Investigation of the Influence of Data Collection and Analysis Procedures on Aerosol Filtration Model Development

Abstract

Fibrous air filters are common devices used to remove airborne particles. Their performance is typically measured through their resistance to airflow and captured particle mass. Models describing the evolution of filter performance have been heavily researched; however, the need for improvement remains. Experimental work is irreplaceable in the development of high-fidelity models, yet the estimation of necessary variables is not trivial and may be influenced by selected measurement instruments and analysis methodologies. Therefore, the purpose of this work is to propose a framework to investigate the response of common aerosol measurement instruments, their corresponding analysis methodologies, and the application of their data. A Scanning Mobility Particle Sizer (SMPS) and Laser Aerosol Spectrometer (LAS) were selected for consideration, and their recorded data were compared against baseline measurements. The results of the experiments indicated that the SMPS and LAS yielded a ratio of estimated mass concentrations to the baseline mass concentrations of approximately 1.175 and 0.749, respectively. Regarding the SMPS, it was suggested that the measurable size range, application of a coverage factor, dynamic shape factor, and association between the curve fits and histograms were influential in the final estimates. For the LAS, the application of a curve fit, its association to the histograms, and the selection of the sampling periods were influential. Considering the results, the impact of these factors may not be considered negligible and may skew reproducibility between studies and fossilize confounding factors. Therefore, the proposed methodologies are useful in addressing potential errors in data collection and analysis.

Keywords

• filtration modeling
• experimental methodology
• particle size distribution
• correction factor