We examine and discuss the evolution and current state of chemical migration testing protocols for children’s toys, from early practices to present-day methods. Drawing from a synthesis of literature and comparisons with international standards such as European standard EN 71-10, the key factors influencing chemical migration testing are identified, including temperature, pH, duration of contact, choice of simulant, and agitation methods. We propose enhancements to existing protocols to improve accuracy and realism, such as adjusting the temperature to physiologic levels, incorporating pH adjustments, extending migration testing duration, and diversifying simulants. Moreover, we advocate for a more holistic approach to toy safety, considering interactions among multiple substances and age-specific vulnerabilities of children. Advancements in analytical technologies are also discussed as promising tools for enhancing testing sensitivity and specificity. We stress the urgency and necessity of global harmonization and collaborative solutions to ensure consistent standards and foster a safer environment for children worldwide. By aligning testing protocols, exchanging best practices, and leveraging technological innovations, stakeholders can prioritize children’s well-being and create a world where toys bring joy without compromising safety.

Photocatalytic oxidation through semiconductor photocatalysis is an efficient and green technology for pollutant removal, which has been widely applied to degrade volatile organic chemicals under ambient conditions. However, most of reports focus on the reduction of VOCs concentration while ignore the generation of toxic intermediates, as well as the corresponding secondary pollution. Therefore, it is necessary to further explore how to timely achieve efficient and deep oxidation of VOCs. In this review, we undertake a detailed analysis of photocatalytic degradation of toluene, a representative compound of aromatic hydrocarbon VOCs, and identify the most capable phenolized pathway governed by hydroxyl radicals (•OH). With this pathway, no toxic intermediate like benzene is produced during the photocatalysis. The driving factor, oxygen vacancy (OV), for fueling the generation of •OH is highlighted and the specific approaches including doping engineering and co-catalyst loading that can create rich OVs in semiconductor photocatalysts are described. Furthermore, the challenges and opportunities faced by the phenolized pathway in the future development are prospected.

Most hyperaccumulator and economic crops do not grow year-round, leading to limited remediation efficiency. Implementing year-round rotation patterns with known and potential hyperaccumulators or economic crops can improve remediation efficiency. This study evaluated the remediation efficiency and agricultural safety of 10 winter crops and 12 summer crops in field-scale trials. Sedum alfredii Hance (SA) and Cichorium intybus L. (CI) exhibited the highest cadmium (Cd) accumulation among winter crops, reducing soil Cd content by 12.1% and 10.4%, respectively. Helianthus annuus Linn. (HA) was the most effective summer crop, reducing soil Cd content by 3.7%. The vegetable oils of all oil crops were within safe heavy metal limits, whereas the edible parts of other economic crops exceeded Cd limits. A combination of the best winter and summer crops was chosen to comprehensively evaluate the remediation efficiency and economic benefits of three rotation patterns: SA + HA, CI + HA, and Linum usitatissimum L. (LU) + HA. SA + HA and CI + HA were more effective than LU + HA, reducing soil Cd by 12.5%, 8.9%, and 3.7%, respectively. The net profits were −27591.19, 749.50, and 3309.76 US$/ha, respectively. Overall, CI + HA demonstrated the highest combined capacity (comprehensive index = 1.79) for both remediation efficiency and economic benefits, achieving safe production and effective restoration of Cd-contaminated agricultural land. However, the accumulation of heavy metals in oilseed meals warrants further attention.

Combining pulverized coal gasifiers with cement kiln production is promising for application in low-cost and efficient NO reduction. This paper presents a pulverized coal gasifier catalytic denitration technique and investigates the homogeneous reduction (by CO and CH₄) and heterogeneous catalytic reduction (by coke, CaO, MgO, and Fe₂O₃) of NO. A combination of Chemkin simulations and fixed-bed experiments is used to elucidate the reaction pathways and key intermediates of NO reduction by carbon-based gases. In addition, the activation energies for different catalyst combinations were analyzed via reaction kinetics. The results demonstrate that the presence of small amounts of O₂ inhibits NO reduction by CO but promotes NO reduction by CH₄. The NCO• radical is essential for the NO reduction process, and the generation of this radical depends on the CH₄ cleavage intermediate and O• radical. CaO and Fe₂O₃ exhibit more significant catalytic effects on NO reduction by carbon-based gases than the other catalysts tested. The presence of a small amount of O₂ in the reacting gas mixtures facilitates the NO reduction reaction. The activation energy is reduced to 1.02 kJ/mol, and the NO conversion reaches 99.80% when the catalyst is C + CaO + MgO + Fe₂O₃ and the gas composition is CO + CH₄ + O₂. This work provides theoretical support and data recommendations for the use of pulverized coal gasifiers for the denitrification of cement kilns.

Chemical stabilization has been widely applied to stabilize various heavy metals in soil, but there have been few systematic investigations of in situ stabilization at practical contaminated sites. In this study, batch experiments were conducted to investigate the stabilization effect of heavy metals in soil from an iron-smelting site using multiple materials. The results showed that FeSO₄ simultaneously reduced the bioavailable heavy metal (BHM) concentrations of Pb, Zn, and As by 61.1%, 28.1%, and 68.6%, respectively. Therefore, FeSO₄ was further applied at the practical contaminated site. Experimental results indicated that the heterogeneous distribution of stabilization efficiency deviated from that of batch experiments, which were influenced by multiple factors. Compared to the control group, the bioavailable Pb, Zn, and As concentrations decreased by 23.1, 13.6, and 4.73 mg/kg, respectively, when the injected FeSO₄ concentration was 0.27 mol/L in the saturated zone. The decreased concentrations of bioavailable Pb, Zn, and As decreased with the distance from the injection well, showing a limited radius of influence at 1.0–2.0 m, larger than the theoretical value (0.92 m). Correlation analysis revealed a significant negative relationship between the change in BHM content and the fraction of BHM content before stabilization (FB), indicating that FB significantly controlled the stabilization efficiency. While excess injected FeSO₄ had only a slight influence on the stabilization efficiency of heavy metals, it negatively impacted groundwater. This study provides new perspectives for in situ stabilization and highlights the importance of pilot-scale experiments over batch experiments for guiding engineering activities.

Landfilling remains the primary disposal method for fly ash produced from municipal solid waste incineration (MSWI) following stabilization/solidification. However, the increasing generation of stabilized fly ash (SFA) is accelerating the depletion of landfill capacity. Furthermore, the small particle size and low bulk density of SFA present significant environmental risks during handling and transportation. To mitigate these issues, a cost-effective compaction method was introduced into the SFA disposal process. The results show that SFA from both grate furnaces and fluidized bed incinerators exhibited high porosity, loose structure, and irregular particle morphology, indicating substantial potential for compaction. Key parameters influencing compaction effectiveness included compaction pressure, holding duration, and moisture content, with optimal values identified as 100–200 MPa, 20 s, and 10%–15% moisture, respectively, depending on the incinerator type. After compaction treatment, the density of SFA more than doubled, while its volume was reduced by over 60%, significantly increasing landfill capacity and enhancing the efficiency of SFA disposal. The compaction process was effectively modeled using the Huang Peiyun equation for gerate furnace ash and the Heckel equation for fluidized bed ash. Furthermore, the unconfined compressive strength and three-point bending strength of compacted SFA met the MU10 standard for lime-sand bricks, making the material suitable for transportation and disposal. Finally, the compaction-based disposal method for SFA demonstrated clear techno-economic advantages and significant potential for broader application in waste management strategies.

Microorganisms are essential contributors to the forest ecosystems of the Qinghai-Xizang Plateau, encompassing generalists, intermediates, and specialists. Investigating the characteristics and drivers of these microbial sub-communities across varying elevations is essential for understanding their ecological functions in high-altitude forest soils. This study examines the diversity patterns, assembly processes, environmental adaptations, and potential functions of bacterial and fungal sub-communities along an elevation gradient from 3900 m to the timberline on Shergyla Mountain, China. The findings revealed notable differences between low and high elevations in the diversity and composition of microbial sub-communities. According to neutral and null models, generalists, characterized by the widest niche width and highest migration rates, were primarily influenced by stochastic processes (71.9%). In contrast, deterministic factors, including homogeneous and variable selection, exerted a stronger effect on the assembly of specialists (51.0%). Elevation and nutrient availability emerged as key environmental drivers shaping microbial sub-communities, particularly for specialists, while generalists experienced fewer constraints from environmental factors. Network analysis further demonstrated that habitat specialists occupy central positions within microbial networks, playing a pivotal role in maintaining network stability. Additionally, nitrogen cycling genes—specifically nifH, amoA, nirS and nosZ—exhibited a U-shaped distribution across the elevation gradient and showed a substantial correlation (p < 0.05) with the Chao1 and Shannon indices of bacterial specialists. The results enhance our knowledge of microbial community dynamics and underscore the crucial ecological role of microbial specialists in the ecosystems of high-altitude forests.

Gasoline vapor emissions from service stations significantly affect urban atmospheric. Despite the research on the mechanisms and effectiveness of gasoline vapor removal is limited, this study innovatively investigates the static and dynamic adsorption of xylene—a typical gasoline vapor and one of the most active secondary organic aerosol (SOA) species—by commercial activated carbon (AC). The results showed that the saturation static adsorption capacity (Q_e) of 12 ACs varied from 0.9 to 870.7 mg/g, which correlated with the specific surface area (SSA) and pore volume. Among them, 11# and 12# ACs were identified as the most effective adsorbents for typical gasoline vapor removal. The maximum dynamic Q_e increased from 301.5 to 414.3 mg/g when the initial xylene concentration rose from 918 to 2008 mg/m³ for 11# AC, and from 201.4 to 406.2 mg/g when the initial xylene concentration increased from 589 to 2120 mg/m³ for 12# AC. These findings implied a direct correlation between higher initial xylene concentrations and greater dynamic Q_e values, with static Q_e values surpassing dynamic values. The adsorption kinetics simulation were analyzed by the pseudo-first-order (PFO) and pseudo-second-order (PSO) kinetics. The kinetics results demonstrated that the PFO was more effective in characterizing the adsorption of xylene onto ACs (R² > 0.989), indicating that the adsorption of typical gasoline vapor by ACs primarily involves physical adsorption. The findings of static/dynamic adsorption and kinetics provide valuable guidance for practical applications of gasoline vapor removal in service stations.

Antibiotics, endocrine-disrupting compounds (EDCs), per- and polyfluoroalkyl substances (PFAS), and microplastics (MPs) are crucial constituents of the pollutants frequently detected in various aquatic environments. These pollutants can negatively affect human health and aquatic organisms. To eliminate these new pollutants from water economically and environmentally, biochar is considered an efficient environmental functional material because of its excellent performance. Although numerous studies have reported the concentration, distribution, and removal methods of individual new pollutants, a comprehensive and systematic understanding of biochar-based materials for the removal of multiple new pollutants from aquatic environments remains to be comprehensively explored. Therefore, in this mini-review, recent research progress on biochar materials in the decontamination of new pollutants, including antibiotics, EDCs, PFAS, and MPs in different water sources, is summarized, and different mechanisms and influencing factors during the removal process are discussed to have a profound understanding of the application of biochar in the water environment. Future studies on biochar materials for the removal of new pollutants are indicated to enlighten future exploration and alleviate new pollutant burdens in aquatic environments.

Membrane fouling poses a significant challenge to the sustainable development of membrane bioreactor (MBR) technologies for wastewater treatment. The accurate prediction of the membrane filtration process is of great importance for identifying and controlling fouling. Machine learning methods address the limitations of traditional statistical approaches, such as low accuracy, poor generalization ability, and slow convergence, particularly in predicting complex filtration and fouling processes within the realm of big data. This article provides an in-depth exposition of machine learning theory. The study then reviews advances in MBRs that utilize machine learning methods, including artificial neural networks (ANN), support vector machines (SVM), decision trees, and ensemble learning. Based on current literature, this study summarizes and compares the model input and output characteristics (including foulant characteristics, solution environments, filtration conditions, operating conditions, and time factors), as well as the selection of models and optimization algorithms. The modeling procedures of SVM, random forest (RF), back propagation neural network (BPNN), long short-term memory (LSTM), and genetic algorithm-back propagation (GA-BP) methods are elucidated through a tutorial example. The simulation results demonstrated that all five methods yielded accurate predictions with R² > 0.8. Finally, the existing challenges in the implementation of machine learning models in MBRs were analyzed. It is notable that integration of deep learning, automated machine learning (AutoML) and explainable artificial intelligence (XAI) may facilitate the deployment of models in practical engineering applications. The insights presented here are expected to facilitate the establishment of an intelligent control framework for MBR processes in future endeavors.

Dissolved organic matter (DOM) participates in and affects many biological processes in aquatic ecosystems, altering nutrient cycling, bioavailability and toxicity of pollutants. Lake water contains thousands of DOM molecules, which largely originate from natural sources and are greatly influenced by external inputs through anthropogenic activities. To elucidate the shaping mechanism of the DOM composition under complex habitat conditions and anthropogenic disturbances, the characteristic molecular fingerprint of DOM was determined based on chemodiversity information obtained via ultrahigh-resolution mass spectrometry for the Baiyangdian wetland (a typical large macrophytic shallow lake in North China). In the Baiyangdian wetland, the DOM composition exhibited high complexity and spatial heterogeneity, and more recalcitrant DOM molecules were identified in summer than in spring. Although multiple natural factors (nutrient concentration, depth of water and quality of submerged macrophytes) and anthropogenic factors (different land uses and discharge of pollutants) were associated with the relative abundance of various DOM molecules, only the influences from the anthropogenic factors were statistically significant. The alpha diversity index of DOM could reflect variations in both the natural factors (total dissolved phosphorus) and the anthropogenic factors (discharge of nitrogen and phosphorus). Furthermore, the DOM composition in each group were clustered according to the ecological functions (natural reserves, tourism, breeding, and domestic supply functions), and exhibited molecular fingerprint features. This study provides an effective approach to characterize the molecular fingerprint features of DOM and critical information to better understand the shaping mechanism of the DOM composition under complex habitat conditions and anthropogenic disturbances.

Iron corrosion in drinking water distribution systems (DWDSs) is the root cause of the deterioration of drinking water quality. Humic acid (HA) is a critical component of dissolved organic matter in drinking water. However, the influences of HA on iron pipe corrosion in DWDSs have not been fully understood, especially the combined effects of corrosive microorganisms and HA with different molecular weights (MWs). This study used bench-scale reactors to explore the impacts of iron-oxidizing bacteria (IOB) (Microbacterium oxydans ZT-1, a common iron-oxidizing bacterium) and HA with different MWs on iron pipe corrosion. Before 6 d, loose and porous goethite (α-FeOOH) was the most prevalent compound in the corrosion products. The addition of ZT-1 and HA promoted iron corrosion and release. Under the condition of ZT-1 + > 100-kDa HA, the maximum values of corrosion rate and total iron concentrations were 0.23 mm/a and 9.94 mg/L, respectively. As corrosion proceeded, magnetite (Fe₃O₄) formed from FeOOH, and Fe-HA complexes accumulated, resulting in deceleration of iron corrosion. After 54 d, the corrosion rate and total iron concentration had decreased by ZT-1, and HA with different MWs.

Chlorite (ClO₂⁻ or COI) is used to establish the advanced reduction and oxidation process (AROP). The iron/biochar-based particles (iron-based hydrothermal carbon with hinge-like structure, Fe_bHCs, 20 mg/L) can be utilized to activate COI (2 mmol/L) to present selective oxidation in removing triphenylmethane derivatives (15 min, 90%). The protonation (H⁺ at ~10² μmol/L level) played a huge role (k-2^nd = 0.136c-H⁺ − 0.014 (R²-adj = 0.986), and r_app = − 0.0876/c-H⁺ + 1.017 (R²-adj = 0.996)) to boost the generation of the active species (e.g., high-valent iron oxidizing species (HVI=O) and chlorine dioxide (ClO₂)). The protonation-coupled electron transfer promoted Fe-substances in Fe_b/HCs activating COI (the calculated k_obs ranging from 0.066−0.285 min⁻¹). The form of ClO₂ mainly attributed to proton-coupled electron transfer (1e/1H⁺). The HVI=O was generated from the electron transfer within the coordination complex. Moreover, carbon particles in Fe_bHCs serve as the bridge for electron transfer. The above roles contribute to the fracture and formation of coordination-induced bonds between L_x-Fe^II/III and ClO₂⁻ at phase interface to form AROP. The ultrasonic (US) cavitation enhanced the mass transfer of active species in bulk solution, and the HVI=O and ClO₂ attack unsaturated central carbon atoms of triphenylmethane derivatives to initiate selective removal. Furthermore, the scale-up experiment with continuous flow (k values of approximately 0.2 min⁻¹, COD removal efficiency of approximately 80%) and the reactor with COMSOL simulation have also proved the applicability of the system. The study offers a novel AROP and new insights into correspondingly heterogeneous interface activation mechanisms.

Iron-based nanoparticles (Fe-NPs) exhibit promising potential for soil remediation. However, their toxic effects on plants have also been reported. Typical Fe-NPs have been introduced into soil–plant systems to examine their possible nanotoxicity and other impacts on plants, while Fe-NPs have been added to pollutant–soil–plant systems to evaluate their performance as remediation agents. Mixed opinions and results have been reported regarding interactions between Fe-NPs and soil or plants. Here, meta-analysis was conducted to evaluate the effects of Fe-NPs on plant morphological and physiological characteristics in soil–plant and pollutant–soil–plant systems. Interestingly, morphological characteristics (dry and fresh weight) were significantly improved by Fe-NPs in both soil–plant and pollutant–soil–plant systems. In terms of plant physiological characteristics, Fe-NPs exerted negative effects on plant pigments in soil–plant systems, but positive effects in pollutant–soil–plant systems. In addition, Fe-NPs greatly increased the Fe contents and decreased the pollutant contents of plants. This study also provides a comprehensive review of the positive and negative effects of Fe-NPs on soil–plant systems and summarizes the pollutant remediation mechanisms of Fe-NPs in soil–plant systems. The results underscore the potential of Fe-NPs in agricultural applications and the future development of food safety.

Insights into the microbial communities in municipal wastewater treatment plants (WWTPs) are critical for the optimization of biological nutrient removal process. However, our understanding about the spatiotemporal characteristics of the microbial communities in WWTPs remains limited. In the present study, 264 samples were collected biweekly from four spatially independent corridors in a typical municipal WWTP. The annual compositional and metagenomic characteristics were investigated based on multiple ecological indicators using statistical tests. The results revealed that the microbial community compositions from the four corridors showed significantly high similarities, as revealed by the statistical analysis at the operational taxonomic unit (OTU) level. Consistent with the OTU level results, the functionality of the microbial communities in the four independent corridors also showed significant similarity. In comparison, the dynamics of the microbial community over the year showed two successional peaks of the microbial communities with the spatial similarity, and this resulted in three alternative stable states of the microbial communities in a calendar year. The microbial communities only drifted in July and November, suggesting an uneven community succession pattern driven by seasonal variation in environmental conditions. The functional characteristics were found to be relatively conservative compared to the microbial community succession, which revealed the decoupling between the composition and functionality of the microbial community in the municipal WWTP. The present study provides an in-depth overview of the microbial communities in a municipal WWTP and will be useful for the establishment of the connection between ecological characteristics and the operational stability of WWTPs.