Presentation by Dr James Tate at Institute of Air Quality Management (IAQM) Dispersion Modellers User Group December 2014. www.its.leeds.ac.uk/people/j.tate http://iaqm.co.uk/event/dmug-2014/

2. Outline
 Background – Modelling Road Transport Emissions
 Large-scale Networks e.g. Regional / National
 City Networks
 Modelling a “VirtualWorld”
 Framework
 Microscopic traffic simulations
 Instantaneous vehicle emission modelling
 Calibration &Validation
 Results
 Mapping vehicle emissions
 Spatial & temporal variations
 Summary & Conclusions
 Work in progress
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3. MODELLING LARGE-SCALE NETWORKS
Represented a Line Sources
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City ofYork
Source: http://ntis.trafficengland.com/map 10.55 am 02/12/2014

4. MODELLING CITY NETWORKS
Short links
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5 km 500 m

5. A “VIRTUAL” YORK
Coupled micro-scopic traffic & instantaneous emission model
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6. TRAFFIC MICROSIMULATIONS1
 TRAFFIC DEMAND
 Average weekday (May 2011)
 Automatic Traffic Count (ATC) & Manual Count data
J ANPR surveys (19th May 2011, 0700 – 1900hrs)
 TIME PERIODS
 AM shoulder
 AM peak
 Inter-Peak
 PM peak
 PM shoulder
 Evening
 NIGHTtime
 24-hour weighted average
• CALBRATION
• Demand/ Flows (DMRB procedure, GEH stat)
• Journey times (DMRB criteria)
+ Vehicle type proportions ( ± 1% )
 Car, Van, HGV (rigid & artic), Bus, Coach
• Vehicle dynamics
• SIMULATIONS
• Harvest ALL vehicle trajectories (1Hz, 10 replications)
• >1 million vehicle kms for the ‘Base’ scenario
1TheYork 2011 S-Paramics network created by David Preater (Halcrow, 2011)
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7. MODELLING FRAMEWORK
Coupled micro-scopic traffic & instantaneous emission model
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8. VEHICLE DYNAMICS
Comparing observed and modelled vehicle dynamics
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OBSERVED
Passenger CarTracking:GPS + Road speed (CAN)
MODELLED
Traffic microsimulations (Paramics) – Passenger car
Sample: AM +PM peak period
100 kms, 4 hours (stationary excluded)
Sample: one replicationAM +PM peak
12, 000 kms, 600 hours (stationary excluded)

9. INSTANTANEOUS EMISSION MODEL
PHEM version 11
 Comprehensive power-instantaneous emission model for the EU fleet
 Simulates fuel consumption (FC) and tail-pipe emissions of NOX,NO2,
CO,HCs, Particulate Mass (PM), Particle Number (PN)
 Whole European vehicle fleet:
 Euro 0 to Euro 6
 Petrol, diesel and hybrid powertrains
 Light and Heavy-duty vehicles etc.
 Simulations:
 Consider all driving resistances including GRADIENT
 Gear shift model
 Transient engine maps (with time correction functions)
 Thermal behaviour of engine, catalyst, SCR etc.
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10. REMOTE SENSING VEHICLE EMISSIONS
Surveying the vehicle fleet on the road
Emission ratios
From peak exhaust plume conc.
 NO / CO2
 Predict NO2 and NOX / CO2
 CO / CO2
 HC / CO2 &
 PM (opacity measure)
Local measurements
4-days surveys September 2011
> 10,000 ‘valid’ records
Camera
(Number plate)
Vehicle Detector
(Speed andAcceleration)
Source/Detector
Mirror Box
Source
Detector
Emissions Analyser
(Common
Configurations)
ESP RSD-4600 instrument
www.esp-global.com
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11. EMISSION MODELLING VALIDATION (2)
Comparison with Remote Sensing Emission Factors
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Car_diesel
ܴܵோ்ௐ ைோ௄ ெ ை஽ா௅ =
ܱܰ௑
ܥܱଶ ோௌ
×
ܥܱଶ
݇݉ ோ்ௐ ைோ௄ ெ ை஽ா௅
Euro class
NOX (grams/km)
1.0
0.5
0.0
E0 E1 E2 E3 E4 E5 E6
E0 E1 E2 E3 E4 E5 E6
Car_petrol
ܴܵை஻ௌாோ௏ா஽ ்ோ஺௃. =
ܱܰ௑
ܥܱଶ ோௌ
×
ܥܱଶ
݇݉ ை஻ௌாோ௏ா஽ ்ோ஺௃.
ܴܵெ ஺ே௎. =
ܱܰ௑
ܥܱଶ ோௌ
×
ܥܱଶ
݇݉ ெ ஺ே௎ .

12. CAR-petrol CAR-diesel VAN HGV COACH
NOX (%)
0 5 10 15 20 25 30 35
BUS
EMISSION CONTRIBUTIONS
Oxides of Nitrogen (NOX)
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13. A “VIRTUAL” YORK 2
Coupled micro-scopic traffic & instantaneous emission model
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14. MAPPING VEHICLE EMISSIONS
The spatial variation in NOX – AM peak
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15. GRAPHING VEHICLE EMISSIONS
The spatial variation in NOX – AM peak
{©Copyright GoogleTM 2014}
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BUS
STOP

16. INFLUENCE TIME OF DAY
Bootham to Gillygate direction
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17. VEHICLE TYPE CONTRIBUTIONS
Bootham to Gillygate direction
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{©Copyright GoogleTM 2014}

18. BOOTHAM  GILLYGATE (South  East)
NOX emissions: EFT v5.2c & PHEM11
AM Peak [08:00  09:00hrs]
0 100 200 300 400 500
0.0 0.5 1.0 1.5 2.0
Distance (metres)
NO X (grams / hr / m)
BOOTHAM   GILLYGATE

19. BOOTHAM  GILLYGATE (South  East)
NOX emissions: EFT v5.2c & PHEM11
EVening [19:00  23:00hrs]
0 100 200 300 400 500
0.0 0.5 1.0 1.5 2.0
Distance (metres)
NO X (grams / hr / m)
BOOTHAM   GILLYGATE

20. Summary
METHOD
 Detailed, coupled traffic-vehicle emission simulations are now feasible
 Emission Factors are in agreement with remote sensing measurements
 The PHEM (total) NOX emissions from Bootham and Gillygate over a
typical weekday are higher than those predicted by the UK EFT 26%
 The approach, moving towards a “virtual” representation of local traffic
networks and the local vehicle fleet:
 naturally encapsulates events that influence emissions e.g. Bus stops
 Complex traffic situations and interventions can be assessed:
 Congestion
 Demand management
 Control strategies e.g. Smoothing flow, penetration new Driver Assist Systems
 Allows the distribution of emissions through urban streets and
intersections to be mapped
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21. Conclusions
 During periods of light traffic demand,NOX emissions are
concentrated around the intersection itself, with emissions at
mid-link locations where vehicles are typically ‘cruising’ at a low-level
 In Peak periods with slow moving queues on links, emissions are
elevated in the vicinity of the intersection, but also spread along
the length of the links
? Does the uniform ‘line source’ assumption still hold for local-scale
vehicle emission assessments & micro-scale dispersion
modelling in street canyons
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22. Further work
MODELVERIFICATION &VALIDATION:
 Developing methods to quantify differences in vehicle dynamics
 e.g. variability in cruising speeds
 Further PHEM validation
 Light- and Heavy-duty chassis dyno measurements (London Drive Cycle)
 Evaluating the complete Traffic –Vehicle Emissions – Dispersion
Modelling chain, comparison to ambient measurements.
APPLICATIONS:
 Fleet renewal e.g. Low Emission Zone evaluation, Bus replacement
 Sustainable transport policies e.g. reducing the demand for travel
 Motorway / Highway environment
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