AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
Abstract View
Modeling Water Uptake by Dust in Residential Environments
David Kormos, Karen C. Dannemiller, ANDREW MAY, The Ohio State University
Abstract Number: 264 Working Group: The Air We Breathe: Indoor Aerosol Sources and Chemistry
Abstract Moisture within homes can impact microbial growth in dust, and thus, contribute to negative human health effects. However, there is currently no mathematical framework to describe this moisture uptake. To test the applicability of common atmospheric models of water uptake for the indoor environment, we conducted controlled equilibrium and kinetic experiments using Arizona Test Dust (ATD), a well-characterized model dust. In the thermodynamic experiments, ATD was incubated at equilibrium relative humidity (ERH) ranging from 50 to 100% increasing at 10% increments per day. Sample mass and water activity were recorded daily (corresponding to each ERH value). In the kinetic experiments, ATD was moved from 50% ERH to a higher level at time zero with many mass and water activity measurements performed over the course of one day in order to assess the temporal response. The kinetic experiments suggest that steady-state (equilibrium) is reached in roughly two hours.
Initial modeling efforts included the κ-Köhler equation for equilibrium experiments and the Maxwellian flux equation for kinetic experiments with constant RH. Using the literature κ value for ATD (0.025) results in an over-prediction of equilibrium water uptake, but we can infer a new value (0.0034) that matches our data well. Similarly, the kinetic equation over-predicts transient water uptake for κ = 0.025; updating to κ = 0.0034 does not remedy the issue. Consequently, we propose an alternative model that is able to capture the overall dynamic behavior, although there is still a discrepancy in the magnitude of the predicted water uptake. Regardless, both models may be able to represent indoor environments where ERH is fluctuating. Since we are ultimately interested in microbial growth (and its implications for human exposure), we couple these kinetic models with a microbial growth model for post hoc predictions of actual residential dust samples.