Statistical analysis of air pollutants and numerical modeling of reactive pollutant dispersion within street canyon

2011 ◽  
Author(s):  
Yun-on Tong
Keyword(s):  
Numerical Modeling ◽  
Statistical Analysis ◽  
Air Pollutants ◽  
Street Canyon ◽  
Pollutant Dispersion ◽  
Reactive Pollutant

Modeling reactive pollutant dispersion in an urban street canyon

2007 ◽  
Vol 41 (5) ◽  
pp. 934-949 ◽  
Author(s):  
Jong-Jin Baik ◽  
Yoon-So Kang ◽  
Jae-Jin Kim
Keyword(s):  
Street Canyon ◽  
Pollutant Dispersion ◽  
Urban Street Canyon ◽  
Urban Street ◽  
Reactive Pollutant

scholarly journals Reactive Pollutants Dispersion Modeling in a Street Canyon

2019 ◽  
Vol 24 (1) ◽  
pp. 91-103 ◽  
Author(s):  
A. Merah ◽  
A. Noureddine
Keyword(s):  
Street Canyon ◽  
Pollutant Dispersion ◽  
Windward Side ◽  
Leeward Side ◽  
Dispersion Modeling ◽  
Wind Tunnel Experiments ◽  
Urban Street ◽  
Ansys Cfx ◽  
Computational Fluid Dynamics Cfd ◽  
Reactive Pollutant

Abstract Reactive pollutant dispersion in a 3-D urban street canyon is numerically investigated using a computational fluid dynamics (CFD) code (Ansys-CFX), with the k–ε turbulence model and includes transport equations for NO, NO2, and O3 with simple photochemistry. An area emission source of NO and NO2 was considered in the presence of background O3 with an ambient wind perpendicular to the along-canyon direction. The results showed that the magnitude of NOx (NO+NO2) concentrations on the leeward side of the upstream buildings was much larger than the windward side of the downstream building, due to the entrainment and dispersion of traffic emissions by the primary vortex. The reverse is the case for ozone with higher concentrations on the windward side compared to the leeward side. The model has been validated against no-reactive pollutant experimental data of the wind tunnel experiments of Hoydysh and Dabberdt [1].

scholarly journals APFoam 1.0: integrated computational fluid dynamics simulation of O<sub>3</sub>–NO<sub><i>x</i></sub>–volatile organic compound chemistry and pollutant dispersion in a typical street canyon

2021 ◽  
Vol 14 (7) ◽  
pp. 4655-4681
Author(s):  
Luolin Wu ◽  
Jian Hang ◽  
Xuemei Wang ◽  
Min Shao ◽  
Cheng Gong
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Air Quality ◽  
Organic Compound ◽  
Volatile Organic Compound ◽  
Street Canyon ◽  
Vehicle Emissions ◽  
Pollutant Dispersion ◽  
Volatile Organic ◽  
Reactive Pollutant

Abstract. Urban air quality issues are closely related to human health and economic development. In order to investigate street-scale flow and air quality, this study developed the atmospheric photolysis calculation framework (APFoam 1.0), an open-source computational fluid dynamics (CFD) code based on OpenFOAM, which can be used to examine microscale reactive pollutant formation and dispersion in an urban area. The chemistry module of APFoam has been modified by adding five new types of reactions, which can implement the atmospheric photochemical mechanism (full O3–NOx–volatile organic compound chemistry) coupled with a CFD model. Additionally, the model, including the photochemical mechanism (CS07A), air flow, and pollutant dispersion, has been validated and shows good agreement with SAPRC modeling and wind tunnel experimental data, indicating that APFoam has sufficient ability to study urban turbulence and pollutant dispersion characteristics. By applying APFoam, O3–NOx–volatile organic compound (VOC) formation processes and dispersion of the reactive pollutants were analyzed in an example of a typical street canyon (aspect ratio H/W=1). The comparison of chemistry mechanisms shows that O3 and NO2 are underestimated, while NO is overestimated if the VOC reactions are not considered in the simulation. Moreover, model sensitivity cases reveal that 82 %–98 % and 75 %–90 % of NO and NO2, respectively, are related to the local vehicle emissions, which is verified as the dominant contributor to local reactive pollutant concentration in contrast to background conditions. In addition, a large amount of NOx emissions, especially NO, is beneficial to the reduction of O3 concentrations since NO consumes O3. Background precursors (NOx/VOCs) from boundary conditions only contribute 2 %–16 % and 12 %–24 % of NO and NO2 concentrations and raise O3 concentrations by 5 %–9 %. Weaker ventilation conditions could lead to the accumulation of NOx and consequently a higher NOx concentration but lower O3 concentration due to the stronger NO titration effect, which would consume O3. Furthermore, in order to reduce the reactive pollutant concentrations under the odd–even license plate policy (reduce 50 % of the total vehicle emissions), vehicle VOC emissions should be reduced by at least another 30 % to effectively lower O3, NO, and NO2 concentrations at the same time. These results indicate that the examination of the precursors (NOx and VOCs) from both traffic emissions and background boundaries is the key point for understanding O3–NOx–VOCs chemistry mechanisms better in street canyons and providing effective guidelines for the control of local street air pollution.

scholarly journals APFoam-1.0: integrated CFD simulation of O<sub>3</sub>–NO<sub>x</sub>–VOCs chemistry and pollutant dispersion in typical street canyon

2020 ◽  
Author(s):  
Luolin Wu ◽  
Jian Hang ◽  
Xuemei Wang ◽  
Min Shao ◽  
Cheng Gong
Keyword(s):  
Air Quality ◽  
Street Canyon ◽  
Vehicle Emissions ◽  
Cfd Simulation ◽  
Pollutant Dispersion ◽  
Urban Air Quality ◽  
Urban Air ◽  
License Plate ◽  
Health And Economic Development ◽  
Reactive Pollutant

Abstract. Urban air quality issues are closely related to the human health and economic development. In order to improve the resolution and numerical accuracy of urban air quality simulation, this study has developed the Atmospheric Photolysis calculation framework (APFoam-1.0), an open-source CFD code based on OpenFOAM, which can be used to examine the micro-scale reactive pollutant formation and dispersion in the urban area. The chemistry module of the newly APFoam has been modified by adding five new types of reaction, which implements the coupling with atmospheric photochemical mechanism (full O3–NOx–VOCs chemistry) and CFD model. Additionally, numerical model has been validated and shows the good agreement with wind tunnel experimental data, indicating that the APFoam has sufficient ability to study urban turbulence and pollutant dispersion characteristics. By applying the APFoam, O3–NOx–VOCs formation processes and dispersion of the reactive pollutants are analyzed in an example of typical street canyon (aspect ratio H / W = 1). Chemistry mechanism comparison shows that O3 and NO2 are underestimated while NO is overestimated if the VOCs reactions are not considered in the simulation. Moreover, model sensitivity cases reveal that 82 %–98 % and 75 %–90 % of NO and NO2 are related to the local vehicle emissions which are verified as the dominated contributors to local reactive pollutant concentration in contrast to their background conditions. Besides, a large amount of NOx emission, especially NO emission, is beneficial to reduce the O3 concentrations since NO consumes O3. Background precursors (NOx/VOCs) from boundary conditions only contribute 2 %–16 % and 12 %–24 % of NO and NO2 concentrations and raise O3 concentration by 5 %–9 %. Weaker ventilation conditions lead to accumulation of NOx and higher NOx concentration, but a lower O3 concentrations due to the stronger NO titration effect consuming O3. Furthermore, in order to reduce the reactive pollutant concentrations under the odd-even license plate policy (reduce 50 % of the total vehicle emissions), vehicle VOCs emissions should be reduced by at least another 30 % to effectively lower O3, NO and NO2 concentrations at the same time. These results indicate that the examination of the precursors (NOx/VOCs) from both traffic emissions and background boundaries is the key point for better understanding O3–NOx–VOCs chemistry mechanisms in street canyons and providing effective guidelines for the joint prevention and control of local street air pollution.

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