Impact of Large-Scale Wildfires and Meteorological Factors on PM Concentrations in Agricultural Regions: Non-Linear Relationship Analysis Using GAM

The intensification of large-scale wildfires, driven by climate change, presents a critical threat to agricultural ecosystems, specifically during the vulnerable sowing season in March. Departing from the prevailing focus on urban air quality, this study elucidates the spatiotemporal dynamics of particulate matter (PM) in eight major Korean agricultural regions during the March 2025 wildfires. By employing a Generalized Additive Model (GAM), we characterized the complex non-linear interactions between PM concentrations and meteorological variables. The analysis reveals a substantial elevation in PM levels during the wildfire event relative to the pre-fire baseline. Most notably, the Sangju region experienced the most acute accumulation, with PM-10 and PM-2.5 concentrations surging by 74% and 46%, respectively; this intensification was significantly compounded by topographic trapping and surface inversion phenomena. Furthermore, GAM results identified temperature and relative humidity as the primary determinants of PM retention, whereas wind speed demonstrated a distinct non-linear, U-shaped effect, facilitating particulate resuspension at higher velocities. These findings quantitatively underscore the susceptibility of agricultural environments to wildfire-induced aerosols and highlight the imperative for establishing agriculture-specific monitoring networks and early warning protocols to safeguard crop productivity.