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An Integrated Systems Solution to Air Quality Data and Decision Support on the Web GEO Architecture Implementation Pilot – Phase 2 (AIP-2) Kickoff Workshop.

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Presentation on theme: "An Integrated Systems Solution to Air Quality Data and Decision Support on the Web GEO Architecture Implementation Pilot – Phase 2 (AIP-2) Kickoff Workshop."— Presentation transcript:

1 An Integrated Systems Solution to Air Quality Data and Decision Support on the Web GEO Architecture Implementation Pilot – Phase 2 (AIP-2) Kickoff Workshop NCAR Mesa Laboratory, Boulder, Colorado September 25-26, 2008 AIP Phase 2 Call For Participation: Sensors and Models

2 VIEWS The Visibility Information Exchange Web System Provides integrated online access to: Monitoring data: from over 3 dozen networks Modeling data: from a variety of modeling scenarios Emissions data: inventories and summaries Satellite data: MODIS, CALIPSO, Aqua, Terra, GOES, etc. Serves as the primary source for: IMPROVE Aerosol and Optical data IMPROVE Regional Haze Rule data IMPROVE Special Studies data Has about 1200 registered users from over 300 organizations, institutions, universities, and companies

3 TSS WRAP Technical Support System Built upon the database and software infrastructure of VIEWS Provides consolidated online access to: Regional technical data, planning guidance, and analysis results Decision support for the development of SIPs and TIPs Source apportionment and visibility projections tools Ongoing tracking and assessment of emissions control strategies Documents the technical methods used in implementation plans

4 How do we compare diverse datasets? Ground-based observations Model results Emissions inventories Satellite data Airborne samples etc… SO4 = SO4 = SO4 = SO4 ?? Measured Modeled Emissions Satellite Fine Sulfate (SO4) equivalence:

5 Establishing Dataset Comparability: Method Metadata Sampling and collection methods (sensors) Analysis methods (IC, XRF, PIXE, etc.) ( sensors ) Calculation methods (EC = 1 + E2 + E3 – OP) Processing and aggregation methods Data handling and transformation methods (AQS to VIEWS) Unit conversion methods etc…

6 Sensor Metadata: Sampling Methods

7 Model Metadata Initial conditions Boundary conditions Model parameters Grid cell size Algorithms and processing Assumptions etc…

8 Inter-domain Rosetta Stone

9 Model Performance Evaluation CMAQ Model Performance vs. Monitored Worst 20% Days in 2002

10 Source Apportionment Mass source apportionment by source category and region From regional photochemical model with comprehensive emissions inputs Species mass for various time periods – directly comparable to monitoring data

11 Network Inter-comparisons Parameter: Nitrate Ion Concentrations Location: Bondville, IL Networks: IMPROVE, STN, and CASTNet Graphs: Time Series and Scatter Plot

12 Method (Sensors and Models) Questions: How do we codify methods (sensors and models)? What is the minimum set of method metadata for each type of dataset? How do we codify the degree of equivalence between methods? How do we associate method metadata with observations and results? How do we educate users about method considerations?

13 TheEnd… Thanks!


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