Impact of the 2019/2020 Australian Megafires on Air Quality and Health.

The Australian 2019/2020 bushfires were unprecedented in their extent and intensity, causing a catastrophic loss of habitat, human and animal life across eastern-Australia. We use a regional air quality model to assess the impact of the bushfires on particulate matter with a diameter less than 2.5 µm (PM2.5) concentrations and the associated health impact from short-term population exposure to bushfire PM2.5. The mean population Air Quality Index (AQI) exposure between September and February in the fires and no fires simulations indicates an additional ∼437,000 people were exposed to "Poor" or worse AQI levels due to the fires. The AQ impact was concentrated in the cities of Sydney, Newcastle-Maitland, Canberra-Queanbeyan and Melbourne. Between October and February 171 (95% CI: 66-291) deaths were brought forward due to short-term exposure to bushfire PM2.5. The health burden was largest in New South Wales (NSW) (109 (95% CI: 41-176) deaths brought forward), Queensland (15 (95% CI: 5-24)), and Victoria (35 (95% CI: 13-56)). This represents 38%, 13% and 30% of the total deaths brought forward by short-term exposure to all PM2.5. At a city-level 65 (95% CI: 24-105), 23 (95% CI: 9-38) and 9 (95% CI: 4-14) deaths were brought forward from short-term exposure to bushfire PM2.5, accounting for 36%, 20%, and 64% of the total deaths brought forward from all PM2.5. Thus, the bushfires caused substantial AQ and health impacts across eastern-Australia. Climate change is projected to increase bushfire risk, therefore future fire management policies should consider this.

Aerosols in the Pre-industrial Atmosphere.

PURPOSE OF REVIEW: We assess the current understanding of the state and behaviour of aerosols under pre-industrial conditions and the importance for climate. RECENT FINDINGS: Studies show that the magnitude of anthropogenic aerosol radiative forcing over the industrial period calculated by climate models is strongly affected by the abundance and properties of aerosols in the pre-industrial atmosphere. The low concentration of aerosol particles under relatively pristine conditions means that global mean cloud albedo may have been twice as sensitive to changes in natural aerosol emissions under pre-industrial conditions compared to present-day conditions. Consequently, the discovery of new aerosol formation processes and revisions to aerosol emissions have large effects on simulated historical aerosol radiative forcing. SUMMARY: We review what is known about the microphysical, chemical, and radiative properties of aerosols in the pre-industrial atmosphere and the processes that control them. Aerosol properties were controlled by a combination of natural emissions, modification of the natural emissions by human activities such as land-use change, and anthropogenic emissions from biofuel combustion and early industrial processes. Although aerosol concentrations were lower in the pre-industrial atmosphere than today, model simulations show that relatively high aerosol concentrations could have been maintained over continental regions due to biogenically controlled new particle formation and wildfires. Despite the importance of pre-industrial aerosols for historical climate change, the relevant processes and emissions are given relatively little consideration in climate models, and there have been very few attempts to evaluate them. Consequently, we have very low confidence in the ability of models to simulate the aerosol conditions that form the baseline for historical climate simulations. Nevertheless, it is clear that the 1850s should be regarded as an early industrial reference period, and the aerosol forcing calculated from this period is smaller than the forcing since 1750. Improvements in historical reconstructions of natural and early anthropogenic emissions, exploitation of new Earth system models, and a deeper understanding and evaluation of the controlling processes are key aspects to reducing uncertainties in future.

Global atmospheric particle formation from CERN CLOUD measurements.

Fundamental questions remain about the origin of newly formed atmospheric aerosol particles because data from laboratory measurements have been insufficient to build global models. In contrast, gas-phase chemistry models have been based on laboratory kinetics measurements for decades. We built a global model of aerosol formation by using extensive laboratory measurements of rates of nucleation involving sulfuric acid, ammonia, ions, and organic compounds conducted in the CERN CLOUD (Cosmics Leaving Outdoor Droplets) chamber. The simulations and a comparison with atmospheric observations show that nearly all nucleation throughout the present-day atmosphere involves ammonia or biogenic organic compounds, in addition to sulfuric acid. A considerable fraction of nucleation involves ions, but the relatively weak dependence on ion concentrations indicates that for the processes studied, variations in cosmic ray intensity do not appreciably affect climate through nucleation in the present-day atmosphere.

Occurrence of pristine aerosol environments on a polluted planet.

Natural aerosols define a preindustrial baseline state from which the magnitude of anthropogenic aerosol effects on climate are calculated and are a major component of the large uncertainty in anthropogenic aerosol-cloud radiative forcing. This uncertainty would be reduced if aerosol environments unperturbed by air pollution could be studied in the present--day atmosphere, but the pervasiveness of air pollution makes identification of unperturbed regions difficult. Here, we use global model simulations to define unperturbed aerosol regions in terms of two measures that compare 1750 and 2000 conditions-the number of days with similar aerosol concentrations and the similarity of the aerosol response to perturbations in model processes and emissions. The analysis shows that the aerosol system in many present-day environments looks and behaves like it did in the preindustrial era. On a global annual mean, unperturbed aerosol regions cover 12% of the Earth (16% of the ocean surface and 2% of the land surface). There is a strong seasonal variation in unperturbed regions of between 4% in August and 27% in January, with the most persistent conditions occurring over the equatorial Pacific. About 90% of unperturbed regions occur in the Southern Hemisphere, but in the Northern Hemisphere, unperturbed conditions are transient and spatially patchy. In cloudy regions with a radiative forcing relative to 1750, model results suggest that unperturbed aerosol conditions could still occur on a small number of days per month. However, these environments are mostly in the Southern Hemisphere, potentially limiting the usefulness in reducing Northern Hemisphere forcing uncertainty.

The magnitude and sources of uncertainty in global aerosol.

Aerosol radiative forcing over the industrial period has remained the largest forcing uncertainty through all IPCC assessments since 1996. Despite the importance of this uncertainty for our understanding of past and future climate change, very little attention is given to the problem of uncertainty reduction in its own right, mainly because most uncertainty analysis approaches are not appropriate to computationally expensive global models. Here we show how a comprehensive understanding of global aerosol model parametric uncertainty can be obtained by using emulators. The approach enables a Monte Carlo sampling of the model uncertainty space based on a manageable number of simulations. This allows full probability density functions of model outputs to be generated from which the uncertainty and its causes can be diagnosed using variance decomposition. We apply this approach to global concentrations of particles larger than 3 and 50 nm diameter (N3 and N50) to produce a ranked list of twenty-eight processes and emissions that control the uncertainty. The results show that the uncertainty in N50 is much more strongly affected by emissions and processes that control the availability of gas phase H2SO4 than by uncertainties in the nucleation rate itself, which cause generally less than 10% uncertainty in N50 in July. Secondary organic aerosol production is assumed to be very uncertain (5-360 Tg a(-1) for biogenic emissions) but the effect on global N3 uncertainty is < 3% except in a few hotspots, and generally < 2% for N50. A complete understanding of the model uncertainty combined with global observations can be used to determine plausible and implausible parts of parameter space as well as to identify model structural weaknesses. In this direction, a preliminary comparison of the model ensemble with observations at Hyytiala, Finland, suggests that an organic-mediated boundary layer nucleation mechanism would help to optimise the behaviour of the model.