Sulfonamide antibiotics（SAs） are artificially synthesized antibiotics， which have been widely used in the medical industry and animal husbandry because of their broad antibacterial property. Unfortunately， SAs can be metabolized by humans or animals and enter the environment through surface runoff， posing threats to environmental ecology and human health. Therefore， it is crucial to develop simple， rapid， highly efficient， and sensitive analytical methods for detecting SAs in water. Sample pretreatment is important for the extraction and enrichment of pollutants from environmental water. Magnetic solid-phase extraction（MSPE） is a new sample pretreatment method， which uses magnetic materials as adsorbents dispersed in solution， and rapid separation can be achieved by the aid of external magnets. Because of its advantages of short enrichment time， less organic solvent consumption， and easy separation of adsorbents， MSPE has attracted much attention. The key to MSPE is the preparation of highly selective magnetic adsorbents. Covalent organic frameworks（COFs） have the advantages of large surface， chemical and thermal stability， tunable porous structure， low density and easy functionalization. Therefore， a sample pretreatment method combining MSPE and COF for the analysis of SAs in complex matrices is very promising. The contents of SAs in environmental water are low， ultra performance liquid chromatography-tandem mass spectrometry（UPLC-MS/MS） has high sensitivity and accuracy. In this paper， the magnetic COF material Fe₃O₄@TpDT was prepared by in-situ synthesis method， which was used as an MSPE adsorbent for the adsorption and enrichment of eight SAs in environmental waters. Based on the π-π conjugation， hydrogen bonding， electrostatic interaction and molecular size effect between Fe₃O₄@TpDT and SAs， in combination with UPLC-MS/MS， this study established a new method for the determination of eight SAs in environmental water samples. The successful synthesis of Fe₃O₄@TpDT was confirmed using scanning electron microscopy（SEM）， Fourier transform infrared spectroscopy（FT-IR）， X-ray diffraction（XRD）， surface area analyzer and X-ray photoelectron spectroscopy（XPS） spectrum. To obtain the optimal extraction efficiency， the extraction conditions（dosage of material， pH of water sample， extraction time） and elution conditions（type and volume of elution solvent， elution time） were systematically investigated. The optimization results show that the Fe₃O₄@TpDT adsorbent can completely adsorb the target compounds within 6 min. After elution with 1 mL of methanol for 2 min， the target compounds can be fully desorbed. The target compound were separated on an ACQUITY UPLC BEH C18 column（100 mm×2.1 mm， 1.7 μm） and gradient elution was carried out with methanol-0.1% formic acid solution as the mobile phase. Multiple reaction monitoring（MRM） was conducted in the positive electrospray ionization mode and the ion source temperature and ion source voltage were set to 500 ℃ and 5 kV， respectively. Under the optimal extraction conditions， the enrichment factors（EFs） of Fe₃O₄@TpDT for eight SAs were 39‒48. The methodological verification results indicated that the eight SAs had good linear relationships（correlation coefficients（r²）≥0.992 6）， and the limits of detection（LODs） and quantification（LOQs） were 0.80‒3.44 ng/L and 2.66‒11.47 ng/L， respectively. The spiked recovery tests were conducted at three spiked levels（50， 500 and 800 ng/L） in blank water samples（tap water plant effluent）. The recoveries of the eight SAs were 73.0%‒112.9%， and the intra- and inter-day precisions were 4.4%‒12.5% and 8.7%‒19.2%， respectively. Finally， this method was successfully applied to the determination of eight SAs in environmental water samples（tap water plant effluent， reservoir water and seawater）. The results showed that no SAs were detected in tap water plant effluent， three SAs were detected in the reservoir water， and one SA was detected in the seawater. At three spiked levels（50， 500 and 800 ng/L）， the recoveries of eight SAs in reservoir water and seawater were 55.0%‒100.9%， and the relative standard deviations（RSDs） were 1.3%‒14.0%. This method is simple to operate， has a short extraction time， and has good accuracy and precision， providing technical support for the enrichment detection of SAs in environmental water samples.

In order to achieve rapid and accurate analysis of sulfonamide and tetracycline drugs in aquatic products， a universal method for the rapid screening and confirmation of multiple residues of 36 sulfonamide and four tetracycline drugs was established. The method combined the PRiME HLB solid-phase extraction（SPE） column with ultra performance liquid chromatography-time-of-flight-mass spectrometry（UPLC-TOF-MS）. Samples were extracted using 80% acetonitrile aqueous solution（containing 0.05 mol/L Na₂EDTA）. The resultant solution was purified by PRiME HLB SPE column and then blown to nearly dry with nitrogen. It was redissolved with 5% methanol aqueous solution and finally passed through a polytetrafluoroethylene filter membrane. Gradient elution was carried out using 0.1% formic acid aqueous solution（containing 2 mmol/L ammonium acetate solution） and 0.1% formic acid methanol solution as the mobile phases， and scanning was performed using the information dependent acquisition（IDA） mode of TOF-MS. The rapid screening and confirmation of the target compounds were achieved through information such as the precise m/z of the parent ion， retention time， isotope abundance ratio， and comparison with the secondary daughter-ion spectral library， and quantification is carried out by the external standard method（using the matrix-matched mixed standard solution）. The UPLC elution program was optimized to achieve good separation of 17 isomers in seven groups within 13 min. By optimizing the collision energy of the secondary mass spectrometry， a comprehensive secondary fragment ion mass spectrum is obtained. Combined with the collected information such as the chemical molecular formula and CAS number of the compounds， a complete database is established. In addition， the procedures of two purification columns（PRiME HLB column and HLB column） was compared， and the composition of the extraction solvent and the type of filter membrane were optimized to obtain the optimal experimental conditions. The methodological validation results indicated that 36 sulfonamide and four tetracycline drugs had a good linear relationship within the range of 2‒50 μg/L， and the correlation coefficients were all ≥0.990 68. Except for sulfanilamide and ambamide， whose LOQs were 10 μg/kg， the LOQs of the other 38 drugs were all 5 μg/kg. Using grass carp meat， shrimp meat， scallop meat and mackerel meat as blank matrix samples， at three spiked levels（5， 10 and 20 μg/kg）， the recoveries of the 40 drugs were 62.8%‒116.4%， and the RSDs were ≤13.8%. This method is simple to operate， has good stability and high universality， and can meet the requirements of rapid screening and confirmation of sulfonamide and tetracycline drugs in aquatic products.

This study developed a novel method for the detection of 22 antibiotics in marine sediments by integrating online solid-phase extraction（SPE） with ultra-high performance liquid chromatography-tandem mass spectrometry（UHPLC-MS/MS）. The method was subsequently applied to the analytical determination of antibiotics in offshore bay sediments. Optimal experimental conditions were established through systematic optimization of sample extraction and online SPE parameters. Sediment samples were extracted using an acetonitrile-EDTA/McIlvaine buffer solution（1∶1， v/v）， diluted with ultrapure water， and then purified and enriched using a large-pore styrene/divinylbenzene-packed PLRP-S online SPE column. The processed samples were separated on a Poroshell EC-C18 column（50 mm×2.1 mm， 1.9 µm） and detected in electrospray ionization（ESI） positive ion mode with multiple reaction monitoring（MRM） acquisition. The entire analytical process was completed within 14 min. The results showed that the 22 antibiotics showed good linearity in their respective mass concentration ranges with the correlation coefficients（R²）≥0.990 0， the limits of detection（LODs， S/N=3） were 0.001‒0.08 ng/g， and the limits of quantification（LOQs， S/N=10） were 0.004‒0.4 ng/g. The spiked recoveries of the 22 antibiotics under three spiked levels（low， medium and high） were 45.1%‒145.6% with the relative standard deviations（RSDs）<14%. The method was used to detect antibiotics in winter and summer sediment samples from Shandong Sishili Bay offshore. The results showed that a total of 19 antibiotics from five classes were detected in nine summer sediment samples， with the contents ranging from 0.01 to 34.64 ng/g； and oxytetracycline exhibited the highest detection level. A total of 20 antibiotics from five classes were detected in 10 winter sediment samples， with the contents ranging from 0.004-19.11 ng/g； and ofloxacin showed the highest detection level. Compared with the commonly used offline SPE method， this method greatly simplifies the sample purification process and provides a simple and effective method for the routine detection of common antibiotics in marine sediments.

To comprehensively assess the distribution， multi-media-partitioning behavior， and key environmental factors that influence the environmental fates of pharmaceuticals and personal care products（PPCPs）， this study employed a combination of field sampling and high-precision analysis to systematically investigate the spatiotemporal distributions， partitioning behavior， and ecological risks of 15 nonsteroidal anti-inflammatory drugs（NSAIDs） and preservatives in the seawater and offshore sediments of Yantai and Weihai. The results showed that the total mass concentrations of the 15 compounds ranged between 2.31 and 662.31 ng/L in seawater， and between 57.11 and 131.09 ng/g in sediments. Among them， antipyrine（PHZ）， fenoprofen（FPF）， and methylparaben（MPB） were the major pollutants in seawater， whereas ibuprofen（IBU） and ketoprofen（KPF） were dominant in sediments. Higher concentrations of PPCPs were observed in the summer， which closely mirrors their usage patterns and human activities during the summer and peak tourist seasons in Yantai and Weihai City. MPB， IBU， PHZ， and FPF exhibited average mass concentrations of 30.16， 15.15， 3.27， and 3.81 ng/L， respectively， in the summer. Regarding the spatial distributions of these compounds， the seawater collected from the Bohai Sea exhibited a higher total PPCP concentration than that in the Yellow Sea in spring and winter， whereas the reverse was observed in summer. Additionally， the total PPCP concentrations in surface and bottom seawater showed no significant seasonal differences. Sediment in the Yellow Sea was found to contain a higher total PPCP concentration than that in the Bohai Sea sediment. Ethylparaben and propylparaben exhibited sediment-water partitioning coefficients of（3.99±0.95） and（3.80±0.57） cm³/g， respectively， which are higher than their corresponding theoretically predicted values from EPISuite model， indicating the complexity of pollutant partitioning behavior between sediment and water in real environments. In terms of ecological risks， total risk quotient（RQ_T） values revealed that PPCP mixtures are likely to pose low risks to algae， crustaceans， and fish in the study area. In addition， while crustaceans exhibited a higher RQ_T value for PPCP mixtures than algae or fish， the differences were not significant. To identify whetherigh-risk pollutants existed in the study area， the prioritization index（PI） of each individual PPCP was calculated. The target PPCPs were found to have PI values of zero and were consequently classified as safe pollutants. Nonetheless， continuous attention needs to be paid to the levels and risks associated with multiple PPCPs in the marine environment， in view of the relative scarcity of studies.

Per- and polyfluoroalkyl substances（PFAS） are notorious environmental contaminants that are often referred to as “forever chemicals”. Eastern China is a major region that produces and utilizes PFAS. These substances can enter the environment and migrate to drinking water sources， thereby posing potential ecological and health risks. To investigate the occurrence and potential risks of both legacy and novel PFAS in the drinking water sources of this region， a study was conducted on water samples collected from 13 drinking water sources. Anion exchange solid-phase extraction coupled with ultra performance liquid chromatography-triple quadrupole mass spectrometry（UPLC-MS/MS） was used to determine PFAS in water. The pollution levels and spatial distribution characteristics of 50 legacy and novel PFAS in these drinking water sources were studied in detail and their ecological and health risks were also assessed. Twenty-six types of PFAS were detected in the drinking water sources of the eastern region， with total mass concentrations ranging from 80.0 to 282 ng/L and a median mass concentration of 153 ng/L. The relatively high concentrations of PFAS in these drinking water samples is likely due to heavy industrial activities in this region. Nevertheless， the levels of perfluorooctanoic acid（PFOA） and perfluorooctanesulfonic acid（PFOS） in all sampling sites were far below the limits of national drinking water standards of China. The detected PFAS in drinking water sources were predominantly short-chain compounds， such as perfluorobutanoic acid（PFBA） and perfluorobutanesulfonic acid（PFBS）， which accounted for 27.6% and 20.8% of the total PFAS concentration， respectively. In contrast， long-chain PFAS（with more than nine carbons） constituted less than 2% of the total PFAS concentration. The observed higher proportions of short-chain PFAS are rationalized by their somewhat higher mobilities in aquatic environments. Low levels of various novel PFAS， such as hexafluoropropylene oxide dimer acid（HFPO-DA）， 1H，1H，2H，2H-perfluorooctanesulfonic acid（6∶2 FTS）， perfluoro（2-ethoxyethane）sulfonic acid（PFEESA）， 9-chlorohexadecafluoro-3-oxanonane-1-sulfonic acid（9Cl-PF3ONS）， and perfluorooctanesulfonamide（FOSA） were detected to varying degrees in the drinking water sources. This indicated that novel PFAS are being increasingly produced and used as alternatives to those restricted by international and Chinese regulations. The overall PFAS pollution levels and compositions in the drinking water sources of Eastern China are significantly influenced by nearby industrial activities， with wastewater discharged from chemical industrial parks and related enterprises contributing significantly to the elevated PFAS levels in the drinking water sources. Pearson correlation analysis suggested that the PFAS in these drinking water sources likely arise from common pollution sources. Ecological risk-assessment data reveal that the PFAS risk quotient in the abovementioned drinking water sources ranged from 9.7×10^-6 to 8.9×10^-³， which suggests that the PFAS levels at the sampling sites in this study evidently pose no ecological risks. The hazard indices for perfluorohexanoic acid（PFHxS）， perfluorononanoic acid（PFNA）， HFPO-DA， and PFBS in the examined drinking water sources ranged from 0.16 to 0.89. The detected levels of these four PFAS are compliant with the limits set by the national primary drinking water regulations of the United States. This study furnishes foundational data that provide a comprehensive understanding of the pollution profiles of PFAS in drinking water sources in Eastern China. Continuous monitoring is necessary to ensure drinking-water safety for residents given the widespread occurrence of both legacy and novel PFAS in drinking water.

The increasing demand for the detection of polycyclic aromatic hydrocarbons（PAHs） in the complex matrices of the marine environment requires overcoming the limitations of traditional detection methods， particularly in terms of sensitivity and accuracy. Analyzing PAHs in seaweed matrices is often hindered by significant interference owing to the complex compositions of these matrices， which compromises both qualitative identification and quantitative determination. To address these challenges， this study developed an innovative and efficient method for detecting PAHs based on ultrasound-assisted gas-liquid microextraction（UA-GLME） coupled with gas chromatography-mass spectrometry（GC-MS）. The developed method involves extracting a seaweed sample with dichloromethane-hexane（DCM-HEX）（1∶1， v/v）， followed by further GLME. The separated sample is then analyzed using a DB-5MS capillary column（30 m×0.25 mm×0.25 µm） in SCAN and selective ion monitoring（SIM） modes. PAH extraction efficiencies were enhanced while significantly minimizing the co-extraction of interfering compounds by exploiting the cavitation effects of ultrasound. This optimization procedure improves both PAH-detection sensitivity and accuracy while reducing matrix effects. Under optimal conditions， the PAHs showed excellent linearity in the range of 5.0-2 000 ng/mL， with correlation coefficients（R²） exceeding 0.999. Limits of detection（LODs） ranged between 0.001 and 0.01 μg/mL， while method detection limits（MDLs） of 0.004–0.04 mg/kg were recorded. The recovery rates at high， medium， and low concentration levels were 62.32%-91.64%， with relative standard deviations（RSDs） between 2.94% and 9.15%. The developed method significantly reduces interference from lipophilic and low-volatility co-extractives， while removing co-extractives， such as long-chain alkanes， fatty acids， and sterols， at rates of up to 100%. Chromatographic comparisons revealed that the UA-GLME method delivers superior peak shapes for the target PAHs， enhanced signal-to-noise ratios， high quantitative accuracies， and remarkable resistance to seaweed-matrix interference. The method was used to detect PAHs in seaweed samples from the East China Sea， Bohai Sea， Yellow Sea， and South China Sea， with the 16 PAHs detected at varying levels. Both low-molecular-weight PAHs（such as naphthalene， phenanthrene， and fluorene） and high-molecular-weight PAHs（such as benzo［a］pyrene and benzo［k］fluoranthene） were detected at high rates. This method offers a reliable approach for the qualitative and quantitative analysis of PAHs in seaweed， thereby providing valuable technical support for assessing marine environmental pollution and evaluating risks. The developed method can be extended to other complex matrices by optimizing the ultrasound conditions and solvent system， thereby offering new strategies for environmental monitoring and pollutant-source tracing.

Emerging pollutants are substances that have recently been discovered or brought into focus， pose ecological or human-health risks， and have not yet been included in regulatory frameworks or for which existing management measures inadequately prevent and control their risks. Synthetic chemicals play key roles in progressing human society and improving quality of life. However， these chemicals may leak into the environment through unintentional or organized emissions during the life cycles of chemical-containing products， thereby becoming potential emerging pollutants and posing ecological and human-health threats. Many new chemicals are typically used without sufficient toxicity assessments； consequently， their potential threats are difficult to predict. Hence， effective toxicity assessments of existing and emerging chemicals are required to address this situation. Toxicity testing all chemicals is expected to be very time-consuming and economically expensive. In addition， there are discrepancies between experimental results from different laboratories leading to inconsistent toxicity-screening standards for emerging pollutants， which hinders preventing and controlling emerging pollutants and explaining their toxicity mechanisms. Addressing these issues requires the development of standard alternative toxicity-testing strategies that screen emerging pollutants in a high-throughput manner. In this study， machine-learning methods were used to predict the toxicities of various compounds in the Tox21 database. The RDKit and Mordred libraries were used to process structural data（presented in SMILES format） for compounds with the aim of generating molecular descriptors for their physicochemical properties. A set of refined features was screened through information-gain calculations and variable selection， and the data were fitted using Python’s Sklearn and XGBoost libraries. Prediction models were constructed based on the screened features using seven machine-learning algorithms in order to evaluate 12 different bioactive endpoints， including datasets related to endocrine disruption， DNA damage， and oxidative stress response， among others. Model performance was evaluated by calculating the accuracy of the test set， and data availability was characterized in terms of the application domain. All training and test data were found to be located in the application domain. The model was found to highly accurately predict 12 endpoints. This study clarified the relationship between the physicochemical properties of chemicals and nuclear receptor activity， and developed corresponding software tools. The model for the 12 Tox21 datasets exhibited an average area under the curve（AUC） of 0.84， and delivered better prediction performance than other participating models. Further insight into toxicological mechanisms was obtained through feature-importance analysis using Shapley Additive exPlanations（SHAPs）. The octanol-water partition coefficient（log P）， molecular topology， and ZMIC and piPC descriptors were identified as key parameters for predicting toxicity； these descriptors elucidate the relationship between chemical structure and biological interaction， thereby providing mechanistic explanations for compound toxicities. For example， high log P values are associated with high cell membrane permeability， which facilitates interactions between intracellular targets and endocrine receptors. The study also developed user-friendly quantitative structure-activity relationships（QSAR） prediction software. Designed for accessibility， this software enables researchers and policymakers to input compound structures in SMILES format and predict their toxicities without the need for specialized machine-learning expertise. The software automatically generates descriptors and predicts whether the input compounds are toxic or not. This study contributes to in silico methods that replace animal testing in future toxicity studies by integrating advanced machine-learning and interpretation methods. The predictive model and accompanying software enable the rapid screening of emerging pollutants and provide guidance for designing safer chemicals. These contributions are critical for advancing environmental safety and public health in the face of expanding chemical inventories.

Drugs and their metabolites are ubiquitous in various environmental media， including water bodies， soil， sediment， and air. These substances pose significant risks to human and animal safety and have emerged as a new category of pollutants. Accurate detection of the content of drugs in the environmental matrix can not only timely and objectively grasp the usage status， spatial distribution characteristics and temporal change patterns of drugs in a certain area， but also precisely assess the impact of long-term low-level exposure on the ecological environment. Currently， monitoring domestic sewage has emerged as a significant tool for tracking drugs use in various countries globally. Data obtained from domestic sewage samples for drugs detection can provide an objective， real-time， accurate， and effective reflection of local drug use patterns. Mass spectrometry has the advantages such as high specificity， high sensitivity and high quantitation accuracy and is mostly used for the analysis of domestic sewage samples. However， laboratory mass spectrometry methods involve complicated and time-consuming sample preparation processes， along with stringent environmental requirements， making them impractical for on-site rapid analysis. Consequently， there is an immediate need for the development of detection methods that are broad-spectrum， rapid， and capable of high throughput. In recent years， direct ionization mass spectrometry technology has been widely applied in on-site rapid detection and analysis work due to its characteristics such as avoiding complex chromatographic separation processes， fast analysis speed， high matrix tolerance， the ability to directly ionize analytes in complex matrix samples， and no（or only very little） sample pretreatment required. Direct ionization mass spectrometry is now playing an essential role in scientific research， environmental monitoring and public security. Pulsed direct current electrospray ionization mass spectrometry（pulsed-DC-ESI-MS） is a portable detection platform， which can be used for the accurate， rapid， on-site， batch， and sensitive analysis of picoliter level samples. In this research， a novelty method of pulsed-DC-ESI-MS was developed to achieve rapid detection of 11 drugs in domestic sewage. The drugs analyzed include methamphetamine（MA）， amphetamine（AM）， 3，4-methylenedioxymethylamphetamine（MDMA）， 3，4-methylenedioxyamphetamine（MDA）， morphine（MOR）， 6-monoacetylmorphine（6-MAM）， ketamine（KET）， norketamine（NKET） cocaine（COC）， benzoylecgonine（BZE）， and codeine（COD）. The sewage samples were extracted using the Oasis PRiME MCX solid-phase extraction（SPE） column. The extraction solution was blowing to nearly dry with nitrogen and then redissolved with 200 μL methanol and vortex for 0.5 min. The redissolved sample solution was filtered through a 0.22 μm organic filter membrane and analyzed by pulsed-DC-ESI-MS. The methodological validation results indicated that the 11 drugs had a good linear relationship within their respective linear ranges. The correlation coefficients（r²） were all ≥0.998 6， the limits of detection（LODs） and quantification（LOQs） were 0.01‒0.5 μg/L and 0.05‒5 μg/L， respectively. At three spiked levels， the recoveries of 11 drugs ranged from 88.0% to 107.6%， the intra- and inter-day precisions were both ≤8.5%. This method has a fast detection speed， greatly improving the detection efficiency， and is suitable for the rapid detection and analysis of common drugs in domestic sewage.

Instrumental analysis is a basic undergraduate course. It is mainly teaching-oriented for chemistry， materials， biology， environment， food and other majors. Among them， chromatography and spectrometry are two of the key teaching contents in the course of instrumental analysis. They have mature theoretical teaching systems and the supporting teaching experiments are relatively coincident. However， the main knowledge points are cluttered and complicated， and the connections between these chapters are not close enough. It’s hard for students to expand and comprehensively apply knowledge on the basis of theoretical knowledge and experimental technology. Besides， the innovation and cutting-edge aspects are relatively lacking. Based on the geographical advantages of coastal schools， this paper combined with the cases of new pollutants microplastics to explore the integrated teaching method of chromatography and spectroscopy in instrumental analysis. It systematically expands the teaching content， teaching mode and teaching effect respectively. The teaching contents of chromatographic and spectroscopic principles are expanded. The analysis abilities were demonstrated by case teaching methods and comparative teaching method. The integrated method of chromatography and spectroscopy can combine the characteristics to achieve the effective complementarity of the two methods. It combines the fast high-throughput analysis abilities of chromatography and the high selectivity and sensitivity of spectroscopy. This course is conducive to promoting the standardization and normalization of screening and identification methods for new pollutants. It can provide more advanced analytical techniques for monitoring new pollutants. In addition， this course can introduce hot topics to broaden the scope of subject knowledge. It is helpful to improve students’ ability to investigate relevant literature， understand scientific frontier development of science， and master the comprehensive application of instruments. It is also beneficial to guide students to master the induction， comparison and analysis of basic theoretical knowledge， which is conducive to students’ integration of instrument analysis. At the same time， it helps students grasp the bottleneck problems in the process of the instrument development. It then motivates students to become leading talents to meet the major strategic needs of the country. This paper is in favor of cultivating students’ innovative awareness and scientific spirit， and finally realizing the fundamental task of establishing morality and cultivating talents.

Pesticides are ubiquitous to human life but their residues are indispensable micropollutants that threaten human health. In recent years， the global use of pesticides has increased significantly in recent years， and their environmental profiles have become increasingly complex as different generations of pesticides have appeared on the market. The residues of various legacy and emerging pesticides are omnipresent in both the environment and food medias. Consequently， developing rapid and sensitive detection technologies for analyzing multiple residues is imperative. Sample pretreatment， particularly adsorbent selection and innovation， is indispensable in this regard. So far， a wide range of hybrid nanomaterials have been used for the enrichment or adsorption of pesticide residues. While traditional solid-phase-extraction-based （SPE-based） sorbents are widely used， they lack specific interactions and are poorly selective. Normal carbon materials （e.g.， graphene oxide and carbon nanotubes）， which have large surface areas and pore volumes， have progressed significantly； however， they still have insufficient active adsorption sites. Notably， porous materials， including metal-organic frameworks （MOFs）， porous organic polymers （POPs） （including covalent organic frameworks （COFs）， covalent triazine frameworks （CTFs）， conjugated microporous polymers （CMPs）， microporous organic networks （MONs， sub-familied by CMPs， porous aromatic frameworks （PAFs）， and hyper-crosslinked polymers （HCPs））， nano-porous carbons（NPCs）， and zeolites display exceptional properties because they have high porosity， tunable pore sizes， large surface areas， and diverse modification sites. In this review， strategies for the enhancement of adsorption performance of porous-material-based adsorbents， including materials hybridization， monomer modification， configuration regulation， and properties adjustment are first introduced. Furthermore， publications from 2018 to 2024 pertaining to the utilization of porous-material-based adsorbents for diverse types of pesticides were briefly elaborated. The properties of pesticides， the designs and performance of porous materials， and their interaction mechanisms were discussed. A total of 14 types of pesticides are included in the discussion， namely organochlorine pesticides （OCPs）， organophosphorus pesticides （OPPs）， pyrethroids （PYRs）， benzoylurea insecticides （BUs）， neonicotinoid insecticides （NEOs）， phenyl-pyrazole insecticides （PPZs）， phenoxy carboxylic acid herbicides （PCAs）， triazine herbicides （TRZHs）， benzimidazole fungicides （BZDs）， azole/triazoles fungicides， strobilurin fungicides （SFs）， carbamate insecticides （Carbs）， phenyl-urea herbicides （PUHs）， and diamide insecticides. Our summary revealed that an adsorbent was predominantly designed based on the textural properties of the target pesticide and the structural characteristics of the hybrid material， such as its functional groups， polarity， and pore size， to enhance adsorption performance and selectivity. MOFs and POPs are the most commonly used pesticide adsorbents， whereas fewer NPCs have been reported in this regard. Additionally， the applications potentials of porous-material-based adsorbents were explored. The findings revealed that conventional pesticides， such as OPPs， have been significantly researched in the extraction technology field. In contrast， concerns surrounding newer pesticides， including NEOs， PPZs， and SFs， as well as some significantly detected residues （BZDs and TRZHs）， have not been fully addressed， highlighting the need for future adsorbent research that prioritizes emerging and significantly detected pesticides.