Abstract: Scanning electron microscopy (SEM) remains a popular approach to determine the shape, size, density and elemental composition of particles collected on leaf surfaces, but the effect of leaf micro-morphology on particle counts is not very well known. In this study, leaves of sixteen urban plant species were examined for particle density in June and September 2016 using SEM. The investigated plant species differed in leaf micro-morphology involving trichomes, raised stomata, epicuticular wax crystals and convex epidermal cells forming deep grooves between cells. The particle density on leaves of the investigated plant species was estimated by particle size fraction and leaf side. Particle density was significantly higher on the adaxial (AD) leaf side compared to the abaxial (AB) leaf side and higher for fine-particles than coarse-particles. The effect of trichome density on particle density of the AB and the AD leaf side was indicated to be significant and positive for both coarse and fine-particles in June but not in September. The successive repeated measurements elucidated that features constructing the topography of a leaf surface such as trichomes, stomata, and epidermal cells frequently contributed towards the edge enhancement effect, resulting in exaggerated particle counts. Besides, the mechanical drift contributed to the disparity in particle density measurements. Lastly, the reduction in particle density between successive measurements were imputed on the charging effect. These results enable us to suggest that in addition to characterization of micro-morphological features on a leaf surface, SEM will continue to be a useful approach for determining the particle: shape, size, elemental composition and density of the deposited particles. Nonetheless, the disparity in particle density measurements can occur due to abnormal particle recognition. Based on the results of September, we recommend that within-session successive repeated measurements (~ n ≥ 5) need to be performed to remove measurement uncertainties and obtain reliable quantitative data of particle counts using SEM.