The biosolids industry in Australia has historically developed in response to the regional challenges, resources available and their markets perception and demands. This has resulted in a variety of priorities, management strategies and reuse applications currently operating nationally. To progress and take advantage of the recovered resources provided by the development of the biosolids industry a national framework providing a level field is required. The result would see the biosolids industry in an improved growth position, more effective utilisation of resources, more control over risk to health and the environment and improve our position nationally with adherence to our global responsibility targets. The mechanism to achieve these goals is estimated to be by the application of a non-prescriptive framework which has risk strategies built into progressive steps in the biosolids product development with strategies targeting specific end use.

PhD Thesis underway by Marilyn Braine.

This project established unifying framework for the calculation of robustness metrics, which assists with understanding how robustness metrics work, when they should be used, and why they sometimes disagree. The framework categorizes the suitability of metrics to a decision-maker based on the decision-context, the decision-makers’s preferred level of risk aversion, and the decision-maker’s preference towards maximising performance or minimising variance. This conceptual framework describes when different robustness metrics are likely to agree and disagree.

PhD Thesis completed by Cameron McPhail in August 2020.

Sunlight-induced degradation is an important removal mechanism for some contaminants and has been commonly overlooked as a removal mechanism in wastewater systems in the past. This project aims to predict the direct sunlight-induced degradation, or direct photolysis, of contaminants of emerging concern in wastewater treatment lagoons to improve monitoring and removal efficacy of the contaminants, and thereby enable water operators and management to perform ecological risk assessment and make better management decisions.

Honours Thesis underway by Michelle Um.

This study successfully developed a variety of specific qPCR assays for the characterisation of host faecal contamination.
The results supported the coupled use of mitochondrial markers with Bacteroides markers for microbial risk assessment for improved efficiency and accuracy.

Honours Thesis completed by Sarah Aucote in November 2017.

This project characterised the acute cytotoxicity of a hydraulic fracturing fluid using a human gastrointestinal cell line and, using this data, contribute to the understanding of potential human health risks posed by Coal Seam Gas (CSG) extraction in Queensland.

Honours Thesis completed by Madeleine Payne in October 2012.

This project investigated the impact of hazardous events (i.e. high organic, high salinity, high toxic shock loads in influent, aeration lost or membrane damage) on decentralised membrane bioreactor performance. This investigation demonstrated validation of membrane bioreactors to fully comply with the requirements of current Australian water recycling guidelines and to provide necessary risk-based information for health and environmental regulators.

PhD Thesis completed by Thi Thanh Trang Trinh in November 2013.

Lake hydrodynamic models are used by water utilities to provide an estimation of the conditions within a water storage. Increasingly, water utilities are employing a pathogen module to simulate the advection and dispersion of pathogens in source water. Lake model outputs provide forecasted pathogen concentrations across the water column of lakes and reservoirs, including at the offtakes of water treatment plants. This pathogen information, in combination with any monitored pathogen concentrations, provides important inputs to water quality experts to conduct quantitative microbial risk assessment.

The quality and outcomes of a lake modelling process depend on several critical steps, some of which are implicitly used by modellers, but which are often not adopted routinely or communicated widely as part of a quality assurance process. There is an emerging need in the drinking water supply industry for information and guidance on the appropriate use of lake models to support QMRAs. Ideally, the information is provided through a set of best practice guidelines that demonstrate a series of quality assurance principles and actions to ensure that model development, implementation and application represent best practice and are commensurate with the intended purpose. This project will identify, review, and communicate guidance on specific modelling steps, such as project administration, conceptual modelling framework, model evaluation metrics, and uncertainty analysis practice, and prepare consultative draft of the detailed best practice guidelines.

The environmental conditions which cause blue-green algae (cyanobacteria) blooms vary according to location, the climate, and other attributes of aquatic ecosystems. This variety has made it difficult to develop one broadly applicable predictive model for cyanobacterial blooms. Water utilities monitor source waters to implement cyanobacterial risk management programmes but there are no standard protocols while limited information transfer between utilities has prevented the identification of management strategies that do or do not work. This research reviewed literature about early warning systems (Almuhtaram et al., 2021) and source control strategies, conducted a survey of 35 utilities in America and Canada (74%) and Australia (Kibuye et al., 2021) and evaluated selected control strategies. These different types of information were synthesised into decision trees within an overarching guidance document. It was concluded that a 3-tier framework to detect algal blooms which monitored biological activity, then confirmed the identification of cyanobacterial genes and associated metabolites gave sufficient early warning, while multi-barrier control strategies gave field-scale efficacy and enabled timely responses.

The aim of Project 1127 was to help the water industry better manage and understand contaminants of emerging concern (CEC), through:

• The creation of a CEC database
• The development of a classification system based on source, treatment and effects to facilitate management of CEC by the water industry
• The development of risk assessment approaches based on different classifications (i.e., source, treatment and effects) and integrate this functionality into the database as a prioritisation tool
• Guidance on including CEC into current water quality risk management plans/frameworks (e.g. ADWG, AGWR)

Every day, Australians produce ~5 billion litres of wastewater, which contains a cocktail of chemicals. Industries that discharge wastewater are required to assess chemical risks to the receiving environments by conducting whole animal direct toxicity assessments (DTAs), which are expensive and pose an ethical dilemma. Our preliminary research shows that new in vitro bioassays provide an ethical and cost effective alternative that could be incorporated into DTA programs if their ecological relevance can be demonstrated. This project will develop and validate a new and internationally significant suite of in vitro bioassays for incorporation into DTA programs, leading to more ethical, cost effective and improved environmental protection.