Source Apportionment Strategies for Atmospheric Particulate Matter in Mega-Cities

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1 Source Apportionment Strategies for Atmospheric Particulate Matter in Mega-Cities James J. Schauer, PhD, PE, MBA Professor

2 Motivation As global populations are moving toward megacities in all continents around the world, air pollution is becoming a grand challenge for megacities In most regions of the world, particulate matter is the biggest air pollutant of concern Exposure to particulate matter is megacities is a very large environmental determinant in the global burden of disease Particulate matter in urban areas is a key contributor to climate forcing and other environmental problems.

3 Urban Infrastructure and Air Quality Transportation Public Transportation Regulation of vehicular emissions Residential Cooking Solid, liquid and gaseous fuels versus electricity Residential Heating Solid, liquid and gaseous fuels versus electricity Waste burning Industry Proximity Regulation of emissions Lack of infrastructure to monitor and manage air quality

4 Megacity Diversity of Infrastructure Development Developed Infrastructure London, Paris, Tokyo Los Angeles Transportation Infrastructure Lacking New York Heating Oil Issue Developing Infrastructure Istanbul, Bogotá, Mexico City, Beijing, Shanghai, Seoul Rapidly Growth with Lacking Infrastructure New Delhi, Lahore, Manila, Lagos Rapidly Growing Cities Future Challenges Addis Ababa, Baghdad, Amman, Santiago

5 Source Apportionment Quantitative understanding of sources is necessary for development of efficient and effective controls Emissions Inventory estimates are a very crude approach to understanding sources Lack spatial and meteorological specificity Two key approaches Chemical transport models Considerable effort to develop and validate Receptor Models

6 Receptor Modeling Approaches Utilize features or characteristics of the pollutants to identify and quantify source contributions Forensic analysis Two major approach Factor Analysis Uses temporal changes in particulate matter concentrations to identify factors, which are related to sources Requires large data sets Chemical Mass Balance Determine the source fingerprints that can re-create the composition of particulate matter measured in the atmosphere Requires measurement of the detailed feature of particulate matter Agreement between these two approaches would give a high level of confidence in the results

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8 Bulk Chemical Analysis Secondary ions and salts Ion Chromatography Elemental and Organic Carbon (ECOC) Different thermal optical methods Key Point: Not the same and should not be used interchangeably Metals X-Ray Fluorescence (XRF) Neutron Activation (INAA) Atomic Absorption (AA) Particle Induced X-Ray Emission (PIXE) Inductively Coupled Plasma Mass Spectrometry (ICPMS)

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10 January February March April May June July Concentration ( g m -3 ) August September October November December Elemental Carbon Organic Matter Sulfate Ion Nitrate Ion Ammonium Ion Other Measured Elements J. E. McGinnis et al., Journal of Environmental Science. In Review

11 Advanced Chemical Analysis Advanced Chemical Speciation Organic Compound Speciation Trace Metals ICPMS techniques for trace elements Metal speciation Isotopic Analysis Biological activity Optical properties

12 Examples of Molecular Markers HO HO O O Cholestanol Pimaric Acid OH Levoglucosan HO H H H H O OH Hopanes R Steranes R Picene

13 Lahore, Pakistan The second biggest city of Pakistan Location: 31 34' N, 74 20' E Sub-tropical and semi-arid region Population: 10,000,000 Annual temperature: C Precipitation: mm

14 Sampling & Chemical Analysis ( ) PM10 & PM2.5 Collected Every 6 th Day at the University of Science and Technology Mass ECOC Secondary and Water Soluble Ions Molecular Markers for CMB Trace Metals by ICPMS ROS Activity by Cellular Macrophage Assay PM10 Collected Every 6 th Day at a Second Urban Site located Downtown Mass ECOC Water Soluble Ions

15 Concentration ( g m -3 ) Organic matter (OC*1.4) Elemental carbon Dust Chloride Sulfate Nitrate Ammonium 0 late-jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec early-jan

16 Concentration ( g m -3 ) Levoglucosan Picene n-alkanes late-jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec early-jan Concentration (ng m -3 ) Concentration (ng m -3 ) Hopanes Concentration (ng m -3 ) Heptacosane Octacosane Nonacosane Triacontane Hentriacontane Dotriacontane Tritriacontane 0 late-jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec early-jan 17 (H)-22,29,30-Trisnorhopane 17 (H)-21 (H)-30-Norhopane 17 (H)-21 (H)-Hopane 0

17 Source Contributions to PM2.5 Organic Carbon Lahore Pakistan, Source Contribution ( gc m -3 ) non-catalyzed Gasoline Vehicles Diesel and Residual Oil Combustion Coal Soot Biomass Burning Vegetative Detritus Other Sources 0 late-jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec early-jan

18 Los Angeles Basin Study Focus on sources of organic carbon (OC) Central LA USC Samples collected every day for one year Analyzed for ECOC and molecular markers A number of source apportionment models were applied Riverside Samples collected every 6 th day for the year Analyzed for ECOC and molecular markers

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22 Denver, Colorado ROS Study 2003 Sample Collection Daily PM 2.5 samplings in Denver for 2003 Bulk Chemical Analysis Not used in this analysis Water Soluble Elements Analysis Method: ICP-MS 52 elements: Li, B, Na,, Pb, Th, U 50 Randomly selected samples analyzed for ROS activity using a micromacrophage assay

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24 Concluding Remarks Particulate matter pollution in mega-cities is a growing concern globally Development of accurate source attribution information is critical to development effective control strategies Sources of particulate matter are very different across seasons and across cities Methods for receptor models are relatively well established and provide key information for understanding the sources of particulate matter Filter based methods for sampling and chemical analysis to support source apportionment are being deployed all around the world

25 Acknowledgements Funding USAID Pakistan Program California Air Resources Board (CARB) Collaborators Prof. Tauseef Quariashi Prof. Mike Hannigan CU Boulder Prof. Costas Sioutas - USC Prof. Betsy Stone University of Iowa Dr. Martin Shafer