Opio, Chris

This research explores estimating off-shore oily waste, considering waste-waste compatibility due to the heterogeneous nature of oily waste. Firstly, hyperparameters for Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Improved Random Forest (IRF) models are optimized to develop a comprehensive oily waste estimation model incorporating liquid, solid, and total waste types. The results show that IRF is the most accurate model, with the lowest error indices and a higher correlation coefficient compared to ANN and SVR. This study then takes a step further to propose a waste allocation framework, which is tested using information on the Bella Bella oil spill incident in British Columbia. Incorporating treatment and receiving facilities' details, such as their location and capacity, the framework distinguishes all possible waste pathways for handling the waste from source to landfill. Genetic Algorithm (GA) is introduced to optimize waste transfer processes and successfully minimize transportation costs. The results show that the model can find the most optimized path to reduce transportation costs. The model's high customization, adaptability, and capacity to consider multiple nodes make it suitable for complex waste transfer networks, demonstrating its practicality in emergency situations. Efficiently allocating resources and ensuring cost-effective waste transportation while considering facility capacities and waste compatibility, the study holds practical implications for waste management practitioners, environmental authorities, and response teams.

Managing the waste generated after response operations is the most challenging part of an offshore oil spill. A waste estimation is required before deciding on the transportation, treatment, and disposal of each type of oil spill waste. So, firstly, this thesis developed a system dynamics model to estimate the quantity of each type of oily waste generated after oil spill response operations, considering different aspects (e.g., weather conditions, the spilled oil volume and characteristics, response time and equipment). The results of the model for an actual oil spill in BC, Canada (2016), as the case study, showed a 86% average accuracy. Sensitivity analysis of the case study illustrated that a five-hour decrease in the response arrival time could increase the oil recovery by 26%. Moreover, sensitivity analysis showed a possibility of 45% overuse of sorbents for the case study. Response surface methodology (RSM) also was conducted, and the significant interaction effects between sea temperature and response arrival time on recovered oil and between sorbent boom weight and sorbent booms usage rate on solid waste were demonstrated. In addition to the oil spill response waste (OSRW) quantity estimation model, the study developed a scenariobased decision-making framework as the second objective to provide the most monetary beneficial strategies to deal with each collected OSRW under different scenarios of impact factors (e.g., waste quantity, waste quality, location, capacity, and availability of treatment and disposal facilities). An optimization model with an objective of minimizing net costs was developed to evaluate all scenarios using hypothetical and actual data. Results were categorized to develop the decisionmaking framework. It was illustrated that oil processing is the best option for managing liquid oily waste from spilled refined oil. For liquid oily waste from crude spilled oil, the oil refinery is the best option if the quantity is above a defined limit in this study. For solid oily waste management, pyrolysis is the most appropriate destination. The optimum solutions and sensitivity analysis for the actual data of a case study validated the results.

Shortage of clean drinking water is a serious problem faced by the world at present times, with water borne diseases claiming 5 million deaths globally each year. Many methods are available to treat contaminated drinking water; however, cultural, economic, and social factors often impair implementation of these methods, particularly in developing countries. Moringa and ginger root powders appear to offer a promising alternative to treat contaminated drinking water. This study examines the nutrient composition of Moringa and ginger roots and determine their antibacterial efficacy against Escherichia coli (E. coli). After growing Moringa and ginger plants in a greenhouse for seven months and three years respectively, their roots were harvested, dried, powdered and analysed for their chemical composition using ICP-MS and Elemental analysis. The most abundant metal found in both the root powders was potassium, while calcium, magnesium, sulphur, sodium, and phosphorus were other elements present in high amounts. However, the concentration of these metals in Moringa and ginger root powders varied significantly. The abundance of essential elements in the two root powders justifies their use as a point-of-use water treatment method. For both Moringa and ginger root powders, 1400 mg/L concentration was determined to be the most effective concentration as it reduced E. coli in contaminated water by 88.66% and 62.63% respectively. The combination of the two root powders appeared to have a synergistic effect on E. coli as Moringa and ginger root powders combined in 1:1 ratio reduced bacterial counts by 94.78% when added to the contaminated water at 2000 mg/L.

Moringa oleifera is a tropical tree with nutritious, anti-inflammatory, and antimicrobial properties. Moringa seeds have been studied for their ability to purify water, however roots have not. This study identified the nutrient composition of Moringa roots grown in a greenhouse, and tested whether the roots improved water quality. Moringa roots were dried, powdered and added to contaminated water to test their impact on E. coli, pH, turbidity, and electrical conductivity. The chemical composition of Moringa roots were measured using ICP-MS. The five main elements observed were potassium, phosphorus, magnesium, sodium and calcium. None of the elements extracted were of health concern for drinking water quality. Electrical conductivity and pH remained within drinking water quality guidelines. Moringa root powder resulted in a significant increase in turbidity. Moringa concentration of 600 mg/L removed up to 87% of E. coli in water. Moringa root powder shows some potential as a point-of-use water treatment.

The boreal forest ecosystems have been changing due to varying levels of anthropogenic land use processes such as logging, oil and gas activities, and agriculture. However, the cumulative impacts of these processes are likely to lead to a lasting degradation of the boreal forest ecosystem; and thus, contributing to environmental change. In this study, methods from Landscape Ecology, GIS, and remote sensing were used to process Landsat images and spatial data for shale gas infrastructure. These datasets and methods were used for measuring and assessing the forest change pattern in a study area in northeastern British Columbia (BC). The results of the study show that gross loss (5.98%) of coniferous forest cover in the timber harvest land base (THLB) is higher than the rate of gross loss (3.22%) of the coniferous forest cover in the area outside the THLB. However, the rate of net loss in coniferous forest cover is smaller in the THLB than that of outside the THLB (net loss THLB=0.6%; net loss non-THLB=1.7%). These dynamics in forest cover suggest that it is more likely for forest cover to regenerate much faster in the THLB than outside the THLB. The quantity of forest cover loss (0.163%) from shale oil and gas well pads development is more than the amount of forest loss from shale oil and gas access roads (0.017%) and pipeline development (0.057%). A higher amount of forest fragmentation is associated with periods and locations that have a high amount of anthropogenic-induced land classes in the landscape. These results of the study could serve as the information for modelling land change and fragmentation in the future. The finding from this study could assist land managers in the allocation of land uses across space as well as the formulation of effective and efficient policy frameworks and management initiatives.

"Access to clean and safe drinking water is a matter of life and death in rural Uganda. Many villagers do not have access to this basic resource and are forced to consume water unfit for human consumption. As a result, many suffer from serious health problems, including water-borne diseases. The provision of clean and safe drinking water in rural Uganda is part of the United Nations Millennium Development Goals and also Uganda’s Water Management Policy. In this context, this study examines the biological, and physical characteristics of drinking water collected from open, shallow areas (i.e., open wells) and that from drilled underground wells installed by a non-governmental organization, NUDF (Northern Uganda Development Foundation). Water collection was conducted in 2008 from Kamdini Parish, Oyam District. Three NUDF wells were randomly selected for sampling as were three random open surface sources that villages have been using (or currently use) as drinking water in the same parish. Field sampling and laboratory analyses were performed according to well established protocols. In general, water samples collected from the NUDF wells had good bacteriological and satisfactory physical characteristics commensurate with Uganda potable water standards, and hence may be used for domestic consumption. The open (old) surface wells on the other hand, showed less satisfactory characteristics and therefore, require water treatment (e.g. settlement or simple filtration and disinfection) prior to direct domestic consumption."