Spatiotemporal assessment of wildfire smoke exposure using a low-cost air quality monitoring system in a developing Amazonian city

Biomass burning is the dominant source of seasonal air pollution in the Amazon, yet local-scale exposure remains poorly characterized due to sparse monitoring. This study aims to quantify the spatiotemporal dynamics and drivers of PM₂.₅ pollution in Santarém, Brazilian Amazon, by integrating measurements from a dense network of low-cost sensors, satellite-derived fire radiative power (FRP), and reanalysis meteorology throughout 2023. We applied Generalized Estimating Equations (GEE) to evaluate the daily influence of fire activity and meteorological conditions on local PM₂.₅. Mean PM₂.₅ concentrations increased from ∼5 μg/m³ in the rainy season to ∼16 μg/m³ in the dry season, with 94% of exceedances occurring from July-December and a fine-particle dominance (PM₂.₅/PM₁₀ ≈ 0.79). Peri-urban communities experienced earlier-season pollution peaks, whereas the urban core showed more persistent late-season accumulation. FRP emerged as the primary driver of PM₂.₅, with effect sizes strengthening from 10% (wet season) to 25% (dry season) per standard deviation, while meteorological factors such as wind speed and boundary-layer height played secondary but modulating roles. A negligible weekend-weekday contrast confirmed that smoke overwhelmingly dominates over local traffic emissions. Finally, we operationalized these relationships into a low-computational-cost FRP-Meteo-PM₂.₅ polar radar tool for identifying high-risk smoke transport corridors. These results provide actionable evidence for early warning and highlight the urgent need for targeted fire management to reduce public health risks in developing Amazonian cities.