The water industry as a whole consumes a considerable amount of energy in the treatment and distribution of water and wastewater. Like all sectors of society today, the industry is focusing efforts on reducing its CO2 emissions and improving the sustainability of its systems and practices. One way of achieving this is through the use of micro-hydropower (MHP) installations in water infrastructure for energy recovery purposes. This paper presents a review of energy use and CO2 emissions in the water industry as well as highlighting the opportunities and challenges for MHP energy recovery. The results indicate that significant potential exists for energy recovery in the water industry. However, many previous investigations have not considered key complexities such as variations in flows or turbine efficiency. Similarly, accurate costing and return on investment data are often absent or lacking sensitivity analysis. Further research is required to address the risks and long-term reliability of installations, alongside the development of firm policy to direct and incentivise sustainability gains in this area.

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The supply and treatment of water is a highly energy intensive process, resulting in large amounts of greenhouse gas emissions as well as incurring large economic costs. Both governments and water service providers worldwide recognise the need for more sustainable water supply systems. In recent years, the use of hydropower turbines within water supply networks has been shown as a viable option for electricity generation. Energy can be recovered in water supply networks at locations of excessively high flow or pressure without loss in the level of service to consumers. The control of pressure to prevent burst pipes and to maintain a reliable water supply service is a top priority for water service providers. This paper presents the results of an analysis of the potential of hydropower energy recovery within water distribution systems in the UK and Ireland. Pressure and flow data were analysed to determine the extent of the potential for energy recovery. The effect of flow rate variation on turbine selection and efficiency was investigated, as well as investment payback period. It was concluded that the sustainability of water supply can be improved through the implementation of small-scale hydropower turbines within water supply networks.

Abstract:The impact of temporal aspects of noise data on model development and intra-urban variability on environmental noise levels are often ignored in the development of models used to predict its spatiotemporal variation within a city. Using a Land Use Regression approach, this study develops a framework which uses routine noise monitors to model the prevailing ambient noise, and to develop a noise variability map showing the variation within a city caused by land-use setting. The impact of data resolution on model development and the impact of meteorological variables on the noise level which are often ignored were also assessed. Six models were developed based on monthly, daily and hourly resolutions of both the noise and predictor data. Cross validation highlighted that only the hourly resolution model having 59% explanatory power of the observed data (adjusted R 2 ) and a potential of explaining at least 0.47% variation of any independent dataset (cross validation R 2 ), was a suitable candidate among all the developed models for explaining intraurban variability of noise. In the hourly model, regions with roads of high traffic volumes, with higher concentrations of heavy goods vehicles, and being close to activity centres were found to have more impact on the prevailing ambient noise. Road lengths were found to be the most influential predictors and identified as having an impact on the ambient noise monitors.

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