Air quality impacts of the 2019-2020 Black Summer wildfires on Australian schools

The 2019-2020 Black Summer wildfires wrought destruction across Australia and exposed millions of people to air pollution. Using a new school-based observational network alongside long-standing observations, we provide the first assessment of spatiotemporal variations in Black Summer's air pollution impacts across Sydney, including how meteorology modulated the severity and timing of these episodes. Throughout the summer, hourly fine particulate matter (PM2.5) concentrations at schools often exceeded 25 mu g m(-3) (i.e. the national daily average standard for PM2.5) for up to 8 h, with PM2.5 spikes frequently reverberating across Sydney, creating city-wide impacts. However, timing and magnitude varied markedly with location, and a geographic sequence of impacts was evident, reflecting smoke transport by the passage of synoptic features, especially pre-frontal troughs. Temperature, dew point temperature, and air pressure had significant, mainly positive non-linear associations with PM2.5, whereas negative relative humidity-PM2.5 associations increased in strength at similar to 70% humidity, and negative wind speed-PM2.5 associations reversed at higher speeds reflecting increased synopticscale advection of PM2.5. This study provides insights into the complex spatiotemporal variations in air pollution during wildfires and the corresponding influential meteorological factors. Together, these insights can inform improvements in air quality forecasting and support planning to reduce exposure to smoke emissions, thus increasing the preparedness requirements of society to mitigate the impacts of severe wildfires.

Automated summary

The study examined the spatiotemporal variations in air pollution during the Black Summer wildfires in Australia, revealing the significant influence of meteorological conditions on the severity and timing of pollution episodes. Different locations experienced varying levels and impacts of pollution, with meteorological factors like wind direction and speed showing distinct associations with PM2.5 concentrations.