A framework for predicting personal exposures to environmental hazards

Abstract

This paper presents a general framework for constructing a predictive distribution of the exposure to an environmental hazard sustained by a randomly selected member of a designated population. The individual’s exposure is assumed to arise from random movement through the environment, resulting in a distribution of exposure that can be used for environmental risk analysis. A specialization of the general framework is that of predicting human exposure to air pollution that can be used to develop models for such things as exposure to particulate matter; practical aspects of their construction are considered. These models can help answer questions such as what fraction of the population sustained ‘high’ levels of exposure for say 5 days in a row. The immediate implementation of the above framework takes the form of a computing platform referred to as pCNEM. This provides a facility for simulating exposures to airborne pollutants and is described in detail elsewhere. This paper considers some theoretical aspects underpinning probabilistic exposure models of this type, with the ideas illustrated in developing a model for predicting human exposure to PM 10.