The infection control efficacy of fixed ventilation systems in hospital wards exhibiting dynamic staff densities remains unclear, necessitating further elucidation of the synergistic effects among staff density, spatial layout, and ventilation conditions on aerosol transmission risk. This study employed in-situ measurements and multi-parameter coupled analyses within clinical wards to examine the dynamic relationships between airflow organization, pollutant transport, and exposure risk across three densely occupied ward typologies, while evaluating the potential of airflow rate adjustments to enhance contamination control. Key findings demonstrate that the ward layout and staff density collectively govern pollution pattern restructuring: high staff occupancy wards are prone to ventilation blind zones due to airflow reorganization, generating dynamic pollution hotspots within obstacle vortex regions, nevertheless, the relative magnitude of pollutant concentrations in the key staff activity areas showed spatial stability. Subsequent quantitative analyses revealed that aerosol suspension rates initially decrease then increase with rising staff density, while deposition rates exhibit the inverse trend, highlighting limitations in single-mode risk assessment models. Notably, despite ventilation intensification reducing indoor contamination, deposition rates in optimized high-density wards remained 4.7–6.8 times higher than in unoptimized single rooms, establishing a clear efficacy boundary for unilateral ventilation strategies. These findings underscore the necessity for synergistic interventions integrating layout optimization (eliminating airflow dead zones), targeted decontamination (highly enriched surfaces), and dynamic personnel flow management, thereby advancing the theoretical foundation for hospital infection control engineering design.

Hydrogen peroxide (H₂O₂) is widely used for disinfection because of its oxidative and antimicrobial properties. However, most studies have focused on surface disinfection, with limited research addressing its effectiveness for air disinfection. In this study, we developed a controlled air duct testing system to evaluate the disinfection performance of H₂O₂ in a ventilation system while precisely regulating environmental parameters. A sensitivity constant (Z) was introduced to quantitatively assess disinfection efficiency, with increased Z-values indicating enhanced disinfection performance. With a 7.5 s flow in the air duct system, the bioaerosol removal efficiency ranged from 26% to 97% under different temperature and humidity conditions. As temperature increased from 15 to 33 ℃, removal efficiency of Serratia marcescens and Escherichia coli increased from 40% to 95% and 78% to 97%, respectively. Correspondingly, Z-values increased from 0.0021 to 0.0076 ppm⁻¹s⁻¹ for S. marcescens and from 0.0072 to 0.0083 ppm⁻¹s⁻¹ for E. coli, suggesting that elevated temperature enhanced H₂O₂’s air disinfection efficiency. Conversely, higher humidities reduced H₂O₂’s efficacy; as the relative humidity decreased from 80% to 30%, the relative concentration of E. coli decreased and the Z-value dropped from 0.017 to 0.0022 ppm⁻¹s⁻¹. When the H₂O₂ concentration increased, the removal efficiency increased slightly, while the Z-value decreased significantly, indicating diminishing returns at higher H₂O₂ concentrations. These findings provide important insights for optimizing H₂O₂-based air disinfection strategies.

Bioaerosol filtration is crucial for improving indoor air quality and reducing cross-infection risk. It is necessary to conduct a comprehensive study on the bioaerosol filtration performance of air filters under different influencing factors. Firstly, this study proposed a standardized test scheme for the comprehensive evaluation of bioaerosol filtration performance. Additionally, the high-efficiency particulate air (H13) and medium-efficiency particulate air (F8) filters were evaluated in depth using Serratia marcescens bioaerosol, considering the face velocity, relative humidity (RH), and operating time. This study also investigated the impact of removing static electricity on the bioaerosol filtration efficiency (BFE) of F-filter materials. The pressure drop (∆P) value of H13-filter and the BFE of F8-filter were significantly affected by face velocity and RH. When the face velocity increased from 5 to 20 cm/s, the H13-filter maintained a BFE above 99%, while ∆P increased by 303 Pa. During a 90 min test, the maximum change in the BFE of the H13-filter was 0.80% and ∆P increased by 26 Pa. Conversely, the BFE of the F8-filter decreased by up to 12.21%, while ∆P increased by only 3 Pa. Higher RH resulted in more pronounced changes in BFE. After removing the static electricity from the F8-filter material, the BFE decreased significantly, with a maximum reduction of 25%. The results may provide valuable insights into the application of conventional filters in bioaerosol filtration and serve as a guide for the enhancement and optimization of filter design.

This study analyzes the growth and reproduction of dust accumulated fungi (DAF) in an air-conditioning system based on field measurement and molecular biology, laboratory experiment and prediction modelling. The field measurement was conducted to collect dust in filter screen, surface cooler and air supply duct of two air handling units (AHUs). The results indicate that dust volume and fungal number in two AHUs generally met the hygienic specification of public buildings, but the cleansing did not fulfil requirements. High-throughput sequencing was conducted, revealing that the dominant fungal species were Alternaria_betae-kenyensis, Cladosporium_delicatulum, Aspergillus_sydowii, Verticillium_dahliae. Laboratory experiment was conducted to analyze the impact of several factors (e.g. growth time, temperature, relative humidity, duct material) and their combination on the DAF growth. The results indicate that fungal growth increased with time, peaking at 4 days or 5 days. Higher relative humidity or temperature was conducive to fungal growth. The orthogonal experiment revealed that the condition of "antibacterial composite, 22 ± 1 °C and 45%-55% RH" had the strongest inhibiting impact on fungal growth. Logistic model, Gompertz model and square-root model were further developed to predict the fungal growth under different conditions. The results show that the Logistic model had high feasibility and accuracy, the Gompertz model was feasible with lower accuracy and the square-root model was feasible with high accuracy. Overall, this study facilitates the understanding of the DAF growth in air-conditioning ducts, which is important for real-time prediction and timely control of the fungal contamination.