Download - Bedogni M. , Costa M.P., Casadei S. AMA Mobility and Environment Agency of Milan, Milan, Italy
G. Pirovano – CESIRICERCA, Italy
Comparison and validation of long term simulation of PM10 over 7 European cities in the
frame of Citydelta project
Bedogni M. , Costa M.P., Casadei S.AMA Mobility and Environment Agency of Milan, Milan, Italy
Pirovano G. CESI RICERCA Spa, Milan, Italy
AMA - MI
G. Pirovano – CESIRICERCA, Italy
http://aqm.jrc.it/citydelta/
Phase III
G. Pirovano – CESIRICERCA, Italy
CAMx version 4.21CAMx version 4.21
• Horizontal advection: Bott Scheme• Resistance Based Dry Deposition• Wet Deposition• Photolysis rates adjusted as a function of cloud cover,
total ozone column and turbidity• Gas phase chemistry
– Mechanism: CBIV99 Solver: CMC• Aerosol phase chemistry
– SIA: Isorropia SOA: SOAP algorithm– Coarse/Fine bins No dynamic processes
G. Pirovano – CESIRICERCA, Italy
Introduction...Introduction...Vautard R. et al., Evaluation and intercomparison of Ozone and PM10 simulations
by several chemistry-transport models over 4 european cities within the City-Delta project, Atm. Env., 2006, in press.
City-delta IIICity-delta III• Base year 2004• Only CAMx model• 5+2 cities: Berlin, Lisbon, London, Milan, Paris, (Prague, Krakow)• MM5 meterological fields at 10 km (Milan 5km, Lisbon 2km)• Kv computation following CMAQ approach• EMEP Emission Inventory & local inventories spatial distribution• Biogenic emissions• CHIMERE continental fields as B.C.• No specific tuning for each city
...We may look at this exercise with......We may look at this exercise with...
G. Pirovano – CESIRICERCA, Italy
……a “synoptic” point viewa “synoptic” point view
……in order to discuss a couple of interesting topicsin order to discuss a couple of interesting topics
• Operational evaluation of the modelling system
• PM10 mass and composition
G. Pirovano – CESIRICERCA, Italy
Stations subsetsStations subsets
- 2 . 5 - 2 - 1 . 5 - 1 - 0 . 5 0 0 . 5 1 1 . 5
- 2 . 5 - 2 - 1 . 5 - 1 - 0 . 5 0 0 . 5 1 1 . 5
5 0 . 5
5 1
5 1 . 5
5 2
5 2 . 5
5 3
5 0 . 5
5 1
5 1 . 5
5 2
5 2 . 5
5 3
2 1
2 7
3 03 4 3 7
3 13 2
3 9
2 6
400 450 500 550 600 650
UTM (km )
4900
4950
5000
5050
5100
5150
UT
M (
km)
M ILANO
G ENO VA
TRENTO
BO LO G NA
VERO NA
PIACENZA
M O DENA
BRESCIA
VARESE
BERG AM O
SO ND RIO
PARM A
NO VARA
ALESSANDRIA
b e r l i s l o n m i l p a r
0
0 . 1
0 . 2
0 . 3
0 . 4
0 . 5
0 . 6
0 . 7
0 . 8
0 . 9
1
ber lis lon mil par
0
20
40
60
80
100
[km
]
NOX Emission density
Distance from city centre
G. Pirovano – CESIRICERCA, Italy
Yearly Mean
ber lis lon mil par
0
5
10
15
20
25
30
35
40
[pp
b]
ber lis lon mil par
0
10
20
30
40
50
60
[pp
b]
ber lis lon mil par
0
10
20
30
40
50
60
70
[g
/m3]
NO2 (24h r.a.) O3 (8h daytime r.a. - summer)
PM10 (24h r.a.)
ber lis lon mil par
0
10
20
30
40
50
60
70
[pp
b]
Ox (24h r.a.)
Obs CAMx
G. Pirovano – CESIRICERCA, Italy
BIAS
NO2 O3
PM10
ber lis lon mil par
-50
-40
-30
-20
-10
0
10
20
30
40
50
[]
ber lis lon mil par
-50
-40
-30
-20
-10
0
10
20
30
40
50
[]
ber lis lon mil par
-50
-40
-30
-20
-10
0
10
20
30
40
50
[]
G. Pirovano – CESIRICERCA, Italy
Sigma ratio
NO2 O3
PM10
b e r l i s l o n m i l p a r
0
0 . 2
0 . 4
0 . 6
0 . 8
1
1 . 2
1 . 4
1 . 6
b e r l i s l o n m i l p a r
0
0 . 2
0 . 4
0 . 6
0 . 8
1
1 . 2
1 . 4
1 . 6
ber lis lon mil par
0
0.5
1
1.5
2
2.5
3
3.5
4
G. Pirovano – CESIRICERCA, Italy
Correlation
NO2 O3
PM10
b e r l i s l o n m i l p a r
0
0 . 1
0 . 2
0 . 3
0 . 4
0 . 5
0 . 6
0 . 7
0 . 8
0 . 9
1
b e r l i s l o n m i l p a r
0
0 . 1
0 . 2
0 . 3
0 . 4
0 . 5
0 . 6
0 . 7
0 . 8
0 . 9
1
b e r l i s l o n m i l p a r
0
0 . 1
0 . 2
0 . 3
0 . 4
0 . 5
0 . 6
0 . 7
0 . 8
0 . 9
1
G. Pirovano – CESIRICERCA, Italy
01020304050607080
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[pp
b]
Time series - NO2 daily mean (city average)
0
10
20
30
40
50
60
70
80
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[pp
b]
Milan
Lisbon
0
10
20
30
40
50
60
70
80
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[pp
b]
Paris
Obs
CAMx
G. Pirovano – CESIRICERCA, Italy
0
20
40
60
80
100
120
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[pp
b]
0
20
40
60
80
100
120
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[pp
b]
0
20
40
60
80
100
120
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[pp
b]
Time series - O3 daily max (city average)
Milan
Lisbon
Paris
Obs
CAMx
G. Pirovano – CESIRICERCA, Italy
020406080
100120140160180
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[ug
/m3]
0
20
40
60
80
100
120
140
160
180
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[ug
/m3]
020406080
100120140160180
1/1 1/2 1/3 1/4 1/5 1/6 1/7 1/8 1/9 1/10 1/11 1/12
[ug
/m3]
Time series - PM10 daily mean (city average)
Milan
Lisbon
Paris
Obs CAMx
G. Pirovano – CESIRICERCA, Italy
PM10 - total mass (yearly mean)
SIAPPM10
PM10
ber kra lis lon mil par pra
0
10
20
30
40
50
60
70[
g/m
3]
C ity C entre
U rban A rea
ber kra lis lon mil par pra
0
10
20
30
40
50
60
70
[g
/m3
]
C ity C entre
U rban A rea
ber kra lis lon mil par pra
0
10
20
30
40
50
60
70
[g
/m3]
C ity C entre
U rban A rea
G. Pirovano – CESIRICERCA, Italy
PM10 - relative composition
Urban areas
City centre
ber kra lis lon mil par pra
0
0.2
0.4
0.6
0.8
1
SO A
N H4+
SO 4=
N O 3-
PPM 10
ber kra lis lon mil par pra
0
0.2
0.4
0.6
0.8
1
SO A
N H4+
SO 4=
N O 3-
PPM 10
G. Pirovano – CESIRICERCA, Italy
PM10 - concentrations vs emissions
Primary PM10 (urban area)
vsUrban area Emix density
0
5
10
15
20
25
0 1 2 3 4 5 6 7[ton/km2]
[ug
/m3]
Lis
ParMil
0
2
4
6
8
10
12
14
16
0 1 2 3 4 5 6 7 8 9[ton/km2]
[ug
/m3]
Nitrate (urban area)
vsDomain Emix density (NOX ) Lis
Mil
Lon
NH3/NOX ratio(Domain Emix density)
0
0.1
0.2
0.3
0.4
0.5
0.6
ber lis lon mil par pra
G. Pirovano – CESIRICERCA, Italyppm10 sulf nitr ammo other
0
10
20
30
40
50
60
70
[g
/m3
]
YearJanuary
Critical episodes - January 2004Critical episodes - January 2004
MilanCity centre
ppm10 sulf nitr ammo other
0
5
10
15
20
25
30
[g
/m3
]
YearJanuary
ppm10 sulf nitr ammo other
0
5
10
15
20
25
30
[g
/m3
]
YearJanuary
Urban area
Paris
ppm10 sulf nitr ammo other
0
10
20
30
40
50
60
70[
g/m
3]YearJanuary
G. Pirovano – CESIRICERCA, Italy
• Good reliability of emission inventories
• Heterogeneous measured data set can mask model discrepancies
• Photochemistry is well reproduced (also in Milan) at domain scale
• Local scale effects on NO2/O3 induce BIAS of 5-15%
• Performances for PM10 are less reliable and more heterogeneous:10-20 % of mass is missing and variability is not well described
• Fine scale meteorology has clearly enhanced model performances
• PM10 yearly mean is around 20 [g/m3] (…not in Milan!)
• Milan: combined effect of low ventilation and chemistry on PM10
• Lisbon: ….a particular case…
• Sever episodes: errors may be emphasised (critical for exceedances)
ConclusionsConclusions
G. Pirovano – CESIRICERCA, Italy
• Evaluation of critical episodes (exceedances)
• Having established several datasets, we are planning to:• perform source-apportionment analysis (OSAT & PSAT)• perform systematic sensitivity analysis (PA & DDM)
Next steps...Next steps...
• Following the “spirit” of Citydelta and the
ACCENT network we are surely interested and
willing to join projects based on model
ensemble approach CAMx
G. Pirovano – CESIRICERCA, Italy
The authors would like to thank CONCAWE (London), IIASA (Vienna) and JRC (Ispra) to have funded and promoted the phase III of Citydelta
modelling exercise.
The authors would also like to thank Claudio Carnevale of the University of Brescia for his valuable contribution in the development
of the emission processor, TERRARIA (Milan) to have provided biogenic emissions, and ARPA Lombardia to have performed some simulations .
Mobility and Environment Agency technical contribution has been sustained by the Municipality of Milan.
Thanks to…
G. Pirovano – CESIRICERCA, Italy
Paris StationsParis Stations
0
5
10
15
20
25
30
35
1 2 3 4 5 6 7 8 9 10 11 12
month
[pp
b]
CERGY
GENNEVI
MELUN
PARIS_1
PARIS_18
VITRY_SS
NO2
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12month
[pp
b]
CERGY
GENNEVI
MELUN
PARIS_1
PARIS_18
VITRY_SS
PM10