Evaluation and prediction of fibrous filters' operating performance in residential fresh air system

Abstract

Fibrous filters play a crucial role in determining indoor air quality and protect people from bacteria, particulates, and viruses such as COVID-19. However, there is a lack of comprehensive research on methods for effectively evaluating and predicting the operating performance of these filters. In this study, we conducted laboratory and field tests on coarse (G4) and medium (F9 or F7) filters from four different brands to assess both their initial and operating performance. We discovered that a fluffy fiber structure in coarse filters could achieve an impressive threefold increase in dust holding capacity (DHC) compared to normal filters. Utilizing initial pressure drop, initial particle capture efficiency, and DHC, we introduced a new quality factor (QF) that integrates these parameters to evaluate the filter's long-term performance. This approach addresses the limitations of traditional quality factor, which neglects DHC and tends to underestimate the performance of filters with high DHC. Additionally, we proposed a simple method to predict the filter's operating pressure drop, using particle concentration data from weather report. This allows for convenient assessment of the fresh air system's operating status, offering potential integration into a user-friendly mobile application or computer software. These findings contribute innovative ideas for enhancing the intelligent and energy-efficient operation of fresh air systems.