Developing Bayesian networks in managing the risk of Legionella colonisation of groundwater aeration systems.

An Australian water utility has developed a Legionella High Level Risk Assessment (LHLRA) which provides a semi-qualitative assessment of the risk of Legionella proliferation and human exposure in engineered water systems using a combination of empirical observation and expert knowledge. Expanding on this LHLRA, we propose two iterative Bayesian network (BN) models to reduce uncertainty and allow for a probabilistic representation of the mechanistic interaction of the variables, built using data from 25 groundwater treatment plants. The risk of Legionella exposure in groundwater aeration units was quantified as a function of five critical areas including hydraulic conditions, nutrient availability and growth, water quality, system design (and maintenance), and location and access. First, the mechanistic relationship of the variables was conceptually mapped into a fishbone diagram, parameterised deterministically using an expert elicited weighted scoring system and translated into BN. The "sensitivity to findings" analysis of the BN indicated that system design was the most influential variable while elemental accumulation thresholds were the least influential variable for Legionella exposure. The diagnostic inference was used in high and low-risk scenarios to demonstrate the capabilities of the BNs to examine probable causes for diverse conditions. Subsequently, the causal relationship of Legionella growth and human exposure were improved through a conceptual bowtie representation. Finally, an improved model developed the predictors of Legionella growth and the risk of human exposure through the interaction of operational, water quality monitoring, operational parameters, and asset conditions. The use of BNs modelling based on risk estimation and improved functional decision outputs offer a complementary and more transparent alternative approach to quantitative analysis of uncertainties than the current LHLRA.

Recycling waste plastics in developing countries: Use of low-density polyethylene water sachets to form plastic bonded sand blocks.

In many developing countries low-density polyethylene (LDPE) sheets, bags and water sachets are a major waste problem because local collection and recycling systems do not exist. As a result, LDPE has no value and is dumped causing aesthetic, environmental and public health issues. A relatively simple technology has been developed in the Cameroon that produces LDPE-bonded sand blocks and pavers. The application of this technology is an example of a community-driven waste management initiative that has potential to impact on the global plastics waste crisis because it can transform waste LDPE and other readily available types of plastics into a valuable local resource. In this research, waste LDPE water sachets have been melted and mixed with sand to form LDPE-bonded sand blocks. The effect of sand particle size and sand to plastic ratio on density, the compressive strength and water adsorption are reported. Optimum samples have been further characterised for flexural strength and thermal conductivity. LDPE-bonded sand is a strong, tough material with compressive strengths up to ∼27 MPa when produced under optimum processing conditions. The density and compressive strength increase as the particle size of the sand decreases. The potential for using this simple technology and the materials it produces to transform LDPE plastic waste management in developing countries is discussed.