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Technical Paper

Estimating Gas Emissions from Multiple Sources Using a Backward Lagrangian Stochastic Model

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Pages 1415-1421 | Published online: 28 Mar 2012

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Veronica K. Figueroa, Kevin R. Mackie, Nick Guarriello & C. David Cooper. (2009) A Robust Method for Estimating Landfill Methane Emissions. Journal of the Air & Waste Management Association 59:8, pages 925-935.
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Richard H. Grant & Matthew T. Boehm. (2022) Emissions of H2S from Hog Finisher Farm Anaerobic Manure Treatment Lagoons: Physical, Chemical and Biological Influence. Atmosphere 13:2, pages 153.
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Cheng-Hsien Lin, Richard H. Grant & Cliff T. Johnston. (2020) Measuring N2O Emissions from Multiple Sources Using a Backward Lagrangian Stochastic Model. Atmosphere 11:12, pages 1277.
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Denglong Ma, Jianmin Gao, Zaoxiao Zhang & Qingsheng Wang. (2019) An Improved Firefly Algorithm for Gas Emission Source Parameter Estimation in Atmosphere. IEEE Access 7, pages 111923-111930.
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Benjamin Loubet, Marco Carozzi, Polina Voylokov, Jean-Pierre Cohan, Robert Trochard & Sophie Génermont. (2018) Evaluation of a new inference method for estimating ammonia volatilisation from multiple agronomic plots. Biogeosciences 15:11, pages 3439-3460.
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Richard H. Grant, Matthew T. Boehm & Alfred J. Heber. (2016) Ammonia emissions from anaerobic waste lagoons at pork production operations: Influence of climate. Agricultural and Forest Meteorology 228-229, pages 73-84.
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Qing Huo, Xuhui Cai, Ling Kang, Hongsheng Zhang, Yu Song & Tong Zhu. (2014) Inference of emission rate using the inverse-dispersion method for the multi-source problem. Agricultural and Forest Meteorology 191, pages 12-21.
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Yung-Tse Hung, Erick Butler & Ruth Yu-Li Yeh. (2011) Chemicals and Allied Products Waste Treatment. Water 3:2, pages 629-648.
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Lowry A. Harper, Thomas K. Flesch, Kim H. Weaver & John D. Wilson. (2010) The Effect of Biofuel Production on Swine Farm Methane and Ammonia Emissions. Journal of Environmental Quality 39:6, pages 1984-1992.
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Eugene Yee & Thomas K. Flesch. (2010) Inference of emission rates from multiple sources using Bayesian probability theory. J. Environ. Monit. 12:3, pages 622-634.
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