Inadequate access to clean water is hugely detrimental both to economic development and human health. In the developing world 3900 children die daily from diseases transmitted through unsafe water and 1.2 billion people lack access to safe water (1). Even in the developed world, waterborne pathogens can cause huge problems, in terms of both public health and lost productivity. For example, in the past few years cryptosporidiosis outbreaks in the UK have infected hundreds of people and resulted in hundreds of thousands of households being issued with boil water notices (2). As the population continues to grow, increased industrialisation occurs and climate change reduces freshwater supplies, the problem of water scarcity will intensify (1). One of the biggest challenges is to detect the presence of pathogens, especially those present at low level concentrations. The rapid and robust detection of pathogens is required in the water industry to monitor the integrity of existing treatment facilities and in international development to rapidly and accurately obtain analytical data on water quality in the field. A Scottish Water R&D aim is to achieve zero-disruption to the public, while safeguarding drinking water quality. Therefore, rapid and accurate methods to monitor water for pathogen presence are required. Current methods to indicate, e.g. cryptosporidium presence take around 3 days. Furthermore, the method does not indicate viability or species, which is essential information to determine whether the detected oocysts are pathogenic to humans and to decide on appropriate response strategies. The ideal solution would be an online automated detection system linked to methods for rapid determination of species and viability. We propose a novel biosensing approach for more rapid detection of waterborne pathogens with the aim of incorporating sensors into online automated systems. The recognition of the pathogen utilises imprinted polymers, which provide a low-cost and robust alternative to the current antibody-based recognition, and have previously been used to detect benzimidazole in water (3). The signal transduction will be performed by low-cost, wireless magnetoelastic (ME) sensors (4); such sensors have been used to detect pesticides in water (5). The project will investigate various techniques for the synthesis of imprinted polymers, on ME sensors, capable of specific detection of pathogens of interest to the water industry. This project will focus upon cryptosporidium, further work will extend to Giardia and bacteria. While the above technology will indicate pathogen presence, it is extremely desirable to obtain further information about the detected pathogen, e.g. speciation and viability. To provide information about which species of pathogen is present, we will investigate lab-on-a-chip PCR. Microfluidic PCR systems allow for rapid temperature cycling and Zaysteva et al demonstrated an assay of pathogen RNA on a PDMS microfluidic system in just 15 mins (6). Scottish Water have demonstrated 80% successful PCR from one cryptosporidium oocyst, although 24hrs is required for testing. We will study whether similar success rates can be achieved, in considerably shorter timescales, when this protocol is adapted for incorporation into a microfluidic device. 1. Shannon et al, Nature 2008 452 301 2. http://www.cieh.org/policy/cryptosporidium_outbreaks.html 3. Cocha et al, Talanta 2009 78 1029 4. Grimes et al, Sensors 2002 2 294 5. Zourob et al, Analyst 2007 132 338 6. Zaysteva et al, Lab Chip 2005 5 805

Clean drinking water is vital for human life. Water is also essential to agriculture, energy and manufacture. The United Nations recently reported an expected increase in demand for water of 55% by 2050. The reliable and sustainable provision of clean water for all is urgently needed worldwide, and is the focus of one of the Sustainable Development Goals established by the UN (Goal 6). In a scenario where conventional water resources are becoming increasingly insecure and contaminated, the development of new improved and resilient water treatment technologies is imperative to meet the UN's target. This proposal takes an important step towards a solution involving membrane filtration in water supply. Nanofiltration (NF) and reverse osmosis (RO) membrane processes are increasingly popular as they supply high quality water, including drinking water, from any available water source. A high pressure feed water is filtered through the membrane, producing permeate, i.e. clean water, whilst contaminants are retained on the feed side. Membranes are however known to foul due to an accumulation of contaminants on the membrane surface. Biofouling in particular, is caused by the accumulation, adhesion and growth of microorganisms on the membrane surface leading to dangerously reduced quality and flow of permeated water, increased operational and energy costs and membrane life reduction. Chemical cleaning regimes, such as chlorination, are used to combat membrane biofouling. These processes are inefficient and they require process downtime. They can also modify the properties of the membrane, ultimately reducing its life. This project will demonstrate a simple, novel cleaning technique to prevent biofouling formation on NF and RO membranes. We will explore the regular introduction of a burst of high salinity - a High Salinity Pulse (HSP) - into the input feed flow of the membrane. The HSP causes a high osmotic pressure difference to occur between the feed and permeate sides of the membrane. As a consequence, the direction of water permeation through the membrane temporarily reverses, flowing from the permeate side to the feed side. The membrane is backwashed and adhered microorganisms removed from the surface, avoiding growth and subsequent biofilm formation. This will maintain water production quantity and quality at lower operational and energy costs and extend the usable lifespan of a membrane, having an immediate transformative effect on industries where NF and RO membranes are used, which include the water, wastewater, aquaculture and food & drink industries.

Here we argue that decentralised and point of use water infrastructure and technologies are fundamental in delivering health and economic sustainability in rapidly growing cities of the Global South. Further we advocate that research on decentralisation with developing world partners has the potential to catalyse radical change in unsustainable centralised western practices and thus will be mutually beneficial. There has been significant investment by charities and government agencies in developing novel wastewater treatment technologies and many are now close to market readiness. The Asian Institute of Technology in Thailand are piloting a suite of novel market-driven decentralised biological wastewater treatment technologies that were developed with Bill & Melinda Gates Foundation funding. The technologies work but their performance is variable. There is evidence that this is caused by variability in the microbial populations at the heart of the technologies, which are poorly understood. We will work with AIT to characterise and optimise the structure and function of the microbial treatment communities. The aim will be to mitigate the risk of failure by refining the AIT designs and offering rapid low-tech remediation strategies that can be deployed by customers should failures occur.

Scottish Water has identified the need to develop their approach to dealing with uncertainty when assessing the risk of river erosion at pipeline crossings. In particular, there is a need to develop and pilot methods that can use data from initial asset inspections to quantify risks and uncertainties in making decisions on where to invest additional resources in more detailed inspections, for assets deemed to be at greater risk from river bank erosion or scour around bridge abutments. This challenge arises from the reality that, over the past 10-15 years, pipeline crossing inspections have been undertaken in an ad-hoc manner. The aim of this proposal is, therefore, to develop a decision support framework to incorporate river bank stability in pipeline crossing risk assessment. This will be used immediately during 2016 in Scottish Water's first, national-scale pipeline bridge asset inspection programme. The specific objectives are to: (i) evaluate uncertainty in the existing low-cost app-based inspection database that is used to screening risk; (ii) assess the uncertainty that arises from the initial desk-based phase of river bank stability assessment; (iii) develop a pipeline crossing scour assessment framework for analysing river bank stability at the screening phase and determining appropriate analysis for the initial assessment phase; and (iv) recursively test the risk assessment framework. To address these objectives there will be three methodological phases, results from which will be progressively reported. First, a sample of the pipeline crossings will be re-surveyed using a replicate inspection app. Results will enable evaluation of uncertainties in data capture and their consequences for river stability decision making at the screening stage of risk management. Second, uncertainty in assessing bank erosion will be assessed considering data from the asset inspection app, Google Earth imagery, high-resolution aerial images commissioned by Scottish Water, and legacy LiDAR acquired by the Scottish Government. Evidence of river instability will be mapped from imagery. Change will be quantified using appropriate techniques to represent errors in digitising and topographic change analysis. Finally, results will be used to produce a framework to: (i) characterise risk during screening; and (ii) determine the most appropriate forms of desk based analysis for initial risk assessment. The framework will include a multi-criteria process for calculating risk after the initial assessment phase to determine whether a more detailed assessment phase is necessary and, if so, necessary actions. This framework will be tested at a further set of 20 sites. Project outputs will be operationalised and used to improve decision making. App-based data capture will be improved with enhanced data fields and training material for asset inspectors. Results from evaluating uncertainty in data and analysis will be input to a multi-criteria scoring framework that will improve decision making at the screening and initial assessment stages and will thus enable scarce resources to be prioritised for desk-based river bank stability analyses. The framework will be used in the current drinking water pipeline crossing inspection programme and will also be of value for a future waste water pipeline crossing inspection programme. The project will last 12 months which will enable evaluation of uncertainty in a sufficiently large sample of data, analysis approaches and sites. The total cost (80% FEC) of the project is £89,707. This includes staff costs for Williams and Hoey, 9 months research assistant time, computer hardware, and travel.

The water industry faces intensifying risks to its water treatment systems from rising dissolved organic matter (DOM) concentrations in upland raw water supplies. This is leading to rising treatment costs, drinking water quality breaches, and threats to existing infrastructure. Scottish Water (SW), the industrial partner in this proposal, working with CEH, aim to address this challenge by developing an entirely new approach to understanding, managing, and planning responses to DOM increases over the next 50 years in response to environmental change. This represents a radical departure from the current water industry focus on 'managing away' rising DOM levels in supply catchments through upland restoration, which has had only limited success. Risks and costs of rising DOM levels are widespread. They affect other water companies, including United Utilities, Welsh Water and Irish Water, who, alongside SW and academic partners (Universities of Glasgow and Leeds), will form the Project Advisory Board and ensure continued relevance and impact of the project. The project will build on a modelling framework developed by CEH and harness new scientific understanding to equip SW with: 1) state-of-the-art knowledge of the consequences of future environmental change for DOM levels; 2) a web-based Decision Support System (DSS) with which to anticipate where and when treatment-related thresholds are most likely to be breached; 3) the ability to more efficiently manage water treatment assets; and, 4) a robust, long-term strategic basis for sustainable catchment planning and optimised infrastructure investment. By developing these capabilities CEH will provide SW with tools to optimise mitigation (e.g. land-use interventions) and adaption (e.g. infrastructure investment) strategies. Proposed activities and (respective Work Packages) include: finalisation of SW needs and collation of SW data in a project database (WP1); development of an existing model framework to enable forecasting of future DOM quality, quantity and Key Performance Indicators (WP2); model implementation, focussed on circa 100 SW supply catchments (WP3), generation of a spatially explicit model of current and future DOM concentrations across the UK uplands according to climate change and air pollution scenarios (WP4); and, development of the DSS incorporating web-based tools, to provide a front-end for model outputs for use by SW, and enable forecasting of future annual average and seasonal extreme raw water DOM concentrations and quality, and Key Performance Indicators (KPIs) (WP5). Additional funding from SW will support collection of new data to assist in model parameterisation and testing. CEH will work with SW to implement the prototype DSS, initially for a subset of 'exemplar' sites to test and subsequently showcase the application of the tool, before scaling up to the full set of catchments from WP2. Consequences for SW's KPIs will then be assessed for a range of environmental scenarios and mitigation strategies. Results will be disseminated by a CEH in a series of briefing notes to SW and through the DSS directly. Exemplar studies will be presented to the wider water industry at the end-of-project dissemination meeting. At this point other water industry partners will be given the opportunity to engage in a future beta-test of the DSS, and work more closely with CEH and each other in developing further iterations and functionality. Ultimately, the project aims to transform approaches to rising DOM across the UK water industry, and potentially internationally. Project duration will be 18 months. During this time, SW will independently fund a parallel project of new data collection that will help to strengthen the empirical basis and parameterisation of the model to support future use. The total cost of the project, at 80%FEC will be £135,595, with £75,000 from SW to support supplementary sampling.