Abstract

Indoor air pollution contributes significantly as a world-wide environmental issue, impacting health and livelihood. To quantify benefits of filtration on indoor air quality, it is essential to understand the relationships between the various factors impacting the concentrations of indoor air pollutants. This work uses a mass-conserving 2-box model, high-frequency observations of aerosol number concentration, and a home-made, low-cost, 3-layer non-woven fabric filter, powered by a standard ventilation fan to quantify the effectiveness aerosol reduction in multiple indoor environments. The data shows that aerosol loading is effectively reduced under both steady-state and extreme event conditions, although there are significant and important differences between simultaneous observations both indoor and outside. To obtain a proper accounting, the following must be considered: the usage or not of the fan filter, whether windows are opened or closed, the state of outdoor air is pollution, and the strength and duration of indoor emissions. The experiments are applied in residential indoor environments in four cities in eastern (Xuzhou), central (Zhoukou), and southern (Zhuhai and Shunde) China. Photographic evidence of the altered fan filter state under both conditions show that while usually dark/black aerosols dominate, there are conditions when yellow aerosols also dominate. The observations are based on multiple, independent, continuous low-cost sensors which have been calibrated against a GRIMM-180 over the number concentration range from 0.3 to 1.0 microns, and yield a removal rate due to the fan-filter of 46%, 80%, 81%, and 36% respectively across the four cities. A corresponding rate to return from an extreme event to steady-state, is computed outdoors and indoors respectively from: 14.−44. minutes, 6.6–21. minutes, 16.−33. minutes, and 24.−58. minutes. The most important factors contributing to the removal efficiency and decay gradient are observed as keeping windows closed and reducing leakiness, the apartment/classroom size, and the outdoor air pollution loading.

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