Natural deep eutectic solvents (NADES) have emerged as promising alternatives to conventional organic solvents and mineral acids in sample preparation for elemental determination by spectrometric techniques. Their tunable physicochemical properties, low volatility, and potential renewability have led to their increasing application in extraction, digestion, and preconcentration strategies coupled to atomic spectrometry. In parallel, several studies report using green analytical chemistry metrics to support the sustainability of NADES-based methods. However, the criteria used and the interpretation of these metrics vary widely, often leading to optimistic claims of greenness. This review provides a comprehensive overview of NADES composition, physicochemical properties, and their application in sample preparation strategies for elemental analysis using spectrometric techniques, including atomic absorption spectrometry, inductively coupled plasma optical emission spectrometry, and inductively coupled plasma mass spectrometry. NADES-based approaches involving liquid–liquid extraction, ultrasound-assisted extraction, microwave-assisted extraction, and solid-phase extraction are critically discussed, with emphasis on analytical performance, workflow complexity, and practical applicability. In addition, a systematic reassessment of green metrics was conducted using the AGREE and AGREEprep tools, applying harmonized, conservative criteria across selected studies. Unlike literature-reported evaluations, this analysis explicitly incorporates energy consumption, CO₂ emissions, operator safety based on safety data sheets, auxiliary reagent usage, and sample throughput. The recalculated indices reveal significant discrepancies with previously reported values, indicating that NADES-based methods are not inherently green and that solvent substitution alone does not guarantee improved sustainability. Overall, this work demonstrates that while NADES offer considerable potential for greener sample preparation in atomic spectrometry, their real environmental benefits depend on the integrated optimization of solvent composition, extraction strategy, energy efficiency, and operational simplicity. The findings emphasize the importance of transparent, quantitative application of green metrics to identify trade-offs and guide the development of truly sustainable analytical methodologies.
Dispersive liquid-liquid microextraction (DLLME) has progressed into a simple, efficient, rapid, and miniaturized sample preparation procedure for analysis of environmental organic pollutants in different matrices. This review emphasizes recent advancements that enhance the performance and sustainability of DLLME for environmental analysis by eliminating disperser solvents in the analytical procedure. The article discusses advances in disperser solvent-free DLLME (DSF-DLLME), including ultrasound-, vortex-, air-, and effervescence-assisted approaches, which significantly improve mass transfer and extraction kinetics and improve the environmental sustainability of the procedure. The broad utilization of ecofriendly extraction solvents is also addressed, with emphasis on ionic liquids, low-density organic solvents, and deep eutectic solvents as alternatives to conventional solvents. The review also explores hybrid automated DLLME systems, covering their conceptual design, instrumentation, and main advantages, alongside current limitations. Finally, future directions focus on automation, miniaturization, green chemistry principles, and integration with advanced analytical techniques. Overall, these innovations position DSF-DLLME as a promising and practical technique for modern analytical applications in environmental analysis.
The development of novel sample preparation media is crucial for the efficient analysis of hazardous components like pesticide and phenol residues. To facilitate the extraction and enrichment of these residues from complex samples, various functionalized materials have been prepared as adsorbents. Recently, covalent organic frameworks (COFs), a class of functionalized porous organic materials, have emerged as promising adsorbents owing to their high surface area, tunable porosity, and specific recognition properties for pesticides and phenols. These advanced porous organic materials, when paired with modern analytical techniques, have been successfully applied to the analysis of pesticide and phenol residues in complex matrices, including environmental, food, and biological samples. This review encapsulates recent progress in this field. Finally, current challenges and future research directions are discussed to inform the advancement of next-generation COF-based adsorbents.
Nanoplastics (< 1 & micro;m) have emerged as a new frontier in environmental pollution research, presenting analytical challenges distinct from microplastics due to their minute size and unique physicochemical behaviors. Recent innovations in vibrational spectroscopy, Surface-Enhanced Raman Scattering (SERS) and Pyrolysis-Gas Chromatography/Mass Spectrometry (Py-GC/MS) have established a technological foundation for identifying nanometer-scale particles. However, despite these dramatic improvements in detection sensitivity, the field continues to face severe bottlenecks regarding the reliability, reproducibility, and comparability of results in non-spiked environmental samples. This review argues that nanoplastics analysis must be redefined not merely as a deterministic task of detection but as a problem of probabilistic inference fraught with uncertainty. We clarify the conceptual distinction between Signal-level Limit of Detection (LOD) and Distribution-level LOD and critically examine the statistical limitations of currently prevalent analytical techniques. Specifically, we identify the quantification of nanoplastics as a parameter estimation problem for a multinomial distribution. By applying the theoretical framework of Thompson (1987), we mathematically demonstrate that a minimum sample size of approximately 510 particles is required to estimate the proportions of multiple polymer components with 95% confidence and a 5% margin of error. The fact that most current studies analyze only tens of particles suggests that the reported data contains non-negligible uncertainties. Consequently, we propose a new statistical reporting framework that includes distinguishing between exploratory and confirmatory research, explicitly quantifying uncertainty, and, most importantly, justifying sample sizes based on Thompson's theory. This is a prerequisite for nanoplastics research to mature beyond simple identification and produce robust quantitative data capable of informing policy decisions.
Carcinogenic and persistent pollutants (CPPs), including pesticides, per- and polyfluoroalkyl substances, heavy metal ions, and polycyclic aromatic hydrocarbons (PAHs), pose long-term risks to environmental and human health owing to their persistence, bioaccumulation, and chronic toxicity. However, reliably monitoring these contaminants in complex environmental matrices proves analytically challenging, particularly when multiple pollutants coexist. To overcome this challenge, metal-organic frameworks (MOFs) and their composites have emerged as versatile analytical materials owing to their tunable porosity; diverse coordination chemistry; and ability to integrate recognition, enrichment, and signal transduction within a single platform. This review critically examines recent advances in MOF-based analytical strategies for CPP monitoring, with particular emphasis on the transition from conventional single-mode detection to multi-analyte, dual-mode, and multi-mode sensing platforms. Electrochemical and optical approaches, including ratiometric electrochemistry, fluorescence/colorimetric and chemiluminescence/colorimetric sensing, and hybrid electrochemical/optical architectures, are evaluated for their analytical performance, robustness, and suitability for real sample analysis. Particular emphasis is placed on how MOF nanozyme activity, aptamer or DNAzyme functionalization, and composite design enable self-calibrated, interference-resistant detection. Emerging trends toward portable, field-deployable systems, such as paper-based devices and smartphone-assisted multimodal readouts, are also highlighted. Finally, current limitations, including stability, reproducibility, and uneven pollutant coverage, particularly for PAHs, are critically assessed, and future directions for next-generation MOF-based environmental analytical platforms are outlined. Overall, this review provides a timely perspective on how MOFs and their composites are reshaping analytical strategies for reliable CPP monitoring in environmental samples.
Atmospheric organic aerosol (OA) constitutes an exceptionally complex and dynamically evolving molecular system that influences climate forcing, air quality, and human health. Recent advances in FT-ICR MS and Orbitrap-based ultrahigh resolution mass spectrometry (UHRMS) have fundamentally reshaped our ability to characterize this complexity, enabling the detection of thousands of molecular formulas. This review provides a critical assessment of HRMS applications in atmospheric OA research, covering ionization strategies, dataprocessing workflows, molecular descriptor interpretation, and traceability across primary and secondary sources. By synthesizing recent findings across particle, cloud, fog, rain, and snow matrices, we highlight how HRMS resolves the chemical diversity of OA and links molecular composition to environmental processes. We further discuss methodological limitations and outline future directions within an emerging aerosolomics framework. Together, these perspectives position HRMS as a cornerstone for advancing molecular-level understanding of OA and for bridging aerosol chemistry with climate and health relevance.
The analysis of plastics and related chemical compounds, such as plasticizers, flame retardants, and micro- or nanoplastics, often requires working at trace levels, where even minimal contamination can significantly affect results. However, many of these target analytes are also present in common laboratory materials and environments, increasing the risk of cross-contamination. We identified six major cross-contamination pathways frequently found in analytical workflows: (I) laboratory materials, (II) environmental contamination, (III) human handling and manipulation, (IV) solvents and reagents, (V) cleaning and sample preparation, and (VI) instrumental and system-related contamination. For each of these, preventive measures and good laboratory practices are suggested based on both experimental experience and examples in the literature. As a general recommendation, procedural blanks should be included throughout the analytical process, and contamination risks should be anticipated as early as the experimental design stage. This work provides a structured reference to support more reliable and reproducible data generation in the analysis of plastic-related contaminants. Researchers are further encouraged to evaluate contamination risks throughout the workflow and to report them transparently in their publications.
This review highlights a significant gap in the multi-pollutant characterisation of ultrafine particulate matter (PM <0.1µm), focusing on metal(oid)s and polycyclic aromatic hydrocarbons (PAHs). Fractionation mechanisms, sampling protocols and analytical methods are examined with an emphasis on integrating quality assurance measures to ensure high-quality data and facilitate cross-study comparability. Based on studies published between 2010 and 2025, research has largely focused on the analysis of pollutants bound to PM2.5 or PM10. Only 5% of the studies addressed ultrafine particles (UFPs), which have the greatest toxicological impacts. The measurement of both pollutant groups within a single sampling campaign was rare (14% of the studies). The reliability of analytical data was rarely evaluated. Only 33% of the studies employed certified reference materials for quality control and method validation. Microwave-assisted digestion and ultrasound-assisted extraction were commonly used for sample preparation prior to the determination of metal(oid)s and PAHs, by inductively coupled plasma mass spectrometry and gas chromatography–mass spectrometry, respectively. Both pollutant groups exhibited strong seasonal variability, with elevated concentrations observed during heating periods in cold seasons, as well as associated with fine PM and UFPs, fractions that exhibit high bioaccessibility. Smaller PM fractions were associated with anthropogenic sources, including fossil fuel and biomass combustion, traffic and industrial emissions, while coarse PM reflected naturally-derived crustal material. Overall, these findings highlight the importance of uniform and comprehensive protocols for sampling UFPs and quantifying associated pollutants, which are essential for reliable data and effective urban air quality control strategies aimed at mitigating emissions.
Silicone wristbands are increasingly used as passive samplers for assessing personal exposure to volatile organic compounds (VOCs) and semi volatile organic compounds (SVOCs). This review synthesizes 107 peer reviewed studies published between 2014 and 2025 and examines current analytical approaches applied in wristband exposure assessment. Key methodological steps, including treatment before and after deployment, extraction and cleanup procedures, and instrumental analysis, are summarized to characterize prevailing practices across studies. For VOC analysis, thermal desorption is the most applied approach. For SVOCs, mechanical shaking solvent extraction dominates current workflows and is typically combined with cleanup to reduce silicone related interferences prior to chromatographic analysis. Except for analytical processes, this review also connects analytical choices to wristbands’ application in exposure assessment and comparison to other sampling approaches. Wristbands are particularly suited for integrating personal exposure over extended durations and across multiple exposure pathways. Through translating loads to air equivalent concentrations, silicone wristband complements the other active and passive air samplers as exposure assessment tools. Across applications, significant challenges persist in data interpretation and comparability due to variability in deployment protocols, differences in chemical sensitivity of uptake to environmental conditions, and inconsistence in reporting of quality assurance practices. Greater standardization of analytical protocols and more transparent reporting practices would enhance the reliability and comparability of wristband exposure data across studies.
Honeybees and their products integrate landscape-level chemical exposure, making apicultural matrices valuable bioindicators for both food safety and environmental monitoring. This review summarizes current knowledge on pesticide residues in honey, pollen, beebread, beeswax, royal jelly, and propolis from 2019 to 2024, with an overview of analytical methodologies used in their determination. Multi-residue methods remain dominated by Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) extraction combined with liquid and gas chromatography coupled to tandem mass spectrometry, while high-resolution MS enables broader screening. Highly polar pesticides, particularly glyphosate and its metabolites, require specialised single-residue approaches, such as the Quick Polar Pesticides (QuPPe) method and ion chromatography–high-resolution mass spectrometry (IC-HRMS). Co-occurrence patterns frequently involve mixtures of neonicotinoids, acaricides, and fungicides, reflecting combined agricultural and in-hive treatments. Regarding matrices, honey typically shows insecticide and acaricide residues, pollen concentrates fungicides and insecticides as the main exposure route, and beeswax acts as a long-term sink for lipophilic compounds; royal jelly generally exhibits the lowest contamination levels. Although exceedances of Maximum Residue Limits in honey remain uncommon in European monitoring programs, the presence of pesticide mixtures and limited residue data for bee-related products beyond honey raise concern. Future research should prioritize harmonized residue limits for all beekeeping matrices, standardized quality control and reporting practices, targeted mixture-toxicity assessment under realistic co-exposure scenarios, and the broader adoption of green, miniaturized, and matrix-tailored sample preparation strategies to enhance sensitivity, sustainability, and comparability across studies.
The persistent release of emerging contaminants into water and wastewater poses escalating ecological and public health risks, highlighting limitations of conventional treatment systems. Nanomaterials offer a transformative approach by combining efficient contaminant removal with sensitive and real-time analytical monitoring. This review critically evaluates diverse nanomaterial classes including polymeric nanostructures, metal-organic frameworks (MOFs), metal and metal oxide nanoparticles, and multifunctional nanocomposites, focusing on their mechanisms in adsorption, photocatalysis, filtration, and sensing. The distinctive contribution of this review lies in its integrated, application-oriented evaluation of nanomaterials that simultaneously address wastewater remediation and analytical detection, a perspective largely absents in existing literature, which treats these functions separately. Practical considerations including scalability, environmental safety, and regulatory relevance are also addressed. By unifying remediation and monitoring functionalities, this review provides a structured roadmap for designing next-generation nanomaterial-based strategies for sustainable water management.
The widespread occurrence of emerging organic contaminants (EOCs), including pharmaceuticals, personal care products, pesticides, and industrial chemicals, is a growing concern for environmental and human health. Conventional analytical techniques, such as gas and liquid chromatography coupled to mass spectrometry, provide high sensitivity and reliability but remain costly, resource-intensive, and unsuitable for rapid or on-site monitoring. In this context, paper-based sensors are a promising alternative, offering low cost, portability, simple fabrication, and environmental sustainability. This review provides an overview of recent advances in paper-based sensors for the detection and monitoring of EOCs. Key fabrication strategies, including photolithography, wax printing, inkjet printing, screen printing, and laser-based approaches, are discussed with respect to device performance, scalability, and field deployability. Major transduction mechanisms, including electrochemical, colourimetric, fluorescence, and chemiluminescence approaches, are examined together with optimisation strategies based on nanomaterials, molecular recognition elements, and microfluidic design to improve sensitivity and selectivity. Applications in environmental monitoring, healthcare, and pharmaceutical and food analysis are reviewed, with emphasis on real-sample analysis and method validation. Current limitations related to matrix effects, reproducibility, environmental robustness, and large-scale manufacturing are identified, and future perspectives are outlined.
The rapid accumulation of micro- and nanoplastics (MNPs) in agricultural landscapes has raised urgent questions about their fate in soils, their transfer to plants, and their eventual entry into human diets. While early reviews of MNPs in food matrices, soils, and plants provided important foundations, most treated these compartments separately and rarely aligned analytical evidence across the soil-plant-edible tissue continuum. This review synthesizes current knowledge along the agricultural soil-plant-food pathway, with emphasis on analytical workflows such as sampling, pretreatment, spectroscopic imaging, and thermoanalytical and mass-spectrometric quantification. We critically evaluate detection limits, recovery biases, and the suitability of these methods for complex agricultural matrices, while also highlighting emerging computational tools for particle recognition, automated spectral deconvolution, and improved mass-balance closure. Persistent challenges involving sub-50 mu m fractions, nanoscale particles, and environmentally realistic concentrations are discussed. While earlier essential studies are included for context, the focus is on recent literature that captures the rapid evolution of analytical capabilities from 2020 to 2025. Linking field surveys, controlled uptake studies, and exposure modelling shows how harmonized protocols and improved QA/QC can strengthen dietary risk assessment. The review concludes by identifying methodological gaps and introducing recent advances in analytical determination, including advanced imaging techniques such as confocal laser scanning microscopy (CLMS) or photoinduced force microscopy (PiFM), thermoanalytical MS (e.g., pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS), thermal extraction and desorption (TED)-GC/MS and fast-MS platforms), and imagingenhanced Raman/Fourier transform infrared spectroscopy (FTIR), together with novel data analysis workflows that now warrant an integrated appraisal focused on agroecosystems.
Phthalates, extensively used as plasticizers in industrial and consumer products, have long been recognized for their toxicological impacts and environmental persistence. Their classification as endocrine-disrupting chemicals linked to reproductive dysfunction, metabolic disorders, and oxidative stress has amplified global regulatory concern. Compounding these risks is their widespread occurrence in aquatic ecosystems, where phthalates bioaccumulate and contribute to long-term ecological degradation. This review critically examines the classification, health implications, and environmental behavior of phthalates, while evaluating current detection technologies. Conventional chromatographic methods gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography (HPLC) offer high sensitivity but are constrained by cost and operational complexity. Emerging spectrophotometric and electrochemical platforms offer cost-effective and portable alternatives but still face significant challenges such as matrix interference, limited selectivity, and poor reproducibility. Ultimately, bridging these analytical advancements with scalable, real-world applications is essential to effectively mitigate phthalate exposure risks to both human health and the environment.
Background Soil contamination by hydrocarbons, explosives, and pharmaceutical drugs, including antibiotics, poses serious environmental and health risks. These pollutants originate from industrial waste, military activities, and agriculture, leading to long-term toxicity. Sensitive detection methods are crucial for effective monitoring and remediation.Scope and Approach:This review covers recent advances in fluorescent sensors for detecting hydrocarbons, explosives, and pharmaceutical drug contaminants in soil. It highlights sensor materials, detection mechanisms, and array-based approaches. Additionally, the review addresses the challenges and limitations faced by these sensors when applied to real sample analysis.Key Findings and Conclusions:Fluorescent sensors offer high sensitivity, selectivity, and rapid detection of hydrocarbons, explosives, and drug residues. Advances in array based sensing and portable devices have improved detection efficiency. However, challenges remain in enhancing sensor durability and field applicability. Future research should focus on real-time monitoring and practical deployment for effective environmental assessment, as well as the development of reusable sensors, long-range pH stability, and the fabrication of devices such as Fido X4.
Alkylated polycyclic aromatic hydrocarbons (APAHs) are naturally present in petroleum and derivatives and are released into the environment through industrial processes and incomplete combustion of fossil fuels. Due to their hydrophobicity, stability and low polarity, these substances tend to accumulate across different environmental compartments. In the atmosphere, APAHs are detected in both particulate and gas phases, especially in urban and industrial regions. In aquatic systems, less hydrophobic APAHs, such as alkylated naphthalenes and phenanthrenes, are commonly found in surface waters, while sediments serve as long-term sinks for these compounds. In biota, APAHs exhibit bioaccumulation potential, with elevated levels reported in aquatic organisms, particularly in lipid-rich tissues. Despite their environmental relevance, APAHs remain understudied, primarily due to analytical challenges related to their structural diversity, low environmental concentrations, and co-elution of isomers. This review aims to explore the analytical approaches employed for the extraction, detection, identification, and quantification of APAHs in environmental matrices. Extraction and preconcentration techniques, such as solid-phase extraction and microextraction, as well as the application of high-resolution chromatographic and mass spectrometric methods (e.g., GCxGC-TOFMS, GCxGC-HRMS, LCMS/MS) for APAHs were emphasized. Individual APAHs and specific diagnostic ratios employed to indicate petrogenic and pyrogenic sources are presented. To the best of our knowledge, this is the first review focused on
Haloacetonitriles (HANs) are toxic disinfection by-products frequently detected in treated water, posing risks to human health and the environment. Accurate and sensitive characterization of HANs remains challenging due to the volatility and trace-level concentrations. This review provides a comprehensive summary of recent advances in HANs pretreatment and detection over the past decade. While traditional techniques, such as liquid-liquid extraction and gas chromatography-based methods, remain widely used, novel approaches have emerged, including 3D-printed liquid phase microextraction devices, online extraction systems, and high-resolution mass spectrometry (e.g., Q-Exactive MS, Time-of-Flight MS). The application of self-fabricated materials, such as PDMS/DVB-NVP fibers in SPME, has further improved extraction performance. This review critically compares current strategies, highlights key limitations, and discusses future directions for developing efficient, automated, and environmentally friendly methods for HANs analysis.
Microplastic pollution has become a significant problem due to its widespread presence in aquatic ecosystems and its possible negative impacts on human beings and marine life. Traditional detection methods are often time-consuming, and their sensing activity still needs accurate quantification. Electrochemical sensing methods offer a promising alternative for the highly sensitive and quick detection of microplastics. This review explains the outlines of recent advancements in electrochemical sensing methods, with a focus on metal oxide electrodes. These electrodes have been recognized as promising platforms for microplastic detection owing to their relatively high chemical stability, large surface area, and superior conductivity. Various metal oxides, such as zinc oxide (ZnO), titanium dioxide (TiO2), and iron oxide (Fe3O4), have been investigated for their suitability in these applications. This review discusses the principles and mechanisms underlying electrochemical sensing, including voltammetric and amperometric techniques. Key factors influencing the performance of metal oxide-based sensors, such as electrode morphology, surface functionalization, and sensor configuration, are examined. Recent developments in sensors, fabrication techniques, and strategies for enhancing sensitivity and selectivity are also highlighted. In addition, the review confronts the challenges, hurdles, and future directions in electrochemical sensing for microplastic detection, including the need for standardized protocols, validation of sensor performance in real-world samples, and integration into monitoring networks for environmental surveillance. Overall, metal oxide-based electrochemical sensing methods hold great promise for detecting microplastics in environmental samples. Continued research efforts aimed at optimizing sensor performance and addressing practical challenges will contribute to the development of reliable and cost-effective tools for microplastic monitoring and remediation.
