The Mexico City Air Quality Case Study:

MCMA-2003 Field Measurement Campaign

Mario J. Molina and Luisa T. Molina

Massachusetts Institute of Technology

WMO-GURME Workshop, Santiago de ChileOctober 13-16, 2003

Topographical Map of the MCMA•Population Growth

>17.5 million (1999): 20-fold increase since 1900

Growth projection to 25 million (2010)

• Urban Sprawl

>1500 km2 (1999): 10-fold increase since 1960

>Expansion to peripheral areas

• Geographic and Topographical Conditions

>High altitude (2240m): less efficient combustion processes

>Mountains are a physical barrier for winds

>2nd largest mega-city in the world

>Temperature inversions in the dry season

• Increases in Emissions Sources

Expansion of the MCMA

Lead (g/m3)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

1988 1990 1992 1994 1996 1998

Ann. avg.

95 Perc

Annual standard

SO2 (ppb)

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120

140

1986 1988 1990 1992 1994 1996 1998

Daily 95%

Daily 50%

Ann. avg.

24-hr. standard

Annual standard

CO (ppm)

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12

1986 1988 1990 1992 1994 1996 1998

8-hr. 95%

8-hr. 50%

Ann. avg.

8-hr. standard

Trends in criteria pollutant concentrations for the MCMA

(averages of data at five RAMA sites: TLA, XAL, MER, PED, and CES)

Ozone (ppb)

0

50

100

150

200

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300

1986 1988 1990 1992 1994 1996 1998

1-hr. 95%1-hr. 50%Ann. avg.

1-hr. standard

PM10 (g/m3) at manual

0

40

80

120

160

200

1988 1990 1992 1994 1996 1998

Ann. avg.

Annual standard

Trends in criteria pollutant concentrations for the MCMA

(averages of data at five RAMA sites: TLA, XAL, MER, PED, and CES)

Integrated Program on Urban, Regional and Global Air Pollution: Mexico City Case Study

(Mexico City Air Quality Program)

Objective:

Provide objective, balanced assessments of the causes and alternative cost-effective solutions to urban, regional and global air pollution problems through quality scientific, technological, social and economic analysis in the face of incomplete data and uncertainty

- Use Mexico City as the initial case study

- Develop an approach that applies globally

- Build on strong base of ongoing basic research

Ecosystem Impact Model

(Agriculture, Water, Climate Change, etc.)

Health Effects/Impacts

Models(Damage Functions, Productivity Losses, etc.)

Meteorological Model

Gas-Particulate Photochemical

Model

Ecosystem Science

Health Effects Science

Atmospheric Science

Policy Development & Implementation

Behavior and Emissions

<< Integrated Science & Economic Impact >> << Policy & Mitigation >>

Demographic & Health Statistics

Ecosystem Data

Atmospheric Data

Emissions &

Area / Point / Mobile

Reduction Costs

House

hold

/ C

om

merc

ial

Energ

y S

upply

/Indust

ry

Transp

ort

ati

on

Model(

s)

( Response Strategies / Scenarios )

A Framework for Integrated AssessmentA Framework for Integrated Assessment

Economic Costs of Human Impacts

Economic Costs of Ecosystem

Damages

Policy & Other Recommendations

(Institutional & Social Factors / Stakeholder Education & Outreach)

Mexican ParticipantsUniversidad Autónoma Metropolitana (UAM)Instituto Mexicano del Petróleo (IMP)Petroleos Mexicanos (PEMEX)Universidad Nacional Autónoma de México (UNAM)Universidad de las Americas, Puebla (UDLA)Universidad Iberoamericana (UIA)Instituto Tecnológico de Estudios Superiores de Monterrey (ITESM)Secretaría de Medio Ambiente y Recursos Naturales (SEMARNAT)Instituto Nacional de Ecología (INE); Centro Nacional de Investigación y Capacitación Ambiental (CENICA)Gobierno del Distrito Federal (GDF); Secretaria de Medio Ambiente (SMA)Gobierno del Estado de México, Secretaria de Ecología (SEGEM)Secretaría de Salud (SS)Insituto Nacional de Salud Pública (INSP)

US ParticipantsMassachusetts Institute of Technology (MIT)Washington State University (WSU)Montana State University (MSU)University of Colorado at Boulder (UC)Lawrence Berkeley National Laboratory (LBNL)Aerodyne Research Inc. (ARI)Department of Energy/Atmospheric Science Program (DOE/ASP)Argonne National Laboratory (ANL)Pacific Northwest National Laboratory (PNNL)Los Alamos National Laboratory (LANL)Colorado State University (CSU)Pennsylvania State University (PSU)National Science Foundation (NSF)University of California at Riverside (UCR)National Center for Atmospheric Research (NCAR)

European ParticipantsChalmers University, SwedenETH-ZurichEcole Polytechnique Federal de LausanneUniversity of HeidelbergFree University of Berlin

Collaborative Research and Education Program

1. Development of integrated assessment methodologies2. Modeling and monitoring photochemical air pollution3. Linkages between transportation, urban land use and

emissions4. Coupling between urban pollution and global change5. Health effects / epidemiology studies6. Identification of public-policy options7. Evaluation and economic analysis of control strategies8. Education and capacity building

Research Agenda

A jointly developed and balanced program

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

Focus of the Second Phase of the Mexico City Air Quality Program

Systematic development of scientific information, evaluation methodologies and simulation tools in the following areas:

  activities that lead to the generation of pollutants in the MCMA

(transportation, production of goods and services, degradation of the natural environment, etc.);

  dispersion and transformation of atmospheric pollutants

(focus on ozone and particles);   evaluation of risks and the effects of pollutants on the population;   cost-benefit analysis of control strategies;   integrated assessment of policy options and priorities for control strategies;   strategies for capacity building.

Emission inventories:What are the sources of NH3? HCHO? What are their emissions rates?

Are hydrocarbon emissions underestimated? Are NOx emissions overestimated?

Are there significant biogenic emissions, e.g., terpenes?

Chemistry: transformation of emissions in the atmosphere

How is the reduction in NOx and/or HC related to reduction in O3 and PM?

Would reductions in NOx lead to a reduction in nitrate particulates?

What is the impact of reducing ammonia?

How much HCHO is primary vs. secondary (produced photochemically)?

What is the partitioning of NOy (NOx, HNO3, organic nitrates)?

What are the sources and the chemical composition of the fine PM?

MCMA-2003 Field Measurement Campaign Science Questions

MCMA-2003 Field Measurement Campaign Science Questions (cont)

Meteorology:What is the height of the mixing layer?How does it evolve with time?Is there any “carry over” of pollutants from one day to the next?Do the models satisfactorily predict wind speeds and directions?

Urban-Regional-Global Chemical Transformation:What are the effective source terms for emissions for global climate models?What are the roles of aerosols in modifying the local/regional radiative transfer processes and cloud properties?

MCMA-2003 Field Campaign

Supersite Instrumentation

Instrumentation: CENICA - monitoring station, tethered balloon RAMA - monitoring station WSU – VOC sampling DOE/ PNNL – PTRMS, single particle sampler/analyzer, MFRSBR, RSR UCB/LBL – Particle sampling apparatus DOE/Argonne National Lab – PAN, black carbon, olefins, NH3

Colorado U. – AMS Penn State – OH and HO2

IMP – MINIVOLS and MOUDI , aldehyde cartridges MIT/U. Heidelberg - DOAS MIT/ Free U. Berlin – LIDAR MIT – PAHs UCR – nitro-PAHs, PAHs EPFL - LIDAR UNAM – FTIR Chalmers – FTIR, DOAS Plus others

Supersite Location: CENICA (UAM-Ixtapalapa)

Number vs. Mass

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ber

(dN

/dlo

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p),

cm

-3x1

03

0.01 0.1 1 10D iam eter (m ic rom eters )

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Vol

um

e

(dV

/dlo

gDp),

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m3

N u cleation M ode

A itken M od e

C on densa tion S ubm ode

D ropletSu bm ode

C oarse M od e

U ltraf in e P articles

F ine P artic les C oarse P a rticles

Accum ula tion M od e

Model distributions from NARSTO PM Assessment Report

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.

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

Mobile Laboratory: Vehicle Chasing

East South South-West

Radiation:• Spectrometry Actinic photon flux (incl. straylight) -> any J-value• Filterradiometry J(NO2)

MIT/IUP DOAS equipment on Cenica Roof-top (Hut)

DOAS-2L= 4420mH= 70m

• HONO, HCHO, O3• NO2, (NO3)• SO2• Glyoxal

DOAS-1L= 960mH= 16m

• BTX, Styrene• Benzaldehyde, Phenol• Naphtalene• NO2, HONO• HCHO, O3, SO2

MCMA-2003 Field CampaignAdditional Instruments at other Locations

• UNAM – FTIR, Single particle black carbon instrument, biogenic emissions

• IMP – MINIVOLS and MOUDI , aldehyde cartridges, radiosondes

• UAM/ MIT – Pilot balloons

• Chalmers – solar occultation flux (mobile lab)

• Plus others

Environmental Education and Outreach Visiting Mexican scholars at MIT

Workshops/symposia on air quality

Professional development courses on air quality for mid-career personnel in the government, industry and academic sectors as well as non-governmental organizations and the media

Masters Program in Environment and Health Management at MIT and Harvard School of Public Health (INE-MIT-Harvard joint program)

Exchange program between MIT and Mexican institutions

Establish the Research and Development Network on Air Quality in Large Cities in Mexico

Web-based activities for senior high school teachers and students (with Monterrey Tech, ITESM)

Collaborative Activities with Latin American Cities

Air quality forecasting training workshops (with Santiago de Chile and São Paulo)

Transportation/land use and atmospheric modeling and measurements (with Santiago de Chile and other Latin American cities)

Inter-American Network for Atmosphere and Biosphere Studies (IANABIS)

MIT Scenario Analysis

Integrating Bottom-Up and top-Down Analytic Approaches

Three Feasibility “Screens”

– Technical Feasibility (effective)

– Economic Feasibility (affordable)

•Pursued through quantitative analysis

– Political Feasibility (implementable)

•Pursued through qualitative dialogue

“Feasibility” depends in part upon the “Future Story”

•Allows us to identify more robust options

A Diverse Mix of Emissions/Sources

Source: CAM 1998 MCMA Emissions Inventory