current practice of pm-measurements, data processing, interpretation and visualization in belgium
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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 ?. - PowerPoint PPT PresentationTRANSCRIPT
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
IRCEL-CELINE ?
NL : Intergewestelijke Cel voor het LeefmilieuFR : 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
• PM10 : start measurements in 1996• PM2.5 : start measurements in 2000
PM10 (telemetric stations)(>90% valid daily averages)
0
10
20
30
40
50
60
1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
# P
M10
sta
tio
ns
Wallonia
Brussels
Flanders
0
10
20
30
40
50
60
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009#
PM
2.5
stat
ion
s
PM2.5 (telemetric stations)(>90% valid daily averages)
Beside PM : also BC and Black Smoke measurements
PM10 : monitoring stations
Location of PM10 telemetric stations
Locations mostly :- Industrial- Urban or Urban Background
Very few “rural” and “traffic” stations
(Historical reasons)
PM2.5 : monitoring stations
Location of PM2.5 telemetric 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 urban-
background 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
(*) 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
PM10 currently used calibration factors Equivalence after "correction" (*)ESM 1.37 yesTEOM 1.47 yesTEOM-FDMS 1 yesGRIMM 1 yes (**)
PM2.5 currently used calibration factors Equivalence after "correction" (*)ESM 1.46 yes TEOM 1.75 yes TEOM-FDMS 1 yes GRIMM 0.85 yes (**)
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 2-3 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
Monitoringstation
RDRC
IRCEL
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
“Regional Data Processing Centers”
“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
• 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
RIO-Corine interpolation
VITO + IRCEL developed theRIO-corine methodology
43R240
2 km
0 5 10 15 20 25 30 35 400
50
100
150
200
250
300
350
400
CORINE Class
Num
ber
of g
rid c
ells
in b
uffer
42N016
43N073
43R240
Land use indicatorFor each station: Determine buffer
(e.g. 2km radius) Characterize land
use by CORINE class distribution inside buffer
RIO - Land use indicator (1)
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
RIO - Land use indicator (2)
0 0.5 1 1.50
20
40
60
80
100
120
140
NO
2 [
g/m
3 ]
week
rural
urb back
urbind
traff
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.110
15
20
25
30
35
40
45
50
55
60
PM
10 [
g/m
3 ]
week
rural
urb back
urbind
traff
<PM10>
<NO2>
‘Kriging’ condition = ‘spatialy’ homogeneous data
Use relation between land use indicator and AQ statistics to “detrend” monitoring data:
Remove local character of sampling values
Kriging interpolation of “detrended” data
0 0.2 0.4 0.6 0.8 1 1.2 1.40
10
20
30
40
50
60
70
80
90
C
[µg/
m³]
C
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
RIO-corine methodology
LegendRIO map [µg/m³]
34 - 43
44 - 52
53 - 61
62 - 68
69 - 75
76 - 126
LegendKriging [µg/m³]
78 - 85
86 - 87
88 - 90
91 - 95
96 - 99
100 - 109
Legenddelta C [µg/m³]
-4 - 0
1 - 21
22 - 27
28 - 33
34 - 39
40 - 52
(1) Kriging map (2) DC map
(3) RIO map
0 0.2 0.4 0.6 0.8 1 1.2 1.40
10
20
30
40
50
60
70
80
90
C
[µg/
m³] C
Correlation <-> distance
Compare with standard IDW and OK
Valdidation – “leaving-one-out”
Model O3 NO2 PM10
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
Valdidation – using “independent” measurements
0
10
20
30
40
50
60
70
80
90
20
04
06
26
20
04
07
01
20
04
07
06
20
04
07
11
20
04
07
16
20
04
07
21
20
04
07
26
20
04
11
26
20
04
12
01
20
04
12
06
20
04
12
11
20
04
12
16
20
04
12
21
20
04
12
26
20
04
12
31
20
05
01
05
20
05
01
10
observations
RIO-corine interpolated
R² = 0.90MAE = 2.9 µg/m³RMS = 4.3 µg/m³
Average observations : 30.6 µg/m³Average RIO-c interpolation : 31.5 µg/m³
Annual mean PM10 concentrations 2006
RIO-corineOrdinary Kriging
RIOOK
Annual average NO2 concentrations 2002
LegendNO2 [µg/m³]
error
1 - 10
11 - 12
13 - 14
15 - 17
18 - 20
21 - 23
24 - 26
27 - 29
30 - 33
> 33
LegendNO2 [µg/m³]
error
1 - 10
11 - 12
13 - 14
15 - 17
18 - 20
21 - 23
24 - 26
27 - 29
30 - 33
> 33
LegendNO2 [µg/m³]
error
< 10
11 - 12
13 - 14
15 - 17
18 - 20
21 - 23
24 - 26
27 - 29
30 - 33
> 33
RIO-corine : further developments (1)
NO2 - 4x4 km NO2 - 1x1 km
RIO-corine : further developments (2)
New proxy :AOD (aerosol optical Depth) ?
Source : Modis Terra satelite, 2006
Total ColumnAOD 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, BelgiumbBelgian 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).
Brussels
Polluants : PM10 et NO2
Plan : 3 niveaux
Wallonia
Polluant : PM10
Plan : 3 niveaux
Flanders
Polluant : PM10
Plan : 1 niveau
- Information of the public (see ozone EU info/alert thresholds)
- Activation winter SMOG action plans
(FORECASTED PM10 > 70 µg/m³, for two consecutive days)
Goal of Air Quality forecasts ?
Two different types of models
1. Deterministic models• Complex input :
meteo, emissions, geografical information, fysico-chemical 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
NOx emissionscombustion
ExampleTemperature
CHIMERE – Example (1)
Forecast for 21/6/2005
Observations 21/6/2005
CHIMERE – Example (2)
OVL : schematically
Input:•PM10 measurements day-1
•Meteo forecasts
Process:
Output : PM10 daily mean day0, +1, +2, +3 and
+4
Neural
Network
OVL : most important meteo-input parameter
Temperature Inversion
Low windspeeds
Boundary Layer Height
OVL : PM10 – winter/spring 2005forecast day +1
0
20
40
60
80
100
120
140
01/01/05 01/02/05 01/03/05 01/04/05
µg/m
³
metingen
OVL modelR=0.7
Antwerp (monitoring station 42R801)
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, BelgiumbInterregional Cell for the Environment (IRCEL), Kunstlaan 10-11, B-1210 Brussels, BelgiumcRoyal 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.bewww.vmm.be