[Characteristics of Ozone Pollution, Meteorological Impact, and Evaluation of Forecasting Results Based on a Neural Network Model in Beijing-Tianjin-Hebei Region].

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.

[Relationship Between Atmospheric Visibility and PM2.5 Concentrations and Distributions].

Monitoring data were used to analyze the relationships among relative humidity (RH), visibility, and PM2.5 concentrations. A strong, linear relationship expression between the extinction coefficient and PM2.5 concentrations at different relative humidities is proposed. The mean correlation coefficient at RH 40%-90% was higher than 0.75 for most of Central and Eastern China, and reached 0.9 in Beijing. Comparatively, the extinction efficiency of PM2.5 was much larger in Beijing, the Yangzi River Delta Region, and Sichuan than in other regions. However, the influence of RH on visibility varied from region to region. In Beijing, RH dominated the decrease in visibility when RH>90%, while in Guangzhou, this was the case when RH>80%. From 1980 to 1996, the annual variation in PM2.5 concentrations was not significant in Beijing and the PM2.5 concentrations were significantly higher than in the 2000s because of the dominant mode of heating. From 1997 to 2009, PM2.5 concentrations in Beijing showed a slow downward trend, and from 2010 to 2012, showed an upward trend. Since 1980, PM2.5 concentrations in the entire country have been rising. PM2.5 concentrations have always been higher in North China than in other parts of the country.