Road Vehicle Exhaust Emissions

An age of uncertainty

Dr Glyn Rhys-Tyler

Dispersion Modellers User Group 2017April 6th 2017

Holiday Inn, Kensington, London

Overview

We are living through a period of significant change, in terms of knowledge, technologies, behaviour, attitudes, and legislation.

The Chair has expressed a particular interest in the relationship between vehicle dynamics and exhaust emissions.

The first part of this presentation will address some issues of particular relevance to the Strategic Road Network (SRN), and potential lessons from recent Dutch experience.

Time permitting, the latter part will touch on some relevant (and probably familiar) areas of ongoing uncertainty in emissions modelling.

Current UK guidance

• Interim Advice Note 185/15: Updated traffic, air quality and noise advice on the assessment of link speeds and generation of vehicle data into ‘speed-bands’ for users of DMRB Volume 11, Section 3, Part 1 ‘Air Quality and Volume 11, Section 3. Part 7 Noise.

• Asserts that congestion on motorways tends to occur when speeds drop below 50mph (80kph). Assumes >50mph equates to ‘free flow’.

• The advice note identifies that during periods of congestion on the motorway, traffic emissions per vehicle increase relative to free flow conditions.

• Note: IAN 185/15 also provides guidance for Urban / Rural (Non-Motorway) Roads

Motorway speed band descriptors & emissions (IAN 185/15)

NOx emissions (g/km per vehicle) – IAN 185/15

NB. Speed and SD metrics derived from MIDAS data

Analysis in 2014 indicated that EFT tended to underestimate emissions in congested conditions compared to free flow (circa 36%), hence the publication of IAN 185/15.

Example EFT speed / emission relationship

On a motorway, with varying degrees of congestion (speed & acceleration), what really happens to exhaust emissions?

Vehicle dynamics and emission rates

Two key areas of uncertainty:

• Measuring and quantifying vehicle dynamics (speed & acceleration), and:

• Quantifying vehicle exhaust emission rates in different phases of vehicle dynamics.

The TNO (Dutch) approach (1)

• Netherlands Organisation for Applied Scientific Research (TNO) www.tno.nl/en/

• TNO report R10188 “On-road determination of average Dutch driving behaviour for vehicle emissions” (2016)

• Study to investigate and quantify the significance of driving behaviour as a factor in the determination of exhaust emission rates.

• Implemented a test program in 2015 to determine driving behaviour by randomly following / shadowing light vehicles across the Netherlands highway network using an instrumented vehicle.

• Instantaneous speed, acceleration and position were recorded at 1Hz.

The TNO (Dutch) approach (2)

• In this way, ‘average’ driving behaviour for Dutch drivers on Dutch roads (in terms of instantaneous speed and acceleration) was determined across different road types, traffic situations, and levels of congestion, as at 2015.

• Professional driver used to ‘shadow’ a sample of light vehicles• 108 hours of total driving time, covering a distance of 6640 km,

comprising 180 trips (motorway, rural, urban).• Output set of ‘driving vectors’ (‘q’), describing and quantifying the mix

of passenger car driver behaviour (vehicle speed and acceleration) across different road types, levels of congestion, speed limits, and modes of speed enforcement.

The TNO (Dutch) approach (3)

• These ‘vectors’ (‘q’) are then associated with average exhaust emission rates, so that total exhaust emissions for a particular passenger car type can be estimated, using TNO’s VERSIT+ emissions model.

• ‘q’ values quantify the fraction of driving time at different velocities and accelerations normalized to 1 km of total distance travelled.

• Driving dynamics are defined by the dynamic variable ‘w’, defined as:

w = a + 0.014v, where ‘a’ is in units of m/s2, and v is in units of kph.

• Emission factors (EF) in g/km are a function of the emission map ‘u’ and the driving vector ‘q’:

EF(g/km) = (q1*u1) + (q2*u2) + (q3*u3) + … + (q9*u9) + (q10*u10)

TNO ‘w’ values and ‘q’ vectors

Comment:‘w’ values;‘q’ values;Terminology

UK ‘ad hoc’ data collection

Vehicle dynamics data collected on an ‘ad hoc’ informal basis, Oct 2016 to Apr 2017.

Speed (kph) and position at 10Hz

217 hours of data, circa 10,000 miles, circa 70 ‘trips’

Majority on the M1 & A1(M), but also other routes.

Map base © Google Earth Pro

Sample of vehicle speed data – M1 J14 to J21 (northbound)

Acknowledgement: Transport Systems Catapult for graphic

Observed speed and S.D. (70mph speed limit)

Observed speed and S.D. (50mph average speed cameras)

Comparison of Dutch and UK ‘q’ values

• Dutch 120kph closest speed limit to UK 70mph (113kph);

• M1 J14 to J16 a close match to the Dutch average ‘q’ values;

• Observations from M1 J19 to J21 a little faster than the Dutch average ‘q’ values;

Where can we obtain corresponding ‘u’ (emission rate) values?

• Options are limited;• For the purpose of presenting a worked example (only), reference is

made to the data collected by DfT in late 2015;• DfT collected laboratory, on-track, and on-road emissions data from

a range of diesel passenger cars;

• Here we will use some laboratory measurements of NOx (g/sec) from a sample of Euro 6 diesel cars operating over the WLTC drive cycle.

• N.B. DfT reported that on-road (PEMS) NOx emissions were around 3.8 times higher than the WLTC cycle laboratory values for this sample of vehicles. Be careful….

WLTC drive cycle (Class 3)

WLTC drive cycle – DfT 2015 laboratory tests

NOx emissions (g/sec) over the WLTC cycle for 9 Euro 6 diesel cars

1800 second (30 minute) drive cycle; data at 1Hz

Note locations and magnitude of transient peaks (variability).

NOx emission rates derived from laboratory WLTC drive cycle

• Derived from a sample of nine Euro 6 diesel passenger cars;• Within speed bands, mean values ‘generally’ increase monotonically with load;• N.B. Lack of data within ‘q8’ vector using this (WLTC) drive cycle.

Example 1 – 70mph limit (congested)

Example 2 – 50mph limit average speed cameras (congested)

Example 3 – 13 consecutive suburban roundabouts

DfT 2015 PEMS ‘on-road’ test route

On-track and on-road PEMS data;

Potentially a more representative source of emissions data for ‘real world’ driving;

Possible initial source for more generally applicable ‘u’ values……

Map base © Google Earth Pro

Some other areas of uncertainty in exhaust emission modelling

• The ongoing primary NO2 (f-NO2) problem. Still ongoing….

• Observed variability in exhaust emissions performance across vehicle manufacturers. A challenge and an opportunity….

• Exhaust emissions from vans (N1) up to 3.5 tonnes. Deserves more attention….

• Age / mileage /maintenance related deterioration in performance of emissions control technologies. Significant uncertainty….

• The legacy challenge. Perhaps the biggest challenge….

Passenger cars – Total oxides of nitrogen

Source: Carslaw & Rhys-Tyler (2013)

Passenger cars – Nitrogen dioxide emissions

Source: Carslaw & Rhys-Tyler (2013)

Variability in NOx emissions ratios by diesel car manufacturer

Variability in NOx emissions ratios by diesel van manufacturer

References

• Interim Advice Note 185/15: Updated traffic, air quality and noise advice on the assessment of link speeds and generation of vehicle data into ‘speed-bands’ for users of DMRB Volume 11, Section 3, Part 1 ‘Air Quality and Volume 11, Section 3. Part 7 Noise.

• Carslaw D. and Rhys-Tyler G. (2013). Remote sensing of NO2 exhaust emissions from road vehicles. Department for Environment Food and Rural Affairs (DEFRA).

• DfT (2016). Vehicle Emissions Testing Programme (Cm 9259). April 2016.• TNO report R10188 “On-road determination of average Dutch driving behaviour

for vehicle emissions” (2016)

Contact

Dr Glyn Rhys-Tyler

Email: admin@glynrhys-tyler.com

Web: www.glynrhys-tyler.com