Over half of global gross domestic product is dependent on nature, yet the past decades have seen unprecedented damage to ecosystems and declines in biodiversity due to adverse human activities. Financial institutions (FIs) can play an important role in securing a nature-positive future. Decisions by FIs over capital allocation and risk pricing influence structural shifts in the real economy that have profound impacts on nature. Today, opportunities to align nature and capital in ways that benefit people, nature and FIs are missed because these impacts are not accounted for. Our aim is to contribute the foundational networks, upskilling of researchers and robust, standardised methods and tools needed to integrate biodiversity and nature into financial decision making. Our focus is the scenarios used by FIs to influence risk pricing and investment decisions, alongside the relevant and suitable data and tools needed for scenario analysis, such as asset-level data and tools to assess nature-related financial risks. A further novel aspect of our proposal is the on integrated nature-climate scenarios. Scenarios and analytics for use by FIs must consider biodiversity and climate in an integrated way. Biodiversity and climate are often treated in siloes, driving potential systemic risks. Important interactions and feedbacks are not accounted for, leading to underestimation of risks and critical tipping points. An important innovation in our proposal is to bring together the IPBES, IPCC and FI scenarios communities, leaders of whom are partners to this project, to address this gap. Integrating nature and climate requires new science; our proposal is to develop the networks and co-design and pilot the frameworks to achieve this - i.e. the foundational common framework and language needed to close the gap. This will create the foundation to Phase 2 that will generate the new datasets and toolkits needed. Here we particularly target scenarios and analytics for use by Central Banks and Supervisors (CB&Ss). This is because CB&Ss are important catalysts of wider action by FIs. Supervisory expectations and regulations, e.g. disclosure, capital requirements and stress-testing, set the rules by which FIs operate, while monetary policies shape the playing field, together having a major influence on global capital flows and so nature. In developing this proposal, we have consulted with the leading CB&Ss and policy makers (e.g. Defra, HMT) that are shaping this agenda and leading work on scenarios, all of whom have agreed to join the project as project partners. This includes the European Central Bank, the Banque de France, De Nederlandsche Bank, the Network of Central Banks and Supervisors (CB&Ss) for Greening the Financial System (NGFS), and the Task Force on Nature-Related Financial Disclosures (TNFD). Phase 1 of the project will deliver several important building blocks. Firstly, it will establish and operationalise the multi-disciplinary nature-climate-finance network. Secondly, it will co-develop the framework and guidance to generate the nature-climate scenarios and analytics, alongside syntheses of evidence and gap analyses. Finally, it will deliver a demonstrator application to a CB&S use case in stress testing nature-related risks. We will capture lessons learnt through this project to inform Phase 2, as well as share them to inform the development of the wider NERC Nature Positive Futures (NPF) programme. Our goal is that the network and the analytical framework developed will ultimately catalyse shifts in financial flows that reduce systemic risks and are aligned with a nature-positive future. Through consultations, we have understood the key milestones and actors to achieve this and shaped the project accordingly. We will work closely with our project partners, and link to UKCGFI, to ensure our outputs feed into the key processes, as well as collaborate with and support the wider NPF programme goals.

The capacity to identify one another is paramount. It underpins social dialogue, commercial transactions, individual entitlements to goods and services and issues of legal and criminal responsibility. In today's society, each of these activities can take place both within the real world and the cyber world making the concept of identity, and the process of identification, more challenging than ever before. The SID project addresses this challenge through an ambitious and innovative programme of work, bringing together experts from a diverse spectrum of scientific domains ranging from automated biometrics, cyber-psychology, forensic anthropology, human-computer interaction, mathematical modelling, and complex data visualisation. In addition, the project is backed by key industrial and governmental stakeholders, represented through an Advisory Group and providing direct input throughout the project. The first stage of the project is to define the set of identity measures of interest and to gather relevant datasets either from existing resources, or through active data collection from participants across diverse demographic populations. Our measures of interest will fall into four categories: static and behavioural measures in the real world; and static and behavioural measures in the cyber world. These measures will be the basis for our model of Super-Identity, and their selection will be informed by the input of analysts, and end-users within intelligence, e-commerce and forensic sectors. At this early stage, and throughout the life of the project, we explicitly examine the social, legal and ethical considerations associated with data privacy and data protection. Work Package 1 addresses these issues. Once this framework is in place, extensive testing will be conducted to determine the accuracy and reliability of automated and human identification from each measure. This will determine (i) the confidence that should be attributed to each measure, (ii) the effect that changing contexts may have on that measure and (iii) the potential relationship between measures. The results of this phase of work will continually update our Super-Identity model enabling measures to be combined, cross-referenced, and weighted according to their individual confidence estimates. Work Package 2 addresses these issues. Consideration of how to present the information to the end user is the crucial next stage. With the benefit of expertise in human computer interaction and data visualisation, and the participatory engagement from end-users, the model will be refined with specific attention to its visual presentation in a flexible yet intuitive format. Work Package 3 addresses these issues. In combination, SID provides fusion of known measures, revelation of unknown measures, and quantification of certainty associated with each measure, and thus the identification decision overall. In this way, it provides a step-change in the way that we think about identity and identification, and in the value that it might hold for the real world.

The UK is leading the development and installation of offshore renewable energy technologies. With over 13GW of installed offshore wind capacity and another 3GW under construction, two operational and one awarded floating offshore demonstration projects as well as Contracts for Difference awards for four tidal energy projects, offshore renewable energy will provide the backbone of the Net Zero energy system, giving energy security, green growth and jobs in the UK. The revised UK targets that underpin the Energy Security Strategy seek to grow offshore wind capacity to 50 GW, with up to 5 GW floating offshore wind by 2030. Further acceleration is envisaged beyond 2030 with targets of around 150 GW anticipated for 2050. To achieve these levels of deployment, ORE developments need to move beyond current sites to more challenging locations in deeper water, further from shore, while the increasing pace of deployment introduces major challenges in consenting, manufacture and installation. These are ambitious targets that will require strategic innovation and research to achieve the necessary technology acceleration while ensuring environmental sustainability and societal acceptance. The role of the Supergen ORE Hub 2023 builds on the academic and scientific networks, traction with industry and policymakers and the reputation for research leadership established in the Supergen ORE Hub 2018. The new hub will utilise existing and planned research outcomes to accelerate the technology development, collaboration and industry uptake for commercial ORE developments. The Supergen ORE Hub strategy will focus on delivering impact and knowledge transfer, underpinned by excellent research, for the benefit of the wider sector, providing research and development for the economic and social benefit of the UK. Four mechanisms for leverage are envisaged to accelerate the ORE expansion: Streamlining ORE projects, by accelerating planning, consenting and build out timescales; upscaling the ORE workforce, increasing the scale and efficiency of ORE devices and system; enhanced competitiveness, maximising ORE local content and ORE economic viability in the energy portfolio; whilst ensuring sustainability, yielding positive environmental and social benefits from ORE. The research programme is built around five strategic workstreams, i) ORE expansion - policy and scenarios , ii) Data for ORE design and decision-making, iii) ORE modelling, iv) ORE design methods and v) Future ORE systems and concepts, which will be delivered through a combination of core research to tackle sector wide challenges in a holistic and synergistic manner, strategic projects to address emerging sector challenges and flexible funding to deliver targeted projects addressing focussed opportunities. Supergen Representative Systems will be established as a vehicle for academic and industry community engagement to provide comparative reference cases for assessing applicability of modelling tools and approaches, emerging technology and data processing techniques. The Supergen ORE Hub outputs, research findings and sector progress will be communicated through directed networking, engagement and dissemination activities for the range of academic, industry and policy and governmental stakeholders, as well as the wider public. Industry leverage will be achieved through new co-funding mechanisms, including industry-funded flexible funding calls, direct investment into research activities and the industry-funded secondment of researchers, with >53% industry plus >23% HEI leverage on the EPSRC investment at proposal stage. The Hub will continue and expand its role in developing and sustaining the pipeline of talent flowing into research and industry by integrating its ECR programme with Early Career Industrialists and by enhancing its programme of EDI activities to help deliver greater diversity within the sector and to promote ORE as a rewarding and accessible career for all.

United States of America

Predicting the impact of atmospheric aerosols, through their evolving size and chemical composition, relies on using mechanistic models that attempt to predict the partitioning of potentially millions of such compounds between the gas phase and condensed phase. Uncertainties in the physicochemical properties of pure components and condensed phase mixtures affect our ability to accurately predict and resolve this partitioning. How do we tackle such uncertainties? In 2 ongoing NERC grants, a range of fundamental properties of pure components and mixtures (vapour pressures, viscosities and diffusion constants), are being measured with the objective of improving predictions for atmospheric functionalities. Given the urgency of making such measurements, complementary instruments and expertise exists across the EU and North America that is not available through existing NERC projects. Similarly, the laboratory facilities and expertise enabled by the referenced NERC projects are not accessible to such international programmes. Why is the lack of coherence in methodology and expertise a problem? Recent reviews by the international community highlight significant discrepancies between experimental methods. Despite this, there is no coordinated effort to reconcile these differences or to start compiling appropriate data, with appropriate screening, to improve the predictive techniques essential for improving atmospheric aerosol models. Current compiled data are extremely sparse. On top of this, there are no recommended standards to establish accepted criteria for future measurements or an agreed set of modelling tools to determine how accurate the data has to be to predict evolving aerosol properties. Ultimately, we do not know what level of accuracy in properties might be attainable and acceptable. This is a unique opportunity to address these issues internationally whilst directly benefiting existing and future NERC driven programmes. This IOF will catalyse exploitation of data from ongoing NERC grants, consolidating it into new databases built with measurements and expertise from partner organisation, adding value by expanding flexibility and accuracy of predictive techniques. We have identified 3 ongoing and 2 completed NERC grants as detailed in the case for support. Each partner will provide access to their existing measurement and modelling programmes, involvement in evaluation committee meetings, writing publications, hosting researchers to take part in intercomparisons (see letters of support) and supporting engagement with the wider community once the network matures. Whilst we identify activities to take place over a 2-year period, it is crucial to ensure project sustainability. As such, we will not only create new databanks and an agreed set of open source community modelling facilities, but an agreed set of standards for accepting future measurements will be established. We will engage with the global community through open workshops and meetings. The network comprises researchers from: The University of Manchester [lead], University of Bristol [UK-CoI], ETH [Switzerland], Aarhus University [Denmark], Stockholm University [Sweden], Lawrence Berkeley Laboratory [US], Pacific Northwest National Lab [US] and University of British Columbia [Canada].