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Landfills are widely employed as the primary means of solid waste disposal. However, this practice generates landfill gas (LFG) which contains methane (CH4), a potent greenhouse gas, as well as various volatile organic compounds and volatile inorganic compounds. These emissions from landfills contribute to approximately 25% of the total atmospheric CH4, indicating the imperative need to valorize or treat LFG prior to its release into the atmosphere. This review first aims to outline landfills, waste disposal and valorization, conventional gas treatment techniques commonly employed for LFG treatment, such as flares and thermal oxidation. Furthermore, it explores biotechnological approaches as more technically and economically feasible alternatives for mitigating LFG emissions, especially in the case of small and aged landfills where CH4 concentrations are often below 3% v/v. Finally, this review highlights biofilters as the most suitable biotechnological solution for LFG treatment and discusses several advantages and challenges associated with their implementation in the landfill environment. [ABSTRACT FROM AUTHOR]

This study examined the artificial neural network (ANN) modeling of simultaneous biofiltration of methane (CH4) with two volatile organic compounds (VOCs): xylene and ethylbenzene, using an inorganic packed bed biofilter at an empty bed residence time (EBRT) of 4.5 min. Results showed that the removal efficiency (RE) of CH4 was in the range of 50 to 60% for concentrations of 1000 to 10,000 ppmv (0.6 to 6.5 g m−3), while the VOCs-REs were between 70 and 90% for X and EB concentrations in the range of 200 to 500 ppmv (0.9 to 2.2 g m−3). Artificial neural networks were used to predict and simulate the performances of the biofilter, based on a database containing previous biofiltration works. The ANN1 (architecture of 3 (input layer)-18 (hidden layer)-1 (output layer)) accurately predicted CH4 conversion at the pseudo-steadystate condition, while the ANN2 (4 (input layer)-18 (hidden layer)-2 (output layer)) predicted the simultaneous conversion of CH4 and VOCs with slightly lower accuracy than ANN1. The ANN3 (4 (input layer)-30 (hidden layer)-1 (output layer)) successfully predicted the acclimation period and final phase (CH4 concentration of 10,000 ppmv) of the biofilter but could not accurately predict the transient phases and showed differences (up to 20%) from experimental results once the CH4 concentration was changed. This study developed a decision support and prediction tool to anticipate the performance of biofilters in treating residual gases containing CH4 and VOCs, avoiding costs and delays associated with experimentation. [ABSTRACT FROM AUTHOR]