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CeNEM-2007
1. Application of the General Finite Line
Source Model to the prediction of
Benzene concentrations adjacent to a
motorway in Ireland.
Rajiv Ganguly
Brian M. Broderick
Department of Civil, Structural and
Environmental Engineering
Trinity College Dublin
2. Overview
v Objectives
v General Finite Line Source Model (GFLSM)
v Comparison of Monitored and GFLSM data (M50)
v Comparison of GFLSM with CALINE4 (M50)
v Conclusions
3. Overall Research Objectives
Ø To identify suitable modelling techniques for
motorway and urban street canyon.
Ø To develop models suitable for implementation in
integrated transport environmental modelling.
4. Overall Research Objectives
Ø To investigate the sensitivity of model outputs to
meteorological, traffic and background concentration
inputs.
Ø To recommend best practice for air quality modelling of
traffic emissions in Ireland.
Ø To determine the accuracy of the models through
comparison of predicted and ambient air quality data .
7. Study on M50 motorway.
Schematic Diagram of Sampling Location.
Receptors
Receptors
Secondary road
-240m
-120m
-25m
25m
120m
240m
NM50 Motorway
Inner suburbs
and city centre
8. Input Data
l Traffic volume
l Meteorological Conditions (wind speed, wind direction)
l Emission factors
l Briggs Horizontal and Vertical dispersion coefficients.
Output Data.
§ Traffic source related concentration estimates for hydrocarbons
were obtained at the receptor locations.
§ Results for benzene are shown below as they are more
relevant for traffic emissions.
9. Results on M50 Motorway for Benzene.
Variation of monitored and predicted data at 25m
0
0.1
0.2
0.3
0.4
0 5 10 15 20
sampling days
concentration(ppb)
monitored data
CALINE4
GFLSM
10. Results on M50 Motorway for Benzene.
variation of monitored and predicted data at 120m
0
0.1
0.2
0.3
0.4
0 5 10 15 20
sampling days
concentration(ppb)
monitored data
CALINE4
GFLSM
11. Results on M50 Motorway for Benzene.
variation of monitored and predicted data at 240m
0
0.03
0.06
0.09
0.12
0.15
0 5 10 15 20
sampling days
concentration(ppb)
monitored data
CALINE4
GFLSM
12. Results on M50 Motorway for Benzene.
variation of mean concentration with receptor
distance (benzene)
0
0.05
0.1
0.15
0.2
0 50 100 150 200 250
distance from road(m)
meanconcentration
(ppb)
monitored data
CALINE4
GFLSM
13. Results on M50 motorway for Benzene.
scatter plots for measured and predicted data at 25m
0
0.1
0.2
0.3
0.4
0.5
0 0.1 0.2 0.3 0.4 0.5
measured data (ppb)
predicteddata(ppb)
CALINE4
GFLSM
M=P
M=2P
M=0.5P
14. Results on M50 motorway for Benzene.
scatter plots of measured and predicted data at 120m
0
0.02
0.04
0.06
0.08
0.1
0 0.02 0.04 0.06 0.08 0.1
measured data (ppb)
predicteddata(ppb)
CALINE4
GFLSM
M=P
M=2P
M=0.5P
15. Results on M50 motorway for Benzene.
scatter plots of predicted data at 25m
0
0.1
0.2
0.3
0.4
0.5
0 0.1 0.2 0.3 0.4 0.5
CALINE4
GFLSM
16. Results on M50 motorway for Benzene.
scatter plots of predicted data at 120m
0
0.02
0.04
0.06
0.08
0.1
0 0.02 0.04 0.06 0.08 0.1
CALINE4
GFLSM
17. Results on M50 motorway for Benzene.
§ Statistical Analysis of Monitored and Predicted data
(a) At 25 meters.
Monitored CALINE GFLSM
Mean 0.15 0.19 0.19
IA 1.00 0.43 0.57
R 1.00 0.11 0.31
F2 100% 65% 95%
FB 0.00 0.3 0.3
NMSE 0.00 0.43 0.44
18. Results on M50 motorway for Benzene.
variation of IAwith receptor distance
0
0.2
0.4
0.6
0.8
1
0 100 200 300
receptor distance(m)
IAvalues
Monitored data
CALINE4
GFLSM
19. Results on M50 motorway for Benzene.
variation of F2 with receptor distance
0
20
40
60
80
100
0 100 200 300
receptor distance(m)
F2values
Monitored data
CALINE4
GFLSM
20. Results on M50 motorway for Benzene.
variation of NMSE with receptor distance
0
0.5
1
1.5
2
2.5
0 100 200 300
receptor distance(m)
NMSEvalues
Monitored data
CALINE4
GFLSM
21. Ø For the M50 motorway site the performance of GFLSM has
been found to be quite satisfactory when compared with
CALINE4, an USEPA reference model
Conclusions
Ø Further studies have been conducted for in depth
evaluation of GFLSM model and it has been found that
it can be readily incorporated within integrated
environment transport modelling.
Ø An analytical model, GFLSM has been discussed and has
been applied at motorway conditions.
22. Acknowledgement.
l This work is a part of the Environment Transport
Interface (ETI) project funded by the ERTDI Research
Programme.