Aerosol Science and Engineering最新文献

Fog droplets are very often used as a cleaning agent when air pollution can be dangerous for health conditions and ecosystem. This work presents a new system to optimize the cleaning properties of fog by tuning its microphysical parameters. For this purpose, a newly developed system, which is based on the electromagnetic echo effect (EMEE) sensor, is used to detect the most efficient interaction between fog and impurities, i.e., which fog droplets can be used to most effectively clean a certain type of pollutant from the air. Fog droplet spectra controlled by the nozzle pressure system can be used to effectively remove pollutants from the air. For this purpose, an automated system for aerosol generation can allow an accurate control over the fog microphysical parameters and the use of fluids with specific concentrations of pulverized chemical compounds. Fog droplet size distribution is controlled by the feeding gas pressure at the nozzle and chemical simulants. The experimental results showed that the microphysical parameters (MP) are directly related to the impurity of species used in the cleanup simulation process. The MP parameters of fog are liquid water content (LWC), droplet mean radius (R_m), droplet number concentration (N_d), and both aerosol type and mass concentration. In the lab testing, harmless simulants of CBRN (chemical, biological, radiological and nuclear) species were used. During the tests, fog droplet size distribution is controlled by the air pressure at the nozzle and simulants. It is concluded that an integrated fog generator system (IFGS) with EMEE sensor developed in the current work can be utilized broadly to control fog microphysical parameters, leading to an optimum aerosol/chemical species’ cleaning process.

Sanya has geographical and climatic characteristics such as low latitude, high temperature, high salt, high humidity, and strong solar radiation all year round, which is conducive to the occurrence of photochemical reactions; therefore, the problem of ozone photochemical pollution in Sanya needs to be solved urgently. This article is based on the hourly data of O₃ and NO₂ in Sanya City in 2019, various collected meteorological data, and online monitoring of VOC_S major species data to analyze the characteristics of ozone pollution changes and source apportionment in Sanya City. The results indicate that the daily variation characteristics of ozone pollution in Sanya City conform to the typical characteristics of ozone photochemical pollution events, and the EKMA curve indicates that Sanya City as a whole belongs to a NO_X-sensitive area. The OH consumption rate (L^OH) and ozone generation potential (OFP) indicate that the key active components of VOC_S are mainly isoprene, ethylene, n-butane, propane, etc. The corresponding main potential sources of emissions include combustion emissions, solvent volatilization, and automotive exhaust emissions. The O₃ emission reduction plan is to reduce the ozone concentration from 180 to 158 µg·m⁻³, corresponding to a 25 and 20% reduction in the concentrations of the two main precursors, NO_X and VOC_S, respectively. This article provides scientific support for the problem of ozone photochemical pollution in Sanya City.

The primary focus of this investigation is to create a unique main rotor equipped rotary-wing unmanned aerial vehicle (RWUAV) to detect and mitigate air pollution, which is major concern in modern civilization. This RWUAV was designed after careful consideration and analysis in a variety of maneuvering phases under the fluid particle-based aerosol conditions. This method of spraying the atmosphere using an RWUAV is meant to eradicate fog and other airborne pollutants. The RWUAV takes a mixture of hydrogen peroxide and nitric acid solution, which it then sprays into the air. The aerodynamic parameters are estimated using ANSYS Workbench 17.2 equipped with computational fluid dynamic (CFD) solver, i.e., Fluent and ANSYS Workbench 17.2 with Finite element analysis (FEA) solver has been used to assess the RWUAV imposed with a variety of lightweight materials. The aforementioned multi-computational techniques are used to examine the structural robustness and aerodynamic performances under different airflow circumstances. As the load acting on the proposed RWUAV in aerosol-rich environment will be different than the normal environment, thus the need of this study to determine suitable material which will be structurally stable in both the environments. Thus, from the cumulative results of the structural analyses for both VTOL and forward maneuverings of the RWUAV it can be concluded that for VTOL the materials CFRP-WN-230-wet, CFRP-WN-230-ppg, CFRP-UD-230-wet, CFRP-UD-230-ppg, GFRP-S-UD, and GFRP-E-UD have proven to perform better than other lightweight composites. And from the cumulative results of structural analysis for forward motion the materials CFRP-UD-230GPa-ppg, CFRP-UD-230GP-wet, and GFRP-S-UD have proven to perform better than other lightweight composites. Thus, in conclusion CFRP-UD-230GPa-ppg, CFRP-UD-230GPa-wet, and GFRP-S-UD are better materials for RWUAV for better performance under aerosol heavy environment as these materials have shown promising results for both VTOL and forward motion under both normal environment and aerosol heavy environment. Developing this RWUAV would be helped along by the fact that this RWUAV might be made in a way that is less harmful to the environment.

Aerosol is a key component in the climate system. Limited ground monitoring stations impede the acquisition of spatial and temporal aerosol concentration data. However, Remote sensing can provide wider coverage and real-time data, compensating for ground coverage constraints. In the present study, the spatial and temporal variation of Aerosol Optical Thickness (AOT) was analyzed for the Indian cities having significantly different meteorology and geographical conditions like Jaipur and Pune for the years 2020 and 2021 using the Multi-Angle Implementation of the Atmospheric Correction (MAIAC) algorithm. The seasonal mean AOT in winter, pre-monsoon, and post-monsoon are recorded as 0.56, 0.62, and 0.89, respectively, over the entire Jaipur district. However, it was recorded as 0.76, 0.62, and 0.52, respectively, over the entire Pune district. Results of the seasonal analysis indicate that Jaipur and Pune experience high loads of aerosol during post-monsoon and winter, respectively. In this context, the back trajectory, developed through the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, revealed that Jaipur experiences air masses and emissions from the northern region of India during the post-monsoon. However, Pune encounters air masses from the eastern region of India in winter. The mean Angstrom exponent values at Jaipur and Pune aid in understanding the size and type of aerosol. Jaipur and Pune experience biomass burning aerosol and mixed aerosols to a greater extent, respectively. The performance of MAIAC-derived AOT was assessed using Aerosol Robotic Network (AERONET) sun-photometers derived AOT at Jaipur and Pune with coefficient of determination (R²) values of 0.88 and 0.71 and Root Mean Squared Error (RMSE) values of 0.1338 and 0.1869, respectively.

The study examined the factors that contribute significantly to automobile exhaust pollution in the major city of Ghana, Accra. Using an SV-5Q automobile exhaust-gas analyzer, the concentrations of carbon dioxide (CO₂), hydrocarbon (HC), carbon monoxide (CO), and nitrogen oxides (NO_x) were measured on 1002 light-duty gasoline automobiles taking into consideration age, maintenance, and emission technology (catalytic converters). To achieve the aim of the study, the emissions data gathered were analyzed against the vehicle parameters (Age of the vehicle, Frequency of maintenance, and Emission technology). The significant parameters explained variance of 42%, 22%, 32%, and 7% in CO, CO₂, HC, and NO_x, respectively. The results showed that the age of a vehicle is a significant positive predictor of CO, CO₂, and HC emission but has no significant effect on NO_x. The result further shows that the frequency of maintenance negatively predicted HC emissions with no significant effect on CO, CO₂, and NO_x. The results also demonstrated that emission technology was consistently negatively related to CO, CO₂, HC, and NO_x. Finally, the result established that an increase in vehicle age increases the emission level, while regular vehicle maintenance, two-way and three-way catalytic converters fitted on vehicle exhaust system decrease the exhaust emission level.

Global urban air quality and human health are under significant threat from air pollution. China, with its successful “Clean Air Act,” offers valuable expertise in mitigating air pollution over the past decade. The Belt and Road countries in the Indochina Peninsula confront severe air pollution from sources such as biomass burning. This pollution interacts with organic volatiles emitted from the Southeast Asian tropical forests, impacting the ecosystem and climate in the region. China is actively promoting the Belt and Road South-South Cooperation Initiative on climate change. The time has come for China to share its expertise in air pollution mitigation to the Belt and Road countries, with emphases on talent development, technical service export, and intergovernmental research cooperation. This initiative not only reduces cross-border air pollution transmission but also benefits local health in the broader Indochina region.

The classical nucleation theory (CNT) plays an important role in the investigation of vapor heterogeneous nucleation on solid surfaces. However, the CNT relies on the macroscopic surface tension to describe the formation of a nano-sized embryo, which inevitably causes the model inaccuracy. In this study, an improved CNT is developed by integrating the microscopic surface tension as a function of the embryo size obtained using the molecular dynamics (MD) simulation to enhance the model accuracy. The important heterogeneous nucleation behaviors, including the Gibbs free energy of embryo formation, critical saturation ratio, and nucleation probability, are numerically investigated by the improved CNT. Compared with the CNT with the macroscopic surface tension, the improved CNT using the microscopic surface tension predicts lower Gibbs free energy of embryo formation, lower critical saturation ratio, and higher nucleation probability, particularly when the contact angle of the particle is large. The improved CNT proposed in this study is validated by comparing the numerically predicted critical saturation ratios for the heterogeneous nucleation of water vapor on planar surfaces and on nano- and micron-sized insoluble particles with the experimentally measured data published in literature.

PM_2.5/PM₁₀ ratio is a metric that is used both to determine the main origin of particulate matter and to evaluate the concentration of one component in the absence of monitoring for the other. However, further research is required to fully understand the relationship between this ratio, its components, and meteorological conditions in various scenarios. This study analyzed the effect of COVID-19 restrictions on the PM_2.5/PM₁₀ ratio in Recife, Brazil. The data showed that the PM_2.5/PM₁₀ ratio significantly decreased in 2020 due to the reduction in urban mobility and human activities. The strictest restrictions were maintained in the state until August and as soon as the first major loosening took place, the ratio began to approach typical pollution levels. The average daily PM_2.5/PM₁₀ ratios for 2020, 2021 and 2022 were 0.52 ± 0.08, 0.58 ± 0.03 and 0.58 ± 0.02, respectively, lower than those found in other metropolitan areas. During the phases of greater restrictions, the PM_2.5/PM₁₀ ratio had an average value of 0.48 ± 0.08 and as restrictions were lifted, it became 0.56 ± 0.03. The results showed that the reductions observed in 2020 were directly related to the decrease in anthropogenic emissions of PM_2.5. A machine learning approach was used to estimate the expected PM_2.5/PM₁₀ ratio, corrected for the meteorological conditions and it was found that the observed ratios were lower than expected even in this scenario. Furthermore, only temperature and wind speed presented significant correlation to the PM_2.5/PM₁₀ ratio in both the scenarios with and without restriction of activities. Our study provides valuable insights into the efficacy of restriction measures in the Brazilian tropical and coastal metropolis of Recife and also highlight the intrinsic relation between the ratio and the local meteorological variables.

The nexus of the ambient air quality and the COVID-19 pandemic is a topic that has attracted much attention and remains of current interest. The study area of Turkey is one of the countries with high case numbers, but there is no detailed investigation dealing with it in the literature. For this reason, the correlation and links between COVID-19 cases and deaths in Turkey with the air pollutants of PM₁₀, PM_2.5, SO₂, CO, NO₂ and O₃ were determined between 1 April and 31 July 2021 using the statistical methods of cross-correlation and wavelet coherence analysis. According to the findings, for the COVID-19 pandemic parameters, there were positive significant correlations with PM_2.5, SO₂, CO, and NO₂ and an inverse significant correlation with O₃. Although the wavelet transform is not convincing to suggest a standalone coherence, it reveals that air pollution and the spread and mortality of the pandemic in Turkey have short-term periods of co-movement. Additionally, it is notable that the national air quality improved during full lockdown periods in the country. The findings obtained in this study are expected to attract the attention of legislating and enforcing authorities and support more decisive steps being taken to reduce environmental pollutants and to control air pollution.

This study investigates the morphological and mineralogical characteristics of coarse mode particulate matter (PM₁₀) over the Central Himalayan region of India (Nainital: 29.39°N, 79.45°E, 1958 m above mean sea level). X-ray diffraction (XRD), Fourier Transform Infrared (FTIR), and Scanning Electron Microscopy-Energy Dispersive X-ray (SEM–EDX) techniques were employed for morphological and mineralogical analysis of PM₁₀ collected from January to December 2019. XRD and FTIR techniques identify crystalline phases, revealing minerals such as illite, kaolinite, montmorillonite, quartz, dolomite, calcite, magnetite, hematite, gypsum, halite, mascagnite, augite, albite, wollastonite, and calcium aluminium silicate hydrate (C-A-S=-H) in PM₁₀ samples. SEM–EDX analysis confirms the presence of major elements i.e., Si, Al, Ca, K, Fe, Mg, S, Na, Ba, Ti, Zn, and Cl in PM₁₀, indicating the diverse mineral formations. Elemental composition variations are observed, with Si, and Al being predominant. The minerals' elemental composition suggests geogenic sources (e.g., dust storms, rock weathering) for quartz, dolomite, albite, augite, etc., containing Al, Si, Na, Ca, Mg, and Fe. Meanwhile, illite, montmorillonite, mascagnite, hematite, calcium aluminium silicate, etc., with elements like Ca, Al, Si, Fe, K, Zn, Ti, Ba, S, and Cl, are linked to anthropogenic sources (e.g., demolition, construction, combustion, industrial and vehicular emissions). These findings contribute to a better understanding of air quality, environmental conditions, and potential health implications in the Central Himalayan region.