Atmospheric Aerosols: Health, Environmental and Policy of Particulates in the US-Mexico Border Region

July 14, 2005

2003 Field Measurement Campaign

Mexico City Metropolitan Area

Mario Molina

University of California, San Diego

Mario Molina Center, Mexico City

Summary of the First Phase of the Mexico City Air Quality Program

Chapter 1. Air Quality Impacts: A Global and Local Concerns

Chapter 2. Cleaning the Air: A Comparative Overview

Chapter 3. Forces Driving Pollutant Emissions in the MCMA

Chapter 4. Health Benefits of Air Pollution Control

Chapter 5. Air Pollution Science in the MCMA: Understanding Source-Receptor Relationships Through Emissions Inventories, Measurements and Modeling

Chapter 6. The MCMA Transportation System: Mobility and Air Pollution

Chapter 7. Key Findings and Recommendations(Kluwer Academic Publishers, 2002)

Visibility in the

Mexico City Metropolitan Area

Estimated Health Benefits of a 10% Reduction of Pollution Levels in the MCMA

PM10 Background Rate (case-persons-yr)

Risk Coefficient(% per 10µg/m3)

Risk Reduction (cases/yr)

Cohort Mortality

10/1000 3 2000

Time Series Mortality

5/1000 1 1000

Chronic Bronchitis

14/1000 10 10 000

OzoneBackground Rate (case-persons-yr)

Risk Coefficient (% per 10µg/m3)

Risk Reduction (cases/yr)

Time Series Mortality

5/1000 0.5 300

Minor Restricted Activity Days

8000/1000 1.0 2,000,000

Chapter 4. Health Benefits of Air Pollution Control: John Evans, Jonathan Levy, James Hammitt, Carlos Santos Burgoa, and Margarita Castillejos (2002).

Air pollution harms children's lungs for life

Children exposed to higher levels of particulate matter and other air pollutants had significantly lower lung function

Other transport

10%Private

cars12%

Buses15%

HD-diesel Vehicles

32%

Vehicles< 3 ton 8%

Other5%

Soil erosion

6%

Industrialcombustion

3%

Electricitygeneration

3%

Manufacturingindustry 6%

Other transport

7%

Other7%

Metals industry

9%

Buses9%

Private cars9%

Soil erosion

17%

HD- diesel vehicles20%

Chemical industry

4%

Vehicles< 3 ton 5%

Manufacturingindustry 13%

PM2.5 PM10

Percentage of emissions from the MCMA in 2000 by source category

Summary of MCMA-2003 Field Measurement Campaign

• Exploratory mission (February 2002)

• Intensive 5-week field measurement (Spring 2003)

• Special Session on “Megacity Impacts on Air Quality” at the Fall 2004 AGU Meeting, San Francisco, CA

• Special Issue of the MCMA 2003 Campaign in ACP (Atmospheric Chemistry and Physics)

• NARSTO sanctioned field campaign – data will be posted on NARSTO website

• Photochemical/Transport Modeling in progress (CIT, MM5, CAMx, etc.)

• Sponsors: CAM, NSF, MIT/AGS, PEMEX, DOE, others

ChaseDetailed mobile source emissions characterizationPlume tracer flux measurements

Mobile Sampling/MappingMotor vehicle pollution emission ratiosLarge source plume identificationAmbient background pollution distributions

Stationary SamplingHigh time resolution point samplingQuality Assurance for conventional air monitoring sites

Mobile Laboratory Modes of OperationFebruary 2002 & April 2003

Chalco

Teotihuacan

Tula

Ajusco

CENICA

Cuautitlan

Aerosol Mass Spectrometer (AMS) at CENICA

100% transmission (60-600 nm), aerodynamic sizing, linear mass signal.• Jayne et al., Aerosol Science and Technology 33:1-2(49-70), 2000.• Jimenez et al., J. Geophys. Res.- Atmospheres, 108(D7), 8425, doi:10.1029/ 2001JD001213, 2003.

Aerosol measurements (April 15-17, 2003)35

30

25

20

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5

0

PM

1.0

Ma

ss C

on

cen

tra

tion

(g

m-3

)

12:00 AM4/15/2003

12:00 PM 12:00 AM4/16/2003

12:00 PM 12:00 AM4/17/2003

12:00 PM

Nitrate Sulphate Water Ammonium Organics PAH Chloride

PM2.5 Concentration

Gas or Particle Signal

Signal

Emission Ratio = Signal / CO2

“In-plume” Sampling indicated by above-ambient CO2 levels

800

700

600

500

400

30017:54

7/10/0117:55 17:56 17:57 17:58

Time

CO2 (ppm)

CO2

Ambient background level

Emission perturbed level

Vehicle Chase Experiments

Kolb et al., A31D-02 / Zavala et al., A31D-08 / Knighton et al., A14A-03

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.00

50

100

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SCuO

C

X-r

ay

inte

nsi

ty

keV

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.00

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CuO

C

X-r

ay

inte

nsi

ty

keV

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Si

Cu

O

CX-r

ay

inte

nsi

ty (

a.u

)

keV

Heterogeneity in a single soot particle

S inclusion

Only Carbon

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.00

50

100

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KSCu

O

C

X-r

ay

inte

nsi

ty

keV

S, K inclusions

Si inclusion

(Source: MIT/PNNL)

2 µm 500 nm

0.0 0.5 1.0 1.5 2.0 2.5 3.00

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SO

C

X-r

ay in

tens

ity (

a.u)

keV

0.0 0.5 1.0 1.5 2.0 2.5 3.00

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SO

C

X-r

ay in

tens

ity (

a.u)

keV

Fresh soot in city traffic

Processed soot at CENICA

Processing of SootFrom “Chase” Studies In Ambient Air

PIXESpectra

AromaticVOCs

Glyoxal

SOA Precursors SOA

East South South-West

MCMA 2003: Glyoxal and SOA precursors

DOAS-1L= 860mH= 16m

• Benzene, Toluene, Styrene• m-xylene, p-xylene, ethylbenzene• Benzaldehyde, Phenol, pCresol• Naphtalene • HCHO, Glyoxal (DOAS-2)

CENICA

First time DOAS detection of Glyoxal in the atmosphere

Conclusions: PM Measurements

• Rich PM dataset during MCMA-2003

• 58% organics, 26% Inorg., 14% BC– Org: 2/3 OOA, 1/3 POA– Little soil / metals– Intense condensation SIA and SOA– More SOA than in chambers

• “Natural” Holy Week experiment

• PAH measurements