Review of Statistics of Extreme Values with Applications to Air Quality Data

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Abstract
In the field of air pollution control, the rare event is often of more significance than the common event. This is evidenced by the content of air quality standards which define acceptable upper limits of air pollution concentrations and acceptable frequencies with which such concentrations can be exceeded. The principles of extreme value statistics provide important tools for analyzing air quality data in an appropriately significant context. Part II of the paper presents applications of the theory to air quality data. First, application is made to decisions regarding the length of air monitoring experiments and the length of data records for dis-person analyses. The theory is then applied to the analysis of long term air pollution data collected by the South Coast Air Pollution Control District. The interrelations between extremes from monthly and annual samples are noted and are shown to be consistent with theory.

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