2006-10-16 u wisconsin seminar

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Thoughts on Atmospheric Aerosols: Science, Air Quality and Informatics Rudolf B. Husar CAPITA, Washington University Seminar Presented at U. Wisconsin, Madison, WI, October 16, 2006

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Page 1: 2006-10-16 U Wisconsin Seminar

Thoughts on Atmospheric Aerosols:Science, Air Quality and Informatics

Rudolf B. Husar

CAPITA, Washington UniversitySeminar Presented at U. Wisconsin,

Madison, WI, October 16, 2006

Page 2: 2006-10-16 U Wisconsin Seminar

Major Biogeochemical Processes/Flows Visualized by Aerosols:

Volcanoes

Dust storms Fires

Anthropogenic pollution

Aerosols as Indicators of Global Processes and Change

Radiative Climate Human Health Visibility Acid Rain……

As aerosols pass through the atmosphere, the effects include:

Page 3: 2006-10-16 U Wisconsin Seminar

Complex Physico-Chemical Properties:

Particle Size

Particle Composition, Shape

Page 4: 2006-10-16 U Wisconsin Seminar

Scientific Challenge: Characterization of Aerosols

• Gaseous concentration: g (X, Y, Z, T)

• Aerosol concentration: a (X, Y, Z, T, D, C, F, M)

• The ‘aerosol dimensions’ size D, composition C, shape F, and mixing M determine the impact on health, and welfare.

Dimension Abbr. Data SourcesSpatial 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/Form F Microscopy

Ext/Internal Mixture M Microscopy

Aerosol complexity is due multi-dimensionality

Characterization requires 6-8 independent dimensions

Page 5: 2006-10-16 U Wisconsin Seminar

Technical Challenge: Characterization

• PM characterization requires many different instruments and analysis tools.

• Each sensor/network covers only a fraction of the 8-D PM data space.

• Most of the 8D PM pattern is extrapolated from sparse measured data

Satellite-IntegralSatellites, integrate over height, size, composition, shape…dimensions

These data need de-convolution of the integral measures

Page 6: 2006-10-16 U Wisconsin Seminar

Global Earth Observing System of Systems (GEOSS) Challenges:

Integration of 6 (8) – Dimensional Multi-sensory Data and Models

Page 8: 2006-10-16 U Wisconsin Seminar

Regulatory Challenges:Natural Aerosols

Natural haze - windblown dust, biomass smoke and other natural processes

Man-made haze - industrial activities AND man-perturbed smoke and dust emissions

Man-made Emissions Eliminated

Natural Conditions by 2064

Page 9: 2006-10-16 U Wisconsin Seminar

Just like the human eye, satellite sensors detect the total amount of solar radiation that is reflected from the earth’s surface (Ro) and backscattered by the atmosphere from aerosol, pure air, and clouds. A simplified expression for the relative radiatioin detected by a satellite sensor (I/Io) is:

I / Io = Ro e- + (1- e-) P

Satellite Detection of Aerosols

Today, geo-synchronous and polar orbiting satellites can detect different aspects of aerosols over the globe daily.

where is the aerosol optical thickness and P the angular light scattering probability.

Height Type Size Angle Shape

dHdCdDdPdSSPDCHI

Page 10: 2006-10-16 U Wisconsin Seminar

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 HazeLyons W.A., Husar R.B. Mon. Weather Rev. 1976

SMS GOES June 30 1975

Page 11: 2006-10-16 U Wisconsin Seminar

AVHRR satellite optical depth climatology over the oceans, 1988-90

Husar, Prospero, Stove, 1997

Surprise: Small Sulfate Plume, Spring, Summer Only

Page 12: 2006-10-16 U Wisconsin Seminar

MISR Seasonal AOT (MISR Team)

Major smoke emission regions by season

Page 13: 2006-10-16 U Wisconsin Seminar

SeaWiFS AOT – Summer 60 Percentile1 km Resolution

Page 14: 2006-10-16 U Wisconsin Seminar

Satellite Data Increases Spatial Resolution

PM25 Surface Conc. JJA

SeaWiFS AOT. JJA

SeaWiFS AOT. JJA, Terrain

AOT in Valleys

Page 15: 2006-10-16 U Wisconsin Seminar

Satellite Summary

• Satellite data have aided the science of Particulate Matter since the 1970s

• Satellite data have supported PM air quality management since the 1990s.

• Past satellite data helped the qualitative description of PM spatial pattern

• Quantitative satellite data use and fusion with surface data is still in infancy

• Satellite data applications will require collaboration across disciplines

Page 16: 2006-10-16 U Wisconsin Seminar

Aerosol Species Monitoring Growth (1999-03)

• Daily valid station counts for sulfate has increased from 50 to 350

• About 250 sites sample every 3rd day, 350 sites every 6th day

Nitrate

Sulfate Sites 99-03

IMPROVE + EPA Sulfate

Page 17: 2006-10-16 U Wisconsin Seminar

Origin of Fine Dust Events over the US

Gobi dust in springSahara in summer

Fine dust events over the US are mainly from intercontinental transport

Fine Dust Events, 1992-2003ug/m3

Page 18: 2006-10-16 U Wisconsin Seminar

Asian Dust Cloud over N. America

On April 27, the dust cloud arrived in North America.

Regional average PM10 concentrations increased to 65 g/m3

In Washington State, PM10 concentrations exceeded 100 g/m3

Asian Dust 100 g/m3

Hourly PM10

Page 19: 2006-10-16 U Wisconsin Seminar

During the trans-Pacific transit the dust plume was also tracked independently by Washington University and University of Wisconsin using GMS-5 and GOES-9 geostationary satellites, respectively.

GMS-5 Image of Dust over the Central Pacific on April 24

GOES-9 images of Dust over the Central Pacific on April 24

Page 20: 2006-10-16 U Wisconsin Seminar

Supporting Evidence: Transport Analysis

Satellite data (e.g. SeaWiFS) show Sahara Dust reaching Gulf of Mexico and

entering the continent.

The air masses arrive to Big Bend, TX form the east (July) and from the west

(April)

Page 21: 2006-10-16 U Wisconsin Seminar

Sahara PM10 Events over Eastern USMuch previous work by Prospero, Cahill, Malm, Scanning the AIRS PM10 and IMPROVE chemical

databases several regional-scale PM10 episodes over the Gulf Coast (> 80 ug/m3) that can be attributed to Sahara.

June 30, 1993

The highest July, Eastern US, 90th percentile PM10 occurs over the Gulf Coast ( > 80 ug/m3)

Sahara dust is the dominant contributor to peak July PM10 levels.

July 5, 1992

June 21 1997

Page 22: 2006-10-16 U Wisconsin Seminar

Seasonal Average Fine Soil (VIEWS database, 1992-2002)

• Fine soil concentration is highest in the summer over Mississippi Valley, lowest in the winter• In the spring, high concentrations also exists in the arid Southwest (Arizona and Texas)• Evidently, the summer Mississippi Valley peak is Sahara dust while the Spring peak is from local sources

Page 23: 2006-10-16 U Wisconsin Seminar

Mystery Winter Haze:Natural? Nitrate/Sulfate? Stagnation?

Mystery not Solved, too Complicated, Calls for Multidisciplinary Community Analysis

Contributed by the FASNET Community, Sep. 2004

Correspondence to R Husar , R Poirot

Coordination Support by

Inter-RPO WG Fast Aerosol Sensing Tools for Natural Event Tracking, FASTNETNSF Collaboration Support for Aerosol Event Analysis

NASA REASON CoopEPA -OAQPS

AIRNOW PM25 - February

Page 24: 2006-10-16 U Wisconsin Seminar

Midwest HazeCam ImagesJan 27-Feb 3, 2005

• The images were part of the Midwest HazeCam Console of FASTNET project.

Page 25: 2006-10-16 U Wisconsin Seminar

Seasonal PM25 by Region

Page 26: 2006-10-16 U Wisconsin Seminar

FRM PM25 Monthly Concentration

• Monthly average FRM PM25 are shown as circle and contour (Blue: 0; Red: 25 g/m3)• The Feb/Mar peak is clearly evident in the Midwest region; also in January• Hence, there is some deviation in peak location and time among the networks

JAN FEB MAR APR

MAY JUN JUL AUG

SEP OCT NOV DEC

EPA AIRS 1999-2002

Page 27: 2006-10-16 U Wisconsin Seminar

Seasonal Nitrate, VIEWS 2000-2004

JAN

DEC

FEB MAR APR

MAY JUN JUL AUG

SEP OCT NOV

Eastern US Nitrate - Daily Average

‘Nitrate Events’

Page 28: 2006-10-16 U Wisconsin Seminar

Smoke over the Eastern US

• Major contributor to aerosol Events• Key tracers are aerosol organics

Page 29: 2006-10-16 U Wisconsin Seminar

Kansas Agricultural Smoke, April 12, 2003

Fire Pixels PM25 Mass, FRM65 ug/m3 max

Organics35 ug/m3 max

Ag Fires

SeaWiFS, Refl SeaWiFS, AOT Col AOT Blue

Page 30: 2006-10-16 U Wisconsin Seminar

Informatics:The Researcher/Analyst’s Challenge

“The researcher cannot get access to the data;if he can, he cannot read them; if he can read them, he does not know how good they are;and if he finds them good he cannot merge them with other data.”

Information Technology and the Conduct of Research: The Users ViewNational Academy Press, 1989

These resistances can be overcome through a distributed system that catalogs and standardizes the data and provides

tools for data manipulation and analysis.

Page 31: 2006-10-16 U Wisconsin Seminar

Smoke Plumes over the Southeast

• Satellite detection yields the origin and location is the shape of smoke plumes

• The influence of the smoke is to increase the reflectance ant short wavelength (0.4 mm)

• At longer wavelength, the aerosol reflectance is insignificant.

R 0.68 m

G 0.55 m

B 0.41 m

0.41 m

0.87 m

Page 32: 2006-10-16 U Wisconsin Seminar

‘Natural’ Aerosols: Biomass Smoke

Satellite data show numerous small fires in the Southeast

The type of these fires is not known. Prescribed/agricultural burning? Wild fires?

Issue: How does one space-time aggregate such a highly variable emission?

PM2.5 conc., smoke pattern and SeaWiFS image of plumes originating from Kentucky, Nov 15, 1999.

More details here here

Nov 15, 1999

Oct 5, 1998 Oct 5, 1998

Smoke Plumes Smoke Plumes

Regional Smoke?

Page 33: 2006-10-16 U Wisconsin Seminar

Seasonal Pattern of Dust Baseline and Events

• The dust baseline concentration is has a 5x seasonal amplitude from 0.2 to 1 ug/m3• The dust events (determined by the spike filter) occur in April/May and in July• The April/May and July dust peaks are due to the events

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

01/01/92 02/20/92 04/10/92 05/30/92 07/19/92 09/07/92 10/27/92 12/16/92

EventsBaselineTotal