Assessing the effect of environmental attitudes on waste material flow quality through agent-based modelling of...

This study presents an innovative agent-based model for simulating source separation behaviours of residential waste materials, capturing the influence of environmental attitudes on waste management. The model combines sociodemographic data, household-specific geographical coordinates, and the Theory of Planned Behaviour to simulate households' decision-making processes. Developed in AnyLogic, the model uses calibrated parameters from field data and census information to simulate waste generation and sorting intentions. Validation experiments confirmed the model's predictive accuracy in estimating sorting behaviours for various waste types and neighborhoods. The results revealed that households with strong environmental attitudes achieved an average recycling recovery rate of 90 %, while less-engaged groups not only exhibited lower recycling recovery rates but also contributed to contamination rates as high as 25 %. These findings highlight population groups that could benefit from targeted education and incentives to enhance sorting practices and improve the quality of recyclable material flows. Despite limitations in data accuracy, the model offers promising perspectives for more efficient waste management, providing insights for optimizing sorting behaviours and enhancing recyclable material flows in communities.