# Indoor Airflow Dynamics in Compartmentalized Pneumology Units Equipped with Variable-Thickness MERV-13 Filters

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## Abstract

**:**

## 1. Introduction

## 2. Background

#### 2.1. Filtration Systems for Indoor Environment

#### 2.2. Brazilian Hospital Standards

- Level 0. Areas where the risk does not exceed that found in public and collective environments.
- Level 1. Areas in which no health risks related to air quality have been found, but some authorities, organizations, or researchers suggest that some risks should be considered.
- Level 2. Areas in which there is strong evidence of the risk of occurrence of health hazards related to air quality to their occupants or patients, who will use products manipulate in these areas based on well-delineated clinical or epidemiological experimental studies.
- Level 3. Areas where there is strong evidence of a high risk of air quality-related health hazards to their occupants or patients, who will use products manipulated in these areas, under well-delineated experimental, clinical, or epidemiological studies.

## 3. Methodology

#### 3.1. Mathematical Formulation

#### 3.2. Filter Characterization

#### 3.3. Problem Setting

^{3}) divided into 3 smaller rooms (Figure 3). For each room, we assumed that the air-conditioning system is driven by ducts with a squared cross section, 200 $\mathrm{m}$$\mathrm{m}$ length, and feeding inlet (intake grilles) located on the ceiling, besides outlets (exhaust grilles) at the bottom of the walls (Figure 4).

#### 3.4. Discretization Procedures

## 4. Results and Discussion

- Case 0: no device;
- Case 1: 1-inch device;
- Case 2: 2-inch device.

#### 4.1. Statistical Analysis

#### 4.2. Hydrodynamic Analysis

#### 4.3. Numerical Analysis

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Acknowledgments

## Conflicts of Interest

## References

- Chakraborty, I.; Maity, P. COVID-19 outbreak: Migration, effects on society, global environment and prevention. Sci. Total Environ.
**2020**, 728, 138882. [Google Scholar] [CrossRef] - CDC. Scientific Brief: SARS-CoV-2 Transmission. 2021. Available online: https://www.cdc.gov/coronavirus/2019-ncov/science/science-briefs/sars-cov-2-transmission.html (accessed on 10 February 2022).
- Alrebi, O.F.; Obeidat, B.; Abdallah, I.A.; Darwish, E.F.; Amhamed, A. Airflow dynamics in an emergency department: A CFD simulation study to analyse COVID-19 dispersion. Alex. Eng. J.
**2022**, 61, 3435–3445. [Google Scholar] [CrossRef] - Ding, J.; Yu, C.W.; Cao, S.J. HVAC systems for environmental control to minimize the COVID-19 infection. Indoor Built Environ.
**2020**, 29, 1195–1201. [Google Scholar] [CrossRef] - Liu, Y.; Ning, Z.; Chen, Y.; Guo, M.; Liu, Y.; Gali, N.K.; Sun, L.; Duan, Y.; Cai, J.; Westerdah, D.; et al. Aerodynamic analysis of SARS-CoV-2 in two Wuhan hospitals. Nature
**2020**, 582, 557–560. [Google Scholar] [CrossRef] - Machado, A.A. Infecção pelo vírus Influenza A (H1N1) de origem suína: Como reconhecer, diagnosticar e prevenir. J. Bras. Pneumol.
**2009**, 35, 464–469. [Google Scholar] [CrossRef] [PubMed] - Schwartzmann, P.V.; Volpe, G.J.; Vilar, F.C.; Moriguti, J.C. Pneumonia comunitária e pneumonia hospitalar em adultos. Medicina (Ribeirão Preto)
**2010**, 43, 238–248. [Google Scholar] [CrossRef] - Eslami, H.; Jalili, M. The role of environmental factors to transmission of SARS-CoV-2 (COVID-19). AMB Express
**2020**, 10, 92. [Google Scholar] [CrossRef] - Kwon, T.; Gaudreault, N.N.; Richt, J.A. Environmental stability of SARS-CoV-2 on different types of surfaces under indoor and seasonal climate conditions. Pathogens
**2021**, 10, 227. [Google Scholar] [CrossRef] - Stadnytskyi, V.; Bax, C.E.; Bax, A.; Anfinrud, P. The airborne lifetime of small speech droplets and their potential importance in SARS-CoV-2 transmission. Proc. Natl. Acad. Sci. USA
**2020**, 117, 11875–11877. [Google Scholar] [CrossRef] - Wang, J.; Tang, K.; Feng, K.; Lv, W. High Temperature and High Humidity Reduce the Transmission of COVID-19. BMJ Open
**2020**, 3551767, 2020b. Available online: https://www.researchgate.net/publication/339873481_High_Temperature_and_High_Humidity_Reduce_the_Transmission_of_COVID-19 (accessed on 3 February 2023). [CrossRef] - Satheesan, M.K.; Mui, K.W.; Wong, L.T. A numerical study of ventilation strategies for infection risk mitigation in general inpatient wards. In Proceedings of the Building Simulation, Loughborough, UK, 21–22 September 2020; Springer: Berlin/Heidelberg, Germany, 2020; pp. 1–10. [Google Scholar]
- Bourouiba, L. The fluid dynamics of disease transmission. Annu. Rev. Fluid Mech.
**2020**, 53, 473–508. [Google Scholar] [CrossRef] - Löhner, R.; Antil, H.; Idelsohn, S.; Oñate, E. Detailed simulation of viral propagation in the built environment. Comput. Mech.
**2020**, 66, 1093–1107. [Google Scholar] [CrossRef] [PubMed] - Vuorinen, V.; Aarnio, M.; Alava, M.; Alopaeus, V.; Atanasova, N.; Auvinen, M.; Balasubramanian, N.; Bordbar, H.; Erästö, P.; Grande, R.; et al. Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoors. Saf. Sci.
**2020**, 130, 104866. [Google Scholar] [CrossRef] [PubMed] - Al-Baghdadi, M.A.S. CFD analysis of spread COVID-19 with air conditioning systems. Int. J. Energy Environ.
**2021**, 12, 63–73. [Google Scholar] - Barbosa, B.P.P.; de Carvalho Lobo Brum, N. Ventilation mode performance against airborne respiratory infections in small office spaces: Limits and rational improvements for COVID-19. J. Braz. Soc. Mech. Sci. Eng.
**2021**, 43, 316. [Google Scholar] [CrossRef] - Ren, C.; Zhu, H.C.; Cao, S.J. Ventilation Strategies for Mitigation of Infection Disease Transmission in an Indoor Environment: A Case Study in Office. Buildings
**2022**, 12, 180. [Google Scholar] [CrossRef] - Zhang, J.; Huntley, D.; Fox, A.; Gerhardt, B.; Vatine, A.; Cherne, J. Study of viral filtration performance of residential HVAC filters. ASHRAE J.
**2020**, 62, 26–32. [Google Scholar] - ASHRAE. Filtration/Disinfection. 2021. Available online: https://www.ashrae.org/technical-resources/filtration-disinfection (accessed on 10 February 2022).
- Mousavi, E.S.; Kananizadeh, N.; Martinello, R.A.; Sherman, J.D. COVID-19 outbreak and hospital air quality: A systematic review of evidence on air filtration and recirculation. Environ. Sci. Technol.
**2020**, 55, 4134–4147. [Google Scholar] [CrossRef] [PubMed] - ANVISA. COVID-19: Tudo Sobre Máscaras Faciais de Proteção. 2020. Available online: https://www.gov.br/anvisa/pt-br/assuntos/noticias-anvisa/2020/covid-19-tudo-sobre-mascaras-faciais-de-protecao (accessed on 10 February 2022).
- Chia, P.Y.; Coleman, K.K.; Tan, Y.K.; Ong, S.W.X.; Gum, M.; Lau, S.K.; Lim, X.F.; Lim, A.S.; Sutjipto, S.; Lee, P.H.; et al. Detection of air and surface contamination by SARS-CoV-2 in hospital rooms of infected patients. Nat. Commun.
**2020**, 11, 2800. [Google Scholar] [CrossRef] - López-Rebollar, B.M.; Posadas-Bejarano, A.; García-Pulido, D.; Torres-Maya, A.; Díaz-Delgado, C. Proposal of a Mask and Its Performance Analysis with CFD for an Enhanced Aerodynamic Geometry That Facilitates Filtering and Breathing against COVID-19. Fluids
**2021**, 6, 408. [Google Scholar] [CrossRef] - Siemens Digital Industries Software. Simcenter STAR-CCM+ User Guide, version 2021.1. In Adaptive Mesh Refinement for Overset Meshes; Siemens: Berlin, Germany, 2021; pp. 3067–3070. [Google Scholar]
- ANVISA. Resolução n. 9, de 16 de Janeiro de 2003; Technical Report; Ministério da Saúde: Brasília, Brazil, 2003.
- ABNT. NBR-7256, Tratamento de ar em Estabelecimento Assistenciais de Saúde (EAS): Requisitos Para Projetos e Execução das Instalações; Associação Brasileira de Normas técnicas: Rio de Janeiro, Brazil, 2005. [Google Scholar]
- ABNT. Instalação de Ar-Condicionado—Sistemas Centrais e Unitários—Parte 2: Parâmetros de Conforto Térmico; Technical Report; Brazilian Technical Standards Association: Rio de Janeiro, Brazil, 2008. [Google Scholar]
- ABNT. Instalação de Ar-Condicionado—Sistemas Centrais e Unitários—Parte 3: Qualidade do Ar Interior; Technical Report; Brazilian Technical Standards Association: Rio de Janeiro, Brazil, 2008. [Google Scholar]
- NC. Specification for Filters, Air (HVAC). 2017. Available online: https://files.nc.gov/ncdoa/pandc/Documents/BidAttachments/s4130-1.pdf (accessed on 10 February 2022).
- ASHRAE. Handbook—Heating, Ventilating and Air Conditioning Systems; American Society of Heating, Refrigerating and Air Conditioning Engineers: New York, NY, USA, 2008. [Google Scholar]
- ANSI/ASHRAE Standard 52.2-2017; Method of Testing General Ventilation Air-Cleaning Devices for Removal Efficiency by Particle Size. ASHRAE: New York, NY, USA, 2017.
- Ma, Y.; Hu, X.; Wu, D. The permeability of glass fiber mat and its influence on the filling time of RTM process. In Proceedings of the Eleventh International Conference on Composite Materials, Gold Coast, QLD, Australia, 14–18 July 1997; pp. 14–18. [Google Scholar]
- ABNT. NBR-16101, Filtros para Partículas em Suspensão no ar—Terminação da Eficiência para Filtros Grossos; Médios e Finos: São Paulo, Brazil, 2012. [Google Scholar]
- Date, A.W. Introduction to Computational Fluid Dynamics; Cambridge University Press: Cambridge, UK, 2005. [Google Scholar]
- Mase, G.T.; Smelser, R.E.; Mase, G.E. Continuum Mechanics for Engineers; CRC Press: Boca Raton, FL, USA, 2009. [Google Scholar]
- Zhong, W.; Ji, X.; Li, C.; Fang, J.; Liu, F. Determination of permeability and inertial coefficients of sintered metal porous media using an isothermal chamber. Appl. Sci.
**2018**, 8, 1670. [Google Scholar] [CrossRef] - Belforte, G.; Raparelli, T.; Viktorov, V.; Trivella, A. Permeability and inertial coefficients of porous media for air bearing feeding systems. J. Tribol.
**2007**, 124, 705–711. [Google Scholar] [CrossRef] - Malalasekera, W.; Versteeg, H. An Introduction to Computational Fluid Dynamics: The Finite Volume Method; Prentice Hall: Harlow, UK, 2007; p. 1995. [Google Scholar]
- Wang, S.K.; Wang, S.K. Handbook of Air Conditioning and Refrigeration; McGraw-Hill: New York, NY, USA, 2000; Volume 49. [Google Scholar]

**Figure 1.**Approximate location of the Lauro Wanderley University Hospital at the Federal University of Paraíba (HULW/UFPB) in scale-amplified view. Source: prepared by the authors.

**Figure 2.**Pressure drop as a function of the air flow rate over the filter domain for three different filter thickness, namely 1 inch (2.54 cm), 2 inches (5.08 cm), and 4 inches (10.16 cm). Source: prepared by the authors with adaption from Dwyer©.

**Figure 3.**2D design of the clinical care room under study located at Lauro Wanderley University Hospital at the Federal University of Paraíba (HULW/UFPB). Source: prepared by the authors.

**Figure 4.**3D view of the simulation domain added by inlets and outlets. The air inlet duct (ceiling diffuser) is shown in detail from the vertical cross section whose grilles conduct the flow at 45 degrees. Source: prepared by the authors.

**Figure 5.**Example of polyhedral mesh with adaptive refinement used for simulations (detailed lateral view).

**Figure 6.**Example of polyhedral mesh with adaptive refinement used for simulations (cross-sectional view).

**Figure 7.**Horizontal plane crossing the rooms’ physical domains. Dozens of evenly spaced sampling points are placed over each compartment to probe data at the height of $1.5$ $\mathrm{m}$ from the floor, reference point where the velocity field must comply with the Brazilian technical regulations.

**Figure 8.**Violin plots describing the density of the velocity field’s distribution (magnitude measured according to the usual Euclidean norm). From left to right, the boxed figures represent the cases studied (0: no filter; 1: 1′ filter; 2: 2″ filter), organized per room.

**Figure 9.**Quantile–quantile (Q–Q) plots of the velocity distribution (in magnitude) for each case studied (0: no filter; 1: 1 (in) filter; 2: 2 (in) filter), organized per room in blocks of 3. The symbol $\mathcal{N}$ denotes the normal distribution; each $\mathcal{N}$ denotes the normal distribution and ${\mathcal{V}}_{c,r}$ denotes the velocity distribution for the c-th case of the r-th room. It can be verified that all cases move away normality but expound similar behaviors.

**Figure 10.**Data collection pillars were placed at the core of Room 1 for plotting vertical velocity profiles. Each pillar is formed by 20 stacked and uniformly spaced points over the compartment’s height, 2.5 m, and inside a neighborhood 0.85 m from the center, where pillar (C) is found. The other 8 pillars were placed in the cardinal directions along the azimuthal direction of the reference circle drawn at the room’s top surface.

**Figure 11.**Velocity profiles were computed for each pillar inside Room 1. They vary per case (indicated by changing color tones) and pillar position (indicated by direction markers). The orientation of the plots is from top left to bottom right. They are associated with the anti-clockwise direction beginning at the West (W) position. The vertical dashed line in gray marks the abscissa of the velocity value recommended by regulations (0.25 m/s). The horizontal dashed line in blue indicates the ordinate of the regulatory height where we took measurements (1.5 m).

**Figure 12.**Numerical simulations: (

**a**) Case 0; (

**b**) Case 1; (

**c**) Case 2 (legend included). Screenshots of velocity contours over the vertical medial planes (blocks of three along the left column—frontal view) and horizontal medial planes (blocks of three along the right column—superior view) for each case and room. The velocity range is scaled, and the time instant is fixed.

**Figure 14.**Percentage relative error as a function of the mesh element size (

**left**); absolute velocity magnitude for the reference mesh (

**right**). The error decreases as the factor multiplying h decreases, thus indicating that the numerical solution on coarser meshes should converge to that over the (finest) reference mesh (black square marker) through h-refinement. On the right, the colored borders indicate the maximum velocity reached at the pillar C for Case 0 inside each room computed for the reference mesh.

MERV | Efficiency | Typical Contaminant | Applications | Filter Class |
---|---|---|---|---|

20 | Not Applied | ≤$0.3$$\mathsf{\mu}$$\mathrm{m}$ diameter | Clean rooms | HEPA/ULPA |

19 | Not Applied | Viruses | Radioactive materials | Effic. ≤ 99.999% |

18 | Not Applied | Sea Salt | Pharmaceutical industries | Types A, C, D and F |

17 | Not Applied | Combustion fumes | Surgical centers | Not applied |

16 | Not Applied | $0.3$$\mathsf{\mu}$$\mathrm{m}$ to $1.0$ $\mathsf{\mu}$$\mathrm{m}$ | Hospitals | Bag filters |

15 | >95% | All bacteria | General surgeries | Not applied |

14 | 90 to 95% | Cigarette smoke | Smokers’ lounges | Not applied |

13 | 80 a 90% | Cooking oil/paint | Commercial buildings | Not applied |

12 | 70 to 75% | $1.0$$\mathsf{\mu}$$\mathrm{m}$ to $3.0$ $\mathsf{\mu}$$\mathrm{m}$ | Residences (top conditions for air circulation) | Filter bags |

11 | 60 to 65% | Legionella | Commercial buildings | Not applied |

10 | 50 to 55% | Lead/charcoal dust | Hospital laboratories | Not applied |

9 | 40 to 45% | Car emissions | Not applied | Not applied |

8 | 30 to 35% | $3.0$$\mathsf{\mu}$$\mathrm{m}$ to $10.0$ $\mathsf{\mu}$$\mathrm{m}$ | Commercial buildings | Pleated filters |

7 | 25 to 30% | Mold | Residences | Not applied |

6 | <20% | Spores | Industrial places | Disposable filters |

5 | <20% | Cement | Paint booth | Not applied |

4 | <20% | >$10.0$ $\mathsf{\mu}$$\mathrm{m}$ | Minimal filtration | Disposable filters |

3 | <20% | Spanish moss | Residences | Washable filters |

2 | <20% | Paint spray powders | Window air conditioners | Electrostatics |

1 | <20% | Sanding powders | Not applied | Not applied |

**Table 2.**Comparative view of filters according to ASHRAE 62.1 and ABNT/NBR 16101/2012 standards. Source: prepared by the authors.

Efficiency Level | Lower | Higher | |||||||
---|---|---|---|---|---|---|---|---|---|

NBR 16101/2012 | G1 | G2 | G3 | G4 | M5 | M6 | F7 | F8 | F9 |

MERV 62.1 | 1 | 2–4 | 5–6 | 7–8 | 9–10 | 11–12 | 13 | 14 | 15 |

NBR 7256/2005 applications | Not applied | Not applied | Image examination room | Outpatient care | Not applied | Not applied | Pneumology procedure room | Low-risk operating room | High-risk operating room |

Risk level | - | - | 1 | 1 | - | - | 1 | 2 | 3 |

Boundary | Property | BC | Value |
---|---|---|---|

Intake grilles | Velocity | Dirichlet | $2.0$ $\mathrm{m}{\mathrm{s}}^{-1}$ |

Intake grilles | Temperature | Dirichlet | $280.0$ $\mathrm{K}$ |

Exhaust grilles | Pressure | Dirichlet | $0.0$ $\mathrm{k}$$\mathrm{Pa}$ |

Doors and walls | Velocity (no-slip) | Dirichlet | $0.0$ $\mathrm{m}{\mathrm{s}}^{-1}$ |

Doors and walls | Temperature (no-flux) | Neumann | $0.0$ $\mathrm{W}{\mathrm{m}}^{-2}$ |

**Table 4.**Metrics computed for the mesh tests, where h is the average mesh cell size, ${n}_{e}$ is the number of mesh cells, $MCQ$ is the minimum cell quality, and $MSA$ is the maximum skewness angle.

h | ${\mathit{n}}_{\mathit{e}}$ | $\mathit{MCQ}$ | $\mathit{MSA}$ |
---|---|---|---|

0.025 m | 57,121,034 | 0.1511 | 75.33 |

0.050 m | 13,609,162 | 0.1523 | 75.83 |

0.100 m | 7,319,700 | 0.1514 | 75.39 |

0.200 m | 6,552,371 | 0.1572 | 75.41 |

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## Share and Cite

**MDPI and ACS Style**

Araújo Alves, C.G.; Junior, J.T.C.; Da Silva Neto, F.B.; Anjos, G.R.; Dos Santos, M.D.; Peixoto de Oliveira, G.
Indoor Airflow Dynamics in Compartmentalized Pneumology Units Equipped with Variable-Thickness MERV-13 Filters. *Buildings* **2023**, *13*, 1072.
https://doi.org/10.3390/buildings13041072

**AMA Style**

Araújo Alves CG, Junior JTC, Da Silva Neto FB, Anjos GR, Dos Santos MD, Peixoto de Oliveira G.
Indoor Airflow Dynamics in Compartmentalized Pneumology Units Equipped with Variable-Thickness MERV-13 Filters. *Buildings*. 2023; 13(4):1072.
https://doi.org/10.3390/buildings13041072

**Chicago/Turabian Style**

Araújo Alves, Camilo Gustavo, José Tadeu C. Junior, Francisco Bernardino Da Silva Neto, Gustavo R. Anjos, Moisés Dantas Dos Santos, and Gustavo Peixoto de Oliveira.
2023. "Indoor Airflow Dynamics in Compartmentalized Pneumology Units Equipped with Variable-Thickness MERV-13 Filters" *Buildings* 13, no. 4: 1072.
https://doi.org/10.3390/buildings13041072