Stochastic simulation of residual household waste properties

Reliable input data for treatment plants (e.g. municipal solid waste incinerators) need to consider the heterogeneity and variability of waste composition. Asides thoroughly designed sampling protocols, the separation of bulk waste into uniform fractions, and adequate methods for sample preparation and analysis, this requires suitable data evaluation methods. This study presents a probabilistic approach to the quantification of waste properties including total organic carbon as a major constituent, lead as an inorganic contaminant as well as polycyclic aromatic hydrocarbons (PAH) and polychlorinated biphenyls (PCB) as organic pollutants. Variability was considered both in terms of waste composition and spreading of physico- chemical data. As a basis, composition analyses of residual household waste (RHW) carried out between 1998 and 2002 were used. A total of 769 RHW samples with a volume of 1.1 m3 each were collected throughout 15 Bavarian administrative districts characterized by a variety of waste management systems. A stratified sampling scheme was used to account for anticipated effects of settlement structure, i.e. rural, urban and inner urban areas. Local waste management systems were classified according to drop-off and curbside collection of recyclables. Seasonal trends were considered by conduction of summer/winter campaigns.