Chen, FengFengChenHuang, Wei-ChiehWei-ChiehHuangHwang, Wei-ChunWei-ChunHwangWang, YayingYayingWangYe, JianhuaiJianhuaiYeHung, Hui-MingHui-MingHungJha, Poulami2025-12-192025-12-192025-01https://www.scopus.com/pages/publications/105003963359https://scholars.lib.ntu.edu.tw/handle/123456789/734805Indoor air quality is a crucial factor affecting human health, with high levels of CO2 impairing cognition and ozone reacting with human skin to produce volatile organic compounds (VOCs), such as geranyl acetone (Ga), 6-methyl-5-hepten-2-one (6-MHO), and 4-oxopentanal (4-OPA), which can cause irritation to the respiratory tract and skin. In this study, the indoor air quality of a university classroom was monitored using home-built air quality boxes (AQBs) comprising low-cost sensors for various gas species, including CO2, ozone, and NOx. The interaction processes between indoor and outdoor air and human interference were investigated using box model simulation of CO2 and ozone profiles. The results indicate both indoor CO2 and ozone were significantly affected by the ventilation and number of occupants. The simulation of CO2 profiles retrieves an air exchange rate constant of ~1.05 h−1 for one door opening, in addition to the room ventilator of 1.20 h−1. With the derived parameters, the study estimated that ozone, mainly transported from the outdoors and consumed by room and human surfaces, has deposition velocities of 0.019 ± 0.005 and 0.45 ± 0.15 cm s−1 for room and human surfaces, respectively, consistent with the literature. The simulation also suggests that VOCs such as Ga, 6-MHO, and 4-OPA from ozone consumption on human surfaces might accumulate indoors to several parts per billion by volume in a crowded room with poor ventilation. The integration of observation using low-cost sensors with the model simulation quantified the physical and chemical processes controlling indoor ozone concentration and organic ozonolysis. Furthermore, the study suggests that the retrieved parameters from the model could guide proper ventilation strategies to maintain good indoor air quality with energy efficiency based on the number of occupants.Computer controlNitrogen oxidesOzonizationVolatile organic compoundsChemical processHuman healthHuman skinIndoor air qualityLow-cost sensorsModeling simulationPhysical processSensor SimulationsUniversity classroomsVolatile organicsIndoor air pollution[SDGs]SDG3[SDGs]SDG7[SDGs]SDG11journal article10.1155/ina/3358673