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Erschienen in: Journal of Material Cycles and Waste Management 4/2017

08.09.2016 | REGIONAL CASE STUDY

BMP estimation of landfilled municipal solid waste by multivariate statistical methods using specific waste parameters: case study of a sanitary landfill in Turkey

verfasst von: Ilker Sel, Mehmet Çakmakcı, Bestamin Özkaya, Fatih Güreli

Erschienen in: Journal of Material Cycles and Waste Management | Ausgabe 4/2017

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Abstract

The main objective of this study was to determine whether methane potential of waste could be estimated more easily by a limited number of waste characterization variables. 36 samples were collected from 12 locations and 3 waste depths in order to represent almost all waste ages at the landfill. Actual remaining methane potential of all samples was determined by the biochemical methane potential (BMP) tests. The cumulative methane production of closed landfill (cLF) samples reached 75–125 mL at the end of experiment duration, while the samples from active landfill (aLF) produced in average 216–266 mL methane. The average experimental k and L 0 values of cLF and aLF were determined by non-linear regression using BMP data with first-order kinetic equation as 0.0269 day−1–30.38 mL/g dry MSW and 0.0125 day−1–102.1 mL/g dry MSW, respectively. The principal component analysis (PCA) was applied to analyze the results for cLF and aLF along with BMP results. Three PCs for the data set were extracted explaining 72.34 % variability. The best MLR model for BMP prediction was determined for seven variables (pH–Cl–TKN–NH4–TOC–LOI–Ca). R 2 and Adj. R 2 values of this best model were determined as 80.4 and 75.3 %, respectively.

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Metadaten
Titel
BMP estimation of landfilled municipal solid waste by multivariate statistical methods using specific waste parameters: case study of a sanitary landfill in Turkey
verfasst von
Ilker Sel
Mehmet Çakmakcı
Bestamin Özkaya
Fatih Güreli
Publikationsdatum
08.09.2016
Verlag
Springer Japan
Erschienen in
Journal of Material Cycles and Waste Management / Ausgabe 4/2017
Print ISSN: 1438-4957
Elektronische ISSN: 1611-8227
DOI
https://doi.org/10.1007/s10163-016-0543-7

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