Georgia Institute of Technology Atlanta, GA [email protected] Air Quality and Human Health 2004...

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[email protected] Georgia Institute of Technology Atlanta, GA Air Quality and Human Health 2004 Olympic Games Athens, Greece Karsten Baumann Georgia Institute of Technology School of Earth & Atmospheric Sciences Research Opportunities

Transcript of Georgia Institute of Technology Atlanta, GA [email protected] Air Quality and Human Health 2004...

[email protected]

Georgia Institute of TechnologyAtlanta, GA

Air Quality and Human Health

2004 Olympic GamesAthens, Greece

Karsten BaumannGeorgia Institute of Technology

School of Earth & Atmospheric Sciences

Research Opportunities

[email protected]

Georgia Institute of TechnologyAtlanta, GA

Emergency room visits for treatment of asthma increase by 30-40 % when ambient ozone levels are elevated. The US EPA estimates that more than 110 million people reside in counties where the air is

consistently unhealthy due to periodic ozone pollution.

Asthma Epidemic

The percentage of the US population with the disease has nearly doubled since 1980. In 2000,

~11 million people suffered an asthma attack. Sources: Morbidity & Mortality: 2002 Chart Book on Cardiovascular, Lung, and Blood Diseases; National Institutes of Health, National Heart, Lung, and Blood Institute, 2002. Latest Findings on National Air Quality: 2001 Status and Trends; EPA 454/K-02-001; US EPA Office of Air Quality Planning and Standards (OAQPS); September 2002.

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Georgia Institute of TechnologyAtlanta, GA

Athens 2004 Air Quality Study, 1997Moussiopoulos & Papagrigoriou

Aristotle University Thessaloniki & Laboratory of Heat Transfer and Environmental Engineering (LHTEE),

Thessaloniki, Greece

• Renewal of the Athenian vehicle fleet • Exclusion of most polluting passenger cars • Reducing [NOx] from heavy-duty vehicles• Minor effects from pedestrian zones

Urban Air Pollution

IS THIS SUFFICIENT ?

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Georgia Institute of TechnologyAtlanta, GA

Potential US Contributions

• Comprehensive characterization of air quality– Baseline measurements 3 weeks before and 3 weeks after Olympics – Indoor and outdoor measurements / modeling– All measurements before, during, and after the games– Local population and athlete exposure to pollution

• Relate pollutant levels to human health effects• Model / monitor effects of emissions reductions• Long-term monitoring to the benefit of Athens

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Georgia Institute of TechnologyAtlanta, GA

The US Research Team

Centers for Disease Control

Centers for Disease Control

Emory University Asthma Clinic

Emory University Asthma Clinic

Research Institute (GTRI)Research Institute (GTRI)

•NEXLASER Ozone and aerosol lidar• Indoor air quality monitors•NEXLASER Ozone and aerosol lidar• Indoor air quality monitors

Georgia Institute of Technology

Georgia Institute of Technology

Air Resources Engineering Center (AREC)Air Resources Engineering Center (AREC)

•Atmospheric chemistry•Air quality monitoring•Aerosol characterization•Forecasting•Air quality modeling•Emissions from motor vehicles•Emissions modeling

•Atmospheric chemistry•Air quality monitoring•Aerosol characterization•Forecasting•Air quality modeling•Emissions from motor vehicles•Emissions modeling

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Georgia Institute of TechnologyAtlanta, GA

AREC Team

• Baumann, EAS, director, lab & field operations• Bergin, EAS/CEE prof, aerosol optical properties• Chang, EAS, Sr RS, urban AQ modeling• Nenes, EAS prof, heterogeneous modeling• Odman, CEE, Sr RE, adaptive grid modeling• Russell, CEE head, emissions UAM• Weber, EAS, prof, aerosol in situ R&D• Zheng, EAS, RS, lab & field operations, CMB

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Georgia Institute of TechnologyAtlanta, GA

AREC Measurements

• Karsten Baumann, [email protected]– Aerosol characterization

• High-res precurser gases and low-res PM composition

– Air quality monitoring network in TN and GA• Seasonal differences in AQ character {transport & formation}

– Atmospheric chemistry and aerosol transformation(SOS, SCISSAP, ChinaMAP, FAQS, TexAQS, PERCH) • Mobile laboratory for coordinated integrated deployments• Vertical gradients utilizing high-rise buildings and towers

– Diagnostic analyses and collaborative evaluations• Source identification, BL transport, photochemical transformation

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Georgia Institute of TechnologyAtlanta, GA

Benefits of Network Measurements34.6

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Atlanta

FAQS measurement sites significant point sources point sources w/ CO:NOx > 1

Wind Roses with avg [PM2.5] for

summer & winter in µg m-3

and wind frequency in %.

20x20 km

WansleyYates

Bowen

McDonough

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Georgia Institute of TechnologyAtlanta, GA

Benefits of Detailed Measurements

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July 2001 (EST)

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, deg

N C

O, p

pb

RH

, %

TEOM UnID OOE

= 0.4 OC Others LOA OC EC NH4 NO3 SO4 pilsSO4

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Georgia Institute of TechnologyAtlanta, GA

Benefits … Towards SOA

Regional Difference: Higher OM/OC and OC/EC at more rural site!Seasonal Difference: Lower OM/OC and higher OC/EC in winter.

Baumann et al., JGR in press

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Georgia Institute of TechnologyAtlanta, GA

High-Rise O3 levels are significantly higher early mornings and lower at midday

http://www.utexas.edu/research/ceer/texaqs/

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P

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bv

)00:00 06:00 12:00 18:00 00:00

Δ-O3

center 67 %

Benefits of High-Rise PlatformO3

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Georgia Institute of TechnologyAtlanta, GA

Benefits of High-Rise PlatformPM2.5

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TE

OM

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ss

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-3)

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P

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-3)

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Δ-PM2.5

center 67 %

Positive vertical [PM2.5] ‘gradients’ favored more often at night than at day

http://www.utexas.edu/research/ceer/texaqs/

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Georgia Institute of TechnologyAtlanta, GA

AREC Measurements

• Mike Bergin, [email protected]– Aerosol characterization

• Linking physical, optical and chemical properties• Natural background versus anthropogenic influence

– Air quality and visibility• Track changes in mode and hygroscopicity (sp vs ap)

• Link observed changes to air mass history and transport

– Climate change• Less uncertain aerosol parameters for climate models• Effects on regional climate, BL stability, photosynthesis• Spatial and temporal variations in radiative forcing

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Georgia Institute of TechnologyAtlanta, GA

Aerosols Regional to Global Effects

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Georgia Institute of TechnologyAtlanta, GA

Major Findings

Tasmania—predominance of seasalt aerosol indicative of a true background marine site

• Wavelength independence, predominance of coarse mode, strongly hygroscopic/deliquescent aerosol, light scattering >> light absorption

Portugal and Atlanta—anthropogenic perturbation of aerosol results in factor of 5-10 greater impact on radiative transfer

• Strong wavelength dependence, predominance of fine mode, suppressed hygroscopic growth, light scattering > light absorption

Nepal—strong seasonal cycle with spring-time peak comparable to urban areas and possible monsoon impacts

• Low concentrations during monsoon, Pre-monsoon “dusty period with evidence of long-range transport of mineral (Saharan?) dust

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Georgia Institute of TechnologyAtlanta, GA

AREC Measurements

• Rodney Weber, [email protected]– Aerosol chemical characterization (PILS)

• High-resolution PM2.5 composition at ground & airborne

– Source apportionment from transient events• Mobile versus point sources, biomass burning, dust

– Aerosol chemistry w/in large field campaigns(SCISSAP, FAQS, TexAQS, ACE-Asia, TRACE-P) • Source apportionment in plumes (see transients above)• Chemical transformation of transported aerosol (box model)• New particle formation (nucleation)

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Georgia Institute of TechnologyAtlanta, GA

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sol M

ass

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Eastern Standard Time

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A PM2.5Sulfate OC*1.4 EC

Transient Events in Atlanta

Midday sulfate peaks from downmixed power plant plumes.

Morning rush hour EC/OC.

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Georgia Institute of TechnologyAtlanta, GA

Sources for Atlanta Sulfate

Title

Atlanta

Night

Primary OCp, EC morning rush NO

3-

Title

Atlanta

Day

SO2

SO2

SO4

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few SO4

2- eventscars + trucks

SO4

2- Events

T

inversion

Min, OCp + EC

cars + trucks

Most intense during stagnation events. Links to health effects?! (Weber et al., JAWMA in Jan 2003)

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Georgia Institute of TechnologyAtlanta, GA

• Mixed plumes - near northern coastal areas of China, Korea, and Japan.

• On average, about 305% of the fine PM mass in the mixed plumes is from BB emissions.

• K+ is good tracer for BB.

• Molar ratio of dK+/dSO42-

useful to estimate relative influence of BB on PM2.5 mass in mixed plumes.

• Limitation of the method– Dust contribution– Check for correlations

Ma et al., JGR, submitted 2002

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% Biomass contribution 0-20 20-40 40-80 80-100

F10 10015%

F146210%

F19182%

TRACE-P Biomass Burning

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Georgia Institute of TechnologyAtlanta, GA

AREC Measurements

• Mei Zheng, [email protected]– Aerosol particle-phase organics speciation

• GC-MS analysis of high-volume samples

– Field campaigns in SE-US and China

(ChinaMAP, PRDS, PERCH, ACE-Asia) – Chemical mass balance (CMB) receptor model

• Source apportionment to PM2.5 and OC

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Georgia Institute of TechnologyAtlanta, GA

N

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W10 20 µg m

-3

Detect > 100 POC speciesn-alkanes, branched alkanes, cycloalkanesn-alkanoic acids, n-alkenoic acidsalkanedioic acidsPAHs, oxy-PAHs

retenesteraneshopanesresin acids

pimaric acidabietic acidsandaracopimaric acid

aromatic acidslevoglucosan

Ongoing Joint PBS*

*) US-DOD funded “Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities” 2002.

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Georgia Institute of TechnologyAtlanta, GA

Pensacola, FL October 1999

Other organic carbon30%

Wood combustion

39%

Meat cooking 6%

Vegetative detritus

2%

Gasoline exhaust

3%

Diesel exhaust

20%

Source Contributions to OC

Zheng et al., ES&T 2002

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Georgia Institute of TechnologyAtlanta, GA

AREC Modeling

• Mike Chang, [email protected]://www.cure.gatech.edu/faqs.asp

• Thanos Nenes, [email protected]– Inverse modeling– Urban Airshed Model (UAM)-AERO

• successful in LA 1987 SCAQS (Lurmann et al., 1997)• SAPRC-90 gas phase mechanism (n=133, R=130)

• Online aerosol dynamics with inorganic component resolved (H2O, Na, Cl, NO3, NH4,SO4), incl OC/EC

• Evolution of aerosol described by mass balance– ISORROPIA (Nenes et al., 1998)

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Georgia Institute of TechnologyAtlanta, GA

AREC Modeling

• Thanos Nenes, [email protected]– UAM-AERO (continued)

• Collaboration with the University of the Aegean– applied to simulate the atmospheric conditions in the Athens

basin (Sotiropoulou et al., in preparation).

– CAMx (www.camx.com)• “Next-generation” modeling system

– SAPRC-99 improved from version 90– Parallel processing & nested grid– Sotiropoulou et al., in preparation

– Both can be nested into larger scale models

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Georgia Institute of TechnologyAtlanta, GA

AREC Modeling

• Ted Russell, [email protected]

• Talat Odman, [email protected] http://environmental.gatech.edu/~odman/page2.html

– Emissions modeling• Emissions inventory & inverse modeling• Onboard measurements

– Regional air quality impacts modeling• Sensitivities to changes in anthropogenic emissions• Advanced adaptive grid modeling • Sub-regional pollutants transport & transformation

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Georgia Institute of TechnologyAtlanta, GA

Airport Blvd.Aviation Pkwy.

Weston Pkwy.Morrisville

Pkwy.

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(g/s

ec)

Trip Duration (%) -43

Ave. Speed (%) +137

Total Stops (%) -84

HC Emissions (%) -59

NO Emissions (%) -57

CO Emissions (%) -60

Allows measurement of vehicle emissions and engine parameters under real-world conditions

Mobile EmissionsMobile Emissions

On-Board Monitoring (A.Unal)

Effect of Traffic Congestion Effect of Traffic Congestion on Vehicle Emissionson Vehicle Emissions

Enables finding relationships between vehicle emissions and traffic parameters

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Georgia Institute of TechnologyAtlanta, GA

0 1E+07 2E+07 3E+07 4E+070

1E+07

2E+07

3E+07

4E+07

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Computer Simulation with

Air Quality Model

Controlled Burningat Military Base

Adaptive Grid Sensitivity Analysis

Impact to Downwind City

StrategyDesign

Direct sensitivity analysis for predicting the air quality impacts of anthropogenic activities.

Adaptive Grid Modeling

Part of DOD-funded “Study of Air Quality Impacts Resulting from Prescribed Burning on Military Facilities” 2003

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Georgia Institute of TechnologyAtlanta, GA

Adaptive Grid Air Quality Model

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Georgia Institute of TechnologyAtlanta, GA

Superior O3 Predictions

Sumner Co., TN

Graves Co., KY

0.0

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Time starting from 7/14/1995 (hour)

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Observation 4-km Static 8-km Static Adaptive

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Georgia Institute of TechnologyAtlanta, GA

Sensitivity of O3 to NOx Emissions

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Georgia Institute of TechnologyAtlanta, GA

MINOS Asian Monsoon Plume modeled by MATCH-MPIC

Additional AREC Contributors

=> Lawrence et al., Atmos. Chem. Phys. Discuss., 2002: http://www.atmos-chem-phys.org

See also Lelieveld et al., Science 298, 2002

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Georgia Institute of TechnologyAtlanta, GA

Additional AREC Contributors

• Judy Curry, EAS Chair, [email protected]– Robotic Aircraft UAV (Aerosonde, Seascan)

• Small Size• Long Range & Endurance• Autonomous Operations• Automated Missions • Payload 2 to 5 kg• Sensor R&D• Ample Power > 100 watts• Real-Time Full-Motion Video

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Georgia Institute of TechnologyAtlanta, GA

Robotic Aircraft UAV

• Color Video System – Pan / Tilt / Zoom– Inertial Stabilization– Image Processing

Eliminate Unwanted Motion

– Analog Link to 30 Miles– Longer Range with Digital

Compression

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Georgia Institute of TechnologyAtlanta, GA

Robotic Aircraft UAV

US Patent 6,264,140

International Patents in Process

Skyhook Retrieval System for launch and retrieval over sea

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Georgia Institute of TechnologyAtlanta, GA

Proposed GT Measurements

• Complement existing monitoring network • Establish comprehensive sites: urban, rural, high-rise, hill-top 

– Identify rural location– Top of downtown high-rise best represents urban AQ– Olympic Village site if possible– Ideally, upgrade existing urban site in collaboration with locals  – Conduct advanced measurements 

• Evaluate effects of public transportation mediation– relate AQ conditions to traffic activities

• Analyze visibility degradation– Poor visibility is noticed by the public and associated with air pollution– Sources of degradation will be identified and quantified– Information useful in health impact analysis

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Georgia Institute of TechnologyAtlanta, GA

Proposed GT Modeling

• Simulate Athens air quality during Olympics– Apply model with direct source-impact tool– Show impact of specific sources on ozone and PM

species (diesel, biogenic, cooking, etc.)– Validate emissions inventory

• Work with health scientists– Link emissions sources to air quality to health– Model exposure at finer scale than measurements

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Georgia Institute of TechnologyAtlanta, GA

Research Topics

Measurements•Air Quality

•Indoor •Outdoor

•In Situ•Lidar•Satellite

•Meteorology•Emissions Surveys•Traffic Monitoring•Health Monitoring

Modeling•Air Quality•Emissions•BL transport•Physical-Chemical

Transformation•Forecasting•Meteorology•Exposure

Health•Asthma in Athletes•Asthma in Athens

Population•Relationship of

Exposure to Respiratory and Cardiac Disease

•Epidemiology

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Georgia Institute of TechnologyAtlanta, GA

US Research Team

• Gary G. Gimmestad – GT/GTRI– Senior Faculty Leader in remote sensing technology

development

• Leanne L. West – GT/GTRI– Co-Director of Health Science and Technology Research,

UV lidar systems

• Charlene Bayer – GT/GTRI– Indoor air quality, asthma triggers, exposure

• Ted Russell – GT/CEE– Air quality modeling, emission inventories, visibility,

exposure

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Georgia Institute of TechnologyAtlanta, GA

US Research Team

• Karsten Baumann – GT/EAS– Field measurements coordinator, BL transport, physical-

chemical transformation of atmospheric constituents

• W. Gerald Teague – Emory Asthma Center– Relationship of air quality problems to asthma attacks

• Michael S. Friedman – CDC– Effects of air quality problems on human health

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Georgia Institute of TechnologyAtlanta, GA

Anticipated Benefits

• Better understanding of Athens air quality• Demonstration of improvement strategies• Improved forecasting• Link between sources and health• Insight for “Green Olympics” in Beijing 2008

These benefits will help all cities with air quality problems, give insights to improving human health, and will become part of the International Olympics Legacy