Establishing advanced networks for air quality sensing and analyses. Establishing advanced networks for air quality sensing and analyses. This project aims to develop innovative, cost-effective, high resolution air quality networks. Recent developments in sensor technologies improve the ability to harvest atmospheric data. This project will develop, validate and implement methods for high sensitivity atmospheric sensing and apply cutting-edge statistical and analytic techniques to the data sets, ....Establishing advanced networks for air quality sensing and analyses. Establishing advanced networks for air quality sensing and analyses. This project aims to develop innovative, cost-effective, high resolution air quality networks. Recent developments in sensor technologies improve the ability to harvest atmospheric data. This project will develop, validate and implement methods for high sensitivity atmospheric sensing and apply cutting-edge statistical and analytic techniques to the data sets, unprecedented in scope and resolution. Outcomes include an open access database to quantify and visualise intra-urban air pollution and human exposure and develop air quality maps and smoke pollution management tools. It is expected to advance the evidence-based management of air as a resource, increasing economic prosperity and enhancing human health and quality of life.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less
Airborne ultrafine particles in Australian cities. There is an acute deficiency of knowledge in Australia on urban airborne ultrafine particles, originating from transport and other anthropogenic sources, which pose significant health and environmental risks. The aim of this project is to address this deficiency by an extensive multi-city, cross-disciplinary study using state of the art instrumentation and data analytic techniques. The outcome will be an in depth, quantitative insight into the c ....Airborne ultrafine particles in Australian cities. There is an acute deficiency of knowledge in Australia on urban airborne ultrafine particles, originating from transport and other anthropogenic sources, which pose significant health and environmental risks. The aim of this project is to address this deficiency by an extensive multi-city, cross-disciplinary study using state of the art instrumentation and data analytic techniques. The outcome will be an in depth, quantitative insight into the characteristics of the particles, their sources and spatial and temporal variation across different urban areas and time scales. Further, the impacts of changing fuels, vehicle technologies, and climate on future trends of the particles will be elucidated.Read moreRead less