Quantification of Waste Generation in the EU - A PPCA and regression analysis on prediction of recyclable waste
Abstract: In this study, data of the generation of recyclable wastes from the EU member states, and possible explaining factors for describing this generation, are examined through a combination of Probabilistic Principal Component Analysis (PPCA) and multivariate regression analysis. The purpose is to identify some of the biggest contributors to the generation of recyclable wastes, and, based on these contributors, find a linear function that describes the generation of different recyclable wastes, as well as assess the predictive power of this function. Initially, PPCA was used to reduce the number of datasets in order to include only the most important explaining factors. Later, multivariate regression analysis was used to define the coefficients of the waste-generation function. This function describes just above 86% of the total waste generation of recyclables, and an average of nearly 68% of the generation of the individual wastes. The generation of paper and cardboard, glass and plastic are well described by the function. The generation of rubber, textile and wood are less well described. This study points out GDP, primary energy consumption, LMP expenditure and low education level as important predictors of the waste generation of recyclable wastes. These four factors are also important to consider in the future, as they could help define areas of particular interest in the strive towards a sustainable society.
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