This study aims to investigate the co-composting of an inorganic industrial waste (eggshell - ES) in very high levels (up to 60% w/w). Since composting is a process in which solid, liquid and gaseous phases interact in a very complex way, there is a need to shed light on statistical tools that can unravel the main relationships structuring the variability associated to this process. In this study, PCA and data visualisation were used with that purpose. The co-composting tests were designed with increasing quantities of ES (0, 10, 20, 30 and 60%ES w/w) mixed with industrial potato peel and rice husks. Principal component analysis showed that physical properties like free air space, bulk density and moisture are the most relevant variables for explaining the variability due to ES content. On the other hand, variability in time dynamics is mostly driven by some chemical and phytoxicological parameters, such as organic matter decay and nitrate content. Higher ES incorporation (60% ES) enhanced the initial biological activity of the mixture, but the higher bulk density and lower water holding capacity had a negative effect on the aerobic biological activity as the process evolved. Nevertheless, pathogen-killing temperatures (>70°C for 11h) were attained. All the final products obtained after 90days were stable and non-phytotoxic. This work proved that valorisation of high amounts of eggshell by co-composting is feasible, but prone to be influenced by the physical properties of the mixtures.
Keywords: Co-composting; Data visualisation; Eggshell waste; Principal component analysis.
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