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

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
Enviro.
Agency
Ambient
Pollutant
Concentrations
Satellite
Agency
Pollutant
Column
Densities
Met
Agency
met data
Modeling
Community
models
Decision Support
integration
of multiple
observational
datasets
Sign
Policy
international
Makers
agreement?
Air Quality
Analysts
Was pollution
event due
AQ
Managers to transport
from afar?
comparison
of observations,
models
REAL TIME
assimilation of
observations
into models
Air Quality
Forecasters
Public
REAL TIME
distribution of AQ
processed data,
maps
These upstream connections
& capabilities aren’t currently
operational and interoperable
Is it healthy
to go for
a run now?
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
Air Quality & Health Scenario: Actors
• 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, …
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 scenario
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
X
X
X
X
X
X
Assessing intercontinental transport
X
X
X
X
X
Merging satellites,
in-situ, model data
X
X
X
AQ nowcasts,
forecasts to public
X
X
X
X
X