Case study on prediction of remaining methane potential of landfilled municipal solid waste by statistical analysis of waste composition data

Copyright © 2016 Elsevier Ltd. All rights reserved.

Bibliographische Detailangaben
Veröffentlicht in:Waste management (New York, N.Y.). - 1999. - 56(2016) vom: 21. Okt., Seite 310-7
1. Verfasser: Sel, İlker (VerfasserIn)
Weitere Verfasser: Çakmakcı, Mehmet, Özkaya, Bestamin, Suphi Altan, H
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2016
Zugriff auf das übergeordnete Werk:Waste management (New York, N.Y.)
Schlagworte:Journal Article Methane potential Multiple linear regression Prediction Waste characterization Air Pollutants Solid Waste Methane OP0UW79H66
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245 1 0 |a Case study on prediction of remaining methane potential of landfilled municipal solid waste by statistical analysis of waste composition data 
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500 |a Date Completed 18.04.2017 
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520 |a Main objective of this study was to develop a statistical model for easier and faster Biochemical Methane Potential (BMP) prediction of landfilled municipal solid waste by analyzing waste composition of excavated samples from 12 sampling points and three waste depths representing different landfilling ages of closed and active sections of a sanitary landfill site located in İstanbul, Turkey. Results of Principal Component Analysis (PCA) were used as a decision support tool to evaluation and describe the waste composition variables. Four principal component were extracted describing 76% of data set variance. The most effective components were determined as PCB, PO, T, D, W, FM, moisture and BMP for the data set. Multiple Linear Regression (MLR) models were built by original compositional data and transformed data to determine differences. It was observed that even residual plots were better for transformed data the R(2) and Adjusted R(2) values were not improved significantly. The best preliminary BMP prediction models consisted of D, W, T and FM waste fractions for both versions of regressions. Adjusted R(2) values of the raw and transformed models were determined as 0.69 and 0.57, respectively 
650 4 |a Journal Article 
650 4 |a Methane potential 
650 4 |a Multiple linear regression 
650 4 |a Prediction 
650 4 |a Waste characterization 
650 7 |a Air Pollutants  |2 NLM 
650 7 |a Solid Waste  |2 NLM 
650 7 |a Methane  |2 NLM 
650 7 |a OP0UW79H66  |2 NLM 
700 1 |a Çakmakcı, Mehmet  |e verfasserin  |4 aut 
700 1 |a Özkaya, Bestamin  |e verfasserin  |4 aut 
700 1 |a Suphi Altan, H  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t Waste management (New York, N.Y.)  |d 1999  |g 56(2016) vom: 21. Okt., Seite 310-7  |w (DE-627)NLM098197061  |x 1879-2456  |7 nnns 
773 1 8 |g volume:56  |g year:2016  |g day:21  |g month:10  |g pages:310-7 
856 4 0 |u http://dx.doi.org/10.1016/j.wasman.2016.07.023  |3 Volltext 
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