Statistical modelling of air quality impacts from individual forest fires in New South Wales, Australia

Abstract

Abstract. Wildfires and hazard reduction burns produce smoke that contains pollutants including particulate matter. Particulate matter less than 2.5 µm in diameter (PM2.5) is harmful to human health, potentially causing cardiovascular and respiratory issues that can lead to premature deaths. PM2.5 levels depend on environmental conditions, fire behaviour and smoke dispersal patterns. Fire management agencies need to understand and predict PM2.5 levels associated with a particular fire so that pollution warnings can be sent to communities and/or hazard reduction burns can be timed to avoid the worst conditions for PM2.5 pollution. We modelled PM2.5, measured at air quality stations in New South Wales (Australia) from ∼ 1400 d when individual fires were burning near air quality stations, as a function of fire and weather variables. Using Visible Infrared Imaging Radiometer Suite (VIIRS) satellite hotspots, we identified days when one fire was burning within 150 km of at least 1 of 48 air quality stations. We extracted ERA5 gridded weather data and daily active fire area estimates from the hotspots for our modelling. We created random forest models for afternoon, night and morning PM2.5 levels to understand drivers of and predict PM2.5. Fire area and boundary layer height were important predictors across the models, with temperature, wind speed and relative humidity also being important. There was a strong increase in PM2.5 with decreasing distance, with a sharp increase when the fire was within 20 km. The models improve our understanding of the drivers of PM2.5 from individual fires and demonstrate a promising approach to PM2.5 model development. However, although the models predicted well overall, there were several large under-predictions of PM2.5 that mean further model development would be required for the models to be deployed operationally.

Comparing the Effects of Wildfire and Hazard Reduction Burning Area on Air Quality in Sydney

“…Previous research has aimed to understand differences in smoke production, transport and exposure by fire type. However, fire type has not consistently been a useful or the best available predictor of air-quality-related factors, including fuel consumption [11], PM 2.5 concentration from individual fires [15] and large particle plume top height [13], with fire area usually a more reliable predictor. Some studies have found large differences in the effect of wildfire and HRB fire area on air quality.…”

“…The extreme end of fire behaviour distributions (largest areas, fastest spreading fires) are wildfires, but these are a minority of all fires. The outcome of this is that other fire characteristics (intensity, fuel amount, weather) that directly influence smoke production, transport and exposure are probably better than fire type for the prediction of air quality metrics [15]. Distance from a fire is also important for understanding PM 2.5 levels, with monitoring stations close to fires (<20 km) having higher PM 2.5 levels than those farther away [15,33], and HRBs (and their plumes) tend to be closer to urban areas where monitors are than wildfires [14,34].…”

“…This was to exclude days with only isolated hotspots, e.g., small wood piles or agricultural fires, and to exclude days without fires that may have had heightened PM 2.5 due to sources other than forest fires (e.g., dust, wood heater smoke). These very small fires that were excluded from our analysis (mainly small non-HRB and non-wildfires) were unlikely to substantially influence regional PM 2.5 observations because very small fires are generally associated with low observed PM 2.5 [15].…”