Aerosol Behavior Research Articles

Effect of lubricants type and particle size on the rheological properties and aerosolization behavior of dry powder inhalers

A commonly used strategy to improve aerosolization behavior of carrier-based dry powder inhalers (DPIs) is the addition of magnesium stearate as a lubricant, yet it may also negatively affect properties of DPIs. Thus, the aim of this study was to find lubricants that could be used as alternatives of magnesium stearate and meanwhile verify the applicability of using powder rheological properties to predict the performance of different lubricants in DPIs. Here, using fluticasone propionate as a model drug, LH200 as the carrier, influence of lubricants type and particle size, including magnesium stearate, sodium stearate, Leucine, sodium stearate fumarate, Compritol® 888 ATO, and Compritol® HD5 ATO, on the physicochemical properties, powder rheology and aerosolization behavior of the DPI formulations was characterized. Further, the relationship between powder rheological parameters and in-vitro drug deposition parameter, fine particle fraction (FPF), were explored, and the contribution of powder flowability and adhesion was evaluated using principal component analysis (PCA). The results showed that magnesium stearate, sodium stearate and smaller sized leucine significantly reduced the basic flowability energy, aeration energy and Permeability of the DPI formulations, leading to improved aerosolization behavior. A robust linear correlation was established between rheological parameters and FPF. PCA showed that in lubricants containing formulations, the contribution of flowability (74.69%) was greater than that of adhesion (25.31%). In conclusion, sodium stearate and smaller particle size Leucine can be considered as substitutes of magnesium stearate in DPI formulations.

Antibiotic resistance and resistome risks of inhalable bioaerosols at aeration tank of a full-scale wastewater treatment plant

Antibiotic resistome could be aerosolized under wastewater aeration processes, however, their seasonal variation, mobility, hosts, aerosolization behavior, and risk, are largely unknown. Herein, the antibiotic resistant pollution associated with fine particulate matter (PM2.5) from the actual aeration tank (AerT), was analyzed using metagenomic assembly. The antibiotic resistance of AerT-PM2.5 was characterized by significant seasonality. Antibiotic resistance genes (ARGs) in AerT-PM2.5, exhibited higher enrichment and mobility and were harbored more by pathogens than those in upwind-PM2.5, regardless of sampling season. Mobile ARGs were mainly flanked by transposase. Totally, 18 pathogenic antibiotic-resistant bacteria (PARB) carried more than one ARG, including 9 PARB with multiple ARG types. Although wastewater exerted a dominant source contribution for the airborne ARGs (47.31–55.56 %) and PARB (46.18–64.32 %), aeration endowed differential aerosolization capacity for various ARGs and PARB from wastewater. Airborne antibiotic resistome was mainly determined by bacterial community and indirectly influenced by meteorological conditions (i.e., relative humidity). Higher PM2.5-borne resistome risk was observed in AerT than upwind, and the most serious resistome risk of AerT-PM2.5 was found in winter. This study emphasizes the importance of wastewater aeration processes in emission of airborne antibiotic resistome and offers referenced information for mitigating air pollution in wastewater treatment plants.

Insights into bioaerosol contamination in the process of mineralized refuse mining: Microbial aerosolization behavior and potential pathogenicity

The landfill mining process is a main source of anthropogenic bioaerosol release, posing potential risks to the health of occupationally exposed personnel and nearby residents. In this study, microbial aerosolization behavior and potential pathogenicity during the landfill mining process were systematically investigated. The highest concentration of bacterial aerosols was measured in the refuse mining area, with a value of 5968 ± 1608 CFU/m3, while the highest concentration of fungal aerosols was 1196 ± 370 CFU/m3 in the refuse screening area. The bacterial and fungal aerosols were distributed primarily in the particle size ranges of 4.7–7.0 µm and > 7.0 µm, respectively. The pathogenic microbes Arthrobacter, Bacillus, Arthrobotrys and Aspergillus had high bioaerosol aerosolization capacities, with aerosolization indices of 100–329, 31–62, 2–14 and 1–11, respectively, when released from mineralized refuse. There are more than 100 types of pathogenic bacteria in bioaerosols. The microorganisms Lysobacter, Luteimonas and Mycolicibacterium, which carry virulence factor genes (VFGs) (pilG, Rv0440, pilT, etc.), can spread VFGs, aggravate bioaerosol pollution, and threaten the health of workers and nearby residents. This research will help further the understanding of bioaerosol contamination behaviors and potential pathogenicity risks from landfill mining activities.

Lognormal mode dissociation method based on intrinsic characteristics of aerosol size distribution

Aerosols significantly affect the transmission of optical signals in the atmosphere, necessitating accurate atmospheric models for the performance evaluation of electro-optic devices. Aerosol size distribution is a critical parameter in these models, and the lognormal function is commonly used to mathematically represent it. This study aims to handle the lack of a solid criterion for determining the number of lognormal modes and introduces an improved scheme that leverages the characteristics of the second derivative (SD) of the Gaussian curve to identify the mode amount and to initialize mode parameters for fitting. The optimization problem is solved using a genetic algorithm, incorporating a goodness-of-fit index to determine the presence of spurious modes. For aerosol size distributions characterized by a single Gaussian peak, mode parameters such as mode radius and width can be straightforwardly identified through the positions of peaks and roots on the SD curve. However, the original mode dissociation method may overlook potential modes in distributions composed of superimposed Gaussian peaks. Numerical tests indicate that such oversights can result in substantial errors in calculating the aerosol extinction coefficient, with relative errors exceeding 100%. The proposed scheme significantly enhances the accuracy of mode dissociation in aerosol size distribution, reducing errors in aerosol extinction coefficient calculations by approximately 40% when applied to data from the Aerosol Robotic Network (AERONET). An additional benefit of this method is its ability to constrain the number of lognormal modes in an aerosol size distribution. Results from applying this scheme to data from selected AERONET sites reveal that over half of the size distributions consist of more than two lognormal modes, highlighting the effectiveness of the proposed approach in capturing complex aerosol behaviors.

Optimizing indoor air models through k-means clustering of nanoparticle size distribution data

Sectional physics-based aerosol models imply a computational effort that hinders their use in building digital twins, real-time predictive control, and computer-based iterative optimization versus black-box approaches. The innovation of this paper lies in the proposal of a novel systematic methodology to optimize the number of size bins in sectional reduced-order models for particle concentration simulations. This allows its application in indoor air quality management and overcomes generalizability and data-dependency issues of black-box models. This method, based on k-means clustering, aims to ensure precision when tackling relatively fast fine and ultrafine particle simulations targeting the reduction of time and resource consumption from experimentally-determined aerosol size distribution time series. Consequently, three tests were carried out using combustion aerosols inside a custom-designed emission chamber to simulate emission hotspots in non-commercial and occupational settings. 2-, 3-, 4-, and 5-cluster classifications were evaluated for data coming from 13 particle size bins through silhouette analysis and the study of their temporal profiles. Results show that the 4-cluster classification summarizes the behavior of data in the 10–420 nm range, ensuing up to a 77 % improvement in the model's computational demand. Moreover, this method allows an accurate definition of the necessary size ranges to calculate nanoparticle concentrations inside the chamber and facilitates the interpretation of aerosol behavior and processes through the resulting clusters' temporal profiles.

A comprehensive study on the validation and application of multi-lognormal distribution models for atmospheric particles

The particle number size distribution (PNSD) is crucial for evaluating air quality and mitigating environmental pollution, as particles of different sizes have diverse effects on human health and climate. However, obtaining a comprehensive understanding of PNSD is challenging due to its inherent complexities and variability. Multi-lognormal distribution models are employed to fit PNSD, as seen in climate models, but discrepancies between model fits and observed PNSD persist. This study adopts hourly data from 2017 to 2020 across eight monitoring sites in diverse environments—rural, urban, mountainous, and polar, and compares the observed PNDS with those simulated by multi-lognormal distribution models. The results demonstrated that the model generally achieved a high correlation with observed PNSD data (r2 > 0.75), effectively capturing key characteristics of nucleation and Aitken mode particles. However, the model had a tendency to overestimate the total number concentration by approximately 1.09 times, particularly noticeable under conditions of high concentrations of smaller particles. The model successfully represented prevalent bimodal size distribution patterns in urban areas with high ultrafine particle concentrations, though its performance was slightly less accurate in scenarios involving trimodal distributions. Despite these strong correlations and the model's ability to reflect diurnal and seasonal variations, which suggests its broad applicability and utility, there were notable limitations on smaller time scales and in specific particle size ranges. These limitations were particularly evident in capturing detailed phenomena relevant to new particle formation events, indicating areas where model refinement is necessary. The results highlighted the importance of investigating discrepancies between model predictions and actual observations, which is crucial for refining climate models that utilize PNDS. The uniform comparison facilitated a detailed exploration of particle properties from model results, offering deeper insights into aerosol behavior and its environmental impacts.

The diurnal variation of dust and water ice aerosol optical depth at Jezero crater observed by MEDA/TIRS over a full Martian year

The Thermal InfraRed Sensor (TIRS) on the Perseverance rover has provided nearly two full Mars years of systematic monitoring of the total aerosol optical depth above Jezero Crater. These observations span a wide range of timescales, capturing seasonal patterns, diurnal variations, and minute-to-minute fluctuations in aerosol loading. By combining TIRS retrievals with orbital observations, the relative contributions of dust and water ice aerosols can be estimated, revealing their different seasonal and diurnal behaviors. The TIRS record shows distinct periods of dust storm activity, including strong regional storms during the perihelion season as well as short-lived but intense dust events outside the typical dust storm season. Water ice clouds exhibit pronounced seasonal and diurnal variability, with peak activity occurring during the aphelion season but with a presence throughout the year. The diurnal variation of clouds differs significantly between the aphelion and perihelion seasons, with clouds persisting throughout the night during the aphelion season, while largely absent outside of specific periods after sunrise and sunset during the perihelion season. These results provide new insights into the complex behavior of aerosols at Jezero Crater and their connections to atmospheric dynamics and the Martian dust and water cycles.

Comparing the interactions between particulate matter and cloud properties over two populated cities in Texas using WRF-Chem fine-resolution modeling

Accurate modeling of aerosol-cloud interactions is essential for reliable weather and air quality simulations, given their significant impact on precipitation patterns, cloud dynamics, and aerosol distributions. This study employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to examine the impact of enhanced meteorological simulations, achieved through advanced microphysics parameterization supported by data assimilation techniques, on air quality across Texas on August 19 and 20, 2022. We tested four distinct configurations: (1) the Morrison two-moment bulk microphysics scheme, (2) Morrison's with observation nudging, (3) the Spectral Bin Microphysics (SBM), and (4) SBM with observation nudging. While the SBM scheme is known for its detailed representation of aerosol-cloud interactions, our focus was on how improvements in meteorological accuracy translate to more precise air quality simulations. Our findings demonstrated a progressive improvement in simulation accuracy, starting with the Morrison's scheme and further enhanced by adopting the SBM scheme, complemented by incorporating observation nudging. Specifically, the combination of the SBM scheme and the nudging substantially enhanced the model's ability to capture convective precipitation events, as shown by better alignment with NEXRAD radar reflectivity, with R increasing from −0.21 to 0.82, IOA from 0.10 to 0.87, and NMB decreasing from 99% to 34% in Houston. The enhanced meteorology translated into more accurate PM2.5 concentration simulations, particularly through the more accurate representation of aerosol washout during precipitation events. In Houston, the SBM scheme with nudging improved the model's PM2.5 simulations significantly, with NMB decreasing from −20% to 5% and IOA improving from 0.43 to 0.61. In San Antonio, improvements were also notable, with NMB improved from −27% to −22%, R increased from 0.48 to 0.82, and IOA increased from 0.66 to 0.86. Our results underscore the crucial role of accurate meteorological simulations in refining our understanding of aerosol behaviors in relation to precipitation patterns, directly enhancing the reliability and effectiveness of air quality modeling.

Numerical Evaluation of Aerosol Propagation in Wind Instruments Using Computational Fluid Dynamics

This paper examines aerosol propagation in wind instruments through numerical analysis, focusing on particle trajectories within five types of wind instruments: saxophone, clarinet, flute, oboe, and trumpet. Using a computational fluid dynamics approach, it is found that larger particles are deposited within the instruments, while smaller micron-sized particles predominantly exit through the bell. The impact of the instrument’s geometry on aerosol dynamics is quantified; cylindrical instruments (clarinet, flute) show an increased rate of small droplet deposition or escape through tone holes compared to conical instruments (saxophone, oboe). Instruments with steep turnings, such as the trumpet, exhibited significant particle deposition. The study suggests that deposited particles are likely to move towards re-emission points, driven by gravity and airflow, especially in straight-shaped instruments. Integrating computational fluid dynamics (CFD) as a complementary approach to traditional experimental methods provides insights into aerosol transmission mechanisms in musical settings. This methodology not only aids in understanding aerosol behavior but also supports the development of safer musical and educational environments, contributing to the field.

Polarization lidar observations of diurnal and seasonal variations in the atmospheric mixing layer above a tropical rural place gadanki, India

This study presents the daily and seasonal variation of the atmospheric mixing layer height (MLH) over Gadanki, India (13.45°N, 79.18°E), a tropical rural location based on polarization lidar observations. The observations spanned the years 2009–2014, encompassing 303 instances, and coinciding with radiosonde and surface weather station measurements. The MLH was determined through the analysis of aerosol profiles and confirmed with the MLH values derived from radiosonde data. The lidar depolarization ratio was employed to characterize aerosol shape. This study aims to establish a connection between aerosol backscatter and its shape through lidar observations, considering diurnal and seasonal variations, while also identifying the influencing factors. This study illustrates four distinct case studies conducted during different seasons to depict aerosol behavior in both convectively active and non-active periods. These case studies unveil the influence of aerosol shape on water intake and subsequent residual layer and cloud formation. The observed fluctuations in MLH and aerosol shape suggest a dynamic relationship between local meteorology and long-range aerosol transport.

Assessment of Hygroscopic Behavior of Arctic Aerosol by Contemporary Lidar and Radiosonde Observations

Assessment of Hygroscopic Behavior of Arctic Aerosol by Contemporary Lidar and Radiosonde Observations

Do ceiling fans in rooms help to reduce or disperse the transmission of breathing aerosols?

The main focus of this study is the transmission of SARS-CoV-2 through virus-laden aerosols in enclosed spaces that utilize ceiling fans. The impact of an air circulation of ceiling fans on virus transmission is not clear. Computational modeling is employed to investigate aerosol transmission within an enclosed space that features ceiling fans. The aerosol concentration is modeled using a transport equation, and the probability of infection distribution across individuals’ breathing zones is assessed. The particle removal efficiency for two ceiling fan speeds of 10 and 35 rad/s is calculated to evaluate the effect of the ceiling fan’s shear flows on the spread of breathing aerosols. The simulated breathing aerosol considers various environmental situations, including thermal gradients, thermally active surface interaction, and deformability. The results indicate that increasing the ceiling fan speed within an enclosed space causes the aerosol cloud to circulate within the room rather than exiting it. Therefore, ceiling fans may not effectively suppress breathing aerosols and could increase transmissibility. Understanding aerosol behavior is essential in reducing the risk of SARS-CoV-2 transmission in enclosed spaces.

Uncovering Effects of Mixing State on Hygroscopic Behavior of Multicomponent Aerosols with In Situ Transmission Electron Microscopy

Uncovering Effects of Mixing State on Hygroscopic Behavior of Multicomponent Aerosols with In Situ Transmission Electron Microscopy

Modeling the evolution of aerosol particles from a radiological dispersal device

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 0.7μm, 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.

Evolution of black carbon and brown carbon during summertime in Southwestern China: An assessment of control measures during the 2023 Chengdu Summer World University Games

The 31st FISU Summer World University Games (SWUG) was held in Chengdu, southwestern China, from July 22 to August 8, 2023. A series of control measures were carried out to ensure good air quality during the SWUG, providing an opportunity to investigate the atmospheric behaviors of light-absorbing aerosols under such a substantial disturbance caused by the control measures. To assess the impacts of emission controls on primary pollutants, a field campaign was conducted at a rural site in Chengdu to investigate the characterization of equivalent black carbon (eBC). The changes of eBC concentrations before, during, and after the SWUG were characterized. The sources of eBC were resolved, and the impacts of atmospheric processes on the absorption capacity were also investigated. During the SWUG, the eBC concentration decreased by 12.1 % and 25.3 % compared with those before and after the SWUG. A fossil fuel combustion (eBCff) and a biomass burning (eBCbb) originated eBC were resolved using the aethalometer model. Both eBCff and eBCbb decreased during the SWUG, indicating the effectiveness of control measures. After the SWUG, the influence of biomass burning emissions became more and more significant, and the contribution of brown carbon (BrC) to light absorption at 370–660 nm increased by 52, 19, 7, 6, and 17 % compared to those during the SWUG. As the biomass burning emitted aerosols aged, the absorption Ångström exponent and babs(BrC370nm) decreased gradually, which was mainly due to the photobleaching of the chromophores during the daytime. eBCff was mainly affected by strong wind, while high eBCbb concentration was mainly attributed to the gradual accumulation of biomass-burning emissions near the observation site. The results show the significant reduction of eBC with the implementation of the air pollution mitigation campaign, and provide insights on the impacts of atmospheric processes on BC optical properties during summertime.

Experimental study of aerosol behavior in ambient electric and magnetic fields at low indoor relative humidity

The tendency of aerosols to carry viral particles featured significantly in public discourse during the SARS Covid-19 pandemic. In this research, the potential significance of the aerosol electric charge, especially as it relates to indoor relative humidity (RH) is considered. While electrostatic interactions may occur at any level of humidity, the level of humidity has a strong influence on these interactions. Above 55 % RH, there is sufficient moisture in the air to facilitate neutralization of the electric charges of particles and surfaces, whereas, at lower humidity levels, less moisture and higher surface resistivities enable increasingly stronger electrostatic interactions. Experiments were designed and conducted to study the behavior of electrically charged aerosols in fields emanating from capacitive touchscreens and permanent magnets. These preliminary experimental results suggest that operating indoor environments closer to the 55–60 % RH range could reduce interactions between these charged aerosols and capacitive touchscreens. This relative humidity range is within the acceptable ranges of humidity recommended by ASHRAE standard 55 which defines thermal environmental conditions for human occupancy.

Numerical Analysis of Aerosol Behavior in Facemask and Optimization of Microstructure

Numerical Analysis of Aerosol Behavior in Facemask and Optimization of Microstructure

Simulating aerosol droplet dynamics and coalescence in tracheal intubation insights from a CFD-DEM analysis of PSAR tube interactions

This study employed the Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) to investigate targeted droplet delivery in tracheal intubation. Our findings reveal that droplet behavior and deposition patterns are significantly influenced by droplet size. Smaller droplets (3 μm and 5 μm) closely follow airflow, showing similar deposition patterns in both CFD-DEM and CFD-DPM simulations. In contrast, larger droplets (7.5 μm and 10 μm) demonstrate increased deposition, particularly in the bent section of the Point Source Release tube (PSAR tube), due to enhanced inertia following collisions and coalescence. The study highlights that larger droplets experience a higher frequency of coalescence, especially in curved tube sections. This leads to altered droplet size distribution at the outlet, affecting deposition in the lower respiratory tract. These insights are crucial for optimizing inhalation therapy devices, emphasizing the importance of considering droplet interactions in CFD simulations to accurately predict aerosol behavior in pulmonary drug delivery systems.

Fine excipient materials in carrier-based dry powder inhalation formulations: The interplay of particle size and concentration effects

The contributions of fine excipient materials to drug dispersibility from carrier-based dry powder inhalation (DPI) formulations are well recognized, although they are not completely understood. To improve the understanding of these contributions, we investigated the influences of the particle size of the fine excipient materials on characteristics of carrier-based DPI formulations. We studied two particle size grades of silica microspheres, with volume median diameters of 3.31 μm and 8.14 μm, as fine excipient materials. Inhalation formulations, each composed of a lactose carrier material, one of the fine excipient materials (2.5% or 15.0% w/w), and a drug (fluticasone propionate) material (1.5% w/w) were prepared. The physical microstructure, the rheological properties, the aerosolization pattern, and the aerodynamic performance of the formulations were studied. At low concentration, the large silica microspheres had a more beneficial influence on the drug dispersibility than the small silica microspheres. At high concentration, only the small silica microspheres had a beneficial influence on the drug dispersibility. The results reveal influences of fine excipient materials on mixing mechanics. At low concentration, the fine particles improved deaggregation and distribution of the drug particles over the surfaces of the carrier particles. The large silica microspheres were associated with a greater mixing energy and a greater improvement in the drug dispersibility than the small silica microspheres. At high concentration, the large silica microspheres kneaded the drug particles onto the surfaces of the carrier particles and thus impaired the drug dispersibility. As a critical attribute of fine excipient materials in carrier-based dry powder inhalation formulations, the particle size demands robust specification setting.

Real-time measurements and modeling of sodium combustion aerosol dynamics in test chamber to improve the evaluation of SFR containment aerosol behaviour

The initial size distribution and morphological parameters of sodium aerosols are critical in evaluating the accidental suspended aerosol behaviour in Sodium-cooled Fast Reactor (SFR) containment. Mass-based measurements were more familiar in characterizing the sodium aerosols. Real-time number size distribution measurements are carried out in this study. The sensitivity analysis of sodium aerosol effective density (ρe) in deriving the actual number size distributions from the measured Aerodynamic Particle Size Distributions (APSD) and predicting suspended aerosol dynamics is presented. Tests are conducted in a 1 m3 chamber at 47 ± 3% RH for different initial mass concentrations (M0) of 0.1, 1, and 2.9 g/m3. The initial APSDs measured just after the generation completions are observed to be polydisperse with the count median aerodynamic diameter (CMAD) < 1 μm. The literature reported ρe values of sodium aerosols, 2.27, 1.362, and 0.61 g/cm3 are used to derive mobility equivalent PSDs from APSD in each test. The real-time number concentration decay and size growth for four different PSDs are measured and compared with the estimate using nodal method-based code to ascertain the actual parameters. The validated parameters CMD = 0.66 μm, σg = 1.96, ρe = 1 g/cm3 and χ = 1 are used for improved estimation of sodium aerosol dynamics in Indian SFR containment with M0 = 4 g/m3 for severe accident scenarios.