BIOSMHARS: Model description and validation: Deliverable 4.3

Spacecraft is an exceptional closed environment for living and working. It protects the crew against radiation, high vacuum, extreme temperatures and space debris. It should also provide a healthy indoor environment where contaminants are maintained at safe levels. An essential part of this is the control of microbes. Historically, prevention of infectious disease in the crew has been high priority and crewmembers are screened for infectious diseases before flight. Overall, the available monitoring data of ISS show that the air and surface contamination levels in ISS have generally been below the predefined acceptable limits so that the health risk from microorganisms (both from human and environmental origin) do not present severe medical risks for healthy people during relatively short duration flights. Nevertheless, in confined habitats microbial contamination is a hazard and a stress factor per se and can be of concern in space as it can pose a threat to the crew members with reduced immune response and may threaten the crew members' health during long-duration flights. Microbes can also cause deterioration of surfaces. Crewmembers are a major source of microorganisms on spacecraft, although most of the microbes released are generally harmless along with some opportunistic pathogens. Microbial contaminants may also originate from payloads and experiments, water and food, consumables. Moreover, pre-flight contamination may also be a factor. As human space flight moves from the relatively short term into longer duration missions, understanding the effects of long term exposure to microbial contaminants in the space environment is becoming increasingly important. This report describes computational modelling and simulation of the spacecraft indoor environment. The model would be useful for predicting the microbe generation, dispersion and deposition and therby to estimate risk caused by microbial exposure, and for implementing effective countermeasures to minimize the negative effects of microorganisms. They may also be useful in developing effective biocontamination monitoring strategies by suggesting sampling locations and frequency. The modelling efforts during the BIOSMHARS project included several steps and required experimentation to validate and improve the models. This document summarises these efforts and presents the validations done.