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Abstract
Abstract. This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-μm 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 non-linear 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 expected 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.
Highlights
Each year about 5000 km2 of forested land in Europe is burned by more than 50 000 fires (Keramitsoglou et al, 2004)
The goal of the current paper is to present a newgeneration Fire Assimilation System (FAS), which evaluates globally the emission fluxes of primary particulate matter originated from wild-land fires on a daily resolution
The Fire Assimilation System presented above is based on a simple set of assumptions and involves explicit scaling factors to convert the Temperature Anomaly (TA) or Fire Radiative Power (FRP) values to the emissions of particulate matter and other pollutants
Summary
Each year about 5000 km of forested land in Europe is burned by more than 50 000 fires (Keramitsoglou et al, 2004). The wild-land fires occur in all European countries being intensive in the arid southern and eastern regions. The MODIS fire detection procedure is based on a contextual algorithm of Giglio et al (2003) that exploits the strong emission of mid-infrared radiation from fires (Dozier, 1981; Matson and Dozier, 1981). If the characterization of the background is successful, a series of threshold tests are used to confirm the active-fire hypothesis. These search for the characteristic signature of an active fire, in which both the 4 μm brightness temperature and the difference between the 4 and 11 μm brightness temperatures depart substantially from those of the non-fire background. A dedicated effort is needed to separate the wild-land fires from other types of fires, which is done on the basis of the land use reported for the detected fire pixel
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