Browsing by Author "He, Jianxun"
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- ItemOpen AccessA Mesocosm Study of Bioretention Functionality Under Frozen Conditions(2023-06) Elliot, Sean; Cey, Edwin; He, Jianxun; Hayashi, MasakiUrbanization interrupts the natural hydrologic cycle through the development of large impervious areas that prevent infiltration and introduce contaminants to stormwater. Bioretention is a green stormwater management strategy designed to restore natural hydrologic conditions in urban areas by promoting infiltration and removing contaminants at the source. Bioretention technology has proven to be effective in warm climates, but questions remain regarding how the systems perform in cold climates. This study investigated how bioretention systems function under frozen conditions using 24 mesocosm cells in Okotoks, Alberta. The mesocosm cells were lined and had three types of media, three types of vegetation, and two different impervious to pervious ratios. Media types included two typical bioretention media as well as an experimental mixture of clay loam and woodchips. Simulated spring melt events were conducted at the end of March 2021 and March 2022, with an additional event included at the beginning of March 2022 to observe the influence of midwinter melts on bioretention performance. Datasets were analyzed to compare frozen performance among the different design parameters and simulated events, and were also compared to unfrozen conditions using existing datasets from a separate study conducted at the site. The results of this study showed an average 80% decrease in infiltration rate under frozen conditions relative to unfrozen, with significant difference in infiltration rate depending on media type. The findings show that hydrologic performance is largely based on media type, and more specifically, the ability of the media to support preferential flow under frozen conditions. Preferential flow also limited the effects of refreezing midwinter meltwater, as no significant difference in infiltration rate was seen following the midwinter melt event. Nutrient performance was comparable between frozen and unfrozen conditions, with most cells leaching relatively low concentrations of nutrients. Nutrient removal was largely dependent on media type, but plant nutrient uptake also appeared to play an important role. Overall, the results of this study showed that bioretention systems function well under frozen conditions, but the reduced infiltration rates and effects of preferential flow must be taken into consideration when designing the systems.
- ItemOpen AccessArtificial Neural Network Modeling for Organic and Total Nitrogen Removal of Aerobic Granulation(2018-06-12) Gong, Heli; Tay, Joo Hwa; Du, Ke; He, JianxunAerobic granulation is a recent technology with high level of complexity and sensitivity to environmental and operational conditions. To understand this technology properly, mathematical modeling would be an invaluable tool. In this study, Artificial neural network (ANN), a computational tool capable of describing complex nonlinear systems, was selected to simulate the treatment performance of aerobic granulation technology. The model capability in predicting chemical oxygen demand (COD) and total nitrogen (TN) removal efficiencies of aerobic granular reactors under start-up and steady-state condition was thoroughly investigated. The capability of ANN has been examined and compared to a novel and a traditional modeling approach, namely Support Vector Machine (SVM) and Multiple Linear Regression (MLR), respectively. The models were fed with vast datasets collected from laboratory-, pilot, and fullscale studies on aerobic granulation reported in the literature. Statistical error analysis demonstrated that the ANN method yielded comparable or superior prediction accuracy, compared to other methods. The results of this study showed that ANN-based models were capable simulation approach to predict a complicated process like aerobic granulation.
- ItemOpen AccessBio-Refinery of Wastewater in Presence of Carbon Dioxide Utilizing Microalgae(2018-07-12) Hosseini Yazdi, Seyed Mohammad Sadegh; Chu, Angus; Nowicki, Edwin Peter; He, JianxunIn this research, three sets of experiments were conducted to assess the ability of Chlorella Vulgaris (Chlorella V.) to grow in different physical conditions such as light intensity, pH, temperature and mixing by measuring oxygen evolution. Chlorella V. thrives if the medium (Bold’s Basal Media) has a pH range of 7-8, temperature range of 25-30 ͦ C, light intensity of 4755 LUX, and 5% CO2 is introduced into the culture. Chlorella V. has illustrated the same growth rate in both sterile and non-sterile wastewater media under optimal physical conditions. It demonstrated uptake of 100% of dissolved nitrogen compounds and almost 30% of dissolved phosphorus compounds presented in the medium. This ability nominates Chlorella V. for potential tertiary treatment of wastewater. Finally, the ability of this specie for CO2 uptake was determined. Chlorella V. could sequester 20% CO2 in the total gas volume of the photobioreactor headspace in optimal physical conditions. The CO2 fixation rate was higher in the middle of the exponential growth phase compared to other growth phases.
- ItemOpen AccessBiochemical Methane Potential of Landfilled Municipal Solid Waste Using a Non-Slurry Approach(2019-04-25) Pearse, Lauretta Feyisetan; Hettiaratchi, Joseph Patrick A.; He, Jianxun; Chu, AngusThe most widely-used procedure for forecasting landfill methane production in the laboratory is the biochemical methane potential (BMP) assay. Conventional BMP assays for assessing landfilled municipal solid waste (LMSW) use a slurry-based approach which simulates an environment that is predominantly liquid versus a predominance of solids in a landfill, which is likely to misrepresent actual landfill conditions, and could consequently lead to false gas volume predictions. This research was undertaken as a first-step towards modifying the current BMP assays to be more representative of natural landfill conditions termed; the Landfill BMP (LBMP) assay. Three sets of statistically-designed laboratory batch experiments were conducted using organic fraction of MSW to compare the CH4 generation potential (Lo), the rate of CH4 production (Rm) and the first-order rate coefficient (k) values from slurry-phase and solid-phase BMP experiments. The results showed statistically significant differences occurred between slurry-phase and solid phase BMP assays with Lo values obtained from slurry-phase experiments being overestimated by as much as 47 ±12%. Biosolids from Bonnybrook wastewater treatment plant, Calgary, was found to perform poorly compared to a laboratory-derived inoculum. Particle size reduction had a significant effect on Lo and Rm values with smaller particle sizes (< 10 mm) being optimal for CH4 gas production in solid-phase experiments in this study. The Lo values obtained from the LBMP method fell within the range of those obtained from lysimeter and field studies, indicating a possibility of solid-phase BMPs being more likely reliable in forecasting CH4 production from landfills than conventional BMP methods. However, k values were overestimated from both slurry and solid-phase conditions of moisture, suggesting that obtaining k values from laboratory experiments might not be the best approach. The highest coefficient of variation between duplicates in this study was less than 30% indicating good repeatability.
- ItemOpen AccessDevelopment of a Remote Sensing-Based Agriculture Monitoring Drought Index and Its Application Over Semi-Arid Region(2016) Hazaymeh, Khaled; Hassan, Quazi; Islam, Tanvir; Blais, Rodrigue; He, Jianxun; Nowicki, EdwinAgricultural drought is a natural disaster that usually occurs when the available water content goes below the optimal needs of the proper growth of plants during its growing season. It has enormous impacts on economic, environmental, and social sectors. In this study, our overall objective was to develop a fully remote sensing-based method for monitoring agricultural drought conditions and evaluate its performance over a semi-arid heterogeneous rainfed agricultural dominant landscape in Jordan. In general, remote sensing data having both high spatial and temporal resolutions would be required for evaluating agricultural drought conditions, as usually agriculture land cover would be relatively heterogeneous and small in size, while drought could occur during critical short time periods i.e., few days or weeks during the growing season. However, due to different technical and cost issues such high spatio-temporal remote sensing data are still unavailable. Thus, we opted to develop a spatio-temporal image-fusion model (STI-FM) to generate synthetic Landsat-8 like data with 30 m spatial and 8 day temporal resolutions upon combining regular Landsat-8 (having 30 m spatial with 16 day temporal resolutions) with moderate-resolution imaging spectroradiometer (MODIS)-based 8-day composite data having 250-1000 m spatial resolutions. Then, we used these fused data in developing the agricultural drought monitoring index (ADI) as a combination of three uncorrelated remote sensing-based agricultural drought related variables [i.e., normalized difference water index (NDWI), visible and shortwave drought index (VSDI), and land surface temperature (LST)]. Results showed that the proposed STI-FM was able to produce synthetic Landsat-8 data with strong accuracy (i.e., r2 were in the range 0.71 to 0.90). The evaluation of agricultural drought conditions over the study area using the proposed remote sensing-based agricultural drought index showed high agreements such as 85% overall accuracy and 78% Kappa-values, when compared to ground based 8-day standardised precipitation index (SPI) values. These strong results demonstrated that the proposed methods would be great in monitoring agricultural drought conditions at agricultural field scale (i.e., high spatial resolution) and short time periods (i.e., high temporal resolution).
- ItemOpen AccessDevelopment of Flow Forecasting Models in the Bow River at Calgary, Alberta, Canada(Multidisciplinary Digital Publishing Institute, 2014-12-24) Veiga, Victor B.; Hassan, Quazi K.; He, JianxunRiver flow forecasting is critical for flood forecasting, reservoir operations, and water resources management. However, flow forecasting can be difficult, challenging and time consuming due to the spatial and temporal variability of climatic conditions and watershed characteristics. From a practical point of view, a simple and intuitive approach might be more preferable than a complex modeling approach. In this study, our objective was to develop short-term (i.e., daily) flow forecasting models in the Bow River at the city of Calgary, Alberta, Canada. Here, we evaluated the performance of several regression models, along with a newly proposed “base difference” model, by using antecedent daily river flow values from three gauge stations (i.e., Banff, Seebe, and Calgary). Our analyses revealed that using a multivariable linear regression formulated as a function of upstream gauge stations (i.e., Banff or Seebe) and the station of interest (i.e., Calgary) using antecedent flows demonstrated strong relationships (i.e., having r2 (coefficient of determination) and RMSE (root-mean-square deviation) of approximately 0.93 and 14 m3/s, respectively). As such, we opted to suggest that the use of Banff and Calgary stations in forecasting the flows at Calgary could be considered as it would require a relatively lower number of gauge stations.
- ItemOpen AccessField Performance and Water Balance Predictions of Evapotranspirative Landfill Biocovers(2019-09-16) Jalilzadeh, Hiva; Hettiaratchi, Joseph Patrick A.; Chu, Angus; He, JianxunThe present research aims to extend the application of Evapotranspirative (ET) covers to Canadian landfill biocovers and assess their performance under climatic conditions present in Canada. Seven large-scale lysimeters were constructed simulating a capillary barrier landfill biocover and monitored for water balance from May 2018 to May 2019. Two soil types (Topsoil and Compost mixture) and three types of vegetation (Native grass species, Alfalfa, and Japanese Millet) were used to investigate the most effective design. Rainfall simulations were carried out to assess the performance of vegetated and non-vegetated covers. Water balance predictions made using two codes (SEEP/W and HYDRUS) were compared to water balance data from lysimeters over the growing season. The rainfall simulation results suggested that the compost mixture was able to hold 40 % more moisture than topsoil, on average. Percolation as a percentage of rainfall (percolation percentage) was significantly lower for vegetated media compared to bare or poorly vegetated media. During the growing season, Alfalfa had the highest average ET rate, followed by Japanese Millet and Native grass species. Among soil, plant and meteorological factors, solar radiation, surface cover fraction, rooting depth and plant height had a significant effect on ET rates. The results suggested that as plants became established, the average percolation percentage decreased for all crop types. Annual percolation percentage was 13-14 % for lysimeters which were not subjected to rainfall simulations. Among lysimeters subjected to rainfall simulations, lysimeters with Japanese Millet transmitted the lowest amount of percolation (10 %-17 %), followed by Native Grass species and Alfalfa (23 %-28 %). Under the same vegetation coverage, lysimeters with compost mixture generally transmitted lower or equal percolation compared to lysimeters with topsoil. Modelling results from June 2018 to September 2018 (110 days) showed that predicted evapotranspiration was in better agreement with field results when the Penman-Monteith (PM) method was used instead of Penman-Wilson (PW). In general, soil water storage and percolation were overpredicted by both codes using the PM method and underpredicted using the PW method. Model limitations included predictions under high-intensity rainfall events, estimating canopy interception and considering preferential pathways associated with plant roots.
- ItemOpen AccessGeometry Reconstruction and Finite Element Modelling of Porcine Knee Joint(2017) Zheng, Xiaoyue; Li, Leping; Federico, Salvatore; Kwok, Daniel; He, JianxunArthritis is a leading cause of disability in North America. It is believed to be associated with the abnormal contact mechanics of articular cartilage. Contact analyses are widely used to determine the mechanical interplays among the different tissues in the joint. Animal joints are often used to validate a computational model and understand human joint mechanics. The objectives of this research are to construct the geometry of the porcine stifle joint using a combined CT and automated indentation mapping method, and build a finite element model in ABAQUS to determine the joint mechanics. The porcine knee joint model were reconstructed using MATLAB and Rhinoceros. A knee compression was simulated with ABAQUS, which considered fluid pressure and flow in articular cartilages and menisci. The reaction predicted by the model generally agrees with the measurements from laboratory tests, which partially validates the modelling methodology.
- ItemOpen AccessGreen Roof for Urban Stormwater Management in Semi-Arid and Cold Climate(2020-09-23) Akther, Musa Shammi; He, Jianxun; Chu, Angus; Achari, Gopal; van Duin, BertAs a typical type of Low Impact Development technologies, green roofs have become widely used recently to restore the changes in stormwater runoff resulted from urbanization. To present, many studies have showcased their benefits in managing stormwater in particularly in the mild and temperate climatic zones. However, studies in other climatic zones (e.g., semi-arid and cold climate) are still lacking for their implementation with confidence. Additionally, acknowledging that green roofs might leach pollutants especially at their early ages, knowledge and understanding of this technology in this aspect is still very limited. Therefore, this dissertation aimed to filling these research gaps through conducting both the field observation and the laboratory experiment. The investigated field green roof situated in the City of Calgary, Alberta and the laboratory cells constructed using three media types leached several pollutant constituents including nutrients and conductivity during the study period; while the field green roof behaved as the sink of metals. Antecedent moisture condition and media type were identified to be the most influential factors on green roof hydrological and water quality performance, respectively. The degree of the chemical leaching declined exponentially with cumulative inflow initially, and then linearly later. The high explanatory ability of the cumulative inflow implied that the primary source of the pollutant constituents leached was the media of green roofs, namely the pollutants in media gradually leached out/washed off from green roofs. Based upon this notion, a semi-physically based leaching model was proposed. In this model, the maximum pollutant amount was determined according to its initial content in media, and its leaching was expressed as the wash-off function applied in stormwater runoff quality modeling. The model application further confirmed the primary source and the governing process of chemical leaching from green roofs. However, the modeling results also revealed the need to further improve the phosphorus leaching modeling, especially for the field green roof, as it appeared to be also affected by other chemical and biological processes besides the wash-off process. The identified differences between the laboratory and field observations called attention when translating knowledge from the laboratory investigation into real practice.
- ItemOpen AccessGroundwater Contribution to Winter Streamflows in Alpine Watersheds(2016) Paznekas, Andrius; Hayashi, Masaki; Bentley, Larry; He, JianxunAlpine watersheds represent an important source of freshwater in western Canada. Since rainfall, snowmelt, and glacier melt make minimal contributions to streamflow during winter months, essentially all winter flow in unregulated streams is provided by groundwater discharge. The analysis of winter flow in small to medium scale watersheds (21 to 3900 km2) provides critical information regarding the magnitude of groundwater discharge and its relation to the physiographical characteristics of watersheds such as climate, geology, and topography. Furthermore, hydrologic modelling of a small alpine watershed (4.5 km2) provides insight into the storage mechanisms controlling consistent winter flows. Winter flows were in a narrow range (0.2-0.6 mm d-1) throughout the study area, which suggests that the groundwater storage is filled to the maximum capacity every year, and that the groundwater discharge in winter is mostly controlled by the stationary factors such as the spatial variability of geology, topography, and climatic variables.
- ItemOpen AccessHydrological and water quality performance of newly constructed bioretention mesocosms(2020-09-24) Li, Xing; He, Jianxun; Valeo, Caterina; Chu, Angus; Veselinova, ElenaTo examine the effects of growing media, vegetation and other potential influential factors (including event magnitude, and media temperature and moisture) on bioretention performance, 24 bioretention mesocosms were constructed using three types of growing media and planted with three types of vegetation in 2017. As a part of the research project, this thesis used the field observations in 2018 to assess their hydrological and water quality performance and to identify the primary influential factors on bioretention performance in the first year of their operation. A series of 25 simulated events (of different magnitudes) were performed between June and October of 2018. On average, the mesocosms retained 16% of inflow while significant chemical leaching from all mesocosms was observed. Among the potential influential factors, the event magnitude and growing media were identified to be the most dominant factor affecting the hydrological and water quality performance of the bioretention mesocosms, respectively. Among the three types of growing media, the clay-loam (mixed with woodchips) media had lower water retention rate but leached less compared to other two types of growing media.
- ItemOpen AccessInvestigation into the Impacts of a Global Pandemic on the Ability to Properly Operate and Maintain Water and Wastewater Treatment and Management in Indigenous Communities in Canada, With a Focus on First Nations(2022-09-12) Adebayo, Feyisetan; Black, Kerry; Achari, Gopal; Huang, Wendy; He, JianxunThe COVID-19 pandemic spurted research studies on impacts monitoring and emergency planning in the water sector, especially in utility operations. However, studies on Indigenous communities were not significantly explored despite the history of vulnerability to previous pandemics. Considering that the financial and infrastructural gaps had rendered the First Nations' water systems vulnerable to contamination and other crises, the COVID-19 pandemic highlighted the possibility of increased vulnerability for water and wastewater utilities. Since emergency planning strategies and frameworks for First Nations were primarily outdated, the COVID-19 pandemic underscored the need for new studies and updated information. Therefore, the purpose of this research was two-fold. First, it investigated the impacts of the COVID-19 pandemic on water and wastewater utilities in Canada’s First Nations. Second, it explored pandemic planning and impact minimization mechanisms for future emergency planning. In this research, qualitative data collected through an online survey and open-ended semi-structured interviews from forty-two water professionals were analyzed to evaluate the impacts of the COVID-19 pandemic on the operations and management of water and wastewater systems and utilities in Canada First Nations. Through Thematic Content Analysis and Grounded Theory, across-transcript research themes (i.e., common findings between participants) were developed to understand the variations of impacts across the sampled First Nations water professionals and how they compared with their non-Indigenous counterparts. Also, strategies for impact minimization in emergency planning were developed into a First Nation pandemic planning framework to improve the preparedness of water and wastewater systems and utilities for similar emergencies in the future. The end-users completed testing and validation: operators, supervisors, and managers. Findings from this study have been reviewed and verified through oral and written communication with the participants and industry partners. The executive summary and one-pager infographic from this study were distributed to the participants, stakeholders and decision-makers for implementation and policy development opportunities.
- ItemOpen AccessInvestigation of Evapotranspiration in a Bioretention System through Soil Moisture Content(2019-03-25) Nadori, Richard; Chu, Angus; He, Jianxun; Nowicki, Edwin PeterBioretention systems control stormwater runoff through infiltration, groundwater recharge, and water loss via evapotranspiration (ET) processes. The significance of ET as a volume reduction method has been limited in research. This study at a University of Calgary research facility in Okotoks, Alberta, assessed ET in the “40” soil media bioretention system. Soil moisture content sensors installed at 20cm and 40cm depths provided ET estimates. Seasonality impacted ET with the highest estimations occurring in July 2018 and the lowest in September 2018. 20cm ET estimations were generally higher than 40cm ET estimations due to shallow vegetation root systems. ANOVA tests showed woody, herbaceous, and turf grass vegetation types were not significant at 20cm on ET while woody and turf grass vegetations were significant at 40cm. The Hargreaves and Penman-Monteith equations do provide suitable upper and lower limits of ET estimation at 20cm. ET, at 20cm, reduced over 100% of water volumes and was capable of reducing antecedent moisture content in smaller storm events; 26 – 60% of water volumes were reduced in large storm events. At 40cm, ET reduced between 21 – 67% and over 100% of water volumes and was capable of slightly reducing antecedent moisture content in smaller events; 0-50% of water volumes were reduced in large storm events.
- ItemOpen AccessAn Investigation on Methane Flux in Landfills and Correlation with Surface Methane Concentration(2020-04-29) Irandoost, Erfan; Hettiaratchi, Joseph Patrick A.; He, Jianxun; Zhou, QiWith growing concerns over greenhouse gas emissions increase on one hand, and methane’s high global warming potential on the other, direct methane emission measurement techniques from area sources such as landfills are receiving increased scrutiny. The static enclosure chamber method is the only technique that allows direct measurement of landfill gas fluxes. However, due to the large footprint of landfills, as well as the temporal and spatial variability of landfill methane emissions, the static enclosure method may not be the best option under some situations because it is time-consuming and labor-intensive. Collecting surface methane concentration (SMC) data through the instantaneous emission measurement (IEM) technique is relatively easy and inexpensive, however it is merely a qualitative means of evaluating surface methane emissions. This study investigated the development of a relationship between SMCs and methane flux across the soil-atmosphere boundary in a small-scale test cell under a partially controlled environment, in an attempt to translate SMC data into quantitative estimates. In addition, the study investigated the effect of wind speed on surface and flux measurements and the correlation between the two. The results demonstrated a significant positive correlation between SMCs and surface flux measurements. However, a better correlation was achieved when the analysis was performed under calm wind conditions and mild-to-moderate wind conditions separately. Under calm wind conditions, a linear correlation was found between SMCs and flux measurements with a resulting R2 of 0.94 and 0.90 for regression through origin and regression with intercept, respectively. These findings were in agreement with those of various researchers who have suggested surface flux has a positive and, in some cases, strong relationship with methane concentrations. The results also suggested that the presence of wind caused a decrease in average measured flux for the majority of inlet flowrates. It also significantly decreased concentrations measured in the test cell, while shifting the gas to defuse from areas that are further away from the wind source. Under windy conditions, the results of statistical analysis showed that SMCs have a linear correlation with flux divided by wind speed with a resulting R2 of 0.88, and other independent variables were found to be statistically insignificant. This finding was in agreement with the findings of researchers who observed an inverse relationship between SMCs and wind speeds. It is also in line with the Gaussian steady-state dispersion model which shows a direct relationship between SMC and emission rate divided by wind velocity.
- ItemOpen AccessLand Hydrology Studies in North America Using GRACE and Hydrology Models(2020-04-22) Piretzidis, Dimitrios; Sideris, Michael G.; Kim, Jeong-woo; Rangelova, Elena V.; He, Jianxun; Huang, JianliangThe need for a reliable land hydrology model that can monitor the amount of water stored on and beneath the Earth’s surface on a regional and global scale has become very important, especially in overpopulated areas or regions that already suffer from shortage of freshwater. The main objective of this thesis is to examine the hydrology signal in North America using a combination of land hydrology models and satellite gravimetry products coming from the GRACE satellite mission. Our analysis emphasizes on the post-processing of GRACE data. More specifically, we define a detailed framework for the extraction of hydrological signals from GRACE data by removing the contribution of non-hydrologic geophysical components and using advanced processing techniques. In order to carry out this objective, we improve the most frequently-used filtering methods for the suppression of correlated errors from GRACE data, and develop more refined algorithms for their implementation. We formulate a selective decorrelation of GRACE data using machine learning and show that our new approach mitigates the over-filtering effects of the conventional decorrelation. We also solve the instability and inaccuracy problems related to the calculation of isotropic Gaussian filter coefficients and develop new expressions that simplify their evaluation. We assess the GRACE data and the hydrology models, and find a satisfactory level of agreement between them, with an averaged RMS difference of 3.9 cm in terms of equivalent water height. We then combine these independent datasets and develop two combined hydrology models for the monitoring of monthly terrestrial water storage and groundwater storage variations. We examine their seasonal and long-term variations and provide useful insights for the spatiotemporal evolution of water masses in North America from 2003 to 2014. For the most part, North America is affected by negative long-term trends of terrestrial and ground water changes that are more evident in Hudson Bay and southern North America, whereas strong accumulation of water masses is observed in central North America. The combined models developed in this study provide a basis for the continuous satellite-based monitoring of land hydrology in North America and can be used for the improved management of water resources.
- ItemOpen AccessModelling Palaeohydrological Controls in Postglacial Mountain Drainage Basins(2017) Klassen, Peter; Martin, Yvonne; Johnson, Edward; Sjogren, Darren; He, JianxunQuaternary glacial processes were a driving factor in the formation of the landscape of the Canadian Rocky Mountains. Modelling of basin scale hydrology in glaciated mountain regions, including the associated morphology and sedimentology, has not previously been undertaken. The present study investigates drainage basin hydrology for the Kananaskis Valley immediately after glaciation. Low order drainage basins are analyzed to define a prototypical basin to facilitate groundwater modelling. The surface and groundwater modelling software HydroGeoSphere is used to model the prototypical drainage basin hydrology. Results show that glaciated mountain valley morphology and glacigenic sediments are pertinent controls on both the surface and groundwater dynamics in low order drainage basins. Sediments with high hydraulic conductivity were found to play the most significant role for the fate of precipitation in mountain drainage basins. Understanding how a history of glaciation affects mountain drainage basins is crucial for fully conceptualizing the hydrology of these regions.
- ItemOpen AccessOn Geothermal Heat Extraction from the Basal Cambrian Sandstone Unit in Central Alberta, Canada(2021-04-29) Chong, Qinwan; Gates, Ian; Clarke, Matthew; Shor, Roman; Kibria, Golam; He, Jianxun; Prodanovic, VladanThere is no doubt that the trend of ever-increasing energy use will continue with continued human activity. However, traditional energy resources such as fossil fuels are limited and result in serious environmental issues. As renewable energy option, geothermal resources, unlike other kinds of renewable resources, can not only provide clean but also sustained energy for both electricity and direct heating. Alberta, Canada has a long oil industry history but its continued expansion is now in question given current environmental and investment pressures. Recent studies from existing well bore information in central Alberta indicate there is potential for large-scale development of geothermal energy. In the research documented here, a detailed examination of Basal Cambrian Sandstone Unit (BCSU) of the Western Canadian Sedimentary Basin (WCSB) has been studied as a geothermal resource in Central Alberta, Canada. Three studies were conducted: 1. Evaluation of energy extraction from a geothermal resource using open loop well configurations based on analyzed geological data, 2. Numerical analysis of a closed loop U-Tube Deep Borehole Heat Exchanger (DBHE), and 3. An assessment of variable flow rate strategies for closed loop U-Tube DBHE system. The results from this research show that the reservoir is exploitable under most cases of examined well configurations. However, energy utilization is different when different well configurations are applied. For the study of open loop configurations, the temperature of produced water can meet the requirement of generating low-enthalpy power. Compared to five-well pattern systems, two-well pattern systems produce more energy with higher energy efficiency. When closed loop U-Tube DBHE system is conducted, it is more energetically effective than open loop systems. However, its low produced flow temperature and low produced energy indicating the utilization of direct heating on a small-scale. The analysis of operating variable flow rate strategies on closed loop systems reveals the complicated heat transfer performance due to the different flow rate injection during time periods. High-low stepped flow rate of the working fluid appears to have merit because enables the geothermal resource to ‘recharge’ with thermal energy during its operation.
- ItemOpen AccessPassive or Semi-Passive Photocatalytic Treatment of Organic Pollutants in Water(2018-09-18) Heydari, Gisoo; Achari, Gopal; He, Jianxun; Ponnurangam, SathishIn this research, various titanium dioxide (TiO2) supports are studied in both passive and semi-passive modes in the laboratory and in the field. Passive solar photocatalysis experiments using TiO2 coated hollow glass micro-spheres (photospheres) were conducted to degrade Killex®, sulfolane and cyclopentane carboxylic acid (CPA), a typical naphthenic acid. The results showed more than 99.8% degradation of Killex® ingredients and 97.4% degradation of sulfolane by 3.18 MJ/m2 UV energy from sunlight. 100% of CPA was degraded by capturing 1.01 MJ/m2 solar UV energy. Various configurations of photocatalysts including photospheres, anodized titanium plate and mesh, and electro-photocatalysis were also investigated under ultraviolet light emitting diode (UVA-LED) sources. Energy consumption to achieve 60% degradation of 2, 4- D was used to rank the photocatalysts. The results showed both photospheres and mesh consumed approximately 80 J/cm3 energy followed by electro-photocatalysis (112.15 J/cm3), and the anodized plate (114.47 J/cm3). The semi-passive setup was successfully utilized to degrade total organic carbon in oil sands process wastewater (over 95%) by capturing 28.94 MJ/m2 energy from UVA-LED. This study established a base comparison between various photocatalyst supports, field and laboratory applications, as well as providing promising results for using anodized TiO2 mesh for passive and semi-passive applications.
- ItemOpen AccessPermeable Pavement in Cold Climates - Improving Hydraulic and Water Quality Performance(2015-09-28) Huang, Jian; Valeo, Caterina; He, JianxunThe application of permeable pavements has been promoted to reduce pressures on traditional stormwater management systems and enhance urban water. However, the performance of permeable pavement under cold climate context is still uncertain. This thesis focused on assessing the hydraulic and water quality performance of permeable pavements based on field and laboratory experiments and developing a modeling approach for assisting engineering design of permeable pavements. In a series of field experiments, simulated 100-year storm events with durations of 20 minutes were applied to the pavement surfaces in order to examine and compare the hydraulic and environmental performance of the three permeable pavement types under cold climate conditions. Results demonstrated that PA, PC and PICP are all effective in mitigating storm runoff under cold climate conditions. All pavement types in general have the same level of performance in removing TSS, TP, TN, and heavy metals. A series of laboratory experiments were designed to assess the ability of the three pavement types to remove TSS, TP and TN within their surface and sub-surface layers individually. PA, PC and PICP with sub-surface layers consisting of different gravel sizes were investigated at various thicknesses. The lab-scale pavements were also compared with the field-scale pavements in terms of pollutant removal. Superior performance in removing pollutants was found in the PC surface layer compared to surface layers of PA and PICP. A regression model based on these results was developed to provide estimates of water quality performance in the field. A mathematical model for predicting hydraulic and water quality performance in both the short- and long-term is proposed based on field measurements for the three types of permeable pavements. The proposed model can simulate the outflow hydrographs with a coefficient of determination (R2) ranging from 0.762 to 0.907, and normalized root-mean-square deviation (NRMSD) ranging from 13.78% to 17.83%. Comparison of the time to peak flow, peak flow, runoff volume and TSS removal rates between the measured and modeled values in model validation phase had a maximum difference of 11%.
- ItemOpen AccessPredictive Modelling of Advanced Wastewater Treatment Technologies Using Artificial Intelligence(2020-12-10) Zaghloul, Mohamed S.; Achari, Gopal; Hettiaratchi, Joseph P.; He, Jianxun; Krishnamurthy, Diwakar; Chen, BingTraditional mathematical models have many limitations, and current machine learning models are black-box type approaches with little insight into the process dynamics. The need for reliable predictive tools to avoid expensive operation interruptions at wastewater treatment plants is growing. This dissertation presents predictive models for aerobic granular sludge (AGS), and biological nutrient removal (BNR) activated sludge processes using machine learning. The main objective of this thesis is to develop and present models that can be used on-site for long-term operation and provide enough information about the process for the detection of faults before they occur. The data for this thesis were collected from laboratory and pilot-scale reactors for the AGS model and historical operational data of the Pine Creek Wastewater Treatment Plant (Calgary, Alberta) for the BNR model.The data were cleaned by removing outliers and filling gaps, and features were selected using multicollinearity reduction and relative parameter importances. A multi-stage model structure was developed where outputs are predicted in the sequence of the actual process progression, considering the cause-effect factor in the process. Multi-layer artificial neural networks, adaptive neuro-fuzzy inference systems, and support vector regression were applied individually and in ensembles as alternative algorithms. The performance of each of the three individual algorithms was compared to each other, and the best model was used to make final predictions. The ensemble techniques used were artificial neural networks, adaptive neuro-fuzzy inference systems, support vector regression, arithmetic mean, and weighted average.The model simulated the AGS process by predicting the biomass concentrations, settling properties, granulation ratio, granule size, and effluent quality with R2 between 89% and 99.9%. It was also able to track predicted abnormalities to their potential cause, utilizing the multi-stage feature in the model. The model was also able to simulate the full-scale BNR process at the Pine Creek WWTP with some parameter modifications, predicting 15 outputs representing the state of the biomass, the waste and return sludge amounts, and the effluent quality, with R2 up to 82%.