Mathematical models for predicting indoor air quality from smoking activity

Area of Science:

• Environmental Health
• Exposure Science
• Indoor Air Quality

Background:

• Four decades of research have advanced mathematical models for predicting indoor pollutant concentrations from smoking.
• These models are valuable tools for regulators and risk assessors to quantify indoor exposure levels based on smoking activity.

Purpose of the Study:

• To review the development and application of the mass balance model for predicting indoor pollutant concentrations from cigarette smoke.
• To derive the time-averaged version of the mass balance model using conservation of mass principles.
• To provide a tool for comparing predicted indoor concentrations with air quality guidelines.

Main Methods:

• Review of the mass balance model's development and application.
• Derivation of the time-averaged mass balance model from conservation of mass.
• Development of a table for computing respirable particulate concentrations based on smoking activity, room volume, and decay rates.

Main Results:

• The mass balance model provides practical tools for estimating indoor exposure to pollutants from smoking.
• A table allows computation of respirable particulate concentrations for various indoor scenarios.
• Using the ventilatory air exchange rate slightly overestimates concentrations, erring on the side of health protection.

Conclusions:

• Mathematical models for environmental tobacco smoke generally show good agreement with indoor measurements.
• These models are essential for regulatory decision-making and risk assessment regarding indoor smoking.
• Accurate prediction of indoor pollutant concentrations supports the establishment of effective air quality standards.