Probabilistic Health Risk Assessment of Industrial Workers Exposed to Air Pollution

The aim of this article is to present a probabilistic way of determining the cumulative effect of various elements in the air, such as NOx, SO₂, and respirable particulate matter (RPM), that affect the human health. In the past, mostly deterministic models were developed for this purpose, which would test the response of the subject to known amounts of increasing doses. This dose-response curve would reflect the response of the subject only for a particular contaminant like CO, RPM, or NOx. However, most industrial sites are contaminated with several of these pollutants, with some or all of them affecting the workers in a very complex manner. So a new dose-response curve must be constructed that would take into account the effects due to multiple contaminants, i.e., the effect of several contaminants acting at the same time. This dose-response curve has to be constructed for each different set of independently acting variable. With the development of high speed computers, simulation can be used to develop a comprehensive risk analysis model (RAM) for studying the effect of these contaminants. The RAM is developed for an open pit mine using the Monte Carlo simulation technique and tested against the data obtained. The guiding principle in this project is that the effect of various contaminants, acting independently, is the sum of the individual effects put together; i.e., the effects due to a contaminant are independent of the presence of other contaminants. While the writers suggest a change in the probabilistic risk due to changing ambient concentrations of various pollutants, they stop short of pinpointing any resulting disease or disease-related symptoms.