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A numerical physio-chemical model of the NOx-O3 photochemical cycle in the near-wake region of an isolated residential/office building has been presented in this study. The investigation delves into the dispersion of reactive air pollutants through the lens of fluid phenomenology and its impact on chemical reactivity, formation, transport, deposition, and removal. Computational fluid dynamics (CFD) simulations were conducted for the ground-point-source (GES) and roof-point-source (RES) scenarios. Results show that the Damköhler number (Da), which quantifies pollutants’ physio-chemical timescales, displays a strong inverse proportionality with the magnitude and spread of NO–increasing Da reduces human exposure to the toxic NO and NO2 substantially. When different wind directions were considered, the dispersion range of NO exhibited varying shrinking directions as Da increased. Furthermore, as Da increases, the concentration ratio KNO2/KNOx, which quantifies the production of NO2 resulting from NO depletion, forms sharp high-low gradients near emission sources. For GES, the dispersion pattern is governed by the fluid’s phenomenological features. For RES, the intoxicated area emanates from the building’s leading-edge, with the lack of shielding inhibiting pollutant interactions in the near-wake, resulting in scant physio-chemical coupling. The NO2/NOx distribution follows a self-similar, stratified pattern, exhibiting consistent layering gradients and attributing to the natural deposition of the already-reacted pollutants rather than in-situ reactions. In the end, building design guidelines have been proposed to reduce pedestrian and resident exposure to NOx-O3.


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Physio-chemical modeling of the NOx-O3 photochemical cycle and the air pollutants’ reactive dispersion around an isolated building

Show Author's information Yunfei Fu1,§Xisheng Lin1,§Xing Zheng2Liangzhu Wang3Chun-Ho Liu4Xuelin Zhang6Cruz Y. Li5( )K.T. Tse1( )
Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
Future Cities Lab Global, Singapore-ETH Centre, Singapore 138602
Department of Building, Civil and Environmental Engineering at Concordia University, Montreal, Quebec, Canada
Department of Mechanical Engineering, The University of Hong Kong, Pok-fu-lam Road, Hong Kong, China
Department of Civil Engineering, Chongqing University, Chongqing, China
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China

§ Yunfei Fu and Xisheng Lin contributed equally to this work.

Abstract

A numerical physio-chemical model of the NOx-O3 photochemical cycle in the near-wake region of an isolated residential/office building has been presented in this study. The investigation delves into the dispersion of reactive air pollutants through the lens of fluid phenomenology and its impact on chemical reactivity, formation, transport, deposition, and removal. Computational fluid dynamics (CFD) simulations were conducted for the ground-point-source (GES) and roof-point-source (RES) scenarios. Results show that the Damköhler number (Da), which quantifies pollutants’ physio-chemical timescales, displays a strong inverse proportionality with the magnitude and spread of NO–increasing Da reduces human exposure to the toxic NO and NO2 substantially. When different wind directions were considered, the dispersion range of NO exhibited varying shrinking directions as Da increased. Furthermore, as Da increases, the concentration ratio KNO2/KNOx, which quantifies the production of NO2 resulting from NO depletion, forms sharp high-low gradients near emission sources. For GES, the dispersion pattern is governed by the fluid’s phenomenological features. For RES, the intoxicated area emanates from the building’s leading-edge, with the lack of shielding inhibiting pollutant interactions in the near-wake, resulting in scant physio-chemical coupling. The NO2/NOx distribution follows a self-similar, stratified pattern, exhibiting consistent layering gradients and attributing to the natural deposition of the already-reacted pollutants rather than in-situ reactions. In the end, building design guidelines have been proposed to reduce pedestrian and resident exposure to NOx-O3.

Keywords: modelling, dispersion, air, building, pollutant, pollution, reactive, NOx-O3, cycle, isolated, physio-chemical

References(67)

ANSYS (2011). ANSYS Fluent Theory Guide. Canonsburg, PA, USA: ANSYS Inc.

Baik JJ, Kang YS, Kim JJ (2007). Modeling reactive pollutant dispersion in an urban street canyon. Atmospheric Environment, 41: 934–949.

Baker J, Walker HL, Cai X (2004). A study of the dispersion and transport of reactive pollutants in and above street canyons—A large eddy simulation. Atmospheric Environment, 38: 6883–6892.

Blocken B, Stathopoulos T, Carmeliet J (2007). CFD simulation of the atmospheric boundary layer: Wall function problems. Atmospheric Environment, 41: 238–252.

Blocken B (2018). LES over RANS in building simulation for outdoor and indoor applications: A foregone conclusion? Building Simulation, 11: 821–870.

Blocken B, Stathopoulos T, Saathoff P, et al. (2008). Numerical evaluation of pollutant dispersion in the built environment: Comparisons between models and experiments. Journal of Wind Engineering and Industrial Aerodynamics, 96: 1817–1831.

Builtjes PJH (1983). A comparison between chemically reacting plume models and windtunnel experiments. In: de Wispelaere C (ed), Air Pollution Modeling and Its Application Ⅱ. Yew York: Springer.
DOI

Chavez M, Hajra B, Stathopoulos T, et al. (2011). Near-field pollutant dispersion in the built environment by CFD and wind tunnel simulations. Journal of Wind Engineering and Industrial Aerodynamics, 99: 330–339.

Chen Z, Kim B, Lee D-E (2021). Aerodynamic characteristics and lateral displacements of a set of two buildings in a linked tall building system. Sensors, 21: 4046.

Chung TNH, Liu C-H (2012). Large-eddy simulation of reactive pollutant dispersion for the spatial instability of photostationary state over idealised 2D urban street canyons. International Journal of Environment and Pollution, 50: 411–419.

Clark LP, Millet DB, Marshall JD (2014). National patterns in environmental injustice and inequality: Outdoor NO2 air pollution in the United States. PLoS One, 9: e94431.

Galmarini S, De Arellano JVG, Duynkerke PG (1995). The effect of micro-scale turbulence on the reaction rate in a chemically reactive plume. Atmospheric Environment, 29: 87–95.

Gautam D, Bolia NB (2020). Air pollution: impact and interventions. Air Quality, Atmosphere & Health, 13: 209–223.

Goulart EV, Coceal O, Belcher SE (2018). Dispersion of a passive scalar within and above an urban street network. Boundary-Layer Meteorology, 166: 351–366.

Grawe D, Cai X, Harrison RM (2007). Large eddy simulation of shading effects on NO2 and O3 concentrations within an idealised street canyon. Atmospheric Environment, 41: 7304–7314.

He Y, Zhang L, Chen Z, et al. (2023). A framework of structural damage detection for civil structures using a combined multi-scale convolutional neural network and echo state network. Engineering with Computers, 39: 1771–1789.

Jiru TE, Bitsuamlak GT (2010). Application of CFD in modelling wind-induced natural ventilation of buildings—A review. International Journal of Ventilation, 9: 131–147.

Jones WP, Launder BE (1972). The prediction of laminarization with a two-equation model of turbulence. International Journal of Heat and Mass Transfer, 15: 301–314.

Kang YS, Baik JJ, Kim JJ (2008). Further studies of flow and reactive pollutant dispersion in a street canyon with bottom heating. Atmospheric Environment, 42: 4964–4975.

Karim AA, Nolan PF (2011). Modelling reacting localized air pollution using Computational Fluid Dynamics (CFD). Atmospheric Environment, 45: 889–895.

Kikumoto H, Ooka R (2012). A numerical study of air pollutant dispersion with bimolecular chemical reactions in an urban street canyon using large-eddy simulation. Atmospheric Environment, 54: 456–464.

Kikumoto H, Ooka R (2018). Large-eddy simulation of pollutant dispersion in a cavity at fine grid resolutions. Building and Environment, 127: 127–137.

Kwak KH, Baik JJ, Lee KY (2013). Dispersion and photochemical evolution of reactive pollutants in street canyons. Atmospheric Environment, 70: 98–107.

Leighton P (1961). Photochemistry of air pollution. New York: Academic Press.

Li CY, Tse TKT, Hu G (2020). Dynamic Mode Decomposition on pressure flow field analysis: Flow field reconstruction, accuracy, and practical significance. Journal of Wind Engineering and Industrial Aerodynamics, 205: 104278.

Li CY, Chen Z, Tse TKT, et al. (2021). Establishing direct phenomenological connections between fluid and structure by the Koopman-Linearly Time-Invariant analysis. Physics of Fluids, 33: 121707.

Li CY, Chen Z, Tse TKT, et al. (2022a). A parametric and feasibility study for data sampling of the dynamic mode decomposition: range, resolution, and universal convergence states. Nonlinear Dynamics, 107: 3683–3707.

Li CY, Chen Z, Tse TKT, et al. (2022b). A parametric and feasibility study for data sampling of the dynamic mode decomposition: Spectral insights and further explorations. Physics of Fluids, 34: 035102.

Liu J, Cui S, Chen G, et al. (2021). The influence of solar natural heating and NOx-O3 photochemistry on flow and reactive pollutant exposure in 2D street canyons. Science of the Total Environment, 759: 143527.

Meeder JP, Nieuwstadt FTM (2000). Large-eddy simulation of the turbulent dispersion of a reactive plume from a point source into a neutral atmospheric boundary layer. Atmospheric Environment, 34: 3563–3573.

Ming T, Nie C, Li W, et al. (2022). Numerical study of reactive pollutants diffusion in urban street canyons with a viaduct. Building Simulation, 15: 1227–1241.

NIOSH (2019). NIOSH Pocket Guide to Chemical Hazards. Washington, D.C.: The National Institute for Occupational Safety and Health.

Nuvolone D, Petri D, Voller F (2018). The effects of ozone on human health. Environmental Science and Pollution Research, 25: 8074–8088.

Ou Y, West JJ, Smith SJ, et al. (2020). Air pollution control strategies directly limiting national health damages in the US. Nature Communications, 11: 957.

Pasquill F (1974). Atmospheric Diffusion, 2nd edn. Chichester, UK: Ellis Horwood.

Ramponi R, Blocken B (2012). CFD simulation of cross-ventilation for a generic isolated building: Impact of computational parameters. Building and Environment, 53: 34–48.

Roache PJ (1997). Quantification of uncertainty in computational fluid dynamics. Annual Review of Fluid Mechanics, 29: 123–160.

Schatzmann M, Olesen H, Franke J (2010). COST 732 model evaluation case studies: Approach and results. COST Action.

Shih T-H, Liou WW, Shabbir A, et al. (1995). A new k-ε eddy viscosity model for high Reynolds number turbulent flows. Computers & Fluids, 24: 227–238.

Shu WR, Lamb RG, Seinfeld JH (1978). A model of second-order chemical reactions in turbulent fluid—Part Ⅱ. Application to atmospheric plumes. Atmospheric Environment (1967), 12: 1695–1704.

Snyder WH (1981). Guideline for Fluid Modeling of Atmospheric Diffusion. Research Triangle Park, NC, USA: U.S. Environmental Protection Agency.

Steinfeld JI (1998). Atmospheric chemistry and physics: From air pollution to climate change. Environment: Science and Policy for Sustainable Development, 40: 26.

Tominaga Y, Mochida A, Yoshie R, et al. (2008). AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings. Journal of Wind Engineering and Industrial Aerodynamics, 96: 1749–1761.

Tominaga Y, Stathopoulos T (2013). CFD simulation of near-field pollutant dispersion in the urban environment: A review of current modeling techniques. Atmospheric Environment, 79: 716–730.

Tong NYO, Leung DYC (2012). Effects of building aspect ratio, diurnal heating scenario, and wind speed on reactive pollutant dispersion in urban street canyons. Journal of Environmental Sciences (China), 24: 2091–2103.

van Hooff T, Blocken B (2010). Coupled urban wind flow and indoor natural ventilation modelling on a high-resolution grid: A case study for the Amsterdam ArenA stadium. Environmental Modelling & Software, 25: 51–65.

van Hooff T, Blocken B, Tominaga Y (2017). On the accuracy of CFD simulations of cross-ventilation flows for a generic isolated building: Comparison of RANS, LES and experiments. Building and Environment, 114: 148–165.

Weerasuriya AU, Zhang X, Tse KT, et al. (2022). RANS simulation of near-field dispersion of reactive air pollutants. Building and Environment, 207: 108553.

WHO (2018). Ambient Air Pollution: Health Impacts. World Health Organization.

Woodward H, Stettler M, Pavlidis D, et al. (2019). A large eddy simulation of the dispersion of traffic emissions by moving vehicles at an intersection. Atmospheric Environment, 215: 116891.

Wu R, Dai H, Geng Y, et al. (2017). Economic impacts from PM2.5 pollution-related health effects: a case study in Shanghai. Environmental Science & Technology, 51: 5035–5042.

Wu Z, Liu C-H (2019). Parameterisation study of chemically reactive pollutant dispersion over idealised urban areas based on the Gaussian plume model. International Journal of Environment and Pollution, 65: 84.

Xie Z-T, Castro IP (2009). Large-eddy simulation for flow and dispersion in urban streets. Atmospheric Environment, 43: 2174–2185.

Yakhot V, Orszag SA (1986). Renormalization group analysis of turbulence. I. Basic theory. Journal of Scientific Computing, 1: 3–51.

Yang W, Quan Y, Jin X, et al. (2008). Influences of equilibrium atmosphere boundary layer and turbulence parameter on wind loads of low-rise buildings. Journal of Wind Engineering and Industrial Aerodynamics, 96: 2080–2092.

Yang Y, Gu M, Chen S, et al. (2009). New inflow boundary conditions for modelling the neutral equilibrium atmospheric boundary layer in computational wind engineering. Journal of Wind Engineering and Industrial Aerodynamics, 97: 88–95.

Yang B, Zhang KM (2017). CFD-based turbulent reactive flow simulations of power plant plumes. Atmospheric Environment, 150: 77–86.

Yoshie R, Mochida A, Tominaga Y, et al. (2009). AIJ Cooperative project for practical applications of CFD to air ventilation, pollutant and thermal diffusion in urban areas. In: Proceedings of the 7th International Conference on Urban Climate, Yokohama, Japan.

Yu B, Ichinose F, Bloch DB, et al. (2019). Inhaled nitric oxide. British Journal of Pharmacology, 176: 246–255.

Zhang K, Chen G, Zhang Y, et al. (2020a). Integrated impacts of turbulent mixing and NOx-O3 photochemistry on reactive pollutant dispersion and intake fraction in shallow and deep street canyons. Science of the Total Environment, 712: 135553.

Zhang Y, Yang X, Yang H, et al. (2020b). Numerical investigations of reactive pollutant dispersion and personal exposure in 3D urban-like models. Building and Environment, 169: 106569.

Zhang X, Weerasuriya AU, Wang J, et al. (2022). Cross-ventilation of a generic building with various configurations of external and internal openings. Building and Environment, 207: 108447.

Zheng X, Yang J (2021). CFD simulations of wind flow and pollutant dispersion in a street canyon with traffic flow: Comparison between RANS and LES. Sustainable Cities and Society, 75: 103307.

Zheng X, Yang J (2022). Impact of moving traffic on pollutant transport in street canyons under perpendicular winds: A CFD analysis using large-eddy simulations. Sustainable Cities and Society, 82: 103911.

Zhong J, Cai X-M, Bloss WJ (2016). Coupling dynamics and chemistry in the air pollution modelling of street canyons: A review. Environmental Pollution, 214: 690–704.

Zhong J, Cai X-M, Bloss WJ (2017). Large eddy simulation of reactive pollutants in a deep urban street canyon: Coupling dynamics with O3-NOx-VOC chemistry. Environmental Pollution, 224: 171–184.

Zhou X, Ying A, Cong B, et al. (2021). Large eddy simulation of the effect of unstable thermal stratification on airflow and pollutant dispersion around a rectangular building. Journal of Wind Engineering and Industrial Aerodynamics, 211: 104526.

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Publication history
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Acknowledgements

Publication history

Received: 21 January 2023
Revised: 02 May 2023
Accepted: 09 May 2023
Published: 19 August 2023
Issue date: September 2023

Copyright

© Tsinghua University Press 2023

Acknowledgements

Acknowledgements

We would like to express our gratitude to the IT Office of the Department of Civil and Environmental Engineering at the Hong Kong University of Science and Technology for their invaluable assistance in the installation, testing, and maintenance of our high-performance servers. Additionally, Xing Zheng would like to acknowledge the support of Future Cities Lab Global at Singapore-ETH Centre. Future Cities Lab Global is supported and funded by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme and ETH Zurich (ETHZ).

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