Journal of hazardous materials最新文献

Antibiotics are emerging pollutants that adversely affect microbial activity, disrupt nitrogen cycling, and reduce overall system performance in aquaponic systems. This study assessed the performance of media-based aquaponic systems amended with biochar mixed with zero-valent iron (BC/ZVI) under treatments with oxytetracycline (BZ-OTC), sulfadiazine (BZ-SDZ), and amoxicillin (BZ-AMX). Results demonstrated that the BZ-SDZ consistently outperformed the others by mitigating the harmful effects of sulfadiazine, achieving > 99 % antibiotic removal, producing the highest spinach biomass (25.40 ± 3.68 g), promoting the greatest fish growth (24.11 ± 0.44 g) and minimizing nitrous oxide (N₂O) emissions. These benefits are attributed to ZVI-driven redox reactions degrading residual SDZ and biochar's adsorption capacity reducing antibiotic bioavailability to plants and microbes. In contrast, the BZ-OTC showed moderate improvements, while BZ-AMX exhibited the least efficacy. Overall, BC/ZVI media enhanced nutrient use efficiency, system stability, and microbial diversity under antibiotic stress, providing a reliable strategy for sustainable aquaponic production in contaminated environment.

The use of multiple pesticides in agriculture has caused mixed residues, complicating food safety testing. Surface-enhanced Raman scattering (SERS) offers high sensitivity and fingerprinting capabilities for pesticide detection; however,its application is limited by spot size, uneven sample distribution, spectral analysis challenges in mixed samples, and the lack of integrated automated systems for sample preparation, detection, and analysis. Hence, we developed a SERS microfluidic chip integrated with plasmonic microsphere lens arrays, which integrates optical field-modulated microspheres and plasmonic nanostructures to realise the transition of SERS detection from point-hotspots to uniform area-hotspots, achieving high-sensitivity, high-stability Raman detection under wide-field laser excitation. Moreover, a comprehensive a sample-to-answer total analysis system was established with this chip as the core, incorporating the micro-QuEChERS pretreatment module for efficient extraction of pesticides in complex matrices and the random forest-dual annealing spectral parsing algorithm for mixed spectral analysis. The results indicate that the limits of detection for 2,4-dichlorophenoxyacetic acid, acetamiprid, and thiabendazole were 1.15 nM, 0.63 nM, and 0.69 nM, respectively. The linear ranges were 10⁻⁴-10⁻⁹ M, with R² values of 0.9982, 0.9989, and 0.9996, respectively. Average recoveries ranged from 90.8 % -104.66 %, 89.1 %-107.89 %, and 89.73 %-108.4 %, respectively, with relative standard deviations below 8 %. The algorithm quantified mixed pesticides with mean absolute percentage errors of 4.96 %, 5.35 %, and 7.72 %, respectively. The system showed 3 s detection response and 15-minute analysis time. Thus, the method provides a rapid, on-site solution for detecting mixed pesticides in complex matrices by exceptional optical performance and automated processing functionality.

The settling velocity of atmospheric particles in seawater is a key determinant of the ecological impact of atmospheric deposition on marine ecosystems, as it regulates particle residence time and bioavailability in the upper ocean. Settling velocity is primarily governed by particle diameter, shape, and density, however, accurate prediction remains challenging because of the heterogeneous morphology and composition of atmospheric particles. To address this challenge, we developed an interpretable Random Forest model trained on laboratory settling experiments. The model predicts particle settling velocity based on dimensionless diameter (D*), organic matter content (OM), and Corey shape factor (csf), achieving high accuracy (R² > 0.86) relative to theoretical formulations. SHapley Additive exPlanations (SHAP) analysis indicates that particle diameter is the dominant factor influencing dimensionless settling velocity (W*), contributing over 80 %. However, D* exerts weak, stable negative marginal impacts on W* when D* < 0.30 (salinity 0, 10) or D* < 0.25 (salinity 20, 30). Beyond these thresholds, its positive marginal contribution to W* increases markedly. Particle shape exerts a significant influence on W* only when D* exceeds the above thresholds across all four salinity conditions. Organic matter exerts a significant effect under high-salinity conditions. Building on the results, we refined the existing empirical formulation by re-fitting drag coefficient (C_D)-Reynolds number (R_e) relationships separately for low and high-salinity waters, reducing mean squared error (MSE) by 43-58 % while maintaining a high R² of 0.83-0.85. This refinement enables more accurate prediction of atmospheric particle residence time in the upper ocean.

Background: Diabetes and hypertension are major chronic diseases with growing public health significance. Ozone (O₃) pollution has increased in recent years, yet its long-term impact on these outcomes remains unclear.

Methods: This 8-year prospective cohort study included 71,784 middle-aged and older adults in the Tianjin Binhai New Area who were followed up annually. Warm-season (May-October) O₃ exposure was estimated using a satellite-based model. Time-varying Cox proportional hazard models were applied to examine the risk of diabetes and hypertension associated with O₃ exposure. Exposure-response (E-R) relationships, stratified analyses and population attributable fractions (PAFs) under counterfactual scenarios were conducted. Mediation analyses were further conducted for white blood cells (WBC), platelet-to-lymphocyte ratio (PLR), triglycerides (TG), total cholesterol (TC), and total bilirubin (TBIL).

Results: During follow-up, 8662 diabetes and 15,396 hypertension new-onset cases occurred. Each 10 μg/m³ increase of warm-season O₃ exposure was positively associated with higher incidence of diabetes (HR = 1.124, 95 % CI: 1.053-1.199) and hypertension (HR = 1.128, 95 % CI: 1.056-1.204). E-R relationships curve linear associations. O₃-related hypertension risk was great among adults < 65 and diabetes risk was higher in overweight individuals. The PAFs were 22.51 % for diabetes and 19.08 % for hypertension. Inflammatory (WBC, PLR) and metabolic (TG) markers mediated part of the effects, and TBil (oxidative stress) showed a minimal contribution.

Conclusion: Long-term O₃ exposure was associated with increased risks of diabetes and hypertension, partially mediated through inflammatory and metabolic pathways. These findings support stringent O₃ control and biomarker-based risk assessments in chronic disease prevention.

Background: The prevalence of myopia has risen sharply among children in East Asia, emerging as a major public health concern. While genetic and behavioral factors are established contributors, accumulating evidence indicates that air pollution may also play a role in myopia development.

Methods: This nationwide longitudinal cohort study utilized data from South Korea's National Health Insurance Service-National Sample Cohort (NHIS-NSC). A total of 94,830 children aged 6-12 years without major ocular disorders were followed from 2003 to 2019. Myopia onset was defined as the first hospital visit with a primary diagnosis code for myopia. Time-varying two-year moving averages of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations were assigned as exposures and analyzed using a Cox regression model, adjusting for individual- and district-level covariates.

Results: Over 784,349 person-years of follow-up, 35,918 children developed myopia. Each 5 µg/m³ increase in PM_2.5 and 5 ppb increase in NO₂ was associated with hazard ratios (HRs) of 1.030 (95 % CI: 1.003-1.058) and 1.031 (95 % CI: 1.010-1.052), respectively. Greater susceptibility to air pollution-related myopia was observed among boys, younger children, and urban residents compared with girls, older children, and rural residents, although the difference by sex was not statistically significant. These associations remained robust across multiple sensitivity analyses.

Conclusions: Long-term exposure to PM_2.5 and NO₂ was significantly associated with an increased risk of myopia in children. By combining a nationwide longitudinal design with high-resolution machine learning-based exposure estimates, this study provides novel evidence linking chronic air pollution exposure to pediatric visual health.

Pesticides have traditionally been detected based on the inhibition of natural acetylcholinesterase enzyme activity by pesticides. This approach was costly, offered limited detection coverage for pesticides, and suffered from the inherent instability of natural enzymes. To address the instability issue in sensor arrays, artificially synthesized nanozymes with enzyme-like activities were constructed in the sensor array. The diverse enzyme-like activities of nanozymes provide an excellent foundation for developing multi-channel sensor arrays. A four-channel sensor array was constructed based on multienzyme-like activities for the identification and discrimination of nine pesticides. An accurate distinction was achieved for 5 categories of pesticides using the constructed multienzyme-like sensor array method. In addition, a concentration-independent identification model of pesticides based on machine learning was constructed to simulate the detection situation in real environments, with an accuracy of 99.20 %. The proposed sensor array has great practical application prospects to be widely used for the detection of pesticides on food surfaces and in the water environment due to its excellent anti-interference capability.

Hydroxyl radicals (^•OH) is one of the prime reactive species for abiotic transformations of pollutants during redox oscillation in paddy wetland‌. However, the effect of O₂ diffusion rates in wetland on ^•OH generation, as well as its subsequent effects on pollutant removal, remains largely uninvestigated. This study reveals a significant promotion of ^•OH generation and nonphotochemical transformations of organic pollutants by controlling O₂ permeability rates combining in-situ experiments. Batch experiments confirmed that air supply rates determined the generation rates of ^•OH (7.7 ± 0.48-58.04 ± 5.01 μM h^-1), but did not alter the cumulative concentration of ^•OH upon complete oxidation of soil. Interestingly, despite no significant difference in cumulative ^•OH concentration among different air supply rates, higher air supply rates resulted in more efficient pollutant degradation. The presence of soil organic matter, especially dissolved organic matter (DOM), is a key cause of the hindered imidacloprid removal under low air supply rates. Coupled with Fourier transform ion cyclotron resonance mass spectrometry, we found that the lability of DOM increased during the oxidation period, which proved the potential reaction between DOM and ^•OH. In summary, our study links two previously isolated factors (O₂ supply and soil fractions) and enriches the understanding of multi-factor regulatory mechanisms of the contaminant fates in paddy fields. Importantly, increasing O₂ supply and transfer is low-cost and sustainable strategies for soil remediation in subsurface environments with frequent redox fluctuations.

Nitrogen oxides (NO_x), primarily NO from high-temperature fuel combustion, pose serious threats to ecological and human health. Photocatalysis offers a solar-driven approach for NO oxidation, but often leads to toxic NO₂ byproduct due to insufficient active sites and reactive oxygen species (ROS). In this study, the tri-synergetic photocatalyst was developed that integrated the internal electric field (IEF) of AgCl/ZnSn(OH)₆ heterojunction, the surface plasmon resonance (SPR) effect of Ag nanoparticles and the spin polarization effect of Co clusters to realize the rapid separation and transport of photogenerated charges. Experimental and theoretical calculations confirmed that IEF promotes the directional migration of electrons, Ag nanoparticles extends visible light absorption and increases charge density through the SPR effect, and Co clusters acts as electron trap facilitating interfacial transfer after illumination. The Co clusters also caused spin polarization effect to promote exciton separation and became an activation center that enhanced the adsorption and activation of O₂ and H₂O to promote the generation of ROS, and also promote the adsorption and activation of NO to become the intermediate NO^-, which could quickly react with ROS to generate NO₃^- by one step, suppressing the release of NO₂ toxic byproducts. The charge transport mechanism and activation mechanism of the tri-synergistic photocatalyst have important reference significance for the design of photocatalyst for efficient removal of air pollutants.

The effects of exposure to air pollution on epigenetic age acceleration remain unclear. This study investigated the associations between exposure to six air pollutants (PM_2.5, PM₁₀, CO, NO₂, SO₂, and O₃) and DNA methylation age using multiple epigenetic clocks, including Horvath (353 CpGs), Best Linear Unbiased Predictor (BLUP, 319,607 CpGs), and Elastic Net (EN, 514 CpGs) among 2462 participants from the Taiwan Biobank. Both PM_2.5 and PM₁₀ exposure showed significant associations with all three epigenetic clocks. In multi-pollutant models combining PM_2.5 with other pollutants, the associations remained significant. The weighted sum of all air pollutants showed significant associations with all three epigenetic clocks. Weight distribution analyses identified PM_2.5 and PM₁₀ as the predominant contributors across all clock models. These results underscore the importance of air pollution control as a key component of public health strategies aimed at promoting healthy aging.