pm10 modeling for the city of klagenfurt, austria · klagenfurt, austria dietmar Öttl christian...

Ein EU-LIFE Projekt Klagenfurt Graz Bozen

PM10 modeling for the city ofKlagenfurt, Austria

Dietmar ÖttlChristian KurzWolfgang Hafner1

Peter Sturm

Graz University of Technology1Department of Environment Protection Klagenfurt


Model Model aproachaproach

NEMO (Network Emission Model, Rexeis et al. 2005)enables detailed calculation of traffic emissions fordifferent vehicle categories for large road networks.

GRAMM (Graz Mesoscale Model, Oettl 2000)prognostic non-hydrostatic.terrain following grid (tetrahedronal, Almbauer 1995).

GRAL (Graz Lagrangian Model, Oettl et al. 2000, 2002,2003a,b,c)all wind speed (>70% u<1.5m/s), stability conditionstopographyline-sources, point-sources, tunnel portals, areasources.


Non-exhaustNon-exhaust PM10 PM10 emissionemission factorsfactors

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Jan Feb Mär Apr Mai Jun Jul Aug Sep Okt Nov Dez

EF

[g

/km

/ve

h]

Völkerm. TSP 2003

Völkerm. TSP 2004

St. Veiter Str. 2005

Völkerm. PM10 2004


Total PM10 Total PM10 emissionemission factorsfactors

0

0.05

0.1

0.15

0.2

0.25

0.3

Gehrig et al.

2003

Omstedt et

al. 2005

Ketzel et al.

2005

This study

Total PM10 EF

[g/km/veh]

Share of dieselPC in A: >50%


Emission inventory fordomestic heating for 2001[kg/a/ha]

Emission Emission inventoryinventory forfor Klagenfurt Klagenfurt


Wind Wind fieldfield simulationssimulations


AQ AQ simulationssimulations withwith GRAL GRAL

• Public transport not included yet.

• Relatively high uncertainty regarind non-exhaust PM10EF.

• Evaluation using NOx has still to be done.

• Winter services are not considered yet.


AQ AQ simulationssimulations withwith GRAL GRALTraffic-exhaustTraffic-non-exhaustDomestic heatingTradeAgriculturing


AQ AQ simulationssimulations withwith GRAL GRALTotal PM10 annualmean [µg/m³]


ComparisonComparison withwith observedobserved annualannual meanmean PM10 PM10

y = 1.07x + 20.88

R2 = 0.87

0

5

10

15

20

25

30

35

40

0 5 10 15 20

GRAL (without background) [µg/m³]

obse

rved

[µ

g/m

³]


Total PM10 annualmean [µg/m³]

Background

43.1%

Traffic

11.8%

Non-Exhaust

30.0%

Agriculture

1.0%

Domestic heating

8.8%

Trade

5.3%

Südring

annual mean PM10

Background

52.8%Non-Exhaust

19.8%

Agriculture

0.3%

Domestic heating11.8%

Trade

6.4%

Exhaust

8.9%

Völkermarkterstraße

annual mean PM10

Background

67.8%

Traffic

4.2%

Non-Exhaust

10.7%

Agriculture

0.2%

Domestic heating

10.4%

Trade

6.5%

Koschatstraße

annual mean PM10

AQ AQ simulationssimulations withwith GRAL GRAL

Background

81.5%

Traffic

2.5%

Non-Exhaust

4.9%

Agriculture

5.6%

Trade

1.7%

Domestic heating

3.8%

Hörtendorf

annual mean PM10


Brief Brief summarysummary

Direct traffic contribution PM10urban background - kerbside 15%-45%

Regional backgroundkerbside >50%urban background >70%

More research necessary toget a better understandingof the formation of highregional background


NowcastingNowcasting System Klagenfurt System Klagenfurt

GRAL

Data bank:

Stored 2-D concentrationfields for different sourcesand dispersion conditions

(about 1000/source)

Sonic anemometer

Online-traffic data

Hourly surface concentrations

Online background PM10


OutlookOutlookSimulated mean wind speeds for thecity of Graz


Chem. AnalysenChem. Analysen

TU-WienTU-Wien, Puxbaum et al., 2004., Puxbaum et al., 2004.

Messstelle AKH-Wien (städt. Hintergrund)

direkter Verkehrsbeitrag: 19%Auspuff: 8%

Ruß: 5%org. Material: 3%

Reifenabrieb: 1%org. Material: 1%

Aufwirbelung: 10%Mineralien: 7%Ca, Mg: 3%


ChemicalChemical analysisanalysis in in ViennaVienna (Puxbaum et al., 2005)(Puxbaum et al., 2005)

-2

0

2

4

6

8

10

12

14

Jun-

99

Jul-9

9

Aug-9

9

Sep-9

9

Oct

-99

Nov

-99

Dec

-99

Jan-

00

Feb-0

0

Mar

-00

Apr-0

0

May

-00

µg

m-3

UNID

Fe

Carbonates

Minor Ions

OC


WindfeldsimulationenWindfeldsimulationen

0

0.5

1

1.5

2

2.5

3

3.5

4N

NNE

NE

ENE

E

ESE

SE

SSE

S

SSW

SW

WSW

W

WNW

NW

NNW

0

2

4

6

8

10

12N

NNE

NE

ENE

E

ESE

SE

SSE

S

SSW

SW

WSW

W

WNW

NW

NNW

0

0.5

1

1.5

2

2.5

3

3.5

4N

NNE

NE

ENE

E

ESE

SE

SSE

S

SSW

SW

WSW

W

WNW

NW

NNW

0

2

4

6

8

10N

NNE

NE

ENE

E

ESE

SE

SSE

S

SSW

SW

WSW

W

WNW

NW

NNW

0

5

10

15

20N

NNE

NE

ENE

E

ESE

SE

SSE

S

SSW

SW

WSW

W

WNW

NW

NNW


ObservedObserved annualannual meanmean PM10 PM10 concentrationsconcentrations

0

10

20

30

40

50

60

Salzburg Klagenfurt Graz

Annual m

ean P

M10 [

µg/m

³]

Local traffic

Urban background

Rural background

Regional background

GW


ObservedObserved annualannual meanmean PM10 PM10 concentrationsconcentrations

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Salzburg Klagenfurt Graz

Local traffic

Urban background

Rural background

Regional background


WeekdayWeekday//weekendweekend analysisanalysis

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Mon

day

Tuesd

ay

Wed

nesd

ay

Thurs

day

Friday

Satur

day

Sunda

y

Rela

tive c

oncentr

ation

PM10

NO

Werk

Son

Werk

Son

E

E

C

C

s

−

−

=

1

1


WeekdayWeekday//weekendweekend analysisanalysis

Direct traffic contributions PM10 NOxVölkermarkterstreet 25-40% 75%Koschatstreet 20-30% 55%

Decreasing concentrations onsundays not only due to less traffic,but also due to less economicactivities


Situation in Situation in summersummer


Situation in Situation in winterwinter

8 days > 50µg/m³ as daily mean PM10 at urban background AQM75 days > 50µg/m³ as daily mean PM10 at kerb site AQM


Wind Wind fieldfield simulationssimulations

Prognostic non-hydrostatic wind field model GRAMM (GrazMesoscale Model):

400 m horizontal resolution, 15 vertical levels (10m lowest cellheight)Terrain following grid (tetrahedronal grid)Steady-state wind fields for classified meteorological situationsderived from a single point observation in the domain

Numerical instabilities in the region of the mountain PredigtstuhlChanged from explicit to implicit time integration

Constant surface cooling in stable conditions (20W/m²)Spatial variable surface heat flux in convective conditions(shadowing effects of topography)

pm10 modeling for the city of klagenfurt, austria · klagenfurt, austria dietmar Öttl christian...

Documents