10116130Development of an Innovative Intelligent Multiparameter Fluorometer to Sense the Impact of Organic Pollution on River HealthClosedCollaborative R&DInnovate UKIn a report published by The Rivers Trust (2024) data shows that many of the UK's rivers and lakes are not healthy. Toxic chemicals that remain in ecosystems for decades, pollute every stretch of English rivers to the extent that not a single river in England or Northern Ireland are classified as being in _good overall_ health. Of the rivers failing to achieve good status, agriculture and sewage works impact our rivers the most with discharges of sewage effluent having the most widespread impact on rivers. The impacts from raw sewage spills via storm overflows (301,091 recorded in 2022) are a cause of poor river health. Recent legislation requires water companies to reduce harmful bacteria from discharges near designated bathing waters by 2035 and by 2050, discharges will only be permitted where no adverse ecological impact can be demonstrated. As part of the Environment Act (2021), water companies must measure the water quality of rivers up and down stream of all sewage discharge points. To achieve this, new technologies and approaches are needed that can inform river health assessment in real-time. Current water quality sensing technologies are limited in that they only measure basic physical and chemical parameters which alone, do not provide data that informs river health assessment. Subsequently, there is a lack of monitoring data for bacterial and algal contamination in rivers caused by sewage effluents and agriculture. This lack of data is a significant technical and scientific barrier to the effective assessment of evidence-driven interventions aimed at improving river health and water safety. As a leading UK sensor technology manufacturer (Chelsea Technologies), and in collaboration with river conservation experts (The Rivers Trust) and UK academics (UWE Bristol) we will develop and deploy an integrated, low-cost, disruptive multiparameter fluorescence-based sensor for the real-time monitoring of water quality and river health. This new sensor technology will be capable of measuring, in real-time, organic pollution, phytoplankton and bacterial contamination. Using Machine Learning (ML) and Artificial Intelligence (AI), we aim to develop a new Water Quality Index (WQI) by combining the measurement of these new parameters with other real-time data, such as weather events (rainfall). This approach will facilitate more accurate and efficient water quality monitoring, reducing costs without sacrificing the ability to track river health. Our overall aim is to revolutionise the way in which river health is monitored and determined, ultimately helping to improve the health of our rivers.