The ozone concentration characteristics of 13 cities in Beijing-Tianjin-Hebei regions from 2016 to 2020 were analyzed based on ecological environment monitoring and meteorological observation data. The influence of meteorological elements such as daily maximum temperature (Tmax), daily average ground pressure (p), daily average ground relative humidity (RH), and daily average ground wind speed (v) on ozone concentration[ρ(O3-8h)] and the exceeding standard rate of O3-8h were discussed. The AQI, ozone concentration range, and ozone pollution level forecast accuracy rates were evaluated using the neural network statistical model. The results showed that the concentrations of O3-8h-90per[ρ(O3-8h-90per)] of 13 cities in the Beijing-Tianjin-Hebei region from 2016 to 2020 were 157.4, 177.2, 177.3, 190.6, and 175.6 μg·m-3, respectively. The regional ozone concentration increased by 11.6% over the five years from 2016 to 2019. From 2016 to 2019, there was an overall upward trend in volatility, followed by a decline in 2020. Compared with that in 2016, the concentration of O3-8h-90per in the other 10 cities increased by 6-45.5 μg·m-3, except for in Beijing, Zhangjiakou, and Chengde, where it decreased slightly. The average value of ρ(O3-8h) from April to September was higher than 100 μg·m-3, and the highest monthly average concentration of O3-8h was 158.10 μg·m-3 in June. The range of the over standard rate of O3-8h was 8.6%-19.2% in the 13 cities, and 97.8% of ozone concentrations exceeded the standard in the period from April to September. At the regional scale, the concentration of O3-8h had the strongest correlation with the daily maximum temperature. Furthermore, when Tmax was in the range of 25-28℃, the concentration of O3-8h in the 13 cities began to exceed the standard concentration of 160 μg·m-3. Additionally, the concentration of O3-8h negatively correlated with p. When RH was below 60%, ozone concentration increased slowly with relative humidity in most cities. When RH was above 61%-70%, ozone concentration decreased with the increase in daily relative humidity in most cities. When ozone exceeded the standard concentration of 160 μg·m-3, the dominant wind was mainly southerly wind, and the high ozone concentration in most cities tended to be concentrated in the low wind speed range of 2-3 m·s-1 and below. Moreover, the correlation coefficient range of the statistical model of OPAQ 1-9 days in advance was 0.72-0.86, the average accuracy of AQI level forecasts was 67%-86%, and the average accuracy of O3-8h concentration forecasts was 63%-84%. In April to September, when ozone exceeded the standard of 160 μg·m-3, the accuracy rates of the model forecast of light ozone pollution and ozone exceeding the standard concentration of 160 μg·m-3three days in advance were 69% and 66%, which can provide a reference for the management and control of ozone pollution.
Keywords: Beijing-Tianjin-Hebei region; assessment of forecast results; meteorological impacts; neural network; ozone (O3); pollution characteristics.