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[email protected] Low - cost sensor platforms: an emerging tool for air quality studies Lekan Popoola Department of Chemistry University of Cambridge
Low-cost sensor platforms: an emerging tool for air quality studies
Lekan Popoola
Department of Chemistry
University of Cambridge
Outline of Presentation
• Low-cost sensors
– Philosophy of approach
• Examples of ambient low-cost AQ network deployments
– SNAQ London Heathrow airport project
– Air Pollution and Human Health (APHH) Beijing project
– Breathe London (BL) project
• Conclusions
Use of sensor network…..
Sensors have very good
correspondence with conventional
instruments
unique emission patterns
linked to airport
operations
• Gas species (CO, NO, NO2, OX,
SO2, TVOCs & CO2)
• Size speciated PM (0.38 – 17.4µ)
• Temperature, RH, wind speed
and direction
• All 20s data
Combine with meteorology: source apportionment
N
Sensor nodes
Runway
Categorise by
wind speed and
direction
Perimeter road
Traffic source
(perimeter road)
Aircraft source
(runway)
(© OpenAir!)
Use network to separate local and non-local sources
source location
Network – all sensors
(non-local)
CO2
Single sensor
(local only)
Single sensor
(local + non-local)
CO2
CO NO NO2 CO2
Characterisation of pollution sources
Local (single SNAQ node)
NO
2(p
pb
)
Baseline: NO2 only (network response): easterly direction
Features
• London plume
• Road traffic
diurnal profile
diurnal
Pollution predominantly from long range transport (road traffic)
Pollution from
easterly directionRoad traffic
diurnal pattern
Observational constraint of model emission indices:
ADMS (model) SNAQ (measurements)
CO NO
NO2
ADMS
model
(CERC)Δspecies
ΔCO2
Very good
agreement between
observation and
model at different
receptor points
• × 25 deployed in Beijing
✓ × 6 (8, 32, 100, 160, 260, 320 m )
on IAP meteorology tower
✓ × 18 as a network in the city
✓ × 1 co-located with York container
• × 4 in Pinggu (rural location)
SNAQ deployment details
8 m
32 m
102 m
160 m
260 m
320 m
summerwinter
Winter – Summer Contrast
⇒ Winter dominated by elevated CO, NOX, PM (BL stability and
long-range transport) & lower OX (chemistry)
⇒ Summer characterised by higher OX (chemistry dominated)
and lower CO, PM, NOX (unstable BL)
Breathe London project
https://www.breathelondon.org
Breathe London static sensor network
https://www.breathelondon.org
100+ AQMesh
pods NO2, NO,
CO2, (O3), PM
Key differences:
• 1 min data (mostly!)
• CO2 measurements
Not reference!
Diurnals (average and day-of-week) and mean (day of week and monthly) profiles for absolute NOX
AQMesh vs. LAQN & AQE network: April – December 2019
AQMesh network (88 nodes)
AQE network (50 stations)
LAQN network (86 stations)
AQE
LAQN
AQMesh
vs.
Emission ratio determination
NO2 (NOx) CO2
Scale separated NO2, NO
and CO2
Extract local NOx, CO2
Take point by point ratio
(1 min)
Derive ERNOx(t, x, y)
Gradient is
emission ratio
Scale separation now allows local emission ratios to be derived:
All 88 sitesUrban background
Kerbside & roadside
Kerbside
Roadside
ULEZ (× 22)
Non-ULEZ (× 66)
ULEZ (× 7)
Non-ULEZ (× 25)
ULEZ (× 15)
Non-ULEZ (× 41)
ULEZ (× 6)
Non-ULEZ (× 23)
ULEZ (× 9)
Non-ULEZ (× 18)
All sites partition by
ULEZ and non-ULEZ
Disaggregation of NOx emission ratios
UK Lock down impacts: NO2?
Model (ADMS) vs Observations (LAQN & BL)
Lockdown
NO
2(µ
g/m
3)
LAQN network average
BL network average
ADMS model (BL network)
• A reduction in road traffic NOX emissions to around 10-20% of pre-lockdown levels.
• Modelled as ~ 86% reduction in mean traffic emission compared to pre-lockdown
Evaluation of UK lockdown using data assimilation into ADMS model
Summary
❑ low-cost sensor technology for air pollution, viable for……..
• both in developed and low-income countries.
• personal exposure studies.
❑ applications
• Source apportionment
• Emission ratios
• assimilation of sensor network data for improved modelling
Already adding value……..
Thank you for your attention
Contributing partners
Lekan Popoola, Geoff Ma, Le Yuan, Vivien Bright , Iq Mead, Lia Chatzidiakou, Ray Freshwater, and Rod Jones
(Cambridge team)
David Carruthers , Chetan Lad, Amy Stidworthy, Ella Forsyth and Mark Jackson (CERC team)
Ramon Alvarez, Dan Peters, Megan Dupuy-Todd, Elizabeth Fonseca (EDF Team)
Jim Mills, Felicity Sharp (ACOEM /Air Monitors)
Nick Martin (National Physical Laboratory)
Spencer Thomas, Luke Cox, David Vowles (HAL/BAA, BA for airport logistics)
Paul Kaye (and University of Hertfordshire team)
John Saffell (Alphasense, UK)
