1. Spatial and Temporal Pattern of
Air Pollution over China Based on
Remote Sensing Observations
Rudolf B. Husar
With
Li Du, Erin Robinson
Washington University, St. Louis, MO, USA
Seminar at Fudan University,
May 28, 2010, Shanghai, China
2. Atmospheric Aerosol Challenge:
Characterization of Aerosols
Dimension
Abbr.
Data Sources
Spatial dimensions
X, Y
Satellites, dense networks
Height
Z
Lidar, soundings
Time
T
Continuous monitoring
Particle size
D
Size-segregated sampling
Particle Composition
C
Speciated analysis
Particle Shape/Mixing
S
Microscopy, Source Type
•
•
Aerosol complexity is due 7-dim. data space
The ‘aerosol dimensions’ D, C, S determine the
effects on health and climate
Aerosol concentration:
a (X, Y, Z, T, D, C, S)
4. •
Technical Challenge:
Characterization
PM characterization requires many different instruments and analysis tools.
• Each sensor/network covers only a fraction of the 7-Dim PM data space.
Satellite-Integral
Satellites, integrate over height,
size, composition, shape…
dimensions
These data need de-convolution of
the integral measures
5. Satellite Remote Sensing Since 1972
•
•
•
First satellite aerosol paper, Francis Parmenter, 1972
Qualitative surface-satellite aerosol relationship shown, 1976
Focus on regional ‘hazy blobs’, sulfate pollution
Regional Haze
Lyons W.A., Husar R.B. Mon. Weather Rev. 1976
SMS GOES June 30 1975
6. Satellites show the synoptic aerosol pattern
and provide rich spatial context …
e.g. pollution in valleys.
Jan 10, 2003, SeaWiFS
Dec 19, 2007, MODIS
8. Asian Dust Cloud over N. America
In Washington State, PM10
100 µg/m3
concentrations exceeded 100 µg/m3
Asian Dust
Hourly PM10
On April 27, the dust cloud arrived in
North America.
Regional average PM10
concentrations increased to 65 µg/m3
33. Summary
•Each data set has limitations, but gives self-consistent global-scale observations
• More detailed measurements are essential for the understanding
•There are still enormous challenges in integrating multi-sensory data for
characterizing aerosols.
Combining global-scale remote sensing observations with detailed local
observations and research conducted in China could yield faster
progress.
34. International Collaboration Opportunity:
Global Observing System of Systems (GEOSS)
Pooling of Earth Observations nine Societal Benefit Areas
Any Dataset
Serves Many
Communities
Any Problem
Requires Many
Datasets
New International Program - China is a Co-Chair of GEOSS EE
Notes de l'éditeur
The ATS was followed by the Synchronous Meteorological Satellite (SMS), the first series of geosynchronous weather satellites. SMS-1 was launched from Cape Canaveral, FL on May 17, 1974. It was the first operational satellite capable of detecting meteorological conditions from a fixed location
