A modelling system for predicting urban PM 2.5 concentrations. Numerical results and evaluation against the data in Helsinki

e c n e A modelling system for predicting urban r e f n results and PM2.5 concentrations. Numerical o C evaluation againstonthe data in Helsinki n i ...
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e c n

e A modelling system for predicting urban r e f n results and PM2.5 concentrations. Numerical o C evaluation againstonthe data in Helsinki n i t a

e h rc

s i i n k Ari Karppinen, Jaakko Kukkonen, o n e FMI m t Mari Kauhaniemi, Jari Härkönen, r r a a P th H Tarja Koskentalo, h Anu Kousa YTV 9 c s i m r a G

Harmo 9, Ari Karppinen

02/06/2004

1. Aims e c 2. The measurements n e r 3. The modelling system nfe o • Emission modelling C n n o i • Dispersion modelling e t h a c s r i i • Backgroud modelling n k o n m 4. Resultsrand Conclusionsrte a a H concentration P • thspatial distributions h 9 c s measurements • comparison with i m r • problemsa & further work

G

Harmo 9, Ari Karppinen

02/06/2004

Aims

n o ti

n o C

e r fe

e c n n e h

a Development and validation of a c s r i i n k o n modelling system for predicting urban e m t r r a a concentrations PM2.5 H P th

9

r a G

h c s i m

Harmo 9, Ari Karppinen

02/06/2004

Measurements

n o ti

n o C

e r fe

e c n n e h

a (continuous) • YTV –monitoring network c s r i i n k o • EMEP stations (continuous)en m t r r a a • Measurement campaigns H P th

9

r a G

h c s i m

Harmo 9, Ari Karppinen

02/06/2004

PM MONITORING SITES in HELSINKI METROPOLITAN AREA Site

Site type

Töölö

Urban traffic Vallila Urban traffic Leppävaara Suburban traffic

n o m r a

a is

Vehicles /day

e r fe

e c n

Distance Measured from average hourly street quantities 12 000 - 5 m PM10 25 000 14 000 14 m PM2.5 & PM10

n o ti

n o C

c r ki

n e t r a P Kallio 8000 80 m th H Urban background ch 9 s i Luukki Regional 4000 800 m m r background a G 15 000 - 25 m 61 000

n e h

PM10

PM2.5 & PM10

since '99

PM10

Harmo 9, Ari Karppinen

02/06/2004

s i n o m r a

n o i t a

n o C

e r fe

e c n n e h

Geographical information Emission characteristics Measurements Meteorology, traffic, pollution

n e t MM5 ? r a P th H h 9 c Modelling systemsis(FMI) m r a G

c r ki Traffic simulation

Weather Emission inventories prediction, met. VTT, LIISA pre-processing

MacroEMME/2 (YTV)

MicroHUTSIM (TKK)

Corinair

Dispersion of pollutants • stationary sources: UDM-FMI • roadside: CAR-FMI • street canyon: OSPM (NERI) • forecasting air quality: API-FMI

Activity Model Exposure model

HIRLAM, MPPFMI

Statistical Analysis

Harmo 9, Ari Karppinen

GIS MapInfo Visualisation

02/06/2004

Model for urban fine particles

n o C

e r fe

e c n

PM2.5(r,t)= PM2.5tr(r,t) + PM n 2.5st(r,t) + PM2.5nbg(t)

s i n o m r a

o i t a

e t r PM (r,t) a H P h t is the total measured h 9 c concentration at time t, atis spatial coordinate r rm a G 2.5

i k n

e h rc

st : stationary sources tr : vehicular traffic (exh+non-exh) bg: background (LRT)

Harmo 9, Ari Karppinen

02/06/2004

Assumptions:

e r fe

e c n

n o R Exhaust traffic emissions purely PM2.5 C n n o i e R Other traffic related emissions are directly t h a c s r i i n k proportional to exhaust emissions o n e m t r r R Regional and long-rangeatransported a P th H h PM2.5 9 background purely c s i rm proxy for LRT R Ion-sum is aagood G Harmo 9, Ari Karppinen

02/06/2004

Most important model components

n o C

e r fe

e c n

1. Emission model for PM2.5

2. 3.

n n o i ¾ coldstarts taken tinto account e h a c s r i i Roadside dispersion model CAR-FMI n k o n e m t r r Statistical model for regional and long-range a a P th H h transported PM 9 c s i m r a G 2.5

Harmo 9, Ari Karppinen

02/06/2004

Daily averaged PM2.5 line source emissions (kg/d/km) in the Helsinki Metropolitan Area in 2002 Weekday

weekday

th

9

H

n o m r a

a is

m r a 0

G

n o ti

n o C

e r fe

n e t r a P h c is 5

Kilometres

10

3 1 0.5 0.1 0

e c n

c r ki

n e h

to 14.4 to 3 to 1 to 0.5 to 0.1

Harmo 9, Ari Karppinen

02/06/2004

Daily averaged PM2.5 line source emissions (kg/d/km) in the Helsinki Metropolitan Area in 2002 Saturday

th

9

H

n o m r a G

a is

m r a 0

n o ti

n o C

e r fe

n e t r a P h c is 5

Kilometres

10

3 1 0.5 0.1 0

e c n

c r ki

n e h

to 8.3 to 3 to 1 to 0.5 to 0.1

Harmo 9, Ari Karppinen

02/06/2004

Daily averaged PM2.5 line source emissions (kg/d/km) in the Helsinki Metropolitan Area in 2002 Sunday

th

9

H

n o m r a G

a is

m r a 0

n o ti

n o C

e r fe

n e t r a P h c is 5

Kilometres

10

3 1 0.5 0.1 0

e c n

c r ki

n e h

to 7.9 to 3 to 1 to 0.5 to 0.1

Harmo 9, Ari Karppinen

02/06/2004

Daily averaged cold start emissions of PM2.5 (kg/d/km²) in the Helsinki Metropolitan Area in 2002 2000 T > 0°C Weekday

T < 0°C, 41% preheating Weekday

H

th

9

0

n o m r a

5

Kilometres

10

G

a is

4 1 0.5 0.3 0.1 0

to 7.6 to 4 to 1 to 0.5 to 0.3 to 0.1

m r a

n o ti

n o C

e r fe

n e t r a P h c is (4) (38) (30) (54) (95) (62)

0

e c n

c r ki

n e h

Kilometres

4 1 0.5 0.3 0.1 0

Harmo 9, Ari Karppinen

02/06/2004

5

10

to 14.3 to 4 to 1 to 0.5 to 0.3 to 0.1

(15) (55) (69) (58) (45) (41)

Daily averaged cold start emissions of PM2.5 (kg/d/km²) in the Helsinki Metropolitan Area in 2002 2000 T > 0°C Saturday

T < 0°C, 41% preheating Saturday

H

th

9

0

n o m r a

5

Kilometres

10

G

a is

m r a 1 0.5 0.3 0.1 0

n o ti

n o C

e r fe

n e t r a P h c is

to 2.3 (14) to 1 (23) to 0.5 (17) to 0.3 (112) to 0.1 (117)

0

e c n

c r ki

5

n e h

10

Kilometres

Harmo 9, Ari Karppinen

4 1 0.5 0.3 0.1 0

to 4.7 (2) to 4 (33) to 1 (31) to 0.5 (48) to 0.3 (106) to 0.1 (63)

02/06/2004

Daily averaged cold start emissions of PM2.5 (kg/d/km²) in the Helsinki Metropolitan Area in 2002 2000 T > 0°C Sunday

e r fe

T < 0°C, 41% preheating Sunday

H

th

9

0

n o m r a

5

Kilometres

G

10

a is

m r a 1 0.5 0.3 0.1 0

n o ti

n o C

n e t r a P h c is

to 1.9 (7) to 1 (24) to 0.5 (17) to 0.3 (111) to 0.1 (124)

0

e c n

c r ki

n e h

Kilometres

1 0.5 0.3 0.1 0

Harmo 9, Ari Karppinen

02/06/2004

5

10

to 3.9 (30) to 1 (26) to 0.5 (55) to 0.3 (104) to 0.1 (68)

Annual average PM 2.5 concentrations (µg/m³) in the Helsinki Metropolitan Area in 2002 Solely exhaust emissions from local traffic

H

th

9

0

n o m r a

5

Kilometres

10

G

e c n

All emissions from local traffic

a is

m r a >1 0.5 to 1 0.1 to 0.5 < 0.1

n o ti

n o C

e r fe

n e t r a P h c is 0

c r ki

5

n e h

10

Kilometres

Harmo 9, Ari Karppinen

>5 1 to 5 0.5 to 1 0.1 to 0.5 < 0.1

02/06/2004

Annual average PM 2.5 concentrations (µg/m³) in the Helsinki Metropolitan Area in 2002 All local emissions and regional background

th

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H

n o m r a G

a is

m r a 0

n o ti

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n e t r a P h c is 5

Kilometres

10

> 9 8 7
25 10 to 25 5 to 10 1 to 5 50 25 to 50 10 to 25 5 to 10 1 to 5 100 80 to 100 60 to 80 40 to 60 < 40

Harmo 9, Ari Karppinen

02/06/2004

Predicted vs. observed e c daily mean PM2.5 concentrations n e r in Helsinki in 2002 fe • Computations by mainframe version of CAR-FMI line source model •

a is

n o ti

n o C

n o n e m t Observations from YTV r r a a monitoring P th Hstations at h Vallila 9 and Kallio c s i m r a G

c r ki

n e h

YTV, 2003

Harmo 9, Ari Karppinen

02/06/2004

Location of YTV monitoring stations

th

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H

n o m r a

a is

m r a

Kallio station

G

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n e t r a P h c is

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Vallila station

200 m

N

YTV, 2002

Harmo 9, Ari Karppinen

02/06/2004

55 50 45 40 35 30 25 20 15 10 5 0

VALLILA R2 = 1

th

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H

n o m r a

a is

n o ti

0 5 10 15 20 25 30 35 40 45 50 55 predicted

G

55 50 45 40 35 30 25 20 15 10 5 0

n e r fe

KALLIO

n o C

n e t r a P h c is

y = 0.97x - 0.75 R2 = 0.57

m r a

observed

observed

Predicted vs. observed daily mean PM2.5 concentrations –scatter plot c&eIA

VALLILA: R2 = 0.57, IA = 0.84

c r ki

R2 = 1

n e h y = 0.95x + 1.02 R2 = 0.60

0 5 10 15 20 25 30 35 40 45 50 55 predicted

KALLIO: R2 = 0.60, IA = 0.86 Harmo 9, Ari Karppinen

02/06/2004

Predicted vs. observed daily mean PM2.5 concentration in Vallila – scatter plot in terms of wind direction 55

VALLILA

y = 1.07x - 0.69 R 2 = 0.63

50 45

2

R =1

40

downwind

observed

35 30

a is

n o ti

n o C

e r fe

% of wind direction (deg)

20 15 10

th

5 0 0

9

5

H

n o m r a

N 25

NW

20

n e h

NE

15 10

upwind

25

e c n

W

c r ki

5 0

E

n e t r a P h c downwind < 180 deg is

y = 0.94x - 1.19 R 2 = 0.57

SW

SE

Pasila 2002

S

10 15 20 25 30 35 40 45 50 55 predicted

downwind side Linear (downwind side)

G

m r a

upwind side Linear (upwind side)

upwind > 180 deg

Harmo 9, Ari Karppinen

02/06/2004

VALLILA

55 50 45 40 35 30 25 20 15 10 5 0

55 50 45 40 35 30 25 20 15 10 5 0

n o m r a VALLILA

9

G

m r a

7 8 Summer (June, July, August)

n e r fe

VALLILA

55 50 45 40 35 30 25 20 15 10 5 0

n o C

n e t r a P h c is

2 12 Winter (January, February, December) predicted H h t observed

6

n o ti

3

3

3

PM 2.5 (µg/m )

1

a is

3

observed

PM 2.5 (µg/m )

predicted

PM 2.5 (µg/m )

3

PM 2.5 (µg/m )

Predicted and observed daily mean PM2.5 concentrations in Vallila –seasonal variation ce

55 50 45 40 35 30 25 20 15 10 5 0

9

c r ki

predicted observed

n e h

4 5 Spring (March, April, May)

VALLILA predicted observed

10 11 Harmo 9, Ari Karppinen Autumn (September, October,02/06/2004 November)

KALLIO

55 50 45 40 35 30 25 20 15 10 5 0

3

observed

1

KALLIO

9

G 6

n o C

n e t r a P h c is

2 12 Winter (January, February, December)

H thpredicted observed

55 50 45 40 35 30 25 20 15 10 5 0

n o m r a

a is

m r a

7 8 Summer (June, July, August)

n e r fe

KALLIO

55 50 45 40 35 30 25 20 15 10 5 0

n o ti

3

3

3

PM 2.5 (µg/m )

PM 2.5 (µg/m )

predicted

PM 2.5 (µg/m )

3

PM 2.5 (µg/m )

Predicted and observed daily mean PM2.5 concentrations in Kallio –seasonal variation ce

55 50 45 40 35 30 25 20 15 10 5 0

9

c r ki

predicted

observed

n e h

4 5 Spring (March, April, May)

KALLIO predicted observed

10 11 Harmo 9, Ari Karppinen Autumn (September, O ctober, 02/06/2004 November)

Conclusions

‰

e c Modelling system has been developed for urban PM n e r ¾ Applicable also for other European cities (emission coefficients e f country-specific) n o ¾ Includes also the evaluation of regional background PM C n n o Spatial concentration distributions of PM i e t h a c ¾ The influence of traffic and LRT on total concentrations s r i i n k ¾ The annual average, maximum hourly andnguideline o e m concentrations t r r a a Evaluation of the model performance against the P th H h network results 9 of the urban monitoring c s i ¾ Good statistical agreement of the predicted and measured m r daily concentrations a G 2.5

2.5

‰

‰

2.5

Harmo 9, Ari Karppinen

02/06/2004

Challenges for future research e

c n

e r • PM emission modelling – especially none f n combustion and cold start o emissions, and C OSCAR) suspension (studied in SAPPHIRE, n n o i e • The contribution a oft LRT is importanth– Direct •

c s r i would kbei welcome; regional PM2.5 measurements n o continentalrm scale PM modelling ten r a a Modelling of the aerosol processes, including H P h t h size chemical composition 9 distributions iand c s (studied in SAPPHIRE) m r a G Harmo 9, Ari Karppinen

02/06/2004

References

e c Tiitta, P., Raunemaa, T., Tissari, J., Yli-Tuomi, T., Leskinen, A., n Kukkonen, J., Härkönen, J. and Karppinen, A., 2002. Measurements e r Major Road in Kuopio, and Modelling of PM Concentrations Near fae n4057-4068. Finland. Atmospheric Environment 36, pp. o C Pohjola, M.A., Kousa, A., Kukkonen, n J., Härkönen, J., Karppinen, A., n o i e Aarnio, P., Koskentalo, T., 2002. The Spatial and Temporal Variation t h a incthe Helsinki of Measured Urban PMisand PM concentrations r i Air and Soil n k Metropolitan Area. International Journal on Water, o n Pollution: Focus 2 (5-6), pp. 189-201. e m t r r a a HHärkönen, J., Kukkonen,-PJ., Aarnio, P. and Koskentalo, Karppinen, th A., h the portion of fine particulate T.,9 2004. Statistical model for assessing c s and long-range to urban air. matter transported regionally i Scandinavian Journalrofm Work, Environment & Health 24 (s3). a G 2.5

10

2.5

Harmo 9, Ari Karppinen

02/06/2004

This is the end … e c n e r e f CREDITS n o C n n o i e h Academy of Finlandat c s r i i FMI Dispersionon Modelling Groupnk e m t r r a YTV Environmental Office a P th H h 9 c s i m r a G Harmo 9, Ari Karppinen

02/06/2004

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