Development of Fuzzylogic model to predict the effects of ZnO nanoparticles on methane production from simulated landfill

Nano-ZnO enters landfills mostly through disposal of cosmetics, sunscreens and catalysts. However, its effects on waste degradation are still unclear. In this paper, a fuzzy-based model is proposed to predict biogas and methane production from simulated bioreactor landfill with and without ZnO nanomaterials. Eight deterministic inputs (pH, RedOx potential, chemical oxygen demand, volatile fatty acids, alkalinity, Zn concentration, Zn background and leachate recirculation flow rate) were identified as antecedent variables. Two outputs, or consequents, were chosen: biogas production rate and methane fraction. Antecedents and consequents were linked by 66 IF-THEN rules, which stated the effects of the input parameters in a linguistic form. The fuzzy model was tested on the data of a lab-scale study simulating a bioreactor landfill with 100 mg of added nano-ZnO per kg of dry waste. Experimental results indicated that the addition of nano-ZnO resulted in a reduction of methane generation by about 30%.The fuzzy model showed good performance in the prediction of methane generation; in addition, the comparison with the commonly used Gompertz equation showed that the fuzzy model is more consistent with the data. Fuzzy modelling could easily handle the Zn concentration together with other parameters and it highlighted the importance of including this input in the model. The modelling results confirmed the high potential of fuzzy macro-approach in the modelling of very complex processes taking place in landfill environments under different operating conditions.