Detection Of Pesticides Research Articles

Development of a simple polymer-based sensor for detection of the Pirimicarb pesticide

In this study, a sensitive and selective fluorescent chemosensor was developed for the determination of pirimicarb pesticide by adopting the surface molecular imprinting approach. The magnetic molecularly imprinted polymer (MIP) nanocomposite was prepared using pirimicarb as the template molecule, CuFe2O4 nanoparticles, and graphene quantum dots as a fluorophore (MIP-CuFe2O4/GQDs). It was then characterized using X-ray diffraction (XRD) technique, Fourier transforms infrared (FT-IR) spectroscopy, scanning electron microscope (SEM), and transmission electron microscopy (TEM). The response surface methodology (RSM) was also employed to optimize and estimate the effective parameters of pirimicarb adsorption by this polymer. According to the experimental results, the average particle size and imprinting factor (IF) of this polymer are 53.61 nm and 2.48, respectively. Moreover, this polymer has an excellent ability to adsorb pirimicarb with a removal percentage of 99.92 at pH = 7.54, initial pirimicarb concentration = 10.17 mg/L, polymer dosage = 840 mg/L, and contact time = 6.15 min. The detection of pirimicarb was performed by fluorescence spectroscopy at a concentration range of 0–50 mg/L, and a sensitivity of 15.808 a.u/mg and a limit of detection of 1.79 mg/L were obtained. Real samples with RSD less than 2 were measured using this chemosensor. Besides, the proposed chemosensor demonstrated remarkable selectivity by checking some other insecticides with similar and different molecular structures to pirimicarb, such as diazinon, deltamethrin, and chlorpyrifos.

Porphyrin-based covalent organic framework as oxidase mimic for highly sensitive colorimetric detection of pesticides.

A covalent organic framework-based strategy was designedfor label-free colorimetric detection of pesticides. Covalent organic framework-based nanoenzyme with excellent oxidase-like catalytic activity was synthesized. Unlike other artificial enzymes, porphyrin-based covalent organic framework (p-COF) as the oxidase mimic showed highly catalytic chromogenic activity and good affinity toward TMB without the presence of H2O2, which can be used as substitute for peroxidase mimics and H2O2 system in the colorimetric reaction. Based on the fact that the pesticide-aptamer complex can inhibit the oxidase activity of p-COF and reduced the absorbance at 650nm in UV-Vis spectrum, a label-free and facile colorimetric detection of pesticides was designed and fabricated. Under the optimized conditions, the COF-based colorimetric probe for pesticide detection displayed high sensitivity and selectivity. Taking fipronil for example the limit of detection was 2.7ng/mL and the linear range was 5-500,000ng/mL. The strategy was successfully applied to the detection of pesticides with good recovery , which was in accordance with that of HPLC-MS/MS. The COF-based colorimetric detection was free of complicated modification H2O2, which guaranteed the accuracy and reliability of measurements. The COF-based sensing strategy is a potential candidate for the sensitive detection of pesticides of interests.

Glutathione‑iron hybrid nanozyme-based colorimetric sensor for specific and stable detection of thiram pesticide on fruit juices

Glutathione‑iron hybrid nanozyme-based colorimetric sensor for specific and stable detection of thiram pesticide on fruit juices

Integrating transformer-based machine learning with SERS technology for the analysis of hazardous pesticides in spinach

This study introduces an innovative strategy for the rapid and accurate identification of pesticide residues in agricultural products by combining surface-enhanced Raman spectroscopy (SERS) with a state-of-the-art transformer model, termed SERSFormer. Gold-silver core-shell nanoparticles were synthesized and served as high-performance SERS substrates, which possess well-defined structures, uniform dispersion, and a core-shell composition with an average diameter of 21.44 ± 4.02nm, as characterized by TEM-EDS. SERSFormer employs sophisticated, task-specific data processing techniques and CNN embedders, powered by an architecture features weight-shared multi-head self-attention transformer encoder layers. The SERSFormer model demonstrated exceptional proficiency in qualitative analysis, successfully classifying six categories, including five pesticides (coumaphos, oxamyl, carbophenothion, thiabendazole, and phosmet) and a control group of spinach data, with 98.4% accuracy. For quantitative analysis, the model accurately predicted pesticide concentrations with a mean absolute error of 0.966, a mean squared error of 1.826, and an R2 score of 0.849. This novel approach, which combines SERS with machine learning and is supported by robust transformer models, showcases the potential for real-time pesticide detection to improve food safety in the agricultural and food industries.

Mxene-derived Na2O7Ti3 nanoribbon as a promising electrode material for the detection of ethyl paraoxon in complex matrices

This study reports the development of MXene (Ti3C2Tx) derived sodium titanate nanoribbon-based electrochemical sensor for pesticide detection. Titanium Carbide (Ti3C2) MXene-derived sodium titanate nanoribbon (MNR) was obtained by facile hydrothermal synthesis and characterized by powder XRD, field emission scanning electron microscopy (FE-SEM), energy-dispersive X-ray analysis(EDS) and, high-resolution transmission electron microscopy (HR-TEM). The synthesized water-dispersed MNR was stabilized with nafion and deposited on the surface of glassy carbon electrodes (GCE), which provide a symmetrical uniform electrode surface. Further, the electrodes were electrochemically characterized with cyclic voltammetry (CV), differential pulse voltammetry (DPV), linear sweep voltammetry(LSV), and electrochemical impedance spectroscopy (EIS). The electrochemical sensing of ethyl paraoxon was carried out in 0.1 M phosphate buffer (PB) by CV, LSV, and DPV. The developed electrochemical sensor exhibited a limit of detection (LOD) of 0.22 nM, a very wide detection range from 0.69 nM to 174.03 nM, and a reliable sensitivity of 0.707 µA/nM/cm2. Moreover, the developed sensor was also employed for the detection of ethyl paraoxon in real samples (vegetable extract spiked with the pesticide). The results suggest that the developed MNR-based sensor would be a potential approach for efficient and accurate detection of ethyl paraoxon in ambient samples, with minimal interference.

Flexible Sponge Surface Enhances Raman Scattering (SERS) Substrate with Patterned Superwettability for Ultrasensitive Pesticide Detection

Flexible Sponge Surface Enhances Raman Scattering (SERS) Substrate with Patterned Superwettability for Ultrasensitive Pesticide Detection

Universal organophosphate pesticides detection by peptide based fluorescent probes

In practical applications, the rapid and efficient detection of universal organophosphorus pesticides (OPs) can assist inspectors in quickly identifying the presence of OPs in samples. However, this presents a challenge for most well-established methods, typically designed to detect only a specific type of organophosphorus molecule at a time. In this proof-of-concept study, we draw inspiration from the structural similarities among OPs to develop innovative peptide-based fluorescence probes for the first time, which could efficiently detect a broad range of OPs within a mere 3 min. Analysis of fluorescence curve fitting reveals a clear linear correlation between the fluorescent intensity of the peptide probes and the concentration of OPs. Additionally, the selectivity analysis indicates that these peptide fluorescent probes exhibit an excellent response to various OPs while maintaining sufficient selectivity for detecting other pesticide types. Accurate sample analysis has also highlighted the potential of these peptide probes as practical tools for the rapid detection of OPs in actual vegetable samples. In summary, this proof-of-concept study presents an innovative approach to designing and developing ultrafast, universally peptide-based OP probes. These custom-designed peptide probes may facilitate rapid sample screening and offer initial quantification for OPs, potentially saving valuable time and effort in practical OP detection.

Raman silent region – based method for detection of pesticides with cyano group

Based on the fact that not all chemical substances possess good Raman signals, this article focuses on the Raman silent region signals of pesticides with cyano group. Under the optimized conditions of methanol–water (1:1, v/v) as the solvent, irradiation at 302 nm light source for 20 min, and the use of 0.5 mol/L KI as the aggregating agent, Surface-enhanced Raman spectroscopy (SERS) method for azoxystrobin detection was developed by the Raman silent region signal of 2230 cm−1, and verified by detecting the spiked grapes with different concentrations of azoxystrobin. Other four pesticides with cyano group also could be identified at the peak of 2180 cm−1, 2205 cm−1, 2125 cm−1, and 2130 cm−1 for acetamiprid, phoxim, thiacloprid and cymoxanil, respectively. When azoxystrobin or acetamiprid was mixed respectively with chlorpyrifos without cyano group, their SERS signals in the Raman silent region of chlorpyrifos were not interfered, while mixed with cymoxanil in different ratios (1:4, 1:1 and 4:1), respectively, each two pesticides with cyano group could be distinguished by the changes in the Raman silent region. In further, four pesticides with or without cyano group were mixed together in 1:1:1:1 (acetamiprid, cymoxanil, azoxystrobin chlorpyrifos), and each pesticide still could be identified even at 0.5 mg/L. The results showed that the SERS method combined with UV irradiation may provide a new way to monitor the pesticides with C≡N performance in the Raman silent region without interference from the food matrix.

Platinum-nickel nanoparticle-based oxidase-like nanozyme for colorimetric/photothermal dual-mode detection of organophosphorus pesticides

In this study, based on the oxidase-like (OXD) activity of platinum-nickel nanoparticles (Pt-Ni NPs) nanozyme and further in collaboration with 3,3′,5,5′-tetramethylbenzidine (TMB), a colorimetric/photothermal dual-mode probe for organophosphorus pesticides (OPs) detection was developed. TMB undergone the catalytic oxidation of Pt-Ni NPs to change from colorless to blue oxidized substance (oxTMB) and exhibited higher temperature under near-infrared irradiation. The hydrolysis product of acid phosphatase (ACP) with L-ascorbic acid 2-phosphate trisodium competed with the OXD-like activity of Pt-Ni NPs to prevent the oxidation of TMB. As the concentration of OPs grew, inhibiting the blocking effect by deactivating ACP, the generated oxTMB caused notable color and temperature changes in the reaction system. The dual-mode probe responded linearly to chlorpyrifos, with the detection limits for colorimetric and photothermal modes of 1.2 ng/mL and 1.66 ng/mL, respectively. This work proposes a simple and reliable colorimetric/photothermal platform for OPs identification, which overcomes the problem that single-mode detection probes are susceptible to external factors, and has broad application potential in the field of food safety.

Detection and Identification of Pesticides in Fruits Coupling to an Au-Au Nanorod Array SERS Substrate and RF-1D-CNN Model Analysis.

In this research, a method was developed for fabricating Au-Au nanorod array substrates through the deposition of large-area Au nanostructures on an Au nanorod array using a galvanic cell reaction. The incorporation of a granular structure enhanced both the number and intensity of surface-enhanced Raman scattering (SERS) hot spots on the substrate, thereby elevating the SERS performance beyond that of substrates composed solely of an Au nanorod. Calculations using the finite difference time domain method confirmed the generation of a strong electromagnetic field around the nanoparticles. Motivated by the electromotive force, Au ions in the chloroauric acid solution were reduced to form nanostructures on the nanorod array. The size and distribution density of these granular nanostructures could be modulated by varying the reaction time and the concentration of chloroauric acid. The resulting Au-Au nanorod array substrate exhibited an active, uniform, and reproducible SERS effect. With 1,2-bis(4-pyridyl)ethylene as the probe molecule, the detection sensitivity of the Au-Au nanorod array substrate was enhanced to 10-11 M, improving by five orders of magnitude over the substrate consisting only of an Au nanorod array. For a practical application, this substrate was utilized for the detection of pesticides, including thiram, thiabendazole, carbendazim, and phosmet, within the concentration range of 10-4 to 5 × 10-7 M. An analytical model combining a random forest and a one-dimensional convolutional neural network, referring to the important variable-one-dimensional convolutional neural network model, was developed for the precise identification of thiram. This approach demonstrated significant potential for biochemical sensing and rapid on-site identification.

Pesticides and Polychlorinated Biphenyls in Milk and Dairy Products in Croatia: A Health Risk Assessment.

The aim of this study was to evaluate contamination levels and the frequency of detection of organochlorine (OCPs) and organophosphate pesticides (OPPs), pyrethroids, carbamates and polychlorinated biphenyls (seven PCB congeners) in a total of 534 samples of cow's, sheep's and goat's milk and dairy products from Croatia. Concentrations above the limit of quantification (LOQ) were measured for fourteen OCPs, nine OPPs, six pyrethroids, one carbamate and PCBs with a total of 172 results, and no concentrations exceeded the maximal residue levels defined by the European Union. The mean concentrations of pesticides and the sum of seven PCBs were determined in the ranges 0.92-17.4 μg/kg and 1.38-2.74 μg/kg. Pesticides were quantified in 27% of samples, and seven PCBs were quantified in 5.23% of samples. Among the three pesticide groups, the highest numbers of quantified results were found for OCPs (12.1-20.8%). The highest frequencies of detection were found for the sum of 4,4'-dichlorodiphenyltrichloroethane and its isomers (DDTs), hexachlorobenzene and seven PCBs. The sum of seven PCBs was quantified within the range of 3.3-6.67% of samples per milk type and dairy products. Among the OPPs, the highest frequency of detection was found for chlorpyrifos in cow's milk. Based on the estimated daily intakes, chronic risk characterisation showed no risk for adults or ten-year-old children for the consumption of cow's milk and dairy products.

Direct detection of dithiocarbamate fungicides by SALDI/MS using porous TiC ceramic powder as a substrate.

Dithiocarbamate fungicides (DTCs) have been widely used all over the world. Some of them show toxicities, such as growth toxicity and teratogenicity. Therefore, the analysis of DTCs in environments or crops is very significant. However, their direct and individual analysis was difficult, because most of them are metal complex compounds and have macromolecular properties and a low solubility in water or organic solvents. In the conventional analytical methods for DTCs, the total amount of DTCs was obtained by the quantification of the derivatives of the ligand or by measuring the carbon disulfide formed by the decomposition of the fungicides. Surface assisted laser desorption (SALDI)/MS can detect various compounds, such as metal complexes and macromolecules, present in a nanostructured substrate. The porous titanium carbide (TiC) ceramic powder shows adsorptive properties to various substances and can be used as a substrate for SALDI/MS. In this study, a method for the individual and direct detection of dithiocarbamate pesticides by SALDI/MS using porous TiC ceramics as a substrate has been developed. The dithiocarbamate fungicide was mixed with the porous TiC powder in a mortar, and the mixture was analyzed by SALDI/MS. The deprotonated ion of the ethylene-bis-dithiocarbamate complex, mancozeb or zineb, was detected in the negative ion mode. For the dimethyldithiocarbamate complexes, ferbam and ziram, the ion of the eliminated dithiocarbamate ligand was detected in the positive ion mode. Calibration curves by the present method for Manzeb showed good linearity by using an internal standard material. Based on these results, we concluded that this method is useful for the analysis of DTCs.

Research on Soil Pesticide Residue Detection Using an Electronic Nose Based on Hybrid Models

At present, the electronic nose has became a new technology for the rapid detection of pesticides. However, the technique may misidentify them for samples that have not been involved in training. Therefore, a hybrid model based on unsupervised and supervised learning was proposed for the first time in this paper. The model divided the detection process of soil pesticide residues into two steps: (1) an unsupervised machine learning method was used to identify whether the soil was contaminated with pesticides; (2) when the soil was contaminated with pesticides, a supervised classifier was further used to predict the types of pesticides in the soil. The experimental results showed that the model had a recognition accuracy of 99.3% and 99.27% for whether the soil was contaminated with pesticides and the pesticide type of the contaminated soil, respectively, with a detection time of 0.03 s. The results revealed that the proposed hybrid model can quickly and comprehensively reflect the soil information’s status.

Surface-enhanced Raman spectroscopy (SERS) substrate based on gold nanostars–silver nanostars for imidacloprid detection

Surface-enhanced Raman spectroscopy (SERS) is a powerful molecular spectroscopy technique that combines Raman spectroscopy with nanostructured metallic surfaces to amplify the Raman signals of target molecules by more than 103. The high sensitivity of SERS poses a significant opportunity for pesticide detection in complex matrices at ultralow concentrations. In this study, we improved the SERS sensitivity for imidacloprid (IMD) by employing silver nanostars (AgNs) coated with gold nanostars (AuNs) as the SERS-active substrate. The SERS response towards IMD detection increased based on the combination of AuNs and AgNs on the substrate surface. The intensity of the SERS signal of IMD using the AuNs/AgNs substrate increased compared to using individual metal nanoparticle substrates. The excellent reproducibility of SERS intensity using the AuNs/AgNs substrate was achieved with a low relative standard derivative (RSD) of 4.87% for 20 different spots on the same sample and 5.19% for 20 different samples. This detection system can be used for multiple tests, which is crucial for the advancement of handheld sensors designed for field use, where minimal or no high-level technical support is accessible.

Cellulose nanofiber-templated metal-organic frameworks for fluorescent detection of methyl parathion pesticides

Methyl parathion is a typical organophosphorus pesticide that poses threats to the global environment and human health. In this study, we developed a portable 2D sensing pad for monitoring methyl parathion based on the aggregation-induced emission (AIE) properties of an innovated hybrid material that integrates cellulose nanofibers (CNFs) with luminescent metal-organic frameworks (LMOFs). The hybrid material enhanced the flexibility and moldability of LMOFs and significantly improved the scalability of sensing material. The resulting CNF/LMOF material was shaped into a 2D pad, exhibiting fluorescent properties under UV exposure. The fluorescence of the pad was quenchable upon exposure to methyl parathion. This host-guest interaction enabled the precise quantification of the pesticide’s concentration by monitoring the intensity variation of the fluorescence at 405 nm wavelength. We further engineered these hybrid pads into a user-friendly and portable sensing prototype, and then validated them with real sample testing. Time-dependent Density Functional Theory calculations were employed to elucidate the underlying fluorescence quenching mechanism triggered by methyl parathion. This work introduces a practical and sustainable sensing platform for pesticide detection.

Simultaneous detection of mycotoxins and pesticides in human urine samples: A 24-h diet intervention study comparing conventional and organic diets in Spain

Pesticides and mycotoxins, prominent chemical hazards in the food chain, are commonly found in plant-based foods, contributing to their pervasive presence in the human body, as evidenced by biomonitoring programs. Despite this, there is limited knowledge about their co-occurrence patterns. While intervention studies have demonstrated that organic diets can significantly reduce pesticide levels, their impact on mycotoxin exposure has been overlooked.To address this gap, this study pursued two objectives: first, to characterize the simultaneous presence of mycotoxins and pesticides in human urine samples by means of the control of the biomarkers of exposure, and second, to investigate the influence of consuming organic foods on these co-exposure patterns. A pilot study involving 20 healthy volunteers was conducted, with participants consuming either exclusively organic or conventional foods during a 24-h diet intervention in autumn 2021 and spring 2022 to account for seasonal variability. Participants provided detailed 24-h dietary records, and their first-morning urine samples were collected, minimally treated and analysed using LC-Q-ToF-MS by means of a multitargeted method in order to detect the presence of these residues.Results indicated that among the 52 screened compounds, four mycotoxins and seven pesticides were detected in over 25% of the samples. Deoxynivalenol (DON) and the non-specific pesticide metabolite diethylphosphate (DEP) exhibited the highest frequency rates (100%) and concentration levels. Correlations were observed between urine levels of mycotoxins (DON, ochratoxin alpha [OTα], and enniatin B [ENNB]) and organophosphate pesticide metabolites DEP and 2-diethylamino-6-methyl-4-pyrimidinol (DEAMPY). The pilot intervention study suggested a reduction in ENNB and OTα levels and an increase in β-zearalenol levels in urine after a short-term replacement with organic food. However, caution is advised due to the study's small sample size and short duration, emphasizing the need for further research to enhance understanding of the human chemical exposome and refine chemical risk assessment.

Copper Oxide Anchored Carbon Nanofibers: A Versatile Platform for Multiplex Detection of Antibiotics, Heavy Metals and Pesticides.

Electrochemical sensors offer promising prospects for real-time pollutant monitoring. In this study, copper oxide-dispersed graphitic carbon nanofibers (CuO-CNFs) grown via chemical vapour deposition were employed as a robust platform for detecting a variety of environmental pollutants. This array-based sensor adeptly identifies three different classes of analytes, i. e., antibiotics (chloramphenicol (CP) and tylosin tartrate (TT)), heavy metals (cadmium (Cd) and lead (Pb)), and pesticides (quinalphos (QP) and imidacloprid (IP)). Electron collection is facilitated by a glassy carbon electrode, while various physico-electrochemical methods delve into the properties of CuO-CNFs. The CuO-CNF-modified GCE array rapidly discerns (<15 sec) a broad linear range: 1-20 ppm for CP, 1-13.33 ppm for TT, 0.66-11.66 ppm for Cd, 20-33.33 ppm for Pb, 1.6-11.6 ppm for QP, and 5-25 ppm for IP, boasting quantification limits of 1.0, 1.0, 0.66, 20.0, 1.6, and 5.0 ppm for CP, TT, Cd, Pb, QP, and IP, respectively. Notably, this sensor achieves simultaneous identification of mixed analytes, including CP and TT, Cd and Pb, and QP and IP, within real tap water. Furthermore, the electrochemical sensor exhibits robustness; heightened sensitivity, selectivity, and stability; a swift response; and impressive reproducibility in detecting CP, TT, Cd, Pb, QP, and IP within aqueous samples. Consequently, this array-based electrochemical sensor has emerged as a rapid and simultaneous detection tool for diverse pollutant residues in surface and groundwater samples.

Miniaturized flexible micro-tube plasma ionization source for the effective ionization of non-easily ionizable pesticides in food with liquid chromatography/mass spectrometry

In this article, we have studied the potential of flexible microtube plasma (FμTP) as ionization source for the liquid chromatography high-resolution mass spectrometry detection of non-easily ionizable pesticides (viz. nonpolar and non-ionizable by acid/basic moieties). Phthalimide-related compounds such as dicofol, dinocap, o-phenylphenol, captan, captafol, folpet and their metabolites were studied. Dielectric barrier discharge ionization (DBDI) was examined using two electrode configurations, including the miniaturized one based on a single high-voltage (HV) electrode and a virtual ground electrode configuration (FμTP), and also the two-ring electrode DBDI configuration. Different ionization pathways were observed to ionize these challenging, non-easily ionizable nonpolar compounds, involving nucleophilic substitutions and proton abstraction, with subtle differences in the spectra obtained compared with APCI. An average sensitivity increase of 5-fold was attained compared with the standard APCI source. In addition, more tolerance with matrix effects was observed in both DBDI sources. The importance of the data reported is not just limited to the sensitivity enhancement compared to APCI, but, more notably, to the ability to effectively ionize nonpolar, late-eluting (in reverse-phase chromatography) non-ionizable compounds. Besides o-phenylphenol ([M − H]-), all the parent species were efficiently ionized through different mechanisms involving bond cleavages through the effect of plasma reagent species or its combination with thermal degradation and subsequent ionization. This tool can be used to figure out overlooked nonpolar compounds in different environmental samples of societal interest through non-target screening (NTS) strategies.

Enzymatic biosensor for organophosphate pesticide detection using extract from the brain of Genyatremus luteus

This study developed a biosensor for the detection of pesticides, particularly organophosphates, employing an enzymatic inhibition technique using ECPP (Genyatremus luteus), a natural source of acetylcholinesterase. The stonefish is found from the Antilles to southern Brazil and is an important fishery resource for the states of Maranhão and Pará. This species is prominent in artisanal fisheries along the coast of Maranhão, standing out among several economically significant species due to its high abundance and popularity among the population of the state of Maranhão, where it ranks high in daily fish consumption preferences. High consumption consequently leads to waste generation. A byproduct of processing this species was utilized to construct the biosensor. Characterization of the crude extract, optimal temperature, pH, and kinetic studies with different substrate concentrations were conducted. To construct the biosensor, ECPP was incorporated into a carbon graphite paste with the mediator tetracyanoquinodimethane (TCNQ). Following sensor preparation, electrochemical characterization of the immobilized enzyme sensor system commenced. The results were chronocoulometrically recorded. The construction of this biosensor replaces the expensive and non-locally produced acetylcholinesterase from the commercially available electric eel marketed by Sigma, thus offering a cheaper alternative adapted to local conditions.

Porous covalent organic framework nanofibrous membrane for excellent enrichment and ultra-high sensitivity detection of trace organochlorine pesticides in water

Developing adsorbents with high performance and long service life for effective extracting the trace organochlorine pesticides (OCPs) from real water is attracting numerous attentions. Herein, a self-standing covalent organic framework (COF-TpPa) membrane with fiber morphology was successfully synthesized by using electrospun nanofiber membranes as template and employed as solid-phase microextraction (SPME) coating for ultra-high sensitivity extraction and analysis of trace OCPs in water. The as-synthesized COF-TpPa membrane exhibited a high specific surface area (800.83 m2 g−1), stable nanofibrous structure, and excellent chemical and thermal stability. Based on the COF-TpPa membrane, a new SPME analytical method in conjunction with gas chromatography-mass spectrometry (GC–MS) was established. This proposed method possessed favorable linearity in concentration of 0.05–2000 ng L−1, high sensitivity with enrichment factors ranging from 2175 to 5846, low limits of detection (0.001–0.150 ng L−1), satisfactory precision (RSD < 10 %), and excellent repeatability (>150 cycles), which was better than most of the reported works. Additionally, the density functional theory (DFT) calculations and XPS results demonstrated that the outstanding enrichment performance of the COF-TpPa membrane was owing to synergistic effect of π–π stacking effects, high specific surface area and hydrogen bonding. This work will expect to extend the applications of COF membrane to captures trace organic pollutants in complex environmental water, as well as offer a multiscale interpretation for the design of effective adsorbents.