The high-efficiency ball milling treatment technology primarily combines the excitation of oxidation processes with high-speed physical collisions, thereby promoting the reaction processes and enhancing the degradation effectiveness of materials. This technology has gained widespread attention in recent years for its application in the degradation of organic solid chemical pollutants. In this study, quantum chemical density functional theory (DFT) was employed to first analyze the impact of electron addition and subtraction on molecular chemical bonds. The molecular energies of the target pollutants and their possible intermediates were then calculated, and the theoretical energies required for the degradation pathways of the target organic compounds under oxidative-enhanced ball milling were computed. This further validated the accuracy of the ball milling experimental results. The theoretical energy required for the complete mineralization of solid organic chemicals through ball milling degradation was calculated, with values of 16,730.74 kJ/mol for lindane, 20,162.46 kJ/mol for tetrabromobisphenol A, 10,628.04 kJ/mol for sulfamethoxazole, and 4867.99 kJ/mol for trimethoprim. By combining different ball milling experimental conditions, the theoretical reaction time required for the complete mineralization of the target organic chemicals can be calculated. The comparison of theoretical calculations with the experimental results provides new insights into the ball milling degradation process and degradation pathways of the target pollutants.

The kinetic study of micro-electrolysis biotechnology not only determines the removal efficiency of a micro-electrolysis process but also influences the optimal design of a system. This paper investigates the relationship between electric field strength, pollutant degradation rate, and biofilm thickness by constructing a microporous biofilm model for pollutant removal. Additionally, the study derives equations linking electric field strength to reaction rate, pollutant effluent concentration, and biofilm thickness under both high and low pollutant influent concentrations. This work bridges the gap between macroscopic processes and periplasmic mechanisms, enhancing our understanding of pollutant removal mechanisms and facilitating process optimization. It also provides theoretical support for the sustainable development of micro-electrolysis biotechnology. Future research will focus on experimental validation and the optimization of model accuracy and flexibility to accommodate diverse treatment conditions.

Growing ozone (O₃) pollution in industrial cities urgently requires in-depth mechanistic research. This study utilized multi-year observational data from Datong City, China, from 2020 to 2024, integrating time trend diagnostics, correlation dynamics analysis, Environmental Protection Agency Positive Matrix Factorization 5.0 (EPA PMF 5.0) model simulations, and a grey prediction model (GM (1,1)) projection method to reveal the coupling mechanisms among O₃ precursors. Key breakthroughs include the following: (1) A ratio of volatile organic compounds (VOCs) to nitrogen oxides (NO_x) of 1.5 clearly distinguishes between NO_x-constrained (winter) and VOC-sensitive (summer) modes, a conclusion validated by the strong negative correlation between O₃ and NO_x (r = −0.80, p < 0.01) and the dominant role of NO titration. (2) Aromatic compounds (toluene, xylene) used as solvents in industrial emissions, despite accounting for only 7.9% of VOC mass, drove 37.1% of ozone formation potential (OFP), while petrochemical and paint production (accounting for 12.2% of VOC mass) contributed only 0.3% of OFP. (3) Quantitative analysis of OFP using PMF identified natural gas/fuel gas use and leakage (accounting for 34.9% of OFP) and solvent use (accounting for 37.1% of OFP) as key control targets. (4) The GM (1,1) model predicts that, despite a decrease in VOC concentrations (−15.7%) and an increase in NO_x concentrations (+2.4%), O₃ concentrations will rise to 169.7 μg m⁻³ by 2025 (an increase of 7.4% compared to 2024), indicating an improvement in photochemical efficiency. We have established an activity-oriented prioritization framework targeting high-OFP species from key sources. This provides a scientific basis for precise O₃ emission reductions consistent with China’s 15th Five-Year Plan for synergistic pollution/carbon governance.

Per- and polyfluoroalkyl substances (PFASs) are persistent aquatic contaminants whose strong C–F bonds make conventional water treatment ineffective. This review critically synthesizes recent progress in aqueous PFAS degradation through four mechanistic routes: oxidation-driven, biodegradation, reduction-driven, and nonradical processes. Rather than evaluating technologies by parent-compound disappearance alone, we compare their defluorination and mineralization capacities, matrix tolerance, byproduct risks, energy demand, operational stability, and technology readiness. Oxidative and reductive systems can promote rapid degradation or defluorination, but their performance is often constrained by radical/electron quenching, incomplete mineralization, and sensitivity to PFAS structure and water chemistry. Biodegradation and enzymatic approaches offer mild transformation pathways but remain limited by slow kinetics, narrow substrate specificity, and uncertain toxicity evolution. Nonradical and thermochemical processes show stronger potential for deep destruction, particularly in concentrated PFAS streams. Overall, electrochemical oxidation, plasma treatment, and thermal/supercritical oxidation appear closer to practical implementation for spent adsorbents, regenerants, industrial concentrates, and other high-strength wastes, whereas many photocatalytic, biological, and microdroplet systems remain laboratory-stage. Future research should prioritize integrated separation–destruction treatment trains and standardized metrics including total organic fluorine removal, fluoride release, final residual PFAS concentrations relative to regulatory thresholds, transformation-product toxicity, energy consumption, and life-cycle impacts.