A predictive model for the formaldehyde removal performance of sorption-based portable air cleaners with pleated composite filter

Abstract

Sorption-based portable air cleaners (PACs) are widely-used to remove gaseous contaminants. However, their capacity decline as a result of saturation cannot be well predicted through tests alone. Therefore, a predictive model to characterize the performance of a sorption-based PAC installed with a pleated composite filter is proposed in this paper. A salient merit of this proposed model is that once verified, it merely requires information regarding the adsorbent to simulate the assembled PAC. The model verification was conducted at three levels: 1) Dynamic adsorption test on the single-layer filter segment; 2) Contaminant removal test on the assembled PAC in the laboratory, which validated the extrapolation from the filter to the actual PAC unit; and 3) Field test in the research building. The third part estimated the robustness of the model in real situations. Formaldehyde was chosen as the target contaminant. Resultsshow that the model can handle changes in significant factors including temperature, relative humidity, flow rate, and inlet concentration. It was successfully extrapolated to an assembled PAC and was able to capture the point of decline of the clean air delivery rate (CADR) in the laboratory. Besides, the average relative errors between the tested and simulated results in the field test were under 20%, which is considered suitable for engineering applications.