A Bayesian Inference Model for the Estimation of Time-Dependent Pollutant Emissions

Autores

  • Roseane Albani
  • Hélio S. Migon
  • Antônio J. Silva Neto
  • Vinicius Albani

DOI:

https://doi.org/10.5540/03.2022.009.01.0228

Palavras-chave:

Source Estimation, Atmospheric Dispersion, Bayesian Inference, Monte Carlo Markov, Chain Algorithms, Inverse Modeling.

Resumo

Source identification methodologies use inverse problems techniques combined with a dispersion model and observational data to estimate relevant source parameters. This work proposes a time-dependent model to estimate source parameters of multiple point releases. The forward problem or dispersion model accounts for the time variation of the wind field using a Fourier series that best fits the wind field time series of the experimental data. The source parameters are estimated by an adaptive Monte Carlo Markov Chain algorithm.

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Biografia do Autor

Roseane Albani

IPRJ/UERJ, Nova Friburgo, RJ

Hélio S. Migon

IPRJ/UERJ, Nova Friburgo, RJ

Antônio J. Silva Neto

IPRJ/UERJ, Nova Friburgo, RJ

Vinicius Albani

LAMMCA/Dept. Matemática/UFSC, Florianópolis, SC

Referências

R. Albani and V. Albani. “An Accurate Strategy to Retrieve Multiple Source Emissions in the Atmosphere”. In: Atmos. Environ. 233 (2020), p. 117579. doi: 10.1016/j.atmosenv. 2020.117579.

R. Albani, V. Albani, and A. Silva Neto. “Source characterization of airborne pollutant emissions by hybrid metaheuristic/gradient-based optimization techniques”. In: Environ Pollut. 267 (2020), p. 115618. doi: https://doi.org/10.1016/j.envpol.2020.115618.

R.A.S Albani et al. “A Bayesian Inference Approach for the Identification of Multiple Atmospheric Emissions with Uncertainty Quantification”. In: Proceedings of XXIV Encontro Nacional de Modelagem Computacional. 2021. doi: 10.29327/154013.24-62.

R.A.S. Albani and V.V.L. Albani. “An Accurate Strategy to Retrieve Multiple Source Emissions in the Atmosphere”. In: Atmospheric Environment 233 (2020), p. 117579. doi: 10.1016/j.atmosenv.2020.117579.

R.A.S. Albani and V.V.L. Albani. “Tikhonov-Type Regularization and the Finite Element Method Applied to Point Source Estimation in the Atmosphere”. In: Atmos. Environ. 211 (2019), pp. 69–78. doi: 10.1016/j.atmosenv.2019.04.063.

R.A.S. Albani et al. “Uncertainty quantification and atmospheric source estimation with a discrepancy-based and a state-dependent adaptative MCMC”. In: Environmental Pollution (2021), p. 118039. doi: 10.1016/j.envpol.2021.118039.

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Publicado

2022-12-08

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