Evaluating viral filtration efficiency in non-centralized air-conditioning systems: a novel approach grounded in medical experimental data

Figures & data

Figure 1. Research roadmap of this study.

Figure 2. Working diagram of in-room filter.

Figure 3. Filtration efficiency of different MERV on PM2.5.

Figure 4. Comparison Of filtration efficiency of different particle sizes.

Figure 5. Pathogen’s natural decay.

Table 1. Summary of bacterial nebulization experiments.

Research-ers	Year	Bacterial species	Chamber volume, m^3	Filter flow, m^3/min	Subjects	Method	Main conclusions
Kashkooli et al. (2020).	2019	S. aureus	24.35	2.83	Influence of filter installation location on filtration efficiency	3 Locations: the center, the middle of one of the lateral sides, at the middle of the side in front of the axial air circulating fan	The filter worked best when placed in the middle of one of the lateral sides
Zargar et al. (2019).	2019	S. aureus, A. baumannii, G. stearothermophilus	24.35	2.83	Same filters, three kinds of bacteria	Set up a controlled experiment in which the filter did not run to test the filter removal effect	The filter had remarkable removal effect on different bacteria. There were obvious filtration differences among different bacteria
Sattar et al. (2017).	2017	S. aureus	Car, 3.25	0.17, 0.2, 0.17	Three sets of filtration equipment	Evaluation of bacterial removal effect of different automotive filters automobile filters	The time for the three devices to meet the performance standard (99.9%) was 2.3, 1.5 and 9.7 h
Sattar et al. (2016).	2016	S. aureus, K. pneumoniae	24.35	2.8, 3.4, 1.7	Three sets of filtrations, two kinds of bacteria	Set a controlled experiment. The filtration effects of three filters on two kinds of bacteria were tested	The filtration efficiency of filter 1 and 2 exceeded 99.9% for both bacteria within 45 min. Filter 3 has no obvious filtering effect

Figure 6. Concentration of bacteria during filter operation.

Figure 7. Comparison between predicted results and measured results in the natural decay experiments.

Figure 8. Comparison between predicted results and measured results in the nebulization experiments.

Figure 9. Effect of single-pass efficiency on indoor pollutant concentration.

Figure 10. Effect of ${\mathit{\text{ACH}}}_f$ on indoor pollutant concentration.

Figure 11. Effect of ACH on indoor pollutant concentration.

Figure 12. Effect of $f$ on indoor pollutant concentration.

Kashkooli FM, Soltani M, Zargar B, Ijaz MK, Taatizadeh E, Sattar SA. 2020. Analysis of an indoor air decontamination device inside an aerobiology chamber: a numerical-experimental study. Air Qual Atmos Health. 13(3):281–288. doi: 10.1007/s11869-019-00782-w.

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Zargar B, Sattar SA, Rubino JR, Ijaz MK. 2019. A quantitative method to assess the role of indoor air decontamination to simultaneously reduce contamination of environmental surfaces: testing with vegetative and spore-forming bacteria. Lett Appl Microbiol. 68(3):206–211. doi: 10.1111/lam.13109.

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Sattar SA, Zargar B, Wright KE, Rubino JR, Ijaz MK. 2017. Airborne pathogens inside automobiles for domestic use: assessing in-car air decontamination devices using staphylococcus aureus as the challenge bacterium. Appl Environ Microbiol. 83(10):9. doi: 10.1128/AEM.00258-17.

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Sattar SA, Kibbee RJ, Zargar B, Wright KE, Rubino JR, Ijaz MK. 2016. Decontamination of indoor air to reduce the risk of airborne infections: studies on survival and inactivation of airborne pathogens using an aerobiology chamber. Am J Infect Control. 44(10):E177–E182. doi: 10.1016/j.ajic.2016.03.067.

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Data availability statement

The data that support the findings of this study are available from the corresponding author, Dr J. Li, upon reasonable request.