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International Heat Transfer Conference 16

ISSN: 2377-424X (online)
ISSN: 2377-4371 (flashdrive)

ASSESSMENT OF INDOOR PM2.5 CONCENTRATIONS: INFILTRATION FACTOR AND RELATIVE ERROR

Zhiwei Sun
Department of Building Science, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Beijing 100084, China

Jianping Cao
Department of Building Science, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Beijing 100084, China

Yinping Zhang
Department of Building Science, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Beijing 100084, China

DOI: 10.1615/IHTC16.mtr.023202
pages 5785-5793


KEY WORDS: Mass transfer, Numerical Simulation, Energy and environmental system, Infiltration factor

Abstract

The average indoor PM2.5 concentration is often estimated by the average outdoor PM2.5 concentration and the infiltration factor when indoor PM2.5 sources and resuspension could be neglected, where the infiltration factor is calculated under the steady state assumption. However, this steady-state method may result in significant errors because the indoor and outdoor PM2.5 concentrations and occupants' window opening behaviors are time-varying. In this study, the indoor PM2.5 concentration based upon the infiltration factor is assessed for residences in Beijing and compared with the indoor PM2.5 concentration based upon the transient-mass-balance model. Then the errors introduced to the average indoor PM2.5 concentration based upon the infiltration factor are determined. The annually-averaged indoor PM2.5 concentration is often underestimated by the infiltration factor and the relative error ranges from -25.7% to 0.5% with the arithmetic mean of -9.8%. As for the monthly-averaged results, the absolute relative error is less than 10% on July and August when people incline to open window. However, the absolute relative error would be larger than 50% in shorter-time scale situations, e.g. hourly-averaged and daily-averaged indoor PM2.5 concentrations. Based upon the distribution of relative error estimated in this study, this steady-state method could be applied to estimate the annually-averaged indoor PM2.5 concentration for residences in Beijing. However, this method is hard to be applied in daily indoor PM2.5 concentration control.

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