Understanding third hand exposure of Australian people to methamphetamine. In Australia, there is high community concern around inadvertent exposure to methamphetamine residues in contaminated houses. In this proposal, an interdisciplinary research team aim to engage with public health authorities and public housing industry to conduct collaborative research on total exposure to methamphetamine in contaminated indoor environments. The project will assess exposure pathways (via air, dust, surface ....Understanding third hand exposure of Australian people to methamphetamine. In Australia, there is high community concern around inadvertent exposure to methamphetamine residues in contaminated houses. In this proposal, an interdisciplinary research team aim to engage with public health authorities and public housing industry to conduct collaborative research on total exposure to methamphetamine in contaminated indoor environments. The project will assess exposure pathways (via air, dust, surfaces) and link them with methamphetamine levels in samples from occupants (urine, hair). The project is expected to significantly enhance our understanding of how third hand exposure leads to internal exposure in humans. This knowledge provides evidence for policies on residential indoor exposures and remediation strategies.Read moreRead less
Revolutionising water-quality monitoring in the information age. In today’s information age, automated low-cost sensors distributed in the environment have the potential to revolutionise the way we monitor and manage air, water and soil. This project aims to develop novel statistical methods to detect anomalies in the data generated from these in-situ sensors with computationally efficient modelling on river networks through space and time, with the applied goals of automating anomaly detection ....Revolutionising water-quality monitoring in the information age. In today’s information age, automated low-cost sensors distributed in the environment have the potential to revolutionise the way we monitor and manage air, water and soil. This project aims to develop novel statistical methods to detect anomalies in the data generated from these in-situ sensors with computationally efficient modelling on river networks through space and time, with the applied goals of automating anomaly detection in water-quality data and generating predictions of sediment and nutrient concentrations throughout river networks in near-real time. This will represent a fundamental increase in scientific knowledge, which will be immediately useful in the domains of aquatic science, environmental monitoring, and statistics.Read moreRead less