Presentation is loading. Please wait.

Presentation is loading. Please wait.

DEA - Università degli Studi di Brescia Aerosol long term simulation using TCAM model C. Carnevale, G. Finzi, E. Pisoni, M. Volta Department for Electronics.

Published byZachary Thomas Modified over 10 years ago

Similar presentations

Presentation on theme: "DEA - Università degli Studi di Brescia Aerosol long term simulation using TCAM model C. Carnevale, G. Finzi, E. Pisoni, M. Volta Department for Electronics."— Presentation transcript:

1 DEA - Università degli Studi di Brescia Aerosol long term simulation using TCAM model C. Carnevale, G. Finzi, E. Pisoni, M. Volta Department for Electronics and Automation University of Brescia

2 DEA - Università degli Studi di Brescia Index 1.The GAMES modelling system 2.The Transport Chemical Aerosol Model 3.The CityDelta III base case simulation 4.Chemical composition of simulated PM10 5.Conclusion

3 DEA - Università degli Studi di Brescia The Gas Aerosol Modelling Evaluation System (GAMES) Land use Topography MM5 output Meterological Pre-processor TCAM Continental model output Initial and Boundary condition Pre-processors Boundary and Initial condition 3D concentration fields Emission Model Emission inventories Emission Fields 3D wind and temperature fields Turbolence and Boundary Layer parameters VOC speciation Profiles Temporal Profiles System Evaluation Tool

4 DEA - Università degli Studi di Brescia TCAM (Transport and Chemical Aerosol Model): Transport and Depostion Module Eulerian 3D model Terrain-following co-ordinate system Horizontal Transport Module: chapeau function + forester filter Vertical Transport Module: Crank-Nicholson hybrid solver based on the vertical diffusivity coefficient Deposition Module –Dry deposition: resistance-based approach –Wet deposition: scavenging approach for both gas and aerosol species

5 DEA - Università degli Studi di Brescia TCAM (Transport and Chemical Aerosol Model): Gas chemical module Chemical Mechanism –CBIV 90 –SAPRC 90/97 –COCOH 97 Numerical Solver –QSSA (explicit) –IEH (hybrid) Species: 95 Reactions: 187 Fast-Species (12): LSODE (implicit) Slow-Species: Adams-Bashforth (explicit)

6 DEA - Università degli Studi di Brescia Chemical Species: 21 –12 inorganics –9 organics Size Classes: 10 (da 0.01 m a 50 m) –Fixed moving approach Involved Phenomena: –Condensation/Evaporation –Nucleation –SO 2 aqueus chemistry TCAM (Transport and Chemical Aerosol Model): Aerosol module Shell Core

7 DEA - Università degli Studi di Brescia CDIII base case simulation: computational domain 300x300 km 2 Horizontal resolution: 5x5 km 2 Vertical resolution: 11 varying thickness levels –1st level: 20m Simulation year: 2004

8 DEA - Università degli Studi di Brescia CDIII base case simulation: Gas emission fields VOC NOx NH3 SOx

9 DEA - Università degli Studi di Brescia CDIII base case simulation: PM emission fields PM10PM2.5

10 DEA - Università degli Studi di Brescia CDIII base case simulation: Monitoring station Station Yearly Mean Winter Mean Summer Mean Osio42.7957.8328.00 Vimercate42.3153.6429.33 Rezzato49.1162.1333.68 Juvara50.9861.9234.41 Limito43.1959.6229.96 Magenta49.2959.5434.07 Verziere51.8362.6237.07

11 DEA - Università degli Studi di Brescia CDIII base case simulation: Yearly Performance Mean 95th Perc CorrelationNBIAS

12 DEA - Università degli Studi di Brescia CDIII base case simulation: Winter Performances Mean 95th Perc CorrelationNBIAS

13 DEA - Università degli Studi di Brescia CDIII base case simulation: Summer Performances Mean 95th Perc CorrelationNBIAS

14 DEA - Università degli Studi di Brescia CDIII base case simulation: PM10 concentration maps Year Winter Summer

15 DEA - Università degli Studi di Brescia CDIII base case simulation: PM10 yearly chemical composition

16 DEA - Università degli Studi di Brescia CDIII base case simulation: mainly inorganic fraction maps NH4+ NO3-

17 DEA - Università degli Studi di Brescia Conclusion Quite good performance in terms of mean values both in winter and summer; Correlation lower than 0.65 in all the station –CAUSES? TCAM reproduces reasonably the chemical composition of PM10 –overestimation of ammonium fraction

18 DEA - Università degli Studi di Brescia Emission pre-processor (UNIBS) POllutant Emission Model for CDIII (POEM-CDIII) provides hourly base case and scenario emission fields for: CAMx TCAM JRC data Time modulation Chemical characterization Chemical/Size characterization Gas: CBIV99 PM: 2 size bins, 8 chemical species Gas: COCOH97 PM: 6 size bins, 8 chemical species CESI AMA

19 DEA - Università degli Studi di Brescia Boundary pre-processor (CESI) Boundy Module provides hourly base case and scenario boundary conditions Chimere Gas: 23 species PM: 4 size bins 11 chemical species BOUNDY TCAM Gas: 62 species PM: 10 size bins 21 chemical species PM experimental size profiles

20 DEA - Università degli Studi di Brescia CDIII base case simulation: PM2.5/PM10 concentration map PM2.5/PM10 Concentration PM2.5/PM10 Emisison

Download ppt "DEA - Università degli Studi di Brescia Aerosol long term simulation using TCAM model C. Carnevale, G. Finzi, E. Pisoni, M. Volta Department for Electronics."

Similar presentations

DEA - Università degli Studi di Brescia TCAM model configuration for POMI simulations C. Carnevale, G. Finzi, E. Pisoni, M. Volta Dipartimento di Elettronica.

DEA - Università degli Studi di Brescia TCAM model configuration for POMI simulations C. Carnevale, G. Finzi, E. Pisoni, M. Volta Dipartimento di Elettronica.
R. L. Buckley and C. H. Hunter Atmospheric Technologies Group Savannah River National Laboratory Recent Improvements to an Advanced Atmospheric Transport.

R. L. Buckley and C. H. Hunter Atmospheric Technologies Group Savannah River National Laboratory Recent Improvements to an Advanced Atmospheric Transport.
ESF- MedCLIVAR Workshop Climate Change Modeling for the Mediterranean region, ICTP, Trieste, Italy, 13-15 Oct 2008 Regional air quality decadal simulations.

ESF- MedCLIVAR Workshop Climate Change Modeling for the Mediterranean region, ICTP, Trieste, Italy, Oct 2008 Regional air quality decadal simulations.
PREV AIR : An operational system for air quality monitoring and forecasting www.prevair.org presented by Laurence Rouïl.

PREV AIR : An operational system for air quality monitoring and forecasting presented by Laurence Rouïl.
POMI Po Valley Model Intercomparison Exercise CAMx model overview In cooperation with AMA - MI.

POMI Po Valley Model Intercomparison Exercise CAMx model overview In cooperation with AMA - MI.
Integrated modelling and monitoring for use in forecasting Jørgen Brandt and Finn Palmgren National Environmental Research Institute Department of Atmospheric.

Integrated modelling and monitoring for use in forecasting Jørgen Brandt and Finn Palmgren National Environmental Research Institute Department of Atmospheric.
Institute for Environment and Sustainability1 POMI Kick-off Meeting 07/03/2008.

Institute for Environment and Sustainability1 POMI Kick-off Meeting 07/03/2008.
Urban Modelling 1 03/2003 © Crown copyright Urban Scale NWP with the Met Office's Unified Model Peter Clark Mesoscale Modelling Group Met Office Joint.

Urban Modelling 1 03/2003 © Crown copyright Urban Scale NWP with the Met Office's Unified Model Peter Clark Mesoscale Modelling Group Met Office Joint.
Paolo Tuccella, Gabriele Curci, Suzanne Crumeyrolle, Guido Visconti

Paolo Tuccella, Gabriele Curci, Suzanne Crumeyrolle, Guido Visconti
PREV AIR : An operational system for large scale air quality monitoring and forecasting www.prevair.org.

PREV AIR : An operational system for large scale air quality monitoring and forecasting
CHIMERE air quality forecasts : results during Pays de la Loire summer 2004 experiment and end-user point of view ! Arnaud REBOURS - AIR PAYS DE LA LOIRE.

CHIMERE air quality forecasts : results during Pays de la Loire summer 2004 experiment and end-user point of view ! Arnaud REBOURS - AIR PAYS DE LA LOIRE.
EC Regional Air Quality Deterministic Prediction System (RAQDPS) Mike Moran Air Quality Research Division Environment Canada, Toronto, Ontario Mtg on AQ.

EC Regional Air Quality Deterministic Prediction System (RAQDPS) Mike Moran Air Quality Research Division Environment Canada, Toronto, Ontario Mtg on AQ.
National Institute of Environmental Research Atmospheric Physics Division National Institute of Environmental Research Fax:82-32-568-2040,

National Institute of Environmental Research Atmospheric Physics Division National Institute of Environmental Research Fax: ,
Use of Lidar Backscatter to Determine the PBL Heights in New York City, NY Jia-Yeong Ku, Chris Hogrefe, Gopal Sistla New York State Department of Environmental.

Use of Lidar Backscatter to Determine the PBL Heights in New York City, NY Jia-Yeong Ku, Chris Hogrefe, Gopal Sistla New York State Department of Environmental.
Applying the DELTA-FAIRMODE tool to support AQD: the validation of the TCAM Chemical Transport Model C. Carnevale, G. Finzi, A. Pederzoli, P. Thunis, E.

Applying the DELTA-FAIRMODE tool to support AQD: the validation of the TCAM Chemical Transport Model C. Carnevale, G. Finzi, A. Pederzoli, P. Thunis, E.
The MINNI Project Italian Agency for New Technologies Energy and the Environment Long Range Transboundary Air Pollution Convention TFIAM Meeting, Amiens,

The MINNI Project Italian Agency for New Technologies Energy and the Environment Long Range Transboundary Air Pollution Convention TFIAM Meeting, Amiens,
A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University.

A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University.
1 AirWare : AirWare : C OMPREHENSIVE A IR QUALITY M ODEL WITH E X TENSIONS VERSION 4.30, PBM DDr. Kurt Fedra Environmental Software & Services GmbH A-2352.

1 AirWare : AirWare : C OMPREHENSIVE A IR QUALITY M ODEL WITH E X TENSIONS VERSION 4.30, PBM DDr. Kurt Fedra Environmental Software & Services GmbH A-2352.
1 st Chimere workshop 21-22 March 2005Stortini,Bonafe,Deserti,Minguzzi,Jongen Operational implementation of NINFA in Northern Italy ARPA Servizio IdroMeteorologico.

1 st Chimere workshop March 2005Stortini,Bonafe,Deserti,Minguzzi,Jongen Operational implementation of NINFA in Northern Italy ARPA Servizio IdroMeteorologico.
CMAQ and REMSAD- Model Performance and Ongoing Improvements Brian Timin, Carey Jang, Pat Dolwick, Norm Possiel, Tom Braverman USEPA/OAQPS December 3, 2002.

CMAQ and REMSAD- Model Performance and Ongoing Improvements Brian Timin, Carey Jang, Pat Dolwick, Norm Possiel, Tom Braverman USEPA/OAQPS December 3, 2002.

Similar presentations

Ads by Google