Bioelectricity generation from wastewater and actual landfill leachates: A multivariate analysis using principal component analysis

Principal component analysis (PCA) suggested that the 9 original variables could be reduced to 2 explanatory variables, i.e., two main principal components, further simplifying the analysis of experimental results. These PCs could be assigned either phys-chem or performance meanings. PCA revealed that performance variables ηCOD and CE contrasted with influent characteristic variables suggesting that an increase of the first group were associated to decrease of the second group, i.e., performance was better with MWW on the average compared to results with leachates. For instance, MFCs fed with MWW exhibited average ηCOD and CE of 72 and 27%, respectively, whereas the values from MFCs loaded with leachate or mixture MWW-L were 53 and 9.5%, respectively. Moreover, PCA reinforced the conclusion of a negative effect of mixing together MWW and leachates, an issue that deserves further research. To the best of our knowledge this is the first report on the use of MFCs to the treatment of atypical actual leachates from a landfill in Mexico and its mixtures with MWW.