Evaluation of modeled smoke plumes of wildfires in the Argentinian Patagonia, against satellite observations.

Carbon monoxide, nitrogen oxides, volatile organic compounds and aerosols are the dominant species emitted by wildfires, affecting air quality and contributing to global greenhouse gases. This study implements the APIFLAME fire emissions model, the EDGAR anthropogenic emission inventory, the WRF weather prediction model, and the CHIMERE chemical transport model to simulate air quality during wildfires. Three configurations assessed the impact of smoke injection height: a standard configuration with a plume rise model and fixed heights at 2500 and 5000 m. The case study is a wildfire in Patagonia during summer 2018, burning over a million hectares. Fire emissions were in the order of (CO, NMVOCs) and surpassed (NOx, PM10, PM2.5 and SO2) the annual Argentinian emissions from transport and oil refineries. NO2 and aerosol optical depth (AOD) were assessed with satellite data: QA4ECV/OMI (KNMI) and MAIAC/MODIS (NASA). To compare modeled- to satellite NO2, averaging kernels were applied. All configurations showed high correlation (ρ>0.69) and a deviation of -10.38 to 3.93% for different radii around the hotspots. Concerning AOD, normalized mean bias overpredicts the lowest deviation locally when compared to 470 nm MAIAC data, at 0.25-0.50∘ around the hotspot positions, for the 5000 m injection height configuration (28.8 to 28.6%), 2500 m injection height configuration (46.83 to 52.69%) and standard configuration (60.21 to 66.2%). In addition, the spatio-temporal evolution of the plume was well reproduced by the standard configuration. Model-satellite intercomparisons in the spatial domain reveal long-range transport, complementing local statistical metrics, and highlight the influence of injection height on plume dispersion. This study provides valuable insights into the impact of wildfires on air quality in Patagonia. Given limited ground-based observations, future work should evaluate updated satellite datasets and refine fire emission estimates.