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This file contains the complete dataset collected and underpinning the estimated carbon emissions data in the companion paper, in Microsoft Excel (XLSX) format. The workbook contains an index sheet with full details of each included worksheet. The file has been verified to open in Microsoft Excel (https://products.office.com/excel) and LibreOffice (https://www.libreoffice.org)

The ERC-funded FRAGSUS Project (Fragility and sustainability in small island environments: adaptation, cultural change and collapse in prehistory, 2013–18), led by Caroline Malone (Queens University Belfast) has explored issues of environmental fragility and Neolithic social resilience and sustainability during the Holocene period in the Maltese Islands. This, the first volume of three, presents the palaeo-environmental story of early Maltese landscapes. The project employed a programme of high-resolution chronological and stratigraphic investigations of the valley systems on Malta and Gozo. Buried deposits extracted through coring and geoarchaeological study yielded rich and chronologically controlled data that allow an important new understanding of environmental change in the islands. The study combined AMS radiocarbon and OSL chronologies with detailed palynological, molluscan and geoarchaeological analyses. These enable environmental reconstruction of prehistoric landscapes and the changing resources exploited by the islanders between the seventh and second millennia bc. The interdisciplinary studies combined with excavated economic and environmental materials from archaeological sites allows Temple landscapes to examine the dramatic and damaging impacts made by the first farming communities on the islands’ soil and resources. The project reveals the remarkable resilience of the soil-vegetational system of the island landscapes, as well as the adaptations made by Neolithic communities to harness their productivity, in the face of climatic change and inexorable soil erosion. Neolithic people evidently understood how to maintain soil fertility and cope with the inherently unstable changing landscapes of Malta. In contrast, second millennium bc Bronze Age societies failed to adapt effectively to the long-term aridifying trend so clearly highlighted in the soil and vegetation record. This failure led to severe and irreversible erosion and very different and short-lived socio-economic systems across the Maltese islands.

Frustration in the energy landscape has been quantified using a number of different metrics. These metrics have been applied to the databases in the subdirectories, which contain information about the energy landscape in the form of minima and transition states. The frustration metrics are coded within The PATHSAMPLE program, available for download at: http://www-wales.ch.cam.ac.uk/PATHSAMPLE/ Documentation can also be found at the same web address. The relevant keywords for the work described in this paper can be found at: http://www-wales.ch.cam.ac.uk/PATHSAMPLE.2.1.doc/node5.html Keywords CV, SHANNON and SHANNONR are described in the documentation. SHANNON and SHANNONR calculate frustration measures for the landscape as a function of temperature. The CV keyword gives a heat capacity calculation and hence allows an estimate of the melting temperature. Each Directory holds the database for the relevant system and input files for the PATHSAMPLE program. The output of the frustration calculation, for SHANNON, is given in Shannon.out. Some databases also contain output for the heat capacity calculation in CV.out. If required the OPTIM program is also available for download at: http://www-wales.ch.cam.ac.uk/OPTIM/ Documentation can also be found at the same web address. The program for drawing disconnectivity graphs, disconnectionDPS, can be found at: http://www-wales.ch.cam.ac.uk/software.html There is also input and output for the disconnectivity graph construction in each directory.

This repository contains the data related to the Data in Brief article titled: Bulk and critical material demand for selected ‘Starter Kit’ energy system models. The data include the modeled mass of materials and their embodied emissions. A metadata file is also included to clarify the units, materials and scenario names.

Currently, fossil fuels make up a significant proportion of global energy demand and cause many concerns, such as increasing greenhouse gas emission. Therefore, there is a considerable need for cost-effective, facile and efficient processing of environmental-friendly energy harvesting and storage systems. Solar energy is one of the most promising energy sources that meet the energy demand. The silicon-based solar cells exhibit competitive power conversion efficiency and dominate the solar cell market in recent years. In contrast, organic solar cells (OSCs) have emerged as promising third-generation photovoltaic devices owing to their outstanding properties such as the potential of low-cost mass manufacturing, lightweight, mechanical flexibility and easy processability. Therefore, OSCs have received growing attention from the research community. For solar cell technologies, a smectic liquid crystal C8-BTBT was selected in Chapter 3 due to its unique thermal dynamic and crystal properties. A range of ternary OSCs with and without C8-BTBT loading at gradient weight fractions were thermally treated and fabricated. In addition, the assessment of fabricated OSCs on the photovoltaic characteristics reveals the evolution of various cell parameters with annealing temperature and C8-BTBT weight fractions. The cell with 5 wt% C8-BTBT loading exhibited the best performance after thermal annealing treatment at 120 oC. Furthermore, flexible hydrogel substrates were fabricated for flexible OSCs in Chapter 4. The PHEMA hydrogel films were optimised via adjusting photopolymerisation duration under UV light. Based on the fabricated PHEMA substrates, flexible OSCs were subsequently made, whose extracted device parameters showed comparable characteristics with those in Chapter 3. Moreover, PHEMA-based OSCs can be dissolved in different types of polar solvents, which is promising for realising sustainable and recyclable solar cells. For the development of energy storage devices, asymmetric carbon nanohorns were proposed as an active material to fabricate flexible solid‐state carbon wire (CW)‐based electrochemical supercapacitors (ss‐CWECs) which exhibited high power density and ultra‐low cutoff frequency. Based on microscopy and electrochemical characterisation, the fundamental reaction mechanism in polyvinyl‐based electrolyte system was elucidated in Chapter 5, as being associated with deprotonation reaction under the acid, base, and elevated temperature conditions. In Chapter 6, by using activated carbon, multi‐walled carbon nanotubes, and single‐wall carbon nanohorns as hybrid electrode materials (5:1:1), remarkable specific length capacitance of 48.76 mF cm−1 and charge-discharge stability (over 2000 times cycles) of ss‐CWECs were demonstrated, which are the highest reported to date. Furthermore, a high‐pass filter for eliminating ultra‐low electronic noise was demonstrated, enabling an optical Morse Code communication system to be operated. vThe collective works in this thesis demonstrate novel energy conversion and storage applications with the liquid crystal in OSCs and carbon nanoparticles in supercapacitors. These results provide a step forwards in the development of energy conversion and storage devices for a more efficient energy system.

Efficient integration of solar energy into the electricity mix depends on a reliable anticipation of its intermittency. A promising approach to forecast the temporal variability of solar irradiance resulting from the cloud cover dynamics is based on the analysis of sequences of ground-taken sky images or satellite observations. Despite encouraging results, a recurrent limitation of existing deep learning approaches lies in the ubiquitous tendency of reacting to past observations rather than actively anticipating future events. This leads to a frequent temporal lag and limited ability to predict sudden events. To address this challenge, we introduce ECLIPSE, a spatio-temporal neural network architecture that models cloud motion from sky images to not only predict future irradiance levels and associated uncertainties, but also segmented images, which provide richer information on the local irradiance map. We show that ECLIPSE anticipates critical events and reduces temporal delay while generating visually realistic futures. The model characteristics and properties are investigated with an ablation study and a comparative study on the benefits and different ways to integrate auxiliary data into the modelling. The model predictions are also interpreted through an analysis of the principal spatio-temporal components learned during network training. Manuscript accepted for publication in Applied Energy

Owners of housing stocks require reliable and flexible tools to assess the impact of retrofits technologies. Bottom-up engineering-based housing stock models can help to serve such a function. These models require calibrating, using micro-level energy measurements at the building level, to improve model accuracy; however, the only publicly available data for the UK housing stock is at the macro-level, at the district, urban, or national scale. This paper outlines a method for using macro-level data to calibrate micro-level models. A hierarchical framework is proposed, utilizing a combination of regression analysis and Bayesian inference. The result is a Bayesian regression method that generates estimates of the average energy use for different dwelling types whilst quantifying uncertainty in both the empirical data and the generated energy estimates. Finally, the Bayesian regression method is validated and the use of the hierarchical Bayesian calibration framework is demonstrated.

The purpose of this research is to introduce a qualitative sustainability performance assessment framework for food supply networks, based on the perception of their key stakeholders’ upper management. Moreover, the paper provides industry insights by exemplifying the value of the proposed framework for the UK food industry. A critical review on the most acknowledged sustainability assessment methodologies and tools resulted in the synthesis of the proposed framework. An illustrative application follows, based on data from semi-structured interviews with C-level executives from key players of the UK poultry sector. The results demonstrate an easy-to-use approach, with a comprehensive and sharp outcome on supply chain sustainability performance assessment. Industry insights demonstrate an adequate sustainability performance with respect to the entire supply chain. A detailed view on different echelons reveals specific areas that could be improved, such as the environmental performance at both farming (production) and processing levels. This work extends the scope of current sustainability performance assessment tools by providing a tangible triple bottom-line overview, as well as echelon-specific and indicator-specific details, in a user-friendly, yet straightforward, way. UK food industry insights are valuable for practitioners and academics. The illustration is based exclusively on C-level executives’ viewpoint; thus, any generalization of the results should be considered to this effect. Supply chain stakeholders, policy-makers, and researchers could perform a quick and reliable supply network sustainability performance assessment.