Fingerprinting Australian soils based on their source location

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dc.contributor.authorCrawford, Jen_AU
dc.contributor.authorCohen, DDen_AU
dc.contributor.authorAntancio, AJen_AU
dc.contributor.authorManohar, Men_AU
dc.contributor.authorSiegele, Ren_AU
dc.date.accessioned2022-02-11T04:23:19Zen_AU
dc.date.available2022-02-11T04:23:19Zen_AU
dc.date.issued2021-03-03en_AU
dc.date.statistics2022-02-03en_AU
dc.description.abstractSampling of PM2.5 has been undertaken twice per week at the Liverpool and Mascot sites (in Sydney, Australia) since 1998. Ion Beam Analysis (IBA) was applied to each sample to determine the concentrations of 21 elements from hydrogen to lead and the black carbon concentration was determined using photon transmission techniques. Sampling days that displayed high and low airborne soil concentrations were identified and three distinct sets of soil fingerprints were determined using Positive Matrix Factorisation (PMF) source apportionment techniques. A fingerprint for all sampling days (representing the average soil fingerprint for each site), a fingerprint corresponding to low soil days associated with local retrained road dust and a fingerprint for high soil days associated with agricultural activities. The ratios of key soil elements (i.e. Si, Al, Fe) displayed larger temporal variation for the high soil days, whereas lower variation was observed for low (local) soil days. Furthermore, it was found that the El Niño-Southern Oscillation (ENSO) affected the concentration of windblown soil dust in the atmosphere. The average soil fingerprint, for all data, was heavily influenced by sampling days containing higher concentrations of soil dust, thus representing the dominant soil type. However, we did observe differences in the K/Fe and Ca/Si ratios to be a distinguishing factor between the average soil fingerprint and the high soil day fingerprint. The Soil fingerprint for the low soil concentration days had a large fraction of black carbon associated with vehicle emissions, represented retrained road dust. © 2021 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V.en_AU
dc.description.sponsorshipThe authors would like to acknowledge NCRIS funding for accelerators.en_AU
dc.identifier.citationCrawford, J., Cohen, D. D., Atanacio, A., Manohar, M., & Siegele, R. (2021). Fingerprinting Australian soils based on their source location. Atmospheric Pollution Research, 12(3), 173-183. doi:10.1016/j.apr.2021.01.007en_AU
dc.identifier.issn1309-1042en_AU
dc.identifier.issue3en_AU
dc.identifier.journaltitleAtmospheric Pollution Researchen_AU
dc.identifier.pagination173-183en_AU
dc.identifier.urihttps://doi.org/10.1016/j.apr.2021.01.007en_AU
dc.identifier.urihttps://apo.ansto.gov.au/dspace/handle/10238/12813en_AU
dc.identifier.volume12en_AU
dc.language.isoenen_AU
dc.publisherElsevier B. V.en_AU
dc.subjectAerosolsen_AU
dc.subjectSoilsen_AU
dc.subjectDustsen_AU
dc.subjectTrajectoriesen_AU
dc.subjectSamplingen_AU
dc.subjectSouthern Oscillationen_AU
dc.subjectIon beamsen_AU
dc.subjectAtmospheresen_AU
dc.subjectDataen_AU
dc.subjectPhoton transmission scanningen_AU
dc.titleFingerprinting Australian soils based on their source locationen_AU
dc.typeJournal Articleen_AU
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