S148
Positive Matrix Factorization (PMF) Analysis of PM2.5 Speciation Data from DISCOVER-AQ Sites: Baltimore, MD and Fresno, CA

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Sunday, 2 February 2014
Hall C3 (The Georgia World Congress Center )
Daniel Wesloh, JCET/Univ. of Maryland Baltimore County, Baltimore, MD; and D. Orozco, R. Delgado, and R. M. Hoff

Particulate matter in the atmosphere, specifically particulates with diameter less than or equal to 2.5 μm (PM2.5), is a key variable of air quality studies. Identification and apportionment of PM2.5 to their sources is an important step in air quality management. Source apportionment of 24–hour integrated PM2.5 chemical speciation data for Baltimore, MD and Fresno, CA was performed using the receptor model, Positive Matrix Factorization (PMF). Locations are part of the NASA sponsored research project Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER AQ). DISCOVER AQ is an effort to understand the relationship between satellite observations related to particulate matter such as aerosol optical depth, which give information about the whole column of air above a given area, and surface observations. PMF is a mathematical technique used to separate this concentration data into two components, one representing source factor profiles, and the other representing factor contribution over time. The PMF model was run, with varying numbers of factors and model setups, until a mathematically and physically sound solution was found. The model finds solutions by minimizing a least squares objective function that depends on both the model error and user-provided uncertainty data. Data obtained from the Environmental Protection Agency (EPA) Air Quality System (AQS) was used for the identification of 8 chemical speciation clusters (factors): sulfate-rich secondary aerosol, nitrate-rich secondary aerosol, gasoline, diesel, soil, biomass burning, marine aerosol, and industrial processing. Source apportionment results indicate that sulfate-rich aerosol and nitrate-rich aerosol are the primary sources of PM2.5 in Baltimore and Fresno, respectively. Chemical speciation data was compared to aerosol hygroscopic measurements. A humidifier-dryer system for a TSI 3563 Nephelometer was designed and built in order to measure the scattering coefficient σsp(λ) at three different wavelengths (λ =440, 550 and 700nm) in a relative humidity (RH) range from 25 to 95%. Scattering measurements reveal the presence of hygroscopic and hydrophobic aerosols in Baltimore and Fresno, respectively.