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 ?
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
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).
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).
Number of PM10 and PM2.5 monitoring stations
60
60
50
50
40
40
Wallonia
30
Brussels
Flanders
20
# PM2.5 stations
# PM10 stations
• PM10 : start measurements in 1996
• PM2.5 : start measurements in 2000
30
20
10
10
0
0
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
PM10 (telemetric stations)
PM2.5 (telemetric stations)
(>90% valid daily averages)
(>90% valid daily averages)
Beside PM : also BC and Black Smoke measurements
Location of PM10 telemetric stations
PM10 : monitoring stations
Locations mostly :
- Industrial
- Urban or Urban
Background
Very few “rural”
and “traffic” stations
(Historical reasons)
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
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).
PM measuring techniques in Belgium
1. 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 urbanbackground locations, started in 2009) + 1 Rural background
location
2. Brussels
- Oscillating Micro Balans (only TEOM-FDMS since 2004-2005)
3. Wallonia
- Bèta Absorption (MP101 integration time 24h)
- Optical techniques (GRIMM)
Automatic PM monitors <> EU reference method
PROBLEM :
automatic monitors <> EU (gravimetric) reference method
NO PROBLEM :
When “equivalence” is demonstrated
Current “calibration” of PM in Belgium
PM10
ESM
TEOM
TEOM-FDMS
GRIMM
currently used calibration factors
1.37
1.47
1
1
Equivalence after "correction" (*)
yes
yes
yes
yes (**)
PM2.5
ESM
TEOM
TEOM-FDMS
GRIMM
currently used calibration factors
1.46
1.75
1
0.85
Equivalence after "correction" (*)
yes
yes
yes
yes (**)
(*) 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
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)
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)
Spatial and temporal variation of
calibration factors
Contents
1. Choice of PM-Measurement locations
2. Calibration of PM-Measurements - equipment
3. Future technical development in the next 23 years
4. Data acquisition - Handling of PM-data
5. Spatial Interpolation of PM-point data
6. Forecast Modelling (deterministic / statistical
models).
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
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
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).
Data acquisition of automatic measurements
Monitoring
station
RDRC
“Regional Data Processing Centers”
Every hour (26’ after each hour)
-> ½ - hourly measurements
IRCEL
-> FTP to IRCEL servers
-> calculation of hourly / 8-hourly / 24-hour
averages.
-> publication real-time data + maps on
websites
“Real-Time” publication on websites - tables
“Real-Time” publication on websites - maps
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).
How to define a scientifically based methodology
for assessment of spatial representativeness?
CORINE land use map
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
VITO + IRCEL developed the
RIO-corine methodology
RIO - Land use indicator (1)
Land use indicator
43R240
2 km
400
42N016
43N073
350
43R240
300
Number of grid cells in buffer
For each station:
 Determine buffer
(e.g. 2km radius)
 Characterize land
use by CORINE class
distribution inside
buffer
250
200
150
100
50
0
0
5
10
15
20
CORINE Class
25
30
35
40
RIO - Land use indicator (2)
Land use indicator is based on CORINE class
distribution
week
60
rural
55
urb back
urb
50
ind
traff

 CORINE  log 1   ai .nCORINE class i 

i

CORINE class i 

n
i
 PM 10  [  g/m 3 ]
45
40
35
30
25
<PM10>
20
10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
1.1

week
140
rural
urb back
120
urb
ind
traff
100
3
 NO 2  [  g/m ]
Calibration of coefficients ai :
multi-regression to optimize
trend for mean and
standard dev. of monitoring
data
15
80
60
40
<NO2>
20
0
0
0.5
1

1.5
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
90
80
70
 C  [µg/m³]
60
C
50
40
30
20
10
0
0
0.2
0.4
0.6
0.8

1
1.2
1.4
RIO-corine methodology
Correlation <-> distance
(1) Kriging map
(2) DC map
90
80
Legend
delta C [µg/m³]
Legend
Kriging [µg/m³]
70
60
 C  [µg/m³]
1. Detrend sampling
values
2. Interpolate
detrended values
with Ordinary Kriging
3. Determine local value
4. Get corresponding
trend shift (C)
5. Add C to
interpolation result
C
50
40
78 - 85
-4 - 0
86 - 87
1 - 21
88 - 90
22 - 27
91 - 95
28 - 33
96 - 99
34 - 39
100 - 109
40 - 52
(3) RIO map
30
20
10
Legend
RIO map [µg/m³]
0
0
0.2
0.4
0.6
0.8

1
1.2
1.4
34 - 43
44 - 52
53 - 61
62 - 68
69 - 75
76 - 126
Valdidation – “leaving-one-out”
Compare with standard IDW and OK
Model
O3
RMS
E
Bias
NO2
PM10
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
14.45
-0.67
9.89
0.01
-0.08
Valdidation – using “independent” measurements
R² = 0.90
MAE = 2.9 µg/m³
RMS = 4.3 µg/m³
90
observations
80
RIO-corine interpolated
70
60
50
40
30
20
10
Average observations
: 30.6 µg/m³
Average RIO-c interpolation : 31.5 µg/m³
20050110
20050105
20041231
20041226
20041221
20041216
20041211
20041206
20041201
20041126
20040726
20040721
20040716
20040711
20040706
20040701
20040626
0
Annual mean PM10 concentrations 2006
Ordinary Kriging
RIO-corine
Annual average NO2 concentrations 2002
OK
Legend
NO2 [µg/m³]
RIO
Legend
NO2 [µg/m³]
error
error
1 - 10
1 - 10
11 - 12
11 - 12
13 - 14
13 - 14
15 - 17
15 - 17
18 - 20
18 - 20
21 - 23
21 - 23
24 - 26
24 - 26
27 - 29
27 - 29
30 - 33
30 - 33
> 33
> 33
RIO-corine : further developments (1)
NO2 - 4x4 km
Legend
NO2 [µg/m³]
error
< 10
11 - 12
13 - 14
15 - 17
18 - 20
21 - 23
24 - 26
27 - 29
30 - 33
> 33
NO2 - 1x1 km
RIO-corine : further developments (2)
New proxy :
AOD (aerosol optical Depth) ?
Total Column
AOD 2006
Source : Modis Terra satelite, 2006
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
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).
Goal of Air Quality forecasts ?
- Information of the public (see ozone EU info/alert thresholds)
- Activation winter SMOG action plans
Polluant : PM10
(FORECASTED PM10 > 70 µg/m³, for twoPlan
consecutive
: 1 niveau days)
Flanders
Brussels
Wallonia
Polluants : PM10 et NO2
Plan : 3 niveaux
Polluant : PM10
Plan : 3 niveaux
Two different types of models
1.
Deterministic models
• Complex input :
meteo, emissions, geografical information, fysicochemical processes
• Long CPU
-> CHIMERE (forecasts) / BelEUROS (emission
scenario’s)
2.
Statistical or neural-network models
• Simple input :
database with measurements, some simple
forecasted meteo parameters
• Short CPU (minutes)
-> SMOGSTOP (Ozone) / OVL (PM10, NO2)
CHIMERE : simple schematic
overview
Example
Temperature
NOx emissions
combustion
CHIMERE – Example (1)
Forecast for 21/6/2005
Observations 21/6/2005
CHIMERE – Example (2)
OVL : schematically
Input:
•PM10
measurements day-1
•Meteo
forecasts
Neural
Process:
Output :
Network
PM10
daily mean day0,
+1, +2, +3 and +4
OVL : most important meteo-input
parameter
Temperature Inversion
Boundary Layer Height
Low windspeeds
OVL : PM10 – winter/spring 2005
forecast day +1
140
R=0.7
metingen
OVL model
120
100
µg/m³
80
60
40
20
0
01/01/05
01/02/05
Antwerp (monitoring station 42R801)
01/03/05
01/04/05
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
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.be
www.vmm.be