Ultrafine particulate matters (PM0.1) are closely related to indoor air quality, which has been proved to do great harm to the human health. The behaviors of human habitation, such as window-opening can influence indoor air quality to a great extent. In this study, a single room was established as a physical model. The simulation analysis method was developed to illustrate the characteristics and influences of window-opening behaviors on indoor ultrafine particles (PM0.1) under the assumption of steady-state flow and well-mixing conditions indoors. The usage rate of air conditioners was quantified by logistic regression analysis and indoor temperature as the trigger restriction of window-opening. Monte Carlo model and Agent-Based Modeling (ABM) were applied to describe the random human behavior of window-opening. The results showed the random characteristics of window-opening caused the change rate of 40.3% for PM0.1 concentrations due to the significant differences in the frequency and the length of time of window-opening in different seasons. In that case, impact of random window-opening behavior on indoor ultrafine particles was quantified to be accumulative value of 34.8% higher compared with certainty model. This study could be better understanding of impact of windows-opening behavior on indoor ultrafine particulate matters.
Tian, X., Chen, S., Wei, Z., Zhang, H., Guan, J., Lin, Y., & Guan, S. (2017). Impact of Window-opening Random Behaviors on Indoor Ultrafine Particles: A Preliminary Simulation Study. In Procedia Engineering (Vol. 205, pp. 2793–2799). Elsevier Ltd. https://doi.org/10.1016/j.proeng.2017.09.886