AAAR 33rd Annual Conference
October 20 - October 24, 2014
Rosen Shingle Creek
Orlando, Florida, USA
Abstract View
Selenium in Ambient Fine Particulate Matter: Measurement and Trend Analysis
LI DU, Jay Turner, Washington University in St. Louis
Abstract Number: 349 Working Group: Source Apportionment
Abstract Selenium compounds in ambient particulate matter (PM) have been categorized as hazardous air pollutants by the US Environmental Protection Agency (EPA) due to their toxic effects on human health. In addition, selenium often serves as one of the primary tracers for coal and oil combustion emissions in air quality studies. However, the presently low selenium mass loadings at most sites in the Chemical Speciation Network (CSN) pose challenges to detection by X-Ray Fluorescence (XRF) as implemented for the CSN. For example, the detectability of selenium (percentage of samples above the method detection limit, MDL) at a site in St. Louis decreased by more than 50% during the past decade because of the reduction in ambient selenium levels. In this study, a selenium measurement methodology based on Inductively Coupled Plasma/Mass Spectrometry (ICP-MS) that was originally developed to measure selenium in aquatic organisms was adopted. Spiking the digested sample solution with 3% (v/v) of methanol improved the sensitivity of the selenium signal using the standard mode of ICP-MS and lowered the MDL by about 65% compared to XRF analysis as routinely implemented for the CSN. The adopted method was optimized and applied to CSN protocol PM2.5 samples collected as part of the Roxana Air Quality Study (RAQS) which is being conducted in Roxana (IL) and as of July 2014 will include two years of 24-hour integrated 1-in-6 day sampling for PM2.5 mass and speciation. For the 90 samples collected and analyzed to date, the detectability was 9% for XRF analysis as implemented for the CSN, 0% for ICP-MS without methanol addition, and 47% for ICP-MS with methanol addition. The extent to which selenium appears to be a suitable tracer for coal combustion was examined using various tools such as potential source contribution function (PSCF) and will also be presented.