Routes to Clean Air 2016 - Dr Kevin Turpin, TRL

© Copyright 2016 TRL Ltd

Dr Kevin TurpinOctober 2016

Development of Remote Sensors for Vehicle Emissions Detection


Contents

2

• Background

• Idea

• Objectives

• Approach

• Results

• Conclusions

• Applications

• Follow on research


Background

1. Past 20 years: Little sustainable improvement in AQ

2. Trend data shows that NO2 concentrations at roadside locations in Inner London Boroughs have barely improved since the early 2000s (Policy Exchange 2016)

3. Road transport is responsible about 46% of total NOX (Transport Professional 2015)

4. Road transport contribution to NO2 can be as high as 80% at some near road locations (Transport Professional 2015)

5. Primary NO2 emissions from diesel vehicles are a key issue

6. Vehicle NO2/NOX ratio has increased over the decade. Some evidence perhaps that f-NO2 is now stabilising (Carslaw et.al. 2016)

7. Devices fitted to vehicles to control emissions may not be as effective as one might expect particularly on light vehicles

8. One solution perhaps to map and manage NO2 is to further develop remote sensors

9. Provide better evidence for national and local air quality management (e.g. AQMAs)

3


Initial Idea

FEAT (20 years old)

HC+CO+CO2

+NO

IR/UV technology

Adding NO2+NH3

(1Year+£30K)

?

Cambridge University

Department of Chemistry

LEDs and Differential

optical absorption

spectroscopy

Potential for a state-of-

the-art upgrades

Awarded DfT Innovation

Grant

Low end

Accuracy

option

High end

Accuracy

option


Objectives

1. Construct a prototype lab based NO2 DOAS measurement system at Cambridge University;

2. Carry out laboratory sensitivity tests of the NO2 system;

3. Calibrate FEAT to measure CO, HC and CO2 concentrations in controlled conditions at TRL;

4. Undertake field trials of the NO2 DOAS system alongside FEAT under controlled conditions at TRL;

5. Analyse NO2 results from the DOAS system with fast response CO2

measurements measured by FEAT;

6. Provide recommendations for future commercial evolution of the system including potential developmental funding opportunities.


Approach

Construct a prototype lab based NO2 DOAS measurement system

The key to this system is the application of a bright and stable LED which is much more robust and compact than conventional IR and UV light sources (e.g. those used in FEAT).

Key issue: Whether the light level observed through the detector is acceptable for sensitive NO2 measurements

Results from the bench test proved successful!

Blue LED source

Adsorption detected by sensor

Principal of the lab testing


Approach

Carrying out laboratory sensitivity tests of the NO2 system

Comparisons between the spectrum outputs were made with what is expected from a known concentration of NO2

20 ppm concentration of NO2 was injected to a Tedlar gas sampling bag (with a depth of 5 cm along the direction of the beam, similar to that of a typical tailpipe plume) and then placed in the middle of the light beam.


Approach

Setting up and calibrating FEAT

Convert raw voltage output values to concentrations as a percentage of exhaust gas

No obvious way of understanding this process

To overcome this issue, TRL undertook a series of tests to calibrate the FEAT system in the laboratory

The calibration cell used for this experiment was 20 mm long by 25 mm in diameter and the lens was made from quartz.


Approach

Performing field trials of the NO2 measurement system alongside FEAT under controlled conditions at TRL

Two phases of field trials were conducted for this study using controlled hanger facilities

FEAT and NO2 measurement system were set up alongside each other at the same height with the light sources aligned

Recording CO-HC-CO2 & NO2


Approach

Performing field trials of the NO2 measurement system alongside FEAT under controlled conditions at TRL

10 vehicles (mainly diesels were used in the testing phase)

Three drive-bys for each vehicle


Results

NO2 measurement system calibration results

Upper panel: Calibration at 40 Hz (grey dots), 10 Hz (green lines), and 1 Hz (black lines) acquisition rate. Lower panel: Probability distribution of a series of zero-ppm measurements made at 40 Hz.


Results

FEAT calibration results (US data)

High peaks in NO2 readings were recorded

Source: FEAT System US


Results

FEAT calibration results

This test allows the team to understand the voltage output with respect to the change in pollutant concentration

1% change in CO2 causes the FEAT output to change by 73.1 mV


Results

FEAT calibration results (initial drive-by test)

Shows the initial blockage of light by the vehicle and then the trace recovering back to a steady state (e.g. ~5,250 mV for CO2)

Steady state

0 0.120.04 0.06 0.08 0.10.020

1000

2000

3000

4000

5000

6000

7000

8000

9000

Time (s)

Source reading (mv) Vehicle detected


Results

Laboratory drive-by testing (Phase 1)

Measured and reference spectra for NO2 from one of the vehicle passes. This confirms an absolutely unambiguous NO2 identification


Results


The observed NO2 from a 2005 diesel van and a 2010 eco-diesel passenger car are presented.

The FEAT system recorded % CO, HC and CO2

Conclusions from the NO2 measurement system:

The two vehicles have similar NO2 emissivity;

The same vehicle can show significantly different particle emissivity (e.g. Pass 1 and 3, for the older 2005 van);

Diesel Eco was no better in terms of NO2 emissivity, but it seems that fewer particles were emitted during its two passes;


Results


The data from the NO2 measurement system were also calculated to provide NO2

concentrations based on the assumed exhaust plume width (i.e. 8cm). The average reading for each vehicle tested is given below


Results


Data were logged from the FEAT and NO2 measurement system and analysed together to provide results for HC, CO and NO2 in terms of percentage ratio with CO2 for each vehicle tested

NO2 emission factors can then be derived


Conclusions

Unequivocal detection of NO2, identified by its unique spectral signature as demonstrated clearly in this presentation against data reported in the literature.

Demonstrating from laboratory tests that the sensitivity level required for the project has been achieved

Controlled field trials that have demonstrated real world detection of NO2 using the optical sensor alongside the existing proven FEAT technology from a range of different moving vehicles

Integration of fast response (40Hz) DOAS NO2 measurements with those from the FEAT system enabling NO2 emission factors to be derived for a range of vehicles

Demonstrates the DfT’s priorities to better characterise emissions from vehicles in real-time and goes a step further in developing a measurement system that has the potential to better characterise the primary NO2 fraction from vehicle exhausts.


Applications

There are a number of potential applications;

Identifying high emitters on the road so that they can be rectified

Apportionment of the NO2 emissions to difference vehicle types (car, taxi, LGV, HGV, bus etc.) so that the higher contributors can be targeted

Checking the performance of a fleet of vehicles – e.g. bus emissions measured at the depot

Identifying new vehicle models which have suspicious NO2 emissions, which could be selected for the type approval market surveillance testing

Conducting ad hoc on-road emission testing, of fleets or individual vehicles, e.g. at ports or off slip roads

With the addition of a NO channel, the NO2 proportion of NOx (f-NO2) could be investigated at different locations


Follow on research

DfT T-TRIG Grant;

Demonstration of proof of concept of a prototype low cost optical pollution sensor

Why do we need these devices?

Because existing monitoring using real-time or passive methods are often not sufficient to adequately assess emission impacts and existing optical NO2

measuring devices are expensive, bulky and require mains power supplies.

The aim of the research:

Provide proof of concept of an optical measuring device that uses the same principles but is low cost, potentially smaller and battery powered.


Follow on research: challenges

The research will need to better understand;

A range of spectrum and wavelengths Attenuation of signal and frequency of data loggers Power supplies Pollutant path lengths Proportion of light detected & detectable limits

Etc.

One application: Real time AQ impact assessment


Thank you for listening

Dr Kevin Turpin

email: [email protected]

Environment

Routes to Clean Air 2016 - Dr Kevin Turpin, TRL