Search Results (108)

Long-term source apportionment of PM_2.5 during high-pollution periods is essential for achieving sustained reductions in both PM_2.5 levels and their health impacts. This study conducted PM_2.5 sampling in Shenzhen from January to March over the years 2021–2024 to investigate the long-term impact of coronavirus disease 2019 and the short-term impact of the Spring Festival on PM_2.5 levels. The measured average PM_2.5 concentration during the research period was 22.5 μg/m³, with organic matter (OM) being the dominant component. Vehicle emissions, secondary sulfate, secondary nitrate, and secondary organic aerosol were identified by receptor model as the primary sources of PM_2.5 during the observational periods. The pandemic led to a decrease of between 30% and 50% in the contributions of most anthropogenic sources in 2022 compared to 2021, followed by a rebound. PM_2.5 levels in January–March 2024 dropped by 1.4 μg/m³ compared to 2021, mainly due to reduced vehicle emissions, secondary sulfate, fugitive dust, biomass burning, and industrial emissions, reflecting Shenzhen’s and nearby cities’ effective control measures. However, secondary nitrate and fireworks-related emissions rose significantly. During the Spring Festival, PM_2.5 concentrations were 23% lower than before the festival, but the contributions of fireworks burning exhibited a marked increase in both 2023 and 2024. Specifically, during intense peak events, fireworks burning triggered sharp, short-term spikes in characteristic metal concentrations, accounting for over 50% of PM_2.5 on those peak days. In the future, strict control over vehicle emissions and enhanced management of fireworks burning during special periods like the Spring Festival are necessary to reduce PM_2.5 concentration and improve air quality. Full article

In this work, the development of Al-based metal matrix composites (MMCs) is achieved using hybrid SiC and ZrO₂ reinforcement particles for automotive applications. Powder metallurgy (PM) is employed with various combinations of important process parameters for the fabrication of MMCs. MMCs were characterized using scanning electron microscopy (SEM), X-ray diffractometry (XRD), and a microhardness study. All XRD graphs adequately exhibit Al, SiC, and ZrO₂ peaks, indicating that the hybrid MMC products were satisfactorily fabricated with appropriate mixing and sintering at all the considered fabrication conditions. Also, no impurity peaks were observed, confirming high composite purity. MMC products in all the XRD patterns, suitable for the desired applications. According to the SEM investigation, SiC and ZrO₂ reinforcement components are uniformly scattered throughout Al matrix in all produced MMC products. The occurrence of Al, Si, C, Zr, and O in EDS spectra demonstrates the effectiveness of composite ball milling and sintering under all manufacturing conditions. Moreover, an increase in interfacial bonding of fabricated composites at a higher sintering temperature indicated improved physical properties of the developed MMCs. The highest microhardness value is 86.6 HVN amid all the fabricated composites at 7% silica, 14% zirconium dioxide, 500° sintering temperature, 90 min sintering time, and 60 min milling time. An integrated Particle Swarm Optimization–Support Vector Machine (PSO-SVM) model was developed to predict microhardness based on the input parameters. The model demonstrated strong predictive performance, as evidenced by low values of various statistical metrics for both training and testing datasets, highlighting the PSO-SVM model’s robustness and generalization capability. Specifically, the model achieved a coefficient of determination of 0.995 and a root mean square error of 0.920 on the training set, while on the testing set, it attained a coefficient of determination of 0.982 and a root mean square error of 1.557. These results underscore the potential of the PSO-SVM framework, which can be effectively leveraged to optimize process parameters for achieving targeted microhardness levels for the developed Al-SiC-ZrO₂ Composites. Full article

Quantum Dots (QDs) are small semiconductor nanoparticles (<10 nm) with strong, relatively stable, and tunable luminescent properties, which are increasingly applied in the sensing and detection of various analytes, including metal ions, biomarkers, explosives, proteins, RNA/DNA fragments, pesticides, drugs, and pollutants. In this review, we critically assess recent developments and advancements in luminescent QD-based sensors from an analytical perspective. We collected, tabulated, and analyzed relevant data reported in 124 peer-reviewed articles. The key analytical figures of merit, including the limit of detection (LOD), excitation and emission wavelengths, and size of the particles were extracted, tabulated, and analyzed with graphical representations. We calculated the geometric mean and median LODs from those tabulated publications. We found the following geometric mean LODs: 38 nM for QD-fluorescent-based sensors, 26 nM for QD-phosphorescent-based sensors, and an impressively low 0.109 pM for QD-chemiluminescent-based sensors, which demonstrate by far the best sensitivity in QD-based detection. Moreover, AI-based sensing methods, including the ATTBeadNet model, optimized principal component analysis(OPCA) model, and Support Vector Machine (SVM)-based system, were reviewed as they enhance the analytical performance of the detection. Despite these advances, there are still challenges that include improvements in recovery values, biocompatibility, stability, and overall performance. This review highlights trends to guide the future design of robust, high-performance, QD-based luminescent sensors. Full article

This study investigates the emission characteristics and environmental impacts of pollutants from bagasse-fired biomass boilers through the integrated field monitoring of two sugarcane processing plants in Guangxi, China. Comprehensive analyses of flue gas components, including PM_2.5, NOx, CO, heavy metals, VOCs, HCl, and HF, revealed distinct physicochemical and emission profiles. Bagasse exhibited lower C, H, and S content but higher moisture (47~53%) and O (24~30%) levels compared to coal, reducing the calorific values (8.93~11.89 MJ/kg). Particulate matter removal efficiency exceeded 98% (water film dust collector) and 95% (bag filter), while NOx removal varied (10~56%) due to water solubility differences. Heavy metals (Cu, Cr, Ni, Pb) in fuel migrated to fly ash and flue gas, with Hg and Mn showing notable volatility. VOC speciation identified oxygenated compounds (OVOCs, 87%) as dominant in small boilers, while aromatics (60%) and alkenes (34%) prevailed in larger systems. Ozone formation potential (OFP: 3.34~4.39 mg/m³) and secondary organic aerosol formation potential (SOAFP: 0.33~1.9 mg/m³) highlighted aromatic hydrocarbons (e.g., benzene, xylene) as critical contributors to secondary pollution. Despite compliance with current emission standards (e.g., PM < 20 mg/m³), elevated CO (>1000 mg/m³) in large boilers indicated incomplete combustion. This work underscores the necessity of tailored control strategies for OVOCs, aromatics, and heavy metals, advocating for stricter fuel quality and clear emission standards to align biomass energy utilization with environmental sustainability goals. Full article

A fiber Bragg grating (FBG)-based ocean temperature and depth sensor structure is proposed. The pressure sensing section employs a secondary sensitization design comprising a piston and the polycarbonate buffer, while the temperature sensing section utilizes an FBG encapsulated within a metal silver tube, accompanied by a temperature compensation structure. Simulation analyses verify the enhanced sensitivity of the proposed configuration. By selecting suitable materials for the piston, metal tube, and polymer, and optimizing the dimensions of key components, the sensitivity of the bare FBG sensor is significantly improved through the combined effects of the piston, polymer, and metal tube. After optimization, the sensor exhibits a pressure sensitivity of 1.33 nm/MPa and a temperature sensitivity of 102.77 pm/°C, meeting the high-precision detection requirements for ocean temperature and depth sensing. The experimental results show that the temperature sensitivity is 109.9 pm/°C within the temperature range of −5~35 °C, and that the pressure sensitivity is 1.63 nm/MPa within the pressure range of 1~10 MPa. These results confirm that the sensor is well-suited for high-precision ocean temperature and depth measurements. Full article

Fine particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM_2.5) has been extensively studied due to its adverse health effects. Most research has focused on its impact on the respiratory system; however, increasing attention is being directed toward its effects on the brain. Associations between air pollution and neurological disorders—such as Alzheimer’s disease, cerebral infarction, and autism spectrum disorder—have been reported, with mechanism-based studies in animal models providing further insights. PM_2.5 comprises a complex mixture of thousands of chemical constituents. To elucidate its neurotoxicity mechanisms, it is essential to investigate both its transport pathways to the brain and the specific actions of its individual components. This review highlights key PM_2.5 components—water-soluble ions, metals, carbonaceous particles, polycyclic aromatic hydrocarbons, quinones, plastics, and bioaerosols—and outlines their potential routes of entry into the central nervous system, along with their associated mechanisms of action. By integrating these findings, this review contributes to a deeper understanding of the neurological effects mediated by PM_2.5, which represent one of the most critical aspects of its health impact. Full article

This study investigates the concentrations, health risks, and potential sources of heavy metal elements and polycyclic aromatic hydrocarbons (PAHs) in PM_1.1 particles in Zhuji, a major copper-processing city in China. The ratios of heavy metals (summer: 0.906; winter: 0.619) and PAHs (>0.750 in both seasons) in PM_1.1/PM_2.0 suggest significant accumulation in ultrafine particles. In winter, heavy metal concentrations in PM_1.1 reached up to 448 ng/m³, and PAH concentrations were 13.4 ng/m³—over ten times higher than in summer. Health risk assessments revealed that hazard index (HI) values exceeded 1.00 for five age groups (excluding infants) during winter, indicating chronic exposure risks. Incremental lifetime cancer risk (ILCR) values surpassed the upper acceptable limit (1.0 × 10⁻⁴) for four age groups, with Cr, As, Cd, and Pb as major contributors. PAH-related ILCRs were also elevated in winter, with benzo[a]pyrene (BaP) identified as the most potent carcinogen. Enrichment factor (EF) and principal component analysis (PCA) indicated that industrial activities and traffic emissions were the dominant anthropogenic sources of heavy metals. Diagnostic ratio analysis further showed that PAHs mainly originated from vehicle and coal combustion. These findings provide critical insights into pollution patterns in industrial cities and underscore the importance of targeted mitigation strategies. Full article

Rapid progress in lithium-ion batteries and AI-powered autonomous driving is poised to propel electric vehicles to a 50% share of the global automotive market by the year 2035. Today, there is a major focus on recycling electric vehicle motors, particularly on extracting rare earth elements (REEs) from NdFeB permanent magnets (PMs). This research is based on a single-furnace process concept designed to separate metal components within PM motors by exploiting the varying melting points of the constituent materials, simultaneously extracting REEs present within the PMs and transferring them into the slag phase. Thermodynamic modeling, via Factsage Equilib stream calculations, optimized the experimental process. Simulated materials substituted the PM motor, which optimized modeling-directed melting within an induction furnace. The 2FeO·SiO₂ fayalite flux can oxidize rare earth elements, resulting in slag. The neodymium oxidation reaction by fayalite exhibits a ΔG° of −427 kJ when subjected to an oxygen partial pressure ($P_{O_2}$) of 1.8 × 10⁻⁹, which is lower than that required for FeO decomposition. Concerning the FeO–SiO₂ system, neodymium, in Nd³⁺, exhibits a strong bonding with the ${\mathrm{S}\mathrm{i}\mathrm{O}}_4^{4^{-}}$ matrix, leading to its incorporation within the slag as the silicate compound, Nd₂Si₂O₇. When 30 wt.% fayalite flux was added, the resulting experiment yielded a neodymium extraction degree of 91%, showcasing the effectiveness of this fluxing agent in the extraction process. Full article

The creation of coatings by the cathodic arc evaporation method has outstanding advantages: these coatings are highly durable and wear-resistant, especially since the method has an intense ionization process and the atoms can penetrate deep into the surface substrates, resulting in excellent adhesion. Furthermore, this approach provides precise control over the chemical composition and thickness of the coating, ensuring consistent quality across the entire surface. However, uneven evaporation and ejection of molten metal droplets from the cathode during cathode arc deposition produce particles and droplets, resulting in an uneven coating surface. This study presents a new design for a magnetically controlled cathode arc source to effectively reduce particles and droplets during the cathodic arc deposition of multi-component alloy targets for nitride-based hard coatings. The study compares the performance of a new source with a conventional magnetic-controlled arc source for depositing TiAlNbSiN and AlCrSiN films. In the conventional source, the magnetic field is generated by a permanent magnet (PM), whereas in the new source, it is generated and controlled using an electromagnet (EM). Both films are produced using multi-component alloy targets (TiAlNbSi and AlCrSi) with identical composition ratios. The plasma characteristics of the two different arc sources are investigated using an optical emission spectrometer (OES), and the surface morphology, structural characteristics, deposition rate, uniformity, and surface roughness (Sa) are examined using scanning electron microscopy (SEM). When the EM was applied to have high plasma density, the hardness of the TiAlNbSiN film deposited with the novel arc source measured 31.2 ± 1.9 GPa, which is higher than that of the PM arc source (28.3 ± 1.4 GPa). In contrast, the AlCrSiN film created using a typical arc source exhibited a hardness of only 25.5 ± 0.6 GPa. This lower hardness may be due to insufficient ion kinetic energy to enhance stress blocking and increase hardness, or the presence of the h-AlN phase in the film, which was not detected by XRD. The electromagnet arc source, with its adequate ion bombardment velocity, facilitated a complementary effect between grain growth and stress blocking, leading to a remarkable hardness of 32.6 ± 0.5 GPa. Full article

This study examines long-term trends in fine particulate matter (PM_2.5) composition and oxidative potential in Los Angeles based on data from the University of Southern California’s Particle Instrumentation Unit, with chemical composition retrieved from the EPA’s Air Quality System (AQS). While regulatory interventions have reduced PM_2.5 mass concentration and primary combustion-related components, our findings reveal a more complex toxicity pattern. From 2001 to 2008, the PM_2.5 oxidative potential, measured via the dithiothreitol (DTT) assay, declined from ~0.84 to ~0.16 nmol/min/m³ under stringent tailpipe controls. However, after this initial decline, PM_2.5 DTT stabilized and gradually increased from ~0.35 in 2012 to ~0.97 nmol/min/m³ by 2024, reflecting the growing influence of non-tailpipe emissions such as brake/tire wear. Metals, such as iron (Fe, ~150 ng/m³) and zinc (Zn, ~10 ng/m³), remained relatively stable as organic and elemental carbon (OC and EC) declined, resulting in non-tailpipe contributions dominating PM_2.5 toxicity. Although PM_2.5 mass concentrations were effectively reduced, the growing contribution of non-tailpipe emissions (e.g., brake/tire wear and secondary organic aerosols) underscores the limitations of mass-based standards and tailpipe-focused strategies. Our findings emphasize the need to broaden regulatory strategies, targeting emerging sources that shape PM_2.5 composition and toxicity and ensuring more improvements in public health outcomes. Full article

The ascorbic acid (AA) assay is a widely recognized tool for assessing the oxidation potential (OP) of atmospheric particulate matter (PM), including PM_2.5. OP quantified through the cell-free AA assay can be used to study the association between chemical properties and harmful biological effects, such as the degradation of AA in the lungs by PM sample. AA is oxidized and depleted in solutions containing redox-active species such as polycyclic aromatic hydrocarbon quinones and heavy metal ions (Cu²⁺ and Fe²⁺), which are potential PM components. The metal ions form a Werner-type complex with ligands; thus, the AA depletion rate changes with the co-existing ligands in the PM sample. However, how the coordination structure of the complexes affects the AA depletion rate is poorly understood. This study examined the impact of the Werner-type complex formation of Cu²⁺ and Fe²⁺ on the AA depletion rate. Cu²⁺ and Fe²⁺ complexes were prepared by mixing them with three ethyleneamine forms: ethylenediamine, diethylenetriamine, and triethylenetetramine. The AA depletion rate was determined by measuring the changes in absorbance at 265 nm in the reaction solutions. Results indicated that the AA depletion rates of Cu²⁺ and Fe²⁺ were suppressed by the formation of complexes, and the degree of suppression depended on the coordination number and stability constants of the ethyleneamines. Additionally, AA depletion rates decreased with decreasing oxidative reduction potential in the solutions and changes in the coordination structures of the metal ion complexes. These findings demonstrate that the formation of Werner-type complexes with Cu²⁺ and Fe²⁺ reduces the AA depletion rate. As the number of ligands coordinating to the metal ions increases, the ORP decreases, creating a reducing environment that suppresses the oxidation of AA. Full article

Identifying the relationship between the microbiomes of urban dust particles from different biotopes is important because the state of microorganisms can be used to assess the quality of the environment. The aim of this work was to determine the distribution and interaction patterns of microorganisms of dust particles in the air and on leaf surfaces. Metabarcoding of bacterial and fungal communities, PAH, and metal content analyses and electron microscopy were used in this work. The results obtained allowed us to characterise the biological and chemical components of the dust particles. Some bacterial and fungal genera were correlated with benzanthracene, fluoranthene, and Cu, Ni, Co, Zn, and Mn contents. Bacterial communities were found to be more sensitive to all the pollutants studied. PM10 microbial communities circulated between biotopes and study areas due to air flows, as evidenced by the presence of similar ASVs in fungi and bacteria. The results could help to understand the effects of climate change and anthropogenic activities. Full article

Environmental pollution continues to increase with industrial development and has become a threat to human health. Atmospheric particulate matter (PM) was designated as a Group 1 carcinogen by the International Agency for Research on Cancer in 2013 and is an emerging global environmental risk factor that is a major cause of death related to cardiovascular and respiratory diseases. PM is a complex composed of highly reactive organic matter, chemicals, and metal components, which mainly cause excessive production of reactive oxygen species (ROS) that can lead to DNA and cell damage, endoplasmic reticulum stress, inflammatory responses, atherosclerosis, and airway remodeling, contributing to an increased susceptibility to and the exacerbation of various diseases and infections. PM has various effects on human health depending on the particle size, physical and chemical characteristics, source, and exposure period. PM smaller than 5 μm can penetrate and accumulate in the alveoli and circulatory system, causing harmful effects on the respiratory system, cardiovascular system, skin, and brain. In this review, we describe the relationship and mechanism of ROS-mediated cell damage, oxidative stress, and inflammatory responses caused by PM and the health effects on major organs, as well as comprehensively discuss the harmfulness of PM. Full article

The combination of metal–phthalocyanine complexes and axially coordinated organic molecules into polymer chains presents a significant challenge in the synthesis of hybrid materials. A calculated structure for one-dimensional coordinate polymers with N-donor ligands using ab initio (PM6) and DFT (LanL2Dz) methods is presented. DFT methods have shown that there is a linear, one-dimensional structure without distorted geometry for the two bipyridine ligands. The components of the proposed polymers consist of square-planar Zn complexes of phthalocyanine (PcZn) connected via bridging ligands (L). Electronic properties of the monomer PcZnL of zinc phthalocyanine with bidentate ligands have been analyzed using calculations based on density functional theory (B3LYP6-31G(d,p)). Molecular orbital calculations show that this connection between the metallomacrocycle and the conjugated ligand results in a small energy gap, promising molecularly active materials as conductors. The crystallographic reports indicate that obtaining this kind of polymer with the participation of Pc Zn and bidentate ligands is possible. Full article

This study leveraged 2019 online data of particulate matter (PM_2.5) and volatile organic compounds (VOCs) in Tianjin to analyze atmospheric pollution characteristics. PM_2.5 was found to be primarily composed of water-soluble ions, with nitrates as the dominant component, while VOCs were predominantly alkanes, followed by alkenes and aromatic hydrocarbons, with notable concentrations of propane, ethane, ethylene, toluene, and benzene. The receptor model identified six major sources of PM_2.5 and seven major sources of VOCs. The secondary source is the main contribution source, while motor vehicles and coal burning are important primary contribution sources in PM_2.5. And, industrial processes and natural gas volatilization were considered major contributors for VOCs. A health risk assessment indicated negligible non-carcinogenic risks but potential carcinogenic risks from trace metals As and Cr, and benzene within VOCs, underscoring the necessity for focused public health measures. A risk attribution analysis attributed As and Cr in PM to coal combustion and vehicular emissions. Benzene in VOCs primarily originates from fuel evaporation, and industrial and vehicular emissions. These findings underscore the potential for reducing health risks from PM and VOCs through enhanced regulation of emissions in coal, industry, and transportation. Such strategies are vital for advancing air quality management and safeguarding public health. Full article