Refinement and evaluation of the suspension emission model Mari Kauhaniemi Research Scientist Finnish meteorological Institute, Air Quality, Dispersion modelling NORTRIP meeting (Arlanda) 16.11.2010
Refinement and evaluation of the suspension emission model
Mari KauhaniemiResearch ScientistFinnish meteorological Institute, Air Quality, Dispersion modelling
NORTRIP meeting (Arlanda)16.11.2010
Background• Based on the PM emission model developed by
Omstedt et al. (2005).
• Aim is to use it also in forecasting slightly modified.
• Paper in progress: • Refinement and evaluation of a road dust suspension model for
predicting the concentrations of PM10 in street canyon in Helsinki.
• Kauhaniemi, Kukkonen, Härkönen, Nikmo, Kangas, Omstedt, Ketzel, Kousa, Haakana, and Karppinen
• No measured suspension emissions available
• Evaluated against observed PM10 concentrations
• PM10 concentration computed by a street canyon model (OSPM)
• Study period: 8.1.-2.5.2004
• Study site: Runeberg Street
KaisaniemiRuneberg Street
Urban background measurement station
Meteorological stationAir quality measurement station
Wind mast
Measurement sites
Sensitivity analysis
Influence of precipitation studied with: Influence of precipitation studied with: •Kaisaniemi precipitation data (0-3.8 mm/h)•No precipitation•Maximum precipitation of Kaisaniemi data (3.8 mm/h)
13
.1
1.2
3.2
5.2
15
.21
6.2
17
.22
0.2
21
.22
5.2
26
.22
7.2
1.3
2.3 9.3
12
.31
4.3
15
.3
23
.32
4.3
25
.32
6.3
27
.31
.42
.43
.4
0
100
200
300
400
500
600
700
800
900
1000
1.1 6.1 11.1 16.1 21.1 26.1 31.1 5.2 11.2 16.2 21.2 26.2 2.3 7.3 12.3 17.3 23.3 28.3 2.4 7.4 12.4 17.4 22.4 27.4
Su
sp
en
sio
n e
mis
sio
n facto
r (µ
g/v
eh
/m)
Date
SF (precipitation accounted)SF (no precipitation)SF (max precipitation)20 sanding says11 sanding days26 anding says
• SF (Kaisaniemi data) is occasionally higher than SF (no precipitation) max 48%.
Sensitivity analysis
Influence of sanding studied with: Influence of sanding studied with: •20 sanding days•11 sanding days
If Kaisaniemi precipitation data or no precipitation is used:• SF (20 sanding days) max about 15 % higher than SF (11 sanding days)If maximum precipitation data is used:• SF calculated with 20 or 11 sanding days have no difference.
13
.1
1.2
3.2
5.2
15
.21
7.2
20
.22
1.2
25
.22
6.2
27
.21
.32
.3
14
.31
5.3
23
.32
4.3
25
.32
6.3
27
.3
0
100
200
300
400
500
600
700
800
900
1000
1.1 6.1 11.1 16.1 21.1 26.1 31.1 5.2 11.2 16.2 21.2 26.2 2.3 7.3 12.3 17.3 23.3 28.3 2.4 7.4 12.4 17.4 22.4 27.4
Su
sp
en
sio
n e
mis
sio
n fa
cto
r (µ
g/v
eh
/m)
Date
1) SF (Kaisaniemi precipitation, 20 sanding days)
2) SF (Kaisaniemi precipitation, 11 sanding days)
3) SF (no precipitation, 20 sanding days)
4) SF (no precipitation, 11 sanding days)
5) SF (max precipitation, 20 or 11 sanding days)
20 sanding days
11 sanding days
FMI vs. SMHI suspension emission factors
Normalised sand dust layer (ls)
IA = 0.94
SF (FMI) is max 67% lower than SF (SMHI)
Suspension emission factor (SF)
SF (SMHI) is systematically higher than SF (FMI) because:• LSincrese is greater (SMHI: 0.048, FMI: 0.029)• LS is increased more often (SMHI: 885 times, FMI: 20 times)• LS is increased on different days and hours (e.g. SMHI: 2 Feb at 0, FMI: 1 Feb
at 23) reduction factors may influence differently on dust layer.
Daily PM10 in 8.1-2.5.2004
0
20
40
60
80
100
120
8.1. 15.1. 22.1. 29.1. 5.2. 12.2. 19.2. 26.2. 4.3. 11.3. 18.3. 25.3. 1.4. 8.4. 15.4. 22.4. 29.4.Date
Co
nc
en
tra
tio
n (
µg
/m3 ) predicted (Runeberg Street)
observed (Runeberg Street)
background (Kaisaniemi)
Cleaning & dust binding
Under-prediction: possible because•pedestrian ways cleaned after car lines,•traffic volume under-estimated?•No on-site meteorological data suspension emission factors under-estimated?
Over-prediction: due to the snowing/raining. •No on-site meteorological data suspension emission factors over-estimated?•Precipitation too light to be taken into account in the suspension model.
Under-prediction due to the cleaning of road surfaces.
•Can rise dust into the air in short time periods.•Not taken into account in the suspension model.
IA = 0.87FB = 0.03F2 = 94%
pre
dic
ted
(µ
g/m
3)
observed (µg/m3)
Daily PM10 concentrations