Browsing by Author "Ayoko, GA"

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    Elemental composition of ambient fine particles in urban schools : sources of children’s exposure
    (Aerosol and Air Quality Research, 2014-12-01) Crilley, LR; Ayoko, GA; Stelcer, E; Cohen, DD; Morawska, L
    Currently, there is a limited understanding of the sources of ambient fine particles that contribute to the exposure of children at urban schools. Since the size and chemical composition of airborne particle are key parameters for determining the source as well as toxicity, PM1 particles (mass concentration of particles with an aerodynamic diameter less than 1 µm) were collected at 24 urban schools in Brisbane, Australia and their elemental compositions determined. Based on the elemental compositions four main sources were identified; secondary sulphates, biomass burning, vehicle and industrial emissions. While secondary sulphates were likely to be a large contributing source by mass, industrial emissions accounted for the most variation in trace metals in the PM1 that children were exposed to at the schools. PM1 concentrations at the schools were compared to the elemental composition of the PM2.5 particles (mass concentration of particles with an aerodynamic diameter less than 2.5 µm) from a previous study conducted at a suburban and roadside site in Brisbane. This comparison suggested that the more toxic heavy metals (V, Cr, Ni, Cu, Zn and Pb), mostly from vehicle and industrial emissions, were predominantly in the PM1 fraction. Thus, the results from this study points to PM1 as a potentially good particle size fraction for investigating the health effects of airborne particles. Further work is required to confirm this hypothesis. © 2014 Taiwan Association for Aerosol Research
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    Relating urban airborne particle concentrations to shipping using carbon based elemental emission ratios
    (Elsevier, 2014-10) Johnson, GR; Juwono, AM; Friend, AJ; Cheung, HC; Stelcer, E; Cohen, DD; Ayoko, GA; Morawska, L
    This study demonstrates a novel method for testing the hypothesis that variations in primary and secondary particle number concentration (PNC) in urban air are related to residual fuel oil combustion at a coastal port lying 30 km upwind, by examining the correlation between PNC and airborne particle composition signatures chosen for their sensitivity to the elemental contaminants present in residual fuel oil. Residual fuel oil combustion indicators were chosen by comparing the sensitivity of a range of concentration ratios to airborne emissions originating from the port. The most responsive were combinations of vanadium and sulphur concentration ([S], [V]) expressed as ratios with respect to black carbon concentration ([BC]). These correlated significantly with ship activity at the port and with the fraction of time during which the wind blew from the port. The average [V] when the wind was predominantly from the port was 0.52 ng m−3 (87%) higher than the average for all wind directions and 0.83 ng m−3 (280%) higher than that for the lowest vanadium yielding wind direction considered to approximate the natural background. Shipping was found to be the main source of V impacting urban air quality in Brisbane. However, contrary to the stated hypothesis, increases in PNC related measures did not correlate with ship emission indicators or ship traffic. Hence at this site ship emissions were not found to be a major contributor to PNC compared to other fossil fuel combustion sources such as road traffic, airport and refinery emissions. © 2014, Elsevier Ltd.
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    Source apportionment of PM2.5 at two receptor sites in Brisbane, Australia
    (CSIRO Publishing, 2011) Friend, AJ; Ayoko, GA; Stelcer, E; Cohen, DD
    In this study, samples of particulate matter with aerodynamic diameter less than 2.5 mu m (PM2.5) collected at two sites in the south-east Queensland region, a suburban (Rocklea) and a roadside site (South Brisbane), were analysed for H, Na, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Br, Pb and black carbon (BC). Samples were collected during 2007-10 at the Rocklea site and 2009-10 at the South Brisbane site. The receptor model Positive Matrix Factorisation was used to analyse the samples. The sources identified included secondary sulfate, motor vehicles, soil, sea salt and biomass burning. Conditional probability function analysis was used to determine the most likely directions of the sources. Future air quality control strategies may focus on the particular sources identified in the analysis. © 2011, CSIRO Publishing
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    Source identification and source apportionment of air pollution aeolian dust: its potential role as a carrier of terrestrial salt in Australia
    (Australian Nuclear Science and Technology Organisation, 2008-07) Friend, AJ; Ayoko, GA; Stelcer, E