The understanding of complex inhalation and transport processes of pollutant particles through the human respiratory system is important for investigations into dosimetry and respiratory health effects in various settings, such as environmental or occupational health. The studies over the last few decades for micro- and nanoparticle transport and deposition have advanced the understanding of drug-aerosol impacts in the mouth-throat and the upper airways. However, most of the Lagrangian and Eulerian studies have utilized the non-realistic symmetric anatomical model for airflow and particle deposition predictions. Recent improvements to visualization techniques using high-resolution computed tomography (CT) data and the resultant development of three dimensional (3-D) anatomical models support the realistic representation of lung geometry. Yet, the selection of different modelling approaches to analyze the transitional flow behavior and the use of different inlet and outlet conditions provide a dissimilar prediction of particle deposition in the human lung. Moreover, incorporation of relevant physical and appropriate boundary conditions are important factors to consider for the more accurate prediction of transitional flow and particle transport in human lung. This review critically appraises currently available literature on airflow and particle transport mechanism in the lungs, as well as numerical simulations with the aim to explore processes involved. Numerical studies found that both the Euler–Lagrange (E-L) and Euler–Euler methods do not influence nanoparticle (particle diameter ≤50 nm) deposition patterns at a flow rate ≤25 L/min. Furthermore, numerical studies demonstrated that turbulence dispersion does not significantly affect nanoparticle deposition patterns. This critical review aims to develop the field and increase the state-of-the-art in human lung modelling.

The objective quantification of three-dimensional kinematics during different functional and occupational tasks is now more in demand than ever. The introduction of new generation of low-cost passive motion capture systems from a number of manufacturers has made this technology accessible for teaching, clinical practice and in small/medium industry. Despite the attractive nature of these systems, their accuracy remains unproved in independent tests. We assessed static linear accuracy, dynamic linear accuracy and compared gait kinematics from a Vicon MX-f20 system to a Natural Point OptiTrack system. In all experiments data were sampled simultaneously. We identified both systems perform excellently in linear accuracy tests with absolute errors not exceeding 1%. In gait data there was again strong agreement between the two systems in sagittal and coronal plane kinematics. Transverse plane kinematics differed by up to 3° at the knee and hip, which we attributed to the impact of soft tissue artifact accelerations on the data. We suggest that low-cost systems are comparably accurate to their high-end competitors and offer a platform with accuracy acceptable in research for laboratories with a limited budget.

Occupational exposure limits for respirable coal dust are based on exposure during working hours, but coal miners may experience additional community-based exposures during nonworking hours. We analyzed Australia National Pollutant Inventory (NPI) data for the years 2008–2018 to estimate air pollutants (metals, nitrogen oxides, particulate matter ≤ 10 micrometers (PM10) and ≤2.5 micrometers (PM2.5)) originating from coal mines. PM10 levels from community-based air monitors in Queensland and New South Wales were also compared between mining and nonmining communities. Results indicated that tons of coal mined increased over the study period, and that levels of particulate matter, metals, and nitrogen oxides increased significantly over time as well. Coal mines accounted for 42.1% of national PM10 air emissions from NPI sites. PM2.5 from coal mines accounted for 19.5% of the national total, metals for 12.1%, and nitrogen oxides for 10.1%. Coal mining occurred in 57 different post codes; the 20 coal-mining post codes with the highest PM10 emissions were home to 160,037 people. Emissions of all studied pollutants were significantly higher from coal mining sites than from other types of NPI sites. Results from community-based air monitoring stations indicated significantly higher population PM10 exposure in coal mining communities than in nonmining communities. The health of the public at large is impacted by coal mining, but to the extent that miners also live near coal mining operations, their total exposure is underestimated by consideration of exposure only during working hours.