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Air Quality Decision Support Example: Justification and Granting of Exceptional Event Status

Air Quality Decision Support Example: Justification and Granting of Exceptional Event Status. Internet. Exceptional Event Regulatory Status. Natural events such as forest fire smoke and wind blown dust are be exempt from air quality standards compliance.

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Air Quality Decision Support Example: Justification and Granting of Exceptional Event Status

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  1. Air Quality Decision Support Example:Justification and Granting of Exceptional Event Status

  2. Internet Exceptional Event Regulatory Status • Natural events such as forest fire smoke and wind blown dust are be exempt from air quality standards compliance. • State AQ control agencies can petition exemptions from the federal EPA for the those exceptional days. • However, they are required to provide sufficient justification that the event was indeed caused by sources beyond their control. • Decision Making: Based on the ‘weight of evidence’ provided by the states, the federal EPA decides if the requested waiver is justified. • Both the states and the EPA can use observational and modeling data from a broad range of sources to justify their actions. Federal EPA Petition Decision State AQ Agency

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  4. Internet

  5. Exceptional Event AQ Warning and Forecast • By law, state agencies are required to issue advisories to the public when unhealthy air quality conditions are anticipated. • Forest fire smoke and wind blown dust can produce such conditions. • Based on real-time monitoring of the air quality situation, the DSS monitors the appearance of and forecasts the evolution of potentially harmful events. • Decisions by States: Issuing the warning and forecast. (where, when, what emergency) • Decisions By Public: How to respond (asthmatics, recreation, etc.)

  6. June 27, 2006 July 6, 2006 MODIS MODIS GOES GOES Canadian Smoke Events Based on real-time satellite observations (MODIS, GOES), around July 1, 2006 Canadian smoke impacted the Midwest for several days. Smoke Smoke Smoke Smoke

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  10. Decision Systems Impacted by Smoke

  11. Canadian Smoke Events • Monitoring: Jane monitors the AQ situation looks at indicators through console • Event Detection: Jane detects an event and takes a “closer look” (space, time and sensing parameters) • Characterization: An “event team” characterizes the event based on all the available sensory and model data. • Event Triggers: If warranted trigger messages are sent to the relevant decision systems. • Characterization-Decision-Action Loop: The characterization and decision teams interact to and create an agile decision support system.

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