Journals / Atmospheric Pollution Research / 2017 / Cilt: 8 - Sayı: 4

Estimation of landfill methane emissions using stochastic search methods

Pages
597–605
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Results show effectiveness of the optimization-based emission estimation and sourcelocating scheme.

📌 3 Key Takeaways

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Objective & Hypothesis:Municipal solid waste (MSW) landfills significantly contribute to global methane emissions.
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Key Findings & Data:In order to establish methane mitigation strategies, one important step is to quantify fugitive methane emissions resulting from organic waste decomposition.
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Conclusion & Impact:Results show effectiveness of the optimization-based emission estimation and sourcelocating scheme.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

Municipal solid waste (MSW) landfills significantly contribute to global methane emissions. In order to establish methane mitigation strategies, one important step is to quantify fugitive methane emissions resulting from organic waste decomposition. This paper presents a cost-effective method to estimate methane emissions using ambient air methane measurements taken within a landfill. Stochastic search techniques combined with the standard Gaussian dispersion model are employed to identify locations and emission rates of potential emission sources. Four stochastic search techniques are tested and compared. Results show effectiveness of the optimization-based emission estimation and sourcelocating scheme. Two hand-generated case-studies showed that methane flux estimation-error is lower than 15%. The method proves also useful in identifying locations of emission sources. Furthermore, when monitoring data of a real closed landfill are used, results showed that method results are comparable with those obtained using more established experimental Tracer-based technique.

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Cite This Article

KORMİ, T., ALİ, N. B. H., ABİCHOU, T., GREEN, R. (2017). Estimation of landfill methane emissions using stochastic search methods. Atmospheric Pollution Research, Cilt: 8 - Sayı: 4, 597–605. https://ajindex.com/articles/218435

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References (4)

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