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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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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(dN
/dlo
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p),
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0.01 0.1 1 10D iam eter (m ic rom eters )
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um
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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