Abstract
Understanding airborne pathogen transmission in cruise ship environments remains a critical challenge due to the confined nature of indoor spaces, high occupancy, and limited access for real-world experimentation. This study addresses the gap in empirical data on particulate matter and CO₂ dynamics aboard operational cruise ships, providing a high-resolution dataset that can be used for the validation of Computational Fluid Dynamics (CFD) models and informing infection probability risk assessments. An experimental trial was designed for two mechanically ventilated cruise ship rooms (R01, R02), instrumented at ten locations under eight ventilation scenarios: R01 with 100 % (S1a) and 50 % (S1b) design flow rates; R02 with 100 % (S2a), 50 % (S2b) and 10 % (S2c) design flow rates; R01 with high aerosol rate and 50 % flow rate (S3); and R01 with an air purifier at maximum (S4a, 1300 m3 h−1) and minimum (S4b, 422 m3 h−1) clean air delivery rate (CADR). A live UK-EU cruise hosted the experimental trial. Particulate matter and CO₂ concentration, temperature and relative humidity were collected using portable sensors to build a unique dataset to validate subsequent computational modelling of aerosol dispersion, infection probability and transmission prevention, mitigation and management (PMM) approaches in arbitrary passenger ship spaces. As expected, PM and CO₂ were markedly reduced under 100 % design flow ventilation compared with 50 %. Maximum PM2.5 reductions were 84 % during background, 29 % in build-up, and 72 % in decay experimental phases. An air purifier further reduced particulate matter, with peak PM reductions of 57 % (PM10), 48 % (PM2.5), and 45 % (PM1). These findings offer practical guidance for optimising air quality management strategies in cruise ships and other high-occupancy spaces, besides providing a crucial high-resolution dataset for validating numerical modelling. Moreover, this study provides valuable insights into mechanically ventilated shipboard airflow behaviour.