AIP AQ Unified Scenario

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Unified Scenario

This is an attempt to broaden the scope of the AQ scenario beyond fire events. It is motivated by a concern that a focus on fire events will not lead to developments that are applicable to more generalized issues with respect to air quality assessment and forecasting.

Summary

Provide a summary of the scenario and the community that the scenario supports.

Air pollution is a global problem that causes premature mortality and morbidity, damages crops and ecosystems, and contributes to climate change. Furthermore, air pollution does not respect jurisdictional boundaries and is affected by sources and processes over local, regional, intercontinental, and global scales. In the United States alone, poor air quality is estimated to cause tens of thousands of deaths and cost society more than $100 billion annually. Globally, air pollution contributes to the deaths of more than 800 thousand people per year, most in the developing world. Recent scientific and technical advancements, including new observing and information technologies and insights into atmospheric processes, have created opportunities to better assess and manage air pollution and its impacts. Improved information about air quality enables policy-makers and environmental managers to develop more effective policies and plans to improve public health and well being, protect critical ecosystems, and maintain a vital economy. Enhanced air quality forecasts allow communities and individuals, especially those suffering from asthma, allergic diseases, cardiovascular disease, or pulmonary disease, to more effectively limit exposure and the adverse effects of poor air quality.

To better understand, forecast, and manage air pollution, there is a need to bring together information about

• a variety of atmospheric constituents from different observational platforms (surface monitoring networks, satellites, sondes, ground-based remote sensors, aircraft, ...)
• nonlinear chemical and physical atmospheric processes from meteorological and chemical transport models
• emissions and emissions-generating activities
• population demographics, exposure-related behavior, and health impacts

For scientific assessment and analysis of management strategies, this integration can be done using historical datasets. For air quality forecasting to inform the public and manage individual air pollution episodes or events, it is necessary to perform this integration in near real time.

This air quality use scenario envisions a cyberinfrastructure for air quality information that facilitates access, integration, and use of the information described above for purposes of air quality assessment and forecasting. This scenario is consistent with project HE-07-03: Integrated Atmospheric Pollution Monitoring, Modelling, and Forecasting in the GEO 2007-2009 Work Plan, which includes efforts to:

• Advocate a stable and improved in-situ and space-based observing system of global air quality in line with the Integrated Global Atmospheric Composition Observations (IGACO) recommendations.
• Support WMO efforts related to increased spatial and temporal resolution. As a priority, evaluate and recommend strategies for an integrated sampling frame for air pollution.
• Coordinate and facilitate appropriate activities and consortia that complement UNECE CLRTAP HTAP activities and pursue implementation of projects integrating Earth observation data on long range transport with other data, such as health and socio-economic data, to improve decision making.
• Support the development of international systems for both sand and dust storm warning and biomass burning monitoring.
• Coordinate the construction of a high spatial and temporal resolution monitoring and forecasting system including atmospheric, terrestrial and oceanic observations, modelling and chemical data assimilation for global and local air quality.
• Organise appropriate symposia in 2007.

This scenario is also consistent with the efforts of the CEOS Atmospheric Composition Constellation; the development of the GMES Atmospheric Service, GEMS, and its planned extensions; the evolution of AIRNow, IDEA, 3D-AQS, and Datafed; and other ongoing efforts.

Identify the specific decisions to be made.

A particular emphasis is placed on:

• the near real time analysis of large air pollution events (such as those associated with large fires, dust storms, and regional air pollution episodes)
• the assimilation of satellite observations to improve numerical forecast models and provide forecasts where ground-based monitors do not exist
• the assessment of the international or intercontinental transport of air pollution
• the provision of relevant information to the health community and the general public.

Context and pre-conditions

Identify the actors in the scenario. Actors are any persons involved in the scenario.

The actors involved in the scenario come from a wide variety of types of institutions but may be classified into several different roles:

• Earth Observations Providers - including 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, ...)

• Other Related Information Providers - including National, State/Provincial, Local Commerce/Transportation/Energy/Land Use/Health Authorities; Industry; Consultants; Academic and Other Research Institutes

• Air Quality Modelers, Forecasters, and Analysts - including National, State/Provincial, Local Environmental Management Agencies; National Meteorological Agencies; National Space Agencies; Industry; Consultants; Academic and Other Research Institutes; and international scientific cooperative fora or projects (e.g., IGAC, GEMS (and MACS), ECMWF, EMEP, ...)

• Information Management Specialists - including National, State/Provincial, Local Environmental Management Agencies; National Meteorological Agencies; National Space Agencies; National Land Management Agencies; Industry; Consultants; Academic and Other Research Institutes

• Air Quality Management Decision-Makers - including National, State/Provincial, Local Environmental Management Agencies and Multi-lateral Cooperative Fora (such as LRTAP Convention, EANET, Male Declaration, CAI-Asia, Arctic Council, ...); Industry

• Other Consumers of Air Quality Information - including the general public; National, State/Provincial, and Local Health and Emergency Response Authorities; Academic and Independent Research Institutes (including health and environmental impacts research); Mass Media (including television, newspapers, radio, internet, ...)

List, at a summary level, the specific information assumed to be available before the scenario begins.

Information available before scenario begins:

• 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, ...)
• Atmopsheric 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)

List, at a summary level, the specific processing and collaboration functionality assumed needed in the scenario.

• Convenient portals for identifying, accessing, visualizing, and processing observational and modeling data by analysts in near real time and for historical analysis
  • Data sharing and integration functionality including (1) registry/catalog for finding resources (2) standard-based access to spatio-temporal data and metadata, workflow software for integrating Service Components
• Integration of multiple observational data sets to create rich 4-dimensional descriptions of the atmosphere to improve understanding of atmospheric processes
• Comparison of observational data to numerical model estimates to improve numerical model descriptions of historical conditions (events or long-term trends)
• Real-time assimilation of observational data into numerical models to improve numerical forecasts
• 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

Elaborate the steps that result in the creation of decision support products developed in collaboration by the actors.

• Real Time Event Analysis

• Assimilation of Observations for Air Quality Forecasting

• Assessment of International and Intercontinental Transport of Air Pollution

• Provision of Relevant Information to the Health Community and the Public

Use the table to identify the main sequence of events in the scenario, including alternative branch steps.

• Develop connections between existing repositories of air quality related information and tools for integrated analysis of observational data and comparison to models. E.g. HTAP Data Network Proposal
• Develop tools for analysis and assimilation of observational data into atmospheric models and other decision support systems in near real time for producing air quality forecasts. i.e. AIRNow, IDEA
• Develop a virtual observatory for collaborative exploration of large events and ...

1. Designated and voluntary observers will use a 'virtual observatory' to monitor the current aerosol 'weather' situation over their region of interest (e.g. North America, Central America, Europe, Asia? - do we need to spell out regions? ).
2. The observers scan the spatial, temporal aerosol pattern on the real-time satellite images, surface monitors, as well as monitoring the electronic media and private citizen reports.
3. Once an ‘interesting’ smoke event appears, the observers explore the pattern of other peripheral data sources such as weather pattern, trajectories and other monitors to ascertain the emergence of a smoke event.
4. Throughout the event’s emergence, the observers share their observations and views on a shared virtual workspace, including the the deliberations whether to issue alert(s).
5. Using standardized Common Notification Protocol), alert(s) are issued to different groups (Public, Regulatory, Science - see) that may need to act or who are interested in observing/participating in smoke monitoring or response action action.
6. In response to the alert, more intense monitoring and just-in-time analysis is initiated. This includes additional sampling, high resolution targeted smoke source/dispersion modeling, harvesting of other real-time data resources etc.
7. As the smoke event evolves, a virtual workgroup of analysts summarizes the smoke situation, including sources, transport, aerosol pattern, forecast and impact in a manner suitable for multiple user communities, Public, Regulatory and Science.
8. Based on those reports and other input, during the smoke event, a multiplicity of decisions and actions are executed by Public, Regulatory and Scientific decision makers.
9. Following the smoke event, the event is evaluated for its impact, consequences and possibly for detailed retrospective analysis.

Related Links

• AIP AQ Scenario A: Smoke and Dust
• AIP AQ Scenario C: forecasts