Application of EPA Unmix and Nonparametric Wind Regression on High Time Resolution Trace Elements and Speciated Mercury in Tampa, Florida Aerosol

• Published in: Environmental science & technology 2011-04, Vol.45 (8), p.3511-3518
• Main Authors: Pancras, Joseph Patrick, Vedantham, Ram, Landis, Matthew S, Norris, Gary A, Ondov, John M
• Format: Article
• Language: English
• Subjects: Aerosols; Aerosols - analysis; Air Pollutants - analysis; Air Pollution - statistics & numerical data; Airborne particulates; Applied sciences; Atmospheric pollution; Cities; Environmental Modeling; Environmental Monitoring - methods; Exact sciences and technology; Florida; Mercury; Mercury - analysis; Models, Chemical; Parameter estimation; Particle Size; Particulate Matter - analysis; Pollutants physicochemistry study: properties, effects, reactions, transport and distribution; Pollution; Regression Analysis; Time; Trace elements; Trace Elements - analysis; United States; United States Environmental Protection Agency; Wind
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/es103400h

Intensive ambient air sampling was conducted in Tampa, FL, during October and November of 2002. Fine particulate matter (PM2.5) was collected at 30 min resolution using the Semicontinuous Elements in Aerosol Sampler II (SEAS-II) and analyzed off-line for up to 45 trace elements by high-resolution ICPMS (HR-ICPMS). Divalent reactive gaseous mercury and particulate bound mercury were also measured semicontinuously (2 h). Application of the United States Environmental Protection Agency’s (EPA) Unmix receptor model on the 30 min resolution trace metals data set identified eight possible sources: residual oil combustion, lead recycling, coal combustion, a Cd-rich source, biomass burning, marine aerosol, general industrial, and coarse dust contamination. The source contribution estimates from EPA Unmix were then run in a nonparametric wind regression (NWR) model, which convincingly identified plausible source origins. When the 30 min ambient concentrations of trace elements were time integrated (2 h) and combined with speciated mercury concentrations, the model identified only four sources, some of which appeared to be merged source profiles that were identified as separate sources by using the 30 min resolution data. This work demonstrates that source signatures that can be captured at 30 min resolution may be lost when sampling for longer durations.