Multi-stage downscaling procedure to analyse the impact of exposure concentration in a factory on a specific worker through computational fluid dynamics modelling
Restricted accessResearch articleFirst published online April, 2018
Multi-stage downscaling procedure to analyse the impact of exposure concentration in a factory on a specific worker through computational fluid dynamics modelling
Indoor air quality plays a significant role in human health, especially for those who spend the majority of their time indoors, as is the case of workers in the industrial field. The control of contaminants inside the occupational indoor environment becomes critically important for promoting health. In terms of Health Impact Assessment, indoor air quality inside a factory becomes an essential factor of industrial hygiene. Here, computational fluid dynamics-based indoor environmental design was applied to potentially evaluate the environmental quality in a factory and to improve industrial hygiene. In particular, this study proposes an integrated simulation procedure to predict the inhalation exposure concentration of a hazardous chemical compound (here, cyclohexanone) by using a multi-stage, one-way nesting method. This procedure connects a factory building space, a micro-climate around the human body, and a respiratory tract in the human body. This research provides quantitative and qualitative detailed information of contaminant dosing in workers. The exact inhalation dose of contaminants in the human airways can be estimated based on factory-environment conditions through this procedure. Subsequently, the average contaminant concentration in the work place and inside the human body can be calculated.
SundellJ. On the history of indoor air quality and health. Indoor Air2004; 14: 51–58.
2.
LinSJonesRMunsieJPNayakSGFitzgeraldEFHwangSA. Childhood asthma and indoor allergen exposure and sensitization in Buffalo, New York. Int J Hyg Environ Health2012; 215: 297–305.
3.
DiezUKroebnerTRehwagenMRichterMWetzigHSchulzRBorteMMetznerGKrumbiegelPHerbarthO. Effects of indoor painting and smoking on airway symptoms and atopy risks children in the first year of life results of the LARS study. Int J Hyg Environ Health2000; 203: 23–28.
4.
de Oliveira Fernandes E, Jantunen M, Carrer P, Seppanen O, Harrison P and Kephalopoulos S. EnVIE Co-ordination action on indoor air quality and health effects. Final Activity Report. PF6, Project No. SSPE-CT-2004-502671; European Commission, Community Research and Development Information Service (CORDIS), Porto, Portugal, 2009, p.165.
5.
FelixPMAlmeidaSMPinheiroTSousaJFrancoCWolterbeekH. Assessment of exposure to metals in lead processing industries. Int J Hyg Environ Health2003; 216: 17–24.
6.
JonesAP. Indoor air quality and health. Atmos Environ1999; 33: 4535–4564.
7.
Walgocki P and Seppänen O. Indoor climate and productivity in offices. REHVA Guidebook No. 6. Brussels: Federation of European Heating and Air-conditioning Associations, REHVA, 2006.
8.
Murakami S, Kaneko T, Ito K and Fukao H. Study on the productivity in classroom (Part 1) field survey on effects of air quality/thermal environment on learning performance. In: HB 2006. The 8th international conference and exhibition on healthy buildings 2006, Lisboa, Portugal, June 4–8 2006; pp.271-276.
9.
Ito K, Murakami TK and Fukao H. Study on the productivity in classroom (part 2) realistic simulation experiment on effects of air quality/thermal environment on learning performance. In: HB 2006, the 8th International Conference and Exhibition on Healthy Buildings 2006, Lisboa, Portugal, June 4–8 2006; pp.207–212.
10.
Kameda K, Murakami S, Ito K and Kaneko T. Study on the productivity in classroom (part 3) nationwide questionnaire survey on effects of indoor environmental quality on learning performance. In: The 9th REHVA World Congress, CLIMA 2007, “Wellbeing Indoors”, Helsinki, Finland, June 10–14 2007; p.405.
11.
KeLShunzhangY. Leukemia mortality and occupational exposure to rubber: a nested case-control study. Int J Hyg Environ Health2002; 204: 317–321.
12.
VerbeekJ. When work is related to disease, what establishes evidence for a casual relation?Saf Health Work2012; 3: 110–116.
13.
International Labour Organization. The prevention of occupational diseases, World Day for safety and health at work. Geneva: International Labour Organization, 2013. ISBN 978-92-2-127447-6.
14.
LeeBK. Occupational health management in the lead industry: the Korean experience. Saf Health Work2011; 2: 87–96.
15.
HorieS. Occupational health policies on risk assessment in Japan. Saf Health Work2010; 1: 19–28.
16.
VerbeekJIvanovI. Essential occupational safety and health interventions for low-and middle- income countries: an overview of the evidence. Saf Health Work2013; 4: 77–83.
17.
LaDouJ. International occupational health. Int J Hyg Environ Health2003; 206: 303–313.
18.
AwodeleOPopoolaDOgbuduBSAkinyedeACokerHABAkintonwaA. Occupational health hazards and safety measures amongst the paint factory workers in Lagos, Nigeria. Saf Health Work2014; 5: 106–111.
19.
International Labour Foundation for Sustainable Development. National Report: Chemicals in El Salvador – main sectoral risks, legislation and impacts on workers and the environment, Sustain Labour, El Salvador 2012.
20.
Chamber of Textile Industry. Clothing and tax-free zones in El Salvador. CAMTEX. Profile of textile, clothing and tax-free zones, Industry Report, CAMTEX, El Salvador 2014; p.3 (in Spanish).
21.
GadSCDerelankoMJPowersWJMulderSGaviganFBabichPC. Toxicity of cyclohexanone oxime. Toxicol Sci1985; 5: 128–136.
22.
GuptaPKLawrenceWHTurnerJEAutianJ. Toxicological aspects of cyclohexanone. Toxicol Appl Pharmacol1979; 49: 525–533.
23.
MitranECallenderTOrhaBDragneaPBotezatuG. Neurotoxicity associated with occupational exposure to acetone, methyl ethyl ketane, and cyclohexanone. Environ Res1997; 73: 181–188.
24.
KeshavaNOngTM. Occupational exposure to genotoxic agents. Mutat Res Rev Mutat Res1999; 437: 175–194.
25.
ViaeneMVermeirGGodderisL. Sleep disturbances and occupational exposure to solvents. Sleep Med Rev2009; 13: 235–243.
26.
Grant S, Wilkinson J and Learmonth A. Occasional Paper No. 1: an overview of health impact assessment, Technical Report. Northern and Yorkshire Public Health Observatory, Public Health England, Stockton on Tees, England, May 2001.
27.
SonnemannGCastellsFSchuhmacherM. Integrated life-cycle and risk assessment for industrial processes, Boca Raton, FL: CRC Press LLC, 2004.
28.
NielsenPV. Fifty years of CFD for room air distribution. Build Environ2015; 91: 78–90.
29.
NielsenPV. Computational fluid dynamics and room air movement. Indoor Air2004; 14: 34–43.
30.
ChenQ. Ventilation performance prediction for buildings: a method overview and recent applications. Build Environ2009; 44: 848–58.
31.
JonesPJWhittleGE. Computational fluid dynamics for building airflow prediction – current status and capabilities. Build Environ1992; 27: 321–38.
32.
Nielsen PV. Prediction of air flow and comfort in air conditioned spaces. ASHRAE Trans 1975; 81. Part II.
33.
KassomenosPKarayannisAPanagopaulosIKarakitsiosKPetrakisM. Modelling the dispersion of a toxic substance at a workplace. Environ Modell Software2008; 23: 82–9.
34.
LiJYavuzICelikIGuffeyS. Predicting worker exposure – the effect of ventilation velocity, free-stream turbulence and thermal condition. Occup Environ Hygiene2007; 4: 864–874.
35.
HelmisCGTzoutzasJFlocasHAHaliosCHStathopolouOIAssimakopoulosVDPanisVApestolatouMSgourosG. Indoor air quality in a dentistry clinic. Sci Total Environ2007; 377: 349–65.
36.
ZhaiZ. Application of computational fluid dynamics in building design: aspects and trends. Indoor Built Environ2006; 15: 305–313.
37.
SrebricJHeidarinejadMLiuJ. Building neighbourhood emerging properties and their impact on multi-scale modeling of building energy and airflows. Build Environ2015; 91: 246–262.
38.
Srebric J. Opportunities and challenges for multi-scale modelling of sustainable buildings. In: US Frontiers of Engineering, report on leading-edge engineering from the 2011 symposium, National Academy of Engineering, Washington DC, September 19–21 2011; pp.97–100.
39.
ItoK. Integrated numerical approach of CFD and epidemiological model for multi-scale transmission analysis in indoor Spaces. Indoor Built Environ2014; 23: 1029–1049.
40.
RohdinPMoshfeghB. Numerical predictions of indoor climate in large industrial premises. A comparison between different k-e models supported by field measurements. Build Environ2007; 42: 3872–3882.
41.
ChenQ. Comparison of different k-e models for indoor airflow computations. Numer Heat Transfer1995; 28: 353–369.
42.
TianZFTuJYYeoGHYuenRKK. On the numerical study of contaminant particle concentration in indoor airflow. Build Environ2006; 41: 94–108.
43.
ANSYS/Fluent manual, Release 15.0. Pennsylvania, PA: ANSYS Inc., SAS IP Inc., 2013.
44.
GosselingJRChenQ. A computational method for calculating heat transfer and airflow through a dual-airflow window. Energy Build2008; 40: 452–458.
45.
HolmerI. Thermal manikin history and applications. Eur J Appl Physiol2004; 92: 614–618.
46.
CheongKWYuWJKonosenRThamKWSekharSC. Assessment of thermal environment using a thermal manikin in a field environment chamber served by displacement ventilation system. Build Environ2006; 41: 1661–1670.
47.
Zhang Y, Novieto D and Yingchun J. Human environmental heat transfer simulation with CFD, the advances and challenges. In: Proceedings of the 11th international IBPSA conference. building simulation 2009, IBPSA, Glasgow, July 27–30 2009, pp.2162–2168.
48.
HayashiTIshizuYKatoSMurakamiS. CFD analysis on characteristics of contaminated indoor air ventilation and its application in the evaluation of the effects of contaminant inhalation by a human occupant. Build Environ2002; 37: 219–230.
49.
SorensenDNVoightLK. Modelling flow and heat transfer around a seated human body by CFD. Build Environ2003; 38: 753–762.
50.
CroitoruC. Airflow and heat transfer modelling for a human body by computational fluid dynamics. Scient J Tech Univ Civil Eng2011; 1–2: 77–83.
51.
ItoKHottaT. Development of virtual manikins and its grid library for CFD analysis. Transact SHASE (The Society of Heating, Air-Conditioning and Sanitary Engineers of Japan)2006; 113: 27–34. (in Japanese).
52.
AbeKKondohTNaganoY. A new turbulence model for predicting fluid flow and heat transfer in separating and reattaching flows: flow-field calculations. Int J Heat Mass Transfer1994; 37: 139–151.
53.
Koch SE. A survey of nested grid techniques and their potential for use within the mass weather prediction model. NASA, Technical Memorandum 87808, Greenbelt, MD, 1987.
54.
Harris LM and Durran DR. An idealized comparison of one-way and two-way grid nesting. Mon Weather Rev 2009; 138: 2174–2187.
55.
KunzRMoussiopoulosN. Implementation and assessment of a one-way nesting technique for high resolution wind flow simulations. Atmos Environ1997; 31: 3167–3176.
56.
MaBRuwetVCorieriPTheunissenRRiethmullerM. CFD simulation and experimental validation of fluid flow and particle transport in a model of alveolated airways. Aerosol Sci2009; 40: 403–414.
57.
Rahimi-GorjiMPourmehranOGorji-BandpyMGorjiTB. CFD simulation of airflow behaviour and particle transport and deposition in different breathing conditions through the realistic model of human airways. J Mol Liq2005; 209: 121–133.
58.
InthavongKZhangKTuJY. Numerical modelling and verification of nanoparticle deposition and its application in the nasal cavity and the tracheobronchial. Comput Meth Biol Med Eng2011; 14: 633–643.
59.
TuJYInthavongKAhmadiG. Computational fluid and particle dynamics in the human respiratory system, Berlin: Springer, 2013.
60.
ItoK. Toward the development of an in silico human model for indoor environmental design. Proc Jpn Acad Ser B2016; 92: 185–203.
61.
Yoo SJ and Ito K. Numerical prediction of airway tissue dosimetry using PBPK-CFD hybrid model integrated into computer simulated person. In: Proceedings of indoor air 2016, the 14th international conference on indoor air quality and climate, ISIAQ, Belgium, 3–8 July 2016, p.87. Paper ID-698 2016.
62.
PhuongNLItoK. Investigation of flow pattern in a realistic replica model of human respiratory tract using PIV. Build Environ2015; 94: 504–515.
63.
ItoKInthavongKKurabuchiTUedaTEndoTOmoriTOnoHKatoSSakaiKSuwaYMatsumotoHYoshinoHZhangWTuJY. CFD Benchmark Tests for Indoor Environmental Problems: Part 1 Ishothermal/non-ishotermal flow in 2D and 3D room model. Int J Architect Eng Technol2015; 2: 1–22.
64.
ItoKInthavongKKurabuchiTUedaTEndoTOmoriTOnoHKatoSSakaiKSuwaYMatsumotoHYoshinoHZhangWTuJY. CFD benchmark tests for indoor environmental problems: Part 2 cross-ventilation airflows and floor heating systems. Int J Architect Eng Technol2015; 2: 23–49.
65.
ItoKInthavongKKurabuchiTUedaTEndoTOmoriTOnoHKatoSSakaiKSuwaYMatsumotoHYoshinoHZhangWTuJY. CFD benchmark tests for indoor environmental problems: Part 3 Numerical thermal manikins. Int J Architect Eng Technol2015; 2: 50–75.
66.
ItoKInthavongKKurabuchiTUedaTEndoTOmoriTOnoHKatoSSakaiKSuwaYMatsumotoHYoshinoHZhangWTuJY. CFD benchmark tests for indoor environmental problems: Part 4 Air-conditioning airflows. Residential kitchen airflows and Fire-induced flow. Int J Architect Eng Technol2015; 2: 76–102.
67.
SørensenDNNielsenPV. Quality control of computational fluid dynamics in indoor environments. Indoor Air2003; 13: 2–17.
68.
Nielsen PV, Awbi FA, Davidson H and Schalin A. Computational fluid dynamics in ventilation design, REHVA Guidebook No. 10. Brussels: Federation of European Heating and Air-conditioning Associations, REHVA, 2007.
