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

  • Research Article
  • Indoor/Outdoor Airflow and Air Quality
  • Published:
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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.

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Data availability

The datasets generated during and/or analyzed during the current work are restricted by provisions of the funding source but are available from the corresponding author on reasonable request.

Abbreviations

ABL:

atmospheric boundary layer

c :

instantaneous concentration

cu j :

turbulent heat flux

C 0 :

reference concentration

C s :

roughness constant

D :

molecular diffusion coefficient or molecular diffusivity

Da :

Damköhler number

Da NO :

Damköhler number for NO

FAC2:

factor of 2 of the observation

FB:

fractional bias

F s :

safety factor

GCI:

grid convergence index

GES:

ground emission source

h :

elevated source height

hv:

solar photon

H :

reference height

I :

emission rate of NO

\({J_{{\rm{N}}{{\rm{O}}_2}}}\) :

photolysis rate of NO2

K :

normalized concentration

k :

turbulent kinetic energy

k 1 :

reaction rate

k 2 :

reaction rate

K c :

eddy diffusivity of the pollutants

K no :

normalized concentration for NO

\({K_{{\rm{N}}{{\rm{O}}_2}}}\) :

normalized concentration for NO2

\({K_{{\rm{N}}{{\rm{O}}_x}}}\) :

normalized concentration for NOx

l :

eddy length-scale

M:

a third-party molecule absorbs excess energy

NMSE:

normalized mean square error

O:

activated oxygen atom

p :

order of accuracy for GCI

p i :

instantaneous pressure

q :

hit rate

Q :

pollutant exhaust rate in the wind tunnel

Q e :

pollutant exhaust rate

r :

linear grid refinement for GCI

RANS:

Reynolds averaged Navier-Stokes equations

Re b :

building Reynolds number

RES:

roof emission source

RLZ:

realizable k-ε turbulence model

RNG:

renormalized group k-ε turbulence model

Sc t :

turbulent Schmidt number

S ij :

strain-rate tensor

Sno :

emission source of NO

\({S_{{\rm{N}}{{\rm{O}}_2}}}\) :

emission source of NO2

STK:

standard k-ε turbulence model

TKE:

turbulence kinetic energy

u, v, w :

wind speeds in longitudinal, lateral, vertical directions

u i :

instantaneous velocity

u i u j :

Reynolds stress

u T :

friction velocity

U j :

mean wind speed

U ref :

reference velocity

\(U_{{\rm{ABL}}}^ \ast \) :

friction velocity for atmospheric boundary layer

X i :

instantaneous position

z :

length in the vertical direction

z 0 :

roughness height

z ref :

reference height of z-direction

δ if :

Kronecker delta

ε :

turbulent kinetic energy dissipation rate

κ :

von Karman constant

ν t :

eddy viscosity

τ d :

turbulent diffusion time scale

τ r :

reaction time scale

τ r,NO :

chemical time scale for NO

τr,NO2 :

chemical time scale for NO2

τr,O3 :

chemical time scale for O3

φ :

diameter of the pollutant emission source

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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).

Funding

The work described in this paper was supported by the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. C7064-18G). Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. 16207118 and No. 16211821). This work is also partly supported by the Natural Science Foundation of Chongqing, China (Project No. cstc2019jcyj-msxmX0565 and No. cstc2020jcyj-msxmX0921), the Key Project of Technological Innovation and Application Development in Chongqing (Project No. cstc2019jscx-gksbX0017), and the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Project No. 311020001).

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Author notes

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

Authors and Affiliations

  1. Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China

    Yunfei Fu, Xisheng Lin & K. T. Tse

  2. Future Cities Lab global, Singapore-ETH Centre, Singapore, 138602, Singapore

    Xing Zheng

  3. Department of Building, Civil and Environmental Engineering at Concordia University, Montreal, Quebec, Canada

    Liangzhu Wang

  4. Department of Mechanical Engineering, The University of Hong Kong, Pok-fu-lam Road, Hong Kong, China

    Chun-Ho Liu

  5. Department of Civil Engineering, Chongqing University, Chongqing, China

    Cruz Y. Li

  6. School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, China

    Xuelin Zhang

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  1. Yunfei Fu
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Contributions

Yunfei Fu: conceptualization, methodology, data curation, writing—original draft preparation; Xisheng Lin: data curation, methodology; Xing Zheng: conceptualization, investigation; Chun-Ho Liu: project administration, funding acquisition, writing—review & editing; Xuelin Zhang: project administration, funding acquisition; Liangzhu Wang: project administration, funding acquisition; K.T. Tse: project administration, supervision, software, writing—review & editing, funding acquisition; Cruz Y. Li: supervision, investigation, data curation, writing—original draft preparation; writing—review & editing.

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Correspondence to Cruz Y. Li or K. T. Tse.

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

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Fu, Y., Lin, X., Zheng, X. et al. Physio-chemical modeling of the NOx-O3 photochemical cycle and the air pollutants’ reactive dispersion around an isolated building. Build. Simul. 16, 1735–1758 (2023). https://doi.org/10.1007/s12273-023-1042-0

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