Uncertainty assessment for the airborne nanoparticle collection efficiency of a TEM grid-equipped sampling system by Monte-Carlo calculation

A mini particle sampler (MPS) equipped with a transmission electron microscopy (TEM) grid enables convenient particle sampling to subsequent analysis. However, its sampling efficiency involves uncertainties, and accurate sampling efficiency is required for particle collection applications. In this study, the sampling efficiency uncertainties from measured data and models are quantified using Monte-Carlo methods. The Sobol variance-based sensitivity analysis is used to determine the contributions of parameters to the sampling efficiency uncertainties. The results reveal that the sampling efficiency uncertainties from experimental dispersion calibration and theoretical models are generally less than 1% and 9%, respectively. Most sampling efficiency measured data are covered by the efficiency uncertainty range simulated by theoretical models. Pore size and flowrate contribute significantly to the sampling efficiency uncertainties and require control to improve the sampling efficiency precision. Besides, the Cunningham correction factor is also a sensitivity parameter. The utilization of proper models is crucial to support simulations for further process optimization. This study offers a quantitative method for nanoparticle collection efficiency analysis, which will help assess nanomaterials’ workplace exposure.