Matching Items (5)
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- All Subjects: Civil Engineering
- Genre: Masters Thesis
- Creators: Fox, Peter
Description
This study was devised to elucidate key information concerning the potential risk posed by Legionella in reclaimed water. A series of biological experiments and a recharge basin soil column study were conducted to examine the survival, growth, and transport of L. pneumophila through engineered reclaimed water systems. A pilot-scale, column study was set up to measure Legionella transport in the columns under Arizona recharge basin conditions. Two columns, A and B, were packed to a depth of 122 cm with a loamy sand media collected from a recharge basin in Mesa, Arizona. The grain size distribution of Column A differed from that of Column B by the removal of fines passing the #200 sieve. The different soil profiles represented by column A and B allowed for further investigation of soil attributes which influence the microbial transport mechanism. Both clear PVC columns stand at a height of 1.83 m with an inner diameter of 6.35 cm. Sampling ports were drilled into the column at the soil depths 15, 30, 60, 92, 122 cm. Both columns were acclimated with tertiary treated waste water and set to a flow rate of approximately 1.5 m/d. The columns were used to assess the transport of a bacterial indicator, E. coli, in addition to assessing the study's primary pathogen of concern, Legionella. Approximately, 〖10〗^7 to 〖10〗^9 E. coli cells or 〖10〗^6 to 〖10〗^7Legionella cells were spiked into the columns' head waters for each experiment. Periodically, samples were collected from each column's sampling ports, until a minimum of three pore volume passed through the columns.
The pilot-scale, column study produced novel results which demonstrated the mechanism for Legionella to be transported through recharge basin soil. E. coli was transported, through 122 cm of the media in under 6 hours, whereas, Legionella was transported, through the same distance, in under 30 hours. Legionella has been shown to survive in low nutrient conditions for over a year. Given the novel results of this proof of concept study, a claim can be made for the transport of Legionella into groundwater aquifers through engineering recharge basin conditions, in Central Arizona.
The pilot-scale, column study produced novel results which demonstrated the mechanism for Legionella to be transported through recharge basin soil. E. coli was transported, through 122 cm of the media in under 6 hours, whereas, Legionella was transported, through the same distance, in under 30 hours. Legionella has been shown to survive in low nutrient conditions for over a year. Given the novel results of this proof of concept study, a claim can be made for the transport of Legionella into groundwater aquifers through engineering recharge basin conditions, in Central Arizona.
ContributorsMcBurnett, Lauren Rae (Author) / Abbaszadegan, Morteza (Thesis advisor) / Alum, Absar (Committee member) / Fox, Peter (Committee member) / Arizona State University (Publisher)
Created2014
Description
One of the two objectives of this dissertation is an investigation into the possible correlation between rainfall events and increased levels of E. coli and Mycobacterium using an existing data set. The literature states that levels of microbial concentrations do increase after rainfall events, but there are no studies to indicate this correlation applies in any Arizona water systems. The data analyzed for the bacterial concentrations project suggested the possibility of a correlation along one river but it is not conclusive to state that any correlation exists between rainfall events and the microbial concentration for many other sites included in the analysis. This is most likely due to the highly engineered water delivery systems that are not directly impacted.
The secondary objective was to determine if there are environmental variables collected from an ongoing project which would be a good candidate for making predictions about any of the project data parameters. Of the 79 possible opportunities for the model to accurately predict the dependent variable, it showed strong statistical favorability as well as experimentally favorable results towards Dissolved Organic Carbon as the best dependent variable from the data set, resulting in an accuracy of 41%. This is relevant since Dissolved Organic Carbon is one of the most important water quality parameters of concern for drinking water treatment plants where disinfection by-products are a limiting factor. The need for further analysis and additional data collection is an obvious result from both studies. The use of hydrograph data instead of rainfall would be a logical new direction for the heavily engineered water delivery systems.
The secondary objective was to determine if there are environmental variables collected from an ongoing project which would be a good candidate for making predictions about any of the project data parameters. Of the 79 possible opportunities for the model to accurately predict the dependent variable, it showed strong statistical favorability as well as experimentally favorable results towards Dissolved Organic Carbon as the best dependent variable from the data set, resulting in an accuracy of 41%. This is relevant since Dissolved Organic Carbon is one of the most important water quality parameters of concern for drinking water treatment plants where disinfection by-products are a limiting factor. The need for further analysis and additional data collection is an obvious result from both studies. The use of hydrograph data instead of rainfall would be a logical new direction for the heavily engineered water delivery systems.
ContributorsBuell, Andrew (Author) / Fox, Peter (Thesis advisor) / Abbaszadegan, Morteza (Thesis advisor) / Alum, Absar (Committee member) / Arizona State University (Publisher)
Created2018
Description
Bioretention basins are a common stormwater best management practice (BMP) used to mitigate the hydrologic consequences of urbanization. Dry wells, also known as vadose-zone wells, have been used extensively in bioretention basins in Maricopa County, Arizona to decrease total drain time and recharge groundwater. A mixed integer nonlinear programming (MINLP) model has been developed for the minimum cost design of bioretention basins with dry wells.
The model developed simultaneously determines the peak stormwater inflow from watershed parameters and optimizes the size of the basin and the number and depth of dry wells based on infiltration, evapotranspiration (ET), and dry well characteristics and cost inputs. The modified rational method is used for the design storm hydrograph, and the Green-Ampt method is used for infiltration. ET rates are calculated using the Penman Monteith method or the Hargreaves-Samani method. The dry well flow rate is determined using an equation developed for reverse auger-hole flow.
The first phase of development of the model is to expand a nonlinear programming (NLP) for the optimal design of infiltration basins for use with bioretention basins. Next a single dry well is added to the NLP bioretention basin optimization model. Finally the number of dry wells in the basin is modeled as an integer variable creating a MINLP problem. The NLP models and MINLP model are solved using the General Algebraic Modeling System (GAMS). Two example applications demonstrate the efficiency and practicality of the model.
The model developed simultaneously determines the peak stormwater inflow from watershed parameters and optimizes the size of the basin and the number and depth of dry wells based on infiltration, evapotranspiration (ET), and dry well characteristics and cost inputs. The modified rational method is used for the design storm hydrograph, and the Green-Ampt method is used for infiltration. ET rates are calculated using the Penman Monteith method or the Hargreaves-Samani method. The dry well flow rate is determined using an equation developed for reverse auger-hole flow.
The first phase of development of the model is to expand a nonlinear programming (NLP) for the optimal design of infiltration basins for use with bioretention basins. Next a single dry well is added to the NLP bioretention basin optimization model. Finally the number of dry wells in the basin is modeled as an integer variable creating a MINLP problem. The NLP models and MINLP model are solved using the General Algebraic Modeling System (GAMS). Two example applications demonstrate the efficiency and practicality of the model.
ContributorsLacy, Mason (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2016
Description
Vegetative filter strips (VFS) are an effective methodology used for storm water management particularly for large urban parking lots. An optimization model for the design of vegetative filter strips that minimizes the amount of land required for stormwater management using the VFS is developed in this study. The resulting optimization model is based upon the kinematic wave equation for overland sheet flow along with equations defining the cumulative infiltration and infiltration rate.
In addition to the stormwater management function, Vegetative filter strips (VFS) are effective mechanisms for control of sediment flow and soil erosion from agricultural and urban lands. Erosion is a major problem associated with areas subjected to high runoffs or steep slopes across the globe. In order to effect economy in the design of grass filter strips as a mechanism for sediment control & stormwater management, an optimization model is required that minimizes the land requirements for the VFS. The optimization model presented in this study includes an intricate system of equations including the equations defining the sheet flow on the paved and grassed area combined with the equations defining the sediment transport over the vegetative filter strip using a non-linear programming optimization model. In this study, the optimization model has been applied using a sensitivity analysis of parameters such as different soil types, rainfall characteristics etc., performed to validate the model
In addition to the stormwater management function, Vegetative filter strips (VFS) are effective mechanisms for control of sediment flow and soil erosion from agricultural and urban lands. Erosion is a major problem associated with areas subjected to high runoffs or steep slopes across the globe. In order to effect economy in the design of grass filter strips as a mechanism for sediment control & stormwater management, an optimization model is required that minimizes the land requirements for the VFS. The optimization model presented in this study includes an intricate system of equations including the equations defining the sheet flow on the paved and grassed area combined with the equations defining the sediment transport over the vegetative filter strip using a non-linear programming optimization model. In this study, the optimization model has been applied using a sensitivity analysis of parameters such as different soil types, rainfall characteristics etc., performed to validate the model
ContributorsKhatavkar, Puneet N (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Committee member) / Wang, Zhihua (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2015
Description
Large-scale cultivation of photosynthetic microorganisms for the production of biodiesel and other valuable commodities must be made more efficient. Recycling the water and nutrients acquired from biomass harvesting promotes a more sustainable and economically viable enterprise. This study reports on growing the cyanobacterium Synechocystis sp. PCC 6803 using permeate obtained from concentrating the biomass by cross-flow membrane filtration. I used a kinetic model based on the available light intensity (LI) to predict biomass productivity and evaluate overall performance.
During the initial phase of the study, I integrated a membrane filter with a bench-top photobioreactor (PBR) and created a continuously operating system. Recycling permeate reduced the amount of fresh medium delivered to the PBR by 45%. Biomass production rates as high as 400 mg-DW/L/d (9.2 g-DW/m2/d) were sustained under constant lighting over a 12-day period.
In the next phase, I operated the system as a sequencing batch reactor (SBR), which improved control over nutrient delivery and increased the concentration factor of filtered biomass (from 1.8 to 6.8). I developed unique system parameters to compute the amount of recycled permeate in the reactor and the actual hydraulic retention time during SBR operation. The amount of medium delivered to the system was reduced by up to 80%, and growth rates were consistent at variable amounts of repeatedly recycled permeate. The light-based model accurately predicted growth when biofilm was not present. Coupled with mass ratios for PCC 6803, these predictions facilitated efficient delivery of nitrogen and phosphorus. Daily biomass production rates and specific growth rates equal to 360 mg-DW/L/d (8.3 g/m2/d) and 1.0 d-1, respectively, were consistently achieved at a relatively low incident LI (180 µE/m2/s). Higher productivities (up to 550 mg-DW/L/d) occurred under increased LI (725 µE/m2/s), although the onset of biofilm impeded modeled performance.
Permeate did not cause any gradual growth inhibition. Repeated results showed cultures rapidly entered a stressed state, which was followed by widespread cell lysis. This phenomenon occurred independently of permeate recycling and was not caused by nutrient starvation. It may best be explained by negative allelopathic effects or viral infection as a result of mixed culture conditions.
During the initial phase of the study, I integrated a membrane filter with a bench-top photobioreactor (PBR) and created a continuously operating system. Recycling permeate reduced the amount of fresh medium delivered to the PBR by 45%. Biomass production rates as high as 400 mg-DW/L/d (9.2 g-DW/m2/d) were sustained under constant lighting over a 12-day period.
In the next phase, I operated the system as a sequencing batch reactor (SBR), which improved control over nutrient delivery and increased the concentration factor of filtered biomass (from 1.8 to 6.8). I developed unique system parameters to compute the amount of recycled permeate in the reactor and the actual hydraulic retention time during SBR operation. The amount of medium delivered to the system was reduced by up to 80%, and growth rates were consistent at variable amounts of repeatedly recycled permeate. The light-based model accurately predicted growth when biofilm was not present. Coupled with mass ratios for PCC 6803, these predictions facilitated efficient delivery of nitrogen and phosphorus. Daily biomass production rates and specific growth rates equal to 360 mg-DW/L/d (8.3 g/m2/d) and 1.0 d-1, respectively, were consistently achieved at a relatively low incident LI (180 µE/m2/s). Higher productivities (up to 550 mg-DW/L/d) occurred under increased LI (725 µE/m2/s), although the onset of biofilm impeded modeled performance.
Permeate did not cause any gradual growth inhibition. Repeated results showed cultures rapidly entered a stressed state, which was followed by widespread cell lysis. This phenomenon occurred independently of permeate recycling and was not caused by nutrient starvation. It may best be explained by negative allelopathic effects or viral infection as a result of mixed culture conditions.
ContributorsThompson, Matthew (Author) / Rittmann, Bruce E. (Thesis advisor) / Fox, Peter (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2015