Predicting violations of national ambient air quality standards using extreme value theory for Delhi city

Abstract Type I asymptotic distribution of extreme values was used for making predictions of the expected number of violations of the National Ambient Air Quality Standards (NAAQS) for 24–hour average sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ) and suspended particulate matter (SPM), monitored at the four National Ambient Air Quality Monitoring (NAAQM) stations run by the Central Pollution Control Board (CPCB) for Delhi city. The parameters of the distribution were estimated using Gumbel's method. A comparison of the predicted violations of NAAQS and the exceedance of the maximum pollution concentration with that of the observed data indicates that Type I asymptotic distribution adequately fits to the observed extreme value data. The application of extreme value theory as a tool for managing urban air quality was highlighted.