Journal of Aerosol Science最新文献

The exposure to air fine aerosols can cause health effects due to inhalations of alpha emitters such as ²²²Rn daughters. Lead-210 and ²¹⁰Po are mainly associated to aerosols with median aerodynamic diameter lower than 1 μm. The ²¹⁰Po is characterized by having a high radiotoxicity. The precise measurement of ²¹⁰Po in surface air aerosols is usually quite complex due to the significant contribution of the ²¹⁰Pb on their concentrations. Additionally, there is no possible means to manufacture a certified material to validate the measurements of ²¹⁰Pb and ²¹⁰Po concentrations in surface air aerosols. For these reasons, this study aims to develop a novel and comprehensive methodology to validate ²¹⁰Po measurements in surface air aerosols by preparing in our laboratory “standard samples” with known activities of both ²¹⁰Pb and ²¹⁰Po. A detailed sensitivity analysis on the precision of ²¹⁰Po concentration measurements has been carried out as a function of the involved variables such as sampling time, time elapsed between the sampling start and ²¹⁰Po self-deposition and the ²¹⁰Po/²¹⁰Pb activity ratio in surface air aerosols. This study is necessary to find the optimum conditions for a precise measurement of ²¹⁰Po in surface air aerosols. In addition, this methodology has been applied for the determination of ²¹⁰Po concentrations in 30 samplings campaigns of atmospheric aerosols carried out at the El Carmen campus (Huelva province) from March 25th to July 15th, 2022. The results obtained for ²¹⁰Pb and ²¹⁰Po concentrations and atmospheric aerosol residence times (via ²¹⁰Po/²¹⁰Pb activity ratio) were consistent with other previous works.

Bioaerosol generation, sampling, and cultivation-independent quantification of pathogenic bacteria play a crucial role in studying dose-response effects of Legionella pneumophila. Here, the Next Generation Impactor (NGI), initially created for pharmaceutical inhaling studies, was assessed for its potential to sample airborne bioaerosols and to separate size-dependent wet droplets by incrementally increasing the airflow speed. This stainless-steel sampler was shown in this study to be suitable for sampling prior to cultivation-independent analysis of pathogen-containing bioaerosols using washable cups. The applicability was studied by quantifying the total and intact cell count of L. pneumophila by flow cytometry after being dispersed into a droplet aerosol. Our results demonstrate a high total sampling efficiency of 95.5% ± 11.8% despite a lower biological sampling efficiency of 59.7% ± 16.5% for dry aerosols. However, by elevating the relative humidity (RH) to 100% in a liquid aerosolization unit, the biological sampling efficiency increased to over 90% for L. pneumophila. More than 50% of the cells were found in stage 1 using the liquid aerosolization unit. In comparison, 80% of the cells were sampled in stages 4–6 at 30% RH. Specifically, while at 100% RH, the droplet size mattered, at 30% RH, the size distribution of dry particles, in this case L. pneumophila, was relevant due to evaporation processes, which explains the size differences. These findings indicate the potential of the NGI for further exploration and application in studying other aerosol-borne pathogens, especially concerning the size distribution of wet droplets, viability, or effect-based bioanalysis.

Livestock farms are hotspots of antibiotic resistance due to the intensive use of antibiotics, in which the characteristics of air-borne and feces-borne antibiotic resistance genes (ARGs) and microbial communities are of great significance. This study delves into the distribution of ARGs and microbial communities across various livestock farms in China, and the correlation of microorganisms between livestock farms and other global environments was investigated. The concentrations of ARGs and mobile genetic elements (MGEs) in air samples were basically at the same level, but those in fecal samples collected from chicken farms were universally higher than those in pig and cattle farms. There was significant ability of ARGs to spread easily among different bacteria in all samples in livestock farms. Additionally, there may be more possible host bacteria of airborne ARGs in chicken farms. In the global-scale analysis of highly similar microbial communities, the database matching with the highest number of similarities to microbial communities collected from livestock farms is genes related to human sources (54.8%). This study advances our understanding of ARG dynamics in different livestock farms and contributes to the development of sustainable livestock management practices.

This study investigates the effects of beverage consumption on droplet production during coughing and speaking. Interferometric Mie imaging (IMI) measures particle size using the diffraction characteristics of light and was used to examine the particle size distribution and particle count concentration of exhaled droplets without water (WW), with still water (SW), and with carbonated water (CW). The parameters of the IMI technique were calibrated using glass beads and respiratory droplets were measured for 16 subjects, which showed that drinking beverages had a significant impact on the particle size distribution during coughing and speaking. Another important aspect of this study was the variability in particle emissions among individuals. The results showed that the consumption of SW and CW led to a significant increase in total particle count concentrations in the coughing condition when compared with WW, with no significant difference among beverage type. Individuals with relatively high particle emissions WW showed more particle generation when consuming SW and CW. When speaking, SW ingestion significantly increased the total particle count concentrations when compared with the WW condition, whereas CW consumption did not increase the total particle count concentrations to the same extent as that in the SW condition. These results emphasize that the consumption of beverages such as SW and CW have the potential to significantly increase particle production during respiratory activities, amplifying the potential risks associated with infection transmission.

Accurate measurements of cloud condensation nuclei (CCN) activity and hygroscopicity of black carbon (BC)-containing particles are particularly important because of the positive climate forcing from these particles. Such measurements are typically conducted on particles selected by a Differential Mobility Analyzer (DMA), which in addition to singly charged particles transmits multiply charged larger particles that have the same electrical mobility. These larger particles activate at lower supersaturations than the singly charged particles, biasing measurements and resulting in overestimation of CCN activity and hygroscopicity parameter (κ). Here, we measure the CCN activity and determine κ for different BC surrogates with electrical mobility diameters from 100 to 200 nm selected 1) only by electrical mobility with a DMA, and 2) by both electrical mobility and mass using a DMA and a Centrifugal Particle Mass Analyzer (CPMA), thus allowing selection of only singly charged particles. We demonstrate the use of the DMA-CPMA system in resolving biases caused by multiply charged particles, and we show that the effect of multiple charging on the CCN activity of the BC particles is strongly influenced by morphology dispersion, i.e., the variability due to the range of morphologies of particles that have the same electrical mobility and mass. Our findings show that electrical mobility-based methods alone are unlikely to lead to accurate results in measurements of CCN activation and hygroscopicity of BC particles, even for those with a more compact morphology.

Building activities commonly generate substantial amounts of construction dust, adversely affecting the nearby environment and public health. Construction workers, in particular, face significant health hazards due to their prolonged exposure to elevated levels of this dust. Traditional method of monitoring individual exposure to construction dust, such as gravimetric samplers or high-end analytical instruments, are often expensive, cumbersome, and not suitable for real-time, widespread deployment. This study employs the low-cost sensors (PMS A003-G10) to measure dust concentrations in varied environments: first low, then high, and then once again low concentrations. In the first low-concentration environment, the G10 sensors showed strong correlation (R² > 0.81) and acceptable error (RMSE<13.6 μg/m³). However, in high-concentration environment, the G10 sensor faced range limitation issues, yet maintained good correlation. Post high-concentration exposure, the G10 sensor exhibited increased NRMSE and MAPE, indicating adverse impacts on its measurement capability. To enhance the G10's performance in high concentrations, temperature and humidity were used as calibration factors. Four machine learning algorithms (MLR, RF, KNN, and XGBoost) were compared, with XGBoost demonstrating superior calibration (R² > 0.96, RMSE<117.1 μg/m³). The model's generalizability was validated by integrating data from both low and high-concentration environments into the XGBoost training. Subsequent application to the second low-concentration dataset post high-concentration exposure assessed the model's generalizability and applicability. This study demonstrates that with appropriate calibration, low-cost sensors can effectively monitor individual exposure to construction dust across diverse concentration levels.

Constant monitoring of indoor microbial contamination is crucial due to its direct impact on individuals' health through the inhalation of bioaerosols. This study assessed the bioaerosol content of outlet air from evaporative cooling systems (ECS) and air conditioning splits (ACS) at the Qom School of Health under various operating conditions. The microbial load (CFU m⁻³) was analyzed using the Andersen method, employing separate media cultures for bacteria and fungi. Fungal species and density were determined through staining with Lactophenol cotton blue and microscopic observation. The average fungal load in ECS outlet air (54.56 CFU m⁻³) significantly exceeded the bacterial load (20.30 CFU m⁻³) (p-value <0.01). Increased ECS fan speed correlated with a higher bacterial load, while high salinity and total dissolved solids (TDS) in ECS water reduced microbial growth. Changes to wetted screens increased the microbial load. Aspergillus versicolor and Aspergillus Niger were the prevalent fungal species in ECS, with higher fan speeds associated with increased fungal load. An elevation in ACS temperature significantly reduced the bacterial load in outlet air. Cladosporium and Aspergillus species dominated fungal density in ACS. A comparison between coolers indicated a higher bacterial load in ACS and a higher fungal load in ECS. Washing internal filters reduced the cumulative annual risk of disease according to quantitative microbial risk assessment (QMRA). Given the considerable time spent indoors, indoor contamination poses significant health risks, necessitating continuous monitoring of indoor microbial loads.

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.