Restricted accessResearch articleFirst published online 2020
Numerical study of the influence of ventilation modes on the distribution and deposition of particles generated from a specific cooking process in a residential kitchen
Computational fluid dynamics have been used to numerically study the particle diffusion and deposition in a residential kitchen under several ventilation modes. First, combining the renormalized group turbulent model with cooking release conditions, the airflow field in a kitchen was simulated and its airflow characteristics were analysed. Second, the drift flux model was adopted to predict the spatial distribution of particles, quantifying various mechanisms that affect the particle diffusion. Finally, the deposition flux towards the wall was determined by a semi-empirical particle deposition model. The results show that the rising thermal plume has a great influence on the diffusion of particles. When particles with small sizes diffuse in the kitchen, the influence of turbulence plays a crucial role. The case studies show that the ventilation form is an important factor affecting the concentration distribution and deposition of particles. However, the ultrafine particles distribution with different sizes is little sensitized to changes of the airflow field. The results also show that the main determinant of the deposition flux is the particle concentration near the wall. There is not much difference in the particle deposition flux under different particle sizes, which is related to the larger air exchange rate.
WangLZhengXStevanovicSWuXXiangZYuMLiuJ.Characterization particulate matter from several Chinese cooking dishes and implications in health effects. J Environ Sci2018;
72: 98–106.
2.
Amouei TorkmahallehMOspanovaSBaibatyrovaANurbaySZhanakhmetGShahD.Contributions of burner, pan, meat and salt to PM emission during grilling. Environ Res2018;
164: 11–17.
3.
ZhaoYChenCZhaoB.Emission characteristics of PM2.5-bound chemicals from residential Chinese cooking. Build Environ2019;
149: 623–629.
4.
LiSGaoJHeYCaoLLiAMoSCaoY.Determination of time- and size-dependent fine particle emission with varied oil heating in an experimental kitchen. J Environ Sci2017;
51: 157–164.
5.
WanM-PWuC-LSze ToG-NChanT-CChaoCYH.Ultrafine particles, and PM2.5 generated from cooking in homes. Atmos Environ2011;
45: 6141–6148.
6.
WangGChengSWeiWWenWWangXYaoS.Chemical characteristics of fine particles emitted from different Chinese cooking styles. Aerosol Air Qual Res2015;
15: 2357–2366.
7.
YiHHuangYTangXZhaoSXieXZhangY.Characteristics of non-methane hydrocarbons and benzene series emission from commonly cooking oil fumes. Atmos Environ2019;
200: 208–220.
8.
Amouei TorkmahallehMGorjinezhadSUnluevcekHSHopkePK.Review of factors impacting emission/concentration of cooking generated particulate matter. Sci Total Environ2017;
586: 1046–1056.
9.
GorjinezhadSKerimrayAAmouei TorkmahallehMKelesMOzturkFHopkePK.Quantifying trace elements in the emitted particulate matter during cooking and health risk assessment. Environ Sci Pollut Res Int2017;
24: 9515–9529.
10.
ZhaiSRAlbrittonD.Airborne particles from cooking oils: emission test and analysis on chemical and health implications. Sustainable Cities Soc2020;
52: 101845.
11.
ChoHYounJSOhIJungYWJeonKJ.Determination of the emission rate for ultrafine and accumulation mode particles as a function of time during the pan-frying of fish. J Environ Manage2019;
236: 75–80.
12.
BuonannoGMarksGBMorawskaL.Health effects of daily airborne particle dose in children: direct association between personal dose and respiratory health effects. Environ Pollut2013;
180: 246–250.
13.
StabileLBuonannoGFiccoGScungioM.Smokers' lung cancer risk related to the cigarette-generated mainstream particles. J Aerosol Sci2017;
107: 41–54.
14.
PacittoAStabileLVianaMScungioMRecheCQuerolXAlastueyARivasIAlvarez-PedrerolMSunyerJDroogeBLGrimaltJOSozziRVigoPBuonannoG.Particle-related exposure, dose and lung cancer risk of primary school children in two European countries. Sci Total Environ2018;
616–617: 720–729.
15.
LaiACKChenFZ.Modeling of cooking-emitted particle dispersion and deposition in a residential flat: a real room application. Build Environ2007;
42: 3253–3260.
16.
GaoJCaoCXiaoQXuBZhouXZhangX.Determination of dynamic intake fraction of cooking-generated particles in the kitchen. Build Environ2013;
65: 146–153.
17.
GaoJJianYCaoCChenLZhangX.Indoor emission, dispersion and exposure of total particle-bound polycyclic aromatic hydrocarbons during cooking. Atmos Environ2015;
120: 191–199.
18.
LaiACK.Particle deposition indoors: a review. Indoor Air2002;
12: 211–214.
ChenCLinC-HWeiDChenQ.Modeling particle deposition on the surfaces around a multi-slot diffuser. Build Environ2016;
107: 79–89.
21.
LvYWangHZhouYYoshinoHYonekuraHTakakiRKuriharaG.The influence of ventilation mode and personnel walking behavior on distribution characteristics of indoor particles. Build Environ2019;
149: 582–591.
22.
ChenXLiA.An experimental study on particle deposition above near-wall heat source. Build Environ2014;
81: 139–149.
23.
LvYWangHWeiS.The transmission characteristics of indoor particles under two ventilation modes. Energy Build2018;
163: 1–9.
24.
CaoQLiuYLiuWLinC-HWeiDBaughcumSNorrisSShenXLongZChenQ.Experimental study of particle deposition in the environmental control systems of commercial airliners. Build Environ2016;
96: 62–71.
25.
SajjadiHSalmanzadehMAhmadiGJafariS.Simulations of indoor airflow and particle dispersion and deposition by the lattice Boltzmann method using LES and RANS approaches. Build Environ2016;
102: 1–12.
26.
PanYLinC-HWeiDChenC.Experimental measurements and large eddy simulation of particle deposition distribution around a multi-slot diffuser. Build Environ2019;
150: 156–163.
27.
ZhouYDengYWuPCaoS-J.The effects of ventilation and floor heating systems on the dispersion and deposition of fine particles in an enclosed environment. Build Environ2017;
125: 192–205.
28.
ZhangZChenXMazumdarSZhangTChenQ.Experimental and numerical investigation of airflow and contaminant transport in an airliner cabin mockup. Build Environ2009;
44: 85–94.
29.
QianHLiY.Removal of exhaled particles by ventilation and deposition in a multibed airborne infection isolation room. Indoor Air2010;
20: 284–297.
30.
MaoJGaoN.The airborne transmission of infection between flats in high-rise residential buildings: a review. Build Environ2015;
94: 516–531.
31.
HanOLiAKosonenR.Hood performance and capture efficiency of kitchens: a review. Build Environ2019;
161: 106221.
32.
LiuYLiHFengG.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. Build Simul2016;
10: 135–144.
DobbinNASunLWallaceLKulkaRYouHShinTAubinDSt-JeanMSingerBC.The benefit of kitchen exhaust fan use after cooking – an experimental assessment. Build Environ2018;
135: 286–296.
35.
ZhuangCYangGLongTHuD.Numerical comparison of removal and deposition for fully-distributed particles in central- and split-type air-conditioning rooms. Build Environ2017;
112: 17–28.
GolkarfardVTalebizadehP.Numerical comparison of airborne particles deposition and dispersion in radiator and floor heating systems. Adv Powder Technol2014;
25: 389–397.
38.
HolmbergSLiY.Modelling of the indoor environment – particle dispersion and deposition. Indoor Air1998;
8: 113–122.
39.
ZhaoBLiXZhangZ.Numerical study of particle deposition in two differently ventilated rooms. Indoor Built Environ2004;
13: 443–451.
40.
CaoCGaoJWuLDingXZhangX.Ventilation improvement for reducing individual exposure to cooking-generated particles in Chinese residential kitchen. Indoor Built Environ2016;
26: 226–237.
41.
ParkerSNallyJFoatTPrestonS.Refinement and testing of the drift-flux model for indoor aerosol dispersion and deposition modelling. J Aerosol Sci2010;
41: 921–934.
42.
ZhaoBChenCTanZ.Modeling of ultrafine particle dispersion in indoor environments with an improved drift flux model. J Aerosol Sci2009;
40: 29–43.
43.
HindsWC.Aerosol technology: properties, behavior, and measurement of airborne particles. 2nd ed.
New York:
Wiley, 1999.
44.
CroweCT.Multiphase flows with droplets and particles. 2nd ed.
Boca Raton, FL:
CRC Press, 1998.
45.
TalbotLChengRKScheferRWWillisDR.Thermophoresis of particles in a heated boundary layer. J Fluid Mech1980;
101: 737–758.
46.
CamuffoD.Dry deposition of airborne particulate matter—mechanisms and effects. Microclimate for cultural heritage.
Amsterdam, Netherlands:
Elsevier Science, 2019.
47.
ChenFYuSCMLaiACK.Modeling particle distribution and deposition in indoor environments with a new drift–flux model. Atmos Environ2006;
40: 357–367.
ZhouBChenFDongZNielsenPV.Study on pollution control in residential kitchen based on the push-pull ventilation system. Build Environ2016;
107: 99–112.
51.
GaoJCaoCZhangXLuoZ.Volume-based size distribution of accumulation and coarse particles (PM0.1–10) from cooking fume during oil heating. Build Environ2013;
59: 575–580.
52.
ZhaoBZhangYLiXYangXHuangD.Comparison of indoor aerosol particle concentration and deposition in different ventilated rooms by numerical method. Build Environ2004;
39: 1–8.
53.
HongBLinBQinH.Numerical investigation on the coupled effects of building-tree arrangements on fine particulate matter (PM2.5) dispersion in housing blocks. Sustainable Cities Soc2017;
34: 358–370.
54.
ZhaoBWuJ.Effect of particle spatial distribution on particle deposition in ventilation rooms. J Hazard Mater2009;
170: 449–456.
55.
Grau-BovéJStrličMMazzeiL.Applicability of a drift-flux model of aerosol deposition in a test tunnel and an indoor heritage environment. Build Environ2016;
106: 78–90.
56.
NaseriMJouzizadehMTabeshMMalekipirbazzariMGabdrashovaRNurzhanSFarrokhiHKhanbabaieRMehri-DehnaviHBekezhankyzyZGimnkhanADareiniMKurmangaliyevaAIslamNCrapeBBuonannoGCasseeFTorkmahallehMA.The impact of frying aerosol on human brain activity. Neuro Toxicol2019;
74: 149–161.
57.
LaiACKChenJ.Numerical study of cooking particle coagulation by using an Eulerian model. Build Environ2015;
89: 38–47.
58.
LaiACKHoYW.Spatial concentration variation of cooking-emitted particles in a residential kitchen. Build Environ2008;
43: 871–876.
