GEOSS Architecture Implementation Pilot Air Quality and Health Scenario Stefan Falke, Rudy Husar, Francis Lindsay, David McCabe Boulder Kickoff Meeting

Who does the air quality scenario benefit? The scenario is quite broad and ambitious, structured around the needs of three end-users: -A policy-maker, needing synthetic assessments of long-range transport of air pollution -An air quality manager, assessing whether an episode qualifies as an ’exceptional event’ under AQ regulations Exceptional events such as fires, dust storms are not counted as an exceedance under AQ regulations. In US, petitioners can use any applicable data to show exceptionality of an event. -The public, needing information on air quality now and tomorrow Enables individuals, families to adjust plans if air quality is/will be poor; allows health community, other decision-makers to plan for episodes

What does the air quality scenario envision? Data, tools, and capabilities for one group of end users generally benefit all end users Much data, tools already exist; not currently operational or interoperable

Policy Makers Sign international agreement? AQ Managers Was pollution event due to transport from afar? Event analysis Public Is it healthy to go for a run now? Decision Support Air Quality Analysts Air Quality Forecasters integration of multiple observational datasets comparison of observations, models REAL TIME assimilation of observations into models REAL TIME distribution of AQ processed data, maps Met Agency met data Modeling Community models Enviro. Agency Ambient Pollutant Concentrations Satellite Agency Pollutant Column Densities These upstream connections & capabilities aren’t currently operational and interoperable

What does the air quality scenario envision? Data, tools, and capabilities for one group of end users generally benefit all end users Much data, tools already exist; not currently operational or interoperable The air quality scenario represents a great test bed for an interoperable, system-of-systems approach

Earth Observations Providers Space agencies; met, land management, and environmental/health agencies (national, regional, local); Academics; Private sector Air Quality Modelers, Forecasters, and Analysts Environmental/health management and met agencies (national, regional, local) Modelers and analysts in many settings Information Management Specialists Air Quality Management Decision-Makers Environmental, health agencies; Multi-lateral Cooperative Fora: LRTAP, EANET, Malé Declaration, Arctic Council Other Consumers of Air Quality Informations Public, researchers, mass-media, … Air Quality & Health Scenario: Actors

Many actors are ‘decision-makers’ Policymakers, sensitive individuals, modelers, parents, transit officials, air quality managers, weather forecasters, air quality analysts, environmental compliance officials, …

Air Quality & Health:Starting Information Meteorological data –Observations from ground-based networks, satellites, sondes –Forecasts from numerical models at the global and regional scales Geographical data –Land use –Demographics –Emissions-related activity Atmospheric Composition (Air Quality) Observations –Surface Monitoring Networks –Satellite Observations –Sondes –Ground-based remote sensors –Aircraft Measurements Numerical Air Quality Chemical Transport Models –(at regional to global scales)

Air Quality & Health Scenario: Existing Efforts Real-Time Large-Scale Event Analysis –FASTNET, IDEA, SmogBlog Assessment of International and Intercontinental Transport of Air Pollution –HTAP Data Network, AMET, RSIG, HemiTap Assimilation of Observations for Air Quality Forecasting –GEMS, RAQMS Provision of Relevant Information to the Health Community & the Public –AIRNow, PHASE

extra slides

Air Quality & Health AIP Scenario Air pollution remains a serious global public health problem Worldwide: hundreds of thousands of deaths from outdoor air pollution To understand, forecast, and manage air pollution, diverse information needs to be brought together: –surface monitors, satellites, airborne sensors –meteorological & chemical transport models –emissions & emissions-generating activities –demographics, exposure-related behavior, health impacts –air pollution crosses political boundaries so information must too`

Examples – pieces of the puzzle GAW: WMO Global Atmosphere Watch

Development of the AIP Air Quality Scenario Developed iteratively by a collaborating multi-organization group Written on the ESIP wiki, using online forum and telecons to plan, discuss, and develop the submitted scenarioESIP wikidiscuss Helped develop the ESIP air quality Community of Practice, which is co ‑ evolving with the AIP Pilot and other activities Published with AIP Phase Two CFP, 27 June 2008 Community of Practice Wiki for AQ Scenario

Examples – pieces of the puzzle GEMS: Global & regional Earth system Monitoring using Satellites (ECMWF)

Examples – pieces of the puzzle Informing the public about Air Quality & Forecasts in real time: AIRNow

Interoperability needed! many systems, many pipes…. we shouldn’t keep reinventing wheels!

Societal needs and the actors Data wonks Modelers Air Quality analysts Local policy maker Distant policy maker Sensitive individual Real time event analysis XXXXXX Assessing inter- continental transport XXXXX Merging satellites, in-situ, model data XXX AQ nowcasts, forecasts to public XXXXX