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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.

Phytoremediation is a technology that can be used in several ways to remediate polluted soils and water. Today, phytoremediation is viewed by many as a technology in the development phase and therefore it is important to evaluate existing facilities to create more support for future establishment. At the closed landfill of Dragmossen situated outside Älvkarleby, Sweden, there is a plantation of salix (Salix spp.) used for leachate management by collecting the leachate in ponds and using it to irrigate the salix. The goal is to let the water evaporate partially and then use the remaining water in the plantation, thus keeping pollutants in the system and stored in the biomass of the plants. In this Degree Project within Environmental and Water Engineering the performance and the risks associated with the salix plantation at the landfill Dragmossen were evaluated. The study was conducted by analyzing data of samples taken from the salix biomass, soil and water in regards to metal concentrations. The allocation of different metals in the plant was investigated and the transfer coefficient (TC-quota) and the translocation factor (TF-quota) were calculated for the salix. The mass flow of metals was mapped and quantified by construction of a model to calculate the load of metals within the system and the extraction of metals from the plantation. The input data for the model consisted of metal concentrations in the leachate, metal concentrations within salix biomass, estimated volume of leachate and the growth of the salix biomass. The results showed that lead, cadmium, copper, chrome, nickel and zinc were extracted in a higher amount than the load from the irrigation. The extraction of arsenic was lower than the amount that was added from the irrigation. The extraction rate for arsenic, lead, cadmium, copper, chrome, nickel and zinc was investigated by calculating the extraction per year and hectare. The extraction rate differs between the metals where zinc was extracted with the highest rate and arsenic with the lowest. A basic risk assessment was conducted where the development of the pollutants in the ground water below the salix plantation was investigated together with the concentrations of metals in the soil on the plantation. This showed that the concentrations of copper and zink over the general reference value for less sensitive land use was exceeded in some areas. The overall results showed that a salix plantation can be a good tool for leachate management for the majority of the metals. The extraction of metals is affected by different parameters of the soil and water chemistry which makes it important to evaluate site-specific conditions before an establishing a salix plantation. / Fytosanering är en teknik som kan användas på flera olika vis för att sanera både förorenad mark och vatten. Idag betraktas fytosanering av många som en teknik under utveckling och det är därmed viktigt att utvärdera befintliga anläggningars prestanda för att skapa ett bättre underlag för framtida etableringar. På den sluttäckta deponin Dragmossen används en salixodling för lakvattenhantering genom att salix (Salix spp.) bevattnas med lakvatten som samlas upp i dammar på området. Vattnet avgår då genom transpiration och tanken är att föroreningarna ska tas upp och lagras i växterna. I detta examensarbete i miljö- och vattenteknik undersöktes prestandan och riskerna med salixodlingen på deponin Dragmossen. Detta genom att sammanställa och analysera data från provtagningar av salix, jord och vatten. Examensarbetet omfattade även en analys av upptag och allokering av metaller i salixplantorna, samt hur dessa metaller förhåller sig i de olika växtdelarna genom att beräkna överföringskoefficienten (TC-kvot) och translokationsfaktorn (TF-kvot). Massflöden av metaller kartlades genom konstruerande av en modell som kvantifierar belastning och upptag av metaller i salixen. Modellens indata bestod av metallhalter i lakvattnet, metallhalter i salixens ved, uppskattad volym lakvatten och tillväxt av salixens biomassa. Resultatet från modellen visade att bly, kadmium, koppar, krom, nickel och zink togs upp i större mängd än vad som tillfördes genom bevattning. Upptaget av arsenik var dock mindre än det som tillfördes genom bevattningen. Upptagshastigheten för arsenik, bly, kadmium, koppar, krom, nickel och zink undersöktes genom att beräkna upptaget per år och hektar. Upptagshastigheten skiljer sig åt mellan olika metaller där zink tas upp snabbast och arsenik är den metall som extraheras i lägst grad. En enklare riskbedömning genomfördes där utvecklingen av föroreningshalter i grundvattnet under salixodlingen undersöktes samt halter av de undersökta metallerna i jorden på salixodlingen. Denna visade på att halter av koppar och zink idag är högre än det generella riktvärdet för mindre känslig markanvändning. Det styrande skyddsobjektet för Cu och Zn är markmiljön. Uppmätta metallhalter i marken kring salixodlingen bedöms inte innebära någon risk för andra skyddsobjekt som människa och grundvatten. Sammantaget visar resultatet att en salixodling som verktyg för lakvattenhantering kan vara ett bra redskap för flertalet metaller. Upptaget påverkas av olika mark- och vattenkemiska parametrar vilket erfordrar att platsspecifika förutsättningar beaktas vid anläggning av en salixodling.