Chemical characterisation and source identification of atmospheric aerosols in the Snowy Mountains, south-eastern Australia

Characterisation of atmospheric aerosols is of major importance for: climate, the hydrological cycle, human health and policymaking, biogeochemical and palaeo-climatological studies. In this study, the chemical composition and source apportionment of PM2.5 (particulate matter with aerodynamic diameters less than 2.5 mu m) at Yarrangobilly, in the Snowy Mountains, SE Australia are examined and quantified. A new aerosol monitoring network was deployed in June 2013 and aerosol samples collected during the period July 2013 to July 2017 were analysed for 22 trace elements and black carbon by ion beam analysis techniques. Positive matrix factorisation and back trajectory analysis and trajectory clustering methods were employed for source apportionment and to isolate source areas and air mass travel pathways, respectively. This study identified the mean atmospheric PM2.5 mass concentration for the study period was (3.3 +/- 2.5) mu g m(-3). It is shown that automobile (44.9 0.8)%, secondary sulfate (21.4 +/- 0.9)%, smoke (12.3 +/- 0.6)%, soil (11.3 +/- 0.5)% and aged sea salt (10.1 +/- 0.4)% were the five PM2.5 source types, each with its own distinctive trends. The automobile and smoke sources were ascribed to a significant local influence from the road network and bushfire and hazard reduction burns, respectively. Long-range transport are the dominant sources for secondary sulfate from coal-fired power stations, windblown soil from the inland saline regions of the Lake Eyre and Murray-Darling Basins, and aged sea salt from the Southern Ocean to the remote alpine study site. The impact of recent climate change was recognised, as elevated smoke and windblown soil events correlated with drought and El Nino periods. Finally, the overall implications including potential aerosol derived proxies for interpreting palaeo-archives are discussed. To our knowledge, this is the first long-term detailed temporal and spatial characterisation of PM2.5 aerosols for the region and provides a crucial dataset for a range of multidisciplinary research. Crown Copyright (C) 2018 Published by Elsevier BM. All rights reserved.