Table of contents

Sensor report summary

22 January 2024


Authors

Hannah Walker

Louisa Kramer

Stephen Stratton

Approved by

Brian Stacey

Customer

Internal

Compilation Date

January 22, 2024

Copyright

Ricardo Energy & Environment

EULA
http://ee.ricardo.com/cms/eula/

1 Summary

The results from the performance assessment presented here show that under the specific conditions of the test, when the data is corrected and the system evaluated under a full type test assessment the NO2 sensor may achieve Class 1 performance, the PM10 sensor may achieve Class 1 performance and the PM2.5 sensor may achieve Class 1 performance.

2 Introduction

Ricardo is undertaking an ongoing performance assessment of the SCS Cube air quality sensor system. The sensors were deployed at the Heathrow Bath Road reference monitoring site.

This report summarises the performance of the sensor systems against the reference monitoring stations. Comparison of the data is performed in three ways:

  • “Out of the box” assessment.

  • Processed sensor data (data that has been initially screened to identify and remove obvious poor quality data) followed by a correction for overall slope and offset – a QA/QC adjustment for scatter against the reference analysers.

  • Processed sensor data followed by a monthly correction for slope and offset (where data for more than a month are available) – the monthly slopes are not used to assess the final performance of the sensor, but to provide information on potential seasonal variations in the sensor sensitivity.

3 Background

Sensor systems are increasingly more widespread in use. Their small size and relatively low cost provides potential for air quality data to be collected in more locations than ever before. However, the quality of the measurements from sensors does not currently compare to measurements collected with conventional “reference grade” air pollution analysers.

A series of test regimes is in preparation to assess the data quality from sensors BS EN17660-1:2021 (gas measurements) and BS EN17660-2 (PM10/PM2.5 measurements, expected to be published in 2024), grading them from Class 1 (suitable for indicative measurements) to Class 3 (suitable only for estimation). A key aspect of the testing is co-location of the sensors at real-world monitoring locations to compare against reference analysers.

The assessment is undertaken on 1-hour averages for gases and daily averages for particles, as this is in line with what is expected to be in place for the technical specification for measurements using low cost sensors.

This report focuses on the pollutants currently of most interest in the UK: NO2, PM10 and PM2.5.

4 Analysis

For each pollutant, the data are presented as follows:

  • Timeseries plots – to examine whether the sensors follow the same trends as the reference measurements.

  • Scatter plots – to evaluate how close the sensor measurements are to the reference measurements. The scatter plots also allow a calculation of slope and offset, with respect to the reference analysers.

  • Calculated measurement uncertainty. Using approved methodologies, the measurement uncertainty of the sensors (at Limit Value concentrations) is calculated and compared to the Class system classifications. These uncertainties are summarised below.

Table 1: Class system limits of measurement uncertainty for gases and particulate matter.
Class Gases PM (proposed)
Class 1 25 50
Class 2 75 100
Class 3 200 200

At least one month of data is used for the calculations. The data are analysed as raw “out of the box” data, where the processed outputs direct from the supplier are assessed. Using the overall slope and offset calculations, the out of the box data are reprocessed and the analysis repeated, with the expectation that this QA/QC will lead to improvements in data quality.

Where multiple months of data are available, the slope and offset are calculated from out of the box data for each month and the monthly data corrected to assess potential changes in the slope with seasonal variations.

The data presented here are indicative of the field performance of the sensor for the period of evaluation. It should not be assumed that this performance would be repeated at other locations, other meteorological conditions or other periods of time. This report does not constitute a formal MCERTS test under BS EN17660. Co-location of purchased sensor systems is strongly recommended before undertaking any measurement surveys.

5 Statistical overview

Table 2: Statistical summary of all results for the corrections applied, including and excluding outliers. The “Slope range (monthly analysis)” presents the range of slopes calculated when the statistical results are determined by month.
Pollutant Variable Uncorrected Corrected
NO2 Intercept not forced 3.2 (Significant) 0 (Not Significant)
NO2 Slope not forced 0.97 (Significant) 1 (Not Significant)
NO2 Slope range (monthly analysis) 0.71 - 1.01 0.98 - 1.01
NO2 Expanded Uncertainty at Limit Value (%) 9.07 (Pass) 9.4 (Pass)
NO2 Number of measurements 6754 6754
PM10 Intercept not forced 3.9 (Significant) -0.23 (Not Significant)
PM10 Slope not forced 0.78 (Significant) 1.02 (Not Significant)
PM10 Slope range (monthly analysis) 0.58 - 1.03 0.88 - 1.06
PM10 Expanded Uncertainty at Limit Value (%) 30.13 (Pass) 11.78 (Pass)
PM10 Number of measurements 304 304
PM2.5 Intercept not forced 1.24 (Significant) -0.14 (Not Significant)
PM2.5 Slope not forced 0.74 (Significant) 1.02 (Not Significant)
PM2.5 Slope range (monthly analysis) 0.58 - 1.01 0.94 - 1.04
PM2.5 Expanded Uncertainty at Limit Value (%) 44.28 (Pass) 13.77 (Pass)
PM2.5 Number of measurements 304 304

6 Time series

The plots below show the time series of pollutant measurements from the reference instrument and the SCS Cube sensor. The relevant tabs show any corrections that have been applied to the sensor measurements, calculated using all available data. The sub-tabs indicate each pollutant.

May 2022Jul 2022Sep 2022Nov 20220102030405060
ReferenceCandidate (SCS Cube)NO​2 concentration / ppb
Mar 2022May 2022Jul 2022Sep 2022Nov 2022102030405060
ReferenceCandidate (SCS Cube)PM​10 concentration / µg m​-3
Mar 2022May 2022Jul 2022Sep 2022Nov 2022510152025303540
ReferenceCandidate (SCS Cube)PM​2.5 concentration / µg m​-3
May 2022Jul 2022Sep 2022Nov 20220102030405060
ReferenceCandidate (SCS Cube)NO​2 concentration / ppb
Mar 2022May 2022Jul 2022Sep 2022Nov 20220102030405060
ReferenceCandidate (SCS Cube)PM​10 concentration / µg m​-3
Mar 2022May 2022Jul 2022Sep 2022Nov 2022510152025303540
ReferenceCandidate (SCS Cube)PM​2.5 concentration / µg m​-3

7 Regression - All data

The plots below show a direct comparison of the measurements made by the reference instrument, compared to the SCS Cube sensor. Each tab indicates what correction has been applied to the sensor measurement, while the sub-tabs indicate each pollutant.

Black points on each plot represent a single measurement. The orange line indicates the linear regression through the points available, the linear regression equation and correlation coeffiecient (R2) for which are written above the plot. Behind the points, the blue and grey shading indicates the Class 1, Class 2 and Class 3 limits for this pollutant, respectively. The 1:1 line is indicated by the dashed line.

8 Regression - Monthly

The plots below show a direct comparison of the measurements made by the reference instrument, compared to the SCS Cube sensor for each month of the co-location period. These plots provide an indication as to whether the agreement between the reference and the sensor changes over time.

Each tab indicates what correction has been applied to the sensor measurement, while the sub-tabs indicate each pollutant. By clicking on the “Play” button the plots will cycle through each month. To view a specific month, click on the month name below the plots.

In each sub-plot, only data available for that month has been used to determine the regression. A plot label of “No data available” means no data was recorded during that month, while “Not enough data available” means there was less than 5 days of measurements available to calculate a regression.

The blue points on each plot represent a single measurement. The orange line indicates the linear regression through the points available, and the 1:1 line is indicated by the dashed black line.

0204060020406002040600204060010203040010203040
Currently showing: Mar 2022Mar 2022Apr 2022May 2022Jun 2022Jul 2022Aug 2022Sep 2022Oct 2022Nov 2022Dec 2022Reference concentrationSCS Cube concentration NO​2 (ppb)PM​10 (µg m​-3)PM​2.5 (µg m​-3)Play
0204060020406002040600204060010203040010203040
Currently showing: Mar 2022Mar 2022May 2022Jul 2022Sep 2022Nov 2022Reference concentrationSCS Cube concentration NO​2 (ppb)PM​10 (µg m​-3)PM​2.5 (µg m​-3)Play

9 Conclusions

This report summarises the SCS Cube sensor measurements of NO2, PM10 and PM2.5 during the co-location period. The estimated classification of each pollutant is calculated from all data available and detailed in the tabs below.

The percentages expressed in each table indicate the percentage of unique measurements within each class threshold. This means that all measurements within the limits of Class 1 are included in that value. The Class 2 percentage includes the measurements outside of the Class 1 limits but within Class 2, and so on for Class 3. The remaining measurements outside the Class 3 limits are given as Unclassified.

Table 3: Summary of the number of measurements in each class range.
Correction level Class 1 Class 2 Class 3 Unclassified
Uncorrected 75.1% 21.5% 3.3% 0.2%
Corrected 82.1% 15.5% 2% 0.3%
NO2 class conclusion

The expanded uncertainty for NO2 measurements from this SCS Cube sensor is 9.4% during the co-location period. If the performance of the sensor during actual type testing matched this performance for all test parameters, the sensor would be classified as Class 1, under the specific conditions and location reported here.

Table 4: Summary of the number of measurements in each class range.
Correction level Class 1 Class 2 Class 3 Unclassified
Uncorrected 99.3% 0.3% 0.3% 0%
Corrected 100% 0% 0% 0%
PM10 class conclusion

The expanded uncertainty for PM10 measurements from this SCS Cube sensor is 11.78% during the co-location period. If the performance of the sensor during actual type testing matched this performance for all test parameters, the sensor would be classified as Class 1, under the specific conditions and location reported here.

Table 5: Summary of the number of measurements in each class range.
Correction level Class 1 Class 2 Class 3 Unclassified
Uncorrected 100% 0% 0% 0%
Corrected 100% 0% 0% 0%
PM2.5 class conclusion

The expanded uncertainty for PM2.5 measurements from this SCS Cube sensor is 13.77% during the co-location period. If the performance of the sensor during actual type testing matched this performance for all test parameters, the sensor would be classified as Class 1, under the specific conditions and location reported here.