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Stratification and multi-representative optimization approach to waste composition analysis

Publication at Faculty of Science |
2021

Abstract

The amounts of mixed municipal waste in the EU countries differ during the last decades. Waste composition is influenced especially by the recent trends in the packaging of products that are daily purchased and the attitude towards sorting of municipal solid waste.

Waste composition is one of the most important factors that shape future waste management planning. The sortable waste fraction in the mixed municipal waste specifies the potential for an increase in separation efficiency.

The composition of the waste can be determined via analysis, but only a limited number of such analyses can be carried out. Moreover, the respective analysis is a challenging task and presents a complex statistical problem which must reflect many aspects of human activity.

Appropriate waste sampling based on spatial stratification is crucial to estimate the waste composition quality in different regions. The waste samples for analysis are defined using principles of operational research to cover the regional variability.

Mathematical models are developed to identify optimum clustering of waste generation areas. The principals and practice from local investigations are used to reveal waste composition.

Decisions are made as to where to sample the waste and how many representative samples are necessary to faithfully describe the waste composition in the entire area. This means that suitable division into sub-areas and optimal choice of representative sub-areas in the sense of waste composition must be made.

These results are then used to design the waste treatment infrastructure. The described approach to waste composition is also shown via a micro-region-level case study.