A unified analytical solution of the steady-state atmospheric diffusion equation

Guerrero, J.S. Pérez; Pimentel, Leonardo Duarte; Júnior, José Francisco Oliveira; Filho, Paulo Fernando Lavalle Heilbron; Ulke, Ana Graciela

doi:10.1016/j.atmosenv.2012.03.015

Cited by 24 publications

(24 citation statements)

References 54 publications

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“…However, the solutions are mainly available over unstable and neutral conditions [2][3][4][5], whereas there is a lack of works considering the solution of the pollutant dispersion equations under stable conditions [3,6,7]. As argued by Salmond & McKendry [8], the strongly layered structure and intermittent characteristics of turbulence in the very stable nocturnal boundary layer present a particular challenge to meteorologists and air pollution modellers alike.…”

Section: Introductionmentioning

confidence: 99%

“…The solution of the associated eigenvalue problem for situations with arbitrary functional forms for the mean wind velocity and eddy diffusivities was obtained by Pérez Guerrero et al [4] using the generalized integral transform technique (GITT), following the procedure described by Mikhailov & Cotta [16]. With that procedure, the ordinary differential equation of the eigenvalue problem was reduced to an algebraic eigenvalue system.…”

Section: Introductionmentioning

confidence: 99%

“…Pérez Guerrero et al [4] using the classic integral transform technique (CITT) developed a unified analytical solution of the steady-state atmospheric diffusion equation. The solution was obtained by considering an arbitrary mean wind velocity depending on the vertical coordinate (z) and a generalized separable functional form for the eddy diffusivities in terms of the longitudinal (x) and vertical coordinates (z).…”

Section: Introductionmentioning

confidence: 99%

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Assessment of the unified analytical solution of the steady-state atmospheric diffusion equation for stable conditions

et al. 2014

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In this work, the performance of a unified formal analytical solution for the simulation of atmospheric diffusion problems under stable conditions is evaluated. The eigenquantities required by the formal analytical solution are obtained by solving numerically the associated eigenvalue problem based on a newly developed algorithm capable of being used in high orders and without missing eigenvalues. The performance of the formal analytical solution is evaluated by comparing the converged predicted results against the observed values in the stable runs of the Prairie Grass experiment as well as the simulated results available in the literature. It was found that the developed algorithm was efficient and that the convergence rate depends on the stability condition and the considered parametrizations for wind speed and turbulence. The comparisons among predicted and observed concentrations showed a good agreement and indicate that the considered dispersion formulations are appropriate to simulate dispersion under slightly to moderate atmospheric stable conditions.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessment of the unified analytical solution of the steady-state atmospheric diffusion equation for stable conditions

et al. 2014

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“…Currently, the MRRJ has been facing several problems related to high CO concentrations that have been routinely detected through air quality stations (INEA, 2010;ZERI et al, 2011) and/or by the application of analytical models of atmospheric diffusion or air quality regulators (GUERRERO et al 2012;CUNHA et al, 2009;SOARES et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…In the last decades, air pollution and air quality in large urban and industrial centers are a serious social and environmental problem around the world (GUERRERO et al 2012;ZERI et al, 2016). Atmospheric pollutants are influenced directly by meteorological conditions, topographic features along with local, mesoscale and synoptic meteorological systems (OLIVEIRA JÚNIOR et al, 2010;ZERI et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Carbon monoxide trend in the city of Rio de Janeiro via mann-kendall and cusum tests

Góis¹,

Oliveira‐Júnior²,

Silva³

et al. 2017

Biosci. J.

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(2011) for positive values (Z > 0) and p-value > 0.05. CUSUM test showed that Q magnitude did not exceed the critical value at 1% and 5% probability levels. Cumulative Sum Test (CUSUM) showed homogeneous and significant CO concentrations. Significant abrupt changes occurred in the months of May, June, July, August and September and insignificant in January, February, June, August and November at 1% and 5% probability. CO concentrations occurred in the predominant directions North-Northwest (NNW), South-Southwest (SSW) and South-west (SW). Both sectors are influenced by the main synoptic systems (Frontal System and South Atlantic Subtropical High) that act on CRJ. MK and CUSUM tests proved to be efficient in evaluating trends and abrupt changes in CO concentrations and air quality stations in the CRJ.

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Pollutant Dispersion Modeling via Mathematical Homogenization and Integral Transform-Based Multilayer Methods

Costa

Pérez-Fernández

Bravo‐Castillero

2019

Towards Mathematics, Computers and Environment: A Disasters Perspective

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A unified analytical solution of the steady-state atmospheric diffusion equation

Cited by 24 publications

References 54 publications

Assessment of the unified analytical solution of the steady-state atmospheric diffusion equation for stable conditions

Assessment of the unified analytical solution of the steady-state atmospheric diffusion equation for stable conditions

Carbon monoxide trend in the city of Rio de Janeiro via mann-kendall and cusum tests

Pollutant Dispersion Modeling via Mathematical Homogenization and Integral Transform-Based Multilayer Methods

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