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Application of General Finite Line Source Model to predict benzene levels near Irish motorway
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.