This study was designed to optimize particle counting of a unique deposition pattern of iron oxide (Fe 3 O 4 ) particles that were collected by a multidomain magnetic passive aerosol sampler (MPAS). Fe 3 O 4 is paramagnetic with a high magnetic susceptibility, rendering high collection efficiencies. The MPAS was designed exclusively for measuring particle penetration through protective clothing. To quantify particle deposition by size, two counting methods were employed with a computer-controlled scanning electron microscope (CCSEM). Based on a sequential set of measurements at known coordinates, particles were quantified across particle clusters collected by individual magnets. Because all magnets were of equal dimensions and strength, the particle concentration per cluster across the entire MPAS substrate was expected to be relatively uniform. However, since individual CCSEM fields are extremely small compared with the full sample, a randomized counting approach was used to determine how many fields were needed to obtain a representative subsample. Results by the sequential method show that particle numbers were higher toward the edge of the cluster, dominated by smaller particles; moderate at the center, dominated by larger particles; and null at the corners. The results additionally show that counting by the random method was comparable with the sequential method and repeatable for particle counts ranging from 3 to 383 particles per field, or 409,565-52,287,826 particles per substrate, taking between 25 and 53 min, respectively. The results suggest that with the random