Although most people spend most of their time indoors, policies on air pollution (and most epidemiological studies of air pollution) have tended to focus on the ambient (or outdoor) atmosphere.  In the case of health impact assessments, there is  some danger in this focus, for it can ignore many of the behavioural and micro-environmental factors that influence exposure, and which can be manipulated to protect health.   While many assessments therefore need to model patterns and processes of outdoor air pollution, this may not be the end of the story, and information may also be required on indoor air.

Modelling ambient concentrations

Reflecting the needs of policy, the majority of the air pollution models that have been developed to date are targetted at estimating ambient concentrations.  While a wide variety of models has been developed, two general approaches can be recognised:

• dispersion models, which attempt to simulate the physical (and to some extent chemical) processes involved in transport;
• statistical models, which largely ignore the intervening processes, but represent the relationship between the source and concentrations at the receptor in the form of (empirically-informed) formulae or statistical functions.

The distinctions between these two approaches is not always clear, and various hybrid techniques have been developed.  In most cases, however, dispersion models are to be favoured for the purpose of impact assessment, because they more explicitly represent the real-world processes that occur, and should therefore be more reliable as a basis for prediction (see link in panel to left).  Their use is nevertheless limited in some cases by constraints of data or the heavy processing requirements and software costs.  In these circumstances alternative approaches may be more appropriate.   Moreover, ambient air pollution models only provide reliable estimates of actual exposure where:

• exposures from indoor sources are not of interest (e.g. policies focused on outdoor concentrations and ambient exposures)
• outdoor to indoor penetration of the pollutant of interest is relatively high and consistent (e.g. PM_2.5)
• the target population can be assumed to remain stationary in relation to the concentration field (e.g. secondary air contaminants). 

Where these conditions do not apply, results need to be linked to indoor air pollution models that can represent the transfers and transformations that take place as pollutants pass into buildings, and/or the additional influence of indoor sources. 

Further information on dispersion and  statistical models are given via the links in the panel to the left, and links to a range of air pollution are included in the Model section of the Toolkit. 

Modelling indoor concentrations

As with ambient pollution, methods for modelling indoor concentrations vary.  Where the focus is on pollutants which are largely derived from outdoor sources, the simplest approach has been to assume a constant ratio between outdoor and indoor concentrations.  Where indoor sources are of greater concern, categorical models have been developed, using the presence or absence of specific emission sources (e.g. cooking, heating) as an indicator of likely indoor concentrations.  More realistic models require that account is taken of the mixing, air exchange and transformation processes that can occur both within the indoor environment, and between indoors and outdoors.  To represent these, some form of mass-balance or fluid dynamic model is likely to be necessary (see link to Indoor air pollution models, in panel to left).