Current%20practice%20of%20PM-measurements,%20data%20processing,%20interpretation%20and%20visualization%20in%20Belgium

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

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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

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Contents

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

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Contents

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

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Number of PM10 and PM2.5 monitoring stations

• PM10 start measurements in 1996
• PM2.5 start measurements in 2000

PM10 (telemetric stations)(gt90 valid daily
averages)
PM2.5 (telemetric stations)(gt90 valid daily
averages)
Beside PM also BC and Black Smoke measurements
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Location of PM10 telemetric stations
PM10 monitoring stations

• Locations mostly
• Industrial
• Urban or Urban Background
• Very few rural
• and traffic stations
• (Historical reasons)

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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

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Contents

1. Choice of PM-Measurement locations
2. Calibration of PM-Measurements - equipment
3. Future technical development in the next 2-3
   years
4. Data acquisition - Handling of PM-data
5. Spatial Interpolation of PM-point data
6. 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)

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Automatic PM monitors ltgt EU reference method

• PROBLEM
• automatic monitors ltgt EU (gravimetric) reference
  method
• NO PROBLEM
• When equivalence is demonstrated

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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
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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)
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First comparative campaign (VMM) PM2.5
Higher calibration factors for PM2.5 than for
PM10 -gt higher volatile fraction Comparative
PM10 and PM2.5 measurements in Flanders
(Belgium), VMM, Period 2006 - 2007 (www.vmm.be)
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Spatial and temporal variation of calibration
factors
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Contents

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

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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

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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

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Contents

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

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Data acquisition of automatic measurements
Monitoringstation
RDRC
Regional Data Processing Centers
Every hour (26 after each hour) -gt ½ - hourly
measurements -gt FTP to IRCEL servers -gt
calculation of hourly / 8-hourly / 24-hour
averages. -gt publication real-time data maps
on websites
IRCEL
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Real-Time publication on websites - tables
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Real-Time publication on websites - maps
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Contents

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

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How to define a scientifically based methodology
for assessment of spatial representativeness?
CORINE land use map
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RIO-Corine interpolation

• 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

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RIO - Land use indicator (1)

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

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RIO - Land use indicator (2)

• 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
ltNO2gt
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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

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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 lt-gt distance
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Valdidation leaving-one-out

• Compare with standard IDW and OK

Model O3 O3 NO2 NO2 PM10 PM10
Model RMSE Bias RMSE Bias RMSE Bias
IDW 10.97 -1.70 18.17 4.74 12.12 1.70
OK 10.37 -0.44 16.85 1.45 11.65 1.22
RIO 9.56 -0.08 14.45 -0.67 9.89 0.01
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Valdidation using independent measurements
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Annual mean PM10 concentrations 2006
RIO-corine
Ordinary Kriging
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Annual average NO2 concentrations 2002
OK
RIO
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RIO-corine further developments (1)
NO2 - 4x4 km
NO2 - 1x1 km
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RIO-corine further developments (2)
New proxy AOD (aerosol optical Depth) ?
Total Column AOD 2006
Source Modis Terra satelite, 2006
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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
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Contents

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

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Goal of Air Quality forecasts ?

• Information of the public (see ozone EU
  info/alert thresholds)
• Activation winter SMOG action plans
  (FORECASTED PM10 gt 70 µg/m³, for two consecutive
  days)

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Two different types of models

• Deterministic models
• Complex input
• meteo, emissions, geografical information,
  fysico-chemical processes
• Long CPU
• -gt CHIMERE (forecasts) / BelEUROS (emission
  scenarios)
• Statistical or neural-network models
• Simple input
• database with measurements, some simple
  forecasted meteo parameters
• Short CPU (minutes)
• -gt SMOGSTOP (Ozone) / OVL (PM10, NO2)

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CHIMERE simple schematic overview
ExampleTemperature
NOx emissionscombustion
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CHIMERE Example (1)
Forecast for 21/6/2005
Observations 21/6/2005
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CHIMERE Example (2)
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OVL schematically

• PM10 measurements day-1
• Meteo forecasts

Input
Neural Network
Process
Output
PM10 daily mean day0, 1, 2, 3 and 4
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OVL most important meteo-input parameter
Temperature Inversion
Boundary Layer Height
Low windspeeds
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OVL PM10 winter/spring 2005forecast day 1
R0.7
Antwerp (monitoring station 42R801)
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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

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CHIMERE OVL advantages and disadvantages
CHIMERE
OVL

• Physics, chemistry and emissions taken into
  account
• Possible grid refinement
• Satisfying results at the scale of Belgian
  Regions
• Representation of hourly concentrations

• Based on dispersion in the atmosphere (BLH)
• Results available for specific location
• Satisfying results at local scale
• Adaptability to current emission level
• Reduced computing time

• Computing time increases with resolution
• High dependence on emission inventories ( link
  with long-range transport)
• Formation of secondary PM

• Forecast available only at measurement stations
  (time series)
• Long-range transport not taken into account
• Formation of secondary PM

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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