Probabilistic Models for Calculating Air Pollution Damage

Seymour Schwartz

DOI: 10.2190/YHUT-NEGJ-D0RM-M4R7


A decision process that weighs the real benefits of pollution-control-the reduced incidence of undesirable effects-against the costs of control requires the prediction of future damage. An alternative to a cost-benefit evaluation is the use of damage statistics which display the effects of pollution on different segments of the population. Probabilistic models are developed to yield both the expected value statistic for use in a cost-benefit evaluation and "percentage-frequency" relationships, which show the distribution of damage as well as the amount. The probabilistic response characteristic, which is the key to the transformation of air quality information to damage information, is introduced. Its construction is illustrated with actual eye irritation data. The submodels required for the complete damage calculation are identified and their interconnections shown. Time and geographical variations in pollutant concentration, as well as variability in human response to pollution, are accounted for in this model.

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