Mikrosensorer - oppsummering av NILUs seminar

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1 Mikrosensorer - oppsummering av NILUs seminar Muligheter utfordringer veien videre Núria Castell Franck René Dauge Philipp Schneider Alena Bartonova og Matthias Vogt, William Lahoz, Kerstin Stebel, and the entire CITI-SENSE team

2 Innhold 1. Bakgrunn 2. Hva er status for mikrosensor-teknologien i dag? 3. Bruk av mikrosensorer til å generere høyoppløselige luftkvalitetskart 4. Oppsummering

3 Forskningsarbeid EU: FP7 CITI-SENSE EMIIA II CITI-SENSE-MOB FP6 MEMORI COST actions, AQUILA, CEN Forskningsrådet: INNOSENSE Annet: CrowdAir

4 CITI-SENSE in 9 European cities, Ostrava Edinburgh Haifa Oslo Vienna FP7 grant no Vitoria Gasteiz Belgrade Ljubljana Barcelona

5 3 universities 7 secondary schools 17 elementary schools 54 kindergartens 9 tennants associations 9 cities >1.200 CityAir-app-users 2036 reported perceptions, app still running! 334 air sensor units in network at >50 public places volunteers one time Additional sensor clusters CITI- SENSE i EUROPA 9,4 million observations (9/ ) 327 LEOvolunteers 1530 answers to AQ questionnaire >300 evaluations of products FP7 grant no

6 Traditional Air Quality Monitoring Is there another way? Large Complex High-maintenance Expensive Very sparse Bidgee

7 There might be

8 Opportunities Supplement routine ambient air monitoring networks Monitor personal exposure Monitoring at the source and where people is affected Stimulate citizen participation and increase awareness

9 Air Patrol and Flow by Plume labs No information about the performance

10 Airbeam No information about the performance in their website but independent field calibration by AQMD

11 Low-cost sensor platforms are available to the public but information about performance is lacking

12 The AQMesh platform v3.5 Information extracted from AQMesh documentation in CITI-SENSE project Environmental Instruments Ltd, UK, Can we reproduce those values?

13 Can we use low-cost nodes for air quality management?

14 Laboratory evaluation: set-up CEN Gas analyzers Low-cost nodes Gas CO NO 2 NO O 3 Sensor type Electrochemical CO-B4 Electrochemical NO2-B42F Electrochemical NO-B4 Electrochemical OX-B421 Gas Analyzer CO Teledyne API 300E (EN14626) NO x Teledyne API 200A (EN 14211) O 3 Teledyne API 400 (EN 14625) Performance of the sensor nodes against traceable gas standards under reproducible and accurately controlled ambient conditions. Two sensor nodes: and was tested after 3 months of field deployment.

15 Laboratory evaluation: results Cross-sensitivity: NO 2 (Low-High) LOD: 1.8 ppb Cross-sensitivity: No LOD: 2.7 ppb Cross-sensitivity: No LOD: 2.4 ppb Cross-sensitivity: No LOD: 21 ppb

16 Field evaluation: set-up Gas CO NO 2 NO O 3 Sensor type Electrochemical CO-B4 Electrochemical NO2-B42F Electrochemical NO-B4 Electrochemical OX-B421 Performance of the sensor nodes when exposed to a range of different environmental conditions (e.g. weather, traffic). Gas Analyzer CO EC Serinus 30 (EN14626) NO x EC Serinus 40 (EN 14211) O 3 Teledyne API 400 (EN 14625) 13 th April 24 th June 2015: 24 AQMesh nodes at Kirkeveien AQM 1 st July 22 nd September 2015: Kirkeveien (10 nodes), Manglerud (4 nodes), Åkebergveien (5 nodes) and Alnabru (4 nodes)

17 Field evaluation results: calibration Low accuracy Low precision Good accuracy Good precision Low accuracy Low precision CO NO NO 2 O 3 Low accuracy Good precision A good performance in the laboratory is not indicative of a good performance in field. Correlations significantly lower in the field than in the laboratory. Necessary to calibrate the sensors in the field. The results show that even for identical sensors and platform, the performance can vary sensor to sensor. Challenge in ensuring sensor measurement repeatability.

18 NO, node Field evaluation results: long-term performance Clear change in the behaviour during the 6 months co-location period due to varying weather conditions and atmospheric concentrations. The variation in the calibration parameters month to month can be significant. This can lead to increased errors and biases that can pass unnoticed once the nodes are deployed in the field.

19 Field evaluation results: dependence on meteorological conditions The response of each sensor to weather conditions is unique, and it is necessary to evaluate each sensor individually. We can have false increases in concentrations due to changes in temperature.

20 Field evaluation results: dependence on the location Node CO NO NO 2 O 3 PM 10 PM 2.5 Coef. determination (r 2 ) Lab Coef. determination (r 2 ) Field (dense traffic) Coef. determination (r 2 ) Field (calm traffic) Slope Lab Slope Field (dense traffic) Slope Field (calm traffic) Intercept Lab Intercept Field (dense traffic) Intercept Field (calm traffic) The linear calibration parameters are different when the node is located in a traffic-saturated environment or at a traffic-calm environment. It is important to calibrate the nodes in an environment similar to the one in which they would be deployed (or better, to perform in-situ calibration at the deployment site).

21 The CleanAIR project: AirSensEUR A multi-sensor platform designed for the monitoring of air pollution at low concentration levels. Completely open platform (both hardware and software) Designed/developed by JRC in Ispra Three AirSensEUR units tested as part of the CleanAir project with Telia and Oslo Kommune Calibration methodology developed inhouse at NILU (multiple linear regression and neural networks tested) Field calibration for NO 2 carried out at Kirkeveien station AirSensEUR unit with Teflon enclosure Co-location at Kirkeveien station

22 First results for NO 2 look promising

23 First results for NO 2 look promising Three AirSensEUR units (P1, P2, and P3) have been co-located at Kirkeveien during February and March R 2 values are consistently around 0.8 and higher.

24 Eksempel på anvendelse - høyoppløslige luftkvalitetskart

25 ? Red markers: Locations of Air Quality Monitoring stations for NO 2 Blue markers: Deployment sites of low-cost microsensors

26 Note: The sensors used here were all colocated for several weeks at the Kirkeveien AQ monitoring station before deployment and are thus field-calibrated! Oslo NO 2 model-derived annual average basemap (background) and observations from AQMesh nodes (markers) on 6 January 2016 at 9:00 UTC. Units in µg/m 3. Result of data fusion process (background) and observations from AQMesh nodes (markers). Units in µg/m 3.

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28 Example of 24 hours of data fusion results in Oslo, combining NO 2 measurements from the AQMesh units with a longterm average basemap derived from the EPISODE model, here shown for 6 January 2016

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30 Hva har vi lært? Gode resultater på lab er ingen garanti for god ytelse i felt Kalibrering av mikrosensor-plattformene reduserer usikkerhetene i dataene, men Kalibrering i lab er ikke tilstrekkelig Kalibrering i felt er helt nødvendig Høy variabilitet i ytelse fra en sensorenhet til en annen Ikke tilstrekkelig å teste bare en sensor Individuell kalibrering av sensorene er nødvendig Egenskapene til mikrosensorene endrer seg mye over tid (ikke-lineær drift)

31 Hva har vi lært? Kvaliteten på dataene er i dag ikke god nok til å benyttes i regelverksammenheng (over/under grenseverdiene), men kan gi en grov indikasjon om forurensningsnivå for enkelte komponenter Etter dataprosessering kan man få ut nyttig informasjon og i kombinasjon med andre data, kan man generere detaljerte luftkvalitetskart Mangelfull dokumentasjon fra produsenter av mikrosensor plattformer Viktig å håndtere forventninger hos brukere

32 Veien videre Behov for mer avanserte kalibreringsmetoder som tar høyde for interferens med temperatur, relativ fuktighet og andre gasser Behov for en felles standard for hvordan man skal evaluere ytelsen til mikrosensorer Produsentene må utarbeide bedre teknisk dokumentasjon Data fra et nettverk av sensorer kan, hvis det kombineres med andre data fra f.eks. spredningsmodeller, gi nyttig informasjon til brukere - MEN det er viktig å sikre god kvalitet på sensordataene Brukere, produsenter og forskere trenger å samarbeide for å utvikle nye generasjoner av rimelige mikrosensor-plattformer

33 Takk for oppmerksomheten! For mer informasjon: