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ACCENT/GLOREAM W orkshop Paris, France, 11-13 O ctober 2006 19th w orkshop on tropospheric chem ical transportmodelling Long term simulations with Chimere over Northern Italy . Marco Deserti , Enrico Minguzzi, Michele Stortini, Giovanni Bonafè, Suzanne Jongen ARPA-SIM, Area Meteorologia Ambientale

Long term simulations with Chimere over Northern Italy

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Long term simulations with Chimere over Northern Italy . Marco Deserti , Enrico Minguzzi, Michele Stortini, Giovanni Bonafè, Suzanne Jongen ARPA-SIM, Area Meteorologia Ambientale. Background, problems to be solved Model set up (NINFA) 1 year hindcast, model verification - PowerPoint PPT Presentation

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Page 1: Long term simulations with Chimere over Northern Italy

ACCENT/GLOREAM Workshop

Paris, France, 11-13 October 2006

19th workshop on tropospheric chemical transport modelling

Long term simulations with Chimere over

Northern Italy.

Marco Deserti, Enrico Minguzzi, Michele Stortini, Giovanni Bonafè, Suzanne Jongen

ARPA-SIM, Area Meteorologia Ambientale

Page 2: Long term simulations with Chimere over Northern Italy

Contents

• Background, problems to be solved• Model set up (NINFA)• 1 year hindcast,

– model verification – air quality assessment

• Scenario analysis (CLE 2020, zero EMR)• Conclusions and perspectives

Page 3: Long term simulations with Chimere over Northern Italy

Background

number of exceeedances, Emilia Romagna cities

PM10

O3

Po valley-Northern Italy do not comply the AQ limit values.

• 2002: the Regional Government of Emilia-Romagna, the Provincial Authorities and the main Municipalities subscribed the Regional Agreement on Air Quality, focused on PM10 pollution management and aiming to reach the target values. The agreement is still valid. ARPA start to forecast air pollution to assist local authorities to decide if stop traffic before the pollution episodes.

• 2003: the Emilia Romagna Regional government entrust ARPA with a task to develop a model system to assess and forecast air pollution.

• 2005: the NINFA system start to be operational

• 2006: the European Council invite the Repubblica Italiana to take measures to ensure that a plan or programme is prepared for attaining the limit value

• 2005-2006 the government of Emilia Romagna, Friuli Venezia Giulia, Lombardia, Piemonte, Veneto, Provincia Autonoma di Trento sign the Northern Italy agreement to prevent and reduce the air pollution. A technical task force on air quality modelling is established.

Page 4: Long term simulations with Chimere over Northern Italy

NINFA modelling system (1) Northern Italian Network to Forecast photochemical and Aerosol pollution

Orography height (m)

• CTM: Chimere (dust & sea salt included)

• 10 km horizontal resolution, 8 vertical levels up to 500 hPa

• Meteorological input : LAMI (7 km horizontal resolution)

• Emissions: adapted from Corinair 2000 Italy + EMEP

• Boundary conditions: Prev’air (0.5°*0.5°)

Page 5: Long term simulations with Chimere over Northern Italy

NINFA modelling system (2)

The Chimere CTM has been adapted to Northern Italy:

• interface with LM meteorological fields

• modification of MH and Kz evaluation

• more urban corrections to meteorological input

• evaluation of plume rise for point sources

NOx gridded emissions, year 2000 annual total

The NINFA system is used for:

- operational air-quality forecasts (started in October 2005, available at www.arpa.emr.it/sim)

- Long-term simulations for air-quality assessment and scenario evaluation

- Base case: 1-year hindcast simulation (apr 2003 – mar 2004), Meteorological input form LAMI re-analysis

Page 6: Long term simulations with Chimere over Northern Italy

Model results: base case Ozone

O3, summer: average day-time concentration (left), number of days with 8-hours mean >120 μg/m3 (right)Max number of exceeedances 25 per year

• The threshold for health protection is frequently exceeded

• The situation is worst in rural areas in Northern Po Valley

High values in Ligurian sea are due to BC (no measurements available!!)

Page 7: Long term simulations with Chimere over Northern Italy

Model results: base case PM10

PM10: summer average (left), winter average (right)

• PM10 reaches its highest value during the winter in the plain area, extending from the west sub alpine region to the North-East Adriatic coast.

• higher values are located in and around the main urban agglomerates (Milano and Torino),

the smaller urban areas are not described (too coarse !), the exceedances of the threshold in urban areas are not reproduced (underestimation!)

Page 8: Long term simulations with Chimere over Northern Italy

Model validation

Fonte: APAT- CTN-ACE 2004

polluttant av. time period

% of models data which comply data-quality

objectives for Modelling (RB and SB stations with 90

% of valid data)

% of station which compy Data-quality

objectives for continuous

measurement

O3 1 h day/year 100% 73%O3 8 h day/year 91% 73%

PM10 1 year 24 h/year 75% 67%

EC Directives:1999/30/EC,2000/69/EC, 2002/3/EC

Page 9: Long term simulations with Chimere over Northern Italy

Model verification statistics

0

20

40

60

80

100

120

140

160

BUTTIGLI

ERADASTI

CASON

MO

NTECUCCOLI

NO

ACQUIT

ERME

ALBA

BORG

ARO

COLI

CO

COSSATO

S.LAZZARO

SALICETO

V.VID

OLE

TTI

N.

supe

ram

enti

VL

0,8

0,82

0,84

0,86

0,88

0,9

0,92

0,94

0,96

0,98

1

Coe

ffice

nte

corr

elaz

ione

NINFA OSS R

OZONE

0

10

20

30

40

50

60P

M10 m

edia

annuale

( g/m

3)

00,1

0,20,3

0,40,50,6

0,70,8

0,91

coeffic

ente

di corr

ela

zio

ne

media sim media oss R

PM10

O3

g/m3

Bias RMSE Corr.

coeff.

RB (N=3)

-10 / -3 24 / 30 0.80

SB

(N=8)

2 / 14* 25 / 32* 0.74

* Colico station excluded

PM10

g/m3

Bias RMSE Corr.

coeff.

RB (N=3)

-20 / -5 11 - 26 0.57

SB

(N=6)

-29 / -11 15 - 36 0.63

Page 10: Long term simulations with Chimere over Northern Italy

Model verification

• daytime ozone concentrations (1-hour and maximum daily 8-hour mean) agree very well with the observed ones, with correlation coefficients higher than 0.7 and low bias

• PM10 annual mean levels are underestimated (the bias is approximately -20 μg/m3), although correlation coefficients for the daily mean are around 0.6

PM10, year 2003-2004

0,00

10,00

20,00

30,00

40,00

50,00

RB (N=2) SB (N=6) UB (N=8) UT (N=4)

mg/

m3

sim oss

O3, summer2003

0

20

40

60

80

100

RB (N=3) SB (N=8) UB (N=16) UT (N02)

g/m

3

sim oss

Page 11: Long term simulations with Chimere over Northern Italy

O z o n o - G io rn o tip ico d a l 01 /06 /1995 a l 31 /08 /1995

0

20

40

60

80

100

120

140

160

1 3 5 7 9 11 13 15 17 19 21 23

O R E

g/m 3

città

m ontagna

co llina

rura lip ianura

F igura 1: confronto tra i giorni tip ici estivi d i quattro d iversi siti d i m isura durante il periodoestivo 1995.

NINFAmodel

April – Sept 2003

The daily cycle is well reproduced by NINFA:

Plane: high peak values during the day, minimum during the night,

Mountain: little diurnal cycle…

Observed: MOTAP

Model verification: Ozone mean day in the plane, in the hills and in the mountain

Page 12: Long term simulations with Chimere over Northern Italy

Granulometric distribution of PM, Summer (left) and winter (right) months

Milan and Bologna are urban, SPCapofiume rural in Po valley, Febbio rural in Appenines.

D (micron)D (micron)

g/m

3Base case: PM size distribution

Page 13: Long term simulations with Chimere over Northern Italy

normalized annual mean

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0,45

0,50

0.01-0.6 0.6-2.5 2.5-10

D (micron)

mic

rog

/m3

NINFA POLVERE

NINFA

0

2

4

6

0.01-0.04 0.04-0.15 0.15-0.6 0.6-2.5 2.5-10 10 -40

D (micron)

micro

gramm

i/m3

PolveRE

0,00

0,10

0,20

0,30

0,40

0,50

0-0.49 0.49-0.95 0.95-1.5 1.5-3 3-7.2 7.2-10

D (micron)

micr

ogra

mm

i/m3

Bologna (annual mean)

Model verification: PM size distribution

model

observed

Page 14: Long term simulations with Chimere over Northern Italy

Model verification: PM10 speciation

Bologna, annual mean*Caution 2003 vs 2003-2004 !

* Data from CNR-ISAC (S.Fuzzi, C. Facchini)

Page 15: Long term simulations with Chimere over Northern Italy

PM10 speciation and PM size distribution in Bologna

There is a lack of experimental data, a very rough comparison indicate that:

• organic seems to be strongly underestimated

• Inorganic is underestimated

• Dust agreement• Salt: sea salt can be

neglect in Bologna, other sources..?

• Similar results for continental (Prev’air 50 km) and regional (NINFA 10 km) simulations

• There is a general, although rough, agreement between observed and simulated size distribution

PM size distribution normalized annual mean

0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

0,40

0,45

0,50

0.01-0.6 0.6-2.5 2.5-10

D (micron)

mic

rog

/m3

NINFA POLVERE

PM speciation, Bologna

0,00

2,00

4,00

6,00

8,00

10,00

NO3 -hno3

NH4 -nh3

nssSO4- hso4

OM -soa

min.dust

sea salt unacc. -ppm

g/

m3

Putard 2003 Long4 Prev'air

Page 16: Long term simulations with Chimere over Northern Italy

385

258

314

238

132 147

0

50

100

150

200250

300

350

400

450

COV COV

Lombardia Emilia-Romagna

kTo

n/a

rea/

ann

o CityDelta97

CityDelta CLE2000

INEMAR 2001

CTN 2000

ER 2000

232208

225

183

104

132

0

50

100

150

200

250

NOx NOx

Lombardia Emilia-Romagna

kT

on

/are

a/a

nn

o CityDelta97

CityDelta CLE2000

INEMAR 2001

CTN 2000

ER 2000

22

36

24 23

14 12

05

10152025303540

PM10 PM10

Lombardia Emilia-Romagna

kTo

n/a

rea/

ann

o CityDelta97

CityDelta CLE2000

INEMAR 2001

CTN 2000

ER 2000

EMISSIONS:

Annual total from different data sources over Lombardia and

Emilia Romagna regions

CityDelta: http://aqm.jrc.it/citydelta/

CTN 2000: http://www.sinanet.apat.it

LombardiaNOx COV PM10(kt/anno) (kt/anno) (kt/anno)

CityDelta97 232 385 22CTN 2000 183 238 23

difference % 27 62 -4

CityDelta CLE2000 208 258 36CTN 2000 183 238 23

difference % 14 8 57

INEMAR 2001 225 314 24CTN 2000 183 238 23

difference % 23 32 4

Emilia RomagnaNOx COV PM10(kt/anno) (kt/anno) (kt/anno)

ER 2000 132 147 12CTN 2000 104 132 14

difference % 27 11 -14

ER 2003 129 142 11CTN 2000 104 132 14

difference % 24 8 -21

Page 17: Long term simulations with Chimere over Northern Italy

Air quality assessment in Northern Italy

• NINFA has been run over 1 year period in the hindcast mode to simulate ozone and PM10 concentration.

• The hindcast run is helpful to estimate the size of the polluted area and to analyze the spatial patterns of the atmospheric pollution in Northern Italy

• The spatial structure of the simulated fields reproduces the mountain-plain concentration gradients of pollutants.

• spatial patterns are linked to wind regimes, characterized by frequently stagnation of air masses in the Po Valley and to the emissions distribution,

• Ozone: large amount of exceedances of the target value for the protection of human health (120 μg/m3 maximum daily 8-hour mean) are in the sub alpine region and in the plane. Most exceedances (up to 120 per year) are located downwind of the main urban agglomerates (Milano and Torino).

• PM10: annual average reaches its highest value in the plain area, extending from the west sub alpine region to the North-East Adriatic coast. The highest values are located in and around the main urban agglomerates (Milano and Torino).

Page 18: Long term simulations with Chimere over Northern Italy

Scenario analysis

Preliminary results, the scenarios considered are:

• CLE 2020”: emission reductions of 50-60%, based on EU legislation for year 2020, have been applied on all the domain of integration.

• “Emilia-Romagna Zero”: to assess the maximum possible effectiveness of emission reduction policies at local scale, all emissions in Emilia Romagna region (about 20% of Po Valley surface, 15% of emissions) have been switched off.

Page 19: Long term simulations with Chimere over Northern Italy

PM10 emission, 1 year total: base case (left) and current legislation scenario “CLE2020 (*)” (right)

Emissions scenarios

EMISSIONS CHANGE %CO VOC NH3 NOx PM10 SO2

CLE2020 18% 46% 7% 51% 47% 63%ZERO-EMR 12% 13% 17% 13% 12% 13%

(*) CLE 2020 from EMEP

Page 20: Long term simulations with Chimere over Northern Italy

Ozone: number of days with 8-hours mean >120 μg/m3 (60 ppb) (right), base case (left) and CLE (right)Max number of exceeedances 25 per year

•Total NOx emissions decrease about 60% and VOC decrease about 50% over the full area

• ozone summer daily mean decrease about 5%

• the number of exceedances of the 120 g/m3 limit decrease about 15%

The ozone ozone limit values will not be complied !

CLE 2020, Ozone

Page 21: Long term simulations with Chimere over Northern Italy

PM10 annual average, base case (left) and scenario CLE (right)

• Total NOx and PM10 emissions decrease about 60% over the full area

• PM10 annual mean decrease about 20% in rural areas, up to 30% in urban areasCaution: due to the PM10 underestimation only the relative variations can be considered

CLE 2020, PM10

Page 22: Long term simulations with Chimere over Northern Italy

Ozone: number of days with 8-hours mean >120 μg/m3 (60 ppb) (right), base case (left) and EMRZero (right)Max number of exceeedances 25 per year

• Zero emissions over Emilia Romagna, total emissions (VOC, NOx,) decrease about 13% over the full area

• ozone summer daily mean not change

• the number of exceedances of the 120 g/m3 limit decrease about 15% in the Bologna area

The effectiveness of local actions is very poor for ozone!

Emilia Romagna Zero, Ozone

Page 23: Long term simulations with Chimere over Northern Italy

PM10 annual average, base case (left) and scenario EMRZero (right)

• Zero Emissions over Emilia Romagna, total emissions (VOC, NOx, SOx, PM10) decrease about 13%, NH3 decrease about 17%, over the full area

•PM10 annual mean is substantially reduced (decrease 30-40% far from the boundaries)

Local actions could be effective to reduce PM10 concentration!

Emilia Romagna Zero, PM10

Page 24: Long term simulations with Chimere over Northern Italy

Conclusions

• The NINFA system is operational since October 1995, forecast and hindcast are daily available on the WEB (www.arpa.emr.it/sim )

• NINFA has been applied to assess Ozone and PM10 air pollution in Northern Italy (Base case 2003-2004)

• The comparison with experimental data show that NINFA works well for ozone while PM10 is underestimated, even if correlation with observed data is rather good. Main processes and dynamics are reproduced. PM10 should be improved.

• Two additional 12 months simulations have been performed:• “CLE 2020” and “Emilia_Romagna Zero” to assess the maximum

possible effectiveness of emission reduction policies at local scale,• Actions to improve the system are ongoing:

– a finer resolution (5 km) Emilia-Romagna version will be nested inside the Northern Italy coarse model (10 km),

– the emission inventory will be upgraded, increase of PM10 emissions estimation are expected,

– new experimental data will be collected and used for model verification and improvement.

Page 25: Long term simulations with Chimere over Northern Italy

Riserve

Page 26: Long term simulations with Chimere over Northern Italy

Speciation of PM10, Milan, Summer (left) and winter (right) months

Risultati: PM10, caso base

Page 27: Long term simulations with Chimere over Northern Italy

Risultati: PM10, caso base

Granulometric distribution of PM10, Milan, Summer (left) and winter (right) months

Bla

Page 28: Long term simulations with Chimere over Northern Italy

Mixing height

Average mixing height during winter months, estimated by Chimere pre-procesor. Default configuration (left) and setup adapted to Northern Italy (right)

Page 29: Long term simulations with Chimere over Northern Italy

Note

- Modifications to Hmix: disabled enhancement below clouds, modified nocturnal scheme (now Mahrt 2002, function of U* only), increased minimum value in urban cells, introduced a maximum value of 2500 m

- Plume rise scheme: taken from CAMx model (Turner 1986, modified )