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A mathematical model for predicting indoor PM_(2.5) concentration under different ventilation methods in residential buildings

机译:在住宅建筑中不同通风方法预测室内PM_(2.5)浓度的数学模型

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摘要

Experiments and theoretical analyses are conducted in a residential building in Changzhou to study indoor PM_(2.5)concentrations by establishing a combined parameter model. An alternative method for predicting the particle deposition rate and penetration coefficient is proposed, and its accuracy is tested and verified by experiments using time-dependent concentrations and air exchange rate measurements. The predicted PM_(2.5)penetration coefficient increased from 0.70 to 0.88 when the air exchange rates were varied from 0.2 h~(−1)to 0.5 h~(−1). In addition, outdoor sources of PM_(2.5)dominantly contributed approximately 90% to 98% to the indoor concentrations for both mechanically and naturally ventilated structures. Finally, a mathematical model for predicting the indoor concentration is presented using a mass balance equation, which estimates the parameter values in the building. The indoor PM_(2.5)concentrations ranged from 40 to 46 µg/m~(3)by using a fresh air system with 82% filtration efficiency, while those by using open windows for natural ventilation ranged from 105 to 118 µg/m~(3)when the outdoor PM_(2.5)concentration ranged from 115 to 137 µg/m~(3). The results of this study can be used to estimate the indoor particle level. Practical application : By applying the ventilation criteria for acceptable indoor air quality in ASHRAE Standard 62.1, the indoor PM_(2.5)monitoring results show serious pollution in dwellings in 2018. More dwellings are expected to maintain a clean indoor environment in the future. Thus, it is crucial to consider the indoor PM_(2.5)pollution risk in the building design to prevent the possible consequences of unsafe high indoor concentrations. The use of this prediction model, as discussed in this article, will provide further information on the influence of the particle deposition rate ( K ) and penetration coefficient ( P ) on indoor PM_(2.5)concentrations.
机译:实验和理论分析是在常州的住宅建筑中进行的,通过建立组合参数模型来研究室内PM_(2.5)浓度。提出了一种用于预测粒子沉积速率和穿透系数的替代方法,并通过使用时间依赖的浓度和空气汇率测量来测试并验证其精度。当空气交换速率从0.2小时变化至0.5小时〜(-1)时,预测的PM_(2.5)穿透系数从0.70增加到0.88增加。此外,PM_(2.5)的户外来源将大约90%的贡献贡献约90%至98%,适用于机械和天然通风结构的室内浓度。最后,使用质量平衡方程提出了一种预测室内浓度的数学模型,其估计建筑物中的参数值。室内PM_(2.5)浓度通过使用具有82%的过滤效率的新鲜空气系统,浓度为40至46μg/ m〜(3),而通过使用开放窗口的自然通风的浓度范围为105至118μg/ m〜( 3)当室外PM_(2.5)浓度范围为115至137μg/ m〜(3)。该研究的结果可用于估计室内颗粒水平。实际应用:通过在Ashrae标准62.1中应用通风标准,室内PM_(2.5)监测结果在2018年的住宅中显示出严重的污染。预计未来更多的住宅将保持清洁的室内环境。因此,考虑建筑设计中的室内PM_(2.5)污染风险至关重要,以防止不安全的高室内浓度的可能后果。如本文所讨论的,使用该预测模型将提供关于颗粒沉积速率(K)和渗透系数(P)对室内PM_(2.5)浓度的影响的进一步信息。

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  • 作者单位

    School of Environmental and Municipal Engineering Xi’an University of Architecture and Technology;

    School of Building Services Science and Engineering Xi’an University of Architecture and Technology;

    School of Building Services Science and Engineering Xi’an University of Architecture and Technology;

    School of Building Services Science and Engineering Xi’an University of Architecture and Technology;

    Department of Building Science School of Architecture Tsinghua University;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Mathematical model; air quality; PM2.5; emission source; ventilation;

    机译:数学模型;空气质量;PM2.5;排放来源;通风;

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