Water authorities in European countries are required to carry out regular impact assessments of pesticides in their water bodies under the EU Water Framework Directive (Directive 2000/60/EC; WFD). This requirement poses a significant challenge for water authorities in Sweden, which has up to 100,000 lakes and more than 500,000 km of water-courses. To support their work under the WFD, we developed VERBER for surface waters, a GIS-based model for pesticide risk assessment and management. VERBER predicts average concentrations of active substances originating from arable fields at the outlet of sub-catchments in inter-connected networks of lakes and water-courses in Sweden. The modelling approach combines a parsimonious steady-state mass balance model with a classification tree trained on Swedish environmental monitoring data, to estimate the fraction of an applied pesticide lost to surface waters based on hydrological characteristics of soils, pesticide properties and application season. According to VERBER model runs for seven active substances (either priority substances in the WFD with particularly hazardous properties or river basin-specific pollutants) at the national scale, 2.2% of sub-catchments in Sweden are at risk of being affected by pesticide concentrations that constitute chronic toxicity to aquatic organisms. A comparison between average surface water concentrations predicted by VERBER and measured concentrations of the seven active substances and two additional substances that often exceed the EU drinking water limit value (0.1 μg L−1) indicated that the model predictions are generally realistic, although it does also seem to be conservative in a few cases.
This study investigates the adsorption properties of amine-functionalized mesoporous organic hybrid materials (μOHMs) for the removal of heavy metals, specifically Cu, Ni and Zn from industrial wastewater streams such as steel sludge. The synthesized microscale (40–60 μm) materials were characterized and evaluated for adsorption performance in synthetic metal solutions and real steel sludge leachate under batch and continuous-flow conditions. Through batch adsorption experiments, equilibrium behavior was characterized using isotherm modeling, with apparent maximum adsorption capacities of 63.5, 43.1, and 36.2 mg/g for Cu, Ni, and Zn, respectively. Kinetic analysis showed that the pseudo-second-order model provided the best empirical description of the adsorption kinetics among the models evaluated. When applied to real steel sludge leachate, μOHMs removed 96.1% of Cu at an adsorbent loading of 1 g/L, while Ni and Zn removal reached 93.2% and 92.5%, respectively, at 6 g/L, with minimal removal of Ca, Mg, and Mn. Under continuous-flow treatment of the steel sludge leachate, Cu and Ni remained below the breakthrough threshold over the 60 min experiment, while Zn exhibited breakthrough at approximately 40 min and Ca, Mg, and Mn showed immediate breakthrough. In single-metal continuous-flow experiments, the experimentally integrated dynamic capacities were 58.0, 41.9, and 45.8 mg/g for Cu, Ni, and Zn, respectively, while the Thomas model provided the best overall representation of the breakthrough behavior. Competitive adsorption experiments in synthetic equimolar multicomponent systems further confirmed preferential Cu adsorption over Ni and Zn. Regeneration studies demonstrated repeated Cu uptake over 50 adsorption-desorption cycles using 0.1 M HNO3, with an average apparent Cu uptake of 33.5 mg/g. Overall, these findings demonstrate the potential of μOHMs for selective metal recovery from complex industrial streams while retaining Ca- and Mg-rich solutions for potential downstream carbon sequestration.
Metal–organic framework (MOF) photocatalysis is commonly judged by a single end-point percentage pollutant removal even though the reported decrease can combine adsorption, photolysis, partial transformation, true catalytic degradation, and catalyst decomposition. This metric-centered literature has produced many high-performing materials but few transferable design rules. Here, MOF photocatalysts are re-evaluated through an evidence-gated coordination-to-risk framework that asks whether five sequential conditions are satisfied including the contaminant can access and be productively positioned within the pore or interfacial microenvironment, absorbed photons generate charges with adequate lifetime and redox potential, those charges produce a verified reactive pathway rather than a diagram inferred from band edges alone, chemical conversion yields mineralization or demonstrable toxicity reduction, and the active material remains recoverable, compositionally stable, and effective in realistic matrices and reactor formats. Using this framework, the roles of metal-node identity, linker electronics, pore matching, defects, mixed-metal coordination, MOF-on-MOF interfaces, semiconductor coupling, MOF-derived phases, and immobilized photo-Fenton architectures are critically compared. Representative systems are treated as causal tests rather than as a catalogue of efficiencies, and mechanistic claims are ranked according to the strength of optical, electrochemical, spectroscopic, radical, pathway, leaching, and post-reaction evidence. The analysis shows that improved adsorption and faster apparent kinetics are valuable only when they preserve charge utilization, product safety, and structural continuity. A recommended reporting framework is therefore proposed to distinguish disappearance, degradation, mineralization, detoxification, and process durability. By shifting the unit of comparison from “best removal percentage” to “verified contaminant-risk reduction per stable catalytic cycle,” this review establishes a more discriminating basis for designing MOF photocatalysts that can progress from elegant coordination solids to credible water- and air-treatment technologies.
Understanding the distinct mechanisms by which straw and biochar regulate soil organic carbon (SOC) sequestration is essential for optimizing agricultural practices. To investigate the physical-microbial coupling mechanisms of SOC sequestration, we amended three upland soils collected from Yuzhong (YZ), Yangling (YL), and Changwu (CW) of the Loess Plateau with 13C-labeled straw and biochar. Straw promoted the formation and carbon (C) enrichment of macroaggregates (>0.25 mm), increasing macroaggregate-associated SOC by 40–110% in YZ and YL soils. Conversely, biochar increased the proportion of silt-clay fractions (<0.053 mm) and elevated SOC therein, with a 257% increase observed in CW soil. Straw stimulated certain r-strategist bacteria such as Proteobacteria and Bacteroidota, whereas biochar favored K-strategists such as Actinobacteriota, leading to more complex bacterial co-occurrence networks and greater niche differentiation. Path modeling and correlation analyses revealed two distinct sequestration pathways: a fungal-driven physical protection pathway under straw, wherein fungi promoted macroaggregate formation that physically protected particulate organic C (POC); and a bacterial-driven mineral stabilization pathway under biochar, wherein its chemical stability and porous structure enhanced organic matter adsorption and bacterial activity, promoting the formation of stable mineral-associated organic C (MOC). Specifically, straw was better suited for coarse-textured or low-SOC soils with unsaturated aggregate formation, whereas biochar was more effective in fine-textured or high-SOC soils with abundant mineral surfaces for MOC stabilization. Matching amendment type to soil conditions could therefore maximize C sequestration potential in dryland farming systems.
Red mud stockpiles may pose long-term heavy-metal-related risks to surrounding soils, yet microbial indicators for ecological effect assessment remain poorly defined. Because direct microbial evidence from red mud stockpiles is limited, published studies on heavy metal contaminated soils were synthesized to screen candidate indicators for this scenario. This meta-analysis integrated 116 studies comprising 763 observations and quantified responses of microbial biomass, alpha diversity, community structure, beta diversity, and enzyme activities to cadmium, mercury, arsenic, lead, chromium, copper, zinc, and nickel. Subgroup analyses, climatic meta-regressions, and precision-weighted random forest models evaluated associations between microbial responses and concentration-toxicity category, soil properties, climatic background, land use, and experimental setting. Heavy metal contamination was associated with significant decreases in microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) by 25.8% and 39.6%, respectively, lower bacterial richness and Shannon diversity, and significant shifts in bacterial community structure. Eight enzyme activities showed significant inhibition of 16.8%-41.8%, with dehydrogenase and urease showing high sensitivity and ecological relevance to microbial metabolic activity and nitrogen cycling. Urease, dehydrogenase, and MBC showed the clearest responses across potential ecological risk index-derived categories, while soil pH, soil organic carbon, soil texture, climatic background, land use, and experimental setting were associated with indicator-specific variation among studies. Overall, MBC, MBN, bacterial community structure, dehydrogenase, and urease were identified as candidate core indicators, supporting an evidence-based microbial framework for ecological effect assessment and risk management in red mud stockpile scenarios.
