Modeling the Development of Coccidioides Spores in Convective Dust Plumes Using the Flux-Gradient Method
EVELYN KEEFE, Samuel Jurado, Franklyn Telles, Toby Ault, Nour Kastoun, Helena Tsigos, Tyler Sanders, Kylie Miller, Simran LaBore, Jack Halberstadt, Cornell University
Abstract Number: 212
Working Group: Aerosol Exposure
Abstract
The movement and transport of dust and particulate matter through Earth’s atmosphere can have immense effects on radiative forcing and atmospheric chemistry, as well as prominent impacts on air quality and human health. The transport of pathogens via dust particulates presents an important consideration for flux modeling in addition to public health, and has unique implications for our collection area in the American Southwest. Coccidioidomycosis, caused by fungi in the genus Coccidioides and known colloquially as “valley fever”, is an infection caused by the inhalation of fungal spores suspended and transported by dust particulates. Spores are found within the soil of arid locations such as our data collection site and released when dust is carried through the air. Understanding dust flux gradients and potential spread via convective dust plumes is an important aspect of understanding how atmospheric conditions can increase the risk of transmission and infection. This study aims to connect the transmission of valley fever with boundary layer flux behaviors by examining flux gradients and turbulent values within situations where convective plumes may be present and therefore traditional assumptions of neutrality may not be applied. Data will be collected in summer 2025 from eddy covariance towers located in the Jornada Experimental Range in New Mexico. In addition to the data taken from the towers, data will also be taken from two Air Quality Egg sensors, borrowed from Cornell’s Emergent Climate Risk Lab, as well as a Kestrel weather meter to measure meteorological profiles and dust flux. The ground-truth data collected by the towers will be compared to iterative calculations of turbulent values and flux derived from non-eddy covariance wind data. This will serve to contribute to the development of spore modeling as well as improve understanding of convective dust plume behavior and its impact on spore transmission and impacts to human health.