Environmental Science: Nano最新文献

The application of nanomaterials as fertilizers, biostimulants, and pesticides has been emerging as a promising approach in recent years, aiming to support sustainable and precision agriculture, while simultaneously addressing the challenges of climate change, global population growth, and the search for alternative energy sources (biofuels). In this work, to computationally assess the effects of nanoparticles (NPs) on plant growth (encoded in terms of length of e.g., root, shoot or overall plant length), we performed extensive data curation and enrichment with atomistic descriptors of an existing NP–plant interactions database, ensuring high-quality data for the development of machine learning (ML) models. To address class imbalance, data augmentation techniques were applied. An autoML workflow was developed to optimise and evaluate seven ML algorithms for predicting the plant length response class following NP exposure. The optimised XGBoost model demonstrated superior predictive performance during external validation, achieving an accuracy of 85% and a balanced accuracy of 83%, and its applicability domain was clearly defined. One of the key advantages of the plant length response model is that it requires no experimental input data to generate predictions, thus facilitating virtual screening prior to implementation of controlled experimental setups. The curated dataset has been made findable, accessible, interoperable and reusable (FAIR) via the nanoPharos database (https://db.nanopharos.eu/Queries/Datasets.zul?datasetID=np31) and the XGBoost model was documented in a standardized QSAR model report format (QMRF) to enhance its usability and FAIRness and made available as a user-friendly web-application, CeresAI-nano, via the Enalos Cloud platform (https://enaloscloud.novamechanics.com/chiasma/agrinano/).

Ion-selective electrodialysis (SED) has emerged as a promising approach for water purification, resource recovery, and electrochemical processes. While conventional ion-exchange membranes (IEMs) enable efficient charge-based ion separation, their disordered polymer networks lack the structural precision needed to distinguish ions with similar valence or hydrated size. As separation demands become increasingly stringent, IEMs have evolved toward advanced ion-selective membranes that introduce nanoscale confinement and engineered interfacial chemistries. These developments have culminated in the emergence of nanochannel membranes, which feature geometrically defined sub-nanometer channels that promote surface-governed ion transport and enable ion–ion selectivity far beyond the capabilities of traditional IEMs. This review integrates fundamental principles of electrochemical ion transport with recent advances in nanochannel membrane design for SED. We first elucidate the key mechanisms governing ion selectivity, including dehydration-based partitioning at the channel entrance, intra-channel ion–pore interactions, and dimensionality-dependent transport in 1D, 2D, and 3D nanochannels. We then survey major material platforms used to construct nanochannel membranes, such as ultrathin polymeric layers, two-dimensional nanosheet laminates, crystalline porous frameworks, and ceramic nanochannels. Finally, we outline design principles for controlling channel dimensions, interfacial charge, and structural stability, and discuss remaining challenges in translating nanochannel-enabled SED into efficient, durable, and industrially relevant ion-separation technologies.

In this review, we explore recent advances in coupling nanoscale zero valent iron (nZVI) with biological treatments for environmental remediation, emphasizing mechanisms, system configurations (direct vs. indirect contact), microbial interactions, and key factors that govern performance. We first provide an overview of the current literature pertaining to nZVI- and or biological-mediated reductive treatment of organic/inorganic pollutants and compare the pros and cons of individual treatment methods. We emphasize the need for combined processes and explore the mechanisms driving hybrid systems, examining various system configurations. We then conduct a comprehensive evaluation of microbial–nZVI interactions and the environmental/material parameters, paired with engineering control strategies for enhanced performance. We also highlight the influential parameters that affect treatment efficiency, providing a critical analysis of the factors that can either enhance or impede the remediation process. In summary, we prioritize practical optimization, risk considerations, and pathways for scaling from laboratory to field applications, offering guidance for future research and practical applications.

Nano-enabled agricultural technologies, particularly the application of small-sized selenium nanoparticles (Se NPs, <100 nm), demonstrate significant potential for stimulating crop growth and enhancing Se biofortification efficiency in dryland farming systems. However, the influence of Se NP size on bioavailability in flooded systems remains poorly understood. In this study, a rice (Oryza sativa L.) cultivation system was used to explore the relationship between the Se NP size (30 and 110 nm, 22 μm) and Se bioavailability under waterlogged conditions. Interestingly, 110 nm Se NPs significantly enhanced rice biomass, evidenced by a 19.4% increase in root fresh weight, and improved Se bioavailability in plants compared to both smaller (30 nm) and larger particles (2 μm). Mechanistically, smaller Se NPs (30 nm) appeared to enhance radial oxygen loss (ROL) and stimulate antioxidant enzyme activity (superoxide dismutase [SOD], peroxidase [POD], and catalase [CAT]). This physiological response promoted Fe(II) oxidation and subsequent iron plaque (IP) deposition on root surfaces, with DCB-extractable Fe levels showing a 29.1% increase compared to those of the 110 nm NP treatment group. The resulting increase in Se adsorption by the IP reduced Se translocation to aerial tissues, thereby decreasing its bioavailability in the smaller Se NP treatment group. Full life cycle experiments further confirmed that 110 nm Se NPs exhibited significantly higher Se accumulation in grains, an 85.3% increase compared to 30 nm NPs. These findings underscore the critical role of nanoparticle size and IP sequestration in determining Se bioavailability in rice grains. This study provides valuable insights for optimizing nano-Se fertilizers to improve Se biofortification in flooded agricultural systems.

The large-scale application of organophosphate (OP) pesticides poses serious challenges to food safety, environmental sustainability, and human health, creating an urgent need for rapid and sensitive detection technologies. In recent years, carbon quantum dots (CQDs) derived from natural biomass have emerged as environmentally benign fluorescent nanoprobes, offering tunable photoluminescence, high photostability, and versatile surface functionalities. Some CQD fluorescence sensors of OP pesticides use the quenching mechanisms of inner filter effect (IFE), photoinduced electron transfer (PET), and Förster resonance energy transfer (FRET), with detection limits as low as 0.1–5 ppm towards compounds as varied as methyl parathion, chlorpyrifos, and malathion. In real-sample studies, the sensors obtained satisfactory recovery rates between 88% and 104% in matrices with the use of waters, soil, and fruit extracts with satisfactory reproducibility (RSD < 5%). However, most existing strategies are still limited to controlled lab environments with limited selectivity, stability, and tolerance to the matrix. Additionally, although there has been notable development in the sensing of pesticides, the sensing of toxic OP metabolites such as p-nitrophenol (PNP), a key biomarker of exposure, has still attracted relatively minor interest. This review critically summarizes the recent developments in biomass-derived CQDs for OP pesticide and metabolite detection, highlighting the influence of precursor composition, surface functionalization, and optical quenching pathways on sensing performance. Particular emphasis is placed on structure–function relationships, fluorescence quenching mechanisms, and real-sample validation. By delineating current challenges and opportunities, this review outlines strategies for designing robust, portable, and sustainable CQD-based sensors capable of bridging the gap between proof-of-concept research and practical applications in food safety, environmental monitoring, and human health protection.

Bauxite residue, or red mud (RM), is a highly alkaline by-product produced during alumina extraction from bauxite. The global accumulation and unscientific disposal of RM raise concerns, considering their negative impact on the environment. In addition, due to their recalcitrance to biological treatment, the unprecedented rise in the concentration of pharmaceuticals in the aquatic biota poses a threat to non-targeted species. To address these issues, RM was sustainably utilized to prepare beads and subsequently surface-modified (MRM beads) through alkali-assisted ultrasonication to immobilize a Z-scheme Bi₁₂O₁₅Cl₆/Fe₂O₃@C heterostructure for the photocatalytic degradation of a mixture of norfloxacin (NLX) and doxycycline (DCL) in a continuous-flow photocatalytic reactor. Under optimal conditions, the photocatalyst-coated MRM beads achieved degradation efficiencies of 91.6% for NLX and 86.2% for DCL after a residence time of 240 min, with corresponding degradation rate constants of 0.0103 min⁻¹ and 0.0083 min⁻¹, respectively. The main active species responsible for NLX and DCL degradation were found to be O₂^˙−, with subsequent roles played by HO˙ and h⁺, as confirmed through EPR. Moreover, the BFC-II coated MRM beads exhibited remarkable reusability for up to six cycles and could partially restore the photocatalytic activity when heated. Moreover, XRD analysis indicated the retention of the crystallographic properties, while micro-Raman spectra revealed carbon loss due to repeated calcination during regeneration. Real water matrices negatively affected the degradation of NLX and DCL due to their intrinsic constituents. This study advocates the sustainable utilization of RM as a catalyst support in a continuous-flow photocatalytic reactor, promoting waste management and scalability.

Universal and equitable accessibility to clean and affordable drinking water is one of the sustainable goals established by the United Nations General Assembly to achieve the millennium development goals. However, the contamination of natural freshwater reservoirs by toxic agrochemicals like pesticides has reduced the availability of safe drinking water, necessitating the development of innovative mitigation approaches. Recently, bioinspired green NPs synthesized using biological entities have evolved as a sustainable choice for the catalytic degradation of a broad spectrum of recalcitrant emerging pollutants due to their conducive properties and cost-effectiveness. In this regard, the present review comprehensively examines the potential application of green nanoparticles (NPs) in (bio)electrochemical systems for the effective mineralisation of pesticides. Pesticide removal in the range of 79.3% to 100.0% has been reported using green NPs, while a power density up to 4.7 W m⁻³ has been attained in (bio)electrochemical systems. This study further highlights the antibacterial properties of green NPs, offering potential applications in the agricultural, environmental and biomedical fields. This review also highlights the environmental impacts and sustainability of green NPs, along with their critical limitations, particularly in the context of (bio)electrochemical systems. Ultimately, plausible strategies to overcome the impending challenges in green synthesis techniques have been outlined as a future perspective that will aid in standardising and streamlining these novel synthesis procedures.

Engineered nanomaterials (ENMs) offer a double-edged sword for aquatic remediation: while serving as powerful agents for pollutant removal, their inherent reactivity creates significant ecotoxicological risks. This critical review deconstructs this duality by providing an integrated analysis of remediation benefits versus mechanistic hazards. It is argued that the physicochemical properties driving remedial function—such as high surface reactivity and redox potential—are the shared origin of the molecular initiating events of toxicity. For instance, while photocatalytic ENMs can achieve >90% degradation of recalcitrant organics, this same non-selective reactivity can trigger a 1.5–2-fold increase in intracellular ROS in non-target aquatic organisms. The analysis reveals how this relationship is dynamically modulated by environmental transformations (e.g., eco-corona formation, aggregation), creating profound challenges for conventional risk assessment. Consequently, a paradigm shift from a reactive, post hoc evaluation to a proactive safe-and-sustainable-by-design (SSbD) framework is advocated. This approach, which embeds mechanistic toxicology as an a priori design tool, is presented as the critical pathway to rationally decouple efficacy from hazard. Only through this integrated perspective can the transformative potential of nanoremediation for ensuring global water security be realised through sustainable design.

Micro- and nanoplastic (MNP) particles have emerged as a novel class of anthropogenic contaminants, now recognized as pervasive across all environmental compartments and in food and drinking water. Their extreme heterogeneity in size, morphology, density, polymer type, surface chemistry, and degree of aging presents major analytical challenges, with reported abundances spanning up to ten orders of magnitude. Reliable assessment of their occurrence and impacts therefore requires advanced analytical approaches capable of identifying, quantifying, fractionating, and characterizing these particles across scales. This review systematically evaluates state-of-the-art analytical strategies for MNP detection, organized into four major categories: mass-based identification methods (e.g., Py-GC/MS, TED-GC/MS, MALDI-ToF/MS), particle-based quantification techniques (e.g., μ-FTIR, μ-Raman, ToF-SIMS), separation and fractionation methods (e.g., FFF and HDC-SEC coupled with spectroscopy or mass spectrometry), and morphological and surface characterization tools (e.g., SEM/EDX, AFM-IR, nano-FTIR, SP-ICP-MS). For each category, we critically assess detection limits, strengths, and limitations, highlighting their suitability for micro- versus nanoplastic detection. Special attention is devoted to emerging approaches that push detection toward the nanoscale, as well as the need for harmonization and standardization across methodologies. By comparing and integrating these techniques, we outline how complementary approaches can provide comprehensive characterization of MNPs and support reliable risk assessment. Finally, future perspectives are discussed for advancing analytical sensitivity, method automation, and cross-disciplinary standardization to address the global challenge of MNP pollution.