street emission ceilings (sec) exercise
DESCRIPTION
Street Emission Ceilings (SEC) exercise. Task leader: Nicolas Moussiopoulos Aristotle University Thessaloniki Team: Dick van den Hout, TNO Steinar Larssen, NILU Frank de Leeuw, RIVM Zissis Samaras, AUT/LAT. Many thanks to: Roel van Aalst - PowerPoint PPT PresentationTRANSCRIPT
AUT /LHTEE
Street Emission Ceilings (SEC) exercise
Task leader:
Nicolas Moussiopoulos
Aristotle University Thessaloniki
Team: Dick van den Hout, TNO
Steinar Larssen, NILU
Frank de Leeuw, RIVM
Zissis Samaras, AUT/LAT
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Acknowledgements
Many thanks to:• Roel van Aalst• Leonor Tarrason et al.• Ruwim Berkowicz• Ioannis Douros, Liana Kalognomou, Christos
Naneris, Apostolos Papathanasiou
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Objectives
Quantifying the influence of urban and local emissions and other smaller scale effects on concentrations at urban hotspots as a basis for measures for attaining compliance.
Development and pilot application of a methodology for this purpose, also with relevance to health issues.
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So far activities
• Review of relevant existing studies• Design of city and street typologies• Analysis of excess concentrations (PM10,
PM2.5 ,NO2) at selected traffic air monitoring stations by comparing with the urban background
• Interpretation of the above analysis in terms of local emission estimates
• Demonstration of model application potential
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Planned activities
• Review of relevant simple and state-of-the art models
• Expand application of suitable urban and local scale models to a limited number of well-documented cases
• Synthesis of results, presentation to a wider audience, first ideas on how to generalize
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Review of relevant existing studies• Field campaigns related to source
apportionment• Monitoring data analysis associated with the
characteristics of hotspots• Resuspension studies• Modelling studies leading to source-receptor
relationships• Emission patterns in busy streets and
associated key parameters
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Why city and street typology?
To develop a method for determining at which emissions in streets (depending on street and city type) limit values are reached.
Such a method will• allow taking the street level into account in
CAFE’s IA modelling• help local authorities in identifying critical
hotspots
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First tentative typification
Quantification of• Regional background contribution
… using EMEP model results• Urban background contribution
… setting-up a city typology• Hotspot contribution
… setting-up a street typology
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Towards a citycity typology
Key parameters:• Population (continuous)• Region and local climate:
• enclosed / open• West/North; Central; South
• Type of predominant emission sources:• major industry• no major industry
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Towards a streetstreet typology
Key parameters:• Street emission (continuous)• Average wind speed nearby:
3.5 m/s• > 3.5 m/s
• Configuration:• Open rural terrain• Non-canyon streets in built-up areas • Wide street canyon (W/H > 1.5)• Narrow street canyon (W/H 1.5)
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0
2.5
5
7.5
10
12.5
15
20
25
Urban background concentrations
0.00
1.80
0 800000
Population
Urb
an
ba
ckg
rou
nd
co
nc
entr
atio
n
Type C1a
Type C1b
Type C2a
Type C2b
Type C3a
Type C3b
Type C4a
Type C4b
Type C5a
Type C5b
Type C6a
Type C6b
Street concentrations
0.00
1000.00
0 800000Street emission
Str
eet
co
nc
entr
ati
on
Type S1a
Type S1b
Type S2a
Type S2b
Type S3a
Type S3b
Type S4a
Type S4b
Illustration oftypification
City typologydefining f(pop)
Street typologydefining g(emi)
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From concentrations to SECs
Concentration in a street of j-th type in a city of i-th type:
c(Ci,Sj) = cRBG + fi(pop) + gj(emi)
Street emission ceiling for this street:
SECij = Gj(cLV – [cRBG + fi(pop)])
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Analysis of excess concentrationsThe aim of this subtask is to:• contribute to knowledge of (relative) emission
factors for vehicles, by comparing PM and NOx concentrations, as functions of vehicle distribution in traffic
• contribute to analysis of the road dust resuspension source, by comparing PM2.5, PM10 and NOx concentrations, together with meteo data
• contribute to relationships between street/traffic parameters and resultinh concentrations
• provide a basis for model-measurement comparisons / model validation.
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Data analysis (1/2)
Intention to study excess concentrations at hotspot stations. Analysis includes:• deltaC (hotspot – urban background), hourly
time series• hourly time series of the other parameters• average, percentiles, max (hour and day)• separate in work-days and weekend days• compare deltaC at the various stations,
explain differences in terms of traffic, meteo, strength of resuspension source,..
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Data analysis (2/2)
Furthermore:• Study deltaC as a function of time of day• Study deltaC as a function of wind direction• Study ratio PM/NOx (hour, day):
plot time series in parallel look for peaks & variations analyse scatter plots to find ratios and
outliers/different domains in the data (e.g. dry/wet road surface, poor dispersion)
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Progress of data analysisReview reports are being finalized.Up to now 5 stations pairs have been analysed:• Hornsgatan, StockholmHornsgatan, Stockholm• Skårersletta, Oslo• Marylebone Road, London• Ermou,ThessalonikiErmou,Thessaloniki• Vrsovice, Prague• Frankfurter Allee, Berlin• Copenhagen• Madrid• Hannover• Milano
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Hornsgatan, Stockholm (1/3)
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90 m
70 mN
S
R
Hornsgatan, Stockholm (2/3)
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Hornsgatan, traffic dataTraffic data
0
10
20
30
40
50
60
1 2 3 4 5 6 7 8 9 10 11 12
Month
AADT/1000 Heavy duty (%) Speed (km/h)
Daily distribution of cars
0
200
400
600
800
1000
1200
1400
1600
1800
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Nu
mb
er o
f car
s
Midle Max
Daily distribution of velocity, Hornsgatan
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Vel
oci
ty,
km/h
Midle Max
Daily distribution of HDV percentage
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
%
Midle Max
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Hornsgatan
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10 11 12
Month
Co
nse
ntr
atio
n
PM10 Street PM2.5 Street NOx/10 Street
Urban background
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10 11 12
Month
Co
nse
ntr
atio
n
PM10 Urban background PM2.5 Urban background
NOx/10 Urban background
Delta
0
10
20
30
40
50
60
70
80
1 2 3 4 5 6 7 8 9 10 11 12
Month
Del
ta c
on
sen
trat
ion
Delta PM10 Delta PM2.5 Delta/10 NOx
Ratios
0,00
0,05
0,10
0,15
0,20
0,25
0,30
0,35
0,40
0,45
1 2 3 4 5 6 7 8 9 10 11 12
Month
Ra
tio
dPM10/dNOx dPM2.5/dNOx
Hornsgatan station pair, monthly averages
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PM10 - Hornsgatan station vs. urban and rural background, annual variation (3 years)
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Hornsgatan, average daily PM10Daily distribution, PM10, street
0
10
20
30
40
50
60
70
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nce
ntr
atio
n
Midle Max /10
Daily distribution, PM10, urban background
0
2
4
6
8
10
12
14
16
18
20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nce
ntr
atio
n
Midle Max /10
Daily distribution, Delta PM10
0
10
20
30
40
50
60
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nce
ntr
atio
n
Middel Max /10
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Hornsgatan, average daily PM2.5Daily distribution, PM2.5, street
0
2
4
6
8
10
12
14
16
18
20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nce
ntr
atio
n
Midle Max /10
Daily distribution, PM2.5, urban background
0
2
4
6
8
10
12
14
16
18
20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nce
ntr
atio
n
Midle Max /10
Daily distribution, Delta PM2.5
0
2
4
6
8
10
12
14
16
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nce
ntr
atio
n
Midle Max /10
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Hornsgatan, average daily NOx
Daily distribution, NOx, street
0
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nce
ntr
atio
n
Midle Max /10
Daily distribution, NOx, urban background
0
10
20
30
40
50
60
0 5 10 15 20 25 30
Hour
Co
nce
ntr
atio
n
Midle Max /10
Daily distribution, Delta NOx
0
50
100
150
200
250
0 5 10 15 20 25 30
Hour
Co
nce
ntr
atio
n
Midle Max /10
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Interpretation via emissions estimates
Calculation of emissions for CO, NOx, using COPERT 3 methodology, taking into account: Traffic volume and speed Fleet composition (% HDV) Road characteristics Vehicle classification
using TRENDS model results.
Sector Subsector Tech January
Heavy Duty Vehicles Gasoline >3,5 t Conventional 0Heavy Duty Vehicles Diesel 3,5 - 7,5 t Conventional 12406Heavy Duty Vehicles Diesel 3,5 - 7,5 t Euro I - 91/542/EEC Stage I 2882Heavy Duty Vehicles Diesel 3,5 - 7,5 t Euro II - 91/542/EEC Stage II 4126Heavy Duty Vehicles Diesel 3,5 - 7,5 t Euro III - 2000 Standards 0Heavy Duty Vehicles Diesel 7,5 - 16 t Conventional 13630Heavy Duty Vehicles Diesel 7,5 - 16 t Euro I - 91/542/EEC Stage I 3166Heavy Duty Vehicles Diesel 7,5 - 16 t Euro II - 91/542/EEC Stage II 4533Heavy Duty Vehicles Diesel 7,5 - 16 t Euro III - 2000 Standards 0Buses - Coaches Urban Buses Conventional 6461Buses - Coaches Urban Buses Euro I - 91/542/EEC Stage I 630Buses - Coaches Urban Buses Euro II - 91/542/EEC Stage II 819Buses - Coaches Urban Buses Euro III - 2000 Standards 0Buses - Coaches Urban Buses Euro IV - 2005 Standards 0Buses - Coaches Urban Buses Euro V - 2008 Standards 0Buses - Coaches Coaches Conventional 1615Buses - Coaches Coaches Euro I - 91/542/EEC Stage I 158Buses - Coaches Coaches Euro II - 91/542/EEC Stage II 205Buses - Coaches Coaches Euro III - 2000 Standards 0
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Comparison with data analysis resultsRatios
0,00
0,05
0,10
0,15
0,20
0,25
0,30
0,35
0,40
0,45
1 2 3 4 5 6 7 8 9 10 11 12
Month
Rat
io
dPM10/dNOx dPM2.5/dNOx
0,00
0,01
0,02
0,03
0,04
0,05
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
PM
2.5/
NO
x ra
tio
•Results are in good agreement with ratios derived from the data analysis.
•Only hot emissions are assumed as the cold start effect is assumed to be negligible in the specific street canyon.
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Ermou str., Thessaloniki: area features
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Ermou str., average daily PM10, NO2 and NOx
Street, daily distribution
0
20
40
60
80
100
120
140
160
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nc
en
tra
tio
n,
µg
/m3
PM10, street NO2, street NOx, street
Urban background, daily distribution
0
5
10
15
20
25
30
35
40
45
50
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
Co
nc
en
tra
tio
n,
µg
/m3
PM10, urban background NO2, urban background NOx, urban background
Delta, daily distribution
0
20
40
60
80
100
120
140
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Hour
con
cen
trat
ion
, µ
g/m
3
Delta PM10 Delta NO2 Delta NOx
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Ermou str., CO vs. NOx
CO/NOx/100 ratio
0,0
0,1
0,1
0,2
0,2
0,3
1 4 7 10 13 16 19 22
Emission ratio Concentration ratio
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Ermou str., PM vs. NOx
Ratios
0,00
0,20
0,40
0,60
0,80
1,00
1,20
1,40
1 4 7 10 13 16 19 22
PM10/NOx conc. ratio PM2.5/NOx emission ratio
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Conclusions• So far data analysis has been very instructive (in
terms of excess concentrations and PM/NOx ratios).
• Comparison between emission and concentration ratios has shown variable results so far.
• Experience with model application is encouraging.• Yet, data has been hard to find (station pairs and
PM2.5 concentrations) and is still being processed, the aim being to improve European coverage.
• Model application should be expanded to more cities and more model systems.