Estimating the frequency distributions of PM10 and PM2.5 by the statistics of wind speed at Sha-Lu, Taiwan.

The frequency distribution of air pollutant concentration varies with the meteorological conditions and pollutant emission level. There exists a simple relation between the frequency distribution of wind speed and frequency distribution of air pollutant concentration. The concentration of air pollutant, C, at cumulative probability, p, is inversely proportional to the wind speeds, u, at probability of (100 - p) when the distributional types and shape factors of both data are the same. The relationship is shown as K=Cp u(100 - p), where K is constant. In this study, three theoretical distributions (log-normal, Weibull and type V Pearson distributions) are selected to fit the measured data of PM10, PM2.5 and wind speed. The frequency distributions of air pollutants can be estimated from the simple relationship of air pollutant concentration and wind speed. The results show that the log-normal distribution is the best one to represent the data of PM10, PM2.5 and wind speed. The K values of PM10 and PM2.5 are nearly constant from the 30-80th percentiles. It was also found that the distributions of PM10 and PM2.5 can be successfully estimated from the distribution of wind speed. The Kolmogorov-Smirnov (K-S) test shows that there is no significant discrepancy between the estimated and measured distribution of PM10 and PM2.5 at the 95% confidence level. Therefore, the distribution of air pollutants is easily estimated when the wind speed data are known.