The nasal cavity is the inlet to the human respiratory system and is responsible for the olfactory sensation, filtering pollutant particulate matter, and humidifying the air. Many research studies have been performed to numerically predict allergens, contaminants, and/or drug particle deposition in the human nasal cavity; however, the majority of these investigations studied only one or a small number of nasal passages. In the present study, a series of Computed Tomography (CT) scan images of the nasal cavities from ten healthy subjects were collected and used to reconstruct accurate 3D models. All models were divided into twelve anatomical regions in order to study the transport and deposition features of different regions of the nasal cavity with specific functions. The flow field and micro-particle transport equations were solved, and the total and regional particle deposition fractions were evaluated for the rest and low activity breathing conditions. The results show that there are large variations among different subjects. The standard deviation of the total deposition fraction in the nasal cavities was the highest for <impaction parameter (IP)< with a maximum of 20%. The achieved results highlighted the nasal cavity sections that are more involved in the particle deposition. Particles with IP = 30,000 deposit more in the middle turbinate and nasopharynx areas, while for particles with IP = 300,000, deposition is mainly in the anterior parts (kiesselbach and vestibule regions). For small IP values, the amounts of deposition fractions in different regions of the nasal cavity are more uniform.