AUT / LHTEE Street Emission Ceilings (SEC) exercise Task leader: Nicolas Moussiopoulos Aristotle...

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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AUT /LHTEE

SEC-EIONET-Oslo-Oct03

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.

AUT / LHTEE Street Emission Ceilings (SEC) exercise Task leader: Nicolas Moussiopoulos Aristotle...

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