Predicting the exceedances of a critical PM10 concentration—a case study in Taiwan

Abstract

Abstract Three theoretical distributions, lognormal, Weibull and type V Pearson, were used to fit the parent distribution of the PM10 at five air monitoring stations in Taiwan from 1995 to 1999. However, these distributions cause large errors in predicting air pollutant concentration in the high-concentration region. Two prediction methods, method I: type I asymptotic distribution of extreme value and method II: type I two-parameter exponential distribution, were used to fit the distributions of the monthly maximum and high PM10 concentration over a specific percentile, respectively. Moreover, these two methods were taken to estimate the return period and exceedances of a critical PM10 concentration, such as Taiwan EPA's standard, in Taiwan. The result indicates that the lognormal distribution is the most appropriate parent distribution to represent whole PM10 data. However, the fitted type I two-parameter exponential distribution is better matched with the high PM10 concentration levels than the parent lognormal distribution. Both of the prediction methods (I and II) can successfully estimate the return period and exceedances over a critical concentration during the sampling period.