Outline Background Modelling Road Transport Emissions

Large-scale Networks e.g. Regional / National City Networks

Modelling a Virtual World 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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MODELLING LARGE-SCALE NETWORKSRepresented a Line Sources

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City ofYork

Source: http://ntis.trafficengland.com/map 10.55 am 02/12/2014

MODELLING CITY NETWORKSShort links

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5 km 500 m

A VIRTUAL YORKCoupled micro-scopic traffic & instantaneous emission model

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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

1 TheYork 2011 S-Paramics network created by David Preater (Halcrow, 2011)

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

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MODELLING FRAMEWORKCoupled micro-scopic traffic & instantaneous emission model

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VEHICLE DYNAMICSComparing observed and modelled vehicle dynamics

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OBSERVEDPassenger Car Tracking: GPS + Road speed (CAN)

MODELLEDTraffic microsimulations (Paramics) Passenger car

Sample: AM +PM peak period100 kms, 4 hours (stationary excluded)

Sample: one replication AM +PM peak12, 000 kms, 600 hours (stationary excluded)

INSTANTANEOUS EMISSION MODELPHEM 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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Emission ratiosFrom peak exhaust plume conc. NO / CO2Predict NO2 and NOX / CO2 CO / CO2 HC / CO2 & PM (opacity measure)

Local measurements4-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)

Camera(Number plate)

Vehicle Detector(Speed andAcceleration)

Source/Detector

Mirror Box

Source

Detector

Emissions Analyser(Common

Configurations)

REMOTE SENSING VEHICLE EMISSIONSSurveying the vehicle fleet on the road

ESP RSD-4600 instrumentwww.esp-global.com

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EMISSION MODELLING VALIDATION (2)Comparison with Remote Sensing Emission Factors

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= Euro class

NO

X(g

ram

s/km

)

0.0

0.5

1.0

E0 E1 E2 E3 E4 E5 E6

Car_diesel

E0 E1 E2 E3 E4 E5 E6

Car_petrol

. = .

. = .

CAR-petrol CAR-diesel VAN HGV COACH

NO

X(%

)

05

1015

2025

3035

BUS

EMISSION CONTRIBUTIONSOxides of Nitrogen (NOX)

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A VIRTUAL YORK 2Coupled micro-scopic traffic & instantaneous emission model

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MAPPING VEHICLE EMISSIONSThe spatial variation in NOX AM peak

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GRAPHING VEHICLE EMISSIONSThe spatial variation in NOX AM peak

{Copyright GoogleTM 2014}

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BUSSTOP

INFLUENCE TIME OF DAYBootham to Gillygate direction

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VEHICLE TYPE CONTRIBUTIONSBootham to Gillygate direction

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{Copyright GoogleTM 2014}

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(g

ram

s/h

r/m

)

BOOTHAM GILLYGATE

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(g

ram

s/h

r/m

)

BOOTHAM GILLYGATE

BOOTHAM GILLYGATE (South East)NOX emissions: EFT v5.2c & PHEM11

SummaryMETHOD

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 andintersections to be mapped

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Conclusions

During periods of light traffic demand, NOX emissions areconcentrated around the intersection itself, with emissions atmid-link locations where vehicles are typically cruising at a low-level

In Peak periods with slow moving queues on links, emissions areelevated in the vicinity of the intersection, but also spread alongthe length of the links

? Does the uniform line source assumption still hold for local-scale vehicle emission assessments & micro-scale dispersionmodelling in street canyons

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Further workMODELVERIFICATION &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 DispersionModelling 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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