Modelling of pollutant dispersion with atmospheric instabilities in an industrial park

Ma, Xiaofei; Wang, Zhong; Wei, Feng; Li, Gang

doi:10.1016/j.powtec.2016.08.062

Cited by 10 publications

(6 citation statements)

References 33 publications

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“…Under unstable atmospheric conditions, overall wind velocities tend to be lower. Previous research by Ma et al [35] indicates that under buoyancy effects caused by plant canopies and the presence of solar radiation, streamlines exhibit an upward trend vertically; additionally, there is an opposite wind direction observed between Case 2 and Case 3 within the northern region "A". The near-ground wind fields become more uniform under unstable weather conditions.…”

Section: Effects Of Meteorological Conditions On Wind Fieldmentioning

confidence: 89%

Section: Effects Of Meteorological Conditions On Wind Fieldmentioning

confidence: 95%

“…The validation diagram, shown in Figure 3a, used a computational domain of 160 m × 60 m × 60 m, which is identical to that used in [31,34]. The canopy height was set at 20 m, horizontally uniform, and more detailed settings can be found in the previous research of Ma et al [35]. Three typical cases with the same inlet velocity and solar radiation heat flux as those in [31,34] were calculated and the time-averaged wind velocity distributions on vertical profiles under different meteorological conditions are presented in Figure 3b.…”

Section: Model Validationmentioning

confidence: 99%

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CFD-DPM Simulation on the Atmospheric Pollutant Dispersion in Industrial Park

Ma,

Zhong

2024

Atmosphere

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In order to mitigate the impact of particulate pollutants in Nanjing Sample Industrial Park, it is imperative to simulate the wind field and pollutant dispersion inside the park. Therefore, a CFD-DPM study was employed to simulate the wind field and pollutant dispersion with an accurate landform model. A large eddy simulation was utilized for calculating wind flow distribution inside the park, which is more suitable than Reynolds-Averaged Navier–Stokes Equations (RANS). The physical model of the plant canopy was incorporated to assess its influence on the wind field and particulate pollutants through drag, buoyancy, and deposition effects. Using this method, the distributions of the wind field, and contaminant and the sensitivity tests were obtained by means of calculating a number of research cases under different meteorological conditions. In the numerical results, the wind field was obstructed by the plant canopy, resulting in near-ground uniformity under unstable weather conditions. The distribution of particulate pollutants was influenced not only by the drag and buoyancy effects but also by deposition, which caused an accumulation of particulate pollutants on the windward side of the canopy under unstable weather conditions. The sensitivity tests were performed by comparing the concentrations of particulate pollutants under various conditional settings. The canopy regions can remove the particulate pollutant by 50% under stable weather conditions. The deposition effect is enhanced by larger particle density and diameter and is also influenced by leaf area density.

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Section: Effects Of Meteorological Conditions On Wind Fieldmentioning

confidence: 89%

Section: Effects Of Meteorological Conditions On Wind Fieldmentioning

confidence: 95%

Section: Model Validationmentioning

confidence: 99%

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CFD-DPM Simulation on the Atmospheric Pollutant Dispersion in Industrial Park

Ma,

Zhong

2024

Atmosphere

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“…It can be seen that the local wind flow in this region is very complicated. As demonstrated in the literature, the complexity of wind field in industrial parks results from the complex underlying surface factors, such as terrain, plant canopy, various buildings, and equipment [21,24,25]. With complex processes at microscales and limited information, the high-precision models, like CFD, are inapplicable.…”

Section: Frequency Of Violation Recordsmentioning

confidence: 99%

“…In theory, the Gaussian puff model is not the most suitable model for simulating the dispersion of organic air pollutants, like methyl mercaptan, which is the subject of this study. Precise dispersion models, like CFD, are preferable for exquisite simulation of the airflow and pollutant dispersion under complex terrain or surface, which is universal in industrial parks [21]. Gaussian puff model was finally used as a forward model in this study for the following considerations.…”

Section: Introductionmentioning

confidence: 99%

Identifying Key Potential Source Areas for Ambient Methyl Mercaptan Pollution Based on Long-Term Environmental Monitoring Data in an Industrial Park

Liu

Huang

et al. 2018

Atmosphere

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Precise source identification for ambient pollution incidents in industrial parks were often difficult due to limited measurements. Source area analysis method was one of the applicable source identification methods, which could provide potential source areas under these circumstances. However, a source area usually covered several sources and the method was unable to identify the real one. This article introduces a case study on the statistical source identification of methyl mercaptan based on the long-term measurements, in 2014, in an industrial park. A procedure for statistical source area analysis was established, which contains independent pollution episode extraction, source area calculation scenario definition, meteorological data selection, and source area statistical analysis. A total of 414 violation records were detected by five monitors inside the park. Three kinds of calculation scenarios were found and, finally, three key source areas were revealed. The typical scenarios of source area calculations were described in detail. The characteristics of the statistical source areas for all pollution episodes were examined. Finally, the applicability of the method, as well as the source of uncertainties, was discussed. This study shows that more concentrated source areas can be identified through the statistical source area method if several excessive emission sources exist in an industrial park.

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Modeling atmospheric emissions during olive husk drying and study of meteorological factors effect in the vicinity of urban areas

Dardouri

Sghaier

2019

Journal of King Saud University - Science

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Modelling of pollutant dispersion with atmospheric instabilities in an industrial park

Cited by 10 publications

References 33 publications

CFD-DPM Simulation on the Atmospheric Pollutant Dispersion in Industrial Park

CFD-DPM Simulation on the Atmospheric Pollutant Dispersion in Industrial Park

Identifying Key Potential Source Areas for Ambient Methyl Mercaptan Pollution Based on Long-Term Environmental Monitoring Data in an Industrial Park

Modeling atmospheric emissions during olive husk drying and study of meteorological factors effect in the vicinity of urban areas

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