The influence of regional wind patterns on air quality during forest fires near Sydney, Australia
journal contribution
posted on 2024-11-17, 16:37authored byMichael A Storey, Owen F Price, Paul Fox-Hughes
Particulate pollution from forest fire smoke threatens the health of communities by increasing the occurrence of respiratory illnesses. Wind drives both fire behaviour and smoke dispersal. Understanding regional wind patterns would assist in effectively managing smoke risk. Sydney, Australia is prone to smoke pollution because it has a large population close to fire-prone eucalypt forests. Here we use the self-organising maps (SOM) technique to identify sixteen unique wind classes for the Sydney region from days with active fires, including identifying sea breeze occurrence. We explored differences in PM2.5 levels between classes and between hazard reduction burning (HRB) and wildfire days. For HRB days, classes with the highest PM2.5 mostly had a sea breeze, whereas better air quality days usually had winds aligned across the region (e.g. all westerly). The wind class with the most HRB days had low wind speeds and a sea breeze and was among the worst wind classes for air quality. For wildfire days, days with a sea breeze were also generally of poor air quality but many classes had at least some poor air quality days, most of which were during the 2019–2020 east coast wildfires in New South Wales. Some poor air quality days occurred in wind classes that sent strong plumes directly over air quality stations, spread smoke over a wide area or transported smoke from outside the region. The classes identified may be useful in scheduling HRBs, for example, identifying days with low pollution risk to conduct an HRB, or for assisting in understanding pollution risk and sending health warnings during HRBs and wildfires. Further development of the approach may allow the creation of multi-day classifications for fire managers to plan HRB ignitions over several days to ensure better smoke dispersal. Further research could incorporate other weather predictors or focus on other regions.