Estimation of fugitive landfill methane emissions using surface emission monitoring and Genetic Algorithms optimization

Copyright © 2016 Elsevier Ltd. All rights reserved.

Bibliographische Detailangaben
Veröffentlicht in:Waste management (New York, N.Y.). - 1999. - 72(2018) vom: 25. Feb., Seite 313-328
1. Verfasser: Kormi, Tarek (VerfasserIn)
Weitere Verfasser: Mhadhebi, Safa, Bel Hadj Ali, Nizar, Abichou, Tarek, Green, Roger
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2018
Zugriff auf das übergeordnete Werk:Waste management (New York, N.Y.)
Schlagworte:Journal Article Genetic Algorithms Methane emission Methane measurements Solid waste landfill Air Pollutants Solid Waste Methane OP0UW79H66
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245 1 0 |a Estimation of fugitive landfill methane emissions using surface emission monitoring and Genetic Algorithms optimization 
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500 |a Date Completed 10.08.2018 
500 |a Date Revised 02.12.2018 
500 |a published: Print-Electronic 
500 |a Citation Status MEDLINE 
520 |a Copyright © 2016 Elsevier Ltd. All rights reserved. 
520 |a As municipal solid waste (MSW) landfills can generate significant amounts of methane, there is considerable interest in quantifying fugitive methane emissions at such facilities. A variety of methods exist for the estimation of methane emissions from landfills. These methods are either based on analytical emission models or on measurements. This paper presents a method to estimate methane emissions using ambient air methane measurements obtained on the surface of a landfill. Genetic Algorithms based optimization combined with the standard Gaussian dispersion model is employed to identify locations as well as emission rates of potential emission sources throughout a municipal solid waste landfill. Four case studies are employed in order to evaluate the performance of the proposed methodology. It is shown that the proposed approach enables estimation of landfill methane emissions and localization of major emission hotspots in the studied landfills. The proposed source-locating-scheme could be seen as a cost effective method assisting landfill operators to reasonably estimate and locate major methane emissions 
650 4 |a Journal Article 
650 4 |a Genetic Algorithms 
650 4 |a Methane emission 
650 4 |a Methane measurements 
650 4 |a Solid waste landfill 
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 Mhadhebi, Safa  |e verfasserin  |4 aut 
700 1 |a Bel Hadj Ali, Nizar  |e verfasserin  |4 aut 
700 1 |a Abichou, Tarek  |e verfasserin  |4 aut 
700 1 |a Green, Roger  |e verfasserin  |4 aut 
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