Identification of response regulation governing ozone formation based on influential factors using a random forest approach.

ABSTRACT: The pursuit of enhanced scientific, refined, and precise ozone and air quality control continues to pose significant challenges. Using data visualization techniques and random forest (RF) algorithms, the temporal distribution of atmospheric pollutants and the interrelationship between O₃ concentration and its influential factors were investigated with one-year monitoring data in Deqing county in 2021. The local atmospheric conditions predominantly belonged to NOx-sensitive and transition zone. Extremely high O₃ concentration were primarily observed when temperatures (T) exceeded 30 °C, with relative humidity (RH) ranging between 30 and 60 %. NO₂, RH and T were identified as the top 3 important factors, and O₃ concentration have stronger linearly

SUBMITTER: Huang Y 

PROVIDER: S-EPMC11367417 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature