Difference between revisions of "AQ Scenario for AIP 2008 CFP"

From Federation of Earth Science Information Partners
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[[GEOSS_AIP_AQ_Scenario |<Back to AQ Pilot Scenario Workspace]]<br>
 
[[GEOSS_AIP_AQ_Scenario |<Back to AQ Pilot Scenario Workspace]]<br>
  
'''2.6.2 Air Quality Scenario'''<br>
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=2.6.2 Air Quality Scenario=
The air quality scenario envisions GEOSS facilitating two broad goals: building connections to facilitate movement of data between actors, and developing interoperable tools for intercomparison and fusion of a wide variety of atmospheric data. This scenario is consistent with GEO project HE-07-03: Integrated Atmospheric Pollution Monitoring, Modelling, and Forecasting in the [http://earthobservations.org/documents/wp0709_v4.pdf  GEO 2007-2009 Work Plan], and with the efforts of the [http://www.scgcorp.com/uic2007/docs/Hilsenrath-CEOS%20Virtual%20Constellation.pdf CEOS Atmospheric Composition Constellation]; the development of the [http://www.gmes.info/181.0.html GMES Atmospheric Service], as well as other major international collaboration efforts.  
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==Summary==
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The air quality scenario envisions GEOSS facilitating two broad goals: building connections to facilitate movement of data between actors, and developing interoperable tools for intercomparison and fusion of a wide variety of atmospheric data. This brief description of the scenario contains hyperlinks to a [[AIP_AQ_Unified_Scenario|more detailed version of the scenario]].
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The scenario is focused on three end users:
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# A policy-maker, needing synthesized information on the importance of [[AIP_AQ_Unified_Scenario#Assessment_of_International_and_Intercontinental_Transport_of_Air_Pollution|intercontinental pollutant transport]]
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# An air quality compliance manager, who needs to assess whether a regional pollution event was caused by an "[[AIP_AQ_Unified_Scenario#Exceptional_Event_analysis|exceptional event]]"
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# The public, needing information about [[AIP_AQ_Unified_Scenario#Informing_the_public_and_the_health_sector_about_air_quality_in_real-time_or_near-real-time_and_future_forecasts_.28e.g._AIRNow.2C_AIRNow-International.2C_EPA.2FNational_Weather_Service_National_Air_Quality_Forecast_guidance.2C_PHASE.29 |air quality now]] and in the near future (via air quality forecasts) to make activity decisions
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This scenario is consistent with GEO project HE-07-03: Integrated Atmospheric Pollution Monitoring, Modelling, and Forecasting in the [http://earthobservations.org/documents/wp0709_v4.pdf  GEO 2007-2009 Work Plan], and with the efforts of the [http://www.scgcorp.com/uic2007/docs/Hilsenrath-CEOS%20Virtual%20Constellation.pdf CEOS Atmospheric Composition Constellation]; the development of the [http://www.gmes.info/181.0.html GMES Atmospheric Service], as well as other major international collaboration efforts.  
 
   
 
   
 
A number of the actors in the scenario have overlapping roles, and in reality the same individuals will serve several downstream decision-makers. In fact, the common need for integrated atmospheric observations is a primary motivation for the structure of this scenario.  In describing how air quality and related earth observations could be used to inform a wide spectrum of decision making; three decision-making end users are featured: <br>
 
A number of the actors in the scenario have overlapping roles, and in reality the same individuals will serve several downstream decision-makers. In fact, the common need for integrated atmospheric observations is a primary motivation for the structure of this scenario.  In describing how air quality and related earth observations could be used to inform a wide spectrum of decision making; three decision-making end users are featured: <br>
# A policy-maker, needing synthesized information on the importance of [http://wiki.esipfed.org/index.php/AIP_AQ_Unified_Scenario#Assessment_of_International_and_Intercontinental_Transport_of_Air_Pollution#Assessment_of_International_and_Intercontinental_Transport_of_Air_Pollution intercontinental pollutant transport]
 
# An air quality compliance manager, who needs to assess whether a regional pollution event was caused by an "[http://wiki.esipfed.org/index.php/AIP_AQ_Unified_Scenario#Exceptional_Event_analysis#Exceptional_Event_analysis exceptional event"]
 
# The public, needing information about [http://wiki.esipfed.org/index.php/AIP_AQ_Unified_Scenario#Informing_the_public_and_the_health_sector_about_air_quality_in_real-time_or_near-real-time_and_future_forecasts_.28e.g._AIRNow.2C_AIRNow-International.2C_EPA.2FNational_Weather_Service_National_Air_Quality_Forecast_guidance.2C_PHASE.29 air quality now] and in the near future (via air quality forecasts) to make activity decisions
 
  
 
Since air pollution is affected by sources and processes over local, regional, and hemispherical scales, understanding the causes of specific instances of air pollution and predicting air quality in any area therefore requires descriptions of atmospheric processes valid and useful on a wide range of scales. Given the wide variety of relevant observations at many scales, each of the above decisions ultimately needs an array of observations and models to describe the atmosphere. Earth observing data are needed from a wide variety of sources such as: ambient monitors, measuring the concentrations of pollutants near the ground; radiosondes and other instruments which profile an atmospheric column; chemical transport models; satellite measurements, which report either column densities of pollutants or, with limited vertical resolutions, 3-D fields; meteorological data and models; emissions data and models; and demographic and economic information.  These data sources, while considered necessary are significantly limited and not able to broadly document the state of the atmosphere. Therefore, synthetic fusion and intercomparison of the data will allow analysts to produce a far more complete and accurate description of the atmosphere than obtainable from any one data source, or any one class of data. There are a number of scientific approaches to this challenge, but the technical tools for intercomparison, fusion, and processing of air quality data are not operationally available.<br>
 
Since air pollution is affected by sources and processes over local, regional, and hemispherical scales, understanding the causes of specific instances of air pollution and predicting air quality in any area therefore requires descriptions of atmospheric processes valid and useful on a wide range of scales. Given the wide variety of relevant observations at many scales, each of the above decisions ultimately needs an array of observations and models to describe the atmosphere. Earth observing data are needed from a wide variety of sources such as: ambient monitors, measuring the concentrations of pollutants near the ground; radiosondes and other instruments which profile an atmospheric column; chemical transport models; satellite measurements, which report either column densities of pollutants or, with limited vertical resolutions, 3-D fields; meteorological data and models; emissions data and models; and demographic and economic information.  These data sources, while considered necessary are significantly limited and not able to broadly document the state of the atmosphere. Therefore, synthetic fusion and intercomparison of the data will allow analysts to produce a far more complete and accurate description of the atmosphere than obtainable from any one data source, or any one class of data. There are a number of scientific approaches to this challenge, but the technical tools for intercomparison, fusion, and processing of air quality data are not operationally available.<br>

Revision as of 09:32, May 23, 2008

<Back to AQ Pilot Scenario Workspace

2.6.2 Air Quality Scenario

Summary

The air quality scenario envisions GEOSS facilitating two broad goals: building connections to facilitate movement of data between actors, and developing interoperable tools for intercomparison and fusion of a wide variety of atmospheric data. This brief description of the scenario contains hyperlinks to a more detailed version of the scenario.

The scenario is focused on three end users:

  1. A policy-maker, needing synthesized information on the importance of intercontinental pollutant transport
  2. An air quality compliance manager, who needs to assess whether a regional pollution event was caused by an "exceptional event"
  3. The public, needing information about air quality now and in the near future (via air quality forecasts) to make activity decisions

This scenario is consistent with GEO project HE-07-03: Integrated Atmospheric Pollution Monitoring, Modelling, and Forecasting in the GEO 2007-2009 Work Plan, and with the efforts of the CEOS Atmospheric Composition Constellation; the development of the GMES Atmospheric Service, as well as other major international collaboration efforts.

A number of the actors in the scenario have overlapping roles, and in reality the same individuals will serve several downstream decision-makers. In fact, the common need for integrated atmospheric observations is a primary motivation for the structure of this scenario. In describing how air quality and related earth observations could be used to inform a wide spectrum of decision making; three decision-making end users are featured:

Since air pollution is affected by sources and processes over local, regional, and hemispherical scales, understanding the causes of specific instances of air pollution and predicting air quality in any area therefore requires descriptions of atmospheric processes valid and useful on a wide range of scales. Given the wide variety of relevant observations at many scales, each of the above decisions ultimately needs an array of observations and models to describe the atmosphere. Earth observing data are needed from a wide variety of sources such as: ambient monitors, measuring the concentrations of pollutants near the ground; radiosondes and other instruments which profile an atmospheric column; chemical transport models; satellite measurements, which report either column densities of pollutants or, with limited vertical resolutions, 3-D fields; meteorological data and models; emissions data and models; and demographic and economic information. These data sources, while considered necessary are significantly limited and not able to broadly document the state of the atmosphere. Therefore, synthetic fusion and intercomparison of the data will allow analysts to produce a far more complete and accurate description of the atmosphere than obtainable from any one data source, or any one class of data. There are a number of scientific approaches to this challenge, but the technical tools for intercomparison, fusion, and processing of air quality data are not operationally available.

Therefore, this scenario a) identifies the actors and their needs for near-real time and historic data facilitated through GEOSS and b) describes the processed and integrated air quality information, created using interoperable, service-oriented tools for data fusion and intercomparison that will be promoted by GEOSS. To describe the needed information and tools, the scenario also documents the upstream users, and the information they need, in the data value chain.

A number of actors process earth observations information upstream of the decision makers, who base their decisions on highly synthesized data. These actors, shown below, have overlapping roles, and in reality the same individuals will serve several downstream decision makers. In fact, the common need for integrated atmospheric observations is a primary motivation for the structure of this scenario.

AQ ActorValueChain.png

The actors and the earth observation information each desires are: Intercontinental Pollution Transport, Exceptional Pollution Event, and Member of the Public Planning Activities. The earth observations used in all three of the decision making information chains are: National, State/Provincial, Local Environmental Management Agencies, National Meteorological Agencies, National Space Agencies, National Land Management Agencies, Industry, Consultants, Academic and Other Research Institutes, and International cooperative fora (e.g.WMO,CEOS,EEA).
Information already available for the scenario events include: 1) meteorological data, such as observations from ground-based networks, satellites, sondes , and forecasts from numerical models at the global and regional scales; 2) geographical data (land use, demographics, emissions-related activity, etc.); 3) atmospheric composition (air quality) observations such as surface monitoring networks, satellite observations ,sondes, ground-based remote sensors, and aircraft measurements; and 4) numerical air quality chemical transport models (at regional to global scales).


In order to interface with the GEOSS Core Architecture, the scenario needs to include the following components and functionality:

  1. Community Catalog(s) for registering data and services to be harvested by the GEOSS Clearinghouse
  2. Community Portal(s) for finding, accessing the data and services needed for the execution of the scenario,
  3. Functionality for standard-based access to spatio-temporal data and metadata, and workflow software for for service orchestration
  4. Community of Practice Workspace(s) where the actors in the scenario can communicate and coordinate their activities.

Additional functionality and facilities specific to the Air Quality Scenario should include tools for visualizing, and processing observational and modeling data for near real time and for historical analysis. These tools should facilitate:

  1. Integration of multiple observational data sets to create rich n-dimensional descriptions of the atmosphere to improve understanding of atmospheric processes;
  2. Comparison of observational data to numerical model estimates to improve numerical model descriptions of historical conditions (events or long-term trends);
  3. Real-time assimilation of observational data into numerical models to improve numerical forecasts;
  4. Effective mechanisms for distributing (in near real time) maps/images, descriptive information, and processed data health, emergency response, and air quality management authorities; to mass media; other research and assessment communities (e.g., health); and the general public.

Scenario Events
The cyberinfrastructure envisioned by this scenario will enable analysts to combine wide range of air quality observations, models, and other information, which will ultimately be used to produce a broad range of decision support products for a number of different audiences. The air quality and health scenario events include: Assessment of International and Intercontinental Transport of Air Pollution, Exceptional Event Analysis, and Informing the Public and the Health Sector About Air Quality. Current projects (e.g. AIRNow, AIRNow-International, 3D-AQS, PHASE, GEMS, IDEA) are significant building blocks along with the evolving data mediatiors (e.g. Datafed, GIOVANNIof the needed networks and tools. As above, the actors will benefit from constructing linkages between data sources and tools, but also from development and linking tools to facilitate comparison of models, observations, and emissions information.