Bioreactor landfills: experimental simulations, full scale monitoring and fuzzy modelling

In the perspective of a sustainable waste management, the amount of biodegradable municipal solid waste (MSW) destined to landfilling should be reduced. In such context, new technologies were developed in recent years with the aim of a more rapid stabilization of the waste, such as pretreatments and bioreactor landfills (BRLs). In the Italian waste management scenario, although solution have been adopted towards waste recycling and recovery, landfilling is still playing an important role. The case study of Cerro Tanaro (CT) landfill depicts a typical situation of an average Italian district without incineration facilities. The MSW disposed in CT landfill is the residual fraction, pretreated through aerobic mechanical-biological treatment (MBT) in order to reduce the biodegradability prior to landfilling. This disposal site, originally built as a conventional landfill, was equipped with a leachate recirculation system. Although the benefit of moisture increase had been previously demonstrated, most of the studies in literature tested the effects on raw MSW, with relatively high organic contents, above 40%. Moreover, the use of existing models for the simulation of landfill behaviour are not suitable for unconventional landfill technologies, unless very high uncertainties are introduced. Based on the case study of CT landfill, the need of novel approaches for the study and the simulation of emerging landfilling solution had been identified. The main aim of this thesis was to offer a novel and simple tool for the prediction of landfill behaviour when unconventional management practises are introduced, regarding both the quality of the MSW landfilled and the operational conditions. Therefore, experimental tests were conducted at lab-scale, the full-scale case study of CT landfill was monitored and a fuzzy-logic (FL) based model was developed for the prediction of landfill gas production. The experimental tests at lab-scale demonstrated that coupling MBT with leachate recirculation could reactivate the biodegradation processes even for low biodegradable waste (LBW), thanks to moisture increase. Although it was difficult to establish a stable methanogenic phase, CH4 production reached 28 NL kg-1 after 442 days of experimentation, that is 85% of its bio-methane potential (BMP). Also leachate quality presented reduced pollution strength with low COD and NH4+ concentrations. The results highlighted the differences between the tested LBW and fresh not pretreated MSW and between the optimized lab-scale and the heterogeneities of the full-scale landfill. Two deterministic models were tested for the estimation of CH4 production from LBW under leachate recirculation: Gompertz kinetic model and BIO-5 model. The production curves obtained by the two models confirmed the limits of deterministic methods and underlined the need of different approaches, able to deal with the uncertainties typical of landfill gas modelling. A FL-based model to predict methane generation in BRLs was proposed. Eleven deterministic inputs (pH, ORP, COD, VFA, NH4+ content, age of the waste, temperature, moisture content, organic fraction, particle size and recirculation flow rate) were identified as antecedent variables. Two outputs, or consequents, were chosen: methane production rate and methane fraction. The fuzzy model was built and tested on the lab-scale experimentation of LBW under leachate recirculation. Additionally, the data of other six lab-scale studies from literature were used to widen the applicability of the proposed model. The proposed fuzzy model was then applied on the full-scale case study of CT landfill. Although this case study was characterized by lack of information from the previous literature, fuzzy modelling represented a valid tool which could be easily adapted to the specific system under study.Another aspect concerning modern landfills has been treated, that is the presence of emerging contaminants among MSW. A FL-based model was developed to evaluate biogas and methane production from BRLs in presence of ZnO nanoparticles (NPs). The fuzzy model was tested on the data of a lab-scale study simulating a bioreactor landfill with 100 mg of added nano-ZnO/kg of dry waste, conducted in the Institute of Environmental Sciences (Boğaziçi University – Istanbul). By comparing the results of the proposed FL-based models with the deterministic models, the FL approach showed better performances for both lab-scale and full- scale methane predictions, confirming its high potential in the modelling of landfill environments under different emerging scenarios. The proposed FL-based models represent a basis to describe methane production in such systems, which, thanks to its learning structure, can be easily upgraded with additional parameters and information coming from future findings in this topic

Experimental simulation and fuzzy modelling of landfill biogas production from low-biodegradable MBT waste under leachate recirculation

In the perspective of a sustainable waste management, biodegradable waste destined to landfilling should be reduced. This work aims to study a combination of waste pretreatments and leachate recirculation. A lab-scale experiment and fuzzy-modelling were chosen to predict cumulative methane production from low-biodegradable waste (LBW) under leachate recirculation. Thanks to moisture increase, the degradation of LBW was reactivated and the cumulative methane production reached 28 NL CH4 kg−1 after 442 days. The organic fraction was stabilized with a final chemical oxygen demand (COD) of 81 mg L−1. Fuzzy model was proposed as an alternative to the common deterministic models, affected by high uncertainties. Eleven inputs (pH, Redox potential, COD, volatile fatty acids, ammonium content, age, temperature, moisture content, organic fraction concentration, particle size and recirculation flow rate) were identified as antecedent, and two outputs, or consequents, were chosen: methane production rate and methane fraction in biogas. Antecedents and consequents were linked by 84 IF-THEN rules in a linguistic form. The model was also tested on six literature studies chosen to test different operational conditions and waste qualities. The model outputs fitted the experimental data reasonably well, confirming the potential use of fuzzy macro-approach to model sustainable landfilling

Fuzzy Approach to Predict Methane Production in Bioreactor Landfills

Bioreactor landfills (BRLs) aim to increase moisture content of municipal solid waste to enhance the biodegradation kinetics of the organic fraction. Biogas production can therefore be increased improving the energy recovery efficiency. Prediction of biogas production is a key tool in the design of appropriate energy recovery system from BRLs. In this paper, we propose the use of a fuzzy model to predict methane generation in BRLs. Eleven deterministic inputs (pH, RedOx potential, chemical oxygen demand, volatile fatty acids, ammonium content, age of the waste, temperature, moisture content, organic fraction concentration, particle size and recirculation flow rate) were identified as antecedent variables. The deterministic dominia were transported in the fuzzy dominium by a fuzzyfication procedure, thus assessing grade of membership and labels for each antecedent. Two outputs, or consequents, were chosen: methane production rate and methane concentration in biogas. Antecedents and consequents were linked by 72 IF-THEN rules, which stated the effects of the input parameters in a linguistic form. The fuzzy model was tested by using six previous laboratory studies from the literature, which were chosen since they stand for different operational conditions and waste qualities. The fuzzy model showed good performances in the prediction of methane generation. The model outputs fitted the experimental data reasonably well, with R2 of 0.96 and 0.93. The results confirm the potential use of fuzzy macroapproach for complex processes taking place in BRLs

Scenarios of bioenergy recovery from organic fraction of residual municipal waste in the Marche region (Italy)

This paper assesses alternative scenarios for the bioenergy recovery by anaerobic digestion (AD) from the organic fraction of residual municipal waste (OFRMW) in the Marche Region (Central Italy, Adriatic Sea Side). The OFRMW investigated consists in the undersize fraction derived from the mechanical selection of the unsorted residual municipal waste (RMW), which is currently treated aerobically before being landfilled as biostabilised waste (bios-OFRMW). This study aims to investigate at what extent the OFRMW produced in the Marche Region could be bio-energetically recovered by AD, or, in the alternative scenario, how much residual methane generation could be expected by aerobically treated bios-OFRMW once landfilled, thus contributing also to the potential environmental impact connected with possible uncontrolled emissions from the regional landfills. With the potential diversion from aerobic to anaerobic biostabilisation, the OFRMW would contribute to the regional energy production with a total electric power equal to 4.8 MW. On the contrary, the current management approach involves greenhouse gases emissions equal to 284 kg CO2 eq per ton of landfilled bios-OFRMW

Scenarios of Bioenergy Recovery from Organic Fraction of Residual Municipal Waste in the Marche Region (Italy)

In the Marche Region (Central Italy), the residual municipal waste (RMW) is commonly processed in mechanical biological treatment (MBT) systems. In these systems, following a first mechanical selection, the undersize organic fraction from RMW (us-OFRMW) undergoes a partial aerobic biological treatment before being landfilled as a biostabilised fraction (bios-OFRMW) without dedicated energy or material recovery. Alternative us-OFRMW management scenarios have been elaborated for this region, at both present (reference year 2019) and future (reference year 2035) time bases. In the first scenario, the potential bioenergy recovery through anaerobic digestion (AD) from the us-OFRMW was evaluated. The second scenario aimed at evaluating the residual methane generation expected from the bios-OFRMW once landfilled, thus contributing also to the potential environmental impact connected with landfill gas (LFG) diffuse emissions from the regional landfills. The diversion to AD, at the present time, would allow a potential bioenergy recovery from the us-OFRMW equal to 4.35 MWel, while the alternative scenario involves greenhouse gas (GHG) emissions equal to 195 kg CO2 eq. per ton of deposited bios-OFRMW. In the future, the decreased amount of the us-OFRMW addressed to AD would still contribute with a potential bioenergy recovery of 3.47 MWel

Scenarios of Bioenergy Recovery from Organic Fraction of Residual Municipal Waste in the Marche Region (Italy)

In the Marche Region (Central Italy), the residual municipal waste (RMW) is commonly processed in mechanical biological treatment (MBT) systems. In these systems, following a first mechanical selection, the undersize organic fraction from RMW (us-OFRMW) undergoes a partial aerobic biological treatment before being landfilled as a biostabilised fraction (bios-OFRMW) without dedicated energy or material recovery. Alternative us-OFRMW management scenarios have been elaborated for this region, at both present (reference year 2019) and future (reference year 2035) time bases. In the first scenario, the potential bioenergy recovery through anaerobic digestion (AD) from the us-OFRMW was evaluated. The second scenario aimed at evaluating the residual methane generation expected from the bios-OFRMW once landfilled, thus contributing also to the potential environmental impact connected with landfill gas (LFG) diffuse emissions from the regional landfills. The diversion to AD, at the present time, would allow a potential bioenergy recovery from the us-OFRMW equal to 4.35 MWel, while the alternative scenario involves greenhouse gas (GHG) emissions equal to 195 kg CO2 eq. per ton of deposited bios-OFRMW. In the future, the decreased amount of the us-OFRMW addressed to AD would still contribute with a potential bioenergy recovery of 3.47 MWel.</jats:p