Aristeidis K. GeorgouliasAristeidis K. Georgoulias

Contribution of Democritus University Contribution of Democritus University of Thrace-DUTH in AMFIC-Projectof Thrace-DUTH in AMFIC-Project

Democritus University of ThraceDemocritus University of ThraceLaboratory of Atmospheric Pollution and Pollution Laboratory of Atmospheric Pollution and Pollution Control Engineering of Atmospheric pollutantsControl Engineering of Atmospheric pollutants

Main ObjectivesMain Objectives::

1. Exploit WP2, WP3, WP4 and WP5 outcome1. Exploit WP2, WP3, WP4 and WP5 outcome- WP2: Ozone, NOWP2: Ozone, NO22, SO, SO22, HCHO columns from GOME, SCIAMACHY and OMI, , HCHO columns from GOME, SCIAMACHY and OMI,

CO & CHCO & CH44 columns from SCIAMACHY, Aerosol properties from AATSR columns from SCIAMACHY, Aerosol properties from AATSR

- WP3: Validation of SOWP3: Validation of SO22, CO and ozone columns, aerosol concentration/properties, CO and ozone columns, aerosol concentration/properties

- WP4: High resolution air quality mapsWP4: High resolution air quality maps

- WP5: model forecasts for ozone, NOWP5: model forecasts for ozone, NO22, SO, SO22, CO and aerosols , CO and aerosols

2. 2. Demonstrate how to use data from satellites to Demonstrate how to use data from satellites to explore and monitor processes relevant to the transport explore and monitor processes relevant to the transport of air pollutionof air pollution

3. Provide3. Provide an extensive system assessment report, an extensive system assessment report, suitable for feeding GEOSS suitable for feeding GEOSS andand GMES requirements GMES requirements

DUTH TasksDUTH Tasks::

1. Data fields will be homogenized and brought into a 1. Data fields will be homogenized and brought into a common spatial and temporal format (INSPIRE)common spatial and temporal format (INSPIRE)

2. A web database will host the (observed, modeled 2. A web database will host the (observed, modeled and/or assimilated) dataand/or assimilated) data

3. A set of tools will allow easy manipulation and 3. A set of tools will allow easy manipulation and analysis of the dataanalysis of the data

• Automatic detection of features such as plumes and monitoring Automatic detection of features such as plumes and monitoring of their evolutionof their evolution

• Data covariance analysis, enabling the detection of emission Data covariance analysis, enabling the detection of emission signatures of different sourcessignatures of different sources

• Cluster analysis Cluster analysis

• Export of data in different formatsExport of data in different formats

Satellite System PredecessorSatellite System Predecessor::

Satellite Earth simulator-AIRSATSatellite Earth simulator-AIRSAThttp://www.satellite-earth-simulator.com/http://www.satellite-earth-simulator.com/

Satellite Data SourcesSatellite Data Sources::• TOMS (Earth Probe TOMS)TOMS (Earth Probe TOMS)

• SCIAMACHY (ENVISAT)SCIAMACHY (ENVISAT)

• GOME (ERS-2)GOME (ERS-2)

• MODIS (AQUA)MODIS (AQUA)

Meteorological Data SourceMeteorological Data Source::• NCEP/NCAR Reanalysis Project NCEP/NCAR Reanalysis Project

Meteorological parametersMeteorological parameters• TemperatureTemperature• HumidityHumidity• PressurePressure• Wind speedWind speed• Precipitation Precipitation

Atmospheric dataAtmospheric data • Ozone vertical columnOzone vertical column• NONO22 vertical column vertical column• Aerosol Optical Thickness over oceanAerosol Optical Thickness over ocean• Cloud Optical Thickness Cloud Optical Thickness • Cloud Top Temperature Cloud Top Temperature • Optical Depth Land and OceanOptical Depth Land and Ocean• Atmospheric Water Vapour Atmospheric Water Vapour

Ocean dataOcean data• ChlorophyllChlorophyll• Sea surface temperatureSea surface temperature,, day day//nightnight

An ExampleAn Example::Data from ICSU World Data Center for Remote Sensing of the Data from ICSU World Data Center for Remote Sensing of the Atmosphere http://wdc.dlr.de Atmosphere http://wdc.dlr.de

geographical areageographical area

data setdata set

time periodtime period

(Spectral(Spectral Harmonic Analysis Harmonic Analysis applied on applied on NASA NASA EP EP TOMS Level 2 dataTOMS Level 2 data))

daily data in csv ascii formatdaily data in csv ascii format(1(1oox1x1oo analysis) analysis)

daily mapsdaily maps

start animationstart animation

select coordinatesselect coordinates

time series for Xanthi [41.133time series for Xanthi [41.133ooN, 24.883N, 24.883ooE] E] graph & csv ascii formatgraph & csv ascii format

animationanimation

Sea Level PressureSea Level Pressure

Relative HumidityRelative Humidity

Statistical exploitation of data (1)Statistical exploitation of data (1)::60% covariance of Sea Level Pressure and Relative Humidity 60% covariance of Sea Level Pressure and Relative Humidity (2006) (2006)

Statistical exploitation of data (2)Statistical exploitation of data (2)::17% covariance of Sea Level Pressure and Relative Humidity 17% covariance of Sea Level Pressure and Relative Humidity (2006)(2006)

Sea Level PressureSea Level Pressure

Relative HumidityRelative Humidity

Statistical exploitation of data (3)Statistical exploitation of data (3)::

Correlation of Precipitation above Correlation of Precipitation above the region of Thrace, Greece and the region of Thrace, Greece and large scale Sea Level Pressure for large scale Sea Level Pressure for several temporal lags (1/2004-several temporal lags (1/2004-

12/2005)12/2005)

Seasonal Correlation of Precipitation Seasonal Correlation of Precipitation above the region of Thrace, Greece above the region of Thrace, Greece and large scale Sea Level Pressure and large scale Sea Level Pressure for several temporal lags (January- for several temporal lags (January-

February-March 2004-2005)February-March 2004-2005)

Statistical exploitation of data (4)Statistical exploitation of data (4)::

95% covariance of Precipitation 95% covariance of Precipitation above the region of Thrace, Greece above the region of Thrace, Greece and Sea Level Pressure (1/2004-and Sea Level Pressure (1/2004-

12/2005)12/2005)

98% seasonal covariance of 98% seasonal covariance of Precipitation above the region of Precipitation above the region of Thrace, Greece and Sea Level Thrace, Greece and Sea Level Pressure (January–February-March Pressure (January–February-March

2004-2005)2004-2005)

Automatic plume detection (1)Automatic plume detection (1)::Example:Example: Etna eruption (Etna eruption (13-113-155/9/2007/9/2007))

Automatic plume detection (2)Automatic plume detection (2)::Image Enhancement by using methods of color Image Enhancement by using methods of color enrichmentenrichment

Finding the location of plumes via chromatic analysis Finding the location of plumes via chromatic analysis of images with the use of local chromatic histogramsof images with the use of local chromatic histograms

Calculation of the distance and spreading of plumes Calculation of the distance and spreading of plumes via calculation of the distance between the centers of via calculation of the distance between the centers of concentrations which result from the method of concentrations which result from the method of clusteringclustering

Automatic plume detection (3)Automatic plume detection (3)::

Methodology:Methodology:

Trace gas transport from standard sourcesTrace gas transport from standard sourcesMaps with back-trajectories from HYSPLIT model and great Maps with back-trajectories from HYSPLIT model and great standard sources, application of a cluster analysis technique, ascii standard sources, application of a cluster analysis technique, ascii data with information on back-trajectories that passed over data with information on back-trajectories that passed over major sourcesmajor sources

Contribution of NOA (1)Contribution of NOA (1)

Task 6.1. NOA will feed DUTH with INSPIRE Task 6.1. NOA will feed DUTH with INSPIRE requirementsrequirements

Task 6.2.a. NOA will organise an intermediate Task 6.2.a. NOA will organise an intermediate user evaluation half-way the project, when we user evaluation half-way the project, when we will ask the users to write an evaluation. Based will ask the users to write an evaluation. Based on this evaluation and the first validation on this evaluation and the first validation results of WP3, the retrieval algorithms (WP2) results of WP3, the retrieval algorithms (WP2) and model developments (WP4 and WP5) will and model developments (WP4 and WP5) will be adjusted accordinglybe adjusted accordingly

Contribution of NOA (2)Contribution of NOA (2)

Task 6.2b: KNMI, NOA and NSMC will organise a Task 6.2b: KNMI, NOA and NSMC will organise a Workshop for end-users. The workshop will help Workshop for end-users. The workshop will help federate and coordinate the demands of end-users federate and coordinate the demands of end-users from China. Prior to, and during the workshop, from China. Prior to, and during the workshop, NOA will utilize the outcome of ongoing ESA GMES NOA will utilize the outcome of ongoing ESA GMES Service Element and DUE (Data User Element) Service Element and DUE (Data User Element) Programmes, such as PROMOTE, GLOBAEROSOL Programmes, such as PROMOTE, GLOBAEROSOL and TEMIS for ensuring that the project outcome and TEMIS for ensuring that the project outcome will directly serve the GMES Thematic Priority will directly serve the GMES Thematic Priority Atmosphere. Also, contribution to GEOSS objectives Atmosphere. Also, contribution to GEOSS objectives and needs will be a key element of this actionand needs will be a key element of this action

Month 6: Determination of web database structureMonth 6: Determination of web database structure

Month 12: Delivery of the web database and software Month 12: Delivery of the web database and software

Month 12: User evaluationMonth 12: User evaluation

Month 18: Testing of the database and optimisation for usersMonth 18: Testing of the database and optimisation for users

Month 24: Operational database compliant with INSPIREMonth 24: Operational database compliant with INSPIRE

Month 24: Delivery of an assessment report Month 24: Delivery of an assessment report

Month 24: End-user workshop Month 24: End-user workshop

Timetable & DeliverablesTimetable & Deliverables::