A decision support tool for selecting the optimal sewage sludge treatment

Tutkimustuotos: Lehtiartikkelivertaisarvioitu

Tutkijat

Organisaatiot

Kuvaus

Sewage sludge contains significant amounts of resources, such as nutrients and organic matter. At the same time, the organic contaminants (OC) found in sewage sludge are of growing concern. Consequently, in many European countries incineration is currently favored over recycling in agriculture. This study presents a Multi-Attribute Value Theory (MAVT)-based decision support tool (DST) for facilitating sludge treatment decisions. Essential decision criteria were recognized and prioritized, i.e., weighted, by experts from water
utilities. Since the fate of organic contaminants was in focus, a simple scoring method was developed to take into account their environmental risks. The final DST assigns each sludge treatment method a preference score expressing its superiority compared to alternative methods. The DST was validated by testing it with data from two Finnish municipal wastewater treatment plants (WWTP). The validation results of the first case study preferred sludge pyrolysis (preference score: 0.629) to other alternatives: composting and incineration (score 0.580, and 0.484 respectively). The preference scores were influenced by WWTP dependent factors, i.e., the operating environment and the weighting of the criteria. A lack of data emerged as the main practical limitation. Therefore, not all of the relevant criteria could be included in the value tree. More data are needed on the effects of treatment methods on the availability of nutrients, the quality of organic matter and sludge-borne OCs. Despite these shortcomings, the DST proved useful and adaptable in decision-making. It can also help achieve a more transparent, understandable and comprehensive decision-making process.

Yksityiskohdat

AlkuperäiskieliEnglanti
Sivut521-529
Sivumäärä9
JulkaisuChemosphere
Vuosikerta193
TilaJulkaistu - helmikuuta 2018
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

ID: 16434257