A mathematical model for predicting indoor PM2.5 concentration considering uneven mixing and fractional efficiency of a filter

Abstract

Indoor PM2.5 control has become an essential part of ensuring high-quality indoor air quality. In this paper, to improve the prediction accuracy, an unsteady-state mathematical model for predicting indoor PM2.5 concentration was established. Air exchange efficiency was considered to characterize the uneven mixing of particle concentration in the model. The filter efficiency of the multi-stage filter system and the actual efficiency of each stage filter were redetermined through particle size distribution and fractional efficiency of filter. The accuracy of the model was verified with existing experimental data. Furthermore, the filtration performance of different combinations of typical filters was analyzed. The results showed that when the filter was installed in the second stage in a multi-stage filter system, the filter efficiency coefficients for filtering PM2.5 were 0.94∼0.98, and decreased to 0.81∼0.94 when installed in the third stage. As air exchange efficiency was increased from 0.6 to 0.9, the purification time was shortened by 10.86∼14.44 min. Under the large outdoor PM2.5 concentration, indoor air quality can be guaranteed by increasing the air change rate or adding filters to enhance the filter efficiency. Moreover, there should exist a minimum air change rate to meet the required indoor PM2.5 concentration.