Journal of Aerosol Science最新文献

Airborne pathogens are typically associated with particles, and the transport behavior of these particles is largely driven by their size. To better understand airborne transmission of viral diseases and develop effective control measures, proper size characterization of virus-laden particles is essential. The Andersen cascade impactor (ACI) is an 8-stage air sampler that separates aerosol particles into 9 aerodynamic size fractions. During sampling with an ACI under certain conditions, particles may bounce upon impact with the collection plates of the ACI, leading to eventual deposition on a stage further downstream than their target stage. Coating collection plates with adhesive materials may help decrease particle bounce; however, it may also affect the viability of collected pathogens. In this study, we evaluated different materials for their ability to minimize particle bounce while conserving virus viability during the collection of viral aerosol particles with an ACI. We evaluated nine materials - Tween® 80, silicone oil, Span® 85, Brij® 35, glycerol, mineral oil, gelatin, bovine serum albumin, and virus growth media - on their effect to inactivate H1N1 influenza virus and bovine coronavirus, a surrogate of SARS-CoV-2. Plates coated with gelatin, silicone oil, and mineral oil resulted in the least reduction of viability for both viruses. These materials were then used to sample viral aerosol particles in a wind tunnel. Results of physical particle collection, viral load and viral viability from the various ACI stages revealed no significant differences in aerodynamic size distribution between coated and uncoated plates, and the size distribution was similar to that reported by an optical particle sizer. Overall, our results did not support the need to coat ACI collection plates when characterizing viral aerosol particles under the conditions of this study. However, we did identify potential coating materials which could conserve virus viability maximally, if particle bounce is of concern.

Modeling pulmonary drug delivery in the airway using computational fluid dynamics (CFD) simulations tracks drug particles throughout the airway, providing valuable information on the deposition location of inhaled drugs. However, most studies simulate particle transport within static airway models that do not incorporate physiological airway motion; this choice limits accuracy since airway motion directly affects particle transport and deposition, notably in newborns with airway abnormalities such as tracheomalacia. The objective of this study is to determine the effect of airway motion on drug delivery in neonates with and without airway disease. For this study, two control subjects without any airway disease and three subjects with tracheomalacia (dynamic tracheal narrowing) were enrolled. Each subject was imaged at approximately 40-weeks post-menstrual age using magnetic resonance imaging (MRI). MRI data were retrospectively reconstructed to obtain static airway images gated to different time points of the breath (i.e., end expiration and end inspiration) and an image representing combined data from all timepoints (ungated). Virtual airway surfaces (pharynx to main bronchi) were made from each MR image. A moving airway surface was created from surface registration of these surfaces and used as the boundary for a CFD simulation of one inhalation, along with subject-specific inspiratory flow waveforms. To assess the effect of airway wall motion on particle deposition, static-walled simulations, based on the airway surfaces at end inspiration, end expiration, and the ungated airway surface, were also performed using the same flow boundary conditions. Particle transport (particles diameter range 0.5–15 μm) was compared between the simulations during the inhalation. Airway surface motion affected particle transport into the small airways by 65% on average (0.5–5 μm– 22%, 5-15 μm– 86%) compared to static-walled simulations, while comparison between static end expiration and other static-walled simulations using geometries acquired during different phases of breathing differed by more than 500% on average (0.5–5 μm– 45%, 5-15 μm– 741%). For particle deposition, airway surface motion affected by 43% on average (0.5–5 μm– 86%, 5-15 μm– 21%) compared to static-walled simulations and comparison between static end expiration and other static-walled simulations differed by 47% on average (0.5–5 μm– 58%, 5-15 μm– 41%). Differences between dynamic and static deposition results and between static simulations from different timepoints occurred in patients with and without airway disease. This study suggests the importance of using airway wall motion in CFD simulations to model aerosolized drug delivery in the airway. If a CFD simulation is limited to only a static airway image without physiological motion, particle deposition mapping may yield markedly inaccurate results, potentially resulting in higher or lower drug dosing than intended.

Trace measurement of aerosol chemical composition in workplace atmospheres requires the development of high-throughput aerosol collectors that are compact, hand-portable, and can be operated using personal pumps. We describe the design and characterization of a compact, high flow, Turbulent-mixing Condensation Aerosol-in-Liquid Concentrator (TCALC) that allows direct collection of aerosols as liquid suspensions, for off-line chemical, biological, or microscopy analysis. The TCALC unit, measuring approximately 12 × 16 × 18 cm, operates at an aerosol sample flowrate of up to 10 L min⁻¹, using rapid mixing of a hot flow saturated with water vapor and a cold aerosol sample flow, thereby promoting condensational growth of aerosol particles. We investigated the effect of operating parameters such as vapor temperature, growth tube wall temperature, and aerosol sample flowrate, along with the effect of particle diameter, inlet humidity, aerosol concentration, and operation time on TCALC performance. Nanoparticles with an initial aerodynamic diameter ≥25 nm could grow to droplet diameters >1400 nm with an efficiency ≥80%. Good droplet growth efficiency was achieved for sampled aerosol relative humidity ≥9%. We measured complete aerosol collection for concentrations of ≤3 × 10⁵ cm⁻³. The results showed good agreement between the particulate mass collected through the liquid collector and direct filter collection. The TCALC eliminates the need for sample preparation and filter digestion during chemical analysis, thereby increasing sample recovery and substantially improving the limit of detection and sensitivity of off-line trace analysis of collected liquid samples.

Combustion-generated carbon nanoparticles exhibit a variety of optical and physicochemical properties. Therefore, when applying laser diagnostic tools for monitoring purpose, it is important to consider the different response of the particles with varying properties as well as the impact of laser irradiation on these properties. In this work, we analyze the possible modification of particle optical and physicochemical properties by coupling extinction measurements with FT-IR and Raman spectroscopy. The aim is to retrieve optical, chemical, and structural properties of the particles under analysis. To our knowledge, the approach proposed in this work has not yet been performed on irradiated particles. Particles are sampled from a premixed flame at two heights above the burner, representing two different aging stages. While extinction measurements are carried out in-flow, FT-IR and Raman spectroscopy are performed on particles collected for ex-situ analysis. Moreover, the analysis is conducted on both pristine and irradiated nanoparticles with one and ten laser shots. While nascent particles do not exhibit relevant modification under laser irradiation, heating mature particles with one or more laser pulses of relatively high energy density is observed to significantly affect absorption properties, particle structures and specific surface functionalities. The presence of oxygenated species in mature particles and in particular the structures spectroscopically correlated with graphene oxide indicates that specific chemical reaction pathways can occur under laser irradiation, likely promoted in the ambient condition under analysis.

The sintering mechanisms and temperature dependence of coalescence of colliding cubic boron nitride (c-BN) nanoparticles are investigated using classical molecular dynamics (MD) simulation. Particle-particle collisions of 2.55-nm octahedral c-BN nanoparticles, consisting solely of the most stable {111} facets, with half of the surface terminations being boron and the other half nitrogen, are analyzed statistically and evaluated to assess the initial temperature range (2500 K – 3100 K) for sintering and its effect on grain growth. At these temperatures, the collision process maximizes contact surface area through interfacial sliding, thereby minimizing free energy and accommodating dangling bonds. Moreover, the exothermic formation of bonds of the coalescing nanoparticles increases the temperature. The alignment of the {111} orientation of the two collided nanoparticles occurs at a temperature slightly above the melting point, and rapid grain growth happens when the temperature is a few hundred degrees higher than that. However, phase separation also takes place at the corners away from the collision plane of the merging nanoparticles. Between 3100 K and 3250 K, crystalline alignment occurs, which aids the sintering process and allows for the formation of a well-structured nanocluster. However, above 3300 K, phase separation dominates and drives the melting of the entire sintered nanocluster.

Requirements on cabin air quality are constantly increasing. The objective is to protect the passengers from ultrafine particles and harmful gases, particularly in small volumes such as car cabins, where pollution is more concentrated in absence of any filtration strategy. It is necessary to extend the single filter approach and combine it with advanced filtration technologies (high separation efficiency), and thus create an effective multistage filtration system. The investigation work is built around a holistic approach. A complete 1D-simulation model has been calibrated with experimental results from a dedicated test rig and an electric vehicle. The results showed a significant improvement of particle level in the cabin with the advanced filtration system. Additionally, an appropriate ventilation strategy has been implemented to deal with the air entering the cabin by other means than the blower operation. This “infiltration”, triggered by vehicle speed, allows pollution to enter the cabin without any filtration stage.

While there has been considerable investigation into the deposition of inhaled aerosols in the airways of adults, less is known about where aerosols deposit in the lungs of children. Clinical investigation into aerosol deposition in children is complicated by ethical concerns surrounding ionizing radiation studies in children. To meet the need for non-clinical methods of estimating regional deposition in pediatric airways, multiple in silico models were developed to represent the lungs of girls and boys aged 6, 8, 10 and 12 years. The models were symmetric and used a single-path deterministic approach to calculate aerosol deposition in the airways. Regional deposition estimates were provided for children using a fixed set of controlled breathing patterns before characterizing regional deposition during typical tidal breathing in each age group. Deposition patterns were found to be strongly influenced by inhalation flow rate and aerodynamic particle size. Differences between boys and girls in the fraction of inhaled aerosol depositing were minimal during fixed breathing patterns, with higher deposition in all regions of the younger age groups. However, when breathing patterns were adjusted to represent typical tidal breathing in each age group, age differences in the regional fraction of particles depositing became negligible. Moreover, peak deposition fractions in both the conducting and peripheral airways occurred within a narrow range of aerodynamic particle diameters between 2.4 and 2.6 μm, a smaller size range than for adults. During exposure over a fixed period of time, age-related differences in minute ventilation resulted in a larger aerosol dose depositing in the intrathoracic airways of older children. Such differences suggest that to achieve comparative dosing in this age range, older children should inhale aerosols for a shorter time. These findings provide an improved understanding of regional deposition in pediatric airways and will assist in optimizing regional drug delivery to children.

Low-cost sensor networks (LCSNs) are expanding worldwide to gather high spatiotemporal resolution data due to their economic feasibility and compact size. The reliability of LCS-recorded data is limited due to their calibration dependencies in the field. Previous studies have focused on the development of LCS calibration models by co-location with the regulatory monitoring stations. However, it is challenging to calibrate LCS in the field for countries with limited infrastructure for air quality monitoring, pointing towards the need for transferable calibration models. Only a few studies have addressed this challenge and provide no information on the factors that may affect the performance of transferable calibration models. Here, we examined the spatial transferability of the calibration models developed using machine learning (ML) algorithms for an LCSN with twenty-two (22) sites in NCT-Delhi. The site-specific calibration models performed well at each site with high R² and significantly low RMSE values. These models were transferred to the other sites, and the effect of distance between the sites (D), source composition, PM ratios, and particle size distribution (PSD) on the transferability of calibration models was investigated. The models developed at the Mundka (S10) and Punjabi Bagh (S16) sites complied with the evaluation criterion (R² ≥ 0.70) for each site, irrespective of the distance between the sites. Furthermore, PM ratios reported by the LCSs did not significantly differ across sites, suggesting that the PMS algorithm provides a proxy of the size-resolved mass fractions. Evaluation of the PSD at different sites supported our findings. We also introduced the concept of selecting representative locations for LCS co-location by computing transferability scores using k-means clustering and presented a reference map for NCT-Delhi for developing scalable calibration models.

Effective pulmonary drug delivery through pressurized-metered dose inhalers (pMDIs) depends on accurately targeting pharmaceutical aerosols to specific lung areas. Achieving this necessitates a comprehensive understanding of airflow dynamics in the airway and particle transport mechanisms.

In this study, a replica of the realistic geometry of the VCU medium-sized mouth-throat (MT) airway was fabricated by rapid prototyping (3D printing) to connect to a next-generation impactor (NGI) setup. The drug concentration deposited in the replica was measured at a constant flow rate of 30 L/min and room temperature using a high-performance liquid chromatography (HPLC) assay. This measurement validated our computational fluid dynamics (CFD) model for simulating particle transport under the same conditions. Large eddy simulation (LES) and discrete phase model (DPM) were employed to model the MT's airflow and particle transport. Using our CFD modeling, we focused on the effects of the temperature distribution of aerosol injection (plume), the influence of inlet air temperature, and the presence of the mucus layer on particle transport and deposition.

Our findings revealed that decreasing the plume temperature from 10 °C to −54 °C reduced deposition by approximately 15%, although increasing the average deposited particle sizes within the MT by about 34.5%. The airflow pattern, affected by different plume temperatures, was the prevalent parameter in particle MT deposition. In contrast, the effect of different air inlet temperatures on deposition was negligible. Additionally, incorporating mucus layer features in CFD modelling could further modify the inhaler's efficiency by up to 11%, depending on the specific conditions like diverse plume temperature (−54 °C–10 °C) and airflow temperature conditions (−15 °C–45 °C).