Guest post by Owen Price (Senior Research Fellow, Centre for Environmental Risk Management of Bushfires, UOW)
Fire management agencies in southern Australia have increased the amount of prescribed burning in southern Australia in recent years as a strategy to reduce the risk from bushfire. One of the potential downsides of this strategy is an increase in smoke exposure to communities on the urban interface because a larger area is treated than would burn from bushfire. Planners of prescribed fires try to avoid smoke impact by modelling the likely dispersion of smoke and avoiding days when smoke will affect local communities. We know very little about the actual smoke impact from prescribed fires, especially near the fire, and the accuracy of smoke dispersal models.
To address this uncertainty, researchers from the University of Wollongong’s Centre for Environmental Risk Management of Bushfire conducted a detailed study of smoke dispersal at one small (52 ha) and one large (700 ha) prescribed fire near Appin in NSW using stationary and mobile pollution monitors, visual observations and rain radar data and compared observations to predictions from an atmospheric dispersion model. The 52 ha fire produced a smoke plume about 800 m high and 9 km long. Particle concentrations (PM2.5) reached very high peak values (>400 μg/m3) and high 24 hour average values (>100 μg/m3) at several locations next to or within ~500 m downwind from the fire, but low levels elsewhere (the national standard aims for daily average exposure < 25 μg/m3). The 700 ha fire produced a much larger plume, peaking at ~2000 m elevation (Figure 1)
Figure 1: Cross-section through Bureau of Meteorology rain radar data showing the plume from the 700 ha fire reached 2 km elevation.
and affecting downwind areas up to 14 km away. Both peak and 24 hour average PM2.5 values near the fire were lower than for the 52 ha fire, but this may be because the monitoring locations were further from the fire. Some lofted smoke spread north against the ground-level wind direction. Smoke from this fire collapsed to the ground during the night at different times in different locations (Figure 2). Although it is hard to attribute particle concentrations definitively to smoke, it seems that the collapsed plume affected a huge area including the towns of Wollongong, Bargo, Oakdale, Camden and Campbelltown (~120,000 ha). PM2.5 concentrations up to 169 μg/m3 were recorded on the morning following the fire.
Figure 2: Trace of Carbon Monoxide measurements for the 700 ha fire at two mine sites near the fire (500 m and 2 km away). This shows a night-time peak in pollution from the collapse of the plume. Mines are evacuated when the level exceeds 15 ppm.
The atmospheric dispersion model accurately predicted the general behaviour of both plumes in the early phases of the fires, but was poor at predicting fine-scale variation in particulate levels (e.g. places 500 m from the fire). The correlation between predicted and observed varied between 0 and 0.87 depending on location. The model also completely failed to predict the night time collapse of the plume from the 700 ha fire.
This study gives a preliminary insight into potential for large smoke impacts from prescribed burning. Further research as part of this project is measuring the size of smoke plumes from a large set of prescribed fires and bushfires (~300) using the rain radar data. This will help us to to better understand when and why smoke impacts might occur and provide better predictions of pollution risk.
