A conceptual approach to determine optimal indoor air quality: A mixture experiment method

Abstract

Achieving good air quality in large residential and commercial buildings continues to be a top priority for owners, designers, building managers and occupants. The challenge is even greater today. There are many new materials, furnishing, products and processes used in these buildings that are potential source of contaminations and pollutants.

A common problem to the indoor and outdoor environments is that of exposure to mixtures of air pollutants. Researchers and practitioners tend to focus on single pollutants (e.g. CO2, PM2.5) ignoring the mixtures combined effect. Fashion dictates to study the pollutant most thoroughly talked about. Distinguishing the effects of such co-pollutants is difficult. The conclusions about which component of a mixture is actually producing a given effect are sometimes less soundly based than could be wished. It is especially important in considering the indoor mixture of air pollutants as this mixture may be entirely different from those found outside. Exposures to raised levels of air pollutants can damage health, for example carbon monoxide can cause death and significant lasting disability. Controlling levels of indoor air pollutants is therefore important, as good indoor air quality is essential to health.

There are three strategies for achieving acceptable indoor air quality: ventilation, source control and cleaning/filtration. Depending on the building and the specific characteristics of the location, these strategies can be used singly or in combination. However, mixture experiment would throw more light and understanding into indoor air composition and interaction properties and the combine effects it has on human health.

Mixture experiments have been used extensively in other industries, for example the pharmaceutical industry and the agrochemical industry, for the production of tablets and the control of plant diseases and pests. Developing a mixture model for the internal microclimate for a particular building type and/or location may help us in developing better indicators, standards and policy document in the near future, when the levels of pollutants concentration can be successfully predicted.