Turbulence and dispersion modeling near highways

Rao, K. Shankar; Gunter, R. L.; White, James R.; Hosker, R.P.

doi:10.1016/s1352-2310(02)00353-9

Cited by 53 publications

(41 citation statements)

References 10 publications

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“…In practical applications the line, plane, and volume sources are subdivided into parts by attributing them separate Gaussian plume equations, including the vehicle-induced turbulence, meteorological state parameters, etc. In such a way the problems of pollution dispersion of line [8] and volume [9] sources are solved, and good dispersion conformity with the experimental data is obtained. Besides, the pollution concentration decrease receding from the roadside is usually close to the exponential law.…”

Section: Introductionmentioning

confidence: 72%

“…At present for the description of the road pollution dispersion, different types of dispersion models are used: box type, Gaussian, Eulerian and Lagrangian, computational fluid dynamic, semi-empirical, stochastic, and deterministic-statistical models, in which the point, line, area, and volume type sources are most frequently used [6][7][8][9]. In the atmospheric dispersion simulation, Gaussian type models are most widely used.…”

Section: Introductionmentioning

confidence: 99%

“…Having introduced empirical parameters, the dispersion of aerosol particles in the size range of 0.01-0.05 µm is well described by the Gaussian plume model [8], but this model cannot explain the dispersion peculiarities of aerosol particles in the size range of 0.05-0.3 µm, though there have been attempts to interpret it as a particle coagulation phenomenon. The aerosol particles belonging to the size range of 0.05-0.3 µm are formed during atmospheric oxidation processes, which are relatively slow [12].…”

Section: Introductionmentioning

confidence: 99%

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Simulation of traffic pollution dispersion near roadways

Martinėnas¹,

Špakauskas²

2010

Lithuanian J. Phys.

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A semi-empirical model intended for simulation of dispersion of aerosol particles with the diameter larger than 0.05 µm near roadways is proposed. The pollution source is simulated as a cut-off cylinder, formed due to traffic pollution on the roadways at the initial time moment and uniformly filled with aerosol particles. The aerosol particle transfer by the wind further from the roadway is simulated, its settling being influenced by the gravitation, particle buoyancy, and thermal pollutant plume rise effects. Good agreement between the model and experimental results is obtained.

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Section: Introductionmentioning

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Simulation of traffic pollution dispersion near roadways

Martinėnas¹,

Špakauskas²

2010

Lithuanian J. Phys.

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“…An important factor is VIT on the formation and dispersion process for on-road particles. Studies have shown that VIT has a strong influence of dispersion model predictions (Rao et al, 2002;Sahlodin et al, 2007). However, more studies directed at understanding VIT effects for on-road particles are still needed.…”

Section: Model Estimation Of Pm 25mentioning

confidence: 99%

Particle Concentration on Freeways: Affecting Factors and a Simple Model Development

Fung

Zhou

Hinds

et al. 2013

Aerosol Air Qual. Res.

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A few field studies have reported high levels of in-cabin ultrafine particles and discussed certain contributing factors such as vehicle operations and atmospheric meteorological conditions. However, to generalize limited field study results to a wide range of conditions, a deeper understanding of affecting factors and a simple model that can predict on-road particle concentrations are essential. This paper has two objectives, first, to analyze the effects of surrounding vehicle density, relative freeway lane position, and vehicle speed on measured particle concentrations on two California freeways, I-405 (5% diesel) and I-710 (25% diesel). The second objective is to test the use of Emission Factor (EMFAC) 2007 and Caline4 (CL4) models in predicting on-road particle concentrations. Particle number and mass concentrations were collected using a mobile laboratory driving on the I-710 and I-405 freeways. Particle number concentration was found to be affected by the density of surrounding heavy duty diesel trucks which is consistent with previous studies. The highest particle number concentrations were measured in the outer lanes on the freeway and the lowest was in the inner lanes. The highest levels of particles were measured at vehicle speeds of 40-50 mph. Analysis of CL4 model was conducted using factor-of-two test. For the I-710, 85% of values were within the factor-of-two envelope, and for the I-405, 77% were within the envelope. Regression analysis showed that the model is able to account for 43% of the variability on the I-710 and 26% of the variability on the I-405. The use of CL4 in conjunction with EMFAC shows promise as a simple tool to estimate on-road PM 2.5 concentration.

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“…They are based on solving the Navier-Stokes equation, which is completed by finite difference and finite volume methods. Rao et al [19] showed a significant role of turbulent kinetic energy in dispersion of aerosols.…”

Section: Introductionmentioning

confidence: 99%

Simulation of traffic-related aerosol dispersion

Špakauskas¹,

Melichov²

2012

Lith. J. Phys.

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This paper presents a quasi-empirical model of the distribution of pollutant particles along the roadway. By modelling the source of the pollutant as a cut-off cylinder we assume that aerosol particles (of 0.3-15 µm in diameter) are distributed according to the Gaussian law both along the vertical and horizontal axes. A cross wind translates the pollutant cloud away from the road and the particles are being influenced by gravity, particle buoyancy and thermal plume rise effects. The obtained pollutant concentration function coincides well with the experimental data obtained by Zhu et al. (2011), Grigalavičienė andRutkovienė (2006), andZechmeister et al. (2005).

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Turbulence and dispersion modeling near highways

Cited by 53 publications

References 10 publications

Simulation of traffic pollution dispersion near roadways

Simulation of traffic pollution dispersion near roadways

Particle Concentration on Freeways: Affecting Factors and a Simple Model Development

Simulation of traffic-related aerosol dispersion

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