Deposition of ambient particles in the human respiratory system based on single particle analysis: A case study in the Pearl River Delta, China

It is important to evaluate how ambient particles are deposited in the human respiratory system in view of the adverse effects they pose to human health. Traditional methods of investigating human exposure to ambient particles suffer from drawbacks related either to the lack of chemical information from particle number-based measurements or to the poor time resolution of mass-based measurements. To address these issues, in this study, human exposure to ambient particulate matter was investigated using single particle analysis, which provided chemical information with a high time resolution. Based on single particle measurements conducted in the Pearl River Delta, China, nine particle types were identified, and EC (elemental carbon) particles were determined to be the most dominant type of particle. In general, the submicron size mode was dominant in terms of the number concentration for all of the particle types, except for Na-rich and dust particles. On average, around 34% of particles were deposited in the human respiratory system with 13.9%, 7.9%, and 12.6% being distributed in the head, tracheobronchial, and pulmonary regions, respectively. The amount of Na-rich particles deposited was the highest, followed by EC. The overall deposition efficiencies of the Na-rich and dust particles were higher than those of the other particle types due to their higher efficiencies in the head region, which could be caused by the greater sedimentation and impaction rates of larger particles. In the head region, the Na-rich particles made the largest contribution (30.5%) due to their high deposition efficiency, whereas in the tracheobronchial and pulmonary regions, EC made the largest contribution due to its high concentration. In summary, the findings of this initial trial demonstrate the applicability of single particle analysis to the assessment of human exposure to ambient particles and its potential to support traditional methods of analysis.