Objective: To determine the best statistical distribution of concentration data of major air pollutants in Shanghai.
Methods: Four types of theoretic distributions (lognormal, gamma, Pearson V and extreme value) were chosen to fit daily average concentration data of PM10, SO2 and NO2 from June 1, 2000 to May 31, 2003 in Shanghai by using the maximum likelihood method. The fit results were evaluated by Chi-square test.
Results: The best-fit distributions for PM10, SO2 and NO2 concentrations in Shanghai were lognormal, Pearson V, and extreme value distributions, respectively.
Conclusion: The results can be further applied to local air pollution prediction and control, e.g., the probabilities exceeding the air quality standard and emission source reduction of air pollutant concentration to meet the standard.