1,721,042 research outputs found
Evaluating low impact developments (LIDs) beyond storm water management : a framework for the public health, environmental performance, and cost analysis
No full textLow Impact Developments (LIDs) are becoming increasingly popular for their benefits to sustainable and cost-effective stormwater management. LIDs include rain gardens, water ponds, and other nature-based infrastructures. However, both stormwater and LIDs contain microbial pathogens sourced from animal waste because these infrastructures are home to many animals and insects. The widespread use of LIDs is likely to increase human exposure to pathogens and the risk of infection, potentially leading to unexpected disease outbreaks in urban communities. The evaluation of LIDs entails the complexity of stormwater regulations, public health risks, environmental performance, and cost. Currently, an assessment of LIDs that confirms their environmental performance and ability to meet public health targets is not feasible. Therefore, an advanced decision-making framework is required to support risk-based planning of LIDs prior to their installation in urban communities.
This research aims to develop an integrated decision-making framework that facilitates the evaluation of LIDs by considering their microbial risks, environmental performance, and cost. A four-step research approach was adopted to achieve this goal. First, I completed a comparative analysis of Canadian stormwater regulations and guidelines, identifying the use of LIDs in ten provinces. In the second step, I integrated Quantitative Microbial Risk Assessment (QMRA) and predictive modeling to evaluate the public health risks during the planning phase of LIDs. In the third step, I employed the life cycle impact assessment and life cycle cost analysis and later compared the environmental performance and cost of various LIDs. Lastly, I applied Multi-Criteria Decision-Making (MCDM) method to combine public health risks, environmental performance, and life cycle cost of LIDs. The findings indicate that the weightage of these criteria influences the ranking of LIDs. Wetland is the best LID in terms of public health and economic cost, whereas box planter has become a top priority in terms of environmental performance.
The developed framework represents an important step toward addressing microbial risks, environmental performance, and the cost of LIDs in an integrated fashion. The proposed framework offers a unique opportunity to prioritize competing interests and guide actions that ensure well-being and sustainable development. Overall, this framework is valuable for contributing to the UN's 2030 Agenda goals, particularly SDGs 3 and 13.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
An integrated fire risk management of multi-unit residential buildings with smart and green features : machine learning-based framework
No full textThe building industry has been facing significant challenges, including high quality, sustainability, cost-effectiveness and safety. Fire risk poses a significant threat and impacts on public safety, property, and the environment. Canada recorded 0.5 million fires in 10 years, which caused 15,000 fatalities, a direct loss of $7.5 billion, 1,200 children were injured, and 1.2 million Canadians were affected directly. In British Columbia (BC), 55% of the fires were associated with multi-unit residential buildings, which are being increasingly built with smart and green features for a positive impact, however, these features may negatively impact from a fire’s perspective.
This research developed an integrated fire risk management framework using machine learning algorithms for multi-unit residential buildings integrating smart and green features (SG-MURBs). Five phases were incorporated in the framework to enhance fire prevention, protection, and intervention strategies: (I) investigated state-of-the-practice to explore fire risk management practices (II) Identified key potential fire risk and safety-related factors considering relative frequencies and their related impacts (III) Developed benchmarks to set the acceptability levels and determine the critical factors accordingly (IV) Developed models to predict the potential impacts of fire incidents in SG-MURBs, and finally (V) Generated optimal solutions and optimized multidimensional fire impacts.
The developed framework was applied and tested for seven cities in BC, Canada. The results discerned the key potential contributing factors to fire incidents covering common, smart, and green factors, including 40 ignition sources, 28 human errors, and 36 combustible materials. Using the developed benchmarks, Vancouver, Kelowna, and Kamloops were found the top critical cities with 58%, 37%, and 47% of very high levels of ignition sources, human errors, and combustible materials, respectively. The most suitable methods for fire control and fire suppression materials for the top critical combustible materials were determined. The ANN models were found to outperform classifiers with prediction abilities of 65%, 72%, 85%, and 99% in predicting related potential impacts. Moreover, the optimal set of fire safety strategies were determined using genetic algorithms to enhance fire risk management. The developed framework will help decision-makers guide policies and enhance investments for specific fire prevention, protection, and intervention strategies accordingly.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
Optimization of water quality and energy use in large water distribution systems
No full textA water distribution system (WDS) is the most expensive and energy-intensive component of a water supply system. Maintaining acceptable water quality (WQ) and adequate pressure with minimum energy use is important in drinking water management. At the very least, water utilities must maintain a certain residual chlorine level to inactivate the pathogens and minimize human health risks. In terms of energy use, inefficient pump scheduling is a common problem identified in water distribution, leading to high energy costs. Due to increasing urbanization, population growth, high energy costs, and related greenhouse gas emissions, there is an increasing need to improve WQ and minimize energy usage simultaneously. Thus, leading to the development of sustainable water management strategies for large WDS. The optimization in the context of WQ and energy usage for large WDS alone is a challenging task. Until now, no established solution is available, as most of the past studies to find an optimal solution were either having a compromised WQ or unable to deal with the increasing energy demands of a large WDS. This research developed an integrated WQ and energy use optimization framework for an existing large WDS. At first, the water quality index and risk-based fuzzy failure modes effect analysis methods were applied to assess and optimize WQ. Later, optimal pump scheduling was identified to minimize energy use by employing a mixed integer goal programming model. In the last phase, both hydraulics and WQ performances were evaluated by developing a unique optimization approach. The proposed framework was demonstrated using a WDS in Al-Khobar (a large-sized city in Saudi Arabia). The case study results reflected the merits of the developed framework as ~20% energy cost reduction was obtained. Similarly, the use of the proposed optimization framework predicted > 40% WQ improvement. The proposed framework is flexible and can be applied to WDS of different sizes. It can assist water utilities in achieving higher performance with minimal energy use.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
Management of unregulated disinfection by-products in water distribution networks : an integrated framework
No full textGood water quality is essential for ecosystem health and human survival. Issues related to deteriorating water quality and its availability with sufficient quantity have become the grand environmental challenges of our times. In an urban environment, water is supplied to the consumers through water distribution networks (WDNs), designed to supply with adequate quantity with acceptable quality. The WDNs performance in terms of service delivery due to internal and external challenges cause water quality failure (WQFs) and can be linked to adverse human health effects. Microbial contamination and the formation of disinfection by-products (DBPs) are a few of the prominent WQF pathways. DBPs in drinking water and their exposure through ingestion and inhalation have been associated with cancer and non-cancer risks. There are numerous regulated and unregulated DBPs (UR-DBPs) present in public water supplies. Water utilities are now increasingly concerned about UR-DBPs because their occurrence has been consistently reported in drinking water supplies. Current research develops an integrated management framework to identify, prioritize, predict, and control the occurrence of UR-DBPs in WDNs. In this study, dichloroacetonitrile (DCAN), trichloropropanone (TCP), and trichloronitromethane (TCNM) were identified as commonly occurring UR-DBPs. The framework is implemented in four phases. Phase 1 identifies and prioritize the commonly occurring UR-DBPs; phase 2 estimates their levels in WDNs through predictive modeling approaches; phase 3 develops a water quality assessment approach to classify water quality and evaluate the impacts; phase 4 prioritizes management alternatives for UR-DBPs control using multi-criteria decision making. The results of this research have the potential to be used at different levels by utility managers, planners, and water purveyors to improve the drinking water quality management in terms of UR-DBPs. Furthermore, the decision-makers can identify and prioritize the UR-DBPs, predict their occurrence in WDNs, and evaluate the impacts of deteriorating drinking water quality on natural water resources. From the management perspective, the applicability of various management strategies in WDNs can be assessed under given settings and criteria. Thus, the water utilities can prioritize investment alternatives by identifying critical contaminants and acknowledging a trade-off between the delivered water quality and associated impacts.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
Ecological risk assessment of tire and road wear particles : a preliminary screening for freshwater sources in Canada
No full textApproximately 1.5 billion tires/year are produced worldwide. Tire tread wear particles due to road abrasion are a major source of environmental microplastic pollution and 5.9 million tonnes/year of tire and road wear particles (TRWP) are emitted globally. Twelve to twenty percent of TRWP are transmitted into surface waters, where they can leach (i.e., release) chemical compounds that can adversely affect aquatic species. The primary objective of this study was to assess the acute, freshwater ecological risk of TRWP emissions. A conceptual ecological risk assessment (ERA) model was developed using ERA frameworks. The model was applied to Kalamalka Lake with respect to British Columbia (BC) Highway 97 (HWY-97) in Western Canada. This was the first ERA of TRWP in Canada and the results and methodology will provide a foundation for future research. This was a screening-level, conceptual ERA, based on secondary data from published scientific studies. Two spatial scenarios were assessed. Spatial scenario 1 assumed annual TRWP emissions from 20 km of HWY-97 equilibrate across the entire lake volume. Spatial scenario 2 assumed TRWP emission from a single storm drain microcatchment (0.875 km of HWY-97) equilibrated adjacent to the shoreline in a smaller water volume in the short-term. For both scenarios, TRWP-derived chemical leachates considered for ERA were aniline, anthracene (ANT), benzo(a)pyrene (B(a)P), fluoranthene (Fl), mercaptobenzothiazole (MBT), and zinc (Zn). An assumed ‘total TRWP-derived leachate set’ was also assessed, based on data representing all compounds present in tire-derived leachate solution tests. The results indicated a potential risk to aquatic species in both spatial scenarios, depending on the contaminant of concern. In Scenario 1, ecotoxicity risk was high from exposure to zinc and the total TRWP-derived leachate set. Scenario 2 results indicated acute risk was high from all TRWP-derived chemicals examined, except MBT. This preliminary screening of ecological risk provides an early signal that freshwater lakes adjacent to busy highways may be at risk from TRWP contamination, demonstrating a need for further research and additional data to verify the results.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
Selection and optimization of marine oil spill response operations using artificial intelligence and soft computing techniques
No full textMarine oil spill incidents are detrimental to both natural environment and human health. Water quality, marine ecosystems, and shoreline conditions can be deteriorated by the spilt oil. Swift and efficient response to an oil spill is crucial to minimize the adverse consequences. However, the oily waste generated from response operations may also become a challenge, requiring careful waste management strategies. Widely used oil spill response methods (OSRMs) include mechanical containment and recovery (MCR), in-situ burning, and the use of chemical dispersants. Choosing the most suitable method is a complex process depending on various factors. Among OSRMs, MCR is the most effective in removal of spilt oil from the marine environment. The management of oily wastewater generated during MCR requires careful attention, as it comprises a significant portion of overall oily waste.
This study developed multiple tools to aid selecting OSRMs in harsh and remote offshore waters. These selection tools employ machine learning techniques and historical response data to predict appropriate OSRMs for new incidents. The tools were developed in MATLABTM using various artificial intelligence and soft computing techniques, such as fuzzy decision tree (FDT), Gaussian process regression (GPR), and artificial neural network, individually or in combination. FDT-based tools were also integrated with regression analysis techniques and an optimization algorithm to enhance their performance. Optimized FDTs integrated with regression analysis and GPR were found to be the most effective techniques based on the prediction power.
Furthermore, this study developed an integrated optimization tool to efficiently manage the mechanical response process. This tool aims to minimize the time and cost associated with MCR and oily wastewater management (OWM) and the volume of weathered oil during the operation. The tool encompasses three components of multi-objective optimization, oil weathering process, and MCR and OWM operational agents, simulating detailed response procedures. Applying the tool to a case study in Canada led to a notable reduction in the time and cost of the entire response, and a considerable increase in the volume of recovered oil. It provides an effective approach to manage response process, and significantly reduces the environmental and socio-economic impacts of oil spill incidents.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
Energy-efficient residential buildings with advanced insulation materials : a lifecycle thinking approach
No full textThe full abstract for this thesis is available in the body of the thesis, and will be available when the embargo expires.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
Evaluation of water systems in small remote Indigenous communities : a risk management framework
No full textAccess to safe drinking water is essential for human health and well-being. However, small remote Indigenous (SRI) communities face barriers in securing reliable water supplies as a result of geographic isolation, inadequate infrastructure, and financial constraints. Chemical pollutants from natural or anthropogenic sources, in particular, constitute a significant source of water quality contamination and deterioration. The ingestion of these chemicals may pose threats related to non-cancer (NCR) and cancer risks (CR). When water systems (WSs) provide water with desirable quality, it enhances public health, reduces disease prevalence, and improves overall community well-being. There are clear benefits associated with access to safe drinking water, such as increased water quality perception, community well-being, more uptake from the community resulting a larger population served and potential economic returns. Exploring drinking water-related risks and benefits is critical to exploring effective management strategies. It offers valuable insights to minimize the impacts of chemical pollutants on human health.
This research aimed to develop a risk management framework to identify, control, and mitigate water quality risks in SRI communities. The study follows a structured approach, which entails three phases. Initially, a literature review was conducted to identify and understand the risks and benefits of drinking water in SRI communities. In the second phase, a detailed risk and benefit assessment was performed. In the third phase, a matrix based on benefit-to-risk ratio (BRR) was developed to guide decision-making. Finally, the framework was applied to six SRI communities across Canada. The findings showed that the risks of two WSs outweigh the benefits, primarily driven by higher concentrations of pollutants, which led to lower water quality perception and reduced population served. The developed framework also provides a foundation to facilitate best management practices. It helps identify which primary pollutants contribute to potential health risks, allowing decision-makers to enhance water quality perception, improve public health outcomes, and achieve economic benefits.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
An Integrated asset management of buried infrastructure : a BIM-based life cycle thinking framework
No full textWater and sewer pipe networks are core public infrastructure critical for basic human services. These infrastructures should be sustainable as they consume natural resources and produce emissions into the environment during their life cycle. Water and sewer pipes should be sustainable based on their manufacturing and operation, which is typically evaluated using the established methods such as Life Cycle Assessment (LCA) and Life Cycle Cost Analysis (LCCA). Additionally, a standard data management system that can interact with various built environments and collaborate with various databases improves the decision-making process. Building Information Modelling (BIM) can be used for this purpose, which has the capability of collaboration and interoperability, which are useful for infrastructure conflict resolution and stakeholder management. This research has proposed a BIM-based life cycle thinking framework for integrated asset management of buried infrastructure using a stochastic approach such as the Markov-chain model. A geo-referenced 3D model was developed in Civil 3D using GIS shapefiles obtained from open-source data of the City of Kelowna municipality. The life cycle impacts of five different pipe materials were evaluated using LCA and LCCA for the developed 3D model that includes four phases: production, installation, maintenance, and disposal. The results of life cycle environmental impacts with all the midpoint impact categories are aggregated into a sustainability score using a weighted sum method and compared with ReCiPe’s single score. Furthermore, integrated maintenance is suggested as a possible alternative to conventional sequential maintenance, and a common trench is considered following the CSA, ASTM, ASCE, and AASHTO guidelines. The comparison of ReCiPe’s single score to the estimated life cycle sustainability impact (LCSI) index gave contrasting results, mainly in the analysis of ductile iron and PVC pipe materials. Based on the LCSI index, the pipe materials are ranked, and the best pipe material is selected. The integrated maintenance approach was found to be cost-effective with a life cycle cost savings of 18%, but at a cost of 19% greater CO2eq emissions. Nonetheless, when the LCSI index is considered, the integrated maintenance approach with a common trench has55% less life cycle environmental impacts than separate trenches. The proposed framework has demonstrated the potential for sustainable buried infrastructure through appropriate selection of pipe materials and integrated infrastructure management. Future research may expand the trench design with more green construction materials, that may further reduce the CO2eq emissions and conventional stochastic optimization techniques may be utilized for performance prediction models.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
Sustainable gaseous fuel futures of Canada : a planning framework for fuel supply chain configurations
No full textThe increasing energy demand results in numerous environmental concerns. Despite the popularity gained by renewable energy, certain economic activities still require fossil fuels, with natural gas (NG) playing a critical role in Canada's energy security. However, NG supply chain operations emit significant greenhouse gas volumes. As low-carbon fuels, hydrogen and renewable natural gas (RNG) are considered strategies to decarbonize the NG supply chain. However, hardly any studies have been carried out to suggest integrated pathways for RNG and hydrogen inclusion in conventional gas grids. Therefore, the overall aim of this research is to develop a life cycle thinking-based decision support framework to decarbonize the natural gas supply chain through RNG and hydrogen integration. Multi-criteria decision-making methods were used to select the most suitable RNG and hydrogen production paths. Multi-objective optimization was employed to determine the optimum fuel generation mix and gaseous fuel portfolio that caters to key economic sectors. A dynamic modelling approach was used to evaluate investment decisions from a long-range perspective. Policy implications and recommendations were further proposed for successfully decarbonized gas grid planning and management. The study results indicate that integrating RNG and hydrogen into conventional gas grids can reduce emissions of up to 250 tons CO2eq/year and generate substantial carbon tax savings of up to / MJ and 4.8 $/kg H₂ by 2050 with policy support. The deliverables of this research will aid in decision-making for pre-project planning and sustenance of a diversified gas supply chain with RNG and hydrogen. The developed decision support framework and the models will assist utility providers and investors in identifying the optimum fuel integration path and fuel portfolio allocation for key economic sectors. The deliverables are geared towards ensuring necessary technical support to ensure community energy security and achieve climate action goals. The study findings will contribute to the development of a diversified and decarbonized gas supply chain and an energy-independent community.Applied Science, Faculty ofEngineering, School of (Okanagan)Graduat
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