 2 and OH concentrations simulated with R-AERO and R-NOAERO Main photolysis reactions for OH JO 3 O 3 + h ν → O 1 D + O 2 − − O 2 + H 2 O − → 2 OH − −

Impact on gas concentrations Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions F IG .: Vertical profiles of relative difference between O 3 , NO, NO 2 and OH concentrations simulated with R-AERO and R-NOAERO Main photolysis reactions for NO JNO 2 NO 2 + h ν → NO + O( 3 P) − − − .

Impact on gas concentrations Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions F IG .: Vertical profiles of relative difference between O 3 , NO, NO 2 and OH concentrations simulated with R-AERO and R-NOAERO Main photolysis reactions for NO 2 JNO 2 NO 2 + h ν → NO + O( 3 P) − − − .

Impact on gas concentrations Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions F IG .: Vertical profiles of relative difference between O 3 , NO, NO 2 and OH concentrations simulated with R-AERO and R-NOAERO Main photolysis reactions for O 3 JNO 2 JO 3 NO 2 + h ν → NO + O( 3 P) O 3 + h ν → O 1 D + O 2 − − − − − O( 3 P) + O 2 + M − → O 3 + M O 2 + H 2 O − → 2 OH − − − −

Impact on ground gas concentrations OH ground concentrations Mean reductions of 12% with peak Introduction up to 30% Model ⇒ reduction of the global oxydizing description capacity. For example isoprene Results Impact on photolysis concentrations increase by around rates Impact on 10 % concentrations Impact on air quality monitoring Conclusions O 3 ground concentrations O 3 decrease is maximum where O 3 production strongly dominates O 3 loss. O 3 mean decrease is about 4% with peak at 8%.

Impact on ground aerosols concentrations Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions Secondary aerosol formation is modified by the change on oxydant ( OH, O 3 , HO 2 ) concentrations Ground concentrations of SO 4 and secondary organic are reduced by 3-4 %. Small changes on spatially averaged PM 10 ground concentrations but reduction by up to 8% in regions where AOD and secondary aerosol formation are important

Comparaison with EMEP data Mean correlation RMSE NMB NME Introduction Measurement 74.7 Model O 3 R-NOAERO 84.6 53.9% 28.5 19% 33.4% description R-AERO 81.9 54.4% 27.5 15% 32.1% Results Impact on photolysis Measurement 4.8 rates NO 2 R-NOAERO 4.1 32.2% 2.5 10% 62.7% Impact on concentrations R-AERO 4.2 32.9% 2.5 13% 63.9% Impact on air quality monitoring Measurement 18.7 Conclusions PM 10 R-NOAERO 10.9 71.5% 9.9 37% 42.1% R-AERO 10.9 72.1% 9.8 36% 42% Statistics are slightly better when including photolysis rates modification by aerosols but differences are small.

Which consequences on pollutants thresholds ? Introduction Model description Results Impact on photolysis rates Impact on concentrations Impact on air quality monitoring Conclusions F IG .: Number of O 3 threshold exceedances non simulated with R-AERO Including photolysis rates modifications by aerosols leads to a decrease by a factor 2 of the exceedances of the European alert O 3 threshold (O 3 > 240 µ g.m − 3 ) and the information threshold (O 3 > 180 µ g.m − 3 ).