Autonomous Systems (AS) are cyberphysical complex systems that combine artificial intelligence with multi-layer operations. Security for dynamic and networked ASs has to develop new methods to address an uncertain and shifting operational environment and usage space. As such, we have developed an ambitious program to develop fundamental secure AS research covering both the technical and social aspects of security. Our research program is coupled with internationally leading test facilities for AS and security, providing a research platform for not only this TAS node, but the whole TAS ecosystem. To enhance impact, we have built a partnership with leading AS operators in the UK and across the world, ranging from industrial designers to frontline end-users. Our long-term goal is to translate the internationally leading research into real-world AS impact via a number of impact pathways. The research will accelerate UK's position as a leader in secure AS research and promote a safer society.

With the Kigali Amendment coming into force in 2019, the Montreal Protocol on Substances that Deplete the Ozone Layer has entered a major new phase in which the production and use of hydrofluorocarbons (HFCs) will be controlled in most major economies. This landmark achievement will enhance the Protocol's already-substantial benefits to climate, in addition to its success in protecting the ozone layer. However, recent scientific advances have shown that challenges lie ahead for the Montreal Protocol, due to the newly discovered production of ozone-depleting substances (ODS) thought to be phased-out, rapid growth of ozone-depleting compounds not controlled under the Protocol, and the potential for damaging impacts of halocarbon degradation products. This proposal tackles the most urgent scientific questions surrounding these challenges by combining state-of-the-art techniques in atmospheric measurements, laboratory experiments and advanced numerical modelling. We will: 1) significantly expand atmospheric measurement coverage to better understand the global distribution of halocarbon emissions and to identify previously unknown atmospheric trends, 2) combine industry models and atmospheric data to improve our understanding of the relationship between production (the quantity controlled under the Protocol), "banks" of halocarbons stored in buildings and products, and emissions to the atmosphere, 3) determine recent and likely future trends of unregulated, short-lived halocarbons, and implications for the timescale of recovery of the ozone layer, 4) explore the complex atmospheric chemistry of the newest generation of halocarbons and determine whether breakdown products have the potential to contribute to climate change or lead to unforeseen negative environmental consequences, 5) better quantify the influence of halocarbons on climate and refine the climate- and ozone-depletion-related metrics used to compare the effects of halocarbons in international agreements and in the design of possible mitigation strategies. This work will be carried out by a consortium of leaders in the field of halocarbon research, who have an extensive track record of contributing to Montreal Protocol bodies and the Intergovernmental Panel on Climate Change, ensuring lasting impact of the new developments that will be made.

Depletion of stratospheric ozone allows larger doses of harmful solar ultraviolet (UV) radiation to reach the surface leading to increases in skin cancer and cataracts in humans and other impacts, such as crop damage. Ozone also affects the Earth's radiation balance and, in particular, ozone depletion in the lower stratosphere (LS) exerts an important climate forcing. While most long-lived ozone-depleting substances (ODSs, e.g. chlorofluorocarbons, CFCs) are now controlled by the United Nations Montreal Protocol and their abundances are slowly declining, there remains significant uncertainty surrounding the rate of ozone layer recovery. Although signs of recovery have been detected in the upper stratosphere and the Antarctic, this is not the case for the lower stratosphere at middle and low latitudes. In fact, contrary to expectations, ozone in this extrapolar lower stratosphere has continued to decrease (by up to 5% since 1998). The reason(s) for this are not known, but suggested causes include changes in atmospheric dynamics or the increasing abundance of short-lived reactive iodine and chlorine species. We will investigate the causes of this ongoing depletion using comprehensive modelling studies and new targeted observations of the short-lived chlorine substances in the lower stratosphere. While the Montreal Protocol has controlled the production of long-lived ODSs, this is not the case for halogenated very short-lived substances (VSLS, lifetimes <6 months), based on the belief that they would not be abundant or persistent enough to have an impact. Recent observations suggest otherwise, with notable increases in the atmospheric abundance of several gases (CH2Cl2, CHCl3), due largely to growth in emissions from Asia. A major US aircraft campaign based in Japan in summer 2021 will provide important new information on how these emissions of short-lived species reach the stratosphere via the Asian Summer Monsoon (ASM). UEA will supplement the ACCLIP campaign by making targeted surface observations in Taiwan and Malaysia which will help to constrain chlorine emissions. The observations will be combined with detailed and comprehensive 3-D modelling studies at Leeds and Lancaster, who have world-leading expertise and tools for the study of atmospheric chlorine and iodine. The modelling will use an off-line chemical transport model (CTM), ideal for interpreting observations, and a coupled chemistry-climate model (CCM) which is needed to study chemical-dynamical feedbacks and for future projections. Novel observations on how gases are affected by gravitational separation will be used to test the modelled descriptions of variations in atmospheric circulation. The CTM will also be used in an 'inverse' mode to trace back the observations of anthropogenic VSLS to their geographical source regions. The models will be used to quantify the flux of short-lived chlorine and iodine species to the stratosphere and to determine their impact on lower stratospheric ozone trends. The impact of dynamical variability will be quantified using the CTM and the drivers of this determined using the CCM. The model results will be analysed using the same statistical models used to derive the decreasing trend in ozone from observations, including the Dynamical Linear Model (DLM). Overall, the results of the model experiments will be synthesised into an understanding of the ongoing decrease in lower stratospheric ozone. This information will then be used to make improved future projections of how ozone will evolve, which will feed through to the policy-making process (Montreal Protocol) with the collaboration of expert partners. The results of the project will provide important information for future international assessments e.g. WMO/UNEP and IPCC reports.

High resolution spatio-temporal data is becoming increasingly common, providing statisticians with both the joys and challenges of massive data sets. However the signals under investigation in these data sets are often complex and non-linear with both smoothly and abruptly changing components. This is especially true in applications such as functional magnetic resonance imaging and positron emission tomography, where three dimensional spatial measurements are taken repeatedly during the experimental time frame. Common approaches to the analysis of these data sets are based on the use of mass univariate linear models. Recently, work has shown that great improvements can be made, in terms of estimating the signal, by considering a non-parametric functional smoothing approach, particularly if use is made of the spatial information in the data. However, this methodology is currently limited to simple spatial models and to signals that are only smoothly varying.This projects aims to provide a statistical framework for analysis of spatio-temporal data which is subject to both smooth variations and abrupt changes within the same signal, whether these changes are occurring across space or time. Functional principal component methodology will be extended to incorporate a hidden Markov random field component. This will allow either a clustering of the data into regions of similar function constrained in space, or a fully 4-D spatio-temporal model of the resulting process.Particular attention will be paid to the application of this methodology to functional neuroimaging data. Brain anatomy results in the need for a smoothly changing spatial model subject to abrupt changes while neurochemical reactions and experimental challenges can result in both smoothly varying and abruptly changing signals in time. In addition, the massive amounts of data that need to be considered require that all the methodologies determined must be accompanied by computationally efficient algorithms. By focusing on common experimental paradigms, the goal of this project is to deliver innovative general statistical methodology that is of real and immediate benefit to the analysis of neuroimaging data.

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