Toxics最新文献

The widespread occurrence of atrazine (ATZ) in water environments presents a considerable risk to human health and ecosystems. Herein, the performance of dielectric barrier discharge integrated with periodate (DBD/PI) for ATZ decomposition was evaluated. Results demonstrated that the DBD/PI system improved ATZ decomposition efficiency by 18.2-22.5% compared to the sole DBD system. After 10 min treatment, the decomposition efficiency attained 82.4% at a discharge power of 68 W, a PI dosage of 0.02 mM, and an initial ATZ concentration of 10 mg/L. As the PI dosage increased, the decomposition efficiency exhibited a trend of initially increasing, followed by a decrease. Acidic conditions were more favorable for ATZ removal compared to alkaline and neutral conditions. Electron paramagnetic resonance (EPR) was adopted for characterizing the active species produced in the DBD/PI system, and quenching experiments revealed their influence on ATZ decomposition following a sequence of ¹O₂ > O₂^-• > IO₃• > OH•. The decomposition pathways were proposed based on the theoretical calculations and intermediate identification. Additionally, the toxic effects of ATZ and its intermediates were assessed. This study demonstrates that the DBD/PI treatment represents an effective strategy for the decomposition of ATZ in aquatic environments.

(1) Background: Mercury and lead contamination resulting from various anthropogenic activities represents a global environmental problem and a considerable risk to the health of the human population. (2) Methods: The objective of this research was to evaluate the concentrations of mercury (Hg) and Lead (Pb) in the blood of the child population in the municipalities in the Atrato River basin using a direct Hg analyzer and graphite furnace atomic absorption spectrometry. (3) Results: In total, 171 children (5-14 years of age) were taken into account, and 18.71% (32) of the children had concentrations of Hg and Pb above the permissible values established by the WHO. In the municipality of UN, 19 children had blood Hg concentrations between 5.29 and 17.71 μg/L. In CA, two children had concentrations of 5.03 and 8.43 μg/L, separately. In the case of Pb, seven children showed concentrations between 3.60 and 4.83 μg/dL in the municipality of RQ, three in UN (3.59, 3.61, and 4.60 μg/dL), and one in Carmen de Atrato (5.47 μg/dL). (4) Conclusions: The levels of Hg and Pb in the blood of children living in the riparian areas of the Atrato River basin are related to gold mining activities in the basin and the consumption of contaminated fish.

In the process of flue gas desulfurization and denitrification, the generation of high-sulfate wastewater containing nitrogen is a significant challenge for biological wastewater treatment. In this study, halophilic activated sludge was inoculated in a Sequencing Batch Reactor to remove nitrogen from wastewater with a high sulfate concentration (60 g/L). With the influent concentration of 180 mg/L, the removal rate of total nitrogen was more than 96.7%. The effluent ammonium nitrogen concentration was lower than 1.94 mg/L, and the effluent nitrate nitrogen and nitrite nitrogen concentrations were even lower than 0.77 mg/L. The salt tolerance of activated sludge is mainly related to the increase in the content of ectoine in microbial cells. The Specific Nitrite Oxidation Rate is quite low, while the Specific Nitrite Reduction Rate and Specific Nitrate Reduction Rate are relatively strong. In the system, there are various nitrogen metabolic processes, including aerobic nitrification, anaerobic denitrification, and simultaneous nitrification-denitrification processes. By analyzing the nitrogen metabolic mechanisms and microbial community structure of the reaction system, dominate bacteria can be identified, such as Azoarcus, Thauera, and Halomonas, which have significant nitrogen removal capabilities.

An innovative SPME head space GC-MS method, in cooling mode, using a fully automated routine, was developed to detect 2-phenyl-2-propanol, a representative urinary metabolite of cumene. Following an acid hydrolysis and derivatization step with lowered quantities of reagents, acetic anhydride and pyridine, a 30 μm polydimethylsiloxane SPME fiber was used to sample derivatized 2-phenyl-2-propanol, such as benzenemethanol,α,α-dimethyl-acetate, from the headspace. Performances of the method, optimized through experimental design, provide an LOD of 0.034 mg/L and an LOQ 0.10 mg/L, with a short sampling time necessary per sample. The method, developed on standard solutions, will be applied to both occupationally exposed and non-exposed populations.

To predict the behavior of aromatic contaminants (ACs) in complex soil-plant systems, this study developed machine learning (ML) models to estimate the root concentration factor (RCF) of both traditional (e.g., polycyclic aromatic hydrocarbons, polychlorinated biphenyls) and emerging ACs (e.g., phthalate acid esters, aryl organophosphate esters). Four ML algorithms were employed, trained on a unified RCF dataset comprising 878 data points, covering 6 features of soil-plant cultivation systems and 98 molecular descriptors of 55 chemicals, including 29 emerging ACs. The gradient-boosted regression tree (GBRT) model demonstrated strong predictive performance, with a coefficient of determination (R²) of 0.75, a mean absolute error (MAE) of 0.11, and a root mean square error (RMSE) of 0.22, as validated by five-fold cross-validation. Multiple explanatory analyses highlighted the significance of soil organic matter (SOM), plant protein and lipid content, exposure time, and molecular descriptors related to electronegativity distribution pattern (GATS8e) and double-ring structure (fr_bicyclic). An increase in SOM was found to decrease the overall RCF, while other variables showed strong correlations within specific ranges. This GBRT model provides an important tool for assessing the environmental behaviors of ACs in soil-plant systems, thereby supporting further investigations into their ecological and human exposure risks.

To observe the long-term variations in halocarbons in the Yangtze River Delta (YRD) region, this study analyzes halocarbon concentrations and composition characteristics in Shanxi from 2018 to 2020, exploring their origins and the health effects. The total concentration of halocarbons has shown an overall increasing trend, which is driven by both regulated substances (CFC-11 and CFC-113) and unregulated substances, such as dichloromethane, chloromethane and chloroform. The results of the study also reveal that dichloromethane (1.194 ± 1.003 to 1.424 ± 1.004 ppbv) and chloromethane (0.205 ± 0.185 to 0.666 ± 0.323 ppbv) are the predominant halocarbons in Shanxi, influenced by local and northwestern emissions. Next, this study identifies that neighboring cities in Zhejiang Province and other YRD areas are potentially affected by backward trajectory models. Notably, chloroform and 1,2-dichloroethane have consistently surpassed acceptable thresholds, indicating a significant carcinogenic risk associated with solvent usage. This research sheds light on the evolution of halocarbons in the YRD region, offering valuable data for the control and reduction in halocarbon emissions.

Innovative tools suitable for chemical risk assessment are being developed in numerous domains, such as non-target chemical analysis, omics, and computational approaches. These methods will also be critical components in an efficient early warning system (EWS) for the identification of potentially hazardous chemicals. Much knowledge is missing for current use chemicals and thus computational methodologies complemented with fast screening techniques will be critical. This paper reviews current computational tools, emphasizing those that are accessible and suitable for the screening of new and emerging risk chemicals (NERCs). The initial step in a computational EWS is an automatic and systematic search for NERCs in literature and database sources including grey literature, patents, experimental data, and various inventories. This step aims at reaching curated molecular structure data along with existing exposure and hazard data. Next, a parallel assessment of exposure and effects will be performed, which will input information into the weighting of an overall hazard score and, finally, the identification of a potential NERC. Several challenges are identified and discussed, such as the integration and scoring of several types of hazard data, ranging from chemical fate and distribution to subtle impacts in specific species and tissues. To conclude, there are many computational systems, and these can be used as a basis for an integrated computational EWS workflow that identifies NERCs automatically.

This study aimed to evaluate the presence of various elements in edible insect-based food products available for human consumption. Several products were analyzed using atomic spectroscopy, and descriptive statistical analysis was conducted with IBM SPSS Statistics 27. The results revealed the presence of elements such as arsenic, cadmium, copper, magnesium, nickel, silver, lead, tungsten, uranium, mercury, platinum, aluminum, beryllium, bismuth, lithium, antimony, and thallium. Significant differences were found based on product type, insect species, and country of origin. The findings underscore the need to assess each insect species for its potential as a food source, taking into account element bioaccumulation factors. A comprehensive, global approach is essential for ensuring the food safety of edible insects as a sustainable protein source. Further research is needed to address these safety concerns.

The exacerbation of wildfires caused by global warming poses a significant threat to human health and environmental integrity. This review examines the particulate matter (PM) and gaseous pollutants resulting from fire incidents and their impacts on individual health, with a specific focus on the occupational hazards faced by firefighters. Of particular concern is the release of carbon-containing gases and fine particulate matter (PM_2.5) from forest fires and urban conflagrations, which exceed the recommended limits and pose severe health risks. Firefighters exposed to these pollutants demonstrate an elevated risk of developing pulmonary and cardiovascular diseases and cancer compared to the general population, indicating an urgent need for enhanced protective measures and health management strategies for firefighters. Through a meticulous analysis of the current research findings, this review delineates future research directions, focusing on the composition and properties of these pollutants, the impacts of fire-emitted pollutants on human health, and the development of novel protective technologies.

At present, soil contaminated with arsenic (As) and antimony (Sb) is escalating at an alarming rate, which is harmful to human health. In this study, Fe- and Mn-modified activated carbon (AC) and biochar (BC) were prepared and compared for the remediation of As- and Sb-contaminated soil. The effects on the speciation of As and Sb, soil pH, organic matter (SOM), and enzyme activity with various dosages and remediation times were investigated. The results showed that on the whole, the best stabilization effect of As and Sb was achieved with 3% FeMnBC. Furthermore, with increases in time and dosage, the immobilization effect on As and Sb was more significant. Fe/Mn-modified AC and BC enhanced soil pH, with 3% MnAC being particularly effective; 3% AC and 3% FeMnAC demonstrated the most pronounced enhancement in SOM. The modified carbon materials exhibited a dramatic increase in enzymatic activity. In particular, urease activity showed an increasing trend, and catalase activity first decreased and then increased over 30 days. Among the treatments, 3% MnAC showed the most significant enhancements in catalase and urease activities, whereas 1% FeMnBC had the most pronounced effect on increasing sucrase activity. This study provides theoretical support for the remediation of soil co-contaminated with As and Sb by Fe/Mn-modified AC and BC.