American Association for Aerosol Research - Abstract Submission

AAAR 36th Annual Conference
October 16 - October 20, 2017
Raleigh Convention Center
Raleigh, North Carolina, USA

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Positive Matrix Factorization of Microscopy Data to Apportion Emissions Generated from an Automotive Repair Shop to Ambient PM10 in Rome, Italy

TRACI LERSCH, Gary Casuccio, Roger R. West, Adriana Pietrodangelo, Tommaso Rossi, RJ Lee Group, Inc.

     Abstract Number: 675
     Working Group: Source Apportionment

Abstract
The Consiglio Nazionale delle Ricerche (CNR), or National Research Council, is conducting a study to better understand the composition of ambient particulate matter with the goal of improving the current knowledge on the relationship between anthropogenic emission sources and ambient concentrations. Passive and active samples were collected from an automotive repair shop in Rome, Italy, along with airborne particle samples from the surrounding neighborhood, to assess the localized impact of PM10 from the facility. Automated scanning electron microscopy (SEM) techniques were employed to provide quantitative information on individual particle characteristics at the source and receptor locations. Individual particle data can be a powerful source apportionment tool providing resolution on particle characteristics related to size, morphology and composition. Results obtained from the automated SEM analysis of the automotive repair shop emissions were used to develop source profiles applying positive matrix factorization. Frequently observed source profiles included carbon-rich particles and carbon-rich particles containing sulfur, calcium, barium, iron and/or copper. Also detected were silica particles, silicates, aluminum-rich silicates, calcium and/or barium sulfates, and metal particles (aluminum-rich or iron-rich) where copper and zinc may also be observed. Mixed particles represented an important contribution, too. These particles were composed mainly of carbon-silicate, carbon-sulfate or carbon-iron, suggesting an external mixing structure. This investigation examines the source profiles established from the automotive repair shop emissions, and further evaluates the impact of these emissions on the local ambient environment.