Abstract

The performance of a Markov chain model of the three-dimensional transport of particulates in indoor environments is evaluated against experimentally measured supermicrometer particle deposition. Previously, the model was found to replicate the predictions of relatively simple particle transport and fate models; and this work represents the next step in model evaluation. The experiments modeled were (i) the release of polydispersed particles inside a building lobby, and (ii) the release of monodispersed fluorescein-tagged particles inside an experimental chamber under natural and forced mixing. The Markov model was able to reproduce the spatial patterns of particle deposition in both experiments, though the model predictions were sensitive to the parameterization of the particle release mechanism in the second experiment. Overall, the results indicate that the Markov model is a plausible tool for modeling the fate and transport of supermicrometer particles.

Highlights

  • The transport and fate of supermicrometer particles, those with aerodynamic diameters ≥ 1 μm in indoor environments are important to public health

  • Previous work indicates that the Markov model replicates predictions of relatively simple particle transport and fate models (Jones and Nicas, submitted), and there is theoretical support for the representation of advection-diffusion processes in a Markov chain (Jones, 2008; Nicas, 2010; Jones and Nicas, submitted)

  • This study reflects an important step in the evaluation of mathematical models, in that the Markov model was evaluated against experimental data collected in controlled, but realistic, settings

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Summary

Introduction

The transport and fate of supermicrometer particles, those with aerodynamic diameters ≥ 1 μm in indoor environments are important to public health. While there are many models available and appropriate to predicting the transport of particles in indoor environments, the authors have focused on the application of a Markov chain. The authors developed theory to support the application of a Markov chain to predict the three-dimensional transport and of airborne gaseous and particulate contaminants (Nicas, 2000, 2001, 2010; Jones, 2008), and applied this Markov model to the transport of Mycobacterium tuberculosis in aircraft (Jones et al, 2009). The evaluation of a mathematical model is a multi-step process that includes: 1) development and verification of a theoretical basis for the mathematical construct, 2) benchmarking model predictions against related models, 3) evaluation of the model predictions with experimental data obtained in relatively simple contexts, and 4) evaluation of the model predictions with real-world data reflecting real-world problems. The Markov model predictions are evaluated against experimental data obtained in relatively simple contexts

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