SlideShare a Scribd company logo
Hyperlocal Air Quality Monitoring Network
Jim Mills – Managing Director – Air Monitors Ltd
Breathe London - in 3 parts
MOBILE
AREA
COVERAGE
WEARABLES
REAL LIFE
EXPOSURE
STATIC
TEMPORAL
RESOLUTION
Courtesy - Dr Ben Barratt (Kings College London)
Google
Street View Cars
• High accuracy and precision data,
due to reference grade
instrumentation used
• Provide excellent spatial coverage of
the city
• Identify “hot spots” of high pollution
• where pods can then be located
to provide additional temporal
data
Google Cars
Instrumentation
• Data is collected from
each instrument every
second and sent via cellular
networks to the cloud. It is
then available to the
project partners in near
real time for processing,
analysis and visualisation.
Google Cars
Measurements
• Measuring NO, NO2, O3, CO2, PM10, PM2.5,
PM1, Pn, Nano Particles (LDSA) & Black
Carbon…plus GPS, T, H & P
• Measurement recorded every second
• (A measurement every 10-30m at city speeds)
• Cars run 24/7 and are garaged at NPL,
Teddington where they are checked and
calibrated every week
Google Cars Parked at NPL Teddington
Courtesy of Dr Nick Martin, Stefan Bell and Joe Hayward (NPL)
Google Street View Car – 1 second data output
Courtesy – Prof R L Jones (University of Cambridge)
Typical AQMesh Pod Installation Blackfriars Road London
Over 100 Devices across London - Data available on web application
Drill down to data & street view of location
Calibration
QA/QC
Network
Management
Each individual sensor is calibrated in the lab using dry gases at
high concentrations
Each pod (family of sensors) is calibrated for at least one week
against reference monitors in ambient air before shipping
Pods are compared against each other at reference sites in the
city to ensure agreement with each other and the reference
Offset and slopes adjusted (if required) after regression analysis
Pods deployed at their network monitoring locations across the
city
One pod at each reference location held back and designated
“Gold” (transfer standard)
Gold pods are then used for co-location studies at several pod
network sites to re-verify candidate pods over time.
BIG DATA analysis techniques used to identify possible outliers
which are then investigated further by the field team
NO Pods
without
scaling at 3
LAQN sites
Courtesy of Amy Stidworthy (CERC)
NO2 Pods
without
scaling at 3
LAQN sites
Courtesy of Amy Stidworthy (CERC)
Comparison of
Pod 99245 with
Reference at
Swiss Cottage
Camden
Courtesy of Amy Stidworthy (CERC)
Group of locations for NO2 Feb 19 (1-hour Averaged data)
Group of locations for PM2.5 Feb 19 (1-hour ave data)
Real Time Air Quality Index for Public Engagement
Interactive information on specific pollutants
100 pods = BIG DATA
• 310 electrochemical, 100 optical &
300 solid state sensors
• Approx. 50 channels of information
from each pod every minute
• 3,000 individual readings per hour
per pod
• 300,000 readings per hour across
the city
• 7,200,000 readings per day
• 2.628 BILLION readings per year
• Inform the Politicians & Public
• Engage the Politicians & Public
• Encourage Behaviour Change
• Measure effectiveness of
interventions (e.g.ULEZ)
• Drive continual improvement
in air quality in the city
• Replicate what we learn from
London in other cities
Thanks to
the GLA and
project
partners for
their support
and guidance
Thank You !
www.breathelondon.org www.airmonitors.co.uk

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The London hyperlocal air quality monitoring network - Jim Mills

  • 1. Hyperlocal Air Quality Monitoring Network Jim Mills – Managing Director – Air Monitors Ltd
  • 2. Breathe London - in 3 parts MOBILE AREA COVERAGE WEARABLES REAL LIFE EXPOSURE STATIC TEMPORAL RESOLUTION Courtesy - Dr Ben Barratt (Kings College London)
  • 3. Google Street View Cars • High accuracy and precision data, due to reference grade instrumentation used • Provide excellent spatial coverage of the city • Identify “hot spots” of high pollution • where pods can then be located to provide additional temporal data
  • 4. Google Cars Instrumentation • Data is collected from each instrument every second and sent via cellular networks to the cloud. It is then available to the project partners in near real time for processing, analysis and visualisation.
  • 5. Google Cars Measurements • Measuring NO, NO2, O3, CO2, PM10, PM2.5, PM1, Pn, Nano Particles (LDSA) & Black Carbon…plus GPS, T, H & P • Measurement recorded every second • (A measurement every 10-30m at city speeds) • Cars run 24/7 and are garaged at NPL, Teddington where they are checked and calibrated every week
  • 6. Google Cars Parked at NPL Teddington Courtesy of Dr Nick Martin, Stefan Bell and Joe Hayward (NPL)
  • 7. Google Street View Car – 1 second data output Courtesy – Prof R L Jones (University of Cambridge)
  • 8. Typical AQMesh Pod Installation Blackfriars Road London
  • 9. Over 100 Devices across London - Data available on web application
  • 10. Drill down to data & street view of location
  • 11. Calibration QA/QC Network Management Each individual sensor is calibrated in the lab using dry gases at high concentrations Each pod (family of sensors) is calibrated for at least one week against reference monitors in ambient air before shipping Pods are compared against each other at reference sites in the city to ensure agreement with each other and the reference Offset and slopes adjusted (if required) after regression analysis Pods deployed at their network monitoring locations across the city One pod at each reference location held back and designated “Gold” (transfer standard) Gold pods are then used for co-location studies at several pod network sites to re-verify candidate pods over time. BIG DATA analysis techniques used to identify possible outliers which are then investigated further by the field team
  • 12. NO Pods without scaling at 3 LAQN sites Courtesy of Amy Stidworthy (CERC)
  • 13. NO2 Pods without scaling at 3 LAQN sites Courtesy of Amy Stidworthy (CERC)
  • 14. Comparison of Pod 99245 with Reference at Swiss Cottage Camden Courtesy of Amy Stidworthy (CERC)
  • 15. Group of locations for NO2 Feb 19 (1-hour Averaged data)
  • 16. Group of locations for PM2.5 Feb 19 (1-hour ave data)
  • 17. Real Time Air Quality Index for Public Engagement
  • 18. Interactive information on specific pollutants
  • 19. 100 pods = BIG DATA • 310 electrochemical, 100 optical & 300 solid state sensors • Approx. 50 channels of information from each pod every minute • 3,000 individual readings per hour per pod • 300,000 readings per hour across the city • 7,200,000 readings per day • 2.628 BILLION readings per year
  • 20. • Inform the Politicians & Public • Engage the Politicians & Public • Encourage Behaviour Change • Measure effectiveness of interventions (e.g.ULEZ) • Drive continual improvement in air quality in the city • Replicate what we learn from London in other cities Thanks to the GLA and project partners for their support and guidance
  • 21. Thank You ! www.breathelondon.org www.airmonitors.co.uk