The novelty of this research is that it investigates an on-site solution for the treatment of restaurant waste using a microwave generated plasma for pyrolysis and gasification. The developed system has been used to treat waste from a city centre fast food restaurant. The system was designed with the aim of reducing the amount of waste being sent to landfill by approximately 94%. The waste is mostly food based but also includes paper waste such as napkins. It was separated into three categories: mixed food, paper and fries. Samples of the mixed food and paper waste were analysed for chemical composition and calorific value. A 2.45GHz magnetron was used to supply 1kW of microwave power to a plasma cavity that had an argon flow rate of 1.5 litre per minute. The design of the microwave plasma cavity was performed using the simulation software, COMSOL. The cavity consists of a tapered waveguide section that is shorted at one end to produce a stationary wave with a large electric field at the gas nozzle. The field is strong enough to produce a self-striking argon plasma when the power is applied. Nitrogen was used to keep the plasma cavity clear of smoke, vapours and other hot gas. The best nitrogen flow rates were found to be around 2 litres/minute, although 5 litres/minute was used in the test to avoid the CO sensor saturating. The combination of the argon and nitrogen was used to purge the gasifier of oxygen. The pressure inside the gasifier was held at 200mbar during the experiments. The resulting plasma jet was used to produce syngas from the waste samples inside a thermally insulated, steel-walled reactor. Temperature profiles were recorded to find the best gas flow rates. 10g samples of the three waste categories were tested in triplicate and the results are presented. Syngas production was recorded using a Quintox gas analyser that measured CO, CO2 and O2. The data was captured every 10s during testing using a PC running a custom-built LabVIEW program. This program was also used to set the microwave output power and record the reflected power and temperatures using National Instruments cDAQ modules with analogue to digital converters. The CO and H2 in syngas can be used as a fuel to offset the cost of running the plasma jet. The results reveal that it is possible to generate the syngas using waste food materials. This study has included an investigation of some of the parameters, including power and flow rates of argon and nitrogen, on the plasma created. Others effects were taken into consideration throughout the research such as the study of the sample moisture levels and the final reduction of mass after the experiment. The ashes produced by the tests were investigated using SEM/EDX analysis. These results are also presented and analysed.

Accurate urban water demand forecasting plays a key role in the planning and design of municipal water supply infrastructure. The reliable prediction of water demand is challenging for water companies, specifically when considering the implications of climate change (Zubaidi et al., 2018). Several studies have documented that weather variables drive water consumption in the short-term, and it enhances the accuracy of the prediction model when it is combined with socio-economic factors. However, the impact of climate change on the municipal water demand has yet to be challenged. To surmount this challenge, more research work is needed to accurately estimate the required quantity of water with increasing water demands. Recently, Artificial Neural Networks (ANNs) have been found to be an innovative approach to predict water demand. This PhD study aims to develop a novel methodology to forecast the impact of climate change on municipal water demands for a long-term time series based on the baseline period 1980-2010. It should be highlighted that, based on our knowledge, this is the first study of substantial duration, based on data collected from 1980-2010, which focuses on the associations between monthly climate change and municipal water consumption. A new approach is therefore proposed to quantifying municipal water demands through the assessment of climatic factors, using a combination of a Singular Spectrum Analysis (SSA) technique, three hybrid computational intelligence algorithms and an ANN model. These hybrid algorithms include a Lightning Search Algorithm (LSA-ANN), a Gravitational Search Algorithm (GSA-ANN) and Particle Swarm Optimisation (PSO-ANN). The SSA technique is adopted to decompose the time series of water consumption and climate variables to detect the stochastic signal for each time series. In the same context, the hybrid algorithms are used to find the best value of learning rate coefficient and the number of neurons in both hidden layers of the ANN model. Based on the performance of each hybrid algorithm, the most accurate and reliable water demand forecast model will be selected and used for estimating future water consumption. The considered environments of this study are applied in Australia and the United States from America for mitigating the uncertainty associated with the geographic location (the data of the United States of America was used to support the reliability of developing the municipal water demands prediction model). Furthermore, the Long Ashton Research Station Weather Generator (LARS-WG) model is utilised to simulate future climate factors over three periods (2011-2030, 2046-2065 and 2080-2099) based on the B1, A1B and A2 emission scenarios and seven General Circulation Models (GCMs). The future projection of these climate factors is applied directly to the impact model of water consumption to obtain the projected municipal water demand for different future periods and different greenhouse emission scenarios. The principal findings of this research are the following: from the model perspective, 1) the SSA is a powerful technique when used to remove the effect of socio-economic factors and noise, and detect the stochastic signal time series for water consumption. 2) The ANN model has better performance in term of optimising the correlation between observed and predicted water consumption when using the (LSA-ANN) algorithm. 3) The evaluation of the ANN model (using a validation data set) for Melbourne and Columbia Cities gives a correlation coefficient of 0.96 and 0.95, and the root mean square errors are 0.025 and 0.016 respectively. These findings indicate the capability of the proposed model to predict water demands with high accuracy in different continents. 4) The high performance of LARS-WG model results are found to be appropriate for the simulation of future climate variables. 5) The harmonisation between future monthly water demand (for the periods 2011-2030, 2046-2065 and 2080-2099) and stochastic signals of climate variables, relative to baseline period 1980-2010, emphasises the reliability of the present methodology. However, from the water demand perspective, the water percentage demand (WPD) are likely to rise in winter, drop in summer and fluctuate in both spring and autumn seasons for all periods and under all greenhouse emission scenarios. The results of WPD distribute between -3.5% and 3% for all periods and emission scenarios. The A2 scenario shows the highest and lowest values of WPDs compared to the A1B and B1 scenarios, in particular, in the 3rd period. The mean of seasonal WPD values shows that there is no dominant scenario as the best or the worst case of water demand over all future periods. The highest amount of seasonal demand happens in winter (A2 scenario, 3rd period), and the lowest amount of seasonal demand occurs in autumn (A1B scenario, 3rd period). In conclusion, this study facilitates the conception of the impact of climate change on municipal water demand from the baseline period 1980-2010.

Due to increasing awareness of potential Cr toxicity, there is a pressing need to establish sensitive and robust Cr fractionation and speciation methodologies that will be enable separation of the two redox Cr species (CrIII and CrVI) from different environmental phases and their quantification. The intention of this work was to assess the behaviour of Cr species, especially CrVI, in soils and the factors controlling Cr solubility, fractionation, redox transformation rates and uptake by plants. The analysis methods relied on alkaline extraction in TMAH, liquid chromatography (LC) to separate the chromium species and inductively couple plasma mass spectrometry (ICP-MS) for quantification of chromium. The interference of 40Ar12C+ background peak at mass 52 was reduced by using the CCT-KED facility of the ICP-MS. A solution of 50 mM TRIS buffer, 40 mM NH4NO3, 10-5 M ammonium-EDTA at pH 7.0 was used as the chromatographic eluent. The method developed is suitable for determining CrVI in soil, following alkaline extraction in TMAH, but not for CrIII due to poor recovery, redox transformation and strong binding of CrIII with humic acid despite attempts to preserve the trivalent species using EDTA and heating. The extraction method was applied to assessing Cr speciation and fractionation in a wide range of soil ecosystems collected from urban sites in Wolverhampton, Nottingham, London and a historical sewage sludge disposal farm in Nottinghamshire. To predict soil CrVI content the use of TMAH-extractable Cr (CrTMAH) was better (R=0.911) compared to total soil Cr content (Crtotal; R=0.554). The same analytical approaches were also applied to the development of a method to determine isotopically exchangeable CrVI in soils. This employed isotopically enriched 50CrVI as a ‘spike’ isotope added to soils suspended in varying concentrations of TMAH in an attempt to resolve a consistent fraction of isotopically exchangeable, or ‘labile’, CrVIO42- in soil. It was apparent that, because of the slow exchange kinetics of CrVI in soils, it was difficult to determine a consistent isotopically exchangeable fraction. Nevertheless, the investigation did suggest a refinement of the simple TMAH extraction protocol could enable direct determination of labile soil CrVI. The kinetics of CrVI interaction with a geocolloid (humic acid) was assessed and humic acid was found capable of both reducing CrVI and binding with the resulting CrIII species. Finally, Cr uptake by maize grown on a historical sewage sludge disposal farm was assessed with several approaches to finding a correlation between Cr in soil and Cr uptake by plants. The concentration of CrVI in soil, and its solubility, could be reasonably well predicted from Crtotal or CrTMAH and soil properties. However, restricted uptake of CrVI by the maize plants, and probably reduction of CrVI to CrIII in the root system, made it impossible to predict Cr transfer to shoots or the speciation of the Cr in maize shoots. Overall, due mainly to the apparent ability of the maize plants to control uptake and speciation of CrVI, the produce was considered safe to be consumed by ruminants as regards CrVI content.

The rapid depletion of fossil fuels has raised increasing attention worldwide, and initiated intensive research for sustainable alternatives for energy production. Among these, biodiesel from microalgae has appeared as one of the most promising candidate due to their ability to accumulate large amount of lipids. Indeed, microalgae can achieve a productivity up to 25 higher than other crop sources without need of cultivatable soil, therefore without competing with food production. In the meantime, microalgae have also shown promising results for the treatment of various kind of wastewaters. However, the cultivation of microalgae for energy production suffers from the large costs of harvesting and dewatering of biomass, prior to lipid extraction and biofuel production, which accounts for up to 50% of operating costs. Therefore, the search for cost-effective methods of harvesting and dewatering of microalgae biomass has become necessary to optimize their usage. This study investigates forward osmosis (FO) for the dewatering of microalgae biomass and its implementation within a photobioreactor used for wastewater treatment. FO is a cost-effective filtration process based on the differences of osmotic pressure across a semi-permeable membrane. The use of FO for microalgae dewatering is of high interest, given the high fouling ability of microalgae biomass and the low fouling promises of FO. First, the feasibility of using FO for microalgae dewatering was assessed, focusing on better understanding the fouling mechanisms involved. The filtration performances have been investigated under various operating parameters. It has been found that when Ca2+-containing draw solutions were used, microalgae responded to the back diffusion of calcium ions by an extensive excretion of carbohydrates, accelerating the formation of algal flocs, thus enhancing the rate and extent of flux decline and reducing the algae dewatering efficiency. However, most of the fouling was reversible by simple hydraulic flushing. In addition, substantial adsorption of algal biomass was observed on the feed spacer. Also, Scenedesmus obliquus and Chlamydomonas reinhardtii, with fructose and abundant glucose and mannose in its cell wall, showed strong response to the back diffusion of calcium ions which encouraged S. obliquus to produce more extracellular carbohydrates and formed a stable gel network between algal biomass and extracellular carbohydrates, leading to algae aggregation and severe loss in both water flux and algae biomass during FO dewatering with Ca2+-containing draw solution. Among the species investigated, Chlorella vulgaris without fructose was the most suitable microalgae species to be dewatered by FO with a high algae recovery and negligible flux decline regardless of which draw solution was applied. These findings improve mechanical understanding of FO membrane fouling by microalgae; have significant implications for the algae species selection; and are critical for the development and optimization of FO dewatering processes. Finally, the implementation of FO dewatering with continuous microalgae biomass production and synthetic wastewater treatment was investigated. Two systems (External FO ; Immersed FO) have been studied and compared in order to provide insights on the advantages and disadvantages of each system. Constant parameters have been set identical for both systems: operation time; photobioreactor; hydraulic retention time; biomass production; FO permeate volume. The results reveals that the wastewater treatment efficiency (nutrients removal), as well as the production of biomass were greater with the immersed system due to a greater microalgae growth. However, these may not be sustainable in a long term operation of the immersed system. The external FO system was found better in terms of salinity build-up and FO dewatering performances. Overall, an external FO dewatering is recommended due to its better flexibility and sustainability.

Large-scale complex systems have large numbers of variables, network structure of interconnected subsystems, nonlinearity, spatial distribution with several time scales in its dynamics, uncertainties and constrained. Decomposition of large-scale complex systems into smaller more manageable subsystems allowed for implementing distributed control and coordinations mechanisms. This thesis proposed the use of distributed softly switched robustly feasible model predictive controllers (DSSRFMPC) for the control of large-scale complex systems. Each DSSRFMPC is made up of reconfigurable robustly feasible model predictive controllers (RRFMPC) to adapt to different operational states or fault scenarios of the plant. RRFMPC reconfiguration to adapt to different operational states of the plant is achieved using the soft switching method between the RRFMPC controllers. The RRFMPC is designed by utilizing the off-line safety zones and the robustly feasible invariant sets in the state space which are established off-line using Karush Kuhn Tucker conditions. This is used to achieve robust feasibility and recursive feasibility for the RRFMPC under different operational states of the plant. The feasible adaptive cooperation among DSSRFMPC agents under different operational states are proposed. The proposed methodology is verified by applying it to a simulated benchmark drinking water distribution systems (DWDS) water quality control.

Concerns about climate change and our awareness on energy security have risen during the last decades leading the search for new forms of energy to reduce the world’s dependence on fossil fuels. Bioenergy has been proposed as one route to contribute significantly to meet global energy demand by using renewable sources of energy. The overall objective of this work was to study and optimise a hydrolysis treatment of lignocellulosic biomass but particularly of Miscanthus \(\chi\) giganteus under the biorefinery concept. A modified organosolv method using subcritical water, ethanol and carbon dioxide on a high-pressure batch reactor was proposed and tested for its efficacy on the hydrolysis and fractionation of Miscanthus into its lignocellulose main components, hemicellulose, cellulose and lignin. Temperature (80–200\(^0\)C), reaction time (5–60 min), ethanol concentration (0–70%), carbon dioxide initial pressure (10–55 bar) and load size (2.5–15 g) were the parameters studied and respective ranges. Optimisation models for solubilisation and delignification were obtained and validated using a central composite design based on a response surface methodology. According to both models temperature is the parameter that affects hydrolysis the most obtaining the highest hydrolysis solubilisation and delignification at 200\(^0\)C. On the other side CO2 initial pressure was not significant, what should be further investigated in the future at higher pressures. Reducing sugars quantification obtained a maximum concentration of 2g/10g Miscanthus by DNS assay with an optimal temperature to hydrolyse hemicellulose from 140 to 180\(^0\)C. FTIR analysis of each fraction confirmed a successful separation of the biomass main components with a reduction in the cellulose fibres crystallinity. Temperature was considered the most significant parameter to fractionate biomass with the highest temperature (200 \(^0\)C) being the one that produced a better quality fibres, supernatant and lignin in terms of contamination by the other fractions. However, results also showed that higher temperature tends to oxidise lignin. Fibres analysis by scanning electron microscopy showed that fibre structure was preserved but presented lignin-type globules on their surface indicating lignin reprecipitation.

This research has examined the combustion and emissions of a spray-guided direct-injection spark-ignition (DISI) engine using exhaust gas recirculation (EGR). The impact of EGR type, swirl and tumble intake airflows, compression ratio and fuel type were also investigated. EGR addition resulted in significant fuel consumption improvements and differing particulate matter (PM) behaviour depending on the knock limited maximum brake torque (KLMBT) spark advance achieved. When comparing EGR types, cooled EGR achieved the best fuel consumption and cooled EGR after three-way catalyst (TWC) achieved the best gaseous emissions (NOx and HC). Swirl and tumble intake airflows significantly increased fuel consumption. However, these increases could be minimized with EGR addition. Swirl significantly reduced the accumulation mode particulate emissions, providing a potential solution for PM reduction. EGR addition did not significantly affect PM for the swirl and tumble intake airflow conditions. 20%vol 1-butanol addition to gasoline fuel (Bu20) resulted in significant PM reductions at 8.5 bar IMEP. At 7.0 bar IMEP, EGR addition allowed the KLMBT spark timing to be advanced, as the compression ratio was increased. Fuel consumption was improved by 0.4% due to the spark advance and reduced pumping losses, and PM improved because the formation of primary particles was reduced.

The chemistry of aerosol particles is critical to the influence said particles have over human health, air quality and the distribution of nutrients across the world. Current models estimate that windborne dust represents the movement of thousands of teragrams of solid material of varying composition and solubility across continents and into the world’s oceans. Understanding the composition and surface reactivity of anthropogenic particles from industry, agriculture and vehicle emissions is vital to understanding their potential impact on the world, and the structure and behaviour of inhalable pharmaceuticals is a strong determinant of their efficacy. The following work examines a broad selection of natural and anthropogenic particulate samples with synchrotron-based techniques, including analysis of ship emissions collected directly from stacks for the first time. The effect of simulated atmospheric acid processing on the solubility of iron on coal fly ash is evaluated, and optical trapping is used in conjunction with analytical techniques to observe the influence of relative humidity on the properties of pharmaceutical aerosols and aqueous droplets containing fluorescent protein solutions.

This thesis develops a participatory modelling process to study improvement in the management of irrigation efficiency, including physical and social dimensions in the context of arid and semi-arid regions of Iran. This study develops an interdisciplinary and participatory method to understand and strengthen collective decision-making in local Iranian farming systems. Specific attention is given to groundwater irrigated agricultural practices under the Iranian governance system to provide wider context. Kashan City, in central Iran is selected as a case study area for specific reasons, such as historical water use, the farmers’ rich indigenous knowledge, and successful agricultural practices under conditions of water scarcity. The accessibility and willingness of local farmers to engage in a participatory modelling process are considered. The thesis suggests the first use of role-play simulation for irrigation management practices in Iran, is an effective and insightful method of achieving adaptive management solutions. The application of an innovative participatory simulation modelling with farmers revealed their main incentives for collective irrigation practices, their capabilities to learn and evaluate the system. It is argued that management decisions have major impacts on farmers’ livelihoods and therefore it is essential to integrate farmers’ perspectives in local governance to sustain agricultural productivity.

This hypothesis driven research investigated the removal of Cu, Fe, Zn and Mn from synthetic metal solutions and real Acid Mine Drainage (AMD) from Wheal Jane mine in West Cornwall UK, employing waste gas sludge (BOS sludge) which is an end waste reside generated from steel production. Batch experiments showed the efficiency and adsorption rates increased with reduction in BOS sludge particle size, lower in initial metal concentration, increase in BOS sludge dosage, an increase in initial pH and increase in agitation speed. Fitting of the Langmuir isotherm model to experimental data gave a good fit with correlation coefficients R\(^2\)≥0.99 and the selectivity series of BOS sludge was: Cu\(^2\)\(^+\)>Fe\(^3\)\(^+\)>Zn\(^2\)\(^+\)>Mn\(^2\)\(^+\). For single and multiadsorbate systems, a Pseudo second order model was the most appropriate theory to satisfactorily describe experimental data and the rate limiting step for this process was chemisorption. Adsorption was spontaneous and high pH promoted adsorption possibly by precipitation and/or ion exchange processes which had taken place between the exchangeable cations present in BOS and solutions. Results from the treatment of real and synthetic AMD solutions revealed that BOS sludge worked well and hence BOS sludge as a novel low cost material could be used as a sustainable sorbent in AMD treatment technologies.