Refined design of ventilation systems to mitigate infection risk in hospital wards: Perspective from ventilation openings setting

Zonal demand-controlled ventilation strategy to minimize infection probability and energy consumption: A coordinated control based on occupant detection

Due to the outbreak of COVID-19, an increased risk of airborne transmission has been experienced in buildings, particularly in confined public places. The need for ventilation as a means of infection prevention has become more pronounced given that some basic precautions (like wearing masks) are no longer mandatory. However, ventilating the space as a whole (e.g., using a unified ventilation rate) may lead to situations where there is either insufficient or excessive ventilation in localized areas, potentially resulting in localized virus accumulation or large energy consumption. It is of urgent need to investigate real-time control of ventilation systems based on local demands of the occupants to strike a balance between infection risk and energy saving. In this work, a zonal demand-controlled ventilation (ZDCV) strategy was proposed to optimize the ventilation rates in sub-zones. A camera-based occupant detection method was developed to detect occupants (with eight possible locations in sub-zones denoted as 'A' to 'H'). Linear ventilation model (LVM), dimension reduction, and artificial neural network (ANN) were integrated for rapid prediction of pollutant concentrations in sub-zones with the identified occupants and ventilation rates as inputs. Coordinated ventilation effects between sub-zones were optimized to improve infection prevention and energy savings. Results showed that rapid prediction models achieved an average prediction error of 6 ppm for CO2 concentration fields compared with the simulation under different occupant scenarios (i.e., occupant locations at ABH, ABCFH, and ABCDEFH). ZDCV largely reduced the infection risk to 2.8% while improved energy-saving efficiency by 34% compared with the system using constant ventilation rate. This work can contribute to the development of building environmental control systems in terms of pollutant removal, infection prevention, and energy sustainability.

Study on infection risk in a negative pressure ward under different fresh airflow patterns based on a radiation air conditioning system

COVID-19 and other respiratory infectious viruses are highly contagious, and patients need to be treated in negative pressure wards. At present, many negative pressure wards use independent air conditioning equipment, but independent air conditioning equipment has problems such as indoor air circulation flow, condensate water accumulation, and improper filter maintenance, which increase the risk of infection for healthcare workers and patients. The radiation air conditioning system relies on the radiation ceiling to control the indoor temperature and uses new air to control the indoor humidity and air quality. The problems caused by the use of independent air conditioning equipment should be avoided. This paper studies the thermal comfort, contaminant distribution characteristics, contaminant removal efficiency, and accessibility of supply air in a negative pressure ward with a radiation air conditioning system under three airflow patterns. In addition, the negative pressure ward was divided into 12 areas, and the infection probability of healthcare workers in different areas was analyzed. The results show that the application of radiation air conditioning systems in negative pressure wards can ensure the thermal comfort of patients. Stratum ventilation and ceiling-attached jets have similar effects in protecting healthcare workers; both can effectively reduce the contaminant concentrations and the risk of infection of healthcare workers. Ceiling-attached jets decreases the contaminant concentrations by 10.73%, increases the contaminant removal efficiency by 12.50%, and decreases the infection probability of healthcare workers staying indoors for 10 min by 23.18%, compared with downward ventilation.