To reveal the microbial community structure and functional characteristics in different types of industrial wastewater treatment plants, this study selected three representative facilities in Xiamen—a food-processing plant, a semiconductor plant, and a comprehensive industrial park. Based on high-throughput sequencing and multiple analytical approaches, the diversity, community composition, and metabolic potential of activated sludge microorganisms were systematically compared. The results demonstrated that different types of industrial wastewater significantly influenced microbial community composition, with water quality parameters such as COD, TN, and TP playing critical roles in shaping community structure. While Proteobacteria was the dominant phylum shared across all three plants, Firmicutes, Patescibacteria, and Deinococcota were identified as characteristic phyla in the food, industrial park, and semiconductor plants, respectively. Functional gene prediction revealed distinct differences in the abundance of metabolic pathways among the plants, with the microbial community in the semiconductor plant showing notably lower abundance in pathways related to organic matter degradation. Overall, the structure and function of microbial communities were strongly driven by wastewater characteristics, and the identified key taxa provide a theoretical basis for optimizing industrial wastewater treatment systems.

The aim of this study was to investigate the performance of calcination-modified Drinking Water Treatment Residual (DWTR) in removing typical pollutants in stormwater. The results showed that the aluminium contents of DWTR were as high as 14g/kg, which were significantly higher than that of general soil, and the XRD pattern showed higher alumina peaks, and the calcination modification could further improve the specific surface area and surface characteristics of the sludge; the isothermal adsorption characteristics of DWTR for the typical stormwater pollutants of phosphate, ammonia, nitrogen, and lead ions were better fitted to both Langmuir and Freundlich model, and the results of kinetic experiments showed that the adsorption process was more in line with the quasi-secondary kinetic model, indicating that the adsorption process was dominated by chemical adsorption and accompanied by physical adsorption, and the adsorption performance of calcined modified sludge was generally better than that of air-dried and screened sludge only, and the morphology analysis showed that more adsorbed lead could exist in the relatively stable carbonate-bound state of lead; The adsorption performance of soil columns based on the substrate of sludge from a water purification plant for typical The soil columns based on the water purification plant sludge matrix could remove 100%, 98%, 86.94% and 85% of the typical rainwater pollutants (orthophosphate, lead ion, ammonia nitrogen, COD), and 59% to 78% of the natural rainfall and rooftop rainfall in Beijing with a COD of 65~85mg/L, and the effluent could meet the environmental quality standard of 30mg/L for surface water IV, which indicated that both air-dried sieved and calcined modified sludge have the potential to be used for the treatment of water purification plant sludge. This indicates that both air-dried and calcined water purification plant sludge have the potential to be used as urban artificial wetland substrate for soil replacement and rainwater purification.

A composite of cubic spinel MnFe₂O₄ and carbon nanotubes (CNTs) was synthesized, denoted MnFe₂O₄/CNTs. This study evaluates the efficacy of MnFe₂O₄/CNT for electrocatalytic degradation of phenol, investigating the mechanism of electrocatalytic oxygen reduction to generate H₂O₂ and its subsequent activation into ·OH. The aim is to identify a highly efficient and stable cathode material suitable for electrocatalytic degradation of organic pollutants. Results demonstrate that under optimized conditions (MnFe₂O₄:CNT mass ratio = 19:2, applied voltage = -0.9V, pH = 3, catalyst loading = 0.44mg/cm², O₂ flow rate = 0.5L/min), MnFe₂O₄/CNTs achieved a remarkable phenol degradation efficiency of 99.9% within 30minutes and a total organic carbon (TOC) removal rate of 72.4% after 90minutes. Notably, the composite maintained 84.5% degradation efficiency of phenol after five consecutive cycles. The incorporation of CNTs not only improve electron transfer efficiency within the system, but leads to electron transfer between MnFe₂O₄ and CNTs induces an increase in the relative concentration of non-lattice oxygen species within MnFe₂O₄. Under the above dual effects, MnFe₂O₄/CNTs boost the capability to electrocatalytically reduce O₂ to H₂O₂ and subsequently activate it in situ to generate ·OH, surpassing the performance of pristine MnFe₂O₄. The activation of H₂O₂ is mainly accomplished through a combined process of homogeneous activation involving Mn²⁺ and Fe²⁺ and heterogeneous activation excited by active sites such as non-lattice oxygen in MnFe₂O₄/CNT. The ·OH generated by the activation achieves a relatively thorough oxidation and decomposition of phenol.

A novel exogenous oxidant-free Fenton-like reaction system based on vacuum ultraviolet (VUV)/Fe²⁺/oxalic acid (Ox) was constructed and applied to the degradation of azo dye Acid Red G (ARG). Results indicated that this system enabled the dynamic release of H₂O₂, which further reacts with Fe²⁺ to trigger Fenton-like reactions, and maintained high reactivity over a wide pH range. Experimental data showed that under the conditions of initial ARG concentration of 60mg/L, Fe²⁺ concentration of 0.06mmol/L and Ox concentration of 0.7mmol/L, the ARG removal efficiency by the VUV/Fe²⁺/Ox system reached 96.2% within 5min, and the degradation process fitted well with the pseudo-first-order kinetic model. With the increase of initial solution pH, the ARG removal efficiency exhibited a decreasing trend. Even at pH=7, the first-order rate constant k still reached 0.454min^-1, which was 69.6% of that at pH=3, demonstrating that the system could retain high reactivity under neutral conditions. During the initial 5min of the reaction, the concentration of H₂O₂ in the system gradually increased to a maximum of 62.5μmol/L, then decreased slowly and remained at 51.8μmol/L at 9min. Free radical trapping experiments and the electron paramagnetic resonance (EPR) measurements collectively confirmed that hydroxyl radicals (·OH) and superoxide radicals (O₂^·-) were the dominant reactive oxygen species (ROS). In addition, common inorganic anions in aqueous environments (HCO₃^-, NO₃^-, Cl^-, SO₄^2-) all inhibited ARG degradation to varying degrees. Analysis via UV-visible absorption spectroscopy and liquid chromatography-mass spectrometry (LC-MS) revealed that ROS generated during the degradation process attacked the azo bonds and benzene ring structures in the ARG molecule, thereby achieving decolorization and removal of the dye.

A technique combining ultrasonic-assisted Fenton oxidation for the degradation of tri(2-chloroethyl) phosphate (TCEP) was developed. The Box-Behnken response surface method was used to optimize the reaction parameters. The degradation pathways and ecological toxicity changes of TCEP were investigated using density functional theory (DFT) calculations, liquid chromatography-mass spectrometry (LC-MS) analysis, and toxicity software (T.E.S.T.). The results indicated that under optimal conditions (initial pH = 3, ultrasonic power of 360W, and oxidant dosage of 400mg/L), the ultrasonic-Fenton system was capable of effectively degrading TCEP, achieving a degradation rate of 85.8%. Reactive species in the system, such as hydroxyl radicals, preferentially attacked the reaction sites in the TCEP molecules with lower Laplace bond order (LBO) values (weaker chemical bonds), higher negative surface electrostatic potential (ESP) values (higher electron density), and lower reaction energy barriers (easier reaction occurrence), such as the P-O bond cleavage energy barrier of 126.56kJ/mol and the dechlorination reaction energy barrier of 150.79kJ/mol. LC-MS analysis confirmed that the primary degradation pathways of TCEP involved P-O bond cleavage and dechlorination. Toxicity assessment showed that TCEP itself exhibited high bioaccumulation potential and mutagenicity. Hydroxylated intermediates generated during the initial degradation phase exhibited significantly increased toxicity, with the oral LD₅₀ in rats reaching the "toxic" level defined by T.E.S.T. (LD₅₀<50mg/kg), and potential developmental toxicity. However, toxicity was significantly reduced after complete mineralization. The predictive modeling approach provided convenient and effective theoretical support for the degradation pathways and ecological toxicity evaluation of TCEP.

Polyacrylonitrile (PAN)/polyethyleneimine (PEI) composite nanofiber membranes fabricated via electrospinning were systematically investigated for their adsorption performance and mechanisms toward perfluorooctanoic acid (PFOA). Results showed that when PEI content was 3%, the material achieved the highest saturated adsorption capacity of 1145.55mg/g for PFOA, significantly exceeding samples with lower PEI contents. The adsorption process adhered to the Langmuir monolayer adsorption model, with optimal efficiency observed under acidic conditions (pH = 3), primarily relying on electrostatic interactions between protonated PEI amines and PFOA. Coexisting humic acid (HA) and ions (e.g., Ca²⁺, Mg²⁺, Fe³⁺, HCO₃^-, SO₄^2-) exhibited inhibitory effects, while elevated PEI content enhanced the materials' resistance to interference. Using 0.3mol/L NaCl in 90% methanol as the desorbent, the material retained 88.32% adsorption efficiency after five adsorption-desorption cycles, demonstrating excellent recyclability. Combined analyses of material characterization and adsorption performance indicated that the primary mechanisms were electrostatic interactions, supplemented by hydrophobic interaction.

A dynamic experimental system was employed to conduct long-term constant-flow leaching column tests, combined with water quality testing and hydrochemical analysis, and it was found that groundwater quality was significantly degraded by cement-based grouting materials. Excess ions (Ca²⁺, OH^-, etc.) and liquid-phase products leached from the grouting body caused a marked rise in water pH and severe exceedances of water quality indicators such as total dissolved solids (TDS). This led to a significant increase in water hardness and alkalinity, enhanced its reducibility, and altered its hydrochemical type. Residual pollution from cement grouting resulted in severe disruption to the ion balance of the water body, and varying degrees of clustered deterioration in water quality were induced by different types of cement grouting. The hydration of silica-alumina phase clinker in cement, secondary hydration of added admixtures, and dissolution of controlled filler minerals were confirmed as the core driving factors causing grouting pollution.

The Tandem Neural Network Architecture (TNNA) algorithm was an inversion framework through reverse mapping. Its reliability strongly depended on accurate surrogate modeling within the true posterior region of parameters. For reactive transport problems, establishing a globally accurate surrogate model required a large number of numerical model samples, which considerably limited the efficiency of inversion processes. To address this challenge, the TNNA-AUS-MF inversion method was proposed, in which the original TNNA was integrated with a multi-fidelity (MF) surrogate model and an adaptive updating sampling (AUS) strategy. In this method, multi-fidelity surrogate models were iteratively established based on the conventional TNNA and local samples to update the inversion results. The proposed algorithm was validated using a hypothetical cation-exchange experiment. By controlling the number of initial surrogate model samples, six scenarios with different initial surrogate model accuracies were designed. The results showed that the TNNA-AUS-MF significantly reduced the number of forward simulations while yielding more reliable inversion results compared with the TNNA method. Furthermore, it was demonstrated that the neural network could establish nonlinear relationships between low- and high-fidelity models, and that incorporating the adaptive updating sampling strategy effectively enhanced the performance of the inversion algorithm.

Systematic analyses were conducted on total contents and pollution characteristics of Zn, Pb, Cd, Hg, As, Mn and Sb in surface (0~0.5m), middle (1.0~1.5m), and deep (2.5~3.0m) soils of the Xikuangshan area. Ecological risks of heavy metals (HMs) were evaluated by using potential ecological risk index (PERI), mean effect range median quotient (MERMQ) and network environ analysis (NEA), and their potential sources were apportioned and identified through an absolute principal component score-multiple linear regression (APCS-MLR) receptor model. The results showed that the HM contents in the surface layer were highest, and the average contents of all elements except Pb in soils exceeded the background values of Hunan Province. As the soil depth increased, the changes of HM contents were not significant, indicating contamination has diffused to deeper layers. The antimony mining area exhibited a high probability of toxic effect and severe ecological risk for Sb and Hg, moderate toxic probability and risk for As, and a high risk yet low toxic probability for Cd. In topsoil, the initial risk transmitted from vegetation to microorganisms was 2.23-fold that to herbivores and 22.33-fold that to carnivores. Notably, Sb posed the highest comprehensive ecological risk, and soil microorganisms were the most vulnerable ecological receptor. Source apportionment revealed that Zn, Pb and Cd in soils primarily originated from atmospheric deposition of industrial/mining smelting and transportation, and also impacted by the waste rocks/tailings leaching. As, Mn and Sb predominantly derived from waste rocks/tailings leaching, supplemented by natural resource of high geological background. Hg mainly stemmed from agricultural activities, particularly sewage irrigation, with secondary contributions from waste rocks/tailings leaching.

Biogenic volatile organic compounds (BVOCs) are critical components linking terrestrial ecosystems with the atmospheric environment for gas exchange and information transfer, and they have played essential roles in biogeochemical cycles, climate change, and ecosystem functioning. Soil ecosystems serve as both significant sources and indispensable potential sinks for atmospheric BVOCs. In this review, the progress in soil BVOCs research was systematically synthesized. Their main sources in soil (soil organic matter, litter decomposition, plant roots, and microbial metabolism) and soil sink pathways (atmospheric dry and wet deposition, physical adsorption and dissolution, and microbial degradation) were highlighted. Furthermore, the seasonal variations and ecosystem-specific differences in soil BVOCs flux were summarized, and the potential mechanisms of soil BVOCs source-sink dynamics in the context of global climate change (warming, drought, and nitrogen deposition) were explored. Finally, current research gaps were elucidated, and future key research directions were proposed, aiming to provide new insights for a comprehensive understanding of the role of BVOCs in soil biogeochemical cycling processes.