Doctor of Philosophy (PhD)
Ambient air particulate matter (PM) has been documented to be a contributor to a lot of pollution-related health effects. Due to the common anthropogenic origin, PM could be an effective vehicle to carry and deliver many toxic materials, including environmentally persistent free radicals (EPFRs) and polycyclic aromatic hydrocarbons (PAHs) into the human body, thus significantly raise the health risk of PM exposure. Studies of ambient air PM potentially bear artifacts stemming from the collection methods. We investigated the effects of collection methods on the ambient air PM composition and developed a static collection method relying on the particle entrapment by the plant’s leaf through electrostatic interactions and surface trichomes (“phytosampling”). This method allows for easy particle recovery from the matrix, collection under natural environmental conditions, and enables a dense collection network to represent spatial pollutants distribution more accurately. The experimental results show that the new “phytosampling” method is an effective method to collect PM from ambient air. And the PM retrieving process does not compromise the leaf integrity. On phytosampling collected PM, we detected relatively more potassium and calcium, the larger contribution of oxygen-centered EPFRs, different decay behavior, more consistent PAHs distribution between PM sizes, and less toxicological effects in cell viability test compared to the standard sampling method PM samples. These results indicate that the phytosampling method could prevent some unpredictable changes during PM collection, and collected PM will be more representative as the PM that the general public is exposed to. However, phytosampling cannot evaluate the absolute PM concentration in the air, so it serves as an excellent supplementary tool to work in conjunction with the standard PM collection method. This method has been successfully applied to field studies.
Guo, Chuqi, "Phytosampling of Ambient Air Particulate Matter (PM) -New Method of PM-Associated Pollution Characterization" (2020). LSU Doctoral Dissertations. 5209.
Available for download on Monday, March 15, 2021