Physicochemical and Toxicological Profiles of Particles from Paired Combustions of California Biomass Species
SAAGAR PATEL, Amber Kramer, David Park, Tiancong Ma, Tian Xia, Yifang Zhu,
University of California, Los Angeles Abstract Number: 545
Working Group: Combustion
AbstractThe increased frequency and severity of wildfires on the West Coast due to climate change has led to an increase in emissions of air pollutants. The emission products of these wildfires are complex, and potentially include thousands of species of flora, making toxicity modeling based on plant species difficult. Additionally, hours after a wildfire is contained, the biomass still emits air pollutants that consist of a dramatically different composition of air pollutants. A previous study was conducted where, in a temperature and humidity-controlled chamber, five individual Californian plant species (four native & one invasive) were combusted and their emission products characterized. Emissions were collected immediately after the biomass was ignited and again after a two-hour aging period to determine the profile of emission products that accurately demonstrate human exposure parameters. Significant differences in particle modal diameter, PAH content, and oxidative potential in each individual biomass species led to the synthesis of this study’s design where we seek to explore the possibility of modeling the physicochemical and toxicological profile of two-component combustion experiments using single component combustion data. Additionally, we are interested in examining the interactions between plant species of different material (e.g., grassy vs. woody) and origin (native vs. invasive). Here we pair biomass species in the combustion chamber and evaluate: (1) particle size distribution using SMPS for Particulate Matter (PM) (10 – 500nm) & APS for PM (0.5 – 20 µm) in diameter, (2) polycyclic aromatic hydrocarbon (PAH) profiles using GC-MS, and (3) oxidative potential using both Dichlorofluorescein (DCF) & Dithiothreitol (DTT) assays. Results from this study will provide better understanding wildfire emissions modelling for use in health risk assessments.