Journal of Aerosol Science最新文献

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).

Radiological dispersal devices (RDDs) have a potential to disperse radioactive aerosols into the atmosphere through explosions. Accurately estimating the respirable fraction of these aerosols through experiments presents a considerable challenge. Also, the modeling of aerosol particle evolution stemming from an RDD explosion is inherently complex, involving the interplay of various physical processes operating at different time scales. In this study, we propose a comprehensive numerical model to estimate the respirable fraction of aerosols generated during RDD explosions, integrating the thermodynamic properties of detonation products with microphysical aerosol processes. The model assumes particles are spherical and ignores charge effects. It is also assumed that the thermodynamic properties of the cloud are uniform within its volume and that thermal equilibrium exists between particles and the surrounding medium. Numerical simulations are conducted for diverse experimental scenarios, and performance of the model is assessed by comparing its predictions with experimental data pertaining to Carbon and Cobalt particles. Notably, the model predicts the average particle diameter of Carbon particles within the detonation front of TNT at 13.8 nm, closely matching the experimental observation of 13 nm (Rubtsov et al., 2019). Additionally, the model captures the peak value of the cobalt particle mass fraction distribution, approximating it to be around $0.7\mu m$, in agreement with experimental findings (Di Lemma et al., 2016). These findings indicate that the proposed model is capable of predicting the behavior of both radioactive and non-radioactive aerosols. Also, this study underscores the potential of modeling approaches in addressing existing knowledge gaps related to RDDs, thereby contributing to enhanced impact assessment and management strategies for incidents involving RDDs.

In this work, the oxide nanopowders of Al₂O₃, ZrO₂, Y₂O₃, Gd₂O₃, CeO₂, and SiO₂ were synthesized by CW CO₂ laser vaporization technique with controlled gas condensation in an inert atmosphere. Methods for controlling the size of the resulting nanoparticles by adjusting the gas composition and pressure during the vaporization process have been demonstrated. The potential for producing ultrasmall oxide nanoparticles with dimensions less than 5 nm has been shown. The size distribution of nanoparticles taken from different parts of the evaporation-condensation tract was studied using scanning (SEM) and transmission (TEM) electron microscopy methods. The effect of synthesis conditions (pressure and composition of the inert gas) on characteristics of the nanoparticles is discussed. Using a wide class of simple oxides as the example, it is shown that the powders synthesized by the laser method consist of three types of particles: target spherical particles with a diameter of 3–20 nm (more than 98%), larger spherical particles with a diameter of 50–200 nm, and shapeless large particles with sizes more than 200 nm. The possibility of separating large particles from the main particles using the original labyrinth system for gas pumping is shown. The obtained particles with controlled sizes can be effectively used in various applications, in particular, for the preparation of catalysts and adsorbents.

A light-emitting-diode (LED) based optical technique is developed to measure the surface area per unit volume of particles in aerosols and liquid sprays. The technique uses path-integrated measurements of transmittance, T, from two angles to produce a tomographic reconstruction of the local extinction coefficients, K, in the region of interest, using the Beer-Lambert law and a deconvolution algorithm. When the particles in the flow have sufficiently large diameters (existing in the Mie scattering regime), these extinction coefficients can be related to the surface area per unit volume of the particles. The technique has the potential to be applied to a wide range of two-phase flows. In the present study, it is applied to flows through a pharmaceutical inhaler device, where two powders with different particle size distributions are considered.