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Current practice of PM-measurements, data processing, interpretation and visualization in Belgium

Current practice of PM-measurements, data processing, interpretation and visualization in Belgium. Frans Fierens scientific staff member of the Flemish Environment Agency (VMM) at the Belgian Interregional Environment Agency (IRCEL) PM_lab workshop, 2010 March 4. IRCEL-CELINE ?.

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Current practice of PM-measurements, data processing, interpretation and visualization in Belgium

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  1. Current practice of PM-measurements, data processing, interpretation and visualization in Belgium Frans Fierensscientific staff member of the Flemish Environment Agency (VMM) at the Belgian Interregional Environment Agency (IRCEL) PM_lab workshop, 2010 March 4

  2. IRCEL-CELINE ? NL : Intergewestelijke Cel voor het Leefmilieu FR : Cellule Interrégionale de l'Environnement EN : Belgian Interregional Environment Agency Agreement between the 3 Belgian Regions (1994) • Major tasks : • SMOG (winter/summer) warnings (IDPC) • Interregional Calibration Bench • Interregional AQ Database (3 Regions) • Scientific support • Reports EU-COM / Experts EU-working groups

  3. Contents • Choice of PM-Measurement locations • Calibration of PM-Measurements - equipment • Future technical development in the next 2-3 years • Data acquisition - Handling of PM-data • Spatial Interpolation of PM-point data • Forecast Modelling (deterministic / statistical models).

  4. Contents Choice of PM-Measurement locations Calibration of PM-Measurements - equipment Future technical development in the next 2-3 years Data acquisition - Handling of PM-data Spatial Interpolation of PM-point data Forecast Modelling (deterministic / statistical models).

  5. Number of PM10 and PM2.5 monitoring stations • PM10 : start measurements in 1996 • PM2.5 : start measurements in 2000 PM10 (telemetric stations)(>90% valid daily averages) PM2.5 (telemetric stations)(>90% valid daily averages) Beside PM : also BC and Black Smoke measurements

  6. Location of PM10 telemetric stations PM10 : monitoring stations • Locations mostly : • Industrial • Urban or Urban Background • Very few “rural” • and “traffic” stations • (Historical reasons)

  7. Location of PM2.5 telemetric stations PM2.5 : monitoring stations • Locations mostly : • Industrial • (Sub) Urban • Very few “rural” • and “traffic” • “AEI stations” : • Bruges(*) • Ghent (*) • Antwerp : 2 (*) • Brussels : 2 • Liège • Charleroi • (*) not on the map

  8. Contents Choice of PM-Measurement locations Calibration of PM-Measurements - equipment Future technical development in the next 2-3 years Data acquisition - Handling of PM-data Spatial Interpolation of PM-point data Forecast Modelling (deterministic / statistical models).

  9. PM measuring techniques in Belgium • Flanders - Oscillating Micro Balans (TEOM and TEOM-FDMS) • Bèta Absorption (ESM FH62I-R) • Gravimetric : • Equivalence tests • PM2.5 (to calculate the Average Exposure Index “AEI” on urban-background locations, started in 2009) + 1 Rural background location • Brussels- Oscillating Micro Balans (only TEOM-FDMS since 2004-2005) • Wallonia- Bèta Absorption (MP101 integration time 24h)- Optical techniques (GRIMM)

  10. Automatic PM monitors <> EU reference method PROBLEM : automatic monitors <> EU (gravimetric) reference method NO PROBLEM : When “equivalence” is demonstrated

  11. Current “calibration”of PM in Belgium (*) based on the ‘guide for the demonstration of equivalence of ambient air monitoring methods’ (Excel templates from the JRC) (**) preliminary results of an equivalence program in Wallonia result in somewhat higher calibration factors

  12. New comparative campaign (VMM) : PM10 “calibration” factors calculated in new campaign are slightly higher than previously “Comparative PM10 and PM2.5 measurements in Flanders (Belgium)”, VMM, Period 2006 - 2007 (www.vmm.be)

  13. First comparative campaign (VMM) : PM2.5 Higher “calibration” factors for PM2.5 than for PM10 -> higher volatile fraction “Comparative PM10 and PM2.5 measurements in Flanders (Belgium)”, VMM, Period 2006 - 2007 (www.vmm.be)

  14. Spatial and temporal variation of calibration factors

  15. Contents Choice of PM-Measurement locations Calibration of PM-Measurements - equipment Future technical development in the next 2-3 years Data acquisition - Handling of PM-data Spatial Interpolation of PM-point data Forecast Modelling (deterministic / statistical models).

  16. Future technical development in the next 2-3 years (1) • Flanders : • - More “Chemkar” campaigns ( PM10 “hotspots”,Rural • vs Urban PM10 & PM2.5, Antwerp harbour, …) • - Measuring the effect of Woodburning on PM (levoglucosan) • Additional measuring stations (e.g. Streetcanyon NO2/PM)- Testing of new Bèta-monitors (BAM1020, FAI SWAM 5DC) • UFP measurements (streets) • Further participating in CEN/TC264/WG15 : • * revision of the PM10 standard EN12341 • * revision of the PM2.5 standard EN14907

  17. Future technical development in the next 2-3 years (2) • Brussels : • - “Black Carbon” measurements • - “Counting Particles” (using GRIMM monitors) • Wallonia : • additional measuring stations (e.g. Tournai, Namur) • EC/OC analyser at Vielsalm (Rural background) • Interregional (IRCEL-CELINE) : • further developing Interpolation techniques (eg. use of satellite observations like AOD)- higher spatial resolution modelling • (forecasts + assessment)- implementation of data assessment techniques

  18. Contents Choice of PM-Measurement locations Calibration of PM-Measurements - equipment Future technical development in the next 2-3 years Data acquisition - Handling of PM-data Spatial Interpolation of PM-point data Forecast Modelling (deterministic / statistical models).

  19. Data acquisition of automatic measurements Monitoringstation RDRC “Regional Data Processing Centers” Every hour (26’ after each hour) -> ½ - hourly measurements -> FTP to IRCEL servers -> calculation of hourly / 8-hourly / 24-hour averages. -> publication real-time data + maps on websites IRCEL

  20. “Real-Time” publication on websites - tables

  21. “Real-Time” publication on websites - maps

  22. Contents Choice of PM-Measurement locations Calibration of PM-Measurements - equipment Future technical development in the next 2-3 years Data acquisition - Handling of PM-data Spatial Interpolation of PM-point data Forecast Modelling (deterministic / statistical models).

  23. How to define a scientifically based methodology for assessment of spatial representativeness? CORINE land use map

  24. RIO-Corine interpolation VITO + IRCEL developed the RIO-corine methodology • Observation: • Sampling values depend on land use in (direct) vicinity of the monitoring site • Consequence: • Interpolation scheme needs to know this relation between land use and air quality levels • Approach : • Create land use indicator to express this relation

  25. RIO - Land use indicator (1) 2 km • Land use indicator • For each station: • Determine buffer (e.g. 2km radius) • Characterize land use by CORINE class distribution inside buffer

  26. RIO - Land use indicator (2) <PM10> Land use indicator is based on CORINE class distribution Calibration of coefficients ai : multi-regression to optimize trend for mean and standard dev. of monitoring data <NO2>

  27. Kriging interpolation of “detrended” data ‘Kriging’ condition = ‘spatialy’ homogeneous data Use relation between land use indicator and AQ statistics to “detrend” monitoring data: Remove local character of sampling values

  28. RIO-corine methodology • Detrend sampling values • Interpolate detrended values with Ordinary Kriging • Determine local b-value • Get corresponding trend shift (DC) • Add DC to interpolation result Correlation <-> distance

  29. Valdidation – “leaving-one-out” Compare with standard IDW and OK

  30. Valdidation – using “independent” measurements R² = 0.90MAE = 2.9 µg/m³ RMS = 4.3 µg/m³ Average observations : 30.6 µg/m³ Average RIO-c interpolation : 31.5 µg/m³

  31. Annual mean PM10 concentrations 2006 RIO-corine Ordinary Kriging

  32. Annual average NO2 concentrations 2002 OK RIO

  33. RIO-corine : further developments (1) NO2 - 4x4 km NO2 - 1x1 km

  34. RIO-corine : further developments (2) New proxy : AOD (aerosol optical Depth) ? Total Column AOD 2006 Source : Modis Terra satelite, 2006

  35. RIO-corine : more info “Spatial interpolation of air pollution measurements using CORINE  landcover data ” Janssen Stijna, Dumont Gerwinb, Fierens Fransb, Mensink Clemensa aFlemish Institute for Technological Research (VITO),Boeretang 200, B-2400 Mol, Belgium bBelgian Interregional Cell Environment Agency(IRCEL), Kunstlaan 10-11, B-1210 Brussels, Belgium Atmospheric Environment 42/20 (2008) 4884-4903

  36. Contents Choice of PM-Measurement locations Calibration of PM-Measurements - equipment Future technical development in the next 2-3 years Data acquisition - Handling of PM-data Spatial Interpolation of PM-point data Forecast Modelling (deterministic / statistical models).

  37. Goal of Air Quality forecasts ? Polluant : PM10 Plan : 1 niveau Flanders Brussels Wallonia Polluants : PM10 et NO2 Plan : 3 niveaux Polluant : PM10 Plan : 3 niveaux • Information of the public (see ozone EU info/alert thresholds) • Activation winter SMOG action plans (FORECASTED PM10 > 70 µg/m³, for two consecutive days)

  38. Two different types of models • Deterministicmodels • Complex input : meteo, emissions, geograficalinformation, fysico-chemical processes • Long CPU -> CHIMERE (forecasts) / BelEUROS (emission scenario’s) • Statistical or neural-network models • Simple input : database with measurements, some simple forecasted meteo parameters • Short CPU (minutes) ->SMOGSTOP (Ozone) / OVL (PM10, NO2)

  39. CHIMERE : simple schematic overview ExampleTemperature NOx emissionscombustion

  40. CHIMERE – Example (1) Forecast for 21/6/2005 Observations 21/6/2005

  41. CHIMERE – Example (2)

  42. OVL : schematically • PM10 measurements day-1 • Meteo forecasts Input: Neural Network Process: Output : PM10 daily mean day0, +1, +2, +3 and +4

  43. OVL : most important meteo-input parameter Temperature Inversion Boundary Layer Height Low windspeeds

  44. OVL : PM10 – winter/spring 2005forecast day +1 R=0.7 Antwerp (monitoring station 42R801)

  45. OVL : more info “A neural network forecast for daily average PM10 concentrations in Belgium” Hooyberghs Jefa, Mensink Clemensa, Dumont Gerwinb, Fierens Fransb, Brasseur Olivierc aFlemish Institute for Technological Research (VITO),Boeretang 200, B-2400 Mol, Belgium bInterregional Cell for the Environment (IRCEL), Kunstlaan 10-11, B-1210 Brussels, Belgium cRoyal Meteorological Institute (RMI), Ringlaan 3, B-1180 Brussels, Belgium Atmospheric Environment 39/18 (2005) 3279-3289

  46. Dank voor uw aandacht !Je vous remercie de votre attention !Wir danken Ihnen für Ihre Aufmerksamkeit !Thank you for your attention ! More info :www.ircel.bewww.vmm.be

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