The Australian 2019/2020 bushfires were unprecedented in both their extent and intensity, causing a catastrophic loss of habitat and human and animal life across eastern-Australia. Between October 2019 and February 2020 hundreds of fires burned, peaking in size in December and January and releasing the equivalent of half of Australia’s annual carbon dioxide (CO2) emissions. We use a high-resolution atmospheric-chemistry transport model to assess the impact of the bushfires on particulate matter with a diameter less than 2.5 µm (PM2.5) concentrations across eastern Australia. The health burden from short-term population exposure to PM2.5 is then quantified using a concentration response function. We find that between October and February an additional ~1.9 million people in eastern-Australia were exposed to ‘Poor’, ‘Very Poor’ and ‘Hazardous’ air quality index levels due to the fires. The impact of the bushfires on AQ was concentrated in the cities of Sydney, Newcastle-Maitland and Canberra-Queanbeyan during November, December and, also in Melbourne, in January. The health burden of bushfire PM2.5 across eastern-Australia, regionally and at city level is also estimated. Our estimate indicates that between October and February 171 (95% CI: 66 – 291) deaths were brought forward. The health burden was largest in New South Wales (109 (95% CI: 41 – 176) deaths brought forward), Queensland (15 (95% CI: 5 – 24)) and Victoria (35 (95% CI: 13 – 56)). At a city level the health burden was concentrated in Sydney (65 (95% CI: 24 – 105)), Melbourne (23 (95% CI: 9 – 38)) and Canberra-Queanbeyan (9 (95% CI: 4 – 14)), where large populations were exposed to high PM2.5 concentrations due to the bushfires.

Australian fires are a primary driver of variability in Australian atmospheric composition and contribute significantly to regional and global carbon budgets. However, biomass burning emissions from Australia remain highly uncertain. In this work, we use surface in situ, ground-based total column and satellite total column observations to evaluate the ability of two global models (GEOS-Chem and ACCESS-UKCA) and three global biomass burning emission inventories (FINN1.5, GFED4s, and QFED2.4) to simulate carbon monoxide (CO) in the Australian atmosphere. We find that emissions from northern Australia savanna fires are substantially lower in FINN1.5 than in the other inventories. Model simulations driven by FINN1.5 are unable to reproduce either the magnitude or the variability of observed CO in northern Australia. The remaining two inventories perform similarly in reproducing the observed variability, although the larger emissions in QFED2.4 combined with an existing high bias in the southern hemisphere background lead to large CO biases. We therefore recommend GFED4s as the best option of the three for global modelling studies with focus on Australia or the southern hemisphere. Near fresh fire emissions, the higher resolution ACCESS-UKCA model is better able to simulate surface CO than GEOS-Chem, while GEOS-Chem captures more of the observed variability in the total column and remote surface air measurements. We also show that existing observations in Australia can only partially constrain global model estimates of biomass burning. Continuous measurements in fire-prone parts of Australia are needed, along with updates to global biomass burning inventories that are validated with Australian data.