High-resolution full-coverage ozone (O₃) estimates using a data-driven spatial random forest model in...

The Beijing-Tianjin-Hebei (BTH) region is severely polluted by ozone (O₃). Accurate O₃ estimates are essential for identifying high-polluted zones and developing targeted interventions to relieve the burden of diseases. Although many studies have estimated high-resolution O₃ concentrations in BTH, the estimation accuracies are still insufficient. In this study, we incorporated data-driven spatial weight matrices (DDWs) into a random forest (RF) model to fully utilize both the spatial homogeneity and heterogeneity of maximum daily 8-h ozone concentration (MDA8O₃), and obtained full-coverage MDA8O₃ concentrations at 1 km×1 km in BTH from 2014 to 2022. DDW-RF exhibited satisfactory accuracy (10-fold cross-validation R² =0.937, RMSE=13.919 μg/m³). Overall O₃ level presented a spatial pattern of lower in the north and higher in the southeast and showed a distinct temporal trend, i.e., first increasing and then decreasing during 2014-2021 and increasing slightly in 2022. The accurate MDA8O₃ estimates indicates that more attention and resources should be poured into the areas adjacent to Bohai Rim, Shandong and Henan. Regulated operation of factories under specific meteorological conditions and upgrading industrial structure and production modes are recommended to mitigate the formation of O₃ precursors and reduce O₃ generation. Our findings provide evidence and reference for environmental cleaning policies and targeted interventions.