Numerical investigation of particle deposition in a triple bifurcation airway due to gravitational sedimentation and inertial impaction

Novel statistical time series data augmentation and machine learning based classification of unobtrusive respiration data for respiration Digital Twin model

Digital Twin (DT), a concept of Healthcare (4.0), represents the subject's biological properties and characteristics in a digital model. DT can help in monitoring respiratory failures, enabling timely interventions, personalized treatment plans to improve healthcare, and decision-support for healthcare professionals. Large-scale implementation of DT technology requires extensive patient data for accurate monitoring and decision-making with Machine Learning (ML) and Deep Learning (DL). Initial respiration data was collected unobtrusively with the ESP32 Wi-Fi Channel State Information (CSI) sensor. Due to limited respiration data availability, the paper proposes a novel statistical time series data augmentation method for generating larger synthetic respiration data. To ensure accuracy and validity in the augmentation method, correlation methods (Pearson, Spearman, and Kendall) are implemented to provide a comparative analysis of experimental and synthetic datasets. Data processing methodologies of denoising (smoothing and filtering) and dimensionality reduction with Principal Component Analysis (PCA) are implemented to estimate a patient's Breaths Per Minute (BPM) from raw respiration sensor data and the synthetic version. The methodology provided the BPM estimation accuracy of 92.3% from raw respiration data. It was observed that out of 27 supervised classifications with k-fold cross-validation, the Bagged Tree ensemble algorithm provided the best ML-supervised classification. In the case of binary-class and multi-class, the Bagged Tree ensemble showed accuracies of 89.2% and 83.7% respectively with combined real and synthetic respiration dataset with the larger synthetic dataset. Overall, this provides a blueprint of methodologies for the development of the respiration DT model.

Computational fluid-particle dynamics modeling of ultrafine to coarse particles deposition in the human respiratory system, down to the terminal bronchiole

BACKGROUND AND OBJECTIVES

Suspended respirable airborne particles are associated with human health risks and especially particles within the range of ultrafine (< 0.1 μm) or fine (< 2.5 μm) have a high possibility of penetrating the lung region, which is concerned to be closely related to the bronchial or alveoli tissue dosimetry. Nature complex structure of the respiratory system requires much effort to explore and comprehend the flow and the inhaled particle dynamics for precise health risk assessment. Therefore, this study applied the computational fluid-particle dynamics (CFPD) method to elucidate the deposition characteristics of ultrafine-to-coarse particles in the human respiratory tract from nostrils to the 16^th generation of terminal bronchi.

METHODS

The realistic bronchi up to the 8^th generation are precisely and perfectly generated from computed tomography (CT) images, and an artificial model compensates for the 9^th-16^th bronchioles. Herein, the steady airflow is simulated at constant breathing flow rates of 7.5, 15, and 30 L/min, reproducing human resting-intense activity. Then, trajectories of the particle size ranging from 0.002 - 10 μm are tracked using a discrete phase model.

RESULTS

Here, we report reliable results of airflow patterns and particle deposition efficiency in the human respiratory system validated against experimental data. The individual-related focal point of ultrafine and fine particles deposition rates was actualized at the 8^th generation; whilst the hot-spot of the deposited coarse particles was found in the 6^th generation. Lobar deposition characterizes the dominance of coarse particles deposited in the right lower lobe, whereas the left upper-lower and right lower lobes simultaneously occupy high deposition rates for ultrafine particles. Finally, the results indicate a higher deposition in the right lung compared to its counterpart.

CONCLUSIONS

From the results, the developed realistic human respiratory system down to the terminal bronchiole in this study, in coupling with the CFPD method, delivers the accurate prediction of a wide range of particles in terms of particle dosimetry and visualization of site-specific in the consecutive respiratory system. In addition, the series of CFPD analyses and their results are to offer in-depth information on particle behavior in human bronchioles, which may benefit health risk assessment or drug delivery studies.

Targeted delivery of inhalable drug particles in the tracheobronchial tree model of a pediatric patient with bronchopneumonia: A numerical study

Pneumonia is a common cause of hospitalization and death in children worldwide. Inhalation therapy is one of the methods treating pneumonia However, there are limited studies that distinguish between the physiology of children and adults, especially with respect to targeted drug delivery. A tracheobronchial (TB) tree model of an 11-year-old child with bronchopneumonia is selected as a testbed for in silico trials of targeted drug delivery. The airflow and particle transport are solved by the computational fluid dynamics method at an airflow rate of 15 LPM. The results indicate that the distribution of deposited particles shows aggregation on the particle release map. Point-source aerosol release (PSAR) method can significantly reduce the deposition efficiency (DE) of particles in the TB tree model. Specifically, the PSAR method can reduce the DE of large particles (i.e., 7.5 µm and 10 µm) by 7.57% and 9.61%, respectively. This enables rapid design of patient-specific treatment for different population age groups and different airway diseases.

Numerical investigations of the micro lunar dust particles deposition in the human oral respiratory airway

Understanding the deposition of lunar dust (LD) particles in the human respiratory system is of great significance for protecting astronauts' health from the toxicity of lunar dust. A Euler-Lagrangian approach is adopted to track the LD particle motion in a human oral airway model. The investigations are conducted considering different inspiration rates and micro-particle sizes as well as different abnormal pressures and abnormal temperatures. It is found that 1) almost all the LD particles tend to enter the right lung rather than the left lung, especially in the upper right lobe; 2) at lower ambient pressure, fewer LD particles will deposit in the upper airway, while more particles will enter the lung; 3) at lower temperature, more LD particles are deposited in the upper airway, while fewer are deposited in the lung. In summary, the present work has shown that the LD particles have different depositing properties in the upper airway and the lung lobe regions up to the particle size, inspiration flow rate, temperature and pressure. It should pay more attentions on the upper airway and right upper lobe when it studies the toxicity of the lunar dust, and can't ignore the impact of the environmental temperature and pressure.

Effect of transient breathing cycle on the deposition of micro and nanoparticles on respiratory walls

BACKGROUND AND OBJECTIVE

From various perspectives (e.g. inhalation exposure and drug delivery), it is important to provide insights into the behavior of inhaled particles in the human respiratory system. Although most of the experimental and numerical studies have relied on an assumption of steady inhalation, the transient breathing profile is a key factor in particle deposition in the respiratory tract. In this study, particle transportation and deposition were predicted in a realistic human airway model during a breathing cycle and the effects of steady-state and transient flows on the deposition fraction were observed using computational fluid dynamics.

METHODS

Two transient breathing cycles with different respiratory durations were considered to evaluate the effects of respiration duration on particle transport and deposition characteristics. Two types of steady breathing conditions with corresponding steady-state respiratory volumes were reproduced. The Lagrangian discrete phase model approach was used to investigate particle transportation and deposition under transient breathing conditions. Additionally, the Eulerian approach was used to analyze the transport of nanoparticles in the gas phase. A total of >50,000 monodispersed particles with aerodynamic diameters ranging between 2 nm and 10 μm were selected for comprehensive deposition predictions for particle sizes ranging from the nano- to microscale.

RESULTS

The predicted results were compared with the experimental data. The particle deposition fraction in the nasal cavity and tracheal regions showed differences between the steady and transient simulations. In addition, particle analysis under steady inhalation conditions cannot accurately predict particle transportation and deposition in the lower airway. Furthermore, the breathing cycle had a significant effect on the deposition fraction of the particles and the behavior of the inhaled particles.

CONCLUSIONS

Transient simulation mimicking the breathing cycle was observed to be an important factor in accurately predicting the transportation and deposition of particles in the respiratory tract.

Particle Deposition in Large-Scale Human Tracheobronchial Airways Predicted by Single-Path Modelling

The health effects of particles are directly related to their deposition patterns (deposition site and amount) in human airways. However, estimating the particle trajectory in a large-scale human lung airway model is still a challenge. In this work, a truncated single-path, large-scale human airway model (G3-G10) with a stochastically coupled boundary method were employed to investigate the particle trajectory and the roles of their deposition mechanisms. The deposition patterns of particles with diameters (dp) of 1-10 μm are investigated under various inlet Reynolds numbers (Re = 100-2000). Inertial impaction, gravitational sedimentation, and combined mechanism were considered. With the increasing airway generations, the deposition of smaller particles (dp < 4 μm) increased due to gravitational sedimentation, while that of larger particles decreased due to inertial impaction. The obtained formulas of Stokes number and Re can predict the deposition efficiency due to the combined mechanism in the present model, and the prediction can be used to assess the dose-effect of atmospheric aerosols on the human body. Diseases in deeper generations are mainly attributed to the deposition of smaller particles under lower inhalation rates, while diseases at the proximal generations mainly result from the deposition of larger particles under higher inhalation rates.

Evaluation of Unobtrusive Microwave Sensors in Healthcare 4.0-Toward the Creation of Digital-Twin Model

The prevalence of chronic diseases and the rapid rise in the aging population are some of the major challenges in our society. The utilization of the latest and unique technologies to provide fast, accurate, and economical ways to collect and process data is inevitable. Industry 4.0 (I4.0) is a trend toward automation and data exchange. The utilization of the same concept of I4.0 in healthcare is termed Healthcare 4.0 (H4.0). Digital Twin (DT) technology is an exciting and open research field in healthcare. DT can provide better healthcare in terms of improved patient monitoring, better disease diagnosis, the detection of falls in stroke patients, and the analysis of abnormalities in breathing patterns, and it is suitable for pre- and post-surgery routines to reduce surgery complications and improve recovery. Accurate data collection is not only important in medical diagnoses and procedures but also in the creation of healthcare DT models. Health-related data acquisition by unobtrusive microwave sensing is considered a cornerstone of health informatics. This paper presents the 3D modeling and analysis of unobtrusive microwave sensors in a digital care-home model. The sensor is studied for its performance and data-collection capability with regards to patients in care-home environments.

Effects of airway deformation and alveolar pores on particle deposition in the lungs

The distal lung (G14-G23), which are composed of alveoli and bronchi, are responsible for almost all gas exchange and micro- and nanoparticle deposition in the lungs. In the existing research using computational fluid dynamics, the geometric modeling accuracy of the bronchial bifurcation structure is given priority, and then the alveoli are attached to bronchi as discrete spherical crowns. This method ignores the correlation between alveoli. In fact, the alveoli have a tessellated distribution, and adjacent alveoli are connected by several alveolar pores. Due to the huge number of alveoli, this seemingly small difference will be greatly amplified, which may lead to a large deviation in the prediction of the overall flow. Accordingly, the objective of this study is to construct a two-dimensional distal lung model including the bronchi, acini, and alveolar pores by using the methods of regular hexagonal tessellational subdivision, fusion, and coordinate transformation. A moving boundary is introduced to simulate the process of airflow and particle deposition in the distal lung, and the effects of bronchial deformation, respiratory frequency, and alveolar pores are obtained. The results show that there are significant differences in intrapulmonary flow patterns with and without alveolar pores. Alveolar pores can establish bypass ventilation downstream of a blockage, thus providing a pathway for particles to enter the airways downstream of the blockage. Changing the respiratory frequency and the amplitude of bronchial deformation will change the relative velocity between particles and moving wall, which, in turn, will change the particle deposition efficiency in the distal lung. To summarize this study, a geometric modeling method for the distal lung with alveolar pores is established, and the important roles of detailed characteristics of the distal lung are revealed. The findings of this study provide a reasonable hydrodynamic mechanism for the prevention of related respiratory diseases.

Targeted delivery of inhalable drug particles in a patient-specific tracheobronchial tree with moderate COVID-19: A numerical study

The coronavirus disease 2019 (COVID-19) pandemic has led to severe social and economic disruption worldwide. Although currently no consent has been reached on a specific therapy that can treat COVID-19 effectively, several inhalation therapy strategies have been proposed to inhibit SARS-CoV-2 infection. These strategies include inhalations of antiviral drugs, anti-inflammatory drugs, and vaccines. To investigate how to enhance the therapeutic effect by increasing the delivery efficiency (DE) of the inhaled aerosolized drug particles, a patient-specific tracheobronchial (TB) tree from the trachea up to generation 6 (G6) with moderate COVID-19 symptoms was selected as a testbed for the in silico trials of targeted drug delivery to the lung regions with pneumonia alba, i.e., the severely affected lung segments (SALS). The 3D TB tree geometry was reconstructed from spiral computed tomography (CT) scanned images. The airflow field and particle trajectories were solved using a computational fluid dynamics (CFD) based Euler-Lagrange model at an inhalation flow rate of 15 L/min. Particle release maps, which record the deposition locations of the released particles, were obtained at the inlet according to the particle trajectories. Simulation results show that particles with different diameters have similar release maps for targeted delivery to SALS. Point-source aerosol release (PSAR) method can significantly enhance the DE into the SALS. A C++ program has been developed to optimize the location of the PSAR tube. The optimized simulations indicate that the PSAR approach can at least increase the DE of the SALS by a factor of 3.2× higher than conventional random-release drug-aerosol inhalation. The presence of the PSAR tube only leads to a 7.12% change in DE of the SALS. This enables the fast design of a patient-specific treatment for reginal lung diseases.

Combining experimental and computational techniques to understand and improve dry powder inhalers

INTRODUCTION

: Dry Powder Inhalers (DPIs) continue to be developed to deliver an expanding range of drugs to treat an ever-increasing range of medical conditions; with each drug and device combination needing a specifically designed inhaler. Fast regulatory approval is essential to be first to market, ensuring commercial profitability.

AREAS COVERED

: In vitro deposition, particle image velocimetry, and computational modelling using the physiological geometry and representative anatomy can be combined to give complementary information to determine the suitability of a proposed inhaler design and to optimise its formulation performance. In combination they allow the entire range of questions to be addressed cost-effectively and rapidly.

EXPERT OPINION

: Experimental techniques and computational methods are improving rapidly, but each needs a skilled user to maximize results obtained from these techniques. Multidisciplinary teams are therefore key to making optimal use of these methods and such qualified teams can provide enormous benefits to pharmaceutical companies to improve device efficacy and thus time to market. There is already a move to integrate the benefits of Industry 4.0 into inhaler design and usage, a trend that will accelerate.

Aerosol Particle Transport and Deposition in Upper and Lower Airways of Infant, Child and Adult Human Lungs

Understanding transportation and deposition (TD) of aerosol particles in the human respiratory system can help clinical treatment of lung diseases using medicines. The lung airway diameters and the breathing capacity of human lungs normally increase with age until the age of 30. Many studies have analyzed the particle TD in the human lung airways. However, the knowledge of the nanoparticle TD in airways of infants and children with varying inhalation flow rates is still limited in the literature. This study investigates nanoparticle (5 nm ≤ dp ≤ 500 nm) TD in the lungs of infants, children, and adults. The inhalation air flow rates corresponding to three ages are considered as Qin=3.22 L/min (infant), 8.09 L/min (Child), and Qin=14 L/min (adult). It is found that less particles are deposited in upper lung airways (G0–G3) than in lower airways (G12–G15) in the lungs of all the three age groups. The results suggest that the particle deposition efficiency in lung airways increases with the decrease of particle size due to the Brownian diffusion mechanism. About 3% of 500 nm particles are deposited in airways G12–G15 for the three age groups. As the particle size is decreased to 5 nm, the deposition rate in G12–G15 is increased to over 95%. The present findings can help medical therapy by individually simulating the distribution of drug-aerosol for the patient-specific lung.

Aerosol deposition and airflow dynamics in healthy and asthmatic human airways during inhalation

Inhalation of aerosols such as pharmaceutical aerosols or virus aerosol uptake is of great concern to the human population. To elucidate the underlying aerosol dynamics, the deposition fractions (DFs) of aerosols in healthy and asthmatic human airways of generations 13-15 are predicted. The Navier-stokes equations governing the gaseous phase and the discrete phase model for particles' motion are solved using numerical methods. The main forces responsible for deposition are inertial impaction forces and complex secondary flow velocities. The curvatures and sinusoidal folds in the asthmatic geometry lead to the formation of complex secondary flows and hence higher DFs. The intensities of complex secondary flows are strongest at the generations affected by asthma. The DF in the healthy airways is 0%, and it ranges from 1.69% to 52.93% in the asthmatic ones. From this study, the effects of the pharmaceutical aerosol particle diameters in the treatment of asthma patients can be established, which is conducive to inhibiting the inflammation of asthma airways. Furthermore, with the recent development of COVID-19 which causes pneumonia, the predicted physics and effective simulation methods of bioaerosols delivery to asthma patients are vital to prevent the exacerbation of the chronic ailment and the epidemic.

Modeling of the transport, hygroscopic growth, and deposition of multi-component droplets in a simplified airway with realistic thermal boundary conditions

Accurate predictions of the droplet transport, evolution, and deposition in human airways are critical for the quantitative analysis of the health risks due to the exposure to the airborne pollutant or virus transmission. The droplet/particle-vapor interaction, i.e., the evaporation or condensation of the multi-component droplet/particle, is one of the key mechanisms that need to be precisely modeled. Using a validated computational model, the transport, evaporation, hygroscopic growth, and deposition of multi-component droplets were simulated in a simplified airway geometry. A mucus-tissue layer is explicitly modeled in the airway geometry to describe mucus evaporation and heat transfer. Pulmonary flow and aerosol dynamics patterns associated with different inhalation flow rates are visualized and compared. Investigated variables include temperature distributions, relative humidity (RH) distributions, deposition efficiencies, droplet/particle distributions, and droplet growth ratio distributions. Numerical results indicate that the droplet/particle-vapor interaction and the heat and mass transfer of the mucus-tissue layer must be considered in the computational lung aerosol dynamics study, since they can significantly influence the precise predictions of the aerosol transport and deposition. Furthermore, the modeling framework in this study is ready to be expanded to predict transport dynamics of cough/sneeze droplets starting from their generation and transmission in the indoor environment to the deposition in the human respiratory system.

A numerical study of the aerosol behavior in intra-acinar region of a human lung

The determination of the particle dynamics in the human acinar airways having millions of alveoli is critical in preventing potential health problems and delivering therapeutic particles effectively to target locations. Despite its complex geometrical structure and complicate wall movements, the advanced calculation simulations can provide valuable results to accurately predict the aerosol deposition in this region. The objective of this study was to numerically investigate the aerosol particle transport and deposition in the intra-acinar region of a human lung for different breathing scenarios (i.e., light, normal, and heavy activities) during multiple breaths. Idealized intra-acinar models utilized in this study consisted of a respiratory bronchial model, an alveolar duct model, and an alveolar sac model. The particles with 5 μm in diameter released from the inlet of the model were tracked until they deposited or escaped from the computational domain. The results showed that due to the rhythmic alveolar wall movement, the flow field was divided into two regions: one is the low-speed alveolar flow and the other is the channel flow. It was found that the chaotic acinar flow irreversibility played a significant role in the aerosol transport in higher generations. During the succeeding breaths, more particles deposited or escaped to the relating acinar generation and reached the more distal regions of the lung. The number of particles remaining in the suspension at the end of the third cycle ranged from 0.016% to 3%. When the mouth flow rate increased, the number of particles remaining in the suspension reduced, resulting in higher deposition efficiency. The total deposition efficiencies for each flow rate were 24%, 47%, and 77%, respectively. The particle simulation results also showed that more breathing cycle was required for full aerosol particle deposition or escape from the model. In addition to the alveolar wall motion, the type of breathing condition and breathing cycle had a significant effect on the accurate prediction of the aerosol deposition in the intra-acinar region of the human lung.

Modelling Particle Transport and Deposition in the Human Healthy and Stented Tracheobronchial Airways

The main goal of this study is the quantification of the particle transport and deposition within the human airways during light, normal and exercise breathing conditions using the computational fluid dynamics. In particular we presented a comparison between healthy and stented airways. The considered tracheobronchial model is based on the Weibel symmetric model in which we have inserted the Dumon prosthesis at different locations and on the CT-based geometries of a healthy and a stented airway. The results indicate an important redistribution of the particle deposition locations. Local overdoses can be found in the proximal regions of the prostheses, independently of the breathing conditions, of the particle size and of the considered geometry. The presented work is aimed to contribute to the understanding of the particle deposition in the human lung and to improve drug-aerosol therapies. For patients that underwent airways reconstructive surgery, it can give detailed information about the deposition efficiency and it may help targeting specific airways regions.

Effect of Particle-Wall Interaction and Particle Shape on Particle Deposition Behavior in Human Respiratory System

Dry powder inhalation (DPI) has attracted much attention as a treatment for respiratory diseases owing to the large effective absorption area in a human respiratory system. Understanding the drug particle motion in the respiratory system and the deposition behavior is necessary to improve the efficiency of DPI. We conducted computer simulations using a model coupling a discrete element method and a computational fluid dynamics method (DEM-CFD) to evaluate the particle deposition in human respiratory system. A simple artificial respiratory model was developed, which numerically investigated the effect of particle properties and inhalation patterns on the particle deposition behavior. The DEM-CFD simulations demonstrated that the smaller- and lower-density particles showed higher reachability into the simple respiratory model, and the particle arrival ratio to the deep region strongly depended on the aerodynamic diameter. The particle arrival ratio can be described as an exponential function of the aerodynamic diameter. Furthermore, the exponential relationship between the particle reachability into the depth of the simple respiratory model and the aerodynamic diameter predicted the particle aerodynamic diameter based on the required reachability. The particle shape also had an impact on the particle deposition behavior. The rod-like particles with a larger aspect ratio indicated higher reachability into the depth of the simple respiratory model. This was attributed to the high velocity motion of the particles whose long axis was in the direction of the deep region.

Study on Performance of Mesoscopic Impactor Filters for Aerosol Removal

The mesoscopic impactor filter is designed to filtrate aerosols in the containment, which has not only high collection efficiency but also small flow resistance. In this paper, the influence of structural parameters and working parameters of the inertial impactor on collection performance is studied by the computational fluid dynamic (CFD) method. Under the small Reynolds number, the laminar model is used to simulate the continuous phase, and the discrete phase model (DPM) is used to track the trajectory of the particle. Based on the response surface methodology (RSM), the prediction model of collection efficiency and pressure drop is obtained, which will provide a reference for the design and manufacture of the filter in the future.

Health effects of physical activity as predicted by particle deposition in the human respiratory tract

Although health benefits of physical activity are well known, the risk of physical activity in polluted air is unclear. Our objective is to investigate health effects resulting from physical activity in polluted air by looking at particle deposition in human tracheobronchial (TB) airways. Airflow and particle deposition in TB airways were investigated using a computational fluid dynamics (CFD) method. We chose three regional airways: upper (G3-G5), central (G9-G11) and lower (G14-G16). Physical activity was described by breathing rate at the mouth, for three levels of activity: sedentary (15 l/min), moderate (30 l/min) and intense (60 l/min). We found that particle deposition was strongly affected by physical activity. Particles are deposited in greater number in the lower airways (G14-G16) during sedentary activity, more in the upper airways (G3-G5) during intense activity, and uniformly in the airways during moderate activity. The difference in the deposition pattern was due to the reason that physical activity increased the airflow which increased inertial impaction. Our modeling of particle deposition in the human respiratory airways shows that there are different health effects for different activity levels: sedentary activity leads to chronic health effects, intense activity results in acute effects, and moderate activity minimizes the adverse health effects of physical activity in polluted air.

Computational Fluid Dynamics Modeling of Respiratory Airflow in Tracheobronchial Airways of Infant, Child, and Adult

During human growth and development from infancy to adulthood, dramatic changes occur in the respiratory system. It is important to understand respiratory airflow in different age groups in age-specific treatment of respiratory disorders. This study numerically investigated the age-related effects on inspiratory and expiratory airflow dynamics in four-generation lung airway models under normal breathing conditions. Tracheobronchial airway models of infant (6 month old), child (5 years old), and adult (25 years old) from sixth to ninth generations were constructed for the study. Computational fluid dynamics (CFD) was used to solve the equations governing the airflow. Results of this study indicate that as age increases, airflow velocity, pressure, and wall shear stress decrease for both inspiration and expiration in this particular subregion of the respiratory tract. During inspiration, the splitting of velocity streamlines at bifurcations increases with age. The opposite situation merging happens during expiration, and it also increases with age. The level of splitting and merging of streamlines here reflects the influence of respiratory mechanics in the age groups. The computational models provide new information on characteristics and patterns of age-dependent respiratory airflow in the sixth to ninth generations of tracheobronchial airways and can be applied in other generations.

High-performance inertial impaction filters for particulate matter removal

Airborne particulate matter (PM) is causing more and more serious air pollution and threatening the public health. However, existing air filter technologies with the easy-to-block manner can rarely meet the requirements of high-performance PM filters. Here we propose a conceptually new type of inertial impaction filters for rapidly high-efficiency PM removal. Under the airflow velocity of 8.0 m/s, the real inertial impaction filters show high PM removal efficiencies of up to 97.77 ± 1.53% and 99.47 ± 0.45% for PM2.5 and PM10, respectively. Compared with the traditional air filters reported previously, the inertia impaction filters exhibit extremely low pressure drop of 5-10 Pa and high quality factor (QF) values of 0.380 Pa-1 and 0.524 Pa-1 for PM2.5 and PM10, respectively. These greatly improved QF values are achieved through a series of inertial separation processes. The feature dimension of filtration channel is dozens of times larger than PM average size, which greatly decreases airflow resistance. Particularly, this inertial structure can be made of various types of materials, which shows great potential for low-cost fabrication of large-area devices. As a stand-alone device or incorporated with the existing PM air filter, this inertial impaction filter will bring great benefits to the public health.