According to past experience, the concentration of air pollutants indoor varies significantly in different environmental conditions. The present study focuses on the investigation of the indoor air quality (IAQ) of the underground trains in Athens, Greece. The investigation was performed in both major lines of the ATTIKO METRO. Monitoring was performed in order to determine the concentration of pollutants and particulate matter, specifically TVOCs, PM10, ΡΜ2.5, ΡΜ1 as well as temperature and relative humidity in the coaches of the trains. In the present study, a methodology based on fuzzy inference systems to assess air quality is proposed. A fuzzy logic assessment system (FLAS) is developed incorporating rules stem collected from real data, human experience and intuition. The results demonstrate the applicability and effectiveness of the FLAS.
Copyright © 2012. Published by Elsevier B.V.