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.