Understanding the role of deep flaming in violent pyroconvective events. This project aims to improve the prediction of firestorms by combining state-of-the-art knowledge of dynamic bushfire behaviour with atmospheric models to provide a comprehensive understanding of how the heat and moisture released by a bushfire interacts with ambient atmospheric instability to produce extreme fire events. Firestorms represent the most extreme and catastrophic phase of development of a bushfire. They often c ....Understanding the role of deep flaming in violent pyroconvective events. This project aims to improve the prediction of firestorms by combining state-of-the-art knowledge of dynamic bushfire behaviour with atmospheric models to provide a comprehensive understanding of how the heat and moisture released by a bushfire interacts with ambient atmospheric instability to produce extreme fire events. Firestorms represent the most extreme and catastrophic phase of development of a bushfire. They often cause broad-scale loss of property, environmental damage and human fatalities. Firestorms cannot be suppressed, and so accurate and timely warnings of their occurrence, combined with appropriate community responses, are the only way of mitigating their effects. Better understanding of extreme fire processes may improve mitigation planning, community safety, environmental outcomes and emergency response measures.Read moreRead less
Developing a predictive toxicity model for metallic anions in plants. This project aims to develop competitive anionic toxicity models for antimony, arsenic, molybdenum and selenium supported by detailed speciation information. Available ecotoxicological models for inorganic toxicants have exclusively focused on cations such as zinc, and ignored anionic toxicants such as arsenic and antimony. For available models on cations to be applicable to contaminated environments, it is essential for equiv ....Developing a predictive toxicity model for metallic anions in plants. This project aims to develop competitive anionic toxicity models for antimony, arsenic, molybdenum and selenium supported by detailed speciation information. Available ecotoxicological models for inorganic toxicants have exclusively focused on cations such as zinc, and ignored anionic toxicants such as arsenic and antimony. For available models on cations to be applicable to contaminated environments, it is essential for equivalent anionic toxicity models be developed. This project will develop the first such model, which will provide new insights on ecotoxicological modelling for inorganic anionic toxicants. The project will transform ecotoxicological modelling approaches for metals and metalloids in terrestrial systems and directly improve our ability to assess risks associated with environmental contamination.Read moreRead less