AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
Abstract View
Excitation Emission Matrix Spectroscopy for Analysis of Chemical Composition of Combustion Generated Particulate Matter
Gaurav Mahamuni, Jay Rutherford, Justin Davis, Jonathan Posner, Gregory Korshin, IGOR NOVOSSELOV, University of Washington
Abstract Number: 741 Working Group: Instrumentation and Methods
Abstract Analysis of particulate matter (PM) is important in assessing an individual’s exposure to potentially harmful particles, such as aeroallergens, toxins, and emissions from combustion sources. Polycyclic aromatic hydrocarbons (PAHs) are a widespread class of environmental chemical pollutant found in combustion-generated PM. They are associated with carcinogenic and mutagenic effects. We analyze the presence of 24 PAHs having molecular weight < 302 g/mol (including the 16 PAHs recognized as priority pollutants by the EPA) in combustion-generated PM using excitation emission matrix (EEM) spectroscopy. Combustion-generated PM samples of varying PAH content were generated by combustion of ethane and ethylene fuels diluted with Argon to control the combustion temperature in an inverted gravity flame reactor (IGFR). Spectral peaks in the EEM spectra are correlated with PAH content; the data is compared with GCMS analysis on PM. A multiple linear regression model is developed using principal component regression (PCR) to predict PAH concentrations in each sample. The predictions based on the EEM spectra correlate with PAH concentrations from GCMS analysis with 34% average error. This model trained on the laboratory samples is applied to predict PAH concentrations in PM from woodsmoke and diesel exhaust samples. The approach can be used to predict relative concentration of PAHs, toxicity and carcinogenicity in combustion-generated PM.