To date, most research into the impact of microplastics in the environment has focussed on marine (coastal and ocean) environments. However, there is growing acceptance that microplastics are also pervasive within freshwater (river and lake) systems. The limited number of studies from rivers around the world have all found microplastics to be present within samples of river bed sediments or the water column. This is of concern as the ecotoxicological impact of microplastics will likely have a negative impact on a range of freshwater species with an additional public health concern if pollutants associated with microplastics then enter the human food chain. A fundamental issue regarding the science of microplastics in freshwaters is a lack of data with which to generate physically based models. This thus makes it very hard to establish what are 'normal' levels of microplastics within our rivers and hence whether such levels represent an acceptable level of risk to ecosystems or society more generally, or where clean-up or remediation strategies should be targeted. To make meaningful progress, this issue requires international consensus to be agreed quickly so that ongoing and future research efforts can be properly synthesised to provide meaningful evidence-based policy. The purpose of this proposal is to meet this challenge by assembling a new network of internationally leading freshwater microplastics experts. This network will undertake a focused programme of data collection. By pooling this data and using it to generate new numerical models at a series of workshops the network will be able to reach more robust conclusions as to the overall freshwater plastic flux to the oceans. This will address the significant stumbling block the discipline currently faces and thus allow further development of more physically based models. Such a significant deliverable can only be achieved by the sort of networking opportunity that is facilitated by the global partnerships seedcorn fund.

The Centre for Doctoral Training MAC-MIGS will provide advanced training in the formulation, analysis, and implementation of state-of-the-art mathematical and computational models. The vision for the training offered is that effective modern modelling must integrate data with laws framed in explicit, rigorous mathematical terms. The CDT will offer 76 PhD students an intensive 4-year training and research programme that equips them with the skills needed to tackle the challenges of data-intensive modelling. The new generation of successful modelling experts will be able to develop and analyse mathematical models, translate them into efficient computer codes that make best use of available data, interpret the results, and communicate throughout the process with users in industry, commerce and government. Mathematical and computational models are at the heart of 21st-century technology: they underpin science, medicine and, increasingly, social sciences, and impact many sectors of the economy including high-value manufacturing, healthcare, energy, physical infrastructure and national planning. When combined with the enormous computing power and volume of data now available, these models provide unmatched predictive tools which capture systematically the experimental and observational evidence available. Because they are based on sound deductive principles, they are also the only effective tool in many problems where data is either sparse or, as is often the case, acquired in conditions that differ from the relevant real-world scenarios. Developing and exploiting these models requires a broad range of skills - from abstract mathematics to computing and data science - combined with expertise in application areas. MAC-MIGS will equip its students with these skills through a broad programme that cuts across disciplinary boundaries to include mathematical analysis - pure, applied, numerical and stochastic - data-science and statistics techniques and the domain-specific advanced knowledge necessary for cutting-edge applications. MAC-MIGS students will join the broader Maxwell Institute Graduate School in its brand-new base located in central Edinburgh. They will benefit from (i) dedicated academic training in subjects that include mathematical analysis, computational mathematics, multi-scale modelling, model reduction, Bayesian inference, uncertainty quantification, inverse problems and data assimilation, and machine learning; (ii) extensive experience of collaborative and interdisciplinary work through projects, modelling camps, industrial sandpits and internships; (iii) outstanding early-career training, with a strong focus on entrepreneurship; and (iv) a dynamic and forward-looking community of mathematicians and scientists, sharing strong values of collaboration, respect, and social and scientific responsibility. The students will integrate a vibrant research environment, closely interacting with some 80 MAC-MIGS academics comprised of mathematicians from the universities of Edinburgh and Heriot-Watt as well as computer scientists, engineers, physicists and chemists providing their own disciplinary expertise. Students will benefit from MAC-MIGS's diverse network of more than 30 industrial and agency partners spanning a broad spectrum of application areas: energy, engineering design, finance, computer technology, healthcare and the environment. These partners will provide internships, development programmes and research projects, and help maximise the impact of our students' work. Our network of academic partners representing ten leading institutions in the US and Europe, will further provide opportunities for collaborations and research visits.