http://localhost/xmlui/handle/123456789/1278 2026-08-06T14:09:01Z 2026-08-06T14:09:01Z Mugai, Catherine Wambui http://localhost/xmlui/handle/123456789/7086 2026-08-06T11:11:31Z 2026-08-06T00:00:00Z

Prediction of Subgrade California Bearing Ratio using Falling Weight Deflectometer for Pavement Evaluation in Kenya Mugai, Catherine Wambui Subgrade CBR is a very important parameter which gives an indication of the strength of the pavement’s foundation. Kenya’s Road Design Manual (Part 3) classifies the subgrade as S1 to S6 depending on their CBR range. The objective of this study was to predict subgrade CBR using FWD for pavement evaluation. A sample of 18 road sections were selected purposively for the study due to availability of data. The data required was FWD data, trench logs, laboratory results for the samples collected from the trenches and construction data. The FWD data was collected at intervals of about 100m using Primax FWD equipment. Trial pits were dug at intervals of about 5 km and the samples collected were tested in the laboratory to establish the soil properties. An average of three FWD readings were obtained at the exact chainage where the trial pits were dug. The materials were first characterized and classified using Unified Classification System (UCS). Lean clay (CL) and Elastic Silt (MH) were found to be the predominant soil classes. The average values of PI, OMC and MDD per road section were found to range from 7 to 23%, 12 to 27% and 1250 to 1821 kg/m3 respectively. The 4th geophone (D4), which was positioned at 600mm from the centre of the loading plate, was selected for developing the model based on the deflection bowls and surface modulus graphs. 11 models were developed by considering varying independent variables like deflections, contact pressure, air temperature, MDD, OMC, PI and Soil Class the dependent variables were the predicted CBR values. The data for all the road sections was split randomly into two; 80% was used to train the models and 20% to test the models. The models developed were Linear Regression models (LR) and machine learning models which were Random Forest (RF) and Artificial Neural Networks (ANN). Three models had the highest R2 score of 55 to 61% which means they explained the variability of lab CBR and were the best models. The same models had the lowest RMSE therefore making them the best models for predicting CBR. The CBR values predicted were correlated with the CBR values from the lab and found to have Pearson’s correlation coefficient of 0.81 to 0.84. The two machine learning models require specialized software like python to make predictions. The LR model developed was CBR = 5.2215 + (-0.0036 x D4) + (-0.0144 x Pc) + (-0.2522 x Tair) + (0.0233 x MDD) + (-0.3732 x OMC). The deflections, contact pressure and air temperature are values obtained from the FWD data. The study recommended that the developed predictive models can be subjected to additional validation by using them to predict CBR from other road sections in future pavement evaluations. MSc in Civil Engineering (Transportation Engineering)

2026-08-06T00:00:00Z Ngotho, Elias Waweru http://localhost/xmlui/handle/123456789/7083 2026-08-06T10:15:50Z 2026-08-06T00:00:00Z

Evaluation of the Quality Changes of Kales and Tomatoes Stored in an Improved Zero Energy Cooler Ngotho, Elias Waweru The world is faced with myriad challenges like climate change and ever-increasing population making the achievement of global food security a challenge. Although highly perishable, tomatoes and kales are popular food commodities, farmers must sell the commodities soon after harvest for fear of deterioration. For longer storage, the two crops require an environment with low temperature and high relative humidity. Cooling systems such as refrigeration are not accessible to most small-scale farmers because they require connection to the grid. In this study, a zero-energy cooler was developed and evaluated for the storage of ripe tomatoes and mature kales. The system adopted the principle of evaporative cooling and comprised of walls filled with pumice coupled with a pond filled with water on the roof and below the storage space. A full factorial experimental design was employed. This design allowed water to drip from an elevated tank through the pumice walls and drain into the reservoir below the storage space before recirculation using a solar powered pump. The tomatoes (cultivar Ann F1) were harvested at the turning stage and kales (cultivar thousand headed) were harvest at mature stage. At different times, the two crops were stored in the cooler (treatment) and in the ambient condition (control). The relative humidity in the cooler was significantly higher than in the ambient environment while the temperature in the cooler was generally lower than the temperature at the ambient environment. Data was analysed using ANOVA at p≤0.05. For tomatoes, quality attributes namely firmness, colour, pH, total soluble solids (TSS) and shelf life were evaluated on a seven-day interval for 28 days. For kales the same quality attributes were evaluated on daily basis for ten days. For tomatoes, results showed a significant (p≤0.05) difference for pH, TSS, and firmness between tomatoes stored in the treatment and control. However, there was no significant (p>0.05) difference in the colour (hue angle) for the fruits under the treatment and control. Compared to the control, the developed solar powered storage system increased the shelf life of tomatoes from 14 days to 28 days. On the other hand, kales results showed a significant (p≤0.05) difference for a* colour parameter, and in b* colour parameter. However, comparing the quality parameters between kales stored in the cooler and in the ambient environment, there was no significant (p>0.05) difference between quality parameters; ∆E, TSS and pH. The cooler improved the shelf life of kales from 5 days (control) to 9 days (cooler). The results from this study indicate that pumice padded zero energy evaporative cooler preserves the quality of perishable tomatoes. However, the notable effect of the cooler on kales was maintenance of green colour (a*) and prevention of yellowing (b*). The Cost Benefit Analysis of the cooler under tomatoes was 10.6 and 4.21 for storage of tomatoes and kales respectively. The pay back periods for the cooler under kales and tomatoes were 7.2 Months and 1.9 months respectively. The findings of this study shows that the developed pumice-padded/roof pond zero-energy cooler provides an accessible solution for off grid and resources constrained small-scale farmers. By extending the shelf life of kales and tomatoes without reliance on electricity, the cooler directly addresses the major cause of post harvest losses in fruits and vegetables. The resultant reduction in spoilage will not only minimize economic losses but will also allow farmers greater flexibility in marketing their produce and further enabling them to avoid distress sales and hence access better prices. From a food security angle, the ability to preserve vegetables for a longer period contributes to enhanced availability and stability of nutritious foods in the local markets. The system under study supports eco-friendly agriculture by utilizing zero-energy xviii evaporative, thereby reducing traditional dependence on fossil fuel-based refrigeration and hence lowering negative environmental impact. The low-cost design of the cooler based on use of locally available materials such as pumice, proves its adaptability and scalability across different regions facing post-harvest challenges. Overall, the technology demonstrates a sustainable and economically viable innovation with a high potentiality of wide utilization among smallholder farmers, rural communities and cooperatives. This innovation will contribute to enhancement of agricultural systems, reduced post-harvest losses and improved livelihoods. The zero-energy cooler is recommended for use with other crops besides kales and tomatoes. Key words: Zero energy cooler, Combined cooling mode, Post harvest losses, Kales, Tomatoes, solar powered cooling system MSc in Agricultural Processing Engineering

2026-08-06T00:00:00Z Jelimo, Phanice http://localhost/xmlui/handle/123456789/7073 2026-08-04T08:54:48Z 2026-08-04T00:00:00Z

Spatial Analysis and Quantification of Microplastics in the Nairobi Rivers and Wastewater Treatment Plants Jelimo, Phanice Microplastics have raised significant concerns due to their potential threats to human health and aquatic species. The accumulation of microplastics in aquatic environments has become increasingly alarming in recent years. While microplastics have been widely detected in various water bodies over the past few decades, studies in many developing countries, including those in Africa, remain limited. This study aimed to determine the abundance and composition of microplastic particles in selected rivers and in two wastewater treatment plants in Nairobi, Kenya. Water samples were collected from both the rivers and the wastewater treatment plants, using grab sampling technique. The microplastic particles, ranging in size from 4.75 mm to 300 µm, were categorised through visual identification with a dissecting microscope and characterised using Fourier Transform Infrared Spectroscopy (FTIR). Pearson Product-Moment Correlation analysis was then employed to investigate the relationship between microplastic concentration and land use. The abundance of microplastics in the rivers ranged from 0.22±0.026 to 0.917±0.061 particles/litre. Fibres (51.15%) and white particles (40.08%) were the most common types of microplastics detected, with polyethylene (PE) and polystyrene (PS) being the predominant polymers. Higher concentrations were noted near industrial, commercial, and residential areas, particularly in informal settlements along the rivers. A positive correlation was observed between microplastic abundance and built-up areas, while a negative correlation was found with forested areas and wetlands. In the studied wastewater treatment plants, the average abundance of microplastics in the influent at Ruai was 9.99 ± 0.50 particles per litre, and 4.7 ± 0.28 particles per litre in Kariobangi. This abundance significantly decreased in the final effluent to 1.08 ± 0.18 particles/litre in Ruai and 1.03 ± 0.08 particles/litre in Kariobangi, corresponding to removal efficiencies of 89 ± 1.91% and 78 ± 3.16%, respectively. Despite these reductions, the wastewater treatment plants were releasing approximately 123.1 ± 20 million and 10.3 ± 0.91 million microplastics per day into the receiving river. These findings highlight the influence of anthropogenic activities and wastewater treatment plants on the abundance of microplastics in the Nairobi River Basin. This study represents one of the first detailed assessments of microplastic distribution in Nairobi’s freshwater systems and provides critical baseline data on microplastic pollution in urban rivers of Sub-Saharan Africa. It underscores the urgent need for improved wastewater management and pollution control strategies, as the presence of microplastics poses a serious ecological risk and potential implications for human health. MSc in Soil and Water Engineering

2026-08-04T00:00:00Z Mutunga, Jackline Mwende http://localhost/xmlui/handle/123456789/7043 2026-05-28T12:30:55Z 2026-05-28T00:00:00Z

Experimental Study and Numerical Optimization of a Thermal Swing Adsorber for Biogas Upgrading Mutunga, Jackline Mwende Biogas is a renewable energy source that can be adopted as a reliable and sustainable alternative when upgraded. The composition of carbon dioxide in biogas of up to 45% reduces its energy density. Thermal swing adsorption has proven to be a promising technology in the biogas upgrading process, due to its ease of integration with renewable electricity sources and its suitability for water-deficient areas. The experimental study of the biogas upgrading process has been complicated by the dynamic nature of the process and the high sensitivity to operating conditions, such as pressure, temperature, and gas flow rate. To understand the complex interaction between the process parameters, numerical simulation was utilised. There are, however, limited numerical studies evaluating multi-objective optimization of these process parameters. This study assessed the performance of thermal swing adsorption technology, utilising resistive heating, in upgrading biogas produced from the anaerobic digestion of organic waste. Commercial coconut shell-based activated carbon was used as an adsorbent in the experimental cyclic process to capture carbon dioxide. Aspen Adsorption software was used to develop a thermal swing adsorption numerical model. The simulation model was validated using experimental data obtained from a laboratory-scale setup. A good agreement was observed between the simulation and experimental carbon dioxide breakthrough times, with a mean absolute percentage error of 2%. Dynamic adsorption tests were conducted to evaluate the system performance in carbon dioxide capture. The maximum resistive heating regeneration temperature of 60℃ resulted in a peak carbon dioxide concentration of 39% in the waste gas, an energy requirement of 0.1538 kWh per cycle, and an energy efficiency of 87%. This was a good trade-off between adsorbent recovery for subsequent biogas upgrading cycles and system energy efficiency. In the second phase of the study, the adsorbent particle radius, regeneration temperature, and purge-to-feed flow rate ratio were investigated to determine the system's sensitivity. The adsorption and desorption processes were based on methane and carbon dioxide adsorption isotherms, which were fitted to the Langmuir-Freundlich model. The model described the adsorption behaviour on a heterogeneous adsorbent surface, where adsorption sites had different affinities and capacities. Adsorbent particle radius, steam regeneration temperature, and purge-to-feed flow rate ratio range of 1 to 9 mm, 77 to 227℃, and 0.1 to 0.7, respectively, were adopted. Multi-objective numerical optimization of the selected variables was carried out using the Box-Behnken design response surface methodology. The target output responses maximized were the methane purity and recovery. From the analysis of variance, the purge-to-feed flow rate ratio made the highest contribution to both methane purity and recovery, of 92.37% and 99.90%, respectively. While the particle radius had a negligible influence on the methane recovery model, its contribution to the methane purity was significant. The optimal values for maximum methane purity and recovery obtained were 82.12% and 37.21%, respectively, achieved at a particle radius of 9 mm, steam regenerating temperature of 227℃, and a purge-to-feed flow rate ratio of 0.4152. This study offers valuable insights into the design of a thermal swing adsorption biogas upgrading model, as well as the impact of various variables and configurations on the process. The developed model provides practical guidelines for selecting optimal biogas upgrading process parameters to maximize both methane purity and recovery. Doctor of Philosophy in Mechanical Engineering

2026-05-28T00:00:00Z