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Research Article

Simulation of inhalable aerosol particle distribution generated from cooking by Eulerian approach with RNG k–epsilon turbulence model and pollution exposure in a residential kitchen space

Yu Liu, Huixing Li( ), Guohui Feng
School of Municipal and Environmental Engineering, Shenyang Jianzhu University, Shenyang 110168, China
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Abstract

Cooking-generated fume contains large amounts of fine particle pollutants with high concentration. To study the influence of the aerosol particle pollutant in kitchen, a typical format of residential kitchen in northern China is selected in this paper. FLUENT software is applied to simulate interior space airflow as well as pollutant mass fraction in breathing-section and cooking-section area in the residential kitchen under different vent cases. Furthermore, occupant’s exposure to inhalable aerosol particle is obtained integrated with human inhale model and pollution exposure calculation model. The results demonstrate that cooking side of respiratory region in pollutant mass fraction can be significantly reduced when opening the door, but mass fraction gradient is larger in the vicinity of the stove. The average pollution exposure in the maximum value is about 90 times than that of the minimum value around the cooking personnel with the most adverse conditions in winter when the doors and windows are all closed. The research output can provide valuable reference for the further study on fine particles concentration level as well as to determine individual intake fraction of particles generated in the process of cooking in the residential kitchen.

Keywords

numerical simulationcooking-generated fumeinhalable aerosol particlebreathing modeloccupant’s exposure to pollutants

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Building Simulation
Volume 10 Issue 1,
February 2017
Pages 135-144
DOI: 10.1007/s12273-016-0313-4
Cite this article:
Liu Y, Li H, Feng G. Simulation of inhalable aerosol particle distribution generated from cooking by Eulerian approach with RNG k–epsilon turbulence model and pollution exposure in a residential kitchen space. Building Simulation, 2017, 10(1): 135-144. https://doi.org/10.1007/s12273-016-0313-4

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Received: 20 May 2016
Revised: 13 July 2016
Accepted: 21 July 2016
Published: 06 September 2016
© Tsinghua University Press and Springer-Verlag Berlin Heidelberg 2016
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