DEA - Università degli Studi di Brescia Aerosol long term simulation using TCAM model C. Carnevale,...

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


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


The Gas Aerosol Modelling Evaluation System (GAMES)

Land useTopography MM5

output

MeterologicalPre-processor

TCAM

Continental modeloutput

Initial andBoundary condition

Pre-processors

Boundary andInitial condition

3D concentrationfields

EmissionModel

Emission inventories

Emission Fields

3D wind and temperature fields Turbolence and Boundary Layer parameters

VOC speciationProfiles

TemporalProfiles

SystemEvaluation

Tool


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


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)


• 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

– SO2 aqueus chemistry

TCAM (Transport and Chemical Aerosol Model):Aerosol module

Shell

Core


CDIII base case simulation: computational domain

• 300x300 km2

• Horizontal resolution: 5x5 km2

• Vertical resolution: 11 varying thickness levels– 1st level: 20m

• Simulation year: 2004

400 450 500 550 600 650

4900

4950

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MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

0

200

400

600

800

1000

1200

1400

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1800

2000

2200

2400

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3000

(m asl)

X U TM (km )

Y U

TM

(km

)


CDIII base case simulation: Gas emission fields

VOC

NOx

NH3

SOx

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

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4950

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0

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6500

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

020406080100120140160180200220240260280300320340360380400420

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

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4950

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5050

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MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

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4950

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0

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400

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800

900

1000

1100

1200

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1400

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1600

1700

1800


CDIII base case simulation:PM emission fields

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

020406080100120140160180200220240260280300320340360380400420

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

0

20

40

60

80

100

120

140

160

180

200

220

240

260

280

300

320

340

360

380

PM10 PM2.5


CDIII base case simulation:Monitoring station

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

TORI NO

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

Verziere

Vim ercate

Lim ito

Osio

RezzatoJ uvaraMagenta

Saronno

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

(m asl)

X U TM (km )

Y U

TM

(km

)

StationYearly

Mean

Winter

Mean

Summer

Mean

Osio 42.79 57.83 28.00

Vimercate 42.31 53.64 29.33

Rezzato 49.11 62.13 33.68

Juvara 50.98 61.92 34.41

Limito 43.19 59.62 29.96

Magenta 49.29 59.54 34.07

Verziere 51.83 62.62 37.07


CDIII base case simulation:Yearly Performance

01020304050607080

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

OBS TCAM

0255075

100125150

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

OBS TCAM

0

0.25

0.5

0.75

1

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

-1-0.75

-0.5-0.25

00.25

0.50.75

1

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

Mean95thPerc

Correlation NBIAS


CDIII base case simulation:Winter Performances

0

20

40

60

80

100

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

OBS TCAM

0255075

100125150175

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

OBS TCAM

0

0.25

0.5

0.75

1

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

-0.75-0.5

-0.250

0.250.5

0.75

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

Mean95thPerc

Correlation NBIAS


CDIII base case simulation:Summer Performances

01020304050

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

OBS TCAM

0

25

50

75

100

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

OBS TCAM

0

0.25

0.5

0.75

1

Osi

o

Vim

erca

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Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

-0.75-0.5

-0.250

0.250.5

0.75

Osi

o

Vim

erca

te

Rez

zato

Juva

ra

Lim

ito

Mag

enta

Ver

zier

e

Mean95thPerc

Correlation NBIAS


CDIII base case simulation:PM10 concentration maps

T O R I N O

M I L A N O

G E N O V A

T R E N T O

V E R O N A

P I A C E N Z A

M O D E N A

B R E S C I A

V A R E S E

B E R G A M O

S O N D R I O

P A R M A

N O V A R A

A L E S S A N D R I A

4 0 0 4 5 0 5 0 0 5 5 0 6 0 0 6 5 0

4 9 0 0

4 9 5 0

5 0 0 0

5 0 5 0

5 1 0 0

5 1 5 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

4 5

5 0

5 5

6 0

6 5

7 0

7 5

8 0

8 5

9 0

Year

Winter

Summer

TORI NO

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

TORI NO

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

T O R I N O

M I L A N O

G E N O V A

T R E N T O

V E R O N A

P I A C E N Z A

M O D E N A

B R E S C I A

V A R E S E

B E R G A M O

S O N D R I O

P A R M A

N O V A R A

A L E S S A N D R I A

4 0 0 4 5 0 5 0 0 5 5 0 6 0 0 6 5 0

4 9 0 0

4 9 5 0

5 0 0 0

5 0 5 0

5 1 0 0

5 1 5 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

4 5

5 0

5 5

6 0

6 5

7 0

7 5

8 0

8 5

9 0


CDIII base case simulation:PM10 yearly chemical composition

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

NW N NE W C E SW S SE

Other

EC+OC

SO4=

NO3-

NH4+

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

NW N

NE

WC

E

SWS

SE

TORI NO

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2200

2400

2600

2800

3000

(m asl)

X UTM (km )

Y U

TM

(km

)


CDIII base case simulation:mainly inorganic fraction maps

TORI NO

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

TORI NO

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

NH4+NO3-


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


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 modulationChemicalcharacterization

Chemical/Sizecharacterization

Gas: CBIV99PM: 2 size bins,

8 chemical species

Gas: COCOH97PM: 6 size bins,

8 chemical species

CESIAMA


Boundary pre-processor (CESI)

• Boundy Module provides hourly base case and scenario boundary conditions

Chimere

Gas: 23 speciesPM: 4 size bins

11 chemical species

BOUNDY

TCAM

Gas: 62 speciesPM: 10 size bins

21 chemical species

PM experimental size profiles


CDIII base case simulation:PM2.5/PM10 concentration map

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

4900

4950

5000

5050

5100

5150

0.4

0.45

0.5

0.55

0.6

0.65

0.7

0.75

0.8

0.85

0.9

PM2.5/PM10Concentration

PM2.5/PM10Emisison

TORI NO

MI LANO

GENOVA

TRENTO

VERONA

PI ACENZA

MODENA

BRESCI A

VARESE

BERGAMO

SONDRI O

PARMA

NOVARA

ALESSANDRI A

400 450 500 550 600 650

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4950

5000

5050

5100

5150

0

0.5

0.75

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DEA - Università degli Studi di Brescia Aerosol long term simulation using TCAM model C. Carnevale,...

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