Environmental contamination and hospital-acquired infection: factors that are easily overlooked.

There is an ongoing debate about the reasons for and factors contributing to healthcare-associated infection (HAI). Different solutions have been proposed over time to control the spread of HAI, with more focus on hand hygiene than on other aspects such as preventing the aerial dissemination of bacteria. Yet, it emerges that there is a need for a more pluralistic approach to infection control; one that reflects the complexity of the systems associated with HAI and involves multidisciplinary teams including hospital doctors, infection control nurses, microbiologists, architects, and engineers with expertise in building design and facilities management. This study reviews the knowledge base on the role that environmental contamination plays in the transmission of HAI, with the aim of raising awareness regarding infection control issues that are frequently overlooked. From the discussion presented in the study, it is clear that many unknowns persist regarding aerial dissemination of bacteria, and its control via cleaning and disinfection of the clinical environment. There is a paucity of good-quality epidemiological data, making it difficult for healthcare authorities to develop evidence-based policies. Consequently, there is a strong need for carefully designed studies to determine the impact of environmental contamination on the spread of HAI

Direct Air Capture of CO₂ in Enclosed Environments: Design under Uncertainty and Techno-Economic Analysis

CO₂ capture from enclosed environments such as commercial buildings can result in reduced ventilation, thereby leading to decreased energy loads on the HVAC systems. We propose a model which regulates the air quality inside the room by adsorption of CO₂ on monoliths coated with zeolite 13X, and water adsorption on packed beds with silica gel. We perform a modeling study and energy assessment by simulating a multi-component, multi-bed system which controls carbon dioxide level inside the room on a 24 hr basis. The results obtained indicate a 75% reduction in energy load with the CO₂ capture system as compared to the conventional ventilation system. We have identified areas of uncertainty in the model and compared non-intrusive polynomial chaos method with Monte Carlo simulations to quantify the model uncertainties. The results show improvement in computational efficiency with non-intrusive methods as compared to Monte Carlo simulations. We conclude that the CO₂ capture system can lead to improvement in building energy performance and application of polynomial chaos methods can result in reduction of computational time