Aged refuse with a landfill age of 1.5 years was collected from a municipal solid waste landfill with high kitchen waste content and mixed with soil as biocover material for landfill. A series of laboratory batch tests was performed to determine the methane oxidation potential and optimal mixing ratio of landfill cover soil modified with aged refuse, and the effects of water content, temperature, CO₂/CH₄, and O₂/CH₄ ratios on its methane oxidation capacity were analyzed. The microbial community analysis of aged refuse showed that the proportions of type I and type II methane-oxidizing bacteria were 56.27% and 43.73%, respectively. Aged refuse could significantly enhance the methane oxidation potential of cover soil, and the optimal mixing ratio was approximately 1:1. The optimal temperature and water content were about 25 °C and 30%, respectively. Under the conditions of an initial methane concentration of 15% and an O₂/CH₄ ratio of 0.8–1.2, the measured methane oxidation rate was negatively correlated with the O₂/CH₄ ratio. The maximum methane oxidation capacity measured in the test reached 308.5 (μg CH₄/g)/h, indicating that the low-age refuse in the landfill with high kitchen waste content is a biocover material with great application potential.

Adding organically modified bentonite into impervious wall materials may improve the adsorption of organic pollutants. In this study, cetyltrimethylammonium bromide organically modified bentonite (CTMAB bentonite) was mixed with sodium bentonite and kaolin to obtain two materials, which were then used as cut-off walls for typical pollutants. Soil column consolidation tests, diffusion tests, and breakdown tests were conducted to study migration of organic pollutants in soil columns. The parameter sensitivity of pollutant transport in the cut-off wall was analysed by numerical simulation. The sodium bentonite mixed with 10% CTMAB bentonite and kaolin-CTMAB bentonite showed the greatest impermeability: with a consolidation pressure of 200 kPa, the permeability coefficients were 1.03 × 10⁻⁸ m/s and 3.49 × 10⁻⁹ m/s, respectively. The quantity of phenol adsorbed on sodium bentonite-CTMAB bentonite increased with increasing water head height. The kaolin-CTMAB bentonite column showed the best rhodamine B adsorption performance, and the adsorption rate reached 98.9% on day 67. The numerical results showed that the permeability coefficient was positively correlated with the diffusion of pollutants in the soil column. The quantity adsorbed on the soil column was positively correlated with the retardation factor, and the extent of pollutant diffusion was negatively correlated with the retardation factor. This study provides a technical means for the optimal design of organic pollutant cut-off walls.

High-throughput sequencing was employed to characterize pathogenic fungal communities in soil, groundwater, bioaerosols, and waste pile samples from a typical municipal landfill. The relative abundance of soil-borne pathogenic fungi was significantly higher downstream of the landfill (30.33 %) than upstream (18.75 %), which suggests that the landfill poses more risk to biosafety downstream than upstream. Dominant genera in surface layers and vadose zones included Pseudallescheria, Pichia, Alternaria, Perconia, Bisifusariu, and Fusarium, comprising 84.04 % of pathogenic fungi, while Malassezia, Aureobasidium, and Trichoderma prevailed in deeper phreatic aquifer and bottom layers. Coupled multi-media transport analysis revealed that both leachate-driven groundwater transport and aerosol deposition contributed to the pathogenic fungal load in soils. Variance partitioning analysis (VPA) revealed that environmental factors explained 43.6 % of fungal community variation. Redundancy analysis (RDA) and Canonical correspondence analysis (CCA) revealed that cation exchange capacity (CEC), pH, infiltration, and moisture were the primary environmental drivers shaping fungal communities. Heavy metals concentrations (Cu, As, Cd) have strong correlation with many pathogenic fungi and shared a similar distribution pattern. These findings highlight the landfill's role in disseminating pathogenic fungi, posing elevated biosafety risks to the surrounding soil, and necessitating enhanced monitoring and mitigation.

The release of siloxane from landfill leachate has attracted wide attention. In this study, dodecamethylcyclohexasiloxane (D6) and dodecamethylpentasiloxane (L5) were chosen as the target pollutants to investigate the adsorption characteristics of cyclosiloxane and linear siloxane on municipal solid waste (MSW) under the landfill circumstance. The adsorption behavior could be well described by the Langmuir–Freundlich model, with a maximum adsorption capacity of 0.677 μg g⁻¹ and 15.864 μg g⁻¹ for L5 and D6, respectively. It seems that D6 has a stronger affinity to MSW compared with L5. The maximum adsorption was observed when the pH was 5.0 and 5.5 for D6 and L5. The optical temperature was 30 °C. The organic acid and inorganic ions in the leachate could restrict the adsorption to a low level. The results suggested that the adsorption of siloxane on MSW could be limited at the methanogenic and mature stages, which may promote the distribution of siloxane in the leachate. The results could help to understand the release behavior of siloxane from landfill leachate during the running of a landfill.

The activated sludge process serves as the core barrier in pharmaceutical wastewater treatment, yet its stability is inherently challenged by the extreme complexity of influent composition and the unpredictability of toxic shocks, particularly under contract development and manufacturing organization (CDMO) operations. Current biotoxicity assessment methods face inherent trade-offs among timeliness, specificity, and matrix robustness, resulting in fragmented, reactive management that lacks predictive capacity. In response, this review critically synthesizes evidence on toxicity pathways and monitoring technologies, systematically evaluating their mechanistic basis and engineering applicability. Building on these findings, we propose a conceptual perception–cognition–response architecture that structures decision-making across three adaptive tiers: (i) a perception layer that tolerates false positives for rapid anomaly detection; (ii) a cognition layer that requires effect-based biological verification; and (iii) a response layer that authorizes resilience-oriented interventions. Rather than a linear pipeline, the three tiers form an adaptive feedback cycle that dynamically aligns monitoring intensity, verification depth, and response authority with real-time risk gradients and site-specific constraints. By explicitly linking biological mechanisms to assessment limitations and tiered decision rules, this review provides a hypothesis-generating roadmap that orients biotoxicity management from episodic, composition-based assessment toward adaptive, effect-driven control. The proposed framework is intended to guide future pilot validation, multi-sensor integration, and context-specific calibration, offering a unified narrative for advancing proactive biotoxicity control in complex pharmaceutical wastewater systems.