Monitoring of the composting process of different agroindustrial waste: Influence of the operational variables on the odorous impact

Abstract

Composting is a conventional but economical and environmentally friendly way to transform organic waste into a valuable, organic soil amendment. However, the physico-chemical characterization required to monitor the process involves considerable investment in terms of cost and time. In this study, 52 samples of four compostable substrates were collected randomly during the composting process and analyzed physico-chemically. The physico-chemical characterization was evaluated and reduced by principal component analysis (PCA) (PC1 + PC2: 70% variance). Moreover, a study of the relationship between odor and the raw material and odor and the operational variables was carried out at pilot scale using PCA and multivariate regression. The substrates were grouped by PCA (PC1 + PC2: 87% variance). The odor emission rate (OER) and dynamic respirometric index (DRI) were found to be the most influential variables in the sample variance, being relevant to identify the different emission sources. Dynamic respirometry and multivariate regression could be suitable tools to predict these odor emissions for the majority of compostable substrates, identifying successfully the emission source.