Atmosphere Monitoring
Air quality forecast
using CAMS products
in Hungary
Zita Ferenczi Emese Homolya István Ihász Ilona Krüzselyi
Hungarian Meteorological Service
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O v e r v i e w
• AQ information system of OMSZ
– Current status
– Future plans
• Using Copernicus Atmosphere Monitoring Service products atOMSZ
• Validation of the first results
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• Objectives: – to develop an air quality information website
– to inform the public and support the work of decision makers
• Current situation:– The air quality forecast for Budapest is needed to be revised
– Motivation: • CHIMERE model version 2008 - new model version available
• updated gridded emission data
• Future plans:– Complex website: emission, measurement, model results
– On the modeling page:• much more info, not only forecast
A Q i n f o r m a t i o n s y s t e m o f O M S Z
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• What we would like to present on these pages:– Air quality forecast:
• Aim: to predict smog situations
• Air quality maps for 4 different domains
• Meteorological parameters, which have essential effects on air quality(PBL, SI index…)
• EPSgrams for different cities
– Analysis of the air quality of Hungary:• Assessment of the air quality of Hungary
– Maps and documents
M o d e l l i n g i n f o r m a t i o n
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• CHIMERE: Eulerian off-line chemistry-transportmodel
• The code is completely written in Fortran90, and running scripts are written in shell
• Code version: 2017
• The model requires several numerical tools:
• a Fortran 95 compiler (e.g. gfortran)
• GNU bash Bourne shell, awk and make
• Unidata NetCDF library (free)
• PnetCDF library (free)
• Open MPI or LAM-MPI software (free)
• The NCO libraries (free)
• python libraries (free)
• The key processes are taken into account:
• Emission
• Transport (advection and mixing)
• Chemistry
• Deposition (dry and wet)
C h e m i s t r y t r a n s p o r t m o d e l
MACC LMDz-INCA GOCART
AROME, (WRF)
OMSZEMEP
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P r e - p r o c e s s i n g o f t h e e m i s s i o n
• Emission sources:– Anthropogenic (EMEP, TNO…)
– Biogenic (MEGAN model)
– Mineral dust
– (Volcanoes, forest fires)
– (Resuspension)
• Activity sectors: SNAP code, no GNFR!!
• „Emisurf” preprocessor:– based on a top-down approach, calculates
hourly emission fluxes on the horizontalCHIMERE grid
– Proxies: population density
• Available emission data:– Emission inventory (2015) for Hungary
(OMSZ) and the Carpathian Basin (EMEP)(0.1° x 0.1 °)
– High resolution emission data for three major cities in Hungary (Budapest, Pécs, Miskolc) (0.05° x 0.05 °)
SNAP codes
Sector 1Combustion in the production and
transformation of energy
Sector 2 Non-industrial combustion plants
Sector 3 Industrial combustion plants
Sector 4 Industrial processes without combustion
Sector 5Extraction and distribution of fossil fuels and geothermal energy
Sector 6 Use of solvents and other products
Sector 7 Road Transport
Sector 8 Other mobile sources and machinery
Sector 9 Waste treatment and disposal
Sector 10 Agriculture
Sector 11 Other sources and sinks (nature)
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A n t h r o p o g e n i c E m i s s i o n f l u x e s
• Using the emisurf pre-processor
• Horizontal and monthlydownscaling
– The seasonal factor: at first, a seasonal factor (country specified) for the annual data is applied.
• Weekly and hourly factors are alsoapplied
• Result:
– prepares NetCDF monthly datafiles, projected on the horizontal CHIMERE grid, containing fluxes for the CHIMERE chemical species
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H u n g a r i a n g r i d d e d e m i s s i o n
0.1 °
0.05 °
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I n p u t m e t e o r o l o g i c a l d a t a
Numerical weather predictiondata: AROME (WRF)• In the cases of the cities
(Budapest, Miskolc, Pécs): 0.015° x 0.02°
• Carpathian Basin: 0.1° x 0.1 °
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U s i n g C A M S d a t a a t O M S Z
• Models: CHIMERE, EMEP, EURAD, LOTOSEUROS, MATCH, (MOCAGE, SILAM)
• Pollutants: O3, CO, NO2, SO2, PM2.5, PM10
• Domain: 15°W/45°N/25°W/50°N
• Spatial resolution: 0.1° x 0.1°
• Time resolution:
– 0-48 hours: 1 hour
– 51-96 hours: 3 hours
• Visualisation: HAWK (Hungarian Advanced WorKstation)
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P r o c e s s i n g C A M S d a t a a t O M S Z
• Maps: using our own visualisation system (HAWK)
• Menu with CAMS models:
• Results of the visualisation:
CAMS-CHIMERECAMS-EMEP OMSZ-CHIMERE
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E P S G R A M
• Aim: providing air quality forecast for different cities
• Original grib data files from CAMS– 6 pollutants– 7 model results– Forecast for 94 hours
• Postprocessing the grib files (script)– 14 Hungarian cities– Results are available on our intraweb– Results have to be reviewed only after a validation– In the near future: epsgrams on our web site
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V a l i d a t i o n
• Comparing the model results with the measured data• Starting date: 06.13.2019.• 2.5 months data are available for the validation• Daily averages, daily maxima and hourly data were analysed• Correlation, BIAS and RMSE were calculated• The aim of the „validation”:
– Can we and the policy makers use this information? How?– How can we interpret this information?– Providing comprehensible information to everyday users
• Problems:– Comparing the gridded data with point measurements– City – which grid point should we use?
• The results of the validation are very interesting and useful
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F i r s t r e s u l t s o f t h e v a l i d a t i o n - O 3
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F i r s t r e s u l t s o f t h e v a l i d a t i o n - N O 2
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F i r s t r e s u l t s o f t h e v a l i d a t i o n - P M 1 0
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• Results of the validation– Results are only preliminary with great uncertainty – We need longer time series for a real validation
• O3
– good correlation (0.7)– overestimation– CHIMERE gives the best results
• NO2
– correlation is not bad (0.5)– underestimation– In the case of Miskolc extremely bad results (all models give bad results!)– LOTUSEUROS gives the best results
• PM10
– correlation is not bad (0.3-0.7), in some cases good – underestimation– EMEP gives the best results
C o n c l u s i o n
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T h a n k y o u f o r y o u r a t t e n t i o n !