Personal protective equipment (PPE) restricts the dilution of skin-emitted bio-effluents, which may lead to pollutant accumulation in the breathing zone and thus intensify inhalation exposure of the wearer. This study quantifies the inhalation exposure risk caused by skin-emitted bio-effluents under PPE using ethyl acetate as a tracer combined with a mannequin method. The distributions of thermal-fluid parameters were predicted using computational fluid dynamics. The dispersion of skin bio-effluents was visualized, and the influence of breathing organ, pulmonary ventilation rate, bio-effluent emission rate, and emission location on inhalation exposure was examined. Wearing protective clothing increased the average air temperature and air velocity in the breathing zone by 0.9 °C and 0.09 m/s, respectively, compared with conditions without PPE. The neck and cuffs served as the dominant pathways for leakage of skin-emitted bio-effluents. Protective clothing led to higher inhalation exposure to skin bio-effluents than no PPE, with nasal breathing receiving slightly higher inhalation concentrations than oral breathing. When pulmonary ventilation rate increased from 6 to 9 L/minute under a standing posture and oral breathing, the relative inhalation concentration and the relative exposure index increased by 30.6% and 17.8%, respectively. Inhalation exposure also rose sharply when emission rates exceeded 700 μg h⁻¹p⁻¹. Emission location strongly affected inhalation exposure. Bio-effluents emitted from the groin resulted in substantially higher inhalation exposure than those emitted from the armpit. These findings would enhance the scientific understanding of human-related bio-effluents and further support the rational improvement of PPE design and the effective control of human-related pollutants.

Creating an efficient ward environment is crucial for the sustainable development of healthcare buildings. This study proposes a methodological framework integrating a phase change material-based thermal energy storage outdoor air system (PCM-TES-OAS) to enable personalized ward environments, aiming to enhance patient comfort and respiratory health with low energy consumption. Four representative cities from different building climate zones in China, namely Beijing, Shenyang, Chengdu, and Shenzhen, were selected for a conceptual case study. The proposed system was theoretically evaluated against a conventional fan coil unit (FCU) plus dedicated OAS (FCU + DOAS) for its summer operational performance, indoor air quality impact, and energy-saving potential. The results indicate that the PCM-TES system remains operational for over 60 % of the time across all four cities. Moreover, the new system achieves an air change rate (ACH) of 8 h⁻¹ to 10 h⁻¹ while maintaining ward CO₂ concentrations consistently at a low level (below 500 ppm). In terms of energy performance, the total summer electricity savings are estimated to be no less than 60 kWh/m² in all evaluated cities. These theoretical findings demonstrate the system’s conceptual potential to simultaneously improve patient comfort, enhance inhaled air quality, and reduce energy consumption in ward environmental control. Additionally, it is recommended that the maximum cooling capacity of the OAS and FCU in the new system be approximately 3 times and 0.3 times that of the conventional system, respectively. This study is anticipated to offer a conceptual framework and a promising new approach to designing comfortable, healthy, and sustainable ward environments.

Past studies reveal that air infiltration through the building envelope and its impact on the indoor environment and energy consumption are significantly influenced by climate characteristics. However, little relevant information is available for buildings in southern China, where the building design traditionally follows a philosophy of being open and shaded. The present study employs both experimental measurements and numerical simulations to investigate the airtightness of buildings in Hot Summer and Cold Winter (HSCW) climate region of southern China and the associated energy consumption. The measurements and simulations are based on a typical office building in Changsha. Measurement results show that the air infiltration rate of six tested spaces at the natural pressure difference ranges from 0.10 to 0.30 h⁻¹ with an average of 0.17 h⁻¹ in summer, and from 0.09 to 0.32 h⁻¹ with an average of 0.16 h⁻¹ in winter. The operation of the air-conditioning system affects largely air infiltration, and each unit change in setpoint air temperature can result in an average of one-third or more change in air infiltration rate. Simulation results show that a decrease in air infiltration rate from 0.17 h⁻¹ to 0.01 h⁻¹ reduces the infiltration-related cooling energy consumption from 14.29 to 0.75 kWh/m²·year and heating energy consumption from 8.20 to 0.39 kWh/m²·year. The same change in the setpoint air temperature of air-conditioning system in summer and winter results in different infiltration-related energy consumption. The findings would contribute to an improved energy simulation and assessment of buildings in southern China.

Ventilative cooling is an energy-saving technology to diminish thermal discomfort and overheating risk of buildings, meanwhile achieving high indoor air quality (IAQ). However, there is still no optimal control strategy in practice, which considerably limits its application. This study developed a typical office building model to evaluate the performance of ventilative cooling systems with different control parameters and strategies for five typical cities in different climatic zones of China. Results showed that, when the control parameter was selected as the upper limit of satisfied comfortable zone by 90% of the occupants, the adaptive thermal comfort (ATC) model, which outperformed the other models in terms of outdoor air utilization, was not necessarily optimal in terms of energy efficiency. The outdoor air utilization potential based on the indoor dry-bulb air temperature (T_d) and indoor operative temperature (T_op) control was similar, but the energy usage varies considerably, especially in the hot climatic zones. When the overheating period controlled based on the thermal comfort models was the same, the energy usage would be underestimated by 16%–38% without considering the effect of radiant temperature. The ATC-based control could have up to 37% of energy-saving compared to thermostatic control, but inappropriately low limits could make it less advantages to achieve energy-saving. The energy-saving potential associated with the PMV and ATC controls showed a completely opposite trend in the different climatic zones. The analysis results indicate that eliminating the drawbacks of the lower limit in the ATC model is an effective way to demonstrate energy-saving effectiveness. The findings of this study will contribute to the effective improvement of the application potential of ventilative cooling in different climatic zones.

Smart and personalized ventilation systems have been demonstrated with high performance in creating a healthy and energy-efficient indoor environment, but they have been rarely comprehensively summarized and explored in previous studies. With the progressive development of various terminal devices and control technologies, personalized ventilation based on intelligent control is potentially a promising way to achieve efficient control and energy savings in human micro-environments. This study comprehensively summarizes and analyzes the recent studies and common utilization forms of smart ventilation and PV systems that are based on CO₂ concentration control, to pave path and provide some guidelines for their integration application for reducing energy consumption and improving indoor thermal comfort. Research shows that the combination of personalized ventilation and smart ventilation is an essential development for ventilation systems. Smart ventilation with demand control logic based on CO₂ concentration has been mature enough to effectively improve the effectiveness and comfortable performance of personalized ventilation. However, switching from traditional air conditioning systems to personalized ventilation still requires improved sensors and intelligent control algorithms. In addition, this paper also summarizes the exploratory studies and potential application analysis of machine-learning theories to improve intelligent control of personalized ventilation. To this end, this paper identifies future tendencies for advanced theories, integrated systems, and devices in personalized ventilation systems.