Transcript SOA_AQAnalysis_ThesisPPT

Collaborative Integration of Satellite and Surface
Data for Characterization of Aerosol Events
E. M. Robinson
Advisor, R. B. Husar
2010 M.S. Thesis
St. Louis, MO, Nov. 3, 2010
Illustrate the use of multi-sensory data
Technical Challenge: Characterization
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PM characterization requires many sensors, sampling methods and analysis
tools
Each sensor/method covers only a fraction of the 7-Dimensional PM data
space.
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Spatial dimensions (X, Y, Z)
Temporal Dimensions (T)
Particle size (D)
Particle Composition ( C )
Particle Shape (S)
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Most of the 7 Dim PM data space is extrapolated from sparse measured data
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Others sensors integrate over time, space, chemistry, size etc. .
Satellite-Integral
Satellites, have high spatial resolution but integrate over height
H, size D, composition C, particle shape
Kansas Agricultural Smoke, April 12, 2003
Fire Pixels
PM25 Mass, FRM
Organics
65 ug/m3 max
35 ug/m3 max
Ag Fires
SeaWiFS, Refl
SeaWiFS, AOT Col
AOT Blue
Hurdles
“The user cannot find the data;
If he can find it, cannot access it;
If he can access it, ;
he doesn't know how good they are;
if he finds them good, he can not merge them with other data”
The Users View of IT, NAS 1989
To overcome the first two hurdles need:
1. Service oriented architecture
2. Standards for finding and accessing the data
3. Open, collaborative space to coordinate work
SOA Actions
Actions:
Register– Discover -Access
User
Provider
Broker
The data reuse is possible through the service oriented architecture of GEO
SOA Actions
Actions:
Register– Discover -Access
Broker
Provider
User
The data reuse is possible through the service oriented architecture of GEO
Preparation of Data and Metadata
GEOSS
Clearinghous
e
Access
Provider
User
Data Protocol
Data Metadata
WMS, WCS (netDCF
CF) + conventions
Preparation of Data and Metadata
GEOSS
Clearinghous
e
Register
Metadata
Provider
User
Data Protocol
Data Metadata
WMS, WCS (netDCF
CF) + conventions
Metadata
ISO 19115 subset for
Geospatial Data
Air Quality Metadata Record
GEOSS
Clearinghouse
Discover, Get Access
Key
Provider
User
Metadata for Finding and Accessing Data
Data
Binding
OGC CSW OGC CSW ISO 19115 Metadata Air Quality
Queryable Returnable CSW Profile Description Specific
Exceptional Event Rule:
An air quality exceedance that would not have occurred but for the presence
of a natural event.
Transported Pollution
Natural Events
Human Activities
Transported African, Asian
Dust; Smoke from Mexican
fires & Mining dust, Ag.
Emissions
Nat. Disasters.; High Wind
Events; Wild land Fires;
Stratospheric Ozone;
Prescribed Fires
Chemical Spills; Industrial
Accidents; July 4th; Structural
Fires; Terrorist Attack
Satellite remote sensors provide key observations for Exceptional Events
May 2007 Georgia Fires
An actual Exceptional Event Analysis for EPA
May 5, 2007
May 12, 2007
Observations Used:
OMI NO2 Quantifies the NO2 Emission
Sweat Water fire in S.
Georgia (May 2007)
3. Evidence: Aerosol Composition
Sulfate
Organics
Measured
Sulfate
Organics
Modeled
5. The Exceedance would not Occur, But For the Exceptional
Event
Social Media and Air Quality
SOA Actions
Actions:
Register– Discover -Access
Broker
Provider
User
The data reuse is possible through the service oriented architecture of GEO
Social Media Listening for Air Quality
RSS
Feeds
Air Twitter Aggregator
Air Twitter Filter
ESIPAQWG
Air Twitter – Event Identification
August 2009, Los Angeles
Fires
Normal Weekly Trend
Air Quality EventSpaces
EventSpaces are community workspaces on the ESIP wiki that are
created to describe the Event
Science Data
Social Media
Google Analytics Results: August LA Fires
580
Views
Google Analytics Results: August LA Fires
Future Work: GEOSS Suitable Infrastructure