PhD, EngD and MSc by research theses (SWEE)
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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 Embargo 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 Embargo 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 Embargo 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.Item Open Access Facilitating the predictions of batch and continuous anaerobic digestion processes performance with statistical tools(Cranfield University, 2024-07) Liu, Yanxin; Jiang, Ying; Longhurst, Philip J.; Guo, WeisiAnaerobic digestion (AD) is a promising technology for waste management and renewable energy production. Determining the biomethane potential (BMP) of a material is crucial when considering it as feedstock for the digester. The practical BMP of a material and its degradation kinetics can be derived from the batch BMP test, typically taking at least 30 days, which can be onerous to the industrial operator. Many studies have attempted to predict BMP test results by building regressions between various feedstock physiochemical characteristics and BMP test result. However, these methods primarily predict the ultimate biogas yield of the BMP test and are unable to capture the reaction kinetics. Part I of this study proposed a method to predict the BMP test result of a material, not only the ultimate biogas yield but also the degradation kinetics, which was achieved by discovering a model that describes the biogas production well and then inferring parameters of this model from feedstock’s physiochemical characteristics. The machine learning (ML) model, Decision Tree, was adopted to predict the parameters of the time series model, first-order Autoregressive Model, from the characteristics including total solids, volatile solids, total volatile fatty acid, total ammonia nitrogen, chemical oxygen demand, alkalinity, elemental composition, pH, heavy metals, etc. The DT trained and tested by leave-one-out cross validation with 25 BMP test data had a mean absolute percentage error (MAPE) of 45.63% on the BMP test results, showing unsatisfactory prediction accuracy and unreliable feature importance analysis results. To obtain sufficient data for ML model training and avoid the consistency issues with BMP test data collected from diverse sources, a data augmentation method employing response surface design was proposed. With sufficient data for model training, eXtreme Gradient Boosting (XGBoost) models with three important features determined via feature importance analysis could predict biogas production model parameters with R²values above 0.99 on the test set. Despite the strong regression capabilities of ML models compared to simple statistical model, their explainability remains a challenge. The current popular methods for ML model interpretation focus on feature importance analysis. In this study, Meijei G-functions were used to interpret the predictions of the XGBoost model mathematically to enhance the accessibility and transparency of the black- box ML model to domain experts as a tool for material realistic BMP prediction. The general predictability of the mathematical metamodel was tested using 13 BMP test data sourced from the literature, all within the applicability range of the trained ML model, resulting in a mean absolute error of 38.074 mL CH ₄/g volatile solid added and MAPE of 15.424%. Besides the BMP of a material, operational parameters of the digester are critical to the performance of a continuous AD process. The application of Anaerobic Digestion Model No.1 (ADM1) for continuous AD simulation, which assists in decision-making in the AD industry by predicting digester performance under various operational schemes, is often hindered by its calibration difficulties, especially with limited data. Part II of this study presents a Bayesian inference-based framework to reliably calibrate ADM1 using only initial-stage digester data. A sequence of sensitivity analysis (SA) was applied to identify the most influential kinetic parameters and initial values to be calibrated. SA results revealed that steady-state biogas production was collaboratively influenced by the disintegration rate, hydrolysis rates, and initial concentrations of acetate degraders, cations, and anions. In contrast, Total Ammonia Nitrogen and pH of digestate were predominantly influenced by initial values of cations and anions. These findings challenge the common practice in ADM1 studies of only calibrating kinetic and stoichiometric parameters. Then, using biogas production and digestate data from less than two hydraulic retention times and informative prior distributions determined from domain knowledge, seven the most influential uncertain inputs were calibrated. The calibrated model predicted the steady state performance satisfactorily. The 95% credible intervals of the calibrated model encompassed 66.047% of the 10- day moving average trendline of the daily biogas flow data and all of the steady- state digestate pH and total chemical oxygen demand data.Item Open Access An integrated knowledge transfer framework for enhancing international university-industry collaboration in novel sanitation technology development(Cranfield University, 2023-12) Fox, Harvey; Encinas-Oropesa, Adriana; Lighterness, PaulApproximately 3.5 billion people worldwide lack access to safe sanitation services, a challenge that demands innovative solutions. University-industry collaborations (UICs) are increasingly recognised as a means to develop and commercialise cutting-edge technologies addressing such global issues. However, these partnerships face complexities in transitioning lab-based inventions to market-ready products, especially during the critical stages of technology development and refinement. This thesis presents an integrated knowledge transfer framework for international UICs, focusing on the development and commercial handover of novel sanitation technology. Through a series of interconnected studies, the research explores the micro-level interactions and processes within the execution phase of international UICs. The framework synthesises insights from three key studies: field testing dynamics in cross-cultural settings, which reveals the effectiveness of diverse team structures in different geographical contexts; a novel iterative development process (ERDE: Experimenting, Reviewing, Distributing, Executing), which provides a structured approach to capturing and integrating multi-modal feedback from dispersed partners; and the role of physical and digital boundary objects in technology and knowledge synchronisation across dispersed partners, highlighting the challenges and successes of alignment between university and industry collaborators. Each study contributes unique insights: the field testing research informs practices for geographically dispersed collaborations; the ERDE framework addresses challenges in the technology ‘Valley of Death’ by facilitating decentralised development; and the boundary object study emphasises the need for adaptive communication strategies across cultural and institutional boundaries. By examining a range of critical activities in technology development, this research contributes to both theoretical understanding and practical management of knowledge transfer in international UICs. The integrated frameworks offers a comprehensive approach to navigating the complexities of geographically dispersed innovation processes and facilitating knowledge alignment within international collaborations, particularly for technologies intended for diverse global contexts. This work has implications for academics, practitioners, and policymakers involved in developing and transferring innovative technologies across institutional and international boundaries to achieve far-reaching societal impactItem Open Access Agent-based modelling of crop management(Cranfield University, 2024-07) El-Fartassi, Imane; Waine, Toby W.; Milne, Alice E.; El-Alami, Rafiq; Corstanje, Ronald; Metcalfe, Helen; Alonso-Chavez, VasthiThis study aims to explore the benefits of integrating Agent-Based Models (ABMs) of farmer behaviour with biophysical models to describe and understand the complex agroecological systems that influence decision-making in arid and semi-arid regions. Through a mixed-methods approach combining surveys, interviews, and ABM, the research provides insights into the complex dynamics shaping farmer behaviour and evaluates the potential impacts of various management strategies on agricultural sustainability. Initial online surveys across diverse agro-climatic zones in Morocco revealed that farmer decisions are influenced by environmental pressures, crop characteristics, and water availability. Follow-up in-depth interviews in the Al Haouz Basin highlighted institutional barriers like land tenure insecurity and bureaucratic processes as key constraints to adopting sustainable practices. The study integrates empirical data with Structural Equation Modelling and the Theory of Planned Behaviour to parameterize an ABM. This coupled behavioural-biophysical simulation captures feedback loops between environmental conditions and human decisions. Model simulations revealed potential unintended consequences of policies aimed at increasing productivity, such as increased soil salinization and land abandonment resulting from expanded groundwater access. Key contributions include advancing the understanding of temporal adaptation dynamics in agricultural systems under climate change and developing a novel methodological framework integrating qualitative and quantitative approaches for studying complex socio- ecological systems. By bridging social and natural sciences, this research establishes a comprehensive framework for addressing agricultural sustainability challenges in water-scarce regions.Item Open Access Technical and practical innovations to reduce soil and water losses by improving soil physical properties(Cranfield University, 2024-06) Bahddou, Sophia; Otten, Wilfred; Rickson, R. JaneSoil erosion is a significant environmental challenge that impacts agricultural productivity, environmental sustainability, and food security. The aim of this research is to better understand the processes of soil erosion by water and wind under different tillage and agronomic measures, with a view to reduce soil and water losses. The research is divided into three main studies. The first study examines the effects of soil surface roughness (SSR) orientation and magnitude on runoff, infiltration, and soil erosion under simulated rainfall conditions. Treatments included up- and downslope, across-slope, random SSR, and a smooth surface. The second study explores the combined effects of wind and rainfall on soil erosion using a novel system comprising rainfall and wind simulators. The study evaluates the role of wind-driven rain (WDR) with varying wind velocities on surface runoff, infiltration, and soil loss, comparing smooth and rough soil surfaces. The third study assesses the influence of different wheat lines (wild type vs dwarf), water regimes (dry vs well-watered), and sowing densities on plant traits, soil properties and predicted erosion rates. The outcome of this research indicates that i) random SSR significantly increases runoff and soil loss, while across-slope SSR does not consistently reduce erosion compared to up- and downslope oriented SSR, ii) WDR significantly accelerates runoff generation and increases soil loss compared to windless rain, with higher wind velocities magnifying these effects, iii) initial SSR patterns change during rainfall events, and WDR exacerbates these changes in SSR, iv) dwarf wheat, higher sowing density and well-watered conditions significantly reduce erosion rates through improved aboveground and belowground plant traits and soil properties, particularly at the later stage of plant growth. In conclusion, this research highlights the importance of considering SSR, wind effects, and plant traits in soil erosion studies to develop effective soil conservation strategies and enhance agricultural sustainability.Item Embargo Dry spectral diagnostic tools and methods for precise fertilizer application(Cranfield University, 2024-03) Asrat, Tadesse Gashaw; Sakrabani, Ruben; Corstanje, Ronald; Haefele, Stephan M.; Kebede, FassilThis study explores the potential of soil spectroscopy to enhance fertilizer decision-making by providing cost-effective, portable instruments for farm-level soil property prediction. The study focused on assessing the performance of various spectrometers, including low-cost near-infrared (NIR) devices, compared to mid-infrared (MIR) bench-top instruments, using a case study on maize productivity in East Africa and soil data from Morocco’s semi-arid rainfed wheat- growing regions. The overall aim was to determine whether these spectroscopic methods could generate reliable predictions of key soil properties for nitrogen, phosphorus and potassium fertilizer recommendations. The results indicate that NIR spectroscopy, despite being the most affordable and portable option, demonstrated sufficient accuracy for predicting key soil properties such as soil pH, organic carbon, and exchangeable potassium, with concordance correlation coefficients (CCCs) ranging from 0.77 to 0.96. However, the prediction of phosphorus (Olsen P) showed considerable uncertainty, particularly for values above 15 mg P kg⁻¹, where deviations from measured values increased. Comparatively, the MIR spectrometer showed better prediction accuracy for phosphorus, though its higher cost and complexity limit its applicability in resource-limited settings. The NIR spectrometer, with a prediction accuracy suitable for nitrogen fertilization (deviation between -8 to 8 kg N ha⁻¹), emerged as a promising tool for cost-effective and rapid nutrient recommendations in developing countries. Furthermore, this research demonstrated that integrating spectroscopic data into crop models like QUEFTS for nutrient management enhances decision-making by considering both soil supply and crop response to nutrients. The findings underscore the necessity of developing region-specific calibration models to improve prediction reliability, with spatial autocorrelation analysis of soil spectra suggesting that proper calibration sample selection can improve prediction performance, especially for phosphorus and other key properties. Ultimately, this thesis contributes to the ongoing development of soil spectral libraries and highlights the potential of low-cost, field-friendly spectrometers to improve nutrient management and crop productivity in regions with limited soil data.Item Open Access Chlorate occurrence in drinking water(Cranfield University, 2023-08) Briones Carles, Pablo; Goslan, Emma; Jarvis, PeterThe use of chlorine for disinfection of potable water has been the major public health advancement in the last century. Sodium hypochlorite is currently used worldwide for potable water disinfection. Arising from sodium hypochlorite solutions, chlorate forms as the sodium hypochlorite ages. Chlorate has been recently regulated in the EU directive and is catalogued as a compound of concern for the Drinking Water Inspectorate. The WHO recommended in 2015 a guideline level of 0.7mg/L, and chlorate is currently set at level of 0.25 mg/L in potable water supplies. As chlorate was previously a guidance, and not extensively monitored, this presents a regulatory challenge for most water companies to adopt. From a large historical data set, from 2014 to 2020, it was extrapolated that chlorate monthly running average values were expectedly higher during the warmer season, likely explained by the increased chlorine demand during warmer months, but far from the current regulation limit for well-resourced sites. A questionnaire was completed in cooperation with operators and process scientist on site. The interviews were completed across various WTW in Scotland. The aim was to demonstrate the varying disinfection practices and extract conclusions on the hypothetical chlorate levels arising during the dosing and storage of sodium hypochlorite. The selection of sites provided a good overview on the particularities of the disinfection stage, from small WTW, where the sodium hypochlorite gets diluted on site, to large WTW with bulk storage of 15% sodium hypochlorite. Sites with a varied risk of chlorate occurrence were also included such as on-site electro-chlorination and chlorine gas disinfection. It was concluded that there are correct measures in place during the operation and maintenance of the disinfection stage, but chlorate levels during storage are not centrally reported. The questionnaire has shown some sites where the solutions of sodium hypochlorite were potentially exposed to warm temperatures and extended periods of storage. It is likely that high room temperature is the underpinning cause leading to sudden chlorate increase in combination with high chlorine demands during the warmer months. This emphasised the need for longitudinal studies on the degradation of hypochlorite solutions during storage. It has been identified that a robust supply chain providing fresh hypochlorite deliveries could be a major implementation aiming to tackle high chlorate levels, particularly for remote and isolated potable water treatment works. The need for an accurate determination of chlorine demand on site remains of crucial relevance aiming to adjust disinfectant capability across varying treatment processes. The importance of regular procurement of hypochlorite solutions and the need for contingency was emphasised by the operators in order to avoid high seasonal chlorate levels. As a part of the experimental plan, the aim was to analyse the long-term stability of sodium hypochlorite during storage with a focus on the impact of disinfectant concentration on chlorate formation. The decay rates for sodium hypochlorite solutions and chlorate formation have been determined at varying initial concentrations using incubation experiments in the laboratory. It was determined the application of consecutive refilling during sodium hypochlorite storage with remaining old solutions of hypochlorite. Via bench scale kinetic experiments, it was determined whether the use of a 10% free chlorine concentration of sodium hypochlorite is less prone to promote further chlorate formation compared to the currently used 15% hypochlorite solutions. It has been found the relative chlorate to free chlorine content remains high even after the adoption of lower concentration hypochlorite solutions. This has implications for sites currently using dilution of hypochlorite and high chlorine demands. Lower initial concentrations of sodium hypochlorite also presented more stability and remaining disinfectant capacity during the bench scale studies. It is concluded that extensive monitoring and control will be required in order to achieve tighter chlorate standards. The relative chlorate to free chlorine ratio (mg Chlorate/ mg of free chlorine) has been highlighted as a concern resulting from high values in diluted solutions of hypochlorite and on-site electro chlorination systems. Further mitigation strategies have been summarised discussing the risk factors for future chlorate occurrences, implementations aiming to tackle chlorate occurrence pre-emptively, and limit exceedances of the EU directive, now adopted in Scotland. Overall, the thesis provided a better understanding on the drivers prompting chlorate levels derived from sodium hypochlorite disinfection, a list of comprehensive evidence-based interventions at water treatment facilities and highlighted best management practices.Item Open Access Understanding the impacts of septicity on wastewater treatment(Cranfield University, 2022-12) Mendizabal Bengoetxea, Julen; Soares, Ana; Bajón Fernández, YadiraWastewater septicity develops during wastewater conveyance through the sewerage network to the wastewater treatment plant (WWTP). The problems related to septicity have been mainly researched in sewerage networks and are almost exclusively related to hydrogen sulphide, such as concrete corrosion and odour nuisance. The aim of this work is to better understand the mechanisms governing septicity in wastewater and mitigate the impacts both in sewers and wastewater treatment plants. For doing so, a septicity measure that captures the key indicators was developed, which include sulphide, oxidation reduction potential (ORP), pH, soluble COD and ammonia. Furthermore, the impacts of septicity on a conventional wastewater treatment plant consisting of a primary settler, activated sludge plant and secondary settler were tested. Septic wastewater with 6.4 mg/L of sulphide was found to impact activated sludge flocs, with significant proliferation of filamentous bacteria, resulting also in a reduced COD removal by 55% and nitrification by 44%. Furthermore, sludge bulking in the secondary settler and consequent biomass washout was observed. Additionally, the impact on chemical phosphorus removal (CPR) was tested and septic wastewater was found to reduce the effectiveness of CPR starting at a 0.35 S:Fe molar ratio and only 10% phosphorus removal efficiency was measured at a 1.4 S:Fe molar ratio. Finally, a novel dissolved sulphide sensor was trialled to monitor sulphide at the inlet chamber of a WWTP. The data collected allowed the assessment of the efficiency of nitrate dosing at a rising main. Furthermore, it allowed to build up a data-driven sulphide prediction model utilising readily available data. Overall, the thesis provided the starting bricks for the development of a septicity management framework and highlighted that optimised nitrate dosing at the study rising main utilising the dissolved sulphide data was the most economic septicity management option.Item Open Access Numerical study of coupling between multiphase flow-induced vibrations (mfiv) and vortex-induced vibrations (viv) of slender flexible pipes.(Cranfield University, 2022-08) Bakur, Aminu Ishaq; Verdin, Patrick G.The dynamic response of a riser subjected to external and internal flow-induced vibration is studied numerically through the coupling of a computational fluid dynamics (CFD) solver and a finite element (FE) solver. This thesis describes the vortex-induced vibration (VIV) of elastically mounted rigid cylinders, empty flexible risers and fluid conveying risers using three-dimensional (3D) numerical simulations. The dynamic characteristics of the riser, such as inline (IL) and crossflow (CF) displacements and vibrating frequencies, are provided and discussed. The effects of fluid flow, including velocity magnitude and profile, on the dynamic response are also investigated. A 1 degree of freedom (1DOF) VIV of an elastic cylinder is studied first using 2D and 3D numerical models. The effects of mass and damping ratio on the amplitude of vibration of the cylinder over a reduced velocity range are analysed. Results show a good agreement with published experimental studies. It is demonstrated that increasing the mass and damping ratio reduces the maximum vibration amplitude of the cylinder. A 3D numerical study is then carried out to investigate the effects of velocity magnitude, velocity profile, the elastic modulus of the riser, orientation, and aspect ratio. The study establishes that the IL displacement, CF vibration mode, and frequencies increase with the flow velocity, aspect ratio and reduction of elastic modulus. In addition, the VIV of the riser transporting single-phase internal flow is presented. The numerical study describes the effects of internal flow velocity magnitude on the dynamic response of the riser. It is shown that the internal flow velocity magnitude affects the vibration mode of the riser. Finally, the effects of internal air-water volume fractions on the dynamic response of a riser transporting a two-phase flow are examined in detail. The influence of gas fraction on a pipe with no external flow, on a jumper pipe with no external flow and on a fluid conveying pipe exposed to external flow is investigated. The numerical results show that a variation of the air volume fraction slightly affects the dynamic characteristics of the riser.Item Open Access Annual performance of a novel configuration for an integrated solar combined cycle utilising municipal solid waste(Cranfield University, 2022-08) Al Ramadhn, Ali; Patchigolla, Kumar; Sansom, Christopher L.Climate change has been a major incentive for the global power generation industry to move towards the implementation of sustainable renewable energy technologies in order to reduce the emissions of greenhouse gases, especially carbon dioxide emissions. Concentrated solar power (CSP) has established itself as one of the common renewable energy technologies for large scale power generation. A further attractive feature of this solar technology is its hybrid operation in the form of integrated solar combined cycle (ISCC) which facilitates control and ensures that the power plant is available to meet demand whenever it occurs. ISCC commonly uses natural gas to operate the combined cycle but this CSP hybrid system also has the potential to limit its use of this fossil fuel with a more environmentally friendly fuel, namely the produced syngas from solid feedstock gasification which can be accomplished by further integration of the gasification reactor with ISCC. The organic fraction of municipal solid waste (MSW) was selected for this application, both to replace natural gas as well as for its value as a waste management method. In the present work, the thesis studies and contrasts four configurations of ISCC based on two factors, the type of fuel and the level of solar thermal contribution. One configuration represents the conventional form by using natural gas (ISCC 1) while another configuration uses municipal solid waste (ISCC 2) and in both cases, the solar field generates high -pressure saturated steam using parabolic trough with thermal oil. The last two configurations are related to the research proposal for ISCC which states that this hybrid system runs on municipal solid waste and utilises enhanced solar thermal contribution. This enhanced thermal power from the solar field is used to generate high-pressure superheated steam using parabolic trough with molten salt (ISCC 3) or solar power tower with molten salt (ISCC 4). In all cases, the fuel runs the combined cycle, and the solar field operates in parallel to provide extra steam for the hybrid system. However, the use of gasification in ISCC 2, ISCC 3 and ISCC 4 generates extra steam for the hybrid system through syngas cooling system which is attached to the low-pressure section of the steam turbine cycle. In this work, models are developed to investigate the differences between the various configurations in terms of technical and economic performances using Spain and Saudi Arabia as case studies. The results indicate that the use of a solar power tower in the proposed concept, ISCC 4, gave the highest electricity production at 646 GWh with a solar share of 12.80% under Spanish weather and 644 GWh with a solar share of 15.24% under the Saudi Arabian weather. Furthermore, ISCC 4 offered the lowest levelised cost of electricity at 28.45 $/MWh and 28.62 $/MWh for Saudi Arabia and Spain, respectively, when the novel concept (ISCC 3 and ISCC 4) is compared to the conventional concept (ISCC 1). The main thesis contribution was to reveal the impact of coupling the ISCC using enhanced solar thermal power with municipal solid waste gasification and its potential as Waste-to-Energy plant. Based on the study presented outcomes, The proposed concept of integrated solar combined cycle (ISCC 3 and ISCC 4) demonstrated its practicality against conventional concept (ISCC 1) due to achieving higher performance outcomes with lower costs. The outcomes of ISCC 2 in both countries presented slightly lower LCOE values than the novel concept indicating that the replacement of fuel alone did not show a significant impact against the novel concept in terms electricity production cost.Item Open Access Calcium looping for pulp and paper industry decarbonisation and hydrogen production from biomass and waste(Cranfield University, 2022-08) Da Silva Santos, Monica Patricia; Hanak, Dawid P.; Manovic, VasilijeGlobal CO₂ emissions from fossil fuels have been rising for more than a century. Nevertheless, to meet the ambitious targets set by the Paris Agreement, greenhouse gas emissions must be substantially reduced. The improvement of energy efficiency, implementation of carbon capture and reduction of fossil fuel dependency can play an important role. Of the CO₂ capture technologies, amine scrubbing is the most mature technology; however, calcium looping has shown to be a promising one. Thus, this research aimed to assess the techno-economic feasibility of calcium lopping as a carbon capture technology for combined heat, power and hydrogen production from biomass and/or waste. First, a new concept for the conversion of the pulp and paper industry to carbon-negative that relies on the inherent CO₂ capture capability of the Kraft process was proposed. This concept has shown that a pulp and paper plant can turn from importer to electricity exporter with the cost of CO₂ avoided of 39.0 €/tсо₂ . Second, in the pulp and paper industry, two carbon capture and storage routes were compared, calcium looping retrofitted to the pulp and paper plant and calcium looping coupled with black liquor gasification. The latter was assessed for H₂ production and for electricity generation with a gas turbine combined cycle or solid-oxide fuel cell. The last alternative has shown that the pulp and paper plant can also become a net electricity export asset at the expense of the cost of CO₂ avoided, 50.8 €/tсо₂ . On the contrary, the alternative for H₂ production presented the highest energy penalty but the lowest cost of CO₂ avoided (48.8 €/tсо₂ ). Third, the feasibility of calcium looping for H₂ production and in-situ CO₂ capture was assessed for waste-to-energy conversion in a greenfield scenario. However, this resulted in a significantly higher levelised cost of hydrogen (5.0 €/kgн₂ ) compared to that estimated for conventional gasification (2.7 €/kgн₂ ). Although calcium looping is more cost-efficient for carbon capture in a retrofitted scenario, this technology can become a competitive technology for hydrogen production in a greenfield scenario.