The purpose of this study was to evaluate changes in the concentration of air pollutants in the indoor environments, which could be caused by seasonal changes or changes in operating conditions of subway metro stations. In fact, there are many different types of pollution that can cause contamination in subway stations, and changes in operating conditions can also lead to changes in the indoor air quality (IAQ). Therefore, in order to establish a proper management of IAQ, it would be necessary to evaluate the changes in IAQ according to the changes in conditions. To do this, the present study used a multivariate analysis of variance (MANOVA). The results of testing the hypothesis proved that two groups, divided by the condition of a platform screen door (PSD) system, could differ statistically. Furthermore, those multidimensional differences were caused by installation of a PSD system. When applied to a real-time tele-monitoring system, MANOVA could clearly identify the daily and weekly variations of IAQ in the subway station, as well as the PSD system’s condition. Accordingly, this method could be useful for developing a multivariate system to statistically evaluate the experimental IAQ results in order to optimise operating conditions in a subway metro station to improve IAQ, and to minimise adverse health effects on passengers by exposure to harmful substances.
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