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

Abstract

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.