Characterisation of aerosol constituents from wildfires using satellites and model data: a case study in Knysna, South Africa

Abstract

ABSTRACTStrong winds and dry conditions make it difficult to contain wild fires worldwide. Such fires could cause devastating effects on landscape structures around many urban/peri-urban areas. The greater impact of such fires is commonly felt when landscape elements such as forest vegetation biomass fuel increase the wild fire risk to people and their properties. In order to mitigate the impact of a wild fire at local level, it is imperative to understand its spatial distribution and fuel load dynamics surrounding it. This study aimed at exploring the possibility of integrating various satellites and model data to characterise the aerosols emissions from wild fires which occurred at Knysna (South Africa). The Moderate Resolution Imaging Spectroradiometer (MODIS), the Sentinel-2 normalized difference vegetation index (NDVI), the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), the Hybrid Single-Particle Lagrangian Intergrated trajectory (HYSPLIT) model and the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2) model were employed to characterise the Knysna fires, and the resultant atmospheric conditions that prevailed at altitudes lower than 10 km. Large flames and high amounts of smoke were observed at the Knysna forests by the Sentinel-2 optical data. Our findings showed that there was an apparent reduction in the green vegetation biomass coverage of up to 20.2% following the wildfires as observed by Sentinel-2 data analysis. Biomass burning (BB) aerosols and smoke were observed to reach high altitudes of 2–4 km by CALIPSO. Pyrocumulus clouds were also observed at altitudes of 7.2 km. These clouds were a result of the mixing of the smoke and clouds in the mid-troposphere. The HYSPLIT model and MERRA-2 model showed that the emitted BB aerosols and smoke did not travel inland but rather dispersed in an eastward and south-eastward direction into the Indian Ocean from the source. A multi-satellite data approach proved to be a valuable resource to study the extent of wild fires and to determine their atmospheric impact and thus contributing to climate change. The transport models data was resourceful in determining the destination of the wild fires emissions.