Several operational and environmental conditions can result in poor biogas yield during the operation of anaerobic digesters and anaerobic bioreactor landfills. Over time, anaerobic co-digestion and leachate blending have been identified as strategies that can help address some of these challenges to improve biogas production. While co-digestion entails the co-treatment of multiple substrates, leachate blending involves combination of mature and young landfill leachate. Despite the benefits attributed to these strategies, their impact on recirculating bioreactor landfill scenarios and anaerobic digesters requires further investigation. In the first phase of this thesis, an attempt to assess biogas production improvement from organic fraction of municipal solid waste in simulated bioreactor landfills through recirculation of blended landfill leachate was conducted. Real old and new leachate blends (67%New leachate:33%Old leachate, 33%New leachate:67%Old leachate) as well as 100%New and 100%Old leachate were recirculated through six laboratory-scale bioreactors using open-loop and closed-loops modes. Compared with the control bioreactor where 100% new leachate was recirculated and operated as a closed-loop, cumulative biogas production was improved by as much as 77 to 193% when a leachate blend of 33%New:67%Old was recirculated. Furthermore, comparison of the results from open-loop and closed-loop operated bioreactors indicated that there was approximately 28 to 65% more biogas in open-loop bioreactors. The Gompertz model applied to the methane data produced a better fit (R2 > 0.99) than first order and logistic function models. Leachate blending reduced the lag phase by almost half and thus helps in alleviating the ensiling during the start-up phase. In the second phase, a biochemical methane potential (BMP) assay was conducted to investigate the synergistic effect of percentage sewage scum addition; 10%, 20% and 40% (volatile solids basis) on biogas production during mesophilic co-digestion with various organic substrates viz; organic fraction of municipal solid waste, old leachate, new leachate and a leachate blend prepared from 67%old leachate and 33%new leachate under sub-optimal condition. Results show that the net cumulative bio-methane yield was improved with increased sewage scum percentage during co-digestion because of positive synergism. Meanwhile, the addition of 40% sewage scum to the individual co-substrates improved net cumulative bio-methane yield by 28% - 67% when compared to their respective mono-substrate digestion bio-methane yield. Furthermore, reactors containing leachate blends consistently produced more biogas over other sets because of blending. Kinetic modelling applied to the bio-methane production data shows modified Gompertz equation achieved a better fit with up to an R2 value of 0.999. Finally, co-digestion substantially reduced the lag time encountered during mono-digestion. In the last phase, the biomethane potential involved in the ACo-D of sewage scum, organic fraction of municipal solid waste was investigated in this phase using either thickened waste activated sludge or leachate blend (67%old leachate and 33%new leachate) as a tertiary component. Compared to the mono-digestion of TWAS, results shows that biomethane yield was enhanced in by as much as 32 - 127% in trinary mixtures with SS and OFMSW mainly due to the effect of positive synergism. Furthermore, LB addition improved biomethane production in trinary mixtures of SS:LB: OFMSW by 38% than in corresponding trinary mixtures of TWAS. Whereas an optimal combination of 40%SS:10%TWAS:50%OFMSW and 20%SS:70%LB:10%OFMSW produced the highest biogas yield of 407mL.gVS-1 and 487mL.gVS-1 respectively. The application of the first order model showed that lower hydrolysis rates promoted methanogenesis with k = 0.04day-1 in both 20%SS:70%LB:10%OFMSW and 20%SS:50%LB:30%OFMSW. Estimations by the modified Gompertz and logistic function were conclusive methane production rate improved by as much a 60% in a trinary mixture over the production rate during mono-digestion of TWAS alone. The results of the various experiments of this thesis therefore suggest that leachate blending can be used as a strategy to improve biogas production in both bioreactor landfills and anaerobic digesters. Also, sewage scum as an energy-rich substrate can be better utilized during co-digestion with other low-energy substrates.

abstract: Zero-Valent Metals (ZVM) are highly reactive materials and have been proved to be effective in contaminant reduction in soils and groundwater remediation. In fact, zero-Valent Iron (ZVI) has proven to be very effective in removing, particularly chlorinated organics, heavy metals, and odorous sulfides. Addition of ZVI has also been proved in enhancing the methane gas generation in anaerobic digestion of activated sludge. However, no studies have been conducted regarding the effect of ZVM stimulation to Municipal Solid Waste (MSW) degradation. Therefore, a collaborative study was developed to manipulate microbial activity in the landfill bioreactors to favor methane production by adding ZVMs. This study focuses on evaluating the effects of added ZVM on the leachate generated from replicated lab scale landfill bioreactors. The specific objective was to investigate the effects of ZVMs addition on the organic and inorganic pollutants in leachate. The hypothesis here evaluated was that adding ZVM including ZVI and Zero Valent Manganese (ZVMn) will enhance the removal rates of the organic pollutants present in the leachate, likely by a putative higher rate of microbial metabolism. Test with six (4.23 gallons) bioreactors assembled with MSW collected from the Salt River Landfill and Southwest Regional Landfill showed that under 5 grams /liter of ZVI and 0.625 grams/liter of ZVMn additions, no significant difference was observed in the pH and temperature data of the leachate generated from these reactors. The conductivity data suggested the steady rise across all reactors over the period of time. The removal efficiency of sCOD was highest (27.112 mg/lit/day) for the reactors added with ZVMn at the end of 150 days for bottom layer, however the removal rate was highest (16.955 mg/lit/day) for ZVI after the end of 150 days of the middle layer. Similar trends in the results was observed in TC analysis. HPLC study indicated the dominance of the concentration of heptanoate and isovalerate were leachate generated from the bottom layer across all reactors. Heptanoate continued to dominate in the ZVMn added leachate even after middle layer injection. IC analysis concluded the chloride was dominant in the leachate generated from all the reactors and there was a steady increase in the chloride content over the period of time. Along with chloride, fluoride, bromide, nitrate, nitrite, phosphate and sulfate were also detected in considerable concentrations. In the summary, the addition of the zero valent metals has proved to be efficient in removal of the organics present in the leachate. / Dissertation/Thesis / Masters Thesis Environmental and Resource Management 2019

A new and promising trend in solid waste management is to operate the landfill as a bioreactor. Bioreactor landfills are controlled systems in which moisture addition and/or air injection are used as enhancements to create a solid waste environment capable of actively degrading the biodegradable organic fraction of the waste. Although there are many advantages associated with bioreactor landfills, some challenges remain. One such challenge is the ammonia-nitrogen concentration found in the leachate. The concentrations of ammonia-nitrogen tend to increase beyond concentrations found in leachate from conventional landfills because recirculating leachate increases the rate of ammonification and results in accumulation of higher levels of ammonia-nitrogen concentrations, even after the organic fraction of the waste is stabilized. Because ammonia-nitrogen persists even after the organic fraction of the waste is stabilized, and because of its toxic nature, it is likely that ammonia-nitrogen will determine when the landfill is biologically stable and when post-closure monitoring may end. Thus an understanding of the fate of nitrogen in bioreactor landfills is critical to a successful and economic operation. Ammonia-nitrogen is typically removed from leachate outside of the landfill. However, additional costs are associated with ex-situ treatment of ammonia, as separate treatment units on site must be maintained or the leachate must be pumped to a publicly owned wastewater treatment facility. Therefore, the development of an in-situ nitrogen removal technique would be an attractive alternative. Several recent in-situ treatment approaches have been explored, but lacked the information necessary for field-scale implementation. The objectives of this study were to develop information necessary to implement in-situ ammonia removal at the field-scale. Research was conducted to evaluate the kinetics of in-situ ammonia removal and to subsequently develop guidance for field-scale implementation. An aerobic reactor and microcosms containing digested municipal solid waste were operated and parameters were measured to determine nitrification kinetics under conditions likely found in bioreactor landfills. The environmental conditions evaluated include: ammonia concentration (500 and 1000mg N/L), temperature (25o, 35o and 45oC), and oxygen concentration in the gas-phase (5, 17 and 100%). Results suggest that in-situ nitrification is feasible and that the potential for simultaneous nitrification and denitrification in field-scale bioreactor landfills is significant due to the presence of both aerobic and anoxic areas. All rate data were fitted to the Monod equation, resulting in an equation that describes the impact of pH, oxygen concentration, ammonia concentration, and temperature on ammonia removal. In order to provide design information for a field-scale study, a simple mass balance model was constructed in FORTRAN to forecast the fate of ammonia injected into a nitrifying portion of a landfill. Based on model results, an economic analysis of the in-situ treatment method was conducted and compared to current ex-situ leachate treatment costs. In-situ nitrification is a cost effective method for removing ammonia-nitrogen when employed in older waste environments. Compared to reported on-site treatment costs, the costs associated with the in-situ ammonia removal process fall within and are on the lower end of the range found in the literature. When compared to treating the leachate off-site, the costs of the in-situ ammonia removal process are always significantly lower. Validation of the laboratory results with a field-scale study is needed.

No description available.

The bioreactor landfill is an emerging concept for solid waste management that has gained significant attention in the last decade. This technology employs specific operational practices to enhance the microbial decomposition processes in landfills. However, the unsupervised management and lack of operational guidelines for the bioreactor landfill, specifically leachate manipulation and recirculation processes, usually results in less than optimal system performance. Therefore, these limitations have led to the development of SMART (Sensor-based Monitoring and Remote-control Technology), an expert control system that utilizes real-time monitoring of key system parameters in the management of bioreactor landfills. SMART replaces conventional open-loop control with a feedback control system that aids the human operator in making decisions and managing complex control issues. The target from this control system is to provide optimum conditions for the biodegradation of the refuse, and also, to enhance the performance of the bioreactor in terms of biogas generation. SMART includes multiple cascading logic controllers and mathematical calculations through which the quantity and quality of the recirculated solution are determined. The expert system computes the required quantities of leachate, buffer, supplemental water, and nutritional amendments in order to provide the bioreactor landfill microbial consortia with their optimum growth requirements. Soft computational methods, particularly fuzzy logic, were incorporated in the logic controllers of SMART so as to accommodate the uncertainty, complexity, and nonlinearity of the bioreactor landfill processes. Fuzzy logic was used to solve complex operational issues in the control program of SMART including: (1) identify the current operational phase of the bioreactor landfill based on quantifiable parameters of the leachate generated and biogas produced, (2) evaluate the toxicological status of the leachate based on certain parameters that directly contribute to or indirectly indicates bacterial inhibition, and (3) predict biogas generation rates based on the operational phase, leachate recirculation, and sludge addition. The later fuzzy logic model was upgraded to a hybrid model that employed the learning algorithm of artificial neural networks to optimize the model parameters. SMART was applied to a pilot-scale bioreactor landfill prototype that incorporated the hardware components (sensors, communication devices, and control elements) and the software components (user interface and control program) of the system. During a one-year monitoring period, the feasibility and effectiveness of the SMART system were evaluated in terms of multiple leachate, biogas, and waste parameters. In addition, leachate heating was evaluated as a potential temperature control tool in bioreactor landfills. The pilot-scale implementation of SMART demonstrated the applicability of the system. SMART led to a significant improvement in the overall performance of the BL in terms of methane production and leachate stabilization. Temperature control via recirculation of heated leachate achieved high degradation rates of organic matter and improved the methanogenic activity.

The bioreactor landfill is an emerging concept for solid waste management that has gained significant attention in the last decade. This technology employs specific operational practices to enhance the microbial decomposition processes in landfills. However, the unsupervised management and lack of operational guidelines for the bioreactor landfill, specifically leachate manipulation and recirculation processes, usually results in less than optimal system performance. Therefore, these limitations have led to the development of SMART (Sensor-based Monitoring and Remote-control Technology), an expert control system that utilizes real-time monitoring of key system parameters in the management of bioreactor landfills. SMART replaces conventional open-loop control with a feedback control system that aids the human operator in making decisions and managing complex control issues. The target from this control system is to provide optimum conditions for the biodegradation of the refuse, and also, to enhance the performance of the bioreactor in terms of biogas generation. SMART includes multiple cascading logic controllers and mathematical calculations through which the quantity and quality of the recirculated solution are determined. The expert system computes the required quantities of leachate, buffer, supplemental water, and nutritional amendments in order to provide the bioreactor landfill microbial consortia with their optimum growth requirements. Soft computational methods, particularly fuzzy logic, were incorporated in the logic controllers of SMART so as to accommodate the uncertainty, complexity, and nonlinearity of the bioreactor landfill processes. Fuzzy logic was used to solve complex operational issues in the control program of SMART including: (1) identify the current operational phase of the bioreactor landfill based on quantifiable parameters of the leachate generated and biogas produced, (2) evaluate the toxicological status of the leachate based on certain parameters that directly contribute to or indirectly indicates bacterial inhibition, and (3) predict biogas generation rates based on the operational phase, leachate recirculation, and sludge addition. The later fuzzy logic model was upgraded to a hybrid model that employed the learning algorithm of artificial neural networks to optimize the model parameters. SMART was applied to a pilot-scale bioreactor landfill prototype that incorporated the hardware components (sensors, communication devices, and control elements) and the software components (user interface and control program) of the system. During a one-year monitoring period, the feasibility and effectiveness of the SMART system were evaluated in terms of multiple leachate, biogas, and waste parameters. In addition, leachate heating was evaluated as a potential temperature control tool in bioreactor landfills. The pilot-scale implementation of SMART demonstrated the applicability of the system. SMART led to a significant improvement in the overall performance of the BL in terms of methane production and leachate stabilization. Temperature control via recirculation of heated leachate achieved high degradation rates of organic matter and improved the methanogenic activity.

The bioreactor landfill is an emerging concept for solid waste management that has gained significant attention in the last decade. This technology employs specific operational practices to enhance the microbial decomposition processes in landfills. However, the unsupervised management and lack of operational guidelines for the bioreactor landfill, specifically leachate manipulation and recirculation processes, usually results in less than optimal system performance. Therefore, these limitations have led to the development of SMART (Sensor-based Monitoring and Remote-control Technology), an expert control system that utilizes real-time monitoring of key system parameters in the management of bioreactor landfills. SMART replaces conventional open-loop control with a feedback control system that aids the human operator in making decisions and managing complex control issues. The target from this control system is to provide optimum conditions for the biodegradation of the refuse, and also, to enhance the performance of the bioreactor in terms of biogas generation. SMART includes multiple cascading logic controllers and mathematical calculations through which the quantity and quality of the recirculated solution are determined. The expert system computes the required quantities of leachate, buffer, supplemental water, and nutritional amendments in order to provide the bioreactor landfill microbial consortia with their optimum growth requirements. Soft computational methods, particularly fuzzy logic, were incorporated in the logic controllers of SMART so as to accommodate the uncertainty, complexity, and nonlinearity of the bioreactor landfill processes. Fuzzy logic was used to solve complex operational issues in the control program of SMART including: (1) identify the current operational phase of the bioreactor landfill based on quantifiable parameters of the leachate generated and biogas produced, (2) evaluate the toxicological status of the leachate based on certain parameters that directly contribute to or indirectly indicates bacterial inhibition, and (3) predict biogas generation rates based on the operational phase, leachate recirculation, and sludge addition. The later fuzzy logic model was upgraded to a hybrid model that employed the learning algorithm of artificial neural networks to optimize the model parameters. SMART was applied to a pilot-scale bioreactor landfill prototype that incorporated the hardware components (sensors, communication devices, and control elements) and the software components (user interface and control program) of the system. During a one-year monitoring period, the feasibility and effectiveness of the SMART system were evaluated in terms of multiple leachate, biogas, and waste parameters. In addition, leachate heating was evaluated as a potential temperature control tool in bioreactor landfills. The pilot-scale implementation of SMART demonstrated the applicability of the system. SMART led to a significant improvement in the overall performance of the BL in terms of methane production and leachate stabilization. Temperature control via recirculation of heated leachate achieved high degradation rates of organic matter and improved the methanogenic activity.

The bioreactor landfill is an emerging concept for solid waste management that has gained significant attention in the last decade. This technology employs specific operational practices to enhance the microbial decomposition processes in landfills. However, the unsupervised management and lack of operational guidelines for the bioreactor landfill, specifically leachate manipulation and recirculation processes, usually results in less than optimal system performance. Therefore, these limitations have led to the development of SMART (Sensor-based Monitoring and Remote-control Technology), an expert control system that utilizes real-time monitoring of key system parameters in the management of bioreactor landfills. SMART replaces conventional open-loop control with a feedback control system that aids the human operator in making decisions and managing complex control issues. The target from this control system is to provide optimum conditions for the biodegradation of the refuse, and also, to enhance the performance of the bioreactor in terms of biogas generation. SMART includes multiple cascading logic controllers and mathematical calculations through which the quantity and quality of the recirculated solution are determined. The expert system computes the required quantities of leachate, buffer, supplemental water, and nutritional amendments in order to provide the bioreactor landfill microbial consortia with their optimum growth requirements. Soft computational methods, particularly fuzzy logic, were incorporated in the logic controllers of SMART so as to accommodate the uncertainty, complexity, and nonlinearity of the bioreactor landfill processes. Fuzzy logic was used to solve complex operational issues in the control program of SMART including: (1) identify the current operational phase of the bioreactor landfill based on quantifiable parameters of the leachate generated and biogas produced, (2) evaluate the toxicological status of the leachate based on certain parameters that directly contribute to or indirectly indicates bacterial inhibition, and (3) predict biogas generation rates based on the operational phase, leachate recirculation, and sludge addition. The later fuzzy logic model was upgraded to a hybrid model that employed the learning algorithm of artificial neural networks to optimize the model parameters. SMART was applied to a pilot-scale bioreactor landfill prototype that incorporated the hardware components (sensors, communication devices, and control elements) and the software components (user interface and control program) of the system. During a one-year monitoring period, the feasibility and effectiveness of the SMART system were evaluated in terms of multiple leachate, biogas, and waste parameters. In addition, leachate heating was evaluated as a potential temperature control tool in bioreactor landfills. The pilot-scale implementation of SMART demonstrated the applicability of the system. SMART led to a significant improvement in the overall performance of the BL in terms of methane production and leachate stabilization. Temperature control via recirculation of heated leachate achieved high degradation rates of organic matter and improved the methanogenic activity.

The numerical computer models that simulate municipal solid waste (MSW) bioreactor landfills have mainly two components--a biodegradation process module and a multi-phase flow module. The biodegradation model describes the chemical and microbiological processes of solid waste biodegradation. The models available to date include predefined solid waste biodegradation reactions and participating species. In a bioreactor landfill several processes, such as anaerobic and aerobic biodegradation, nitrogen and sulfate cycling, precipitation and dissolution of metals, and adsorption and gasification of various anthropogenic organic compounds, occur simultaneously. These processes may involve reactions of several species and the available biochemical models for solid waste biodegradation do not provide users with the flexibility to selectively simulate these processes. This research work includes the development of a generalized biochemical process model, BIOKEMOD-3P, which can accommodate a large number of species and process reactions. This model is able to simulate bioreactor landfill processes in a completely mixed condition; when coupled with a multi-phase model it will be able to simulate a full-scale bioreactor landfill. This generalized biochemical model can simulate laboratory and pilot-scale operations which are important to determine biochemical parameters important for simulation of full-scale operations. To illustrate application of BIOKEMOD-3P, two sets of laboratory MSW bioreactors were simulated in this research work. The first demonstrated simulation of data from anaerobic biodegradation of MSW in experimental bioreactors. In another application, simultaneous nitrification and denitrification processes in MSW bioreactors were simulated. The results from these simulations generated information about various modeling parameters that would help implement these processes in a full-scale bioreactor landfill operation.

Landfill leachate characteristics vary depending on the operation type of the landfill and the age of the landfill. At landfills operated as bioreactors, where leachate recirculation is practiced, leachate ammonia nitrogen concentrations may accumulate to extremely higher levels than during single pass leaching, thereby requiring treatment before final discharge to a receiving system (Onay, 1998). Usually several physical/chemical wastewater treatment technologies are used to treat the leachate. In most cases the COD and BOD are treated, and then nitrification is performed in a separate sophisticated ex situ system. The additional costs of these systems can be very high. The use of a readily available media for in situ nitrification should be considered a prime objective to avoid extra costs. The possibility of removing ammonia nitrogen from bioreactor landfill leachate using trickling filter biofilm technology was studied in four laboratory scale reactors filled with four different types of packing media. The different packing media were examined to see which media is the most efficient at supporting ammonia removal biofilms. The highest efficiency was achieved by a packing media consisting of pine wood chips. The effects of varied concentration loading, varied hydraulic loading, and nitrification inhibitors were studied. Varied ammonia concentration did not have a huge impact on the ammonia removal rates (77-87%) in the reactor with pine wood media. The ammonia removal rates showed a strong dependence on hydraulic loading rate with the lowest loading rate producing the highest removal rates. Landfill leachate from the Middle Peninsula Landfill in Glens, Virginia was determined not to contain nitrifying inhibitors. Using a wood media filter chip and a low hydraulic loading rate was determined to be the best method to remove ammonia nitrogen from landfill bioreator leachate. / Master of Science