The 'DecomRegHub' will provide a safe, collaborative environment where industry can engage with regulators and together explore the technical and regulatory requirements of decommissioning and share/manage the associated risks. It will facilitate early engagement between industry, key stakeholders and regulators to explore collaboratively the technical, environmental and safety requirements of decommissioning, as well as identify opportunities to develop and test new techniques, products and regulatory tools that will help ensure the success of the global decommissioning market. 'DecomRegHub' will also provide a customer-focused digital hub bringing together data, advice, guidance, information, best practice, and case studies across the entire regulatory landscape. This collaborative approach will enable knowledge sharing and access to robust evidence, drawn from multiple sources of information that, in turn, will inform policy and regulatory development, operational assessments and decisions. The digital hub will be designed with users to ensure it contains the right information in the right format and is structured to make it easy for users to find and use what they are looking for as easily as possible. The ''DecomRegHub'' is made up of UK regulators and will be supported by the Offshore Petroleum Regulator for Environment and Decommissioning (OPRED), the Health and Safety Executive (HSE), the Environment Agency (EA), the Scottish Environment Protection Agency (SEPA) and Zero Waste Scotland (ZWS). It will: • Provide a safe, collaborative environment that supports industry in the development and testing of innovative new techniques, products and services in support of decommissioning. • Bring together operating companies and multiple regulators (from the oil and gas industry and the waste supply chain). • Understand (holistically) the environmental and safety regulatory requirements and identify opportunities to manage the associated risks together. • Address cross-cutting areas, share best practices and create innovative solutions. • Drive the potential to reduce, re-use and recycle materials, moving towards a circular economy. • Develop knowledge and experience that will grow the industry. • Position the UK as a global leader in late-life oil and gas asset management and decommissioning.

Freshwater ecosystems are critical to biodiversity as well as human health, wealth and wellbeing but are under substantial pressure from a range of catchment and climate stressors. Inputs of chemical nutrients from agricultural land, urban settlements, and discharges of wastewater from treatment works and sewer outflows are the most common cause of poor water quality in the UK. These issues are also being made worse by the increased occurrence of extreme weather events such as storms, floods, and droughts that increase the delivery of nutrients and organics to fresh waters during high rainfall events while acting to concentrate them during periods of low rainfall and river flow. In the UK, there has been significant public and political debate surrounding the state of our rivers and other fresh waters, with questions raised about the adequacy of current approaches to monitoring and regulation. Recent changes to the policy landscape, as well advancements in areas such as low-cost sensing, wireless communications, and artificial intelligence, now provide an opportunity to rethink approaches and embrace new monitoring technologies. However, many commercial solutions for water quality sensing are still too expensive to implement at scale (i.e., region- or nation-wide) or are too limited by their power and data telemetry requirements to enable them to be deployed in more challenging, but often the most data scarce locations. Moreover, while immense progress has been made in the development of artificial intelligence and machine learning methods for data processing and analysis - there are few examples of where these techniques have been integrated into water quality monitoring systems to improve the data provision to users. Finally, some sensor manufacturers use outdated protocols for data transfer that are not compliant with the latest cybersecurity standards, which could potentially introduce vulnerabilities into networks also used by the water industry to support critical national infrastructure. The SenseH2O project will address these challenges by targeting innovation at specific areas of the water quality monitoring lifecycle to develop a new highly integrated, 'systems-level' approach. Our overarching aim of our systems-level approach is to improve the efficacy and scalability of real-time water quality monitoring in the UK. We will achieve this by designing, developing, and demonstrating a prototype water quality monitoring system that integrates the latest in low-cost sensor technologies, adaptable solutions for off-grid power and data communications, artificial intelligence tools for data processing and analysis, and the very best practices in web-based data visualisations. Ultimately, SenseH2O will provide a vision for the future of water quality monitoring at scale in the UK that better addresses the needs of the water industry.

Imagine yourself sitting in a sun-drenched woodland, eyes closed, on a warm summer day, surrounded by the enchanting symphony of birdsong and the gentle rustling of leaves. This natural auditory experience is a rich source of environmental information, but the challenge lies in translating this wealth of data into a format accessible to environmental scientists and policymakers, as manual data interpretation is not scalable. The solution to this challenge lies in the application of machine learning for sound data classification, a task effectively tackled by our Soprano devices. This technology enables us to convert audio data into manageable datasets, facilitating analysis for environmental practitioners. Consequently, we can transmit concise packages of categorised events, rather than unwieldy volumes of raw audio data, over an LPWAN radio network. A single radio gateway can cover vast areas, spanning tens of square kilometers. Once this telemetry infrastructure is established, it becomes logical to extend its use to transmit other environmental variables such as temperature and water levels. These are well-understood problems and can significantly reduce the costs associated with field data collection. The methods for processing and analysing audible, ultrasonic, and hydrophone data are applicable across the board. Thus, we propose solutions for analysing soundscapes in both terrestrial and aquatic environments. To ensure that this system is not only created but also adopted, we will collaborate with stakeholders and demonstrate its practicality through case studies of interest to organisations such as Forest Research, the Scottish Environment Protection Agency, and the Forth Fisheries Board. The Soprano project will deliver a commercially and operationally ready technology demonstrated on carefully chosen case studies. The Soprano system will provide a standardised and sustainable audio-based EdgeAI platform and include the mechanisms to enable third parties to make remunerated contributions in the development of new EdgeAI capabilities. Increasingly, with the ever growing impacts of climate change becoming more visible, we have seen the burgeoning demand for UK-wide, European and International adoption of automated AI-driven biodiversity and ecology monitoring. Soprano will empower and enable both the wider academic community and entrepreneurs to accelerate the adoption of EdgeAI to address the increasingly urgent environmental challenges we all face.

Our proposal will develop and utilise smart sensors, test new infrastructure and approaches for data cleaning, as well as developing predictive analytics and a visualisation platform, to improve the next generation of environmental regulations for water resources. Our tools will allow businesses (eg the whisky and agricultural sectors) to individually assess and control their environmental interactions and ultimately enable regulators to remove the need for traditional environmental inspection and monitoring. Partners in the multi-disciplinary proposal are the Scottish Environment Protection Agency (SEPA) and the Innovation Centre for Sensor and Imaging Systems (CENSIS). Our project will scope out existing and new technology for sensing water resources in remote environments, and then in a demonstrator project, explore the practical implementation of a network of sensors across a catchment integrating data from the national river flow archive, the SEPA managed network of gauging stations, and rainfall information. The results will allow us to assess the potential of this technology to disrupt traditional approaches to environmental regulation by providing a framework for enhanced and superior information gathering while removing the extensive cost and regulatory burden associated with field officers conducting inspections and sampling. A key aspect of this proposal is the promotion and deployment of sensors and communication and analytical methods to extend a previous small scale sensor pilot into a prototype digital predictive and visualisation framework testing the communications infrastructure and integration of data streams to enhance the ability of the UK to better manage water resources (quality and availability) in the context of remote, rural environments. This links into existing networks including the national river flow archive and the SEPA supported network of river gauging stations. In this larger demonstrator project, further sensors will be deployed providing additional spatial coverage of water level sensors, while adding additional types of sensor (rainfall and soil moisture), as well as scoping using a satellite based communications solution. This study will evaluate the potential of reliable and easily deployable sensor communication infrastructure based on the low power wide area network LoRaWAN standard monitoring rural environmental areas. As well as data transmission and communication challenges we will also be attempting to address off-grid powering challenges by making use of low power devices and active duty cycle management as well as renewable energy sources (e.g. solar/wind) in a low cost sustainable format. We will use new infrastructure extending the range of environmental variables to be measured, and test different data communication technologies including satellite (IoT), daisy chaining LoRaWAN and using battery operated LoRaWAN and LoRaWAN hybrid repeater nodes. These are very leading edge and we will be working with the industry leader Semtech in not only new lower power silicon (Q319) but a roll-out of a new meshing standard (TBC). The Hybrid repeater nodes will be custom and bespoke to this project. Our proposal could lead ultimately to many new remote networks that are independent of any infrastructure requirements.

Cyanobacteria (blue-green algae) commonly produce mass populations in UK still- and slow-moving freshwaters. They may generate toxins which present health risks to humans and animals via ingestion and skin contact. Not all cyanobacterial blooms produce toxins, and the presence of toxins can only be confirmed by collecting samples and taking them to the laboratory. From a public health perspective monitoring has been largely reactionary and not proactive and little early warning capability exists However, recent developments in remote sensing techniques have shown promise in the rapid (and reliable) detection of blooms. This proposal is designed to develop and evaluate an approach based on remote sensing (RS) to providing early warning of toxic cyanobacterial development to protect health within a risk assessment framework. Calibration of the (RS) procedure would be carried out using actual cyanotoxin analysis at 2 high-resource UK freshwaters with a history of annual bloom production. The proposal builds on existing modelling work to develop a hazard assessment tool to identify likely water bodies that may pose a hazard from the production toxic cyanobacteria and model the influence of climate change on potentially toxic cyanobacteria production in lakes. A critical question relates to understanding the environmental factors leading to cyanotoxin production and this is addressed within the proposal. The human health risk from direct and indirect exposure to the toxins is addressed along with cost-benefit analysis of monitoring for toxic blooms.