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
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
> 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
9
H
n o m r a
a is
m r a
Kallio station
G
n o ti
n o C
e r fe
n e t r a P h c is
e c n
c r ki
n e h
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
9
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
