Hourly Seamless Surface O₃ Estimates by Integrating the Chemical Transport and Machine Learning Models in the Beijing-Tianjin-Hebei Region.

ABSTRACT: Surface ozone (O₃) is an important atmospheric trace gas, posing an enormous threat to ecological security and human health. Currently, the core objective of air pollution control in China is to realize the joint treatment of fine particulate matter (PM_2.5) and O₃. However, high-accuracy near-surface O₃ maps remain lacking. Therefore, we established a new model to determine the full-coverage hourly O₃ concentration with the WRF-Chem and random forest (RF) models combined with anthropogenic emission data and meteorological datasets. Based on this method, choosing the Beijing-Tianjin-Hebei (BTH) region in 2018 as an example, full-coverage hourly O₃ maps were generated at a horizontal resolution of 9 km. The performance evaluat

SUBMITTER: Xue W 

PROVIDER: S-EPMC9324222 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature