FARM / SURFPro Novità nei modelli Bologna, 4 marzo 2010 ENEA, Riunione plenaria MINNI - Bologna, 4 marzo 2010

Main fatures: Emission of pollutants from area and point sources, with plume rise calculation and mass assignment to vertical grid cells 3D dispersion by advection and turbulent diffusion flexible gas-phase chemical mechanisms configuration FCM Software (SAPRC-90, SAPRC-99, SAPRC-07, EMEP-acid – through FCM) Treatment of PM 10 and PM 2.5 (aero0 inorganic equilibrium module, aero3 modal aerosol module) Dry removal of pollutants dependent on local meteorology and land-use Removal through precipitation scavenging processes One- and two-way nesting on arbitrary number of grids Treatment of additional inert tracers Parallel processing using OpenMP paradigm Inclusion of data assimilation techniques Online calculation of photolysis rates using TUV model (Tropospheric Ultraviolet and Visible radiation model; Madronich et al, 1989); RADM method to correct for cloud cover (Chang et al., 1987) Inclusion of map scale factors and different coordinate systems SAPRC99 and POPs-Hg Gas-phase chemical mechanisms generated via KPP Software (LSODE/Rosenbrock solvers) FARM (Flexible Air quality Regional Model)

Parallel processing using OpenMP paradigm

Speed-Up 4 Processori8 Processori

Inclusion of data assimilation techniques

Zona di conformità Zona di non conformità è possibile combinare le misurazioni in siti fissi con le tecniche di modellizzazione e/o le misurazioni indicative al fine di valutare la qualità dellaria ambiente (la modellazione ha lo stesso valore delle misurazioni) è possibile utilizzare solo tecniche di modellizzazione o di stima obiettiva al fine di valutare la qualità dellaria ambiente (la modellazione è alternativa alle misurazioni) la qualità dellaria ambiente è valutata tramite misurazioni in siti fissi. Tali misurazioni possono essere integrate da tecniche di modellizzazione e/o da misurazioni indicative (la modellazione è secondaria rispetto alle misurazioni) Valore limite (VL) Soglia di valutazione superiore (SVS) Soglia di valutazione inferiore (SVI) Assessment under EU Air Quality Directives Combining models with measurement

100% measurement Measurement, no interpretation Measurement+interpretation Measurement+interpolation Measurement+model fitted to measurement Data assimilation Model validated by measurement in the same zone Model validated elsewhere Unvalidated model 100% modelling Assessment under EU Air Quality Directives Combining models with measurement …there is an almost continuous spectrum of combination of measurements and other assessment methods (mathematical techniques and models) From: Guidance on Assessment under the EU Air Quality Directives, EEA 2002 modelling measurement

Measurement no interpretation Measurement and interpolation Model validated by measurement in the same zone Data Assimilation Measurement Modelling Proposta Integrazione dei dati sperimentali contenuti nel dataset BRACE per la produzione di campi di analisi sul territorio italiano.

1.Observational Nudging/Newtonian Relaxation technique; 2.Optimal Interpolation; 3.Bratseth method of Successive Corrections. Schemi di analisi oggettiva implementati in FARM

The time evolution of the i-th chemical species over the time step Δt is then computed as follow: where L N is the nudging operator. Including the obs nudging (1), the nudging operator has the form: Using the Optimal Interpolation (2) (or the Successive Correction Method / Bratseth scheme), L N has the form: where c A i is the gridded analysed concentration field. Schemi di analisi oggettiva implementati in FARM

Let c(i,j,z=z 0,t) the increment (or decrement) of surface concentration (z=z 0 ) at grid cell (i,j) at time t due to observational nudging. The concentration at upper layers is then computed as follow: R v = 100 m Upper layers weighting

For observational nudging G A is given by the following expressions: i is the observational quality factor, ranging from 0 to 1, that takes into accounts for characteristic errors in measurements and representativeness Observational Nudging/Newtonian Relaxation technique

W j is given by: R is the specified obs radius of influence D id the distance between obs and the grid point z is the vertical distance and R z the vertical scale lenght is the specified time window for obs Observational Nudging/Newtonian Relaxation technique

Weights: W j W x,y WtWt

The analysed state vector X A is given by: where: X G : background state vector Y: observation vector H: observation operator (model space to observation space) B: background error covariance matrix R: observation error covariance matrix K: gain matrix Optimal Interpolation

The Bratseth technique (Bratseth, 1986) is a successive correction scheme that converges to optimal interpolation due to the inclusion of background and observation error statistics. The analysis is initialised with a background field, or first guess, which is then modified by the analysis of local data onto the model grid. The Bratseth Method of Successive Corrections

Online calculation of photolysis rates using TUV model

Calcolo dei ratei di fotolisi Approccio attuale (FCM) Linserimento di un modulo di trasferimento radiativo per il calcolo dei ratei di fotolisi delle diverse specie in un modello di chimica dellatmosfera determina un significativo incremento del tempo di calcolo. Per tale ragione nel modello FARM i ratei di fotolisi delle diverse specie chimiche vengono calcolati mediante lutilizzo di look-up tables assumendo condizioni di cielo sereno. Tali ratei vengono stimati al livello del suolo e quindi corretti per le quote superiori mediante lutilizzo di formule empiriche (Peterson, 1976).

Main fatures: Tropospheric Ultraviolet-Visible Model (TUV) has been developed by Madronich [1989]. TUV is a state-of-the-art radiation transfer model, and is widely used by the scientific community. TUV calculates spectral irradiance, spectral actinic flux, and photodissociation rates (J-values) for the wavelength range between 121 and 750 nm. References: Madronich, S., Photodissociation in the atmosphere 1. Actinic flux and the effect of ground reflections and clouds, J. Geophys. Res., 92, , Calcolo dei ratei di fotolisi TUV

NO 2 + h NO + O ( < 424 nm) actinic flux (photons cm -2 s -1 nm -1 ) absorption cross section (cm 2 ) photolysis quantum yield (photons -1 ) Calcolo dei ratei di fotolisi TUV j-Values: Definition

solar zenith angle observer altitude ozone profile/amount other absorbers/scatterers (O 2, air) surface reflectivity (albedo), Spectral albedo file to be used (as done in MODTRAN) surface altitude aerosol morphology/optical properties cloud morphology/optical properties atmospheric refraction Calcolo dei ratei di fotolisi TUV Factors Affecting Actinic Flux

Calcolo dei ratei di fotolisi in assenza di nuvole NO 2 + h NO + O ( < 424 nm)

Calcolo dei ratei di fotolisi in presenza di nuvole Approccio attuale

Calcolo dei ratei di fotolisi in presenza di nuvole Chang et al., 1987

Calcolo dei ratei di fotolisi in presenza di nuvole Al di sotto della cloud base

Calcolo dei ratei di fotolisi in presenza di nuvole Al di sopra della cloud base

Calcolo dei ratei di fotolisi in presenza di nuvole Confronto al di sotto della cloud base cld bot cld top TCC = 1 cld top -cld nùbot =1000 m

Calcolo dei ratei di fotolisi in presenza di nuvole Confronto al di sotto della cloud base

Calcolo dei ratei di fotolisi in presenza di nuvole Confronto al di sopra della cloud base

Original data Interpolated data Cressmann Calcolo dei ratei di fotolisi (TUV) Columnar ozone - OMI Satellite data 24 June 2009

Calcolo dei ratei di fotolisi (TUV) Columnar ozone - OMI Satellite data 3 January 2005 Optimal Interpolation # of influential points = 50 correlation lenght=20° Original data

Calcolo dei ratei di fotolisi in presenza di nuvole Calcolo dello spessore ottico

Calcolo dei ratei di fotolisi in presenza di nuvole Calcolo dello spessore ottico

Inclusion of map scale factors

Computing Scale Factors where m is the local scale factor, and the symbol dist stands for a small increment of distance on either the map or the earth accordingly.

Advection-diffusion operators where L x, L y are advection-diffusion operators along the two horizontal axes, L z is the vertical operator taking into account transport, diffusion, source injection E i and dry deposition R i processes. c i is i-th gas-phase average species concentration, u, v and w are the components of wind velocity vector, K H and K V the lateral and vertical diffusivities and m is the map scale factor (ratio of the length of a path on the map to the length of the path that it represents on the earth)

Map factor analysis GEMS Domain

Map factor analysis MINNI Domain

POPs and Hg gas-phase chemical mechanism

KPP species #include atoms #DEFVAR { Inorganics } NO= N + O; NO2= N + 2O; NO3= N + 3O; HNO3= H + N + 3O; N2O5= 2N + 5O; PAN= 2C + 3H + 5O + N; SO2= S + 2O; H2SO4= 2H + S + 4O; { PAHs } PAH1= IGNORE; {B[a]P, Benzo[a]pyrene} PAH2= IGNORE; {B[b]F, Benzo[b]fluorene} PAH3= IGNORE; {B[k]F, Benzo[k]fluorene} I_P= IGNORE; {indeno[1,2,3-cd]pyrene} { Dioxins } PCDD1= IGNORE; {2,3,7,8-TeCDD} PCDD2= IGNORE; {1,2,3,7,8-PeCDD} PCDD3= IGNORE; {1,2,3,4,7,8-HxCDD} PCDD4= IGNORE; {1,2,3,6,7,8-HxCDD} PCDD5= IGNORE; {1,2,3,7,8,9-HxCDD} PCDD6= IGNORE; {1,2,3,4,6,7,8-HpCDD} OCDD= IGNORE; {OCDD}

KPP species { Furans } PCDF1= IGNORE; {2,3,7,8-TeCDF} PCDF2= IGNORE; {1,2,3,7,8-PeCDF} PCDF3= IGNORE; {2,3,4,7,8-PeCDF} PCDF4= IGNORE; {1,2,3,4,7,8-HxCDF} PCDF5= IGNORE; {1,2,3,6,7,8-HxCDF} PCDF6= IGNORE; {1,2,3,7,8,9-HxCDF} PCDF7= IGNORE; {2,3,4,6,7,8-HxCDF} PCDF8= IGNORE; {1,2,3,4,6,7,8-HpCDF} PCDF9= IGNORE; {1,2,3,4,7,8,9-HpCDF} OCDF= IGNORE; {OCDF} { PCBs } PCB1= IGNORE; {PCB-28} PCB2= IGNORE; {PCB-105} PCB3= IGNORE; {PCB-118} PCB4= IGNORE; {PCB-153} PCB5= IGNORE; {PCB-180} { Pesticides } gHCH= IGNORE; {gamma-Hexachlorocyclohexane} HCB= IGNORE; {C6Cl6} { Mercury } Hg= Hg; {Mercury elemental} HgO= Hg + O; {Mercury oxide} HgAER= IGNORE; {Mercury in particulate form}

KPP species #DEFFIX O3 = 3O; OH= H + O; CCO_O2= 2C + 3O; H2O= 2H + O; H2O2= 2H + 2O;

KPP reactions #Equations {Inorganic EMEP Acid Reactions} {1} NO2 + hv = NO : phk(1); {fcm_saprc99_phk('NO2_____',1e0,zenith);} {2} O3 + NO = NO2 : ARR(1.80e-12,1370.0e0,0.0e0); {3} O3 + NO2 = NO3 : ARR(1.40e-13,2470.0e0,0.0e0); {4} OH + NO2 = HNO3 : FALL(2.43e-30, 0.0e0,-3.10e0,1.67e-11,0.0e0,-2.10e0,0.60e0); {5} CCO_O2 + NO2 = PAN : FALL(2.70e-28,0.0e0,-7.10e0,1.20e-11,0.0e0,-0.90e0,0.30e0); {6} PAN = NO2 : FALL(4.90e-3, e0,0.0e0,4.0e+16, e0,0.e0,0.3e0); {7} OH + SO2 = H2SO4 :FALL(4.00e-31,0.0e0,-3.30e0,2.00e-12,0.0e0,0.0e0,0.45e0); {8} NO3 + hv = NO : phk(2); {fcm_saprc99_phk('NO3NO___',1e0,zenith);} {9} NO3 + hv = NO2 : phk(3); {fcm_saprc99_phk('NO3NO2__',1e0,zenith);} {10} NO2 + NO3 = N2O5 : FALL(2.80e-30,0.0e0,-3.50e0,2.00e-12,0.0e0,0.20e0,0.45e0); {11} N2O5 = NO2 + NO3 : FALL(1.e-3, e0,-3.5e0,9.7e+14, e0,0.1e0,0.45e0); {12} N2O5 + H2O = 2HNO3 : (2.60e-22); {13} NO + NO3 = 2NO2 :ARR(1.80e-11,-110.0e0,0.0e0); {PAHs: Meylan and Howard, 1993 cited in SRC PhysProp Database} {14} PAH1 + OH = PROD :(5.000e-11); {15} PAH2 + OH = PROD :(1.860e-11); {16} PAH3 + OH = PROD :(5.360e-11); {17} I_P + OH = PROD :(6.447e-11);

KPP reactions {PCDDs: Brubaker and Hites, 1997} {18} PCDD1 + OH = PROD :(1.05e-12); {19} PCDD2 + OH = PROD :(5.60e-13); {20} PCDD3 + OH = PROD :(2.70e-13); {21} PCDD4 + OH = PROD :(2.70e-13); {22} PCDD5 + OH = PROD :(2.70e-13); {23} PCDD6 + OH = PROD :(1.30e-13); {24} OCDD + OH = PROD :(5.00e-14); {PCDFs: Brubaker and Hites, 1997} {25} PCDF1 + OH = PROD :(6.10e-13); {26} PCDF2 + OH = PROD :(3.00e-13); {27} PCDF3 + OH = PROD :(3.00e-13); {28} PCDF4 + OH = PROD :(1.40e-13); {29} PCDF5 + OH = PROD :(1.40e-13); {30} PCDF6 + OH = PROD :(1.40e-13); {31} PCDF7 + OH = PROD :(1.50e-13); {32} PCDF8 + OH = PROD :(6.00e-14); {33} PCDF9 + OH = PROD :(6.00e-14); {34} OCDF + OH = PROD :(3.00e-14);

KPP reactions {PCBs: Anderson and Hites, 1996; Beyer and Matthies, 2001} {35} PCB1 + OH = PROD :ARR(2.70e-10,1650.0e0,0.0e0); {36} PCB2 + OH = PROD :ARR(6.15e-11,1554.0e0,0.0e0); {37} PCB3 + OH = PROD :ARR(6.15e-11,1554.0e0,0.0e0); {38} PCB4 + OH = PROD :ARR(8.12e-11,1850.0e0,0.0e0); {39} PCB5 + OH = PROD :ARR(1.40e-10,2146.0e0,0.0e0); {Pesticides: Brubaker and Hites, 1997} {40} gHCH + OH = PROD :ARR(6.00e-11,1708.0e0,0.0e0); {41} HCB + OH = PROD :ARR(4.90e-10,2923.0e0,0.0e0); {Mercury: Xie et al., 2008 and Jung et al., 2009, AER from CMAQ} {42} Hg + O3 = 0.5HgO + 0.5HgAER:ARR(8.43e-17,1407.0e0,0.0e0); {43} Hg + OH = 0.5HgO + 0.5HgAER:ARR(3.55e-14,-294.0e0,0.0e0); {44} Hg + H2O2 = HgO :(8.50e-19); {44} Hg + NO3 = HgO + NO2:(4.00e-15);

POPs processes

Degradation process of POPs in the atmosphere is considered as the gas-phase reaction of pollutants with hydroxyl radicals and all other reactions are neglected. The degradation process in the atmosphere is described by the equation of the second order: dC/dt=-k air · C ·[OH] where: C is the pollutant concentration in air (gaseous phase), ng/m 3 ; [OH] is the concentration of OH radical, molec/cm 3 ; k air is the degradation rate constant for air, cm 3 /(molec s). Degradation in air

POP partitioning between the gaseous and particulate phase is performed using the Junge-Pankow model [Junge, 1977; Pankow, 1987] based on subcooled liquid vapour pressure p OL (Pa). According to this model the POP fraction adsorbed on tropospheric aerosol particles equals to: = c· / (p OL + c·) where: c is the constant dependant on the thermodynamic parameters of the adsorption process and on the properties of aerosol particle surface; it is assumed c=0.17 Pa·m [Junge, 1977] for background aerosol; θ is the specific surface of aerosol particles, m 2 /m 3. Gas/particle partitioning

Dry deposition flux of the gas-phase is not considered. Dry deposition flux of the particulate phase F p dry (ng/m 2 /s) is a product of dry deposition velocity v d (m/s) and air concentration C P (ng/m 3 ) of a pollutant in the particulate phase taken at an air reference level coinciding with the middle of the lowest atmospheric layer: F p dry = v d · C P Dry deposition

Wet deposition of POPs in gaseous and particulate phase is distinguished in the MSCE-POP model. Making an assumption that the pollutant does not redistribute between dissolved and particulate phase within a raindrop, total dimensionless ratio W T for a substance washout with precipitation is determined by the following equation: W T = W g ·(1-) + W P · Where: W g is the washout ratio of the POP gaseous phase; W P is the washout ratio of a substance associated with aerosol particles; is the substance fraction associated with aerosol particles in the atmosphere. Wet deposition

Allinterno delle nuvole viene utilizzatto lapproccio proposto da Karamchandani (implementato in CAMx - ENVIRON, 2003) per la simulazione dei processi di ossidazione/riduzione che determinano I livelli di mercurio elementare Hg(0) e mercurio ossidato Hg(II). La maggior parte delle secie chimiche necessarie sono fornite da FARM. Le concentrazioni di Cl 2 e HCl sono assunte considerando valori e profili verticali di letteratura. ENVIRON (2003) Modeling Atmospheric Mercury Chemistry and Deposition with CAMx for a 2002 Annual Simulation. Aqueous-Phase Hg Chemistry