Abstract: Based on the hourly data of pollutant concentration and relative meteorological factors during summer (June to August) from 2017-2019, the distribution characteristics of O₃ concentration and its influencing factors in Taiyuan were analyzed using the neural network method.The results show that, during the summer from 2017-2019, the numbers of days in which the O₃ concentration exceeds the limit in Taiyuan are 55 d, 39 d, 59 d, respectively.The cases that the O₃ concentration exceeds the limit mostly occur in June and July.The diurnal variation of O₃ concentration is unimodal, with the lowest around 06:00, and the peak around 15:00.The conditions such as high temperature, strong radiation, low humidity, low pressure, and southwest wind can easily lead to an increase of O₃ concentration in Taiyuan urban areas.The NW wind is beneficial to the diffusion of O₃ concentration.The relationships of NO₂ and CO with O₃ concentration are negative, and the influence of NO₂ is more significant.The selected cases show that the O₃ concentration fluctuates with the influencing factors.The relationship between O₃ concentration and the influencing factors is constructed using the neural network method, with the correlation coefficient of 0.96, the mean square root and average absolute error of 8 μg·m^-3 and 6%, respectively, and TS score of 0.95.The neural network model is valuable for the O₃ concentration prediction and ozone pollution control in the Taiyuan area.