Development and validation of multiresidue analysis method for biomonitoring of pesticides and metabolites in human blood and urine by LC-QToF-MS.

The widespread use of pesticides and their consequential presence in the environment is a growing concern due to the harmful health effects associated with pesticide exposure. For clinical and toxicology laboratories, a method for simultaneously determining these compounds and their metabolic products in body fluids, such as blood and urine, is important. In the present study, a rapid, sensitive and simultaneous LC-QToF-MS method for detecting multiclass pesticides and metabolites in blood and urine samples has been developed and validated. Four sample preparation procedures, protein precipitation and three different variants of QuEChERS-based extraction were evaluated to find a suitable, simple, and effective sample pretreatment technique. The final optimized sample preparation method (acetonitrile; 400 µl, MgSO4; 40 mg and NaCl; 10 mg) was validated for accuracy, precision, matrix effect, recovery, stability, carryover, and dilution integrity. Analyte recoveries ranged from 75.40 to 113.54 % while accuracy was evaluated in the range of 71.41-108.26 % and precision (%RSD) in the range of 0.01 %-16.85 %. The limit of quantification (LOQ) for all compounds was established in the range of 0.82-7.05 ng mL-1. The developed reliable, robust, and sensitive method was successfully applied for the quantification of target pesticides and metabolites in human blood and urine samples. Evaluated samples resulted in detection of eleven analytes (seven pesticides and four metabolites).

Machine learning-assisted laccase-like activity nanozyme for intelligently onsite real-time and dynamic analysis of pyrethroid pesticides.

The intelligently efficient, reliable, economical and portable onsite assay toward pyrethroid pesticides (PPs) residues is critical for food safety analysis and environmental pollution traceability. Here, a fluorescent nanozyme Cu-ATP@ [Ru(bpy)3]2+ with laccase-like activity was designed to develop a versatile machine learning-assisted colorimetric and fluorescence dual-modal assay for efficient onsite intelligent decision recognition and quantification of PPs residues. In the presence of alkaline phosphatase (ALP), the laccase-like activity of Cu-ATP@ [Ru(bpy)3]2+ was enhanced to oxidize colorless o-phenylenediamine (OPD) into dark-yellow 2,3-diaminophenazine (DAP) via electron transfer, appearing a new yellow fluorescence at 550 nm. Meanwhile, the red fluorescence of Cu-ATP@ [Ru(bpy)3]2+ at 600 nm was quenched due to the internal filter effect (IFE) of DAP towards Cu-ATP@ [Ru(bpy)3]2+. However, the selective inhibition of PPs toward ALP activity enabled to observe a dual-modal response of PPs concentration-dependent decrease in colorimetric signal and enhancement in the fluorescence intensity ratio of F600 nm/F550 nm. On this basis, both the colorimetric and fluorescence images were captured and processed with a home-made WeChat applet-installed smartphone to extract the corresponding image color information, thus achieving machine learning-assisted onsite real-time and dynamic intelligent decision recognition and quantification of PPs residues in real samples, which shows a promising potential in safeguarding food safety and environmental health.

Health risk assessment of triazole fungicides around a pesticide factory in China.

The environmental pollution and health effects caused by pesticide production have consistently garnered considerable research interest. In the present study, the concentrations of five triazole fungicides (TFs) in air, indoor dust, and diet were monitored around a pesticide factory in eastern China from November 2020 to May 2021. The levels of five TFs in each sample were determined via UPLC‒MS/MS. For a health risk assessment, the United States Environmental Protection Agency's deterministic method was applied. The findings revealed that the total concentrations of the five TFs around the monitoring area ranged from 0.29 to 5.85 ng/m3 in outdoor air, 287.4 to 9878.5 µg/kg in indoor dust, 0.0578 to 4.948 µg/kg in vegetables, and 0.447 to 3.00 µg/kg in rice. Notably, tebuconazole and hexaconazole had consistently high contributions over the years. For adults and children, the average daily doses (ADDs) were 1.32 × 10-5 and 2.69 × 10-5 mg/kg/day, respectively, in the monitoring area and 4.25 × 10-6 and 6.42 × 10-6 mg/kg/day, respectively, in the control area. In the control area, rice and vegetables were the primary media for exposure to TFs in children and adults, collectively accounting for more than 94% of the total TF exposure. Conversely, indoor dust is identified as the main medium of TF exposure in children residing near the pesticide factory, representing approximately 40% of the total exposure. The risks of noncarcinogenic effects on children and adults in the monitoring area were significantly greater than those in the control area, being approximately ten times greater for children, warranting increased attention. The carcinogenic risk to human health is relatively safe.

Determination of pesticide residues in beans using QuEChERS technique coupled to gas chromatography-mass spectrometry: Multivariate optimization of CEN and AOAC methods.

The use of pesticides has led to environmental pollution and posed a global health risk, since they remain as residues on foods. Beans one of the most widely cultivated crop in Africa, and susceptible to attack by insects both on field and during storage, leading to the application of pesticides to control pests' infestation. However, misuse of these chemicals by farmers on beans has resulted in the rejection of beans exported to European countries, due to the presence of pesticide residues at concentrations higher than the maximum residues levels (MRLs). In this study, the effectiveness of the Association Official Analytical Chemists (AOAC) Official Method and the European Committee of Standardization (CEN) Standard Method, were determined using multivariate approach for the analysis of organochlorine pesticide residues in 6 varieties of beans samples. The significance of factors (mass of sample, volume of acetonitrile, mass of magnesium sulphate, sample pH, centrifugation time and speed) affecting the efficiency of extraction was estimated using Plackett-Burman design, while central composite design was used to optimize the significant factors. The following optimum factors were subsequently used for method validation, recovery tests, and real sample analysis: 4 g of sample sludge (1:1 v/v), 10 mL of acetonitrile, 4.45 g of MgSO4, and 5 min of centrifugation at 5000 rpm. The figure of merit of analytical methodology estimated using matrix-matched internal standard calibration method gave linearity ranging from 0.25 to 500 µg/kg, with correlation coefficient (R2) greater than 0.99, the recovery ranged from 75.55 to 110.41 (RSD = 0.70-16.65), with LOD and LOQ of 0.23-1.77 µg/kg and 0.76-5.88 µg/kg, respectively.

A Portable Electrochemical Biosensor Based on an Amino-Modified Ionic Metal-Organic Framework for the One-Site Detection of Multiple Organophosphorus Pesticides.

Constructing stable, portable sensors and revealing their mechanisms is challenging. Ion metal-organic frameworks (IMOFs) are poised to serve as highly effective electrochemical sensors for detecting organophosphorus pesticides (OPs), leveraging their unique charge properties. In this work, an amino-modified IMOF was constructed and combined with near-field communication (NFC) technology to develop a portable, touchless, and battery-free electrochemical biosensor NH2-IMOF@CS@AChE. -NH2 in NH2-IMOF gives the framework a higher electropositivity compared to IMOF, enhancing the electrostatic attraction with acetylcholinesterase (AChE), which is beneficial for immobilizing AChE. Furthermore, the uncoordinated O atoms and the (CH3)2NH2+ groups in NH2-IMOF help to form stronger bonds with AChE through hydrogen bonds. The results showed a wide linear response range of 1 × 10-15 to 1 × 10-9 M and a low detection limit of 1.24 × 10-13 M for glyphosate (Gly) in the practical detection of OPs. Additionally, electrochemical biosensor arrays were constructed to effectively identify and distinguish multiple OPs on the basis of their unique differential pulse voltammetry (DPV) electrochemical signals. This work provides a simple and effective solution for on-site OP analysis and can be widely applied in food safety and water quality monitoring.

A reliable quantification of organophosphorus pesticides in brown rice samples for proficiency testing using Japanese official analytical method, QuEChERS, and modified QuEChERS combined with isotope dilution mass spectrometry.

The objective of the present study is to provide reliable concentration values as assigned values for target pesticides in brown rice samples used in proficiency testing (PT) organized by the Hatano Research Institute (HRI). The test samples for PT were prepared by immersing brown rice in the pesticide solution and using a spray dryer by the HRI. Homogeneity and stability assessments were performed for PT samples, and the relative uncertainties due to inhomogeneity and instability were 0.58 %-0.78 % and 0 %-0.96 %, respectively. Quantification for the assigned values of target pesticides by the National Metrology Institute of Japan (NMIJ) was carried out using the multiple analytical methods including Japanese official analytical method, QuEChERS, and modified QuEChERS, which were combined with isotope dilution mass spectrometry, to ensure the reliability of the analytical results. The NMIJ assigned values were 0.065±0.004 mg/kg for chlorpyrifos, 0.217±0.012 mg/kg for diazinon, 0.138±0.008 mg/kg for fenitrothion, and 0.138±0.008 mg/kg for malathion.

Study on detection of pesticide residues in tobacco based on hyperspectral imaging technology.

Introduction: Tobacco is a critical economic crop, yet its cultivation heavily relies on chemical pesticides, posing health risks to consumers, therefore, monitoring pesticide residues in tobacco is conducive to ensuring food safety. However, most current research on pesticide residue detection in tobacco relies on traditional chemical methods, which cannot meet the requirements for real-time and rapid detection. Methods: This study introduces an advanced method that combines hyperspectral imaging (HSI) technology with machine learning algorithms. Firstly, a hyperspectral imager was used to obtain spectral data of tobacco samples, and a variety of spectral pre-processing technologies such as mean centralization (MC), trend correction (TC), and wavelet transform (WT), as well as feature extraction methods such as competitive adaptive reweighted sampling (CARS) and least angle regression (LAR) were used to process the spectral data, and then, grid search algorithm (GSA) is used to optimize the support sector machine (SVM). Results: The optimized MC-LAR-SVM model achieved a pesticide classification accuracy of 84.1%, which was 9.5% higher than the original data model. The accuracy of the WT-TC-CARS-GSA-SVM model in the fenvalerate concentration classification experiment was as high as 91.8 %, and it also had excellent performance in other metrics. Compared with the model based on the original data, the accuracy, precision, recall, and F1-score are improved by 8.3 %, 8.2 %, 7.5 %, and 0.08, respectively. Discussion: The results show that combining spectral preprocessing and feature extraction algorithms with machine learning models can significantly enhance the performance of pesticide residue detection models and provide robust, efficient, and accurate solutions for food safety monitoring. This study provides a new technical means for the detection of pesticide residues in tobacco, which is of great significance for improving the efficiency and accuracy of food safety detection.

Unveiling responses and mechanisms of spice crop chive exposure to three typical pesticides using metabolomics combined with transcriptomics, physiology and biochemistry.

Pesticides are frequently used to control target pests in the production of spice crops such as chives (Allium ascalonicum). However, little information is available on the responses and underlying mechanisms of pesticide exposure in this crop. Our findings revealed that the uptake, transportation, and subcellular distribution of three typical pesticides-the fungicide pyraclostrobin (PAL), insecticide acetamiprid (ATP), and herbicide pendimethalin (PND) in chives, as well as their physiological, biochemical, metabolic, and transcriptomic responses-were dependent on pesticide properties, especially hydrophobicity. The distribution of PAL and PND in chives decreased in the order root > stem > leaf, but the distribution order of ATP was the opposite. The proportion of PAL and PND in the solid phase of the root cells gradually increased, but ATP mainly existed in the cell-soluble component, indicating that the latter had an upward translocation ability and thus mainly accumulated in the leaves. Malondialdehyde levels in chive leaves were not significantly affected by exposure to these pesticides; however, the activities of superoxide dismutase (SOD) and catalase (CAT) in chive leaves increased significantly. Moreover, these pesticides exhibited critical differences in chive responses through the interaction of metabolites and regulation of differentially expressed genes. PAL dramatically influenced five carbohydrate metabolic pathways (34.35 %), disturbing the starch-to-sucrose balance. ATP strongly affected five amino acid (AC) metabolic pathways (33.38 %), enhancing four free amino acid levels. PND notably affected eight fatty acid (FA) metabolic pathways (25.38 %), increasing two unsaturated and decreasing one saturated FA. Simultaneously, PND, ATP, and PND accumulated in the chives could be detoxified through metabolic pathways mediated by cytochrome P450 (P450) and glycosyltransferase (GT)/glutathione S-transferase (GST), producing phase I (7, 4, and 5) and II (11, 13, and 10) metabolites, respectively. This study provides important molecular insights into the responses and underlying mechanisms of spice crop exposure to pesticides.

Mapping pesticide residues in soil for China: Characteristics and risks.

The widespread application of pesticides in China has led to the accumulation of residues in soil. However, few regional studies have fully elucidated the characteristics of pesticide residues in soil (PRS) and the associated risks to the ecosystem and human health on a national level. Therefore, this study aims to compile a dataset on PRS in China from 2006 to 2020 and analyze the interactions and impacts between PRS and the environment. The average concentration of PRS in China was 243.96 µg/kg which was lower than the levels reported in Euro-Americans and other nations. This study revealed PRS in China predominantly originates from organochlorine pesticide residues, with DDTs and HCHs being significant contributors. Despite the high intensity of pesticide application in the Southeast China, PRS concentrations were comparable to those in the Northeast, due to environmental factors that favor pesticide degradation in the Southeast. Both legacy and in-use pesticides were transported by surface runoff or air current, resulting in their accumulation in soil of the lower Yangtze River basin or the piedmont soil of Qinling Mountains, respectively. The average soil environment carrying capacity of PRS in China was -69.5 kg. The ecological risk contributed by PRS in China was mainly at a negligible level. Carcinogenic risks of PRS to adults (4.6 ×10-4) and children (6 ×10-4) exceeded the tolerable thresholds (10-5) by a small margin.

Eco(geno)toxicity of an acaricidal formulation containing chlorpyrifos, cypermethrin, and fenthion on different plant models and Artemia salina L.

The mixture of pesticides is widely employed in cattle farming to combat ectoparasite resistance, such as ticks. The commercial formulation COLOSSO FC30, which contains three active ingredients (Cypermethrin, Chlorpyrifos, and Fenthion), stands out due to its efficiency. However, animals exposed to this product may become vectors of potentially toxic molecules, possibly causing contamination in aquatic and terrestrial ecosystems. In light of this, this study evaluated the eco(geno)toxic potential of the commercial formulation COLOSSO FC30, using plants (Allium cepa L., Lactuca sativa L., Raphanus sativus L., Pennisetum glaucum L., and Triticum aestivum L.) and Artemia salina L. as model organisms. In the phytotoxicity test, the species were ranked in order of sensitivity to the commercial formulation as follows: P. glaucum > L. sativa > T. aestivum > R. sativus. The most sensitive parameters were root length (RL) and shoot length (SL) of seedlings. In the cytogenotoxicity test with A. cepa, cell division was decreased at concentrations from 0.351 mL L-1 in the meristematic region and root F1. Chromosomal aberrations and micronucleus were observed at all concentrations. In the test with A. salina, the IC50 after 24 h of exposure was 0.01207 mL L-1 of the commercial formulation. The results highlight the need for further research and regulations to understand and minimize the potential environmental impacts of COLOSSO FC30.

Multi-residue analysis method based on QuEChERS followed by ultra-high performance liquid chromatography coupled with diode-array detector for pesticides in human serum and breast milk.

Background: Maternal fluids play a key role in the risk assessment regarding early life pesticide exposure as the chemicals can transfer to neonate through prenatal exposure and lactation.Aim: A developed UHPLC-DAD and modified QuChERS methods were validated for human serum and breast milk. Matrix effect of the biological samples were evaluated.Methods & results: Serum was extracted by unbuffered QuChERS method while breast milk was extracted by citrate buffered method with addition of hexane. Remaining lipid in breast milk extract was later removed using lipid-removal sorbent. Sample matrices caused huge impacted on low-sensitivity pesticides.Conclusion: The modified QuEChERS methods coupled with UHPLC-DAD were fully validated. Application in paired-serum and breast milk samples revealed 6 detected pesticides.

[Box: see text].

Pesticide contamination patterns in Montagu's harrier (Circus pygargus) chicks.

Biomonitoring of persistent pesticides in birds of prey has been carried out for decades, but few studies have investigated their relevance for the monitoring of non-persistent pesticides. Herein, we determined the contamination patterns of multiple pesticides in Montagu's harrier (Circus pygargus) chicks in an intensive farming area of southwestern France. Blood samples from 55 chicks belonging to 22 nests in 2021 were assessed for 104 compounds (herbicides, fungicides, insecticides, safeners and synergists). All chicks had at least one herbicide in their blood, and half had at least two compounds. The 28 compounds detected comprised 10 herbicides, 12 fungicides, 5 insecticides and 1 synergist. Mixtures in blood were predominantly composed of herbicides, and six chicks presented a mixture of the three pesticide classes. The most prevalent compounds were sulcotrione (96% of chicks), tebutam (44%) and chloridazon (31%), of which the latter two had been banned in France for 19 and 3 years, respectively, at the time of sampling. Most compounds are considered non-acutely toxic, but sulcotrione is potentially carcinogenic, mutagenic and reprotoxic, raising questions about the effects on the health of nestlings. Biomonitoring of multiple pesticides through Montagu's harrier chicks in agroecosystems is clearly relevant because it reflects the general pattern of agricultural pesticide use in the study area. It also raises questions about exposure pathways in chicks, and further investigations are needed to disentangle the roles of dietary routes and maternal transfer for the established pesticide contamination patterns.

A conceptual framework for landscape-based environmental risk assessment (ERA) of pesticides.

While pesticide use is subject to strict regulatory oversight worldwide, it remains a main concern for environmental protection, including biodiversity conservation. This is partly due to the current regulatory approach that relies on separate assessments for each single pesticide, crop use, and non-target organism group at local scales. Such assessments tend to overlook the combined effects of overall pesticide usage at larger spatial scales. Integrative landscape-based approaches are emerging, enabling the consideration of agricultural management, the environmental characteristics, and the combined effects of pesticides applied in a same or in different crops within an area. These developments offer the opportunity to deliver informative risk predictions relevant for different decision contexts including their connection to larger spatial scales and to combine environmental risks of pesticides, with those from other environmental stressors. We discuss the needs, challenges, opportunities and available tools for implementing landscape-based approaches for prospective and retrospective pesticide Environmental Risk Assessments (ERA). A set of "building blocks" that emerged from the discussions have been integrated into a conceptual framework. The framework includes elements to facilitate its implementation, in particular: flexibility to address the needs of relevant users and stakeholders; means to address the inherent complexity of environmental systems; connections to make use of and integrate data derived from monitoring programs; and options for validation and approaches to facilitate future use in a regulatory context. The conceptual model can be applied to existing ERA methodologies, facilitating its comparability, and highlighting interoperability drivers at landscape level. The benefits of landscape-based pesticide ERA extend beyond regulation. Linking and validating risk predictions with relevant environmental impacts under a solid science-based approach will support the setting of protection goals and the formulation of sustainable agricultural strategies. Moreover, landscape ERA offers a communication tool on realistic pesticide impacts in a multistressors environment for stakeholders and citizens.

Longitudinal study and predictive modelling of urinary pesticide metabolite concentrations in residents of Guangzhou, China.

Continuous human biomonitoring and predictive modelling of urinary pesticide metabolites are critical for evaluating pesticide exposure trends and associated health risks. We conducted repeat cross-sectional surveys to determine the urinary concentrations of eight pesticide metabolites in the residents of Guangzhou, China, from 2018 to 2022. We longitudinally analyzed the changes in these metabolite concentrations over the years and assessed the potential non-carcinogenic risks by calculating the hazard quotient and hazard index. No significant differences were observed in the total urinary pesticide metabolite concentrations over the 5 years (9.16-12.99 µg/L). The urinary concentrations of 3,5,6-trichloro-2-pyridinol and 2,4-dichlorophenoxyacetic acid reached their lowest levels in 2020 (1.47 and 0.11 µg/L). Conversely, urinary para-nitrophenol concentrations exhibited an inverse trend, peaking in 2020 (6.16 µg/L). The composition profiles of urinary pesticide metabolites showed that para-nitrophenol consistently constituted the largest proportion each year. Males consistently showed higher median concentrations of total urinary pesticide metabolites and individual metabolites of 3,5,6-trichloro-2-pyridinol, trans-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropane-1-carboxylic acid, and para-nitrophenol than females. The concentrations of cis-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropane-1-carboxylic acid in adults' urine were significantly higher than those in minors' urine each year. The total pesticide metabolite concentrations in adults' urine were significantly higher than those in minors' urine in 2018 and 2020, whereas no significant differences were observed in other years. No significant differences in urinary pesticide metabolite concentrations were observed among different BMI groups. Results showed that 14.17% of the population had hazard index values above 1, indicating a higher risk of health hazards. Three predictive models were employed to predict urinary pesticide metabolite concentrations for 2023-2024, revealing an increasing trend in 3,5,6-trichloro-2-pyridinol concentrations while other metabolites are expected to decrease. The study showed the concentration of para-nitrophenol peaked in 2020 while 3,5,6-trichloro-2-pyridinol and 2,4-dichlorophenoxyacetic acid reached their lowest levels, suggests that the COVID-19 pandemic may have influenced pesticide exposure patterns.

A Scientific Review of Pesticides: Classification, Toxicity, Health Effects, Sustainability, and Environmental Impact.

Over the years, the use of pesticides has risen significantly, primarily to combat undesirable organisms that threaten crucial crops. A variety of pesticides are available, each designed to protect crops from specific threats like fungi, bacteria, and other pests. Other than crop protection, pesticides are also used in controlling insect vector-borne diseases like malaria and Lyme disease in humans. However, the application of these pesticides must be carefully measured and managed to prevent adverse effects on humans, non-target animals, and the environment. This review delves into the detailed classification of pesticides, exploring their mechanisms of action, applications, benefits, and potential side effects. Understanding the different categories of pesticides, such as herbicides, insecticides, fungicides, rodenticides, and biopesticides, helps us comprehend how each function to control pests. Additionally, we discuss the advantages of pesticide use, including increased crop yields and the prevention of crop diseases, which contribute to food security and agricultural productivity. This review also addresses the significant concerns related to pesticide usage, such as the development of pest resistance, health risks to humans through exposure and residues in food, as well as the impact on biodiversity and ecosystems. The review emphasizes the importance of using pesticides responsibly and implementing integrated pest management strategies to mitigate this risk of exposure. By providing a comprehensive overview of pesticide classification, mechanisms of action, and implications, this review aims to inform and guide us to the safe and effective use of pesticides for daily agricultural practices.

A Robust Method for Simultaneous Determination and Risk Assessment of Multiresidual Pesticides in Fishery Products.

In this study, we developed and validated a multiresidue analytical method for the simultaneous detection of 24 pesticides in fishery products. Using the EN15662 extraction method and C18 as the adsorbent for purification, the validation results complied with Codex guidelines, achieving recovery rates between 70% and 120% and relative standard deviation values (%RSD) within 20%, indicating excellent performance. The limit of detection ranged from 0.25 to 0.8 ng/kg, and the limit of quantification was between 3 and 10 ng/g, providing sufficient sensitivity to comply with future regulatory standards. The calibration curves for all 24 pesticides exhibited great linearity (R2 > 0.98), also satisfying the Codex requirements. The matrix effect was less than 30% for some pesticides-within ±20%-indicating minimal interference from impurities. An analysis of 300 fishery samples from nine regions across South Korea detected lufenuron at 10 ng/g in eels; however, the risk assessment was below 0.19%, posing no significant hazard to public health. This newly developed analytical method proved effective for the multi-analysis of pesticide residues in fishery products, offering rapid and reliable monitoring of the import and export safety of fishery products.

Unveiling the development trends of environmental and human health concerns for pesticides: Integrating an intelligent approach and data mining across diverse databases.

The impact of pesticide use on environmental and human health has been a persistent global concern. In the era of big data, the scientific literature concerning big data is a significant source of information; however, it is difficult to construct an optimal policy based on traditional insight using keyword searches or a single static-specialized database. In this study, we constructed a new path for data mining across multiple databases to provide a comprehensive picture of the major issues concerning environmental pollution and human health as a result of pesticide use at the global scale. This approach uses a classic unsupervised learning algorithm, Latent Dirichlet Allocation (LDA), in combination with a newly developed dataset of pesticide-associated human health outcomes (PAHHO), including 618 health outcomes classified into 14 types of toxic effects. Our data visualization revealed a shift in the scientific center for pesticide research over the past five decades. The major issues concerning environmental pollutants and health outcomes varied among different countries and in different periods, which was verified in our analysis of several organochlorine pesticides (OCPs) about which people are particularly concerned. A cooccurrence network of adverse health outcomes has gradually increased, suggesting that the impact of pesticides on human health is persistent and cumulative. Our work not only provides a promising research direction related to the most concerning issues in a systematic and visualized way but also provides valuable references to formulate optimal strategies for the goal of the global "One Health" objective in pesticide regulation.

The impact of managed aquifer recharge on the fate and transport of pesticides in agricultural soils.

Groundwater aquifers worldwide experience unsustainable depletion, compounded by population growth, economic development, and climate forcing. Managed aquifer recharge provides one tool to alleviate flood risk and replenish groundwater. However, concerns grow that intentional flooding of farmland for groundwater recharge, a practice known as Ag-MAR, may increase the leaching of pesticides and other chemicals into groundwater. This study employs a physically based unsaturated flow model to determine the fate and transport of residues of four pesticide in three vadose zone profiles characterized by differing fractions of sand (41 %, 61 %, and 84 %) in California's Central Valley. Here, we show that the complex heterogeneity of alternating coarse and fine-grain hydrogeologic units controls the transit times of pesticides and their adsorption and degradation rates. Unsaturated zones that contain a higher fraction of sand are more prone to support preferential flow, higher recharge rates (+8 %), and faster (42 %) water flow and pesticide transport, more flooding-induced pesticide leaching (about 22 %), as well as more salt leaching correlating with increased risks of groundwater contamination. Interestingly, considering preferential flow predicted higher degradation and retention rates despite shorter travel times, attributed to the trapping of pesticides in immobile zones where they degrade more effectively. The findings underscore the importance of considering soil texture and structure in Ag-MAR practices to minimize environmental risks while enhancing groundwater recharge. The study also highlights that selecting less mobile pesticides can reduce leaching risks in sandy areas.

Sensitive Coatings Based on Molecular-Imprinted Polymers for Triazine Pesticides' Detection.

Triazine pesticide (atrazine and its derivatives) detection sensors have been developed to thoroughly check for the presence of these chemicals and ultimately prevent their exposure to humans. Sensitive coatings were designed by utilizing molecular imprinting technology, which aims to create artificial receptors for the detection of chlorotriazine pesticides with gravimetric transducers. Initially, imprinted polymers were developed, using acrylate and methacrylate monomers containing hydrophilic and hydrophobic side chains, specifically for atrazine, which shares a basic heterocyclic triazine structure with its structural analogs. By adjusting the ratio of the acid to the cross-linker and introducing acrylate ester as a copolymer, optimal non-covalent interactions were achieved with the hydrophobic core of triazine molecules and their amino groups. A maximum sensor response of 546 Hz (frequency shift/layer height equal to 87.36) was observed for a sensitive coating composed of 46% methacrylic acid and 54% ethylene glycol dimethacrylate, with a demonstrated layer height of 250 nm (6.25 kHz). The molecularly imprinted copolymer demonstrated fully reversible sensor responses, not only for atrazine but also for its metabolites, like des-ethyl atrazine, and structural analogs, such as propazine and terbuthylazine. The efficiency of modified molecularly imprinted polymers for targeted analytes was tested by combining them with a universally applicable quartz crystal microbalance transducer. The stable selectivity pattern of the developed sensor provides an excellent basis for a pattern recognition procedure.

Profoxydim in Focus: A Structural Examination of Herbicide Behavior in Gas and Aqueous Phases.

This study investigates the chemical structure of profoxydim, focusing on its E-isomer, the main commercial form. The research aimed to determine the predominant tautomeric forms under various environmental conditions. Using proton and carbon-13 NMR spectroscopy alongside theoretical modeling, we examined tautomers and their conformers in different solvents (MeOD, DMSO, CDCl3, benzene) to mimic gas and aqueous phases. The findings reveal that the enolic form dominates in the gas phase, while the ketonic form prevails in aqueous environments, providing key insights into the herbicide's environmental behavior. We also observed an isomeric transition from E to Z under acidic conditions, which could affect profoxydim's reactivity in natural environments. The theoretical calculations indicated that in acidic conditions, the E and Z forms are nearly degenerate, with the E form remaining dominant in neutral environments. Additionally, QSAR models assessed the toxicity of various tautomers, revealing significant differences that could impact bioactivity and environmental fate. This research offers crucial insights into the structural dynamics of profoxydim, contributing to cyclohexanedione chemistry and the development of more effective herbicides.