Mathematical Models for Measuring Environmental Tobacco Smoke Concentrations in A Single Room

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Author(s) Ogunmola B.Y | Adegboyega A. K | Oluwafemi J. D.
Pages 589-598
Volume 5
Issue 11
Date November, 2015
Keywords Environmental Tobacco Smoke, Indoor Air Quality, Contaminant, Particulate Matter, Sink, Dry Deposition, Average Smoking Count And Chemical Removal.

Abstract

This study developed analytical models for a single zone using a macroscopic approach to predict indoor air pollutant concentration in a room. The law of conservation of mass was applied to the box model representing a room apartment with real time measured parameter to develop four models with multi-smoker effect (MSE) and removal mechanisms (RM) other than the normal ventilation effect commonly considered in most box model version. The environmental tobacco smoke (ETS) models, were derived by solving the differential equations analytically to obtain the popular box model and including RMs like dry deposition, chemical removal and filtration. The developed models are a combination of the multiple-smoker version, the sink effect version with dry deposition and chemical removal effect. Data developed using these models show that the inclusion of more than one RM produced a more precise and realistic result close to what obtains in reality than other models with lesser or no RM. Most box models only consider ventilation and filtration which is not enough to determine what real occur in nature. This study seeks to establish the importance of RMs in an indoor air quality (IAQ) model by considering some of the physico-chemical characteristics and behaviour of the contaminants as it affect contaminant concentration in a room. The particle deposition count was also established to determine the number of particulate matter (PM) removed from the micro-environment or deposited on measured surface area over a given time after the smoking activity. MATLAB codes were developed to evaluate the models and the generated graphs and data predicted how indoor ETS concentration can be managed for human health and safety. The model compared favorably with findings of other researchers working on ETS modeling but further validation can be done using real time concentration monitors.

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