Martin Schultz IEK-8 Forschungszentrum Jülich GmbH Rudy Husar Washington University St. Louis.

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Presentation transcript:

Martin Schultz IEK-8 Forschungszentrum Jülich GmbH Rudy Husar Washington University St. Louis

Air Quality Many different species are air pollutants (particles, ozone, SO2, VOCs, POPs, mercury) Air pollution is generated locally Impacts of air pollution are diverse (health, crops, ecosystems, climate) Regulations on air quality are diverse (different thresholds, dose functions) Air pollution has global implications (long-range transport, long-lived species)

Example for long-range transport of air pollution

Community (pl. communities)

Practice GEOSS is (should be) about: producing data distributing data enhancing data visualizing data using data NETWORK NETWORK? Which level of coordination is necessary/possible?

Air Quality Data Portals ACTRIS - Aerosols, Clouds, and Trace gases Research InfraStructure –EARLINET - European Aerosol Research Lidar Network –EUSAAR - European Supersites for Atmospheric Aerosol Research –CLOUDNET AeroCom - Aerosol Model Inter-comparison Project CEOS ACP: Atmospheric Composition Portal CIERA: Community Initiative for Emissions Research and Applications DataFed - Federated Data Systems for AQ Data Access and Analysis EBAS - Norwegian Institute of Air Research GMES MACC: Monitoring Atmospheric Composition and Climate Jülich MACC and HTAP boundary condition server NASA GIOVANNI - Data & Information Services Center US EPA RSIG - Remote Sensing Information Gateway US EPA AQS - Air Quality System VIEWS - Visibility Information Exchange Web System World Data Centers (WDCGG, WOUDC) ? Notes: few „operational“ systems; little realtime data; poor links between systems; no data portal in Asia, Africa, South America, Australia

Jülich BC web interface Making GEOSS work: GMES AQ services Datafed Data producerData server automatic script triggered by user request Ozone episode over western Europe: 07 May 2011

EU threshold (8 hours)

WP3 Status Slide 9 Use of MACC BC during Commonwealth Games, India SLA in preparation (courtesy G. Carmichael)

Data formats (examples) WDCGG, JapanEMEP, NILUCASTNET, US

Ensuring data quality Mean value at this station is ~30 (ppb), valid range = 1 – 40 ppb

Ensuring data quality requires (common?) data quality objectives requires knowledge about data generation must be standardized –across compounds –across measurement networks –across measurement techniques/instruments –across communities Can it be automated?

Forming a community & Establishing practices

link = ST-09-02, DA-02-08, OGC, network, outreach, stakeholders, … link = ln –s foo bar