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Impact of Window-opening Random Behaviors on Indoor Ultrafine Particles: a Preliminary Simulation Study

机译:窗口打开随机行为对室内超细颗粒的影响:初步模拟研究

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Ultrafine particulate matters (PMO. 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.
机译:超细颗粒物质(PMO。1)与室内空气质量密切相关,这已被证明对人类健康产生巨大危害。人类居住的行为,如窗户开口可以在很大程度上影响室内空气质量。在这项研究中,单个房间被建立为物理模型。开发了仿真分析方法,以说明在室内稳态流动和良好混合条件下室内超细颗粒(PM0.1)对室内超细颗粒(PM0.1)的特性和影响。通过Logistic回归分析和室内温度作为窗口开口的触发限制量化空调的使用率。蒙特卡罗模型和基于代理的建模(ABM)用于描述窗口开口的随机人体行为。结果表明,由于频率频率的显着差异和不同季节的窗口开口时间长度,窗口开口的随机特性导致PM0.1浓度的变化率为40.3%。在这种情况下,与确定性模型相比,量化室内超细颗粒对室内超细颗粒上的随机窗口开放行为的影响量高出34.8%。本研究可以更好地了解Windows开放行为对室内超细颗粒物质的影响。

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