Browsing by Author "Ng, Kelvin Tsun Wai"
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Item Open Access An evaluation on electronic waste management and product stewardship programs in North America(Faculty of Graduate Studies and Research, University of Regina, 2023-12) Hasan, Mohammad Mehedi; Ng, Kelvin Tsun Wai; Jin, Yee-Chung; Na (Jenna)Electronic waste (E-waste) has been extensively investigated by researchers throughout the globe, however specific research trends in North America (NA) are yet unknown. The first part of the study attempts to present an up-to-date bibliometric view of e-waste studies and to identify the research sub-fields and networks. A total of 271 documents were retrieved from the Web of Science (WoS) database (from 2001 to 2022). E-waste research topic that originated from NA, as well as its relative growth rate, collaborative measures, institutional productivity, and the popular journals were evaluated in this bibliometric analysis. The first part of the study showed that research productivity increased noticeably in the last decade. The USA has the most e-waste publications (74.62%), followed by Canada (22.38%) and Mexico (10.44%). The topic with the highest percentage of papers (151, or 55.72%) was environmental science. Resources Conservation and Recycling was the most active journal on e-waste research. The University of California, USA (10.70 %) played an active role in the publication, and Ogunseitan, O. A. was the most productive author (4.80 %) in this field. Author’s keywords can be generally grouped into four clusters. Network analysis results suggest that collaborative activities by leading universities will likely boost the number of studies. Researchers and policymakers will benefit from the first part of the study by gaining a better understanding of the development and the content trends of e-waste research. It is found in Part 1 that e-waste stewardship studies in Canada are limited, and they are specifically addressed in part 2. The amount of e-waste generated worldwide is growing at an explosive rate. The precious materials contained in this waste stream offers an ample business opportunity that produces high returns for the recyclers both in informal as well as formal sectors. A range of e-waste recycling companies have proliferated not only in developing countries but also in industrialized nations. The second part of the study further analyzed and evaluated e-waste management performances and recycling practices of a Canadian company that operates throughout the country. The company’s annual performance report from 2012 to 2020 served as the source for the e-waste statistics and related materials for the second part of the study. The corporate website is also considered in addition, to gain an overall understanding of the business portfolio. Temporal variations of performance factors were examined, and regression analysis was carried out to assess the relationships among various elements related to the recycling features. The study findings show that the overall e-waste collection rate throughout the country plummeted dramatically during the course of the investigation starting from 1.1-5.04 kg/capita to 1.4-3.0 kg/capita. E-waste drop-off points designated by the company have expanded by more than 800% and industry participation rose to more than 120% during the study period. Furthermore, study reveals that around 77% people in Canada are aware of the e-waste management and 97% people remain very close to the authorized e-waste collection points. The outcomes disclose that there is no overall correlation between public awareness and the rate of stewardship registration or e-waste collection. With just a few minor variations, the company's sector-specific yearly spending allocation over the investigation period was nearly identical. Corporation’s average total recycling expense ranges from $1,290 in 2012 to $1,578 in 2020. The outcomes of the current study can potentially inform recycling entrepreneurs and policy makers crafting methodical and strategic plans for the adoption of e-waste formalization management systems.Item Open Access Analytical Coupling Methodology of Fluid Flow in Porous Media Within Multiphysics Domain in Reservoir Engineering Analysis(Faculty of Graduate Studies and Research, University of Regina, 2020-01) Yuan, Wanju; Zhao, Gang; Jin, Yee-Chung; Jia, Na; Ng, Kelvin Tsun Wai; Chi, Guoxiang; Moore, Robert G.Fluids flow in porous media are usually affected by multiphysics domains. Thermal, mass transfer, and hydraulic domain will all significantly affect the features of fluids flow in porous media. Thermal fluids coupling problems occur almost in every area of reservoir engineering such as geothermal energy development, and heavy oil recovery. Mass transfer is another important mechanism that should be considered in solvent based heavy oil recovery and unconventional enhance oil recovery methods. This research focuses on using analytical source and sink function method applied in heat transfer and mass transfer to simulate two domain coupling model. Based on thermal source and sink function derived in this thesis, convective heat is treated as a simple special form of source and sink function. The calculation of transient convective heat amount in Laplace domain problem has also been solved innovatively in this dissertation. Sensitivity analysis on segment size from computing prospect, thermal diffusivity and velocity from system prospect are analyzed to help understand the heat transfer process integrating conduction and convection mechanism. Secondly, this convective source function methodology is applied in a 2D model of geothermal energy recovery process. A typical geothermal energy recovery well pair is simulated by the innovative coupling methodology. Different well pair locations and fractured wells are examined through this model referring to the enhanced geothermal system technology for hot dry rock reservoir. Big jumps from heat transfer to mass transfer are made to analytically model the solvent injection process for heavy oil recovery. Multi-mechanisms including diffusion and dispersion, viscosity reduction, oil swelling are considered analytically and integrated into the two domain coupling model. Solvent-based Post Cold Heavy Oil Production with Sand (CHOPS) with single fracture structure is also modeled by this methodology. The mass transfer proves to have significant influence on fluids flow in porous media. Heavy oil thermal based recovery methods such as SAGD have complicated interactions phenomenon between thermal domain and pressure domain. Viscosity reduction, fluids thermal expansion and heat loss to caprock will significantly affect the operation energy efficient and environment footprint. Sensitivity analysis of key parameters affecting the thermal injection process are also conducted.Item Open Access Assessing construction and demolition waste generation rates using satellite imagery(Faculty of Graduate Studies and Research, University of Regina, 2024-04) Ray, Sagar; Ng, Kelvin Tsun Wai; Veawab, Amornvadee (Amy)Municipal solid waste management has seen a surge in the use of satellite imagery in decision-making processes, yet its application to analyze quantitative variations in construction and demolition (C&D) waste remains underexplored. Especially the COVID- 19 pandemic disrupted conventional municipal solid waste (MSW) management practices and affected waste generation rates. While MSW streams have been extensively studied and reported, the impact on construction and demolition (C&D) waste remains overlooked. As such, the first part of the study develops an innovative analytical framework utilizing satellite imagery to quantify C&D waste disposal rates during COVID-19 restrictions in a mid-sized Canadian city. Supervised classification of Landsat-8 images is conducted to derive the settlement area over a period of 8.8 years (2014-2022). The relationship between C&D disposal rates and settlement area is evaluated using regression analysis. Results reveal a 73.4% reduction in mean weekly C&D disposal in 2020 compared to pre-pandemic years, reflecting diminished construction activity. The settlement area exhibits a strong positive correlation (R2=0.812) with per capita C&D disposal rate, providing spatial evidence of urbanization patterns affecting C&D waste generation. Among socioeconomic factors examined, the value of building permits issued most influences C&D quantities (R2=0.934). The satellite imagery-based approach allows indirect estimation of disrupted C&D waste streams when on-site auditing is restricted during pandemics. The framework offers municipal authorities spatial decision support to formulate data-driven C&D waste management policies that are resilient to future public health emergencies. The second part of the study employs satellite imagery and multivariate analysis to comprehensively assess and predict C&D waste generation in four diverse urban jurisdictions of Canada (Regina) and the USA (Seattle, Buffalo, and Philadelphia). In Seattle, the annual mean C&D waste amount per capita is 0.624 tonnes, while in Regina, Buffalo, and Philadelphia, it is 0.224, 0.330, and 0.014 respectively. Factors such as settlement area expansion, economic activities, and population growth significantly influence C&D waste rates. Stepwise multivariate regression models tailored to different city types, such as moderately populated (Group 1) and highly populated (Group 2), showcase acceptable predictive capabilities. For moderately populated cities, settlement area, average humidity, and GDP are identified as key predictors, while for highly populated cities, settlement area, unemployment rate, and building permit value prove effective indicators. These models, characterized by R² values from 0.70 to 0.94, provide tailored insights for distinct demographic conditions, aiding waste management planning. This research underscores the importance of satellite imagery and multivariate analysis in understanding C&D waste dynamics and empowers policymakers and waste management agencies with evidence-based strategies for effective waste management in urban centers.Item Open Access Corrosion Inhibition Performance of Methionine for CO2 Absorption Plants(Faculty of Graduate Studies and Research, University of Regina, 2021-03) Udayappan, Balaji; Veawab, Amornvadee; Ng, Kelvin Tsun Wai; Aroonwilas, Adisorn; Muthu, JacobInorganic corrosion inhibitors including heavy metals have been widely used in the carbon dioxide (CO2) absorption process for corrosion control. However, they are not environmentally friendly causing costly handling and disposal costs. This work therefore evaluated corrosion inhibition performance of an organic amino acid compound, namely Methionine (MTI) which is less toxic, more readily biodegradable, and has lower potential for bioaccumulation in aquatic organisms compared to common amine absorption solvents. The evaluation was experimentally implemented using electrochemical and weight loss methods. Carbon steel (CS1018) and 5.0 kmol/m3 Monoethanolamine (MEA) purged with 85% CO2 and 15% oxygen (O2) were used as tested material and absorption solution, respectively. The electrochemical results showed that at solution temperatures up to 80oC, MTI effectively reduced corrosion rates of CS1018 with maximum inhibition efficiencies of 83.56% ± 1.82% under a static condition (0 rpm) and 74.96% ± 0.95% under a dynamic condition (1500 rpm). Its inhibition performance was found to increase with inhibitor concentration and solution temperature but decrease with rotational speed. MTI acted as a mixed-type inhibitor and exhibited pitting tendency. The optimal MTI concentrations were 1500 ppm at 0 rpm and 2000 ppm at 1500 rpm. The post data analysis involving adsorption isotherm and activation thermodynamic properties revealed that MTI protected metal surface by undergoing spontaneous and endothermic physical adsorption. Its adsorption characteristic matched well with the Langmuir adsorption isotherm, thereby suggesting that MTI formed a protective monolayer on the metal surface. The results of quantum chemical analysis suggested MTI has higher affinity, polarizability, and electron donating ability than MEA. III The results of weight loss experiments carried out for up to 28 days showed that at 120oC, 5 bar and 1500 rpm, MTI was able to reduce corrosion rates of CS1018 to below 1 mmpy. The inhibition efficiencies were up to 78.7% for carbon steel specimens fully immersed in the MEA solutions, 53.5% for those partially immersed in the MEA solution and partially exposed to vapor, and 85.6% for those fully exposed to vapor. Pits were observed on carbon steel specimens fully immersed in both uninhibited and MTI inhibited solutions.Item Open Access Effects of a global pandemic on the collection and disposal of municipal solid waste(Faculty of Graduate Studies and Research, University of Regina, 2023-06) Mahmud, Tanvir Shahrier; Ng, Kelvin Tsun Wai; Xue, Jinkai; Khan, Sharfuddin; Lozecznik, StanThe COVID-19 pandemic and the subsequent lockdowns had significant effects on solid waste management, which has received greater research focus during this time due to the infectious nature of the SARS-CoV-2 virus. As such, in the first part of the study, SARIMA models were developed to predict residential waste collection rates (RWCR) across four North American jurisdictions before and during the pandemic. Unlike waste disposal rates, RWCR is relatively less sensitive to the changes in COVID-19 regulatory policies and administrative measures, making RWCR more appropriate for crossjurisdictional comparisons. It is hypothesized that the use of RWCR in forecasting models will help us to better understand the residential waste generation behaviors in North America. Both SARIMA models performed satisfactorily in predicting Regina's RWCR. The SARIMA DCV model's performance is noticeably better during COVID-19, with a 15.7% lower RMSE than that of the benchmark model (SARIMA BCV). The skewness of overprediction ratios was noticeably different between jurisdictions, and modeling errors were generally lower in less populated cities. Conflicting behavioral changes might have altered the residential waste generation characteristics and recycling behaviors differently across the jurisdictions. Overall, SARIMA DCV performed better in the Canadian jurisdiction than in U.S. jurisdictions, likely due to the model's bias on a less variable input dataset. The use of RWCR in forecasting models helps us to better understand the residential waste generation behaviors in North America and better prepare us for a future global pandemic. The second part of the study aims to identify the effects of continued COVID-19 transmission on waste management trends in a Canadian capital city, using pandemic periods defined from epidemiology and the WHO guidelines. Trends are detected using both regression and Mann-Kendall tests. The proposed analytical method is jurisdictionally comparable and does not rely on administrative measures. A reduction of 190.30 tonnes/week in average residential waste collection is observed in the Group II period. COVID-19 infection negatively correlated with residential waste generation. Data variability in average collection rates during the Group II period increased (SD=228.73 tonnes/week). A slightly lower COVID-19 induced Waste Disposal Variability (CWDV) of 0.63 was observed in the Group II period. Increasing residential waste collection trends during Group II are observed from both regression (b = +1.6) and the MK test (z = +5.0). Both trend analyses reveal a decreasing CWDV trend during the Group I period, indicating higher diversion activities. Decreasing CWDV trends are also observed during the Group II period, probably due to the implementation of new waste programs. The use of pandemic periods derived from epidemiology helps us to better understand the effect of COVID-19 on waste generation and disposal behaviors, allowing us to better compare results in regions with different socio-economic affluences. The results of both studies will assist policy makers in developing data-driven solid waste management policies during a global pandemic.Item Open Access Forecasting waste volume and identifying barriers of Canadian photovoltaic waste management(Faculty of Graduate Studies and Research, University of Regina, 2022-09) Romel, Monasib Ahmed; Kabir, Golam; Ng, Kelvin Tsun Wai; Khondoker, Mohammad; Ruparathna, RajeevThe worldwide exponential upsurge of photovoltaic (PV) installations and the subsequent heights of PV waste is a swelling apprehension. The objectives of this study are to forecast the photovoltaic waste volume and to analyze the critical barriers for the photovoltaic waste management in Canada. In the first section, the solar waste volume forecasting was done using linear regression, 2nd order polynomial regression, and power regression models. In the second section, the barriers to photovoltaic solar waste management were identified through literature review and analyzed by formulating a framework from integrating Rough Analytical Hierarchy Process (RAHP), Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methods. The findings of the thesis show that for early loss the PV waste volume will be as high as 270,000 MT and as low as 180,000 MT and for regular loss the PV waste volume will be as high as 180,000 MT and as low as 160,000 MT for the year of 2045. The result of the barrier analysis shows that a complex causal relationship exists among the barriers with “Insufficient Generation of PV Waste”, and “Waste Collection Centre” are the top two crucial barriers with highest driving power and causal effect on others. This thesis is expected to contribute to the concerned government agencies to assess the upcoming volume of PV waste and then evaluate the relationship among the barriers to PV waste management for establishing a sustainable and resilient PV waste management plan for Canada.Item Open Access Investigating The Impacts of Adverse Road Weather Conditions on Free-Flow Speed and Lane Utilization(Faculty of Graduate Studies and Research, University of Regina, 2018-11) Rillagodage, Navoda Yasanthi; Sharma, Satish; Mehran, Babak; Jin, Yee-Chung; Ng, Kelvin Tsun Wai; Peng, WeiWinter driving poses additional safety challenges to drivers and other road users due to reduced visibility, snow and ice accumulation on travel lanes, and variations in transportation infrastructure such as reduced lane width due to snow plow operations and coverage of lane markings by snow. On the other hand, road-weather related variations in transportation infrastructure characteristics and driver behavior negatively impact traffic operations in winter. Therefore, it is crucial to understand the anticipated consequences of extreme road-weather conditions on traffic flow parameters and driver behavior. Thus, in this study, the free-flow speed and the lane utilization patterns under adverse roadweather conditions were studied. Road-weather data were collected from a Road-Weather Information System (RWIS) and traffic data were collected from a Weigh-In-Motion (WIM) station located in Highway 16 in Alberta from October, 2014 to December, 2015. The first part of the study attempts to investigate drivers’ choice of desired speed under adverse road-weather conditions with two main objectives: i) to model the impacts of road-weather events on free-flow speed of light and heavy vehicles, and ii) to explore the variability in free-flow speed models caused by adopting different data analysis methods. Separate linear and nonlinear regression models were developed by adopting three distinct statistical approaches i.e. i) with dependent variable as individual vehicle speeds, ii) with dependent variable as 20 minute aggregate vehicle speeds, and iii) with sampled data. The study results revealed that slight, moderate and heavy snow will reduce the free-flow speed of light vehicles travelling in shoulder lane by 0.2%, 3.4% and 0.8% and the free-flow speed of heavy vehicles by 1.7%, 0.1% and 1.3% respectively. Further, it was unveiled that the drivers’ reaction to ice warning pavement surface conditions is maximum. Linear regression models with aggregated speeds as the dependent variable was concluded as the best fit for the data among the other statistical approaches tested. The second part of the study aims to model lane utilization patterns of light and heavy vehicles under different road-weather conditions in macroscopic and microscopic facets. Two main types of lane utilization models were developed exerting a linear and a logistic regression approach in modelling. Each main model contains three sub models with refined data corresponding to all light and heavy vehicles. Interestingly, moderate rain and nighttime cause the vehicles to prefer shoulder lane irrespective of the vehicle type as suggested by both models. The findings indicated that heavy vehicles tend to choose the median lane under icy pavement conditions as estimated by both model types. Light vehicles tend to utilize the median lane under ice watch and frost pavement conditions in macroscopic and microscopic contexts, respectively. Unlike the other similar studies conducted so far, this study estimates the free-flow speeds and lane utilization patterns of vehicles more accurately because of the unique location configuration of the data collectors. In addition, the study results direct the weather responsive traffic management systems to a new path by introducing more dimensions to be considered about, such as variable speed limits depending on different road-weather conditions and traffic composition, and dynamic lane utilization schemes.Item Open Access Modeling of municipal waste disposal behaviors related to meteorological and astronomical seasons using recurrent neural network models(Faculty of Graduate Studies and Research, University of Regina, 2022-09) Adusei, Kenneth Kwaaboadu; Ng, Kelvin Tsun Wai; Tang, Yili; Zhao, Gary G.The literature suggests that Long Short-Term Memory (LSTM) paired with recurrent neural network (RNN) can better express long- and short-term reliance of a data set. Study one quantifies mixed waste disposal (MWD) behaviors at a Canadian landfill from 2013 to 2021, and develop separate RNN-LSTM models to predict MWD rates under four meteorological seasons. Seasonal variations are clearly presented in the historical disposal data, with higher MWD of 417.8 tonnes/month in summer and about 289.7 tonnes/month in winter. The variabilities of MWD are also different among the seasons. Winter experienced the least variation, probably due to similarities in inhabitants’ lifestyles. All seasonal sets are left-skewed, and the highest skewness is observed in summer. The overall model performance using the entire data range is generally satisfactory, with R2 values between 0.72 ~ 0.86. Meteorological seasons appear to be a significant factor in waste disposal rate modeling. The model performances are less reliable for smaller disposal rates less than 200 tonnes/day, with 0.01 < R2 < 0.59. The results suggest the disposal behaviors on a quiet day can be quite different. The use of distinct time series related to seasons on MWD modeling is original. The proposed analytical approach provides an alternative waste modeling approach accounting for both short term (seasonal) and longer term (annual) effects. Study two further explored the use of astronomical seasons in municipal solid waste disposal rates modeling. The study quantifies seasonal variations of municipal solid waste (MSW) disposal rates in a mid-sized Canadian city with respect to both meteorological and astronomical seasons using RNN – LSTM models. Meteorological seasons are related to the annual temperature cycle, whereas the astronomical seasons are based on the position of Earth in relation to the Sun. It is hypothesized that the number of hours of natural daylight could also affect MSW generation rates. The use of both meteorological and astronomical seasons in waste modeling is original. During the study period, considerably higher rates in summer (417.8-418.2 tonne/day) than in winter (289.0-290.0 tonne/day) were observed. Waste disposal behaviors in winter are however more consistent. The astronomical models appear to better handle extreme situations in the winter and summer. The results indicate that the astronomical models may be more appropriate in some cases. Overall, the predictive accuracy of all models are acceptable, with R2 ranging from 0.70 to 0.86. In general, meteorological models outperformed astronomical models slightly, with RMSE ranged from 72-95 tonne/day. The RMSE of the winter sets are lower, probably due to the lower disposal rates in winter. The results generally support the use of astronomical data to supplement meteorological data in waste seasonal variation studies. The results of both the studies will help policy makers to better implement solid waste management strategies in both meteorological and astronomical seasons.Item Open Access Numerical simulation and optimization of cyclic and continuous fluid injection for geothermal energy recovery(Faculty of Graduate Studies and Research, University of Regina, 2023-07) Li, Runzhi; Jia, Na; Zhao, Gang; Shirif, Ezeddin; Ng, Kelvin Tsun WaiGeothermal energy is a viable solution for reducing greenhouse gas emissions and mitigating climate change. It has a wide geographic distribution, requires little exploration and operation costs, and has virtually no carbon emissions. This renewable energy source can generate electricity, provide direct heating and cooling, and even be utilized for agricultural and industrial processes. It can be harnessed at any scale, from individual buildings to large-scale power plants, and is available in many parts of the world. In addition, the operation and maintenance costs of geothermal energy resources are relatively low, making it a cost-effective alternative to other energy production forms. Meanwhile, geothermal energy emits significantly less carbon dioxide compared to fossil fuel power plants, reducing the dependence on fossil fuels. This thesis focuses on the numerical simulation of the geothermal energy extraction from the geothermal reservoirs by utilizing various recovery strategies originating from the petroleum industry. Initially, this research uses Computer Modelling Group (CMG) reservoir simulator software to simulate the energy extraction in the conventional water base geothermal reservoirs that locate at Western Canada Sedimentary Basin and the area in the City of Regina. The simulation of the primary recovery (rely on the natural energy release from the original reservoirs) and secondary recovery (continuous water injection and cyclic water injection) were discussed. The CMG-CMOST was involved in this study in order to process the optimization process to maximize cumulative energy production and net present value (NPV) of geothermal energy recovery process. In addition, the injected working fluid was changed to carbon dioxide (CO2) for extracting geothermal energy, which is considered a significant source caused global warming issues. In this study, the injected CO2 was controlled at a supercritical state in order to maintain its higher heat capacity. History matching was performed in order to verify the fluid model’s accuracy. All the simulation and optimization process was performed, and the performance of CO2 as a working fluid in the geothermal energy extraction process were discussed.Item Open Access Production of Furfural From Lignocellulosic Biomass Using Sulfonated Carbon-Based Solid Acid Catalysts(Faculty of Graduate Studies and Research, University of Regina, 2021-12) Ogundowo, Oluwafadeyinmi Ibukunoluwa; Ibrahim, Hussameldin; Henni, Amr; Tontiwachwuthikul, Paitoon; Ng, Kelvin Tsun WaiThere is an aching desire to desist from the use of fossil fuel energy sources due to their major contribution to environmental degradation. Hydro, wind, and solar energy may serve as the much-needed alternative energy supply sources to fossil fuels however biomass will be the major alternative source for platform chemicals. Furfural is one of the 12 leading value-added chemicals identified by the US Department of Energy (DOE). It is of importance in the industrial sector, having applications such as; the removal of aromatics from diesel fuel and lubricant refining, and being a platform chemical from which a vast number of other chemicals are produced. The factors that influence furfural yield and selectivity are the catalyst used, solvent, catalysts loading, time, and temperature of the hydrolysis reaction. Farmers on the prairies have had a difficult time gathering and disposing of flax straws. Farmers burn this straw as a means of disposal due to its strong fiber and difficult decomposition. Every year, about 670,000 tonnes of flax straw are burned or destroyed on the prairies. This research work was aimed at the development of a sulfonated carbon-based solid acid catalyst for the production of furfural via hydrothermal hydrolysis of flax straw biomass. Glu-TsOH-Zr catalyst was developed, characterized by TGA, N2 -Physisorption, NH3-TPD, XRD, SEM, and FTIR, and then tested for its capacity in furfural production from flax straw biomass and pure xylose. Glu-TsOH-Ti and Glu-TsOH, replicated from literature were also characterized and applied for furfural production. The effect of residence time (0-120 mins), reaction temperature (170-210°), and the catalyst mass (0.25 -1g) on the furfural yield were also studied. Finally, the methyl tetrahydrofuran solvent ratio for optimal furfural production in a biphasic system was determined and a kinetic study was performed. The results presented that the Glu-TsOH-Zr catalyst had a good potential for improving furfural yield. The order of the catalysts based on the percentage of xylose conversion and furfural yield from pure xylose feed was Glu-TsOH-Ti > Glu-TsOH-Zr > Glu-TsOH. A reaction temperature of 190°C, a residence time of 120 minutes, and a catalyst mass of 1g (0.3 catalyst mass/flax straw mass) were found to be the best-operating conditions for furfural formation from flax straw biomass. The largest influence on furfural yield was determined to be temperature, followed by catalyst mass, and then reaction time. Furthermore, the catalyst with the highest overall acidity, surface area, and pore size (Glu-TsOH-Ti) also yielded the most furfural. The addition of an organic phase enhanced furfural yield, and the catalyst was reusable for up to three cycles with little drop in furfural yield; however, by the fourth cycle, there was a significant decrease in furfural yield. A first-order irreversible series reaction that started with the creation of furfural from xylose and ended with furfural degradation into degradation products was proposed as a kinetic model for the empirical rate data. The reaction leading to furfural production had higher activation energy (222.18kJ/mol) than the reaction leading to degradation products (104.56kJ/mol), showing that the furfural production reaction is more temperature-sensitive than the degradation reaction. Finally, the kinetic model's average absolute deviation (5.9%) indicated that it was an excellent fit for the reaction series.Item Open Access Spatiotemporal heterogeneity in precipitation and moisture transport over China and their connections with anthropogenic emissions and natural variability(Faculty of Graduate Studies and Research, University of Regina, 2022-09) Lu, Chen; Huang, Gordon; Zhu, Hua; Ng, Kelvin Tsun Wai; Deng, Dianliang; Chen, ZhiIn this dissertation research, the following scientific questions are explored: (i) Has the probability distribution of precipitation over China undergone variations since the midtwentieth century? (ii) How are the above changes related to the modes of climate variability? (iii) Can these changes be attributed to anthropogenic behaviors? (iv) What are the mechanisms for these changes in terms of moisture transport and recycling? Specifically, through quantile regression, the quantile trends in monthly precipitation anomalies over China, as well as the individual and combined quantile effects of teleconnection patterns, are examined. The results show that the quantile trends exhibit apparent seasonal variations, with a greater number of stations showing trends in winter, and larger average magnitudes of trends at nearly all quantile levels in summer. The effects of El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO) exhibit evident variations with respect to the quantile level. Spatial clusters are subsequently identified based on the quantile trends, and the individual and combined effects from the teleconnection patterns are further investigated from the perspective of moisture budget. Seven spatial clusters with distinct seasonal quantile trends can be identified; three of them are located in southeastern China and are characterized by increasing trends in summer and winter precipitation. Summer precipitation over this region is positively influenced by ENSO and negatively influenced by NAO, with the former affecting both the dynamic and thermodynamic components of vertically integrated moisture divergence and the latter affecting only the dynamic component. The interaction effect of ENSO and NAO on summer precipitation anomalies in extremely-wetter-than-normal months is statistically significant. The influences of anthropogenic greenhouse gas and aerosol emissions on the probability distribution of daily precipitation over China are explored through a formal detection and attribution analysis. It is found that the increasing trends in winter precipitation at high and extremely high quantile levels, as well as that in spring precipitation at all quantile levels, can be attributed to the effects of historical (ALL) or anthropogenic (ANT) forcing. The effect of anthropogenic greenhouse gas forcing (GHG) is evident over the domain, to which the increasing precipitation trends at all quantile levels in all seasons can be attributed; this effect can be separated from that of anthropogenic aerosol forcing (AER) for winter precipitation trends at high and extremely high quantile levels, and for spring, summer, and autumn trends at low quantile levels. Through integrating detection and attribution analysis and moisture tracking into one framework, the anthropogenic influence on the moisture source-receptor relationship over China is investigated. The subdomains of China can be grouped into 3 categories according to the major moisture sources, which are regions mainly dependent on (a) oceanic sources, (b) external terrestrial sources, and (c) local recycling. It is found that the GHG forcing, in general, favor reduced moisture contributions from oceanic sources to the west of the domain in winter and enhanced those from the ones to the east of the domain in both winter and summer for regions in the first category. Under the GHG scenario, moisture contributions from external terrestrial sources are reduced in summer for subdomains in the first category and show a shift from the north to the south for other regions; under the AER scenario, the opposite case can be observed. Local recycling is generally enhanced in summer under both GHG and AER scenarios, with an exception for the regions in the first category, which exhibit reduced local recycling under the GHG forcing.Item Open Access Temporal and Spatial Analysis of Landfills and Transfer Stations in Saskatchewan(Faculty of Graduate Studies and Research, University of Regina, 2022-03) Ghosh, Abhijeet; Ng, Kelvin Tsun Wai; Veawab, Amornvadee; Xue, Jinkai; Al-Anbagi, IrfanSaskatchewan has the highest number of landfills per capita in Canada. Given the lower population density and the skewed spatial population distribution, comprehensive analysis of municipal solid waste management systems in Saskatchewan is inherently difficult. Most of the published waste studies however focus on city-level waste management, and there is a lack of literature with respect to the rural areas. In first part of the study, landfills and transfer stations were examined temporally and spatially using Geographic Information System. Landfills and transfer stations from 2017 and 2020 were plotted against census division land area, annual budget, and population density to study temporal changes. Saskatchewan witnessed a 54% reduction in the number of landfills and a 55% increase in number of transfer stations between 2017 and 2020. The replacement of landfills with transfer stations were more noticeable in divisions 8, 9, and 16. Further, regression analysis was conducted, and landfill closure operation showed no obvious correlation to division land area, annual budget, or population density. Rural division 18, representing Northern Saskatchewan, was identified as one of the challenging areas. Inclusion of division 18 in data analysis skewed the data set and need to take a different analytical approach has been recommended. The findings suggest different waste management strategies are required for urban and rural areas. The second part of the study concentrates further into the design and operation of waste management systems in rural areas with scarce populations which are often neglected in literature and are less well understood. The study proposed a simplified GIS-based technique to examine the temporal and spatial evolution of waste facilities at a regional level. The key objective was to examine the geospatial distribution of landfills and transfer stations in Saskatchewan, Canada, from 2018 to 2020 based on changes in Euclidean distance computed by both the Central feature (CF) and median center (MdC) spatial statistical tools. Both the CF and MdC results suggest that transfer stations in 2020 were located significantly closer to communities, and an improved level of landfill regionalization is observed. Smoother LF and TS radial curves are generally observed using the MdC tool. About 47.1% of the divisions are classified as challenging areas using the CF method, whereas only 41.1% of the divisions are classified as challenging areas using the MdC method. It appears that the combination of the CF and MdC tools provides a more comprehensive assessment on the temporal-spatial evolution of waste facilities. Six divisions (35.3%) are considered as appropriately managed by both CF and MdC methods. On the contrary, 23.5% of all divisions are suggested by both methods as challenging areas. Most divisions with an improving placement of waste facilities were located near the Canada-US border. The presences of major cities and total division population appear not key factors affecting the evolution of waste facility siting. The results of both the studies will help policy makers to better implement solid waste management strategies in urban and rural areas.Item Open Access Thermal heterogeneity in the proximity of municipal solid waste landfills on forest and agricultural lands(Elsevier BV, 2021-06-01) Karimi, Nima; Ng, Kelvin Tsun Wai; Richter, Amy; Williams, Jason; Ibrahim, HussameldinInformation on the spatial extent of potential impact areas near disposal sites is vital to the development of a sustainable natural resource management policy. Eight Canadian landfills of various sizes and shapes in different climatic conditions are studied to quantify the spatial extent of their bio-thermal zone. Land surface temperature (LST) and normalized difference vegetation index (NDVI) are examined with respect to different Land Use Land Cover (LULC) classes. Within 1500 m of the sites, LST ranged from 18.3 °C to 29.5 °C and 21.3 °C–29.7 °C for forest land and agricultural land, respectively. Linear regression shows a decreasing LST trend in forest land for five out of seven landfills. A similar trend, however, is not observed for agricultural land. Both the magnitude and the variability of LST are higher in agricultural land. The size of the bio-thermal zone is sensitive to the respective LULC class. The approximate bio-thermal zones for forest class and agricultural classes are about 170 ± 90 m and 180 ± 90 m from the landfill perimeter, respectively. For the forest class, NDVI was negatively correlated with LST at six out of seven Canadian landfills, and stronger relationships are observed in the agricultural class. NDVI data has a considerably larger spread and is less consistent than LST. LST data appears more appropriate for identifying landfill bio-thermal zones. A subtle difference in LST is observed among six LULC classes, averaging from 23.9 °C to 27.4 °C. Geometric shape makes no observable difference in LST in this study; however, larger landfill footprint appears to have higher LST.