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Mini-review of sewage sludge parameters related to system modelling

System modelling of sewage sludge (SS) treatment attracts a growing interest for better comparison and optimisation of technologies. However, SS parameters need to be generalised to be used in holistic assessments, since scattered data may inhibit the development and interpretation of system models....

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Detalles Bibliográficos
Autores principales: Chang, Huimin, Zhao, Yan, Xu, Ankun, Damgaard, Anders, Christensen, Thomas H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10170565/
https://www.ncbi.nlm.nih.gov/pubmed/36482728
http://dx.doi.org/10.1177/0734242X221139171
Descripción
Sumario:System modelling of sewage sludge (SS) treatment attracts a growing interest for better comparison and optimisation of technologies. However, SS parameters need to be generalised to be used in holistic assessments, since scattered data may inhibit the development and interpretation of system models. A review of the literature on SS parameters relevant to modelling SS treatment systems revealed 208 datasets published in 162 publicly available scientific papers. We treated thickened and dewatered sludge in the same data analysis, but in some cases, this was an incorrect assumption. The compositional data showed significant variations, but most of the data subscribed to a lognormal distribution, albeit with varying levels of significance. On average, the thickened sludge contained 3.3 ± 1.7% total solid (TS), and the dewatered sludge contained 21.0 ± 6.7% TS. For the combined data, the average Ash content was 32.4 ± 11.8% of TS. Other characteristic parameters were the lower heating value (LHV) of 22.1 ± 2.1 MJ kg(−1) volatile solid (VS) and the biochemical methane potential (BMP) of 0.25 ± 0.11 m(3) CH(4) kg(−1) VS. Fertiliser-related elements were on average 53.3 ± 9.3% C in VS, 6.8 ± 2.2% N in VS, 6.7 ± 2.4% P in Ash and 1.7 ± 1.3% K in Ash. The data reviewed herein provide a good basis for assessing the generality of individual SS data and for selecting key parameters for modelling SS treatment systems. However, the review reveals a need for the better characterisation of SS in the future.