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首页> 外文期刊>Building and Environment >Differentiating between indoor exposure to PM_(2.5) of indoor and outdoor origin using time-resolved monitoring data
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Differentiating between indoor exposure to PM_(2.5) of indoor and outdoor origin using time-resolved monitoring data

机译：使用时间分辨监测数据区分室内暴露于室内和室外PM_（2.5）的室内

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摘要

To effectively control indoor PM2.5 (particulate matter with diameter less than 2.5 mu m) in residential buildings, it is essential to differentiate between the contributions of outdoor PM2.5 infiltration and indoor PM2.5 emissions to the total indoor exposure. This study developed a method for automatically differentiating between indoor exposure to PM2.5 of indoor and outdoor origin using only the time-resolved indoor and outdoor PM2.5 concentrations and information about window opening/closing behavior. This investigation focused on naturally ventilated buildings without the use of portable air cleaners. The proposed approach combines change point analysis, a statistical method; the mass balance for PM2.5, a physical model; and window behavior characteristics to analyze the data and identify the indoor PM2.5 emissions. A series of experiments in a small-scale laboratory setup were conducted to validate the proposed method. The results show that the proposed method can automatically and successfully identify the indoor PM2.5 emissions for all of the 17 cases. Also, the proposed method accurately estimated the indoor exposure to PM2.5 of indoor and outdoor origin as a percentage of the total indoor exposure for all 17 cases with an average absolute error of 0.32%.
机译：为了有效控制住宅建筑中的室内PM2.5（直径小于2.5微米的颗粒物），必须区分室外PM2.5的渗透和室内PM2.5的排放对室内总暴露量的贡献。这项研究开发了一种仅使用时间分辨的室内和室外PM2.5浓度以及有关开窗/关门行为的信息自动区分室内暴露于室内和室外PM2.5的方法。这项调查的重点是不使用便携式空气滤清器的自然通风建筑。所提出的方法结合了变化点分析和统计方法。物理模型PM2.5的质量平衡；和窗户行为特征来分析数据并识别室内PM2.5排放。在小型实验室设置中进行了一系列实验，以验证所提出的方法。结果表明，所提出的方法可以自动，成功地识别所有17种情况下的室内PM2.5排放。此外，所提出的方法准确地估计了室内和室外来源的PM2.5的室内暴露量占全部17个病例的总室内暴露量的百分比，平均绝对误差为0.32％。

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