BMP estimation of landfilled municipal solid waste by multivariate statistical methods using specific waste parameters: case study of a sanitary landfill in Turkey
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. Act...
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| Veröffentlicht in: | Journal of material cycles and waste management 2017-10, Vol.19 (4), p.1479-1487 |
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| creator | Sel, Ilker Çakmakcı, Mehmet Özkaya, Bestamin Güreli, Fatih |
| description | 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. |
| doi_str_mv | 10.1007/s10163-016-0543-7 |
| format | Article |
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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.</description><identifier>ISSN: 1438-4957</identifier><identifier>EISSN: 1611-8227</identifier><identifier>DOI: 10.1007/s10163-016-0543-7</identifier><language>eng</language><publisher>Tokyo: Springer Japan</publisher><subject>Age ; Bone morphogenetic proteins ; Civil Engineering ; Engineering ; Environmental Management ; Kinetic equations ; Landfill ; Landfills ; Mathematical models ; Methane ; Municipal solid waste ; Municipal waste management ; pH effects ; Principal components analysis ; Regional Case Study ; Regression analysis ; Solid waste management ; Statistical analysis ; Statistical methods ; Waste disposal sites ; Waste Management/Waste Technology</subject><ispartof>Journal of material cycles and waste management, 2017-10, Vol.19 (4), p.1479-1487</ispartof><rights>Springer Japan 2016</rights><rights>Journal of Material Cycles and Waste Management is a copyright of Springer, 2017.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c369t-1862dd23568e756e6ac458eeab644e63533c7d711f8ea23d848eb9eb2a3bd5d13</citedby><cites>FETCH-LOGICAL-c369t-1862dd23568e756e6ac458eeab644e63533c7d711f8ea23d848eb9eb2a3bd5d13</cites><orcidid>0000-0002-1770-8385</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10163-016-0543-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10163-016-0543-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Sel, Ilker</creatorcontrib><creatorcontrib>Çakmakcı, Mehmet</creatorcontrib><creatorcontrib>Özkaya, Bestamin</creatorcontrib><creatorcontrib>Güreli, Fatih</creatorcontrib><title>BMP estimation of landfilled municipal solid waste by multivariate statistical methods using specific waste parameters: case study of a sanitary landfill in Turkey</title><title>Journal of material cycles and waste management</title><addtitle>J Mater Cycles Waste Manag</addtitle><description>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.</description><subject>Age</subject><subject>Bone morphogenetic proteins</subject><subject>Civil Engineering</subject><subject>Engineering</subject><subject>Environmental Management</subject><subject>Kinetic equations</subject><subject>Landfill</subject><subject>Landfills</subject><subject>Mathematical models</subject><subject>Methane</subject><subject>Municipal solid waste</subject><subject>Municipal waste management</subject><subject>pH effects</subject><subject>Principal components analysis</subject><subject>Regional Case Study</subject><subject>Regression analysis</subject><subject>Solid waste management</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Waste disposal sites</subject><subject>Waste Management/Waste 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estimation of landfilled municipal solid waste by multivariate statistical methods using specific waste parameters: case study of a sanitary landfill in Turkey</title><author>Sel, Ilker ; Çakmakcı, Mehmet ; Özkaya, Bestamin ; Güreli, Fatih</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c369t-1862dd23568e756e6ac458eeab644e63533c7d711f8ea23d848eb9eb2a3bd5d13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Age</topic><topic>Bone morphogenetic proteins</topic><topic>Civil Engineering</topic><topic>Engineering</topic><topic>Environmental Management</topic><topic>Kinetic equations</topic><topic>Landfill</topic><topic>Landfills</topic><topic>Mathematical models</topic><topic>Methane</topic><topic>Municipal solid waste</topic><topic>Municipal waste management</topic><topic>pH effects</topic><topic>Principal components analysis</topic><topic>Regional Case 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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.</abstract><cop>Tokyo</cop><pub>Springer Japan</pub><doi>10.1007/s10163-016-0543-7</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-1770-8385</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1438-4957 |
| ispartof | Journal of material cycles and waste management, 2017-10, Vol.19 (4), p.1479-1487 |
| issn | 1438-4957 1611-8227 |
| language | eng |
| recordid | cdi_proquest_journals_1949489430 |
| source | SpringerLink Journals |
| subjects | Age Bone morphogenetic proteins Civil Engineering Engineering Environmental Management Kinetic equations Landfill Landfills Mathematical models Methane Municipal solid waste Municipal waste management pH effects Principal components analysis Regional Case Study Regression analysis Solid waste management Statistical analysis Statistical methods Waste disposal sites Waste Management/Waste Technology |
| title | BMP estimation of landfilled municipal solid waste by multivariate statistical methods using specific waste parameters: case study of a sanitary landfill in Turkey |
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