Aerosol Science and Engineering最新文献

The airborne concentration of radioactive materials in radiological facilities is primarily influenced by the ventilation system, air purification system, and emission sources. Continuous Air Monitors (CAMs) are installed in these facilities to monitor the activity concentration of radioactive aerosols during both routine operations and any malfunctioning conditions. Typically, CAM placement is determined by the direction of maximum airflow. However, aerosols do not always adhere to the behaviour of airstreams, raising concerns about the suitability of CAM placement. To address this issue, this study employs software that integrates aerosol dynamics with computational fluid dynamics to calculate the CAM Placement Parameter. This parameter is derived from the peak aerosol concentration and the lag time to reach the specified CAM location, indicating the relative merit of positioning CAMs in a radiological facility under varying ventilation rates. The findings suggest that the coupled aerosol-fluid dynamics model accurately predicts the optimal placement of CAMs in workplace environments, thereby minimizing occupational exposure.

The study investigated the variation in air pollutant concentrations at different sampling points within a higher educational institution located near a coastal region and a national highway in India. From January 2023 to March 2023, air pollutants including Total Suspended Particulate Matter (TSPM), Nitrogen Dioxide (NO₂), and Sulphur Dioxide (SO₂) were sampled and analyzed using standard procedures at three distinct locations: the Main Entrance Gate (S1), Administrative Building (S2), and Sports Complex (S3) of the National Institute of Technology, Karnataka (NITK). A simple box model was employed to estimate the potential impact of emissions on atmospheric concentration. Spearman correlation coefficients were calculated to explore relationships between air pollutants and meteorological parameters. The study revealed higher concentrations of gaseous pollutants and TSPM during the winter season, with the highest levels observed at the main entrance facing National Highway 66. Various factors such as meteorological variations, construction activities, local traffic conditions, and fuel consumption were identified as potential contributors to pollutant concentration fluctuations. Car, jeep, van, and motor vehicle traffic predominated, comprising 89.96% of the observed vehicles. Notably, a significant correlation was found between NO₂ levels and temperature at the sampling sites. The investigation underscores the environmental challenges faced by educational institutions, highlighting the imperative for sustainable practices and pollution control measures within campus boundaries. This study contributes valuable insights into the complex interplay between air pollutants, meteorological factors, and human activities, emphasizing the importance of proactive environmental management strategies in educational settings.

Plasma Torch Aerosol Generation System (PTAGS) has been employed to generate nano aerosols with desirable characteristics. The operational parameters of PTAGS installed in the aerosol test facility have been optimized, and aerosols are generated using non-radioactive SrO₂ powder. The current-voltage characteristics, electro-thermal efficiency and torch power are studied as a function of the flow rate of the plasma-generating gas (mixture of argon and nitrogen) and the arc current of the plasma torch. The relation of arc characteristics is determined using the Nottingham formulation. Based on this, torch parameters evolved and optimized as 20 kW power, 70% electro-thermal efficiency, 25 L min^− 1 flow rate of plasma forming gas, 5 mg min^− 1 powder feed rate and for 4–5 min torch operation towards the generation of SrO nano aerosols to achieve 10¹² m^− 3 and ~ 25 mg m^− 3 for the count and mass concentration of aerosol respectively. The initial size distribution of the aerosols is in the few tens of nanometre range (10–40 nm) with a mean diameter of 26 nm (σ_g = 1.45). Scanning Electron Microscope and Energy dispersive X-ray analysis revealed that the morphology of nano aerosols was nearly spherical and the formation of SrO nanoparticles. A set of PTAGS operational parameters has been standardized to perform further experiments related to reactor safety analysis. PTAGS shall be tuned for aerosol generation in a large facility to achieve the characteristics equivalent to reactor accidental conditions.

One of the significant environmental concerns in urban areas is particle pollution in the air. Traffic intersections have been identified as hotspots for this problem, and it is essential to study the exposure levels of particle mass concentration (PMC), particle size distribution, and respiratory deposition doses for better understanding and control. This study monitored two high-density traffic intersections in Pune, India, for size-segregated PMC and particle number count (PNC) using the Grimm aerosol spectrometer. The study found that PMC and PNC exhibit considerable variability, with a 50–62% increase in the morning compared to the evening. The particle had an unimodal distribution with the highest PM_2.5. Mass and number-based respiratory deposited doses (RDDs) of different PM sizes in human airways were also calculated for various age groups, including infants, children, adults, and the elderly. The study found that elevated RDDs were observed for PM in the morning than in the evening, with PM₁₀ having the highest mass-based deposition doses in human airways. In contrast, PM_2.5 had the highest deposition in terms of number-based deposition. The PM₁₀ has the most significant impact on extrathoracic (ET), tracheobronchial (TB), and alveolar (AL) regions, increasing with age, with the elderly population being the most exposed, subsequently by adults, children, and infants. The findings of this investigation provide critical insights into the health risks posed by traffic-related PM pollution. Effective policies and measures must be implemented to reduce PM emissions and protect public health.

Graphical Abstract

Nitrogen oxides (NOx) in the atmosphere are significant precursors to the formation of fine particulate matter (PM_2.5) and ozone. Effectively reducing the concentration of NOx in the ambient air is crucial for the air pollution control Photocatalytic purification technology harnesses solar energy, operates under mild reaction conditions, and can convert low concentrations NO into nitrates, providing metabolic nitrogen for plant growth. From the perspectives of geochemical cycling and environmental pollution control, it is one of the most promising technologies for the purification of environmental atmospheric pollution. However, traditional catalysts face limitations in practical applications, such as low molecular activation rates, uncontrollable redox capabilities, and poor performance stability. materials. Emphasizing the critical role of active surface site control and molecular This review provides a comprehensive analysis of the advancements in photocatalytic NOx removal using ultrathin layered activation, the study explores various strategies, including defect engineering, crystal facet regulation, element doping, single-atom catalysts, and plasmon coupling, to enhance photocatalytic efficiency and selectivity. Key findings demonstrate that these advanced materials significantly improve NO adsorption, activation, and conversion, leading to higher photocatalytic performance. Despite these advancements, challenges such as the precise control of surface electronic structures, stability of active sites, scalability, and economic feasibility remain. The review highlights the need for further research to address these challenges and optimize photocatalytic technologies for large-scale applications. This work contributes to the field by offering insights into the mechanisms and potential of layered photocatalysts for sustainable and efficient air purification.

Graphical Abstract

The optical, morphological, and elemental characteristics of aerosols from the pristine Gangotri Glacier Valley (GGV) are reported. To our knowledge, this is the first study to examine the morphological and elemental components of aerosols in the northwestern Indian Himalayas. Located far from any anthropogenic air pollution hotspot, this glacier valley in the Himalayas provides an ideal setting for research on aerosol characterization. The observations are made using an optical attenuation-based real-time black carbon monitor (aethalometer type AE 33). The scanning electron microscope equipped with an energy dispersive X-ray spectroscope (SEM–EDX) was utilized to analyze the morphology and elemental composition of individual particles. This analysis focused on the total suspended particles (TSP) that were deposited on the quartz filter tape of the aethalometer. The scanned electron micrographs reveal variable morphological structures in submicron particles. Morphological parameters (viz., aspect ratio (AR) and circulatory factor (CIR)) were computed after careful analysis of electron micrographs using ImageJ software. The frequency distribution of morphological parameters reveals that the AR peaked between 1.1 and 1.3, while the CIR peaked between 0.95 and 1.1. The results are compared to other studies and reveal that GGV particles are more spherical than Indo-Gangetic Basin samples. Energy dispersive X-ray analysis of electron micrographs provides elemental identification and quantitative composition. During the study period (May 2016), the air surrounding GGV was observed to be rich in fluorine, oxygen, carbon, silica, sodium, aluminum, magnesium, sulfur, iron, zinc, potassium, calcium, and barium. Synoptic scale analyses of thermal anomalies and aerosol optical depth were also carried out using MODIS and MERRA-2 satellite data sets, respectively. HYSPILT backward air mass cluster trajectory analysis reveals that air mass transported from south-western Asia and the Indo-Gangetic basin dominated the glacier valley throughout the study period. The current research initiates an important step in our understanding of the aerosol properties in Himalayan glacier valleys. These findings also highlight the importance of understanding regional-scale processes that alter aerosol composition and concentrations in this ecologically vulnerable region. This investigation lays the groundwork for future long-term, multi-seasonal studies. These scientific studies may help environmental regulators protect the Himalayan cryosphere and glacier habitat.

The quantification of bioaerosols and particulate matter within zoo enclosures is a critical yet underexplored area, particularly given the global role of zoological environments in wildlife conservation, research, and public education. Zoos, which host a diverse array of wildlife and attract millions of visitors annually, are complex ecosystems where multiple sources of air pollution converge. This study aimed to systematically assess the prevalence of bacterial aerosols within various animal enclosures, including those of Tigers, Lions, Leopards, Rheas, Deer, Hippos, Ostriches, Crocodiles, and Owls. Utilizing a six-stage Andersen impactor, bioaerosol samples were collected to determine the concentration and dispersion of airborne microorganisms, while the DustTrak Aerosol Monitor was employed to measure levels of particulate matter (PM10, PM2.5, and PM1), carbon dioxide (CO2), and formaldehyde (HCHO). The findings revealed distinct bacterial population peaks across different locations and animal species, highlighting significant variations in airborne bacterial levels within the sampled enclosures. Gram staining identified a predominance of Gram-negative bacteria, which poses broader implications for understanding the transmission of pathogens and antibiotic resistance in confined environments. Notably, this study provides a foundational framework for evaluating bacterial resistance to antibiotics in zoological settings, contributing to the global discourse on antimicrobial resistance (AMR). The insights gained underscore the necessity of judicious antibiotic use to safeguard both animal health and broader public health. Given that animals are substantial generators of bioaerosols, this research emphasizes the importance of stringent maintenance of enclosures and their surroundings, alongside the optimization of microclimatic conditions to mitigate health risks. By shedding light on the microbial dynamics in zoo environments, this study calls for proactive, globally informed measures to ensure the welfare of animals and the health of visitors, thus advancing the broader understanding of bioaerosol management in complex, human-animal interaction spaces.

This study investigates the longitudinal trends and spatial variability of atmospheric trace gases and particulate matter (PM_2.5) in five major Indian metropolitan areas: Delhi, Chennai, Hyderabad, Kolkata, and Mumbai, over the period from 2016 to 2020. Utilizing data from satellite remote sensing and ground-based monitoring stations, we analyze the seasonal and daily variations in concentrations of key pollutants, including nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and PM_2.5. The study reveals distinct seasonal patterns influenced by meteorological conditions, urban activities, and regulatory measures. Elevated levels of pollutants are observed during winter months, particularly in Delhi, attributed to temperature inversions and biomass burning. Comparative analysis highlights significant urban variability, with Delhi exhibiting the highest pollution levels, while Chennai shows the lowest. Statistical analysis reveals that Delhi records the highest average daily concentrations of CH₄ (1869.50 ± 31.08 ppbv) and PM_2.5 (106.99 ± 83.49 µg/m³), while Chennai consistently records the lowest levels of CH₄ (1836.82 ± 26.78 ppbv) and PM_2.5 (33.42 ± 27.85 µg/m³). These findings provide critical insights into the temporal dynamics and spatial heterogeneity of air pollution, essential for devising targeted air quality management strategies in Indian cities.

Due to their influence on climate and human health, organic aerosols, a substantial component of atmospheric particulate matter (PM), are a major area of scientific focus. This study investigates the distribution, seasonal variations, and sources of organic constituents —including n-alkanes, alkanol acids, alkanols, sugars, phthalate esters, lignin and resin products, sterols, and polycyclic aromatic hydrocarbons (PAHs)— in the coarse mode (PM₁₀) of ambient air samples collected in Raipur, India. The total concentration of the organic aerosols ranged from 5106 to 29,099 ng m^− 3, with a mean value of 16,701 ± 3355 ng m^− 3. Fatty acids, phthalates, and levoglucosan were the major components. Seasonal analysis revealed higher concentrations of n-alkanes, PAHs, and lignin products during the winter, while alcohols, fatty acids, sterols, and sugars exhibited elevated levels in both autumn and winter. Size segregation analysis showed that all organic species, except phthalates and PAHs, accumulated predominantly in the fine and ultrafine particle fractions. Source apportionment through factor analysis revealed a complex mixture of sources shaping aerosol composition, including vehicular emissions, various combustion activities (biomass burning and charbroiled cooking), natural background factors, and the combination of urban dust and biogenic materials. The findings highlight the significant climatic and health implications of organic aerosols in the study region, necessitating urgent mitigation measures to address air pollution.

Particulate matter with a size of 2.5 µm or smaller (PM_2.5) has been a threat to human health and the environment worldwide. Over the years, the pollution patterns in India have changed significantly. However, there are not enough data available to properly assess the temporal variations in PM_2.5 concentrations over India. This study aims to quantify the extent of PM_2.5 variation across India from 1998 to 2021 using Atmospheric Composition Analysis Group (ACAG) satellite-derived gridded PM_2.5 data. For this purpose, the ACAG gridded PM_2.5 dataset is validated over India using ground-observed PM_2.5 concentrations. Specifically, daily PM_2.5 observations from 121 Central Pollution Control Board (CPCB) stations spanning over India are used to validate the ACAG gridded dataset. Four evaluation parameters, namely, the coefficient of determination (R²), Nash–Sutcliffe model efficiency coefficient (NSE), root mean square error (RMSE), and percentage difference in the peak value (PD), are used. From the results, an acceptable degree of agreement is observed between the ACAG gridded dataset and the CPCB ground observations. Therefore, the ACAG gridded dataset is further used to analyse the long-term trend in the monthly PM_2.5 concentrations across India. To examine the long-term trend in the PM_2.5 concentration, the Mann‒Kendall (MK) trend analysis is conducted on the gridded data at both annual and monthly scales. The results indicate a steady increasing trend in the PM_2.5 concentration in both the annual and monthly PM_2.5 concentrations. A steep increasing trend in the PM_2.5 concentration is observed in the Central and North Indian regions. Major portions of Indian states such as Uttar Pradesh, Haryana, Punjab, Uttarakhand, Delhi, Bihar, and Sikkim exhibited a percentage change of more than 80% in the PM_2.5 concentrations during December, January, and February. The results of the trend analysis revealed that a significant percentage of grids over India has a very steep increasing trend (MK tau value ≥ 0.7) in PM_2.5 concentrations during January (20.32%), February (20.22%), and December (20.19%).