Journal ArticleDOI
Bayesian Inference and Wind Field Statistical Modeling Applied to Multiple Source Estimation.
Roseane A.S. Albani,Vinicius V. L. Albani,L. Gomes,Helio S. Migon,Antônio José da Silva Neto +4 more
TLDR
In this paper , the authors presented a methodology to identify multiple pollutant sources in the atmosphere that combines a data-driven dispersion model with Bayesian inference and uncertainty quantification.About:
This article is published in Environmental Pollution.The article was published on 2023-01-01. It has received 1 citations till now. The article focuses on the topics: Medicine & Markov chain Monte Carlo.read more
Citations
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Journal ArticleDOI
Atmospheric Dispersion Modeling Using a Stochastic Wind Model
TL;DR: In this article , a stochastic wind field based on the Bayesian dynamic linear model is proposed to account for the wind flow field in the transient advection-diffusion partial differential equation (PDE).
References
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Journal ArticleDOI
Inference from Iterative Simulation Using Multiple Sequences
Andrew Gelman,Donald B. Rubin +1 more
TL;DR: The focus is on applied inference for Bayesian posterior distributions in real problems, which often tend toward normal- ity after transformations and marginalization, and the results are derived as normal-theory approximations to exact Bayesian inference, conditional on the observed simulations.
Book
An Introduction to Boundary Layer Meteorology
TL;DR: In this article, the boundary layer is defined as the boundary of a boundary layer, and the spectral gap is used to measure the spectral properties of the boundary layers of a turbulent flow.
Book
Boundary layer climates
TL;DR: This modern climatology textbook explains those climates formed near the ground in terms of the cycling of energy and mass through systems.
Journal ArticleDOI
Flux-Profile Relationships in the Atmospheric Surface Layer
TL;DR: In this article, the free constants in several interpolation formulas can be adjusted to give excellent fits to the wind and temperature gradient data, and the behavior of the gradients under neutral conditions is unusual, however, and indicates that von Karman's constant is ∼0.35, rather than 0.40 as usually assumed, and that the ratio of eddy diffusivities for heat and momentum at neutrality is ∼1.0.
Book
Hierarchical Modeling and Analysis for Spatial Data
TL;DR: Matrix Theory and Spatial Computing Methods Answers to Selected Exercises REFERENCES AUTHOR INDEX SUBJECT INDEX Short TOC
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