PhD, EngD and MSc by research theses (SWEE)
Permanent URI for this collection
Browse
Recent Submissions
Item Embargo Understanding the risk of underwater skimming of slow sand filters(Cranfield University, 2024-06) Elemo, Tolulope Nwabiani; Hassard, Francis; Jefferson, BruceAbstract This research presents an in-depth examination of underwater skimming (UWS) for cleaning slow sand filters (SSF), as an alternative to the traditional dry skimming (DS). The study explores the risks and advantages of UWS compared to DS methods, particularly in terms of filtration performance, microbial removal effectiveness, and operational efficiencies. The research includes an evaluation of the current state of SSF technology, including operational practices and associated risks faced by operators within the potable water sector, setting the background for identifying the potential improvements that UWS may offer. The study further analyses the risks of particle penetration, head loss development and water quality in SSFs when employing UWS, supported by data from pilot-scale experiments conducted to compare UWS and DS. These experiments compare the effects of UWS against the conventional methods, focusing on filtrate quality, recovery after skimming, and system resilience. Additionally, the study investigates the effects of UWS on dissolved oxygen consumption within the SSF, using a mass balance model to predict the dynamic changes in oxygen levels that occur due to operational disturbances caused by UWS. This aspect of the research highlights the environmental implications of adopting UWS in water treatment practices. One of the key findings from this research is that UWS filters exhibited less disruption post-skimming, allowing for quicker recovery to microbial compliance compared to DS filters. They also maintained more stable microbial water quality immediately post-skim, as evidenced by consistent removals of coliform at 1.9±0.2 log, compared to DS where removals dropped to 1.1±0.4 log. While surface agitation in a worst-case scenario UWS system may increase the likelihood of particle penetration and breakthrough, deeper media depth (>500mm) mitigates this, with particle breakthrough reducing from 2229 no/mL at 200 mm to 53 no/mL at 500mm. Maintaining a 'sweetening flow' during UWS could considerably improve DO supply, and reduce the emergence of anoxic conditions, while considerably reducing the recovery time caused by any flow reductions or pauses. For example, recovery can increase from 10.1-10.9 bed volumes when flow is completely paused, to less than one bed volume with a continuous sweetening flow during skimming. The study maintains that UWS not only addresses the operational challenges posed by traditional methods but also enhances the efficacy and sustainability of SSFs. Through this comprehensive analysis, the research provides substantial evidence that UWS could be instrumental in advancing SSF operation, solidifying its importance as a vital aspect of future research and application in the field. This research contributes to knowledge by demonstrating that UWS enhances the efficacy and sustainability of slow sand filtration systems, reducing operational downtime and maintaining microbial water quality. The potential impact of this research is significant, as it offers a method to increase production capacity from existing SSF assets, potentially transforming slow sand filtration practices globally.Item Embargo Bioremediation of oil-rich wastewater: managing sewer Fats, Oils, and Grease (FOG) deposits with energy uncoupler product(Cranfield University, 2023-09) Jawiarczyk, Natalia; Jefferson, Bruce; Bajón Fernández, YadiraThe disposal of Fats, Oils, and Grease (FOG) down drains in both residential and commercial settings results in the buildup of these substances within sewer systems. This accumulation can ultimately lead to blockages and subsequent sewer overflows, posing significant challenges for the water industry. The impacts include potential customer dissatisfaction, negative effects on business operations, and regulatory fines. Effectively managing FOG is a complex issue, and finding viable solutions is paramount. Solutions leading to an alleviation of this problem are of great value, nonetheless, no uniform approaches have been established so far, and the existing measures remain insufficient. FOG bioremediation is emerging as a promising alternative to traditional sewer cleaning methods, but effective, targeted implementation requires higher scientific understanding of FOG deposit formation and modes of action of biological products. This research introduces a novel approach to understanding and addressing FOG deposit formation and treatment. It does so by tailoring these methods to the specific stages of FOG deposit development and utilizing an energy uncoupler product— specifically, a combination of yeast protein extract with surfactants. To substantiate the effectiveness of this approach, comprehensive trials were conducted. These trials encompassed synthetic solutions to simulate deposit formation, preformed synthetic deposits, as well as real deposits collected from the UK's sewerage network. The results of the thesis question and provide an alternative to the currently accepted model of FOG deposit formation through saponification. Instead, the work proposes a two-stage model based on the initial starch-lipid complexation followed by growth through accumulation of fats, lipids, carbohydrates, proteins, and calcium. The study then assessed the uncoupler treatment's impact through two mechanisms of action, i.e., inhibition and rehabilitation, in terms of reducing deposit mass and removing organic fractions present in wastewater. The results provided compelling evidence for the advantageous use of metabolic uncouplers in minimizing FOG deposit formation within sewer systems. Finally, the economic assessment of using the metabolic uncoupler revealed its financial feasibility for both planned and unplanned sewer cleaning procedures through the reduced maintenance that occurred when using it.Item Embargo Using high organic carbon materials to manipulate soil microbiology for improved nitrogen bioavailability from anaerobic digestate(Cranfield University, 2024-09) Van Midden, Christina; Pawlett, Mark; Harris, Jim A.; Sizmur, Tom; Shaw, Liz; Biotechnology and Biological (BBSRC)Anaerobic digestate is a by-product of biogas production, often used as a fertiliser due to its high nitrogen content. However, nitrogen losses from its application leads to environmental pollution. The aim of this PhD project was to add agronomic value to anaerobic digestate and reduce its environmental impact by understanding the microbial mechanisms associated with improving its nutrient use efficiency by crops. Digestate with a high organic carbon content is known to stimulate microbial growth and the immobilisation of nitrogen into soil microorganisms. However, after phase separation the liquid fraction contains large quantities of nitrogen in bioavailable forms but has reduced organic carbon. Soil incubation experiments were designed to determine the type (i.e. labile or recalcitrant) and rate of organic carbon required to stimulate microbial immobilisation of nitrogen from liquid digestate. A polytunnel pot experiment with spring barley and a field experiment with sugar beet tested the addition of two carbon additives (straw and glycerol) selected from the previous experiments on plant growth and nitrogen use efficiency. The addition of glycerol increased microbial biomass carbon within a month from application in both experiments, however there was no subsequent increase in crop yield or nitrogen uptake, nor were N2O emissions and ammonia volatilisation affected. This indicates that either the carbon rate was too low to stimulate a nitrogen immobilisation that was significant enough to impact crop nitrogen uptake or that nitrogen remineralised too rapidly to be of benefit to later key nitrogen demanding crop growth stages. Future studies need to focus on determining the optimal amount of carbon to add with digestate to positively impact yield and reduce nitrogen losses. In conclusion this PhD thesis demonstrated a proof of concept that materials high in organic carbon content can be used to temporally immobilise digestate supplied nitrogen within the soil microbial biomass.Item Embargo Energy scavenging piezoelectric powered led system for use in tracer ammunition(Cranfield University, 2025-04) Crawley, Fregus; Luo, Jerry; Hucker, Martyn; Almond, HeatherFuel-oxidizer tracer ammunition is the standard technology used to produce bright light for projectile observation. However, a modern electronic tracer system has the potential to eliminate the safety risks associated with combustible materials and open flame systems by replacing them with a safer, integrated energy harvester-powered electronic light-emitting system. The goal of this research is to investigate the technologies necessary to convert kinetic energy from the bullet propulsion into electrical power and to assess whether an integrated energy harvesting system, coupled with electrical storage and an LED with the accompanying circuitry, could feasibly replace the current technology in the future. The study focuses on analysing existing mechanical-to-electrical transduction technologies, understanding their design and use limitations, and evaluating their suitability for implementation with small arms munitions that undergo high linear and rotational acceleration. Additionally, this research examines the complexity of manufacturing, construction, and adaptability of these technologies to smaller and larger of munitions. After reviewing and filtering previous system designs and technology prototypes, piezoelectric energy harvesting technology was selected due to its energy density, material and structural compatibility for withstanding large forces and lower mechanical system complexity for further development. A prototype piezoelectric system was designed and simulated using commercial software to model both structural and electrical behaviour. Experimental validation tests were conducted with high compressive loads and rotational forces experienced in real-world conditions. The research developed three novel spring structures that significantly increase the power density of linear and rotational piezoelectric energy harvesters. These spring structures feature enhanced shearing capabilities with disc spring optimisation allowing 39% energy harvesting improvement and a prototype system tuned for the 7.62 mm tracer outputting 3 V. and can be manufactured with relatively low complexity compared to other energy harvesting technologies. With the novel energy harvesting system in place, additional modelling was conducted to design the accompanying LED circuit and capacitive energy storage, thereby completing the development of the Electronic Tracer system.Item Embargo From source to tap: tracking of drinking water bacteria using flow cytometry(Cranfield University, 2024-04) Claveau, Leila; Hassard, Francis; Jeffrey, PaulUnderstanding how water microbial quality changes occur in distributed water is crucial for ensuring water quality, safeguarding public health, optimizing treatment processes, and predicting the impacts of environmental and anthropogenic changes on microbial ecosystems. However, current monitoring tools, such as heterotrophic plate count, have limitations due to their inability to capture the full diversity of microbial communities, low sensitivity to non- culturable microorganisms, and delayed results that hinder real-time decision- making. Flow Cytometry (FCM) has emerged as a promising alternative offering high- throughput and real-time analysis of microbial cells. Through metrics such as Total Cell Count (TCC), Intact Cell Count (ICC)High Nucleic Acids (HNA), Low Nucleic Acids (LNA), and Bray and Curtis Dissimilarity Index (BCDI) resulting from the CHIC analysis of cell’s fluorescence histogram, FCM provides valuable insights into microbial abundance, viability, and metabolic activity. Despite its potential, the application of these metrics lacks standardised guidance, with metrics such as HNA and LNA not fully comprehended leading to risks of incorrect application potentially resulting in misinterpretation of water quality data and suboptimal treatment decisions. Therefore, there is a need for addressing the research question of how to appropriately use these metrics to monitor water microbial quality. This EngD study aimed to address this gap by identifying the conditions under which the FCM metrics are most valuable and evaluating their potential as early warning indicators for unwanted water microbial quality. A mixed-methods approach was employed, combining the monitoring of 35 Water Treatment Works (WTW)s and 231 associated Service Reservoirs (SR) with in-depth interstage monitoring of one individual WTW. The first case evaluated the relevance of the metrics across different WTW designs, while the second focused on their relevance at different treatment process stages within a single WTW. The findings revealed that cell counts are most effective in high-cell environments, BCDI is particularly useful in low-cell ones, and HNA/LNA metrics are most relevant in treatment stages involving chemicals. These results highlight the need for a standardised framework to guide FCM users in selecting and interpreting metrics to prevent misinterpretations and support effective water quality management.Item Open Access Anaerobic Membrane Bioreactors for water reuse using municipal wastewater: the role of post-treatment(Cranfield University, 2022-07) Huang, Yu; Pidou, Marc; Jeffrey, PaulAnaerobic Membrane Bioreactors (AnMBRs) are seen as a promising alternative to Aerobic Membrane Bioreactor (AeMBR) based water reuse schemes as they better support a circular economy paradigm with the potential for recovery of energy and nutrients. However, evidence of their application for water reuse is very limited which significantly restricts their potential deployment. This research aimed to identify the current challenges of using AnMBRs for water reuse with respect to their ability to achieve the quality requirements in state of the art national and regional standards. The work investigates the performance and feasibility of technologies commonly applied as a post-treatment stage for AeMBRs and ultimately to provide references for possible treatment trains for future water reuse implementations. A critical review and controlled pilot scale AnMBR and AeMBR operations followed by lab-scale post-treatment trials were conducted to understand the performance of the investigated post-MBR processes and their potential role in AnMBR based water reuse applications. The distinctive matrices of AnMBR and AeMBR effluents, in particular the different nitrogen species as ammonia in the AnMBR effluent and nitrate in the AeMBR effluent, were found to influence different performance across the investigated post-MBR technologies. The presence of ammonia caused a higher membrane fouling and a potential failure to meet the standard for potable reuse during the RO filtration of the AnMBR effluent. When chlorinated, the AnMBR effluent provided a controllable residual ammonia and chlorine concentration while exhibiting lower disinfection by-products formation potential compared to the AeMBR effluent. UV/TiO₂ delivered a selective removal of organic and nutrient compounds as a function of varying the UV intensity and TiO₂ dose from the AnMBR effluent. These findings highlight the potential to combine these processes to achieve more sustainable treatment trains producing high quality effluents for various water reuse applications. In particular, the combination of AnMBR-Chlorination shows promise as a circular economy approach to municipal wastewater treatment for agriculture irrigation.Item Open Access Techno-economic analysis of peer to peer energy trading with electric vehicles(Cranfield University, 2022-06) Xue, Chenxi; Long, Chao; Lao, LiyunOne of the most promising technologies of reducing greenhouse gas emissions is the application of electric vehicles (EVs). Despite deliberated efforts by governments with various encouraging policies to promote EV uptakes, the numbers of EVs have not increased as quickly as expected. The growth of EV numbers is hindered by cost, accessibility of charging infrastructures and range anxiety. P2P EV charging might be one of the solutions to mitigate these barriers to promote EV uptakes. P2P EV charging might be able to reduce running costs of EVs, to provide more charging infrastructures via obtaining energy from another individual EVs instead of power grid, and to encourage the installation of P2P charging infrastructures. However, there have not been much work in the literature on the economic benefit analysis of P2P EV charging. The economic analysis is extremely important at this stage for relevant stakeholders (such as power Distributed Network Operators, EV charging infrastructure planner, Charge Point Operators). In order to carry out the economic benefit analysis, this thesis took use of the main thought of activity-based model (ABM) to simulate and estimate EV batteries’ remaining energy after daily travel, and then modified the supply demand ratio (SDR) P2P pricing model for trading prices calculation. The new combination of above two steps was unique and efficient for the calculation of P2P energy trading with EVs. This work also adopted Monte Carlo method using large number of simulations to reduce errors brought by the randomness of simulation cases. The economic benefits of EV energy buyers and sellers were evaluated at different supply and demand scenarios. The results showed that, with the consideration of tariff difference between daytime charging and night charging (Economy 7 tariff) only, P2P EV charging is able to bring energy saving for EV energy buyers up to £3,32/month and bring energy income for EV energy sellers up to £5.48/month. Those reduced electricity costs, from P2P energy trading, although limited, would also encourage people’s purchasing enthusiasm toward EVs, which would consequently help the uptakes of EVs in UK. As P2P energy trading is a relevant new research area, this is an initial economic analysis of P2P EV charging. There are some limitations, e.g. the degradation of batteries, adoption of other P2P pricing models and EV charging from local renewable generators, etc. have not been considered. These will be carried out in future work in this areaItem Open Access Integrated modelling of the clogging processes of plastic grid permeable pavement(Cranfield University, 2021-09) Zang, Ziling; Hess, Tim M.; Bortone, Imma; Grabowski, Robert C.Because of rapid urban expansion increasing the area of impervious land surfaces and climate change, flood risks and extreme precipitation events are projected to become severe challenges in the future. Sustainable Urban Drainage Systems (SUDS) are designed to increase urban surface permeability and reduce stormwater runoff. As a commonly used SUDS technique, plastic grid permeable (PGP) pavement effectively reduces urban surface runoff. However, clogging is a severe problem that reduces the operational performance and lifespan of PGP. Further research is needed on the clogging process, but it is challenging to conduct field experiments to predict permeable pavement's long- term performance for engineers and researchers. This study aims to evaluate the suspended particle clogging process and mechanisms of PGP using a modelling approach. A 1-D model was developed with COMSOL Multiphysics to understand the clogging process, based on the spatially and temporally mathematical expression. The new integrated hydraulic and clogging model for the PGP system consists of three parts: 1) Hydraulic model, 2) Rainfall-infiltration boundary (RIB) condition and 3) Clogging model, which named as the PGP-HRC model. The PGP-HRC model focuses on the interaction, feedbacks, and parameter changes between the three parts. The hydraulic model and RIB provide water flow driven force for the clogging model. Over time, clogging reduces the media porosity and further changes the soil properties, affecting the hydraulic model and RIB. By testing the model input parameters with different rainfall intensity, initial soil water content, suspended particle concentration, particle size and duration, the clogging time, depth and mechanisms of the PGP system can be understood. PGP-HRC model enables detailed study of hydraulic and clogging processes within porous media, and can be adapted for a range of applications. For the mitigation of surface water flooding, it provides a platform to test the design and maintenance of PGP, which will help for climate adaptation strategy and extreme precipitation in the urban area.Item Open Access Development of a method to classify and analyse the composition of mixed waste materials in real-time(Cranfield University, 2022-07) Vrancken, Carlos; Wagland, Stuart T.; Longhurst Philip J.There is a need for innovative technologies to classify and monitor the composition of solid waste in real-time. This research project has highlighted which information is required to improve current process designs. It also identified visible spectrum cameras as the solution that can better inform waste composition and quality without requiring complementing technologies. The experiments applied deep learning methods to classify the materials based on their images, and a method to analyse the composition of mixed waste was developed. There is a high variability in the appearance of waste materials in the context of a material recovery facility. An image capture setup using multiple cameras and light sources was implemented and tested to acquire a representative set of images. The hardware captures images from different angles, with enhanced shadow details, and different exposure levels. Image processing software further augmented the data by rotating and changing the images resolutions. The images were converted to greyscale to increase the method robustness without affecting classification performance. Deep convolutional neural networks were trained on the augmented datasets. The trained networks obtained state-of-the-art performance when tested and validated for the task of waste material classification. Based on this, a composition analysis methodology was developed and tested with mixed material samples. The methodology provides results as accurate as current manual solutions, but it can analyse a waste stream on a conveyor belt in real-time. The findings and observations from the experimental results contribute to knowledge in three main areas: data capture, data processing, and deep learning. This thesis presents the progressive development of the methodology and discusses different applications for waste management. The composition analysis can provide real-time waste data to improve the overall efficiency of the waste treatment industry. This information can be also used by stakeholders for better decision-making in the future.Item Open Access Aerodynamic design optimization of large-scale offshore wind turbine blade using CFD(Cranfield University, 2022-05) Koragappa, Pavana; Verdin, Patrick G.; Nabavi,Seyed AliRenewable energy is expected to be the main source of power by 2050, bringing an end to the use of fossil fuels; this is the only way to achieve Net Zero. Wind turbines which majorly contribute to this agenda, not only help to reduce CO₂ emission, they are also environmentally friendly and form a cost-effective solution. The aerodynamic study and design of a wind turbine blade is essential as it is directly linked to the performance of the wind turbine. The maximum power generating wind turbine currently operating is the Haliade-X (GE) turbine, which has set a trademark at producing 14 MW, 13 MW or 12 MW. However, a need for higher power generating wind turbines is present to be able to reach the Net Zero target. By upscaling the “DTU 10 MW Reference Wind Turbine” this research has achieved an aerodynamically stable 20 MW offshore wind turbine blade design. Variable rotation speed and variable pitch angle configurations have been considered to achieve an ideal power curve. The aerodynamic performance has been evaluated using CFD and quantified for a length optimized blade design. To ensure structural stability, chord and twist optimizations have also been performed. The chord and twist of the designed blade have been optimized through the momentum theory and the blade element theory. 2D numerical simulations on FFA- W3 aerofoils used in the design of the wind turbine blade have been carried out initially to determine the angle of attack at minimum C𝐷/C𝐿 ratios, which further helps to calculate the chord and twist of the blade. From the calculated value, a new design variant has been proposed and the aerodynamic performance has been evaluated using CFD.Item Embargo Transformation of solid and liquid wastes into fertiliser to minimize urban catchment pollution(Cranfield University, 2024-12) Nartey, Eric Gbenatey; Sakrabani, Ruben; Tyrrel, Sean F.Decentralised treatment systems play a critical role in managing faecal sludge (FS) in sub-Saharan Africa (SSA) where safely managed sanitation is lagging with 79% of the population without it. The systems that treat FS and food waste (FW) into faecal derived fertilisers (FDFs) play a more critical role in linking safely managed sanitation to improved food security. To recover nutrients and organic matter to their fullest potential is urgent in the context of SSA. The International Water Management Institute (IWMI) and partners have led research to convert urban FS and FW through co-composting into various FDF for use in agriculture. Though some strides have been made in developing and commercialising FDF, there are still some research and knowledge gaps including limited information on nutrient and pathogen flow in the decentralised FS and FW treatment system; limited information on the shelf life of stored FDF and on residual effect of FDF application on crops and soil. Hence, this study aimed to generate new knowledge and understanding on the recovery of nutrients and E. coli inactivation during treatment and use of fertiliser produced from FS and solid waste. The methodology involved different experimental set-ups to collect primary data. This followed an end-to-end monitoring of FS and FW treatment to produce FDF, storage of FDF and the use of the FDF in successive lettuce cultivation. Findings from this study, show that between 50-70% of total N from FS is lost at the dewatering stage of treatment. More than 50% of total N is lost during co-composting. While E. coli inactivation efficiency of the dewatering process is minimal (0-14%) in the percolate, dewatered FS on the other hand observed higher E. coli inactivation efficiency of 88-98% (1-2 log reductions). Inactivation efficiency of co-composting stage for E. coli was 100%. No detectable presence of indigenous E. coli was observed in FDF at the end of storage. Storage temperature and duration did not affect re-growth of indigenous E. coli in co-composted FDF. Longer storage of enriched FDF co- compost (NECo) under lower temperatures resulted in decreasing NH4-N concentrations. The field experiment show, residual effect of FDF co-compost (Co) gave lettuce yield of 344% more compared to the control by the second cycle. E. coli was absent on lettuce after successive cultivations. Co plots had higher gross margins/profit per cycle of cultivation. The ROI for Co was 385.7 for first cycle and 309.2 for second cycle.Item Open Access Impacts of urease inhibitors on nitrogen assimilation in wheat and on reducing nitrogen losses(Cranfield University, 2024-03) Drame, Marieme; Kirk, Guy J. D.; Carswell, Alison; Misselbrook, Tom; Pawlett, Mark; Jemo, MartinA major global challenge for the 21st century is to ensure food security and sustainable development while limiting the adverse impact of agricultural reactive nitrogen (Nr) pollution and global warming greenhouse gas emissions (GHG). Climate change mitigation and adaptation strategies, with varying effectiveness, have been implemented across different regions in this perspective. The use of enhanced efficiency N fertilisers (EEF) in agriculture is a potential management strategy towards this aim, with documented benefits but with existing knowledge gaps. In this thesis, the efficacy of EEF, particularly urease inhibitors (UI), was determined under warmer, dryer climatic conditions as are expected to occur more frequently under climate change scenarios. Additionally, the potential of UI to improve nitrogen use efficiency (NUE) and enhance the tolerance of wheat varieties to drought stress at different N rates was evaluated, as well as the influence of UI on plant N assimilation and potential contribution to nitrous oxide (N₂O) emissions. The effects of high soil temperature (>25℃) and low soil moisture (<40% water filled pore space; WFPS) on emissions of ammonia (NH₃ ) and N₂O following application of urea to soil was assessed, and the efficacy of UI in reducing N losses. The findings suggest that treatment of urea with UI effectively reduces NH₃ losses at temperatures reaching 35℃, although overall effectiveness decreases with increasing temperature and low soil moisture conditions. Nitrous oxide emission was not influenced by the presence of UI but was high at soil moistures <60% WFPS. Nitrous oxide emission was also measured from wheat plants grown in soil and in a hydroponic system under low (7 kg ha⁻¹) and high N (70 kg ha⁻¹) conditions. Plants emitted more N₂O under low N growth conditions when supplied with additional potassium nitrate compared with those supplied with urea treated with UI. However, insufficient evidence was obtained from the hydroponic experiment to confirm plant N₂O formation through nitrate assimilation pathways, other than its overall contribution to N₂O emissions. Furthermore, when applied to plants under drought stressed conditions, UI did not enhance wheat tolerance to drought or increase yield and NUE. Nitrogen assimilation was influence by UI, particularly leaf urea concentration which increased in the presence of UI. Similarly, application of urea included with UI at a high N rate (180 kg ha⁻¹) resulted in lower wheat biomass and yield. Varietal differences were also observed in plant N₂O emission, drought tolerance and NUE. Overall, the findings support the use of UI as a Nr mitigation strategy under warm and dry conditions; however, for increased NUE and yield, appropriate fertiliser and crop management, specific to local conditions may be needed.Item Open Access Phenotyping the nutritional status of crops using proximal and remote sensing techniques(Cranfield University, 2024-05) Cudjoe, Daniel Kingsley; Mohareb, Fady R.; Waine, Toby W.; Hawkesford, Malcom J.Understanding the nutritional needs of crops is crucial for ensuring their health and maximising yield. However, the capability to accurately measure relevant physical characteristics (phenotypes) of important crops in response to complex nutrient stresses is limited. For crop breeders and researchers, the existing capacity to characterise crops with adequate precision, detail and efficiency is hindering significant progress in crop development. In this PhD thesis, the use of advanced sensing techniques to assess the nutritional status of African crops was explored, focusing on three main objectives. First, the use of a handheld proximal sensor was investigated to evaluate the spectral properties of quinoa and cowpea crops grown under different N and P supplies in controlled glasshouse conditions (Chapter 3). By analysing these spectral properties, the aim was to identify spectral indices that could show early signs of N and P stress separately in the plants. These stress indicators were related to the overall performance of the crops. Spectral indices were found that could distinguish between N and P stress at the early growth stage of the crops. However, identifying spectral indices for P stress was limited, particularly in cowpea due to the shorter wavelength range of the handheld device. The results showed significant relationships between the spectral indices and traits related to the morphology, physiology and agronomy of the crops. Second, it was demonstrated that different levels of N impact the drought responses of spring wheat (Chapter 4). By evaluating morpho-physiological changes in the plants under high N and low N conditions, an understanding of how spectral reflectance measured at the leaf level could help distinguish between combined and complex stresses such as drought and nutrient deficiency was investigated. The results showed a greater amplitude of drought response in plants that were supplied with high N compared to low N levels, with interactive effects on many morphological and physiological traits. Out of a group of 39 different SRIs, only the Renormalised Difference Vegetation Index (RDVI) and the Red Difference Vegetation Index (rDVI_790) showed better accuracy in detecting drought stress. The results also revealed that indices sensitive to chlorophyll levels, such as the chlorophyll Index (mNDblue_730), Greenness Index (G) and Lichtenthaler Index (Lic2), as well as red-edge indices like Modified Red-Edge Simple Ratio (MRESR), chlorophyll Index Red-Edge (CIrededge) and Normalised Difference Red-Edge (NDRE), were more accurate in detecting N stress. Lastly, the effectiveness of using spectral information from images collected from a drone and spectral reflectance measured with proximal sensors on the ground were compared for detecting N stress in winter wheat under field conditions (Chapter 5). By comparing these two sensing methods, it was assessed which approach is more accurate, reliable and cost- effective for assessing the N nutritional needs of the crop in real-world agricultural settings. The results indicated that the NDVI measured on the ground at the leaf level could accurately detect the small changes in N levels earlier compared to the drone NDVI and canopy level NDVI and for assessing the agronomic performance of winter wheat. Overall, this PhD research sheds new light on the potential of advanced sensing techniques to improve crop management practices and enhance agricultural productivity by providing timely and accurate information about the nutritional status of the studied crops.Item Open Access Role of solute chemistry on membrane crystallisation of inorganic salts(Cranfield University, 2024-07) Vasilakos, Konstantinos; McAdam, Ewan; Campo Moreno, PabloMembrane distillation crystallisation (MDCr) is a process developed to recover valuable salts from salt-rich solutions like sea water, brackish water, waste and others for the promotion of zero liquid discharge (ZLD). The chemistry of the crystallised salts is characterised by their different crystal-liquid interfacial energy derived from their solubility. Various studies have evidenced the importance of the interfacial energy in the nucleation process through Gibbs energy but it has never previously used to determine the scaling, nucleation and crystal growth kinetics of membrane distillation crystallisation. Using a combination of a backscatter technique and digital microscopy to detect bulk and scaling induction, this work provides a precise determination of scaling and bulk induction and metastable zone width (MSZW), resulting into a critical differentiation of heterogeneous adhesive growth for low interfacial energy salt and homogeneous bulk deposition for high interfacial energy growth. After understanding that the membrane is not playing as much role as previously thought in MDCr for high interfacial energy salts, another crucial component of the chemistry of the salt and its solubility, is the solubility–temperature dependence. It was found that even in low interfacial energy salts, the dominant factor of scaling is temperature polarisation and not heterogeneous nucleation as previously assumed. To confirm the less critical role of the membrane in MDCr, three membranes comprised of distinctive properties were compare through the use of a neutral solubility–temperature dependent salt. The results demonstrate how both scaling and crystal growth are kinetically controlled rather than thermodynamically dependent upon the material properties to initiate nucleation. To enhance the dependency of the membrane for nucleation within a kinetically controlled environment, K₂SO₄ was studied which exhibits a sharp positive solubility–temperature dependency. The modification of the solubility limit due to temperature polarisation, modifies the thermodynamic barrier of the MSZW which increase scaling, the extent of which is evidenced to directly inform the nucleation kinetics within the bulk solution. This thesis collectively describes and relates solute chemistry to both scaling and nucleation, enabling enhanced crystallisation strategies to be developed for MDC.Item Open Access Optimising residential electricity demands through innovative demand side management strategies in Nigeria(Cranfield University, 2023-10) Usman, Rilwan; Long, Chao; Mirzania, Pegah; Hart, PhilThe Nigerian power supply faces significant shortages, resulting in frequent nationwide power outages, load shedding and severe energy crises. The country relies heavily on a centralised energy mix, primarily comprising gas-fired power plants with a capacity of 10.6 Giga Watt (GW) and hydropower with a capacity of 1.9 GW. Despite having a total installed capacity of 12.5 GW, only around 4 GW actually reaches end consumers. This is mainly due to limited transmission infrastructure, inadequate distribution facilities, poor metering, inadequate fuel supply, lack of market competition and inadequate management of energy resources. Innovative demand side management (DSM) strategies are required to optimise electricity demands at customer ends to improve the power supply in Nigeria. This thesis develops an innovative DSM method of utilising direct load control (DLC), acting as a mandatory operational strategy for regional residential grids, as opposed to traditional approach of load shedding. The proposed DLC method controls residential loads by classifying loads into three different categories: critical, less critical, and non-critical. The evaluating metrics include energy cost savings and comfort levels of residence (i.e., the length of supply of the critical loads). Furthermore, paper-based surveys are used as the quantitative methods to evaluate the understanding, awareness, and attitude of Nigerian households towards DSM under different representative groups. The survey data are also used to model load profiles, to which the DLC is applied to validate the proposed DLC method. The proposed DLC method was compared with load shedding considering three load shedding scenarios: 1) nobody uses generators during power cut period, 2) running home generators for 4 hours per day during power cut period, and 3) running home generators for 8 hours per day during power cut period. Simulation results showed that, for scenario 1, the proposed DLC method results in a 20% of energy cost saving and a 28% improvement of in comfort level; for scenario 2, the proposed DLC method results in an 87% decrease in household expenditure and a 5% decrease in comfort level, and for scenario 3, the proposed DLC method results in a 93% energy cost saving but a 39% decrease in comfort level. The study shows that households with the post-paid billing systems are less responsive to the DSM approach. However, the proposed DLC strategy results in higher cost savings on the post- paid billing systems (23%) than the pre-paid billing systems (17%), both compared to the load shedding approach. Households working in the public sector who use the pre-paid billing system have proven to be the most effective target group for implementing DSM. This is because these households consume 23% more energy on average compared to other representative household groups. This research presents an innovative DLC method designed to enhance power supply in residential grids, providing an alternative to load shedding in developing countries. Additionally, it utilises a methodology that involves gathering data through paper-based surveys to construct electricity demand profiles, establishing a numerical dataset for future DSM studies. The research findings reveal that the proposed DLC method not only lowers energy expenses but also improve overall household comfort and quality of life.Item Open Access Suspended sediment transport in rivers: new indicators of transport dynamics for analysis of catchment and climate controls(Cranfield University, 2024-10) Shin, Jae Hun; Grabowski, Robert C.; Holman, Ian P.Suspended sediment is found naturally in rivers but can cause environmental and engineering problems, especially if the quantity or quality has been altered. Many factors affect suspended sediment concentration (SSC), such as land cover, land use, vegetation growth, and weather, making it difficult to predict changes in SSC at a location over short time periods (e.g., days to months). The aim of this research was to improve the scientific understanding of intra-annual variations in SSC through the statistical analysis of SSC timeseries data from rivers across a variety of catchment and climate characteristics. The specific objectives were to: (i) characterise the continental scale spatio-temporal variations in SSC dynamics using new transport indicators, (ii) determine the contribution of climate to these variations, and (iii) identify SS transport dynamic responses to climate oscillations as a means to separate out the effects of shifts in seasonal weather from catchment influences. The study used daily SSC (mg/l) and site attribute data from the US Geological Survey (USGS), which included 1,666 gauging stations of SSC across the continent, Hawaii and Puerto Rico. First, new indicators of SSC dynamics were developed and applied to the data, based on magnitude, frequency and timing (MFT). Through statistical analysis e.g., principal component analysis (PCA) and K-means clustering, new insights in spatial variability of temporal dynamics in SSC were identified e.g., high extreme events in desert and mountainous areas, the longest duration of events in upper Midwest and distinctly different timing of events in Puerto Rico. Next, further statistical analyses (regression and geographically weighted regression) were conducted on a reduced number of sites (n=120) to determine the relative importance of different catchment and climate factors. The MFT indicators of SS enabled identification of short term dynamics and new understandings of varying influence of land use and land cover. The key results were identified that agricultural covers were positively related with low frequency SSC events. Urban and forest covers brought higher frequency events, except in the driest region. Annual average precipitation had a negative relationship with SSC magnitude. Finally, the influence of climate oscillations e.g., El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO) on SSC transport dynamic indicators was evaluated for four catchments using continuous and cross wavelet analyses. Periodicities in SSC indicators were identified that match climate oscillations, suggesting that small shifts in seasonal weather (e.g., wetter winters) can cause significant changes in SS transport dynamics in rivers. Future works remain to be using latest SS data in the future or application of latest technology e.g., turbidity as well as optimization of input parameters in modelling by generation of MFT time series. This research provides new understandings of SS transport dynamics in rivers and the relative importance of catchment and climatic factors, which will inform practitioners of SS modelling for better predictability in a changing climate.Item Open Access Assessing the functionality of sand dams as a dryland water source through an evaluation of water loss pathways(Cranfield University, 2024-03) Ritchie, Hannah Nicola Grace; Holman, Ian P.; Parker, AlisonBetween 1 - 2 billion people worldwide suffer from water scarcity, most of whom live in drylands. Irregular but intense rainfall have led to the proliferation of water harvesting. Sand dams, one such technique, comprise a concrete dam wall constructed across ephemeral rivers, which facilitate the accumulation of alluvium. Such dams can store and lose water to varying degrees, the extent of which is unclear. This research therefore aimed to evaluate spatial and temporal water losses from sand dams in order to understand their storage potential and their contribution to water availability within the river channel and surrounding weathered basement aquifer. Through monitoring telemetered abstraction data and employing analytical modelling, this thesis explored variations in rates of water use and seepage from sand dams in Kenya. By being the first study to use 2D geophysics at sand dams, it improved the understanding of how sand dams interact with the surrounding hydrogeological environment. Contrary to assumptions, geophysical inversions successfully showed that the trapped alluvium of sand dams typically overlies weathered basement material up to approximately 25 m in thickness, rather than impermeable bedrock. Alongside simulated flow rates, averaging 32.4 m³/day and empirical evidence, results highlight a partial recharge function performed by sand dams, primarily driven by lateral flow. Despite this, estimated groundwater volumes at full capacity, of up to 4,200 m³, were sufficient to meet community water needs throughout the dry seasons, in part due to recharge to the sand dams. This indicates the storage capabilities of the studied sites. By identifying site and hydrogeological characteristics that may result in lower levels of seepage from the dams, and greater recharge to the dams, the findings aim to enhance site selection and dam construction, enabling more sand dams to better meet storage requirements. This will contribute to facilitating the implementation and scaling-up of sand dams in areas where they are physically suitable and appropriate to the specific needs of a community.Item Open Access Investigating the impact of coupling process-based and data-driven models on wheat crops in arid and semi-arid regions(Cranfield University, 2024-07) Oulaid, Bader; Corstanje, Ronald; Milne, Alice E.; Waine, Toby W.; El Alami, RafiqAccurate prediction of wheat yields in arid and semi-arid regions is challenging due to water scarcity, varying environmental conditions, and the dynamic nature of factors influencing crop growth. This thesis aims to enhance scalable wheat yield prediction by integrating remote sensing (RS) data into process-based and data-driven models for more precise and accurate yield prediction in these regions, supporting both tactical and strategic decision-making in agriculture. AquaCrop was chosen for its robust simulation of crop yield response to water. Four interlinked research questions are addressed in this study. First, I identify key factors impacting wheat yield prediction based on sensitivity and SHAP analysis for process-based and data-driven models, respectively. Second, I compare the trade-offs between calibrating process-based models using ground- based hemispherical data and freely available remotely sensed data, highlighting the trade-offs between accuracy and practicality. Third, I evaluate the effectiveness of early-season data-driven yield prediction models across two geographic regions, emphasising the need for region-specific calibrations to maintain accuracy and quantifying accuracy loss due to model transferability. Model performance improved as the season progressed, with Support Vector Regressors achieving an RMSE of 0.23 t ha⁻¹ in the arid regions and Random Forests achieving 0,50 t ha⁻¹ and 0.46 t ha⁻¹ in semi-arid and global models. Fourth, I examine the integration of data-driven models into process-based models through data assimilation techniques, demonstrating how Bayesian assimilation and high-temporal resolution data improve yield prediction accuracy. Bayesian assimilation reduced the prediction errors, decreasing RMSE and MAPE by 25% and 76.5%, respectively, compared to no assimilation approach. This research contributes to the body of knowledge by providing a comprehensive framework for integrating remote sensing data into yield prediction models, supporting precise and timely agricultural decision-making to optimise productivity in water-limited environments.Item Open Access Computer vision methods for the analysis of multimodal and multidimensional data for high-throughput plant phenotyping(Cranfield University, 2023-12) Okyere, Frank Gyan; Mohareb, Fady R.; Hawkesford, Malcom J.; Simms, Daniel M.Drought and nutrient stresses substantially impact crop productivity, frequently resulting in lower yields and financial losses to farmers. Early detection and tracking of these stresses are significant for improving agricultural yield and achieving the world food challenge goals. Advanced image technologies such as the use of conventional cameras and imaging spectroscopy combined with computer vision methodolgoies are being leveraged for non-invasive plant phenotyping to improve crop productivity, resilience, and sustainability. This thesis seeks to combine these technologies with machine learning algorithms to develop automated phenotyping pipelines to phenotype plants at different growth stages, particularly; for nutrient and drought stress identification and quantification. With this proposal, the onset of plant nutrient and drought stresses could be detected early and at different growth stages of the plants. Three experiments (two in the glasshouse and one in the field) were conducted, and images were acquired using digital RGB and a hyperspectral camera. The first experiment (nutrient stress) was performed in the glasshouse, the second (nutrient stress) on the field and the third (drought stress) in the glasshouse. The glasshouse nutrient experiment was performed on quinoa and cowpea plants made of four treatments: high nitrogen high phosphorus (HNHP), high nitrogen low phosphorus (HNLP), low nitrogen low phosphorus (LNHP) and low nitrogen low phosphorus (LNLP). The field nutrient experiment was performed on wheat plants made of 12 Olsen phosphorus varitions (approximately 3, 6, 9, 12, 15, 18, 21, 25, 30, 40, 50 and 60 ppm). The third experiment is a wheat drought analysis under variable nitrogen at selected plant growth stages. The treatments include: well-watered high- nitrogen (WWHN), well-watered low-nitrogen (WWLN), drought-stress high-nitrogen (DSHN) and drought-stress low-nitrogen (DSLN). Several image processing and machine learning techniques were employed to pre-process, post-process, and analyze plant- specific traits for tracking plant drought and nutrient stresses. Specifically, using digital imaging, a new segmentation algorithm invariant to illumination and complex background scenes was proposed to segment field and glasshouse-based images. Statistical and machine learning methods were employed to identify phenotypic traits sensitive to nutrient (nitrogen and phosphorus) deficiencies. Additionally, plant colour, morphology, and texture features were critically analyzed to assess their response to different stresses in plants. Using a hyperspectral imaging, a hybrid deep learning model was proposed to detect and track plant nitrogen and phosphorus deficiencies. In this case , the spatial and spectral characteristics of plants were analyzed, and deep learning algorithms were combined to understand their response to nutrient and drought stress in plants. Finally, using the spectral characteristics of plants, different conventional machine learning algorithms including Random Forest, Partial Least Square Regression and Support Vector Machines were developed to model the trends and patterns of plants for drought stress detection. The research results show a link between colour and nutrient stress, while texture and colour features were highly responsive to drought stress. The short-wave infrared region of the electromagnetic spectrum was highly responsive to plant phosphorus deficiency, while the blue, red, and near-infrared regions were highly connected to plant nitrogen deficiency. Furthermore, combining a proposed vegetation indices (VIs) from the VNIR regions of the spectrum with already known VIs resulted in the easy identification of plant drought stress compared to using only the known or proposed indices.Item Embargo Analysis of factors driving foreign direct investment in the liquefied natural gas sector: case study Nigeria(Cranfield University, 2024-02) Ogunsanwo, Babafemi; Longhurst, Philip J.; Huo, DaThe empirical data revealed facts about factors driving foreign direct investment in the Nigerian LNG sector. This research uses the primary data gathered to contribute uniquely to empirical findings and knowledge. Some factors are deemed adequate when attracting foreign direct investment. The sufficient factors identified are political stability having a considerable impact on investor decisions, and long-term investment commitments in the LNG sector. The second significant factor identified is government efficiency, and the last factor is corruption with different components classified into two broad categories: attractors and deterrents. In this context, sufficiency is defined as the condition where FDI is likely to occur when a sufficient amount of the three factors listed are in place. Previous research has failed to understand and explain all three factors adequately. This is a new insight and contribution to knowledge. This study explains how factors driving foreign direct investment in Nigeria's liquefied natural gas sector have an impact. The research utilises the successful Bonny NLNG projects as an example to investigate the reasons behind the failure of the Olokola and Brass LNG projects, which were unable to reach a final investment decision. Distinct empirical analysis and research design show key factors driving foreign direct investment in the Nigerian LNG sector. Foreign direct investment is a type of cross-border investment that occurs when an investor from one country develops a long-term stake in and a considerable degree of control over an enterprise located in another country. Additionally, in green-field investment, foreign direct investment is in the form of a parent company establishing a subsidiary in another country and commencing operations from the ground up. The goal of foreign direct investment is the priority of gaining benefits from the investment, maximising return on investment, and seeking to control assets. It offers capital funding in exchange for an equity stake. LNG projects are capital- intensive, it requires sizable up-front financing. LNG project financing can be difficult due to their long-term nature, high costs, and associated risks. Securing funds from foreign lenders, equity investors, and project sponsors can be herculean, only the major exploration and production companies can achieve it. Thus, the research will focus on factors driving FDI in the LNG sector. Key stakeholders, policymakers, and investors will be interviewed. This thesis compiles feedback from stakeholders to identify the key factors driving foreign direct investment in Nigerian liquefied natural gas. The study presents evidence on the factors driving the inflow of foreign direct investment into the Nigerian LNG sector to policymakers, lawmakers, government executives, investors, community leaders, and financial institutions to test the effectiveness and efficiency of the research. The research design incorporates a mixed-method approach. Data collected through a questionnaire-based survey, semi-structured interviews, and focus group discussions, provide solid insight into the factors driving foreign direct investment in the Nigerian LNG sector. The questionnaire-based survey was used to gather data from 118 respondents. Data was gathered from 12 top gas stakeholders through semi-structured interviews, and an additional 4 executive participants participated in the focus group discussion. The study employs purposive sampling to identify the participants and interviewees. The fundamental value of the research comes from the real-world data it collects and the conclusions by looking at factors driving FDI in the LNG sector. Stakeholder theories were chosen as the theoretical framework for the research, emphasising the study's focus and applying the researcher's terminology to address the research questions. The literature review guided this decision. Nigeria's abundance of natural resources, particularly its substantial natural gas reserves, attracts foreign investors. The Nigerian gas sector presents opportunities for economic development, energy diversification, and environmental sustainability in the future. Nigeria has about nine hundred times more gas assets than the country's oil deposits, and its reputation as an oil producer overshadowed the gas sector's potential, even though the country's gas reserves are greater than oil. Gas asset is a necessary factor, but it is not sufficient enough to attract foreign direct investment.