Environmental Science: Nano最新文献

Detecting glyphosate (Gly), a widely used herbicide in agricultural practice worldwide, is crucial due to its environmental impact and potential health risks. This study presents a colorimetric sensor based on gold nanoparticles (AuNPs) functionalized with cysteamine (AuNPs + Cys) for Gly-sensitive and selective detection. The AuNPs were synthesized using the Turkevich method and characterized using ultraviolet-visible spectroscopy (UV-vis), dynamic light scattering, X-ray diffraction spectroscopy, and scanning electron microscopy. The AuNPs display a localized surface plasmon resonance peak at a 520 nm wavelength and have an average size distribution of 23 nm with good dispersion. The AuNPs + Cys exhibit unique optical properties, allowing for visible color changes in response to varying concentrations of Gly. The detection mechanism relies on the interaction between Gly and the Cys on the nanoparticle surface, which induces changes in the aggregation state of the AuNPs, leading to a shift in the UV-vis absorption spectrum. The sensor was tested at a maximum concentration of 100 ppm Gly, with a detection limit of 1.42 ppm and a distinct color change easily visible to the naked eye. To evaluate the sensor's selectivity, assays were conducted in a soil matrix. Glufosinate was employed as a complementary analyte, and the sensor exhibited a clear differentiation, thus achieving selective detection between the herbicides. The developed AuNPs + Cys sensor offers a simple, cost-effective, and efficient method for Gly detection, with potential applications in environmental monitoring and agricultural practices.

Monitoring mercury (Hg²⁺) in aquatic systems is critical for ecological risk assessment, yet a key challenge lies in assessing its bioavailable fraction, which is governed by chemical speciation. Herein, a novel electrochemical sensor for the indirect monitoring of chemically speciated mercury in environmental waters is reported. The sensor is based on surfactant-tailored β-indium sulfide (In₂S₃) quantum dots (QDs) immobilized using a chitosan ink on a disposable graphite electrode. The sulfide-rich surface of the In₂S₃ QDs provides high-affinity binding sites for Hg²⁺. The sensing mechanism relies on the Hg²⁺-induced enhancement of electron transfer for a ferrocyanide redox probe, rather than direct Hg electrochemistry. This indirect approach proved highly sensitive to the free Hg²⁺ ions, as demonstrated by a pronounced counterion effect: the signal intensity followed the trend Hg(NO₃)₂ > (CH₃COO) ₂Hg > HgCl₂, reflecting the lability and bioavailability of the mercury species. The sensor exhibited a detection limit of 21.2 nM, high selectivity against common interferents (Zn²⁺, Cd²⁺, and Pb²⁺), and excellent operational stability, retaining 86% of its signal after 30 days. Crucially, the sensor performed reliably in the analysis of canal water, achieving accurate quantification with recoveries of 101.50 ± 1.25% without any sample pre-treatment. Hence, this robust and low-cost In₂S₃/GPE sensor provides insights into mercury speciation, supporting more accurate environmental monitoring and ecological risk assessment in contaminated aqueous systems.

Chromium (Cr) contamination in soils of rice-growing regions poses a significant risk to both human health and the environment. Elevated Cr levels in soil reduce photosynthetic activity, induce oxidative stress, and limit rice plant growth. This work investigated the remediation of Cr-contaminated soil using bare nZVI (NC), biochar (BC), and biochar-supported nZVI (ZB) and examined their impacts on plant development, Cr uptake, and micronutrient (Zn and Fe) accumulation in rice grains. The result indicates that nZVI–biochar significantly reduced bioavailable Cr in soil [water-soluble (F1) = 71%, exchangeable (F2) = 73%, and oxide-bound (F4) = 64%], which is primarily transformed into unavailable forms. Therefore, the application of nZVI–biochar composites effectively inhibits Cr mobility in the soil. Also, Cr accumulation in rice grains was considerably reduced in the ZB addition (79%), as compared to the untreated soil. Although BC and NC alone improved plant performance in contaminated soil, their combination was more effective. The use of ZB, NC, and BC at 5000 mg kg⁻¹ increased grain Fe content by 91%, 81%, and 51%, respectively. Additionally, biochar in ZB increased grain Zn by 34%, likely due to its low Zn sorption affinity, facilitating Zn transportation and accumulation. Overall, application of ZB at 5000 mg kg⁻¹ enhanced rice growth, biomass, photosynthetic pigments, and antioxidant enzyme activity by decreasing Cr bioavailability in soil, which in turn reduced Cr uptake and translocation to rice grains. Hence, amending soil with a ZB composite may offer a promising approach for the safe utilization of Cr-contaminated sites in the future.

Serving as a staple food for over half of the world population, rice plants tend to accumulate higher levels of cadmium (Cd) and arsenic (As) than other cereal crops. Copper oxide nanoparticles (nCuO), known for their stability and adsorption capacity, show potential for remediating soils contaminated with Cd and As. This study investigated the regulatory effects of nCuO on rice (O. sativa) seedling growth under combined Cd–As stress and the potential detoxification efficacy of nCuO for Cd and As via soil–water partitioning in two distinct soil environments, i.e., acidic organic-rich red soils and neutral high cation-exchange-capacity (CEC) brown soils. Results demonstrated that nCuO at 10–100 mg L⁻¹ alleviated oxidative stress caused by Cd–As and promoted seedling growth. In particular, nCuO reduced Cd–As accumulation in rice seedlings grown in the brown soil by inhibiting the expression of related genes OsNRAMP5 and OsLsi1. However, in the red soil, greater mobility of Cd–As resulted in their higher root accumulation and stronger antioxidant responses in rice seedlings, requiring higher doses of nCuO to achieve effective remediation. Furthermore, nCuO reduced the toxicity of simulated drainage water to Daphnia magna, showing its efficacy in mitigating ecological risks associated with Cd–As partitioning from contaminated soils to aquatic ecosystems. This alleviation was more effective in the brown soil. These findings provide insights into the mechanisms by which nCuO mitigates Cd–As co-stress in rice, and nCuO behaviors in contrasting soil environments for remediating contaminated paddy fields and the adjacent water environments.

Engineered nanoparticles (ENPs) released into aquatic environments can undergo multiple removal processes, including dissolution, sedimentation, advection, and aggregation with natural particles. This study quantitatively assesses the probability that heteroaggregation is the dominant removal pathway among these mechanisms. The aggregation propensity of 36 ENP types was evaluated by estimating attachment efficiencies (α) derived from DLVO theory across a wide range of environmental conditions. Results show that α decreases with particle size at low Hamaker constants but increases with size at higher values. The calculated α values were incorporated into an environmental fate model to quantify the relative importance of aggregation versus other removal processes. Aggregation dominance probabilities varied widely among ENPs – from a few percent to 100% – depending on material composition, particle size, and zeta potential. Based on these outcomes, a five-tier CLUMP classification was developed to categorize ENPs according to the frequency of heteroaggregation dominance. This classification framework provides a comparative measure of nanomaterial mobility and environmental stability, offering a practical tool to support environmental fate modeling and risk assessment.

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.