Application of statistical distribution of PM10 concentration in air quality management in 5 representative cities of China

Objective: To estimate the frequency of daily average PM10 concentrations exceeding the air quality standard (AQS) and the reduction of particulate matter emission to meet the AQS from the statistical properties (probability density functions) of air pollutant concentration.

Methods: The daily PM10 average concentration in Beijing, Shanghai, Guangzhou, Wuhan, and Xi'an was measured from 1 January 2004 to 31 December 2008. The PM10 concentration distribution was simulated by using the lognormal, Weibull and Gamma distributions and the best statistical distribution of PM10 concentration in the 5 cities was detected using to the maximum likelihood method.

Results: The daily PM10 average concentration in the 5 cities was fitted using the lognormal distribution. The exceeding duration was predicted, and the estimated PM10 emission source reductions in the 5 cities need to be 56.58%, 93.40%, 80.17%, 82.40%, and 79.80%, respectively to meet the AQS.

Conclusion: Air pollutant concentration can be predicted by using the PM10 concentration distribution, which can be further applied in air quality management and related policy making.