Evaluating the Efficacy of Microwave Sanitization in Reducing SARS-CoV-2 Airborne Contagion Risk in Office Environments

Response to Reviewer 1 Comments

1. Summary

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: Table 4. Mentions the spectrum of bio-aerosol emissions and size range. Are these values experimentally obtained or obtained from literature. References/ Sources need to be provided

Response 1: These values have been obtained from literature. Below you can find our references.

[30] G. Cortellessa et al., “Close proximity risk assessment for SARS-CoV-2 infection,” Sci. Total Environ., vol. 794, p. 148749, 2021.

[31] G. Cortellessa, C. Canale, L. Stabile, G. Grossi, G. Buonanno, and F. Arpino, “Effectiveness of a portable personal air cleaner in reducing the airborne transmission of respiratory pathogens,” Build. Environ., vol. 235, no. January, p. 110222, 2023, doi: 10.1016/j.buildenv.2023.110222.

Comments 2: Experimental setup consists of a room and as per author’s description room is airlock. Assuming that is the case, authors need to elaborate that particle movement in the experimental volume is driven by Brownian motion or convection? how does

Response 2: The particles are primarily moved by convection due to the thermal gradient present in the room

Comments 3: Comparing the simulations without consideration into composition of droplets make it a far-fetched idea. Droplets/bioaerosols emitted from infected individuals consists of not just the virions but a mixture of salts, mucin and other biological materials. The composition and size of these droplets change not just based on where the droplets originate form (inner lungs/throat) but also how droplets evaporate and its transient time. It is difficult to understand how author can claim they can simulate these behaviors with simple transport models. Though this could be a good model to understand the decay of radio waves with distance and its applications. Estimation of virion viability with simple models seems like a stretch. Additionally, droplets emitted from infected individuals undergo phase changes that effect the viability of biological material itself. Authors need to address these concerns as to how these scientifically observed effects were considered in simulations. If they were not considered, how can authors certainly isolate the effects of Microwave from other factors mentioned above.

Response 2: We thank the reviewer for this important observation. We acknowledge that respiratory droplets are complex, containing mixtures of water, salts, proteins (e.g., mucin), and biological material such as virions. However, our modelling approach simplifies droplets as single-component spherical particles in order to focus on their aerodynamic transport and dispersion behaviour, rather than their detailed internal composition or biological viability.

It is widely accepted in the literature to represent respiratory droplets as spherical particles, particularly for the purposes of airflow interaction, and transport. This assumption has been adopted in numerous peer-reviewed studies [7, 32-35]. These models have successfully captured the core dynamics of droplet sedimentation, and airborne suspension.

Furthermore, due to the rapid evaporation of the water content [36, 37], the remaining droplet nuclei consist primarily of non-volatile material and virions. As shown in previous studies, the trajectory and suspension time of these nuclei are predominantly governed by their aerodynamic size and environmental conditions, rather than detailed chemical composition [5,38]. Once water has evaporated, the particle's effective size stabilizes, and its further motion can be reasonably approximated by a spherical model.

We agree that this simplification limits our ability to predict virion viability or detailed droplet-phase behaviour, and we have clarified this in the revised manuscript. Our focus is on modelling transport pathways and exposure potential, where the spherical droplet assumption provides a computationally efficient and physically reasonable representation.

[5] Stadnytskyi, V., Bax, C. E., Bax, A., & Anfinrud, P. (2020). The airborne lifetime of small speech droplets and their potential importance in SARS-CoV-2 transmission. Proceedings of the National Academy of Sciences, 117(22), 11875-11877.

[7] Morawska, L. J. G. R., Johnson, G. R., Ristovski, Z. D., Hargreaves, M., Mengersen, K., Corbett, S., ... & Katoshevski, D. (2009). Size distribution and sites of origin of droplets expelled from the human respiratory tract during expiratory activities. Journal of aerosol science, 40(3), 256-269.

[32] Xie, X., Li, Y., Chwang, A. T. Y., Ho, P. L., & Seto, W. H. (2007). How far droplets can move in indoor environments–revisiting the wells evaporation–falling curve. Indoor air, 17(3).

[33] Nicas, M., Nazaroff, W. W., & Hubbard, A. (2005). Toward understanding the risk of secondary airborne infection: emission of respirable pathogens. Journal of occupational and environmental hygiene, 2(3), 143-154.

[34] Vuorinen, V., Aarnio, M., Alava, M., Alopaeus, V., Atanasova, N., Auvinen, M., ... & Österberg, M. (2020). Modelling aerosol transport and virus exposure with numerical simulations in relation to SARS-CoV-2 transmission by inhalation indoors. Safety science, 130, 104866.

[35] Dbouk, T., & Drikakis, D. (2020). On respiratory droplets and face masks. Physics of Fluids, 32(6).

[36] Balachandar, S., Zaleski, S., Soldati, A., Ahmadi, G., & Bourouiba, L. (2020). Host-to-host airborne transmission as a multiphase flow problem for science-based social distance guidelines. International Journal of Multiphase Flow, 132, 103439.

[37] Xie, X., Li, Y., Chwang, A. T. Y., Ho, P. L., & Seto, W. H. (2007). How far droplets can move in indoor environments–revisiting the wells evaporation–falling curve. Indoor air, 17(3).

[38] Wells, W. F. (1934). On air-borne infection: study II. Droplets and droplet nuclei. American journal of Epidemiology, 20(3), 611-618.

Comments 4: Figure 8, 9, 10 difficult to read scales.

Response 4: The figure has been modified.

Comments 5: Figure 11. Difficult to read y-axis label

Response 5: The figure has been modified.

Comments 6: Figure 7. Resolution of data too low to be considered for interpolation.

Response 6: The three points obtained experimentally represent the state of the art. The interpolation between the points is linear, considering that under one minute, the inactivation is directly proportional to the energy input into the system

Comments 7: The power of EM radiation exponentially dies off as we move away from the source. It would be an important test for the model to show curves representing radiation exposure with distance from source and theoretical viability.

Response 7: The field generated by the source and propagated in the scenario is shown in Figures 8 and 9. Additionally, to better address your comment, we have created the following figure that shows the field's behavior at various distances from the source.

Response to Reviewer 3 Comments

1. Summary

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: Validation gap. The manuscript never compares CFD‑predicted concentrations with experimental tracer‐gas or particle data collected in the same room. Without validation, quantitative risk reductions (Table 6) remain speculative

Response 1: Thank you for pointing this out. We plan to conduct experimental tests that we would like to present in a second paper.

Comments 2: Single environmental condition. Only a summer mixed‑ventilation case is simulated; winter buoyancy‑driven flows or displacement ventilation could drastically alter exposure

Response 2: We plan to extend the case study to include the winter situation as well in a second paper.

Comments 3: Linear interpolation of virucidal efficacy. The 1‑ and 10‑min laboratory points are linearly interpolated to derive sub‑minute log reductions (Figure 7). Viral inactivation kinetics are seldom linear; please justify or replace with a mechanistic model.

Response 3: The three points obtained experimentally represent the state of the art. The interpolation between the points is linear, considering that under one minute, the inactivation is directly proportional to the energy input into the system

Comments 4: CO₂ as proxy for all aerosol sizes. The Eulerian approach assumes that CO₂ diffusion mirrors particles up to 800 µm (Table 4), conflicting with size‑dependent gravitational settling. Quantify the resulting error or limit the analysis to < 5 µm droplets.

Response 4: As the esteemed reviewer mentioned, using gas as a proxy for respiratory particles is appropriate for diameters below 5 microns. However, it should be noted that although the particles considered for this study were considered up to 800 microns in diameter, this assumption does not contradict the assumption of gas as a proxy for respiratory particles. Because more than 94% of the particles had a diameter of less than 5 microns, and the remaining less than 6% quickly fall to the ground due to gravity and do not become suspended in the air and do not play a role in causing the risk of infection [29, 39, 41, 42].

[29] Gao, Naiping, Jianlei Niu, and Lidia Morawska. "Distribution of respiratory droplets in enclosed environments under different air distribution methods." Building simulation. Vol. 1. Springer Berlin Heidelberg, 2008.

[39] Su, Wei, et al. "Infection probability under different air distribution patterns." Building and Environment 207 (2022): 108555.

[41] D. Zhang and P. M. Bluyssen, “Exploring the possibility of using CO2 as a proxy for exhaled particles to predict the risk of indoor exposure to pathogens,” Indoor Built Environ., vol. 32, no. 10, pp. 1958–1972, 2023.

[42] Z. Ai, C. M. Mak, N. Gao, and J. Niu, “Tracer gas is a suitable surrogate of exhaled droplet nuclei for studying airborne transmission in the built environment,” in Building Simulation, 2020, vol. 13, pp. 489–496.

Comments 5: Mesh and time‑step independence. No information is given on grid resolution, y⁺ values or time‑step sensitivity in either CFD solver. Provide convergence studies and residual histories.

Response 5:  Here it is the list of parameters used in the simulation:

steady state:

Unsteady state:

Time step:0.1 second,  and 1 time step: 10 iteration

Comments 6: Electromagnetic exposure safety. Human muscle dielectric properties are tabulated, but Specific Absorption Rate (SAR) compliance with ICNIRP guidelines is not discussed.

Response 6: From the simulations has been evaluated the maximum value of field amplitude on the edge of the nearest subject in both scenarios (with the device on the table and on the wall). it was possible to estimate the maximum field amplitude over the subject's head and trunk to be 0.48 V/m. Considering conductivity and muscle density, the SAR of 0.002 W/kg was calculated under these conditions. The ICNIRP regulations recommend that the SAR should not exceed 2 W/kg for the head and trunk: as the value we obtained is well below the threshold, the device is compliant with the regulations.

A new section has been added inside the text:

“2.2.3. SAR evaluation

One of the notable characteristics of this technology is its ability to be used in the presence of humans, thereby effectuating real-time sanitation and reducing the risk of contagion in the event of an infected individual. To validate this approach, the Specific Absorption Rate (SAR) value was evaluated under these specific conditions and compared to the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines [27].

Simulations were conducted to determine the maximum field amplitude at the edge of the nearest subject in two scenarios: with the device placed on a table and mounted on a wall. The maximum field amplitude in the subject's head and trunk was estimated to be 0.48 V/m. Considering the conductivity and muscle density, the SAR was calculated to be 0.002 W/kg under these conditions. According to ICNIRP regulations, the SAR should not exceed 2 W/kg for the head and trunk. As the calculated SAR value is significantly below this threshold, the device is compliant with the ICNIRP guidelines.

”

Comments 7: Conflict of interest disclosure. Three authors are employees of the device manufacturer; add a statement explaining how study design and data interpretation were kept independent.

Response 7: The three authors employed by the manufacturing company were responsible for exchanging information about the devices with the co-authors from the Polytechnic University of Turin. The latter developed and calculated the study results independently.

Comments 8: Terminology. “Sanification” is jargon; use “sanitization” or “disinfection” consistently (title and throughout).

Response 8: Correct there sentences inside the text.

Comments 9: Device placement rationale. Figure 5 shows two locations, yet the EM maps (Figures 8‑9) suggest both generate non‑uniform fields with blind spots. Explain why ceiling mounting was not evaluated.

Response 9: The device was designed to be portable; therefore, mobile installations on the side wall have been proposed to allow it to be detached and placed, for example, on a desk or another useful location at the moment. A ceiling installation, although good from a sanitation perspective, would be inconvenient to detach and move to other areas of the room

Comments 10: Uncertainty quantification. Risk outputs are given as single percentages (Table 6) without confidence intervals. Propagate uncertainties from source terms, CFD variability and dose‑response.

Response 10:

The paper describes a methodology that is under use for the analysis of further cases. Table 6 underlines the interesting potential for this technology in this scenario, without covering all the possible applications. In fact, CFD simulations uncertainties quantification requires a very large number of simulations, with enormous computational costs and times, not in the scope in this phase of the work. Nonetheless, flow field results have been validated against numerical measurements in the room. This analysis will be better reported in future papers, but can be partly seen in the following diagrams:

As for ARIA model uncertainties, they are depicted in the output diagram of the model, figure 6, grey band around the probability of infection curve.

Comments 11: ARIA model parameters. The quanta emission rate, breathing rate and deposition fraction used as inputs to ARIA are not reported. Provide a parameter table and cites.

Response 11: Input parameters of Aria model are derived from a systematic review, published on the portal of the tool (https://partnersplatform.who.int/aria), with the full list of reference

Comments 12: Lagrangian–Eulerian agreement. Authors claim “good agreement” but no quantitative comparison is shown. Include scatter plots or Bland‑Altman analysis.

Response 12: While we performed both Eulerian and Lagrangian simulations, in this work we used the results from Lagrangian simulations only to calculate the reduction of infective particles and the relative risk reduction. A more refined comparison will be developed in a future study.

Comments 13: Figure 10 interpretation. Transit‑time distributions are difficult to read; clarify axes and discuss why 60 s is representative relative to the device’s exposure profile.

Response 13: Figure 10 reports the position of the particles emitted by the subject on the right, after 10sec and after 60 sec of transient simulation. Single particle transit time is not indicated in the color code, which refers to particle size. The particles in the volume around the person on the left (susceptible person) are, as expected, low size ones. The picture has a qualitative intent of describing the dispersion of particles.

Comments 14: Spelling and grammatical errors impede comprehension (e.g., “Lagrangian”, “dinamic”, “descriptions”) (p. 8 l. 217)

Response 14: corrected

Comments 15: Reference formatting. Several URLs are pasted twice and some citations lack accessed dates (e.g., WHO brief)

Response 15: We have, accordingly, revised all citations.

Response to Reviewer 4 Comments

1. Summary

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding revisions/corrections highlighted/in track changes in the re-submitted files.

2. Point-by-point response to Comments and Suggestions for Authors

Comments 1: How safe is the microwave for human presence, a short discussion on regulatory compliance (e.g., EM field exposure limits) and safety thresholds for continuous exposure would enhance the practical relevance.

Response 1: From the simulations has been evaluated the maximum value of field amplitude on the edge of the nearest subject in both scenarios (with the device on the table and on the wall). it was possible to estimate the maximum field amplitude over the subject's head and trunk to be 0.48 V/m. Considering conductivity and muscle density, the SAR of 0.002 W/kg was calculated under these conditions. The ICNIRP regulations recommend that the SAR should not exceed 2 W/kg for the head and trunk: as the value we obtained is well below the threshold, the device is compliant with the regulations.

A new section has been added inside the text:

“2.2.3. SAR evaluation

One of the notable characteristics of this technology is its ability to be used in the presence of humans, thereby effectuating real-time sanitation and reducing the risk of contagion in the event of an infected individual. To validate this approach, the Specific Absorption Rate (SAR) value was evaluated under these specific conditions and compared to the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines [27].

Simulations were conducted to determine the maximum field amplitude at the edge of the nearest subject in two scenarios: with the device placed on a table and mounted on a wall. The maximum field amplitude in the subject's head and trunk was estimated to be 0.48 V/m. Considering the conductivity and muscle density, the SAR was calculated to be 0.002 W/kg under these conditions. According to ICNIRP regulations, the SAR should not exceed 2 W/kg for the head and trunk. As the calculated SAR value is significantly below this threshold, the device is compliant with the ICNIRP guidelines.

”

Comments 2: I would suggest merging Fig 3 & 4 since they are about device parameters. 

Response 2: The authors prefer to keep the images separate as Figure 3 refers to an image of the actual object, while Figure 4 shows some details of the antenna alone.

Comments 3: In the simulations, how would room size, ventilation and mixing would affect the efficacy of the microwave device. What about particle deposition and resuspension? 

Response 3: . Ventilation conditions and room size affect the performance of risk reduction. There are numerous parameters that can change, such as the number of infected people present. The room size necessitates the inclusion of an increasing number of devices as the size grows to achieve adequate coverage while remaining compliant with safety standards. In the study, we limited ourselves to the office case, trying to remain as generic as possible. In the future, we plan to evaluate performance in additional scenarios. Particles that settle and are re-emitted were neglected in the model as we believe they are not decisive for the study