Abstract:

Characteristics of ozone pollution in Chongqing were analyzed based on daily air quality data from 2014 to 2018.The results indicated that O₃ is the second primary air pollutants following PM_2.5, and has a distinct seasonal variation.O₃ pollution mostly occurs in summer and is more severe than PM_2.5 pollution in July and August.The annual mean O₃ concentration tends to increase year by year, and O₃ has become the first primary pollutant in Chongqing since 2018, with the day number of O₃ as the daily primary pollutant exceeding that of PM_2.5 for the first time.This suggests Chongqing is turning from a city mainly affected by particulate matter pollution to the one dominantly affected by ozone pollution.Air temperature, humidity, and air pressure are important meteorological factors influenc the O₃ level in Chongqing based on correlation analysis between daily meteorological factors and daily maximum O₃ 8-h moving average (O_3-8H) concentration.The daily maximum O_3-8H concentration is predicted using methods of stepwise regression, support vector machine, and neural network based on meteorological factors.All the three methods perform well and have small underestimations on average.The support vector machine method performs better in prediction of the daily maximum O_3-8H concentration than the other two methods and has a good implication for O₃ concentration prediction in Chongqing.

Key words: Ozone pollution, Meteorological factor, Stepwise regression, Support vector machine, Neural network