Experimental study on bioaerosols behavior and purification measures in a subway compartment

Abstract

Bioaerosols in public transportation systems raise critical environmental concerns, seriously threatening passenger health and safety. In this study, we investigate the spread characteristics of bioaerosols in a standard type-B subway compartment using both air sampling and sediment sampling methods. Additionally, without compromising indoor passenger comfort, two self-designed air purification devices, based on intense field dielectric (IFD) and dielectric barrier discharge (DBD) technologies, respectively, are successfully applied for the improvement of the subway air quality. The results show that bioaerosols can propagate rapidly throughout the entire compartment in 5 min via airborne transmission. Under the effect of the symmetric air ducts and compartment structure, the difference in bioaerosol concentration in the air is less than 10% between both ends of the compartment. Concurrent substantial bioaerosol deposition on the ground, seats, and windows underscores the risk of contact transmission. Furthermore, the real-time purification rates of the two devices integrated into the air conditioning system reach 59.40% and 44.98%, respectively. With their demonstrated high efficiency in purifying bioaerosols and modular design featuring low energy consumption, easy cleaning, and reusability, these devices stand out as viable long-term solutions for large traffic vehicles. These research findings provide practical equipment recommendations and installation strategies for optimizing indoor air quality in subways and are applicable to other similar transportation systems.

Introduction

In recent years, respiratory infectious diseases carried by bioaerosols have increasingly posed considerable challenges to public health, economic growth, and societal progress, with the global emergence of Coronavirus disease 2019 (COVID-19) exacerbating these concerns¹. On the other hand, as a useful strategy to alleviate surface traffic congestion, subway systems have gained prominence as the primary mode of transportation for daily commuters². However, the predominantly underground operation of subway trains may result in restricted access to fresh air. Additionally, in conjunction with the rapid progression of urbanization, passenger density within subway systems has consistently grown, not only during peak commuting hours but also throughout other periods of the day. The risk of respiratory disease transmission inside subways may be positively correlated with the number of passengers³. Therefore, there is an urgent need to understand the dispersion patterns of bioaerosols in subway cabins and to establish effective measures to mitigate the risk of respiratory infections. This is crucial for the sustainable growth of rail transportation systems.

Indoor aerosol transmission patterns have been a topic of significant interest in the academic community^4–6. Large size aerosols (with a diameter of 50 μm or more) tend to sediment due to their great mass, contaminating surfaces in indoor environments^7,8. The dynamic characteristics of small size aerosols (with a diameter of 10 μm or less) are influenced by the surrounding flow field (including air velocity, temperature, and humidity), which could result in prolonged suspension and widespread dissemination of the aerosols^9,10. Therefore, small size aerosols are considered to potentially facilitate more widespread disease transmission compared to large size aerosols. For these fine particles, upon being released, they evaporate rapidly within approximately 0.1 s, transforming into droplet nuclei¹¹. Their evaporation and dispersion behaviors are relatively insensitive to changes in ambient humidity^11–13. According to studies by Yan et al. (2020)¹⁴, the prevailing indoor airflow patterns were found to primarily govern the long-term movement and spread of these aerosols. Besides, previous literature¹⁵ emphasized the need to consider the complete air duct system when studying indoor environments. Overly simplified ventilation models may fail to accurately predict indoor airflow patterns, potentially leading to incorrect distributions of aerosol dispersion within the cabin.

There has been extensive research on the diffusion and exposure risks of droplets, aerosols, and tracer gases in conventional indoor environments, such as hospitals and classrooms^16,17. Various ventilation modes, formed by adjusting the positions of air supply and exhaust vents, have been applied to control the behavior of droplets. However, unlike these common indoor environments, which adopt air supply-exhaust systems or air supply-return systems, subway cabins typically utilize a combined air supply-return-exhaust circulation mode to reduce fan noise, save energy consumption, and maintain passenger comfort. Meanwhile, this ventilation system can result in extremely complex airflow patterns inside the cabin. Su et al. (2021)¹⁸discovered that cross-sectional changes within subway air ducts could cause local recirculation phenomena and reduce the uniformity of air distribution. Through field experiments, Wang et al. (2024)¹⁹observed that the airflow velocity distribution in a carriage exhibits an approximate ‘W-shape’, and the profile of the maximum airflow velocity is equivalent to a ‘parabolic surface’. Additionally, Tao et al. (2019)²⁰ employed porous media models and porous step-face models as substitutes for actual ventilation plates in subway trains. Currently, research on subway cabins primarily focuses on passenger comfort and airflow organization. However, investigations into aerosol motion, exposure risks, and optimal measures in subway indoor environments remain limited.

In scenarios where ventilation is constrained, the utilization of air purification devices has seen a marked expansion in many applications. The incorporation of physical-mechanical filters in buildings equipped with heating, ventilation, and air conditioning systems can capably decrease particulate matter concentrations in the air to levels below established thresholds^21,22. Other fine air filtration devices, such as plasma air filters^23,24and polytetrafluoroethylene multi-tube high efficiency membrane air filters²⁵, are capable of removing pollutants. In general, the pollutant removal process can be categorized into two phases (adsorption and destruction). The process of capturing pollutants through physical or chemical means by a specific medium is referred to as adsorption^26,27, while oxidation techniques like ozone generation, plasma-driven oxidation, and photocatalysis are classified as destructive processes²⁸. However, it is essential to acknowledge that the feasibility and adaptability of air purification technologies still face significant challenges in practical engineering applications²⁹. For instance, some highly efficient purification methods, such as portable air cleaners, may come with a notable increase in energy consumption, potentially rendering them uneconomical in the long run³⁰. Moreover, some technologies (e.g., ozone generators) might not be suitable for densely populated or enclosed settings. Each control technology has its limitations and significance in addressing various indoor air pollutants. To date, air purification devices for reducing bioaerosols have not been applied in subways, and their effectiveness remains unknown. Given the ongoing pandemic, there is a pressing need for further exploration and design of appropriate air purification devices for subway environments.

In this study, we perform experiments on bioaerosols in a conventional type-B subway cabin, which is widely used for global railway transport^31,32. Our experimental setup takes into account the air conditioning cycles and duct configuration. Using two sampling techniques, air and sediment sampling, we collect bioaerosols. These bioaerosols are then cultivated and analyzed to determine their propagation modes under various subway operational conditions, including fully enclosed scenarios and semi-enclosed settings. Moreover, aiming for the copresence of humans and machines in traffic environments, we develop two distinct air purification devices based on intense field dielectric (IFD) and dielectric barrier discharge (DBD) technologies, respectively. These devices have shown a high purification rate of bioaerosols in large traffic environments. Importantly, the concentration of ozone and other byproducts from these devices adheres to indoor air quality standards. To the best of our knowledge, this is the first application of such technologies to mitigate bioaerosols in subway cabin environments.

Materials and methods

Experimental setup

The experimental approach can take into account some practical factors, such as air conditioning recirculation and air duct structure, among others, all of which present challenges when attempting to couple and evaluate their impact using simulation methods. The study investigates the characteristics of pathogen transmission inside the subway cabin using a combined microbiological and engineering approach. The entire research process is divided into three main stages: the preparation of the experimental environment and materials, the execution of specific test cases, and the collection and analysis of data.

Initially, the study constructs a subway train laboratory characterizing an authentic geometric configuration (refer to Fig. 1a). The laboratory encompasses an indoor space with dimensions of 17.34 m (width) × 2.58 m (length) × 2.35 m (height). It is equipped with a comprehensive duct system and interior cabin furniture, enabling the assessment of the effects of diverse ventilation approaches and operation conditions on aerosol transmission. To enhance indoor thermal comfort, insulating panels have been embedded in the layered composition of the sidewalls, floor, and ceiling. The cabin furnishes six windows (dimensions of 1.51 m × 0.85 m), six doors (dimensions of 1.8 m × 1.4 m), five seating units (each extending 2.0 m in length), and four vertical supports (each rising 2.1 m in height).

Fig. 1.

Sketch of the generic train laboratory. (a) Compartment geometric. (b) Ventilaton mode.

This section provides a more detailed description of the ventilation system for the subway cabin. The entire ventilation system consists of air conditioning units, supply air ducts, return air inlets, and exhaust air ducts. Air treated by two air conditioning units is channeled into the compartment through supply air grilles located on the roof. A portion of this air re-enters the air conditioning units via the return air inlets, where it mixes with fresh air and is recirculated into the cabin. Simultaneously, the rest of the air is discharged directly into the external environment through exhaust air outlets. In accordance with the majority of operational subway trains, the current experimental laboratory employs a typical ventilation mode featuring a ‘top air supply-top air return-bottom air exhaust’ configuration (Fig. 1b). This ventilation pattern is advantageous for efficiently expelling heat and pollutants within the cabin³³. It also has positive performance in both energy efficiency and thermal comfort. Relying on the intelligent control cabinet of the air conditioning units, a variety of ventilation modes can be implemented. These encompass external circulation operation and internal circulation operation (without air exchange between the indoor and outdoor environments), each equipped with air supply frequency modulation capabilities in a frequency range of 30–50 Hz. In the context of the standard ventilation mode, the overall supply air volume in the cabin reaches 8,500 m³/h, incorporating a fresh air volume of 2,600 m³/h and a return air volume of 5,900 m³/h. The air conditioning system allows for precise regulation of indoor temperatures, maintaining a range between 16 °C and 28 °C with an accuracy of 0.1 °C.

Experimental devices

Aerosol generation and collection device

Staphylococcus aureus (S. aureus), classified as a biosafety level (BSL) II organism, is routinely employed in bioaerosol dispersion studies within indoor settings and for testing the effectiveness of air purification systems^34–36. In this investigation, pure cultures of S. aureus are inoculated onto Luria Bertani (LB) liquid medium. The cultures are maintained under controlled conditions at 37 °C with a shaking rate of 150 r/min for a duration of 24 h. The concentration of the microbial culture is ascertained utilizing the viable plate count methodology. The suspensions of S. aureus are diluted with phosphate-buffered saline to achieve a final concentration of 10⁶ cfu/ml, which serves as the aerosol generation solution.

Research indicates that most particles emitted from human respiration are primarily within 10 μm^37,38. For consistency, an atomizer is implemented as the aerosol generation system, producing particles that predominantly fall within this size range. To accurately emulate the authentic process of human aerosol release, a manikin representing a standing passenger (approximately 1.7 m in height) is connected to the atomizer via a flexible hose. This arrangement enables aerosol to be released through the nasal region, thus simulating the human breathing process (Fig. 2a). The aerosol system is designed to exhibit time-varying respiratory flow rate based on tested human subjects, and this measured rate is compared with the existing respiratory data from a previous experiment³⁹, as illustrated in Fig. 2b. The results show the bioaerosol emission process closely resembles human respiratory activities. Moreover, the manikin engages in multiple breathing actions, with a 0.2 s interval between each breath.

Fig. 2.

Flow curve of a single breath simulated by the aerosol generator. (a) Respiratory flow rate. (b) Aerosol generation.

This study uses two methods for collecting S. aureus. The first approach involves using Andersen six-stage air samplers for a 3.0 min collection duration at a flow rate of 28.3 L/min⁴⁰ to monitor the variations in bioaerosol concentration within the air. The second method entails placing Columbia blood agar plates directly onto compartment surfaces (such as windows and seats) to observe the deposition characteristics of S. aureus particles with small diameters under the effects of indoor turbulence. Upon completion of the experiments, all agar plates are incubated at 37 °C for 24 h in a constant temperature and humidity shaking incubator (HZQ-F160). Subsequently, the number of colonies on each plate is recorded and counted (i.e., colony forming unit: CFU) using an HCC-01 colony counter.

Air purification device

Given the frequent presence of passengers in traffic environments, air purification devices need to exhibit the characteristics of copresence of human-machine. Moreover, pathogen disinfection in subway cabins requires a targeted approach that is simultaneously implemented in the cabin’s airflow, air ducts, and air conditioning units. We ultimately design two distinct air purification devices based on the suitable techniques and proceeded to carry out experimental evaluations of their performance.

The first purification device employs an intense field dielectric (IFD) technique, utilizing dielectric materials as the medium. Although many traditional physical-mechanical filters⁴¹excel at capturing fine particulates, their design often results in high air resistance, which can negatively impact the overall airflow efficiency of the air conditioning system. With this in mind, we opt for the IFD filter. A notable feature of this filter is its low air resistance⁴², allowing a great volume of air to flow seamlessly into the air conditioning system. This choice stems from in the unique demands of a train environment, especially during peak times and within the confined spaces of train carriages. In such scenarios, maintaining a stable and sufficient air intake is crucial to guarantee good air circulation and ventilation inside the carriage. The purification process for the designed IFD filter is divided into three steps, as shown in Fig. 3a. The first step involves the removal of large particles through a low-resistance filter (the thickness is 1.5 mm). Next, the particles are charged in the holes where the pin electrodes are located. Finally, the dielectric materials form honeycomb-shaped microchannels, generating a powerful electric field with the wrapped electrodes. This field attracts charged particles, thereby diminishing the presence of fine particulate matter. Additionally, the IFD filter neutralizes bacteria and microorganisms adhering to particulates in the strong electric field. This neutralization helps inhibit microbial growth on the filter surface, potentially reducing health risks to maintenance personnel who might come into contact with these microorganisms during inspections or replacements. According to the actual test, the operational power of the IFD filter used in the experiment is 12 W.

Fig. 3.

Air purification device and installation. (a) Operating mode of the IFD filter. (b) Operating mode of the CP generator. (c) Field installation of the IFD filter and CP generator in the air conditioning system.

The effective deployment of air purification devices is another central concern in numerous environmental safety studies. In the context of trains, the air conditioning system serves as the exclusive conduit linking the sealed cabin with the external operating environment, playing an important role in maintaining both indoor airflow quality and air cleanliness⁴³. As a result, in this study, the IFD filter is installed in the mixing chamber of the rooftop air conditioning unit. This location represents the juncture where fresh and recirculated air streams merge, as depicted in Fig. 3c. Strategically situated within the mixing chamber, the IFD filter exerts a considerable influence on the air entering the cabin.

The second purification device, a cold plasma (CP) generator, exploits a non-equilibrium gas discharge technology that features insulating materials integrated into the discharge space (illustrated in Fig. 3b). The technology of negative ion air purification, known for its energy efficiency and low noise, has already been applied^41,44. For the tested device, each distinct module generates a remarkable 3.5-5 million/cm³ positive and negative ions during the running process. Furthermore, the equipment mitigates potential hazards linked to high voltage exposure, a critical aspect in safeguarding the well-being of operators and the adjacent environment. In order to fill the entire cabin space, including the air duct system, with positive and negative ions, this study installs the CP generator in the air supply chamber of the air conditioning unit, as shown in Fig. 3c.

Byproduct evaluation

Considering the long-time and high-density passenger distribution in rail transit systems, certain air purification devices (e.g., ultraviolet lamps) that generate many byproducts may not be suitable. This work also includes testing the indoor ozone concentrations when the air purification devices are operational.

We conduct experiments in a sealed chamber with dimensions of 0.5 m × 0.5 m × 0.5 m, as depicted in Fig. 4. During the tests, we utilize an ozone monitor with the model number PR-MG41-O3, which has a resolution of 0.01 ppm. After several trials, we find that the ozone concentration within the chamber increases by an average of 1.75 ppm over a span of 10 min. Based on this, we estimate the ozone emission rate to be approximately 2.80 mg/h. On the other hand, the ozone test for the IFD device is carried out in an indoor environment, with measurements taken at the outlet of the duct equipped with the IFD filter. Using the same monitoring equipment, the ozone concentration at the air duct outlet is lower than the detector’s minimum measurement limit. The result indicates that the indoor ozone concentration meets the health standards for indoor air quality⁴⁵. This finding suggests that both the IFD and CP devices are safe for scenarios emphasizing the copresence of human-machine.

Fig. 4.

Test for ozone emission rate from CP generator.

In response to concerns related to ozone emissions, particularly the potential hazards stemming from secondary reaction byproducts, relevant experiments are undertaken. Upon activation of the air purification devices, we subject the indoor air to a continuous 4 h monitoring using TVOC (with a resolution of 0.001 ppm) and NO/NO₂ sensors (with a resolution of 0.1 ppm). Our experimental results indicate that there is no increase in the concentrations of TVOC and NO/NO₂, suggesting that the operation of the devices does not significantly contribute to the generation of secondary reaction byproducts.

Experimental condition and devised cases

As temperature and humidity have been found to influence aerosol diffusion patterns¹⁵, full-scale experiments are conducted in a subway cabin environment with regulated temperature and humidity. The indoor temperature is maintained at approximately 20 °C, with a humidity level of 55-60%. Meanwhile, to evaluate the effects of subway door operations during station arrivals and departures, and to examine the efficiency of the air purification devices, five different experimental conditions are established, as presented in Table 1. In actual subway operations, air conditioning systems employ sponge filters for particle filtration. This type of filter is also used in case 1 and case 2 to align with subway conditions. Some established standards related to indoor particulate matter, formaldehyde⁴⁶, and comfort⁴⁷ recommend tests in an unoccupied setting to clearly discern characteristics like ventilation patterns. Therefore, our experimental scenarios are conducted in a vacant vehicle. In this controlled environment, a conventional external air circulation approach is employed with only the mannequin model releasing bioaerosols inside the cabin.

Table 1.

Setups in all test cases.

Case No.	Door	IFD filter	CP generator
1	Close	Off	Off
2	Open	Off	Off
3	Close	On	Off
4	Close	Off	On
5	Close	On	On

In our experiments, the aerosol generation apparatus is set to be located at the cabin’s center. The aerosol emission is directed towards the y-axis, which corresponds to the door opening direction in case 2. To explore the transmission of aerosols carrying active bacteria in the cabin’s complex flow field, two six-stage air samplers are positioned at both ends of the cabin, as shown in Fig. 5(a). These samplers monitor changes in pathogen concentrations at the breathing zone height of seated passengers (1.1 m). Notably, in the door opening scenario (case 2), an additional six-stage air sampler is installed near the outside door to measure the external environment’s bioaerosol concentration. Furthermore, Columbia agar plates are strategically arranged on high-touch physical surfaces, such as seats and window ledges, to evaluate the potential contact risk related to pathogens, as shown in Fig. 5(b). The placement and nomenclature of all measurement points can be seen in Fig. 5(c).

Fig. 5.

Locations of bioaerosol sampling points. (a) Air sampling points inside compartment. (b) Sediment sampling points inside compartment. (c) Overall measuring point layout.

At the same time, the measurements of airflow and bioaerosols are conducted separately to maintain consistency in the initial environmental conditions across different experimental scenarios. Prior to the commencement of each bioaerosol experimental round, portable hotwire anemometer devices are utilized to monitor the flow field data. Once the stability of the flow field conditions is confirmed, the occupant model commences the release of bioaerosols for a duration of 10 min⁴⁸. The six-stage air sampler collects samples at the 5th, 15th, and 25th minutes during the experiment process, each of which lasts for 3 min (Fig. 6). Sample collection on the surface plates is carried out within the time range of 0 to 20 min. The two devices remain operational throughout the circumstances of case 3, case 4, and case 5 (designed for evaluating the efficiency of the purification devices). Within the time interval following each experimental round, the indoor environment is first cleaned using a disinfectant solution, followed by the air conditioner operating in the full fresh air mode for 1 h. Finally, the six-stage air sampler collects samples under the standard air supply mode to ensure that subsequent experiments are not influenced by previous ones or the background environment. The detailed steps of the bioaerosol experiment for different conditions are repeated in four rounds to reduce the potential for occasional errors.

Fig. 6.

Procedures for bioaerosol experiment in the subway compartment.

Results and discussion

The distribution of flow field under standard ventilation mode

The motion of aerosols is closely linked to the characteristics of indoor airflow patterns. Therefore, before conducting investigations concerning bioaerosols, it is crucial to understand the distribution of flow fields within the subway compartment. In compliance with EN14750-1 (2006)⁴⁷, we employ hot-wire anemometer devices, CLIMOMASTER 6501, equipped with probe model 6543 and boasting a precision of 2%, to measure the temperature and velocity parameters within the interior space under the standard ventilation mode. In most areas of the compartment, the air velocities are observed to be below 0.5 m/s. Due to the relative positioning of the supply and return air vents, the peak velocity, registering at 0.51 m/s, manifests at the sampling sites located in the central portion of the cabin (Fig. 7). Furthermore, in the central region (region 2) of the cabin, the five sampling points show an average air velocity of 0.32 m/s, which slightly exceeds that of both ends (0.26 m/s for region 1 and 0.28 m/s for region 3). This is because the resistance and momentum loss in the air ducts decrease as the proximity to the air conditioning unit increases.

Fig. 7.

The average indoor airflow velocity and temperature under standard ventilation mode (The standard deviation of experimental results is used as the error bar). (a) Air velocity. (b) Air temperature.

On the other hand, when examining the temperature distribution within the compartment, it is discernible that across both vertical and horizontal cross-sections, the temperature variation among the different sampling points does not exceed a difference of 2 °C. And the average temperature recorded at a height of 1.7 m from the floor is lower than that at 1.1 m. In general, under the influence of the top-dispersed air supply mode and the compartment’s symmetrical structure, the temperature and velocity fields within the compartment are uniform.

The diffusion characteristics of bioaerosols

Figure 8 captures the single release process of bioaerosols from the manikin equipped with the aerosol generator through camera imaging. Clearly, in the initial phase of the release, the jet, driven by the strong momentum from the respiratory action, propels particles directly forward. With the decrease of respiratory flow, the compartment’s airflow starts to dominate. As a result, aerosols disperse into the surrounding space, subsequently causing a reduction in particle concentration directly in front of the manikin.

Fig. 8.

Visualization of bioaerosol process through breath mode at different time. (a) t = 1.5 s. (b) t = 2.5 s.

Figure 9 quantitatively summarizes the measurement results of the S. aureus bioaerosol particles collected using both methods (air sampling and sediment sampling). The coefficient of variation (the proportion of the sample standard deviation relative to the mean) is employed to evaluate the dependability of the experimental approach. The results show that the coefficient of variation for most measurement points ranges between 5% and 20%. The more considerable experimental deviations observed for some measurement points may be attributable to the intrinsic randomness of cabin turbulence (cabin air velocity below 0.3 Ma) and the inescapable disturbances in the surrounding airflow induced by researchers collecting or replacing the plates. According to the research findings of Kunkel et al. (2017)⁴⁹, the fluctuations in the experimental results of this study are within an acceptable range. From Fig. 9a, the two air measurement points (E1 and W1) detect high concentrations of bioaerosols, indicating that the predominant mechanism for airborne transmission of bioaerosols in subway cabins is long-distance transport. The longitudinal transmission distance of bioaerosols can extend the entire length of the cabin. This means the recommended indoor safety distances⁵⁰ are not applicable to passengers in subway environments. Moreover, under the influence of the nearly symmetrical cabin structures and air ducts, the spatial distribution of bioaerosols exhibits relative uniformity (the difference in S. aureus colony counts between the two measurement points at the 15th minute is less than 10%), in line with the flow field characteristics detailed in Sect. 3.1. To further understand the bioaerosol dispersion in the air, a comparative analysis of the quantity of bioaerosols across different particle size ranges is presented in Table 2. Remarkably, peak concentrations at both ends (approximately accounting for 35% of the concentrations at the sampling sites) are predominantly observed within the 1.1 ~ 2.0 μm particle size range.

Fig. 9.

CFU of bioaerosol at different sampling methods under case 1 and case 2. (a) Air monitoring points under case 1. (b) Sediment monitoring points under case (1) (c) Air monitoring points under case (2) (d) Sediment monitoring points under case 2.

Table 2.

Detection results of air sampling method for case 1.

Monitoring point	Sampling Level	Size distribution (µm)	Mean (unit: CFU/m3)			Std
			5 min	15 min	25 min	5 min	15 min	25 min
E1	Level 1	7.0	141	211	0	44	40	6
	Level 2	4.8 ~ 7.0	224	528	35	73	60	10
	Level 3	3.4 ~ 4.7	294	740	0	94	108	5
	Level 4	2.1 ~ 3.3	3310	9301	141	390	422	29
	Level 5	1.1 ~ 2.0	5595	15,960	2960	201	261	91
	Level 6	0.6 ~ 1.0	2933	8244	810	486	475	82
W1	Level 1	7.0	188	141	47	43	36	10
	Level 2	4.8 ~ 7.0	165	140	59	35	39	25
	Level 3	3.4 ~ 4.7	518	400	58	124	92	24
	Level 4	2.1 ~ 3.3	4335	3887	188	395	367	55
	Level 5	1.1 ~ 2.0	5512	4935	1025	665	323	120
	Level 6	0.6 ~ 1.0	3698	3628	648	539	316	97

Upon the cessation of bioaerosol release, a significant portion of bacteria is either carried directly into the external cabin environment along with indoor airflow or deposited onto cabin surfaces, as depicted in Fig. 9(b). At the 25th minute, there is a notable decrease in the S. aureus concentration within the air, showing a reduction of up to 90%. Simultaneously, the release direction significantly impacts aerosol deposition, with RS2 showing the highest concentration (surpassing 310⁴ CFU/m²) among all measurement points. Additionally, the bacterial count detected on the window and seat surfaces via sedimentation plates demonstrates a sharp decline with an increasing distance from the release source, as illustrated in Fig. 10. Some experimental studies employ tracer gases to simulate the flows of small size (less than 10 μm) aerosols^51,52, neglecting the settling characteristics of such particles. However, bioaerosols carrying pathogens may adhere to any touchable surfaces in subway compartments due to the combined influence of the subway ventilation pattern and distinct indoor geometric structures. The results align with previous investigations, like a large-scale infection event within a Boeing 747 cabin, which underscored the significance of fomite transmission⁵³. It is important to note that the actual risk of transmission may vary. Factors including the viability and the inactivation rate of the microorganism, as well as the frequency of human contact, all play a role in determining the real transmission potential. Meantime, our experimental outcomes also verify that tracer gases are not suitable for simulating the diffusion process of small sized aerosols capable of depositing on physical surfaces.

Fig. 10.

Distribution of bioaerosol settled on different physical surfaces.

Considering the practical operation of subway systems, frequent passenger boarding and alighting can alter the airflow dynamics of the compartments. Therefore, this study further analyzes the influence of the door-open scenario (case 2) on the bioaerosol distribution within the cabin, as displayed in Fig. 9(c) and Fig. 9(d). In conjunction with the data presented in Fig. 9a and Fig. 9b, it is found that a significant reduction of bacteria occurs in the air and on physical surfaces when the door is open, as compared to the door-closed condition (case 1). Air measurement point E1 exhibits a 39.38% reduction (at t = 5 min), while the sedimentation measurement point LS2 decreases by 54.17%. The reason may lie in the following aspects. Firstly, when the door opens, it changes the cabin’s pressure field and airflow pattern, which causes some of the airflow to move directly outside. Second, the open door reduces the physical barriers inside the cabin, decreasing in the overall accumulation of bioaerosols. Additionally, it should be noted that the door measurement point M1 outside the compartment detects a significant amount of S. aureus, comprising approximately 35.89% of the amount found at the air measurement point E1 inside the compartment. The escape of bioaerosols through the vehicle door highlights the potential exposure risk for passengers on the platform. This feature can explain instances of infection due to brief contact during subway travel.

The performance of air purification devices

Air purification devices are commonly used in relatively small indoor environments, but their efficiency and energy consumption in larger spaces require further investigation. In this section, the IFD filter and CP generator are assessed for their individual and combined effectiveness in purifying the air. To better quantify the performance of these devices, this study introduces the bioaerosol purification rate R:

1

where and represent the average values of four rounds of experiments for the control group (case 1) and the experimental group (i.e., cases 3, 4, and 5, with air purification devices activated), respectively³⁴.

Figure 11 depicts the efficiency of various air purification devices in the cabin environment. For air sampling measurement points, during the continuous bacterial dispersal phase (t = 5 min), the R values for the IFD filter and the CP generator can reach 52.46-66.33% and 42.87-47.09%, respectively. Compared to the fresh air dilution effect achieved by relying solely on standard ventilation modes (Case 1), these purification devices can effectively reduce the bioaerosol concentration in the breathing zone of seated passengers in the entire cabin, thereby decreasing the risk of inhaling respiratory pathogens. As the operation time of the devices increases, the efficiency of bioaerosol purification for both devices gradually improves. After 25 min, the bioaerosol concentration in the cabin air approaches zero, demonstrating the rapid bioaerosol purification capability of the IFD and CP devices. In addition, for sediment sampling measurement points, the purification devices effectively reduced the detection amounts on the settling plates at various locations. The average purification ability of the CP generator (87.52%) surpasses that of the IFD filter (83.65%). It is speculated that the enhanced performance of the CP generator is attributed to its pulse discharge, which further inactivates S. aureus deposited on the surface of the material.

Fig. 11.

Purification rate test for different devices. (a) Air monitoring points. (b) Sediment monitoring points.

Another noteworthy finding is that at t = 5 min, the purification efficiency of air sampling point W1 in Case 5 (with both devices activated simultaneously) is marginally lower than that in Case 3 (with only the IFD filter activated). A possible explanation for this observation is that the electric field formed in the IFD filter concurrently absorbs the plasma produced by the CP generator in the indoor airflow and diminishes the combined efficiency. More research is required to provide detailed information about the underlying mechanisms. In future work, we plan to combine experimental and numerical simulation methods to investigate these issues.

We have compared the purification efficiency of air cleaners in different scenarios, as shown in Table 3. While some literature reports that the purification efficiency of air cleaning devices can exceed 69% under certain conditions, the efficiency observed in our study deviates from these findings due to the specific experimental environment and application context. Specifically, in subway carriages, the released particles do not immediately enter the air conditioning system equipped with a purifier but may first disperse to other areas of the carriage. Furthermore, the spacious structure of the subway carriages constrains airflow circulation, and certain stagnant areas further hinder the efficient filtration of particles. Therefore, although our purification efficiency might appear slightly less optimal compared to other studies, our findings still offer valuable insights for evaluating the actual effects of air purification devices in such settings.

Table 3.

Comparison of air purification devices between different scenarios.

Scenario	Release source	Purification condition	Purification Rate	Reference
General room	E. coli K12	HAVC with MERV 8	7 m ~ 69%	49
		HAVC with MERV 11	7 m ~ 85%
		HAVC with MERV 16	7 m ~ 87%
Small room	PM2.5	Fan with IFD filter	About 95%	42
Test board.	PM2.5	IFD filter	About 98%	54
Chamber	Oil droplets	IFD filter	84%~96%	16
Experience room	Air-filled Soap bubbles	Mobile HEPA1	78% (Flow rate is 600 m3/h)	55
Air duct	Dust particles	Plasma reactor	70%	23
Office	Bioaerosols	Plasma air filtration	91.5%	41
Subway	Bioaerosols	IFD	59.40%	Our work
		DBD	44.98%

In conclusion, the IFD filter and the CP generator are both viable options when the air conditioning systems are functioning normally. The IFD filter purifies all air passing through the mixing chamber, including both return air and fresh air, thereby reducing the concentration of microorganisms in the cabin air. As for the CP generator, its functionality initially relies on the driving force provided by the air conditioning system, and subsequently, through the airflow organization created by the air duct structure, it disperses purifying materials throughout the indoor environment. These devices possess cleanability and reusability. From a technical standpoint, the installation and maintenance of the IFD filter and the CP generator are relatively convenient, and their operation does not have adverse effects on indoor temperature and humidity conditions. Moreover, with power consumption of 12 W for the IFD filter and 5 W for the CP generator, respectively, these devices avoid excessive energy consumption. Especially when considering the CP generator, its small size grants a high degree of flexibility, making it suitable for various scenarios. The concurrent deployment of multiple CP generator units in practical applications to enhance pathogen purification rates is also a feasible strategy.

Limitation and future work

While this study offers valuable insights into the transmission of bioaerosols within subway cabins, there are several limitations that should be pointed out. The observed transmission patterns derive from simulated experiments in empty subway cabins. In actual scenarios, human activities and resource location in the cabin may introduce variations to the transmission patterns. Future research will consider these additional influencing factors for a more accurate understanding. Moreover, developing an infection risk model allows for a concrete assessment and prediction of infection risks in indoor environments. Given the significant role particle size plays in disease transmission, it is worth further incorporating this factor into the model to give a more specific suggestion for passenger health in different traffic environments.

Conclusion

In this study, experimental methods are used to explore the diffusion of bioaerosols in a typical subway cabin. The application of both air and sediment sampling methods determines the primary modes of indoor aerosol propagation. Moreover, to decrease the spread of bioaerosols in large public transportation vehicles, our work assesses the individual and combined performance of the two designed air purification devices. The main conclusions of this research are as follows:

(1) Under the coupled effects of multiple flow fields in subway cabins, especially without passenger interference, bioaerosols can disperse throughout the entire cabin via airborne transmission. The symmetric indoor structure and air ducts further contribute to this relatively uniform bioaerosols distribution. Consequently, the concentration difference of aerosols in the air at both ends of the cabin is less than 10%.

(2) The phenomenon of bioaerosols deposition on surfaces at varying heights, including aisles, seats, and windows, further emphasizes the potential risk of contact transmission. However, the actual risk depends on factors such as the inactivation rate and viability of the microorganisms on these surfaces. On the other hand, tracer gases are unable to fully replicate the flow characteristics of small size aerosols in indoor settings featuring multiple obstacles.

(3) The opening of subway cabin doors can alter the diffusion patterns of indoor bioaerosols, leading to a decrease in the concentration of bioaerosols in the indoor air by approximately 38.37% (t = 5 min). Simultaneously, a considerable amount of aerosols is found to escape outside through the cabin door. This flow feature may pose a potential exposure risk to passengers on the platform.

(4) Without compromising the original airflow quality in the cabin, installing devices based on intense field dielectric (IFD) or dielectric barrier discharge (DBD) technologies in the air conditioning system can effectively reduce bioaerosol concentrations in large indoor spaces. During the continuous release of microbial aerosols, the real-time purification rates for the IFD filter and the CP generator reach 59.40% and 44.98%, respectively. However, when both devices operate simultaneously, the purification rate does not exhibit a significant increase, which may be related to the installation positions of the devices.

Author contributions

X.R.: Writing—original draft, Software, Experiments, Investigation; W.F.: Methodology, Investigation, Validation, Data curation; S.L.: Writing—review & editing, Funding acquisition, Investigation; F.Z.: Methodology, Investigation, Validation; Y.J.: Data curation, Investigation; H.Z.: Data curation, Investigation.

Data availability

The datasets and materials used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.