## 1 Introduction  
Particulate matter emission into the atmospheric air is a global health challenge, and emissions are increasing every day [1]. The increasing rate of respiratory health patients is evidence of the health hazards of atmospheric pollution [1]. Precise knowledge of atmospheric aerosol transport and deposition to the airways of the human lung is essential for health assessment and drug delivery purposes [2]. To date, researchers have employed wide-ranging approaches (in silico, in vivo and in vitro) to understand aerosol transport to the airways. The computational fluid dynamics (CFD) approach is the most popular method for airflow and particle transport in airways [3, 4] and most of the studies to date used CFD for aerosol transport in airways. Almost all of the published literature considers the upper airways and analyses aerosol transport in airways [5, 6, 7]. [PERSON] et al. [8] performed an in vivo study for ultrafine aerosol transport and deposition in human oral and nasal airways. The study employed 10 adult healthy males cast for the analysis. The in vivo study reports the smaller cross-section area of the extrathoracic airways and that the complex airway shape influences the overall ultrafine particle deposition pattern. Later, [PERSON] et al. [6] studied ultrafine and microparticles transport in an idealised mouth-throat and upper airways. The symmetric three-generation (G0-G3) model investigates the aerosol deposition pattern for different flow rates. The study reports a higher deposition concentration of the aerosol at the carinal angle region of the airways than in the bifurcating airways. In 2008, [PERSON] et al. [9] considered a 16-generation airway model and analysed the nanoparticle's transport and deposition. The study did not consider the asymmetric whole lung model for the 16 generations, and several 3-generation models were used to analyse the particle deposition. To date, the best available and large-scale asymmetric airway model with maximum bifurcating branches has been developed by [PERSON] et al. [10]. The authors developed a large-scale and highly complex airway model for the first 17 generations of human airways. [PERSON] et al. [5] used the model of [PERSON] et al. [10] and analysed the airflow for the large-scale model for the first time. The digital reference model had 1453 bronchi up to the 17 th Horsfield order. This study analysed the airflow for the first time for a large-scale model and improved the knowledge of the field. Later, in 2017, [PERSON] et al. [7] used the same 17-generation airway model and comprehensively analysed the microparticle transport and deposition in a 17-generation model. This first-ever study considered different physical activity conditions (resting, light activity and heavy physical activity) and analysed the deposition pattern for the first time. However, the CFD simulation of a 3-dimensional anatomically realistic 17-generation lung model based on high-resolution computer tomography (HRCT) data requires huge time and computational resources. The 17-generation model used by [PERSON] et al. [7] took approximately 55 days for a single simulation in a high-performance computing system. This study did not consider all branches of the 17-generation model and would significantly increase the computational cost. [PERSON] et al. [11] also studied ultrafine particle transport and deposition to the lower airways of the 17-generation model, and the first-ever study comprehensively analysed the lobe-specific deposition pattern. The study calculated the deposition hot spot for the ultrafine particles, and the computational cost for ultrafine particle transport for the 17-generation model was significantly high. The computational cost for the CFD model is extremely high due to the huge number of computational cells, and it is nearly impossible to simulate a whole lung model (23 generations) with all bifurcating branches.