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

Estimation of landfill methane emissions using stochastic search methods

Tarek KORMİ
Nizar Bel Hadj ALİ
Tarek ABİCHOU
Roger GREEN
Sayfa
597–605
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

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.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Municipal solid waste (MSW) landfills significantly contribute to global methane emissions.
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Temel Bulgular & Veri: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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Sonuç & Katkı: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.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

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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Bu Makaleye Atıf Yap

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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Kaynakça (4)

  1. Abichou, T., Clark, J., Chanton, J., 2011. Reporting central tendencies of chamber measured surface emission and oxidation. Waste Manag. 31 (5), 1002e1008. Alexander, A., Burklin, C., Singleton, A., 2005. Landfill Gas Emissions Model (LandGEM) Version 3.02 User's Guide. US/EPA, Washington DC, USA. Babilotte, A., Lagier, T., Fiani, E., Taramini, V., 2010. Fugitive methane emissions from landfills: field comparison of five methods on a French landfill. J. Environ. Eng. 136 (8), 777e784. Banga, J.R., Moles, C.G., Alonso, A.A., 2004. Global Optimization of Bioprocesses Using Stochastic and Hybrid Methods. Frontiers in Global Optimization. C. A. Floudas and P. Pardalos. Boston, MA, Springer US, pp. 45e70. Cambaliza, M., Shepson, P., Bogner, J., Caulton, D., Stirm, B., 2015. Quantification and source apportionment of the methane emission flux from the city of Indianapolis. Elem. Sci. Anthropocene 3 (000037). EEA, 2014. Annual European Union Greenhouse Gas Inventory 1990-2011 and Inventory Report 2014. European Environment Agency. Elbeltagi, E., Hegazy, T., Grierson, D., 2005. Comparison among five evolutionarybased optimization algorithms. Adv. Eng. Inf. 19 (1), 43e53. EPA, 2010. Methane and Nitrous Oxide Emissions from Natural Sources. U.S. Environmental Protection Agency, Washington, DC, USA. EPA, 2014. Global Mitigation of Non-CO2 Greenhouse Gases: 2010-2030.
  2. U.S. Environmental Protection Agency, Washington, DC, USA. Figueroa, V.K., Mackie, K.R., Guarriello, N., Cooper, C.D., 2009. A robust method for estimating landfill methane emissions. J. Air Waste Manag. Assoc. 59 (8), 925e935. Foster-Wittig, T.A., Thoma, E.D., Green, R.B., Hater, G.R., Swan, N.D., Chanton, J.P., 2015. Development of a mobile tracer correlation method for assessment of air emissions from landfills and other area sources. Atmos. Environ.102, 323e330. GasSim2.5, (2014), http://www.gassim.co.uk/index.html#.
  3. Goldberg, D.E., 1989.
  4. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley. Goldsmith, C.D., Chanton, J., Abichou, T., Swan, N., Green, R., Hater, G., 2011. Methane emissions from 20 landfills across the United States using vertical radial plume mapping. J. Air Waste Manag. Assoc. 62 (2), 183e197. Gonzalez-Valencia, R., Magana-Rodriguez, F., Maldonado, E., Salinas, J., Thalasso, F., 2014. Detection of hotspots and rapid determination of methane emissions from landfills via a ground-surface method. Environ. Monit. Assess. 187 (1), 4083. Green, R.B., Swan, N.D., Thoma, E.D.