An operational system for the assimilation of the satellite information on wild-land fires for the needs of air quality modelling and forecasting

This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-mu m Brightness Temperature Anomaly ( TA) and Fire Radiative Power (FRP) for the needs of operational chemical transport modelling and short-term forecasting of atmospheric composition and air quality. The treatments of the TA and FRP data are presented and a methodology for evaluating the emission fluxes of primary aerosols (PM2.5 and total PM) is described. The method does not include the complicated analysis of vegetation state, fuel load, burning efficiency and related factors, which are uncertain but inevitably involved in approaches based on burnt-area scars or similar products. The core of the current methodology is based on the empirical emission factors that are used to convert the observed temperature anomalies and fire radiative powers into emission fluxes. These factors have been derived from the analysis of several fire episodes in Europe (28.4-5.5.2006, 15.8-25.8.2006 and in August 2008). These episodes were characterised by: (i) well-identified FRP and TA values, and (ii) available ground-based observations of aerosol concentrations, and optical thickness for the regions where the contribution of the fire smoke to the concentrations of PM2.5 was dominant, in comparison with those of other pollution sources. The emission factors were determined separately for the forested and grassland areas; in case of mixed-type land use, an intermediate scaling was assumed. Despite significant differences between the TA and FRP methodologies, an accurate nonlinear fitting was found between the predictions of these approaches. The agreement was comparatively weak only for small fires, for which the accuracy of both products is ex-pected to be low. The applications of the Fire Assimilation System (FAS) in combination with the dispersion model SILAM showed that both the TA and FRP products are suitable for the evaluation of the emission fluxes from wild-land fires. The fire-originated concentrations of aerosols ( PM2.5, PM10, sulphates and nitrates) and AOD, as predicted by the SILAM model were mainly within a factor of 2-3 compared with the observations. The main challenges of the FAS improvement include refining of the emission factors globally, determination of the types of fires ( smouldering vs flaming), evaluation of the injection heights of the plumes, and predicting the temporal evolution of fires.