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CHIMERE air quality forecasts : results during Pays de la Loire summer 2004 experiment and end-user point of view. ACRI-ST. Arnaud REBOURS - AIR PAYS DE LA LOIRE. 1st CHIMERE workshop 21, 22 March 2005 -Palaiseau France. French air pollution control networks organization. - PowerPoint PPT Presentation
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CHIMERE air quality forecasts : results during Pays de la Loire summer 2004 experiment and end-user point of view
Arnaud REBOURS - AIR PAYS DE LA LOIRE
ACRI-ST
1st CHIMERE workshop 21, 22 March 2005 -Palaiseau France
French air pollution control networks organization
Air Pays de la Loire
NANTES
PARIS
Pays de la Loire region : 3 200 000 inhab.; 32 000 km2
2 missions : air quality survey and information
Air Pays de la Loire
Territorial cover
La Roche/Y
Cholet
Laval
St-Nazaire
10 survey zones 50 survey sites continuous control 15 minutes time resolution
Nantes
Le Mans
Angers
Modelisation tools Regional scale : Calgrid
10 august 2003
Street scale : OSPM
NO2 - Nantes 2001
Industrial scale : Calpuff 11 feb. 2003 - refinery
Scenario mode
CONTEXT 18 june 2004 french regulation : during pollution episodes, air quality public information is based on observations or on risk of exceedings of thresholds -> necessity of forecasting development
Period : 13 july - 12 october 2004
Summer 2004 experiment : operation by ACRI-ST of an air quality forecast system based on MM5-CHIMERE over the Pays de la Loire region
LOCAL FORECASTING PLATFORM
2 zones : Great West area (15 km) and Pays de la Loire region (5 km)
GWEST 15 km
APL 5 km
2 pollutants : O3 and NO2
4 daily outputs : D-1, D, D+1 and D+2 hourly time step
Inputs Outputs
Emissions inventory : 5km and 50 km
Meteorological data : NCEP
Continental chemistry : PREV ’AIR
2D Data
Platform publication
Maps
Forecast computer : MM5-CHIMERE
Interface computer
Job programmer
LOCAL FORECASTING PLATFORM
Meteo-rology
pollution
zone
pollutant4 days forecasts
WEB INTERFACE
FORECAST PRELIMINARY RESULTS Observation data : 20 survey sites
Statistical criteria : BIAS and NMSE
BIAS : D0 FORECAST
-30
-20
-10
0
10
20
30
APL>0GWEST>0PREVAIR>0APL>120GWEST>120PREVAIR>120
FORECAST PRELIMINARY RESULTS
ozone
BIAS : D+1 forecast
-30
-20
-10
0
10
20
30
APL>0GWEST>0PREVAIR>0APL>120GWEST>120PREVAIR>120
FORECAST PRELIMINARY RESULTS
ozone
BIAS : D+2 forecast
-30
-20
-10
0
10
20
30
APL>0GWEST>0PREVAIR>0APL>120GWEST>120PREVAIR>120
FORECAST PRELIMINARY RESULTS
ozone
NMSE : D+1 forecast
0%
20%
40%
60%
80%
100%
120%
140%
160%
180%
200% APL>0GWEST>0PREVAIR>0APL>120GWEST>120PREVAIR>120
FORECAST PRELIMINARY RESULTS
ozone
FORECAST PRELIMINARY RESULTS
NO2
Bias : D+1 forecast
-20
-15
-10
-5
0
5
10
15
20 APL>0GWEST>0PREVAIR>0APL>20GWEST>20PREVAIR>20
FORECAST PRELIMINARY RESULTS
NO2
NMSE : D+1 forecast
0%
100%
200%
300%
400%
500%
600% APL>0GWEST>0PREVAIR>0APL>20GWEST>20PREVAIR>20
POST-PROCESSING ON FORECASTS Vigilance maps improve public information
13 alert zones :5 departments (counties), 7 agglomerations, 1 industrial area
3 symbolic colours : green, orange, red
calculatio
n
2 ways :forecasting
observationvalidati
on
POST-PROCESSING ON FORECASTS Vigilance maps improve public information
Forecasted exceeding
Procedure activating conditions
- agglomerations :
2 sites
- departments :
2 agglomerations or
30% of the zone
communiqués (fax and e-mail) web site : www.airpl.org
POST-PROCESSING ON FORECASTS Vigilance maps improve public information
POST-PROCESSING ON FORECASTS
Air quality index prediction
(D 1 ,...)=
Annualmaps
Exceedings evaluations of limit values, quality objectives and target values
CONCLUSION
Forecast results are acceptable for ozone and better than continental modeled values for NO2 Local platform brings helps to diagnosis : background pollution in the great west of France, influence of Paris pollution, meteorological forecast parameters
Post processing improve air quality information in connection with alert system or daily pollution
PROSPECTS
Integration of detailed emission calculations (AIREMIS)
Integration of meteorological and pollution vertical profiles
Local platform should be operated by Air Pays de la Loire during summer 2005
Statistical adaptation of modeled results with observations for D-1 and D steps