The China National Human Biomonitoring Program （CNHBP） was launched in 2016. The program aims to obtain representative exposure data of environmental pollutants in the general population by carrying out field epidemiological surveys of Chinese population and monitoring of environmental pollutants in human biological tissues. This work will provide a scientific basis for the government to formulate environmental pollution prevention and control policies. One of the objectives of human biomonitoring is to provide accurate and comparable data of chemical pollutants in human biological samples. Multi-dimensional quality control measures are implemented for the targeted quantitative analysis of chemical pollutants from the analysis method， experimental blank and analysis processes. The quality control procedures are divided into two stages： （1） focusing on the verification of biomonitoring analysis method， blank screening and control in the pre-detection stage； （2） the quality control of the large-scale sample analysis process in the detection stage. Analysis methods used in CNHBP need to be validated to evaluate the performance and practicability， with emphasis on method detection limit （MDL） and method quantification limit （MQL）， matrix effects， stability， and residue and dilution. Blank screening procedures are required for all monitoring indicators to identify， eliminate or reduce blank interference， and the blank value of each batch should be less than the MDL. The laboratory adopts a combination of internal and external quality control measures， the measures mainly include： （1） method validation and detection process of the 10 types of monitoring indicators all used biological matrix reference materials produced by the National Institute of Standards and Technology （NIST）， European Reference Materials （ERM） and China Center for Reference Materials， to ensure the accuracy and traceability of the methods； （2） commercial quality control samples and internal quality control samples were used to evaluate the stability of the testing process for the 15 types of monitoring indicators； （3） a total of 60 monitoring indicators of the nine categories participated in the German external quality assessment scheme for analyses in biological materials （G-EQUAS） and achieved satisfactory results； （4） 15 types of monitoring indicators were tested with blind samples. Overall， multi-dimensional quality control measures provide professional support for generating high-quality biomonitoring data.

Polycyclic aromatic hydrocarbons （PAHs） are organic compounds produced primarily through the incomplete combustion of coal， petroleum， and other carbon-based materials. These compounds are environmentally ubiquitous and have attracted widespread attention because they are significantly biologically toxic and have far-reaching implications for public health and societal wellbeing. Consequently， developing a comprehensive understanding of how PAHs and their derivatives metabolically biotransform in the human body is critical for devising precise preventive strategies and targeted health interventions. PAHs and their derivatives metabolically transform in vivo in a complex process involving a broad variety of enzymes and pathways， and are usually divided into three distinct phases. Phase I encompasses oxidative， reductive， and hydrolytic reactions that are primarily catalyzed by cytochrome P450 （CYP） enzymes. These processes produce intermediates such as monohydroxyls， diols， diol-epoxides， and quinones， some of which （e.g.， diol-epoxides） form covalent DNA adducts， thereby contributing to their toxicities. Phase Ⅱ involves conjugation reactions， such as glucuronidation， sulfation， and glutathionylation， which enhance the water solubilities of the metabolites and facilitate their elimination. These detoxified metabolites are actively transported and excreted via bile or urine in phase Ⅲ， which effectively minimizes internal PAH exposure and prevents accumulation. Metabolites generated at various stages of PAH metabolism serve as crucial biomarkers for assessing human exposure levels. For example， urinary monohydroxy PAH metabolites （e.g.， 1-hydroxypyrene） have been widely adopted as reliable biomarkers for characterizing PAH exposure. However， owing to their structural diversity， PAHs metabolize via considerably different mechanisms to afford a variety of products， which highlights the need to differentiate individual PAHs and their derivatives in order to precisely assess exposure and evaluate nuanced health risks. Understanding the time-dose-effect relationships of PAH metabolites provides another major PAH-biomonitoring challenge. Investigating these dynamics is essential for revealing the cumulative and long-term health effects associated with exposure to multiple PAHs and their derivatives. Moreover， such studies provide scientific bases for formulating personalized and refined health-protection strategies. For instance， exploring how individual susceptibility， such as genetic polymorphisms in CYP enzymes or conjugation pathways， affects PAH metabolism is expected to significantly improve risk stratification and targeted interventions. PAH exposure is associated with significant health risks because they are associated with a range of diseases， including lung， pancreatic， and gastrointestinal cancers， as well as respiratory and cardiovascular diseases. The pervasive environmental presence of PAHs further complicates exposure scenarios， necessitating the comprehensive monitoring of various populations and environmental contexts. In addition to individual exposure， population-scale studies are expected to inform public health policies and regulatory actions aimed at reducing PAH exposure， particularly in vulnerable populations. This review concisely summarizes the metabolic pathways and product categories associated with four types of PAHs： parent， nitroxylated， oxidized， and alkylated. It emphasizes recent advances in our understanding of parent PAH metabolism in humans， focusing on their implications for exposure characterization， health risk assessment， source tracing， and regulatory decision-making. This paper aims to provide a scientific foundation for the advancement of human biomonitoring efforts and the development of evidence-based public health interventions tailored to reduce the burden of PAH exposure by addressing the complexities of PAH metabolism.

Biological and environmental samples are complex and contain a highly diverse range of compounds. Analyzing these samples by chromatography-high-resolution mass spectrometry generates a substantial volume of mass-spectrometry data that are composed of mass-to-charge-ratio （m/z）， retention-time （RT）， and peak-intensity information that require considerable time and energy to process. Consequently， employing software to process mass-spectrometry data for identification and analysis purposes is imperative. Among the many mass-spectrometry data-processing options， XCMS （various forms （X） of chromatography mass spectrometry）， which is highly efficient， precise， and freely accessible software for processing mass-spectrometry data， is broadly used in the environmental science field. This study aimed to explore the use of XCMS in environmental science applications by comprehensively reviewing the workflow， underlying principles， and parameter-optimization measures of XCMS. The workflow mainly includes importing， processing， and exporting data. Importing data requires the use of format conversion tools， such as MSConvert， which converts data generated by various instruments into a format acceptable by XCMS， while data processing includes peak detection， alignment， and filling. The various XCMS functions are mainly realized via its built-in algorithms， with the Matched Filter， CentWave， Obiwarp， and Peak Density algorithms most commonly used. The first two algorithms implement the peak-detection function， while the latter two implement the peak-alignment function. XCMS identifies compound peaks from mass-spectrometry data during peak-detection； it first filters for noise and corrects the baseline. An algorithm then detects peaks based on their shapes and intensities. XCMS can also de-emphasize and de-distort to filter out interfering information in each peak signal. The CentWave algorithm is particularly effective for processing high-resolution mass-spectrometry data by improving detection accuracy and recall. Peak-detection is followed by alignment. Here， XCMS uses kernel density estimations to match peaks between samples by estimating the retention-time distribution of matched peaks， which corrects for any nonlinear deviations in retention-times. This step is critical for accurately comparing samples. The peak-filling step resolves missing peaks in the data， and XCMS uses information from other samples to fill these gaps. This process enhances the integrity of the dataset and improves analysis accuracy. In terms of applications， XCMS has demonstrated significant progress for the non-targeted screening of environmental pollutants， identifying exogenous metabolic pollutant transformations， and exploring the endogenous metabolisms of biomolecules. For example， XCMS efficiently extracts the mass spectrometry of complex samples during the non-targeted screening of environmental pollutants， thereby providing a reliable database for subsequent identification. Although the use of XCMS in the environmental science field has delivered particular results， some limitations still exist， including the use of large amounts of memory， problems associated with the software crashing when dealing with large-scale data， and the misclassification of noise as valid signals during feature detection， which results in a large number of false positives， errors， and missed detections when processing data for compounds with complex chemical compositions and structural types. In addition， the degree of user interaction and automation requires further improvement. XCMS offers significant developmental potential in the environmental science field. Continuing algorithmic optimization and database expansion through improvements in algorithmic robustness， data compatibility， and user experience， are expected to see XCMS develop broadly and provide more powerful support for the environmental science field in the future.

Chromatography， a highly efficient and selective separation technology， is broadly applicable and exhibits a range of developmental prospects. The stationary phase of a chromatography column is the most important component of chromatography； hence， the development of advanced stationary-phase materials that exhibit highly resolved separation performance is a continuing research hotspot in this field. In this regard， ordered porous materials （OPMs） are advantageous owing to their precisely controllable pore sizes， morphologies， and regularly arranged pore structures， which are capable of accurately sieving molecules of different sizes and shapes， and reducing disordered molecular diffusion in the flow path. Such materials overcome the limitation of separation accuracy of traditional chromatographic materials， and effectively solve the problems faced by scientific research and industry in the purification of raw materials and products. Over the past few decades， a variety of new OPMs have been developed and used as stationary-phase matrices in chromatography columns. These materials have efficiently and rapidly separated homologues， isomers， isotopes， and other substances with similar properties， and have delivered excellent chromatographic separation and analysis results. In this review， we first discuss the influence of ordered porous structures on column efficiency and resolution during chromatographic separation from a theoretical perspective， which provides a basis for the use of OPMs as stationary phases in chromatography. This review then summarizes research progress on several different OPM types for use in chromatographic separation and analysis applications， including metal organic frameworks （MOFs）， covalent organic frameworks （COFs）， porous organic cages （POCs）， mesoporous silica materials， block copolymer （BCP） assemblies， and high internal-phase emulsion polymers （PolyHIPEs）. The review concludes by discussing current challenges faced by chromatographic OPMs as well as directions for future development.

Selecting a suitable sample preparation method is a significant step prior to chromatographic separation and detection. Directly analyzing samples instrumentally is difficult owing to the complexity of the sample matrix and the trace concentration of analytes. Most sample preparation methods have disadvantages， including complicated operating procedures， the use of large amounts of organic solvent， and ease of analyte loss during multistep processes； consequently， they do not meet the high analytical sample detection requirements of modern industry. The development of simple， environmentally friendly， efficient， and rapid preparation methods is a continuing frontier research area in the analytical chemistry field. Among the many available sample preparation techniques， in-tube solid-phase microextraction （IT-SPME） is receiving extensive attention. IT-SPME enriches the target analytes by extracting them to the inner surface of the capillary tube， and has been applied to extract various analytes in the environmental and food fields. IT-SPME is advantageous because it consumes low amounts of organic solvent and capillaries are mechanical stable； consequently， IT-SPME is a promising sample preparation technique. Magnetic field has been introduced to the IT-SPME system to further improve extraction efficiency and selectivity， leading to the development of magnetism-enhanced in-tube solid-phase microextraction （ME-IT-SPME） as a new technology. ME-IT-SPME uses magnetic field to separate and enrich targets， with different magnetic-field strengths applied to the extraction column during adsorption and elution. Diamagnetic substances in a paramagnetic medium tend to concentrate in regions where the magnetic field is weak when an external magnetic field is applied. Target analytes are detected chromatographically following elution. Conditions are optimized and an analytical method is established and used to detect targets in actual samples， leading to improved extraction sensitivity and precision compared to those obtained using IT-SPME， including shorter analysis time and superior extraction efficiency. This paper reviews the applications of ME-IT-SPME technology in combination with various analytical instruments since its inception in 2012， and analyzes its analysis and detection advantages. Based on hydrophobic interactions， hydrogen bonding， π-π and polarity interactions， coordination， and other extraction mechanisms with analytes， ME-IT-SPME uses innovative functional extraction materials， including nanomaterials， monolithic materials， and magnetic hybrid materials， all of which have high surface areas and numerous adsorption sites. Capillary microextraction columns are prepared using open-tubular capillary， particle-filling capillary， or monolithic capillaries. Diverse analytes are detected when ME-IT-SPME is combined with chromatograph， including organic pesticide residues， heavy-metal ions， herbicides， preservatives， and drug molecules. ME-IT-SPME technology is widely used in the environmental-analysis， food-analysis， and biomedical fields. Future， ME-IT-SPME technological developments should include： （1） focus on the reusability and stability of the magnetic extraction material； （2） discovering new extraction materials that are highly enriching and selective in order to analyze a greater variety of targets； （3） further innovating ME-IT-SPME technology by combining it with other more-sensitive analytical methods and considering its use in other fields； （4） connecting different capillaries to simultaneously enrich a variety of analytes； （5） exploring how the higher magnetic field influences extraction efficiency by designing new magnetic-field-regulating devices with small thermal interference； （6） combining the technology with advanced portable analytical instruments to realize real-time target analysis in the field； （7） exploiting immuno-affinitive extraction tubes that can be used to highly efficiently and selectively extract biological macromolecular drugs.

In this study， a method for the simultaneous determination of 22 organic ultraviolet absorbers （OUVs） in human serum was established by combining protein precipitation technology （PPT）， efficiency lipid removal technology （ELR） and ultra performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. The OUVs include five benzophenone compounds， five benzotriazole compounds， two cinnamate ester compounds and their three metabolites， two salicylate compounds， two camphor derivative compounds， one triazine compound， one dibenzoylmethane compound and one amino aminobenzoic acid derivative compound. Chromatography was performed using an Acquity BEH C₁₈ column （100 mm×2.1 mm， 1.7 μm）， gradient elution was carried out using methanol-water and methanol-0.1% ammonia water as the mobile phases. Compounds were detected in both positive and negative electrospray ionization （ESI⁺/ESI^‒） modes using multiple reaction monitoring （MRM）， and quantified using stable-isotope internal standards. The experimental results showed that the 22 target compounds exhibited good linear relationships within their respective linear ranges， with the correlation coefficients （r）≥0.999 3. The method detection limits （MDLs） ranged from 0.02 to 0.48 ng/mL， and the method quantification limits （MQLs） ranged from 0.02 to 1.60 ng/mL. At the three spiked levels of low， medium and high， the spiked recoveries of the 22 target analytes ranged from 79.9% to 136.1%， the intra-day precisions were from 1.5% to 25.4%， and the inter-day precisions were from 0.6% to 23.5%. After correction by the stable-isotope internal standard method， the matrix effects of the 22 target analytes in fetal bovine serum were 83.0%‒119.9%. The developed method was successfully used to detect 22 OUVs in 110 human serum samples. With the exception of 3-benzylidene camphor （3-BC）， 2-（2H-benzotriazol-2-yl）-4-methyl-6-（2-propenyl）phenol （UV-9）， 4-methylbenzylidene camphor （4-MBC）， 2，2′-dihydroxy-4-methoxybenzophenone （BP-8）， and 2，4-dihydroxybenzophenone （BP-1）， which were not detected， the remaining 17 substances were detected with overall detection rates of 0.9%–65.5% and the detection levels were <MQL‒11.7 ng/mL. The developed analytical method is simple， convenient， highly sensitive， and is expected to become an effective tool for quantifying 22 OUVs in human serum.

The contents of 15 organophosphate ester （OPE） metabolites in the urine of 1 869 adults residing in urban areas were quantified using ultra performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. How gender， age， body mass index （BMI）， smoking status， exercise frequency， family income and dietary intake affected the contents of OPE metabolites in human urine were discussed. Furthermore， the daily intake （EDI） of OPEs was evaluated based on the contents of OPE metabolites in urine. The corresponding potential non-carcinogenic risks were calculated in combination with the non-carcinogenic risk reference dose （RfD）， with the health risks of individual OPE monomers and overall cumulative exposure expressed using the hazard quotient （HQ） and hazard index （HI）. Six OPE metabolites exhibited detection frequencies in excess of 60%， with bis（2-butoxyethyl） phosphate （BBOEP） and 1-hydroxy-2-propyl bis（1-chloro-2-propyl） phosphate （BCIPHIPP）， as the two main OPE metabolites， detected at levels of 0.56 and 0.36 ng/mL， respectively. Men exhibited higher urine contents of bis（1，3-dichloro-2-propyl） phosphate （BDCIPP）， BCIPHIPP， and BBOEP than women， whereas women exhibited higher urine contents of 4-hydroxyphenyl-phenylphosphate （4-HO-DPHP）. The levels of BCIPHIPP and diphenyl phosphate （DPHP） were found to correlate negatively with age， while the BCIPHIPP， and di-o-tolyl-phosphate （DoCP）/di-p-tolyl-phosphate （DpCP） levels correlated positively with family income. Higher exercise frequencies were found to be associated with significantly lower levels of BDCIPP and BCIPHIPP in urine. Furthermore， the frequency of nut consumption and the level of 4-HO-DPHP in urine were determined to be significantly negatively correlated. This study did not identify any significant associations between contents of urinary OPE metabolites and smoking or the intake of other foods， which suggests that smoking and dietary intake are not the primary OPE exposure pathways for the investigated population. Future research should have broader scope to elucidate the principal OPE exposure pathways. The overall OPE exposure levels for all participants in this study ranged between 5.60 and 2 800 ng/（kg⋅d） bw， with a median exposure level of 104 ng/（kg⋅d） bw. Among the four OPE monomers， Tris（2-butoxyethyl） phosphate （TBOEP） exhibited the highest exposure level， with a median value of 57.2 ng/（kg⋅d） bw （ranging between 1.11 and 1 330 ng/（kg⋅d） bw）， thereby contributing up to 55.6% of the total OPE exposure. Additionally， tri-n-butyl phosphate （TNBP） also exhibited significant exposure， with a median level of 32.4 ng/（kg⋅d） bw （ranging between 0.138 and 2 000 ng/（kg⋅d） bw）， which accounts for 31.5% of the total OPE exposure. Gender-based analysis revealed that men exhibited higher OPE exposure levels than women. Specifically， men exhibited a median exposure level of 112 ng/（kg⋅d） bw （ranging between 6.03 and 2 670 ng/（kg⋅d） bw） compared to the value of 89.9 ng/（kg⋅d） bw （ranging between 5.61 and 2 800 ng/（kg⋅d） bw） recorded for women. The vast majority of study participants exhibited HI values of less than one， indicative of no obvious non-carcinogenic risks. The OPEs exhibited HI values in the 0.000 2–1.03， with a median value of 0.06. The exposure risks associated with the four OPE monomers are ranked in following order： TBOEP （median HI=0.038， range： 0.000 7–0.883）， TNBP （median HI=0.013， range： 0.000 05–0.833）， tris（1，3-dichloro-2-propyl） phosphate （TDCIPP） （median HI=0.002， range： 0.000 8–0.288）， and triphenyl phosphate （TPHP） （median HI=0.001， range： 0.000 2–0.350）； these monomers contribute 68.9， 24.4， 4.2， and 2.5% to the overall HI value， respectively. Among all study participants， men exhibited a higher exposure risk （median HI=0.061， range： 0.002–1.03） than women （median HI=0.049， range： 0.002–0.840）. Notably， TBOEP was identified as the primary high-risk monomer for both genders， contributing 70.1% （median HI=0.042， range： 0.000 7–0.883） and 67.6% （median HI=0.035， range： 0.000 8–0.835） to the overall health risks of men and women， respectively. In conclusion， the study population was ubiquitously exposed to OPEs， with men exhibiting higher exposure levels and associated health risks， which suggests that OPE exposure levels are gender-dependent. This study revealed the exposure levels and profiles of OPEs of urban residents， and provides supporting data and a scientific foundation for subsequent studies and policy formulations.

Phthalates （PAEs） are widely employed as plasticizers in plastic products that are used in industrial， agricultural， food， medical， and other fields. PAEs are relatively weakly bonded to plastic products through non-covalent interactions. Consequently， PAEs can easily leak from the product into the environment， which exposes the public to PAEs through food intake， skin absorption from personal care products， and by inhaling air. Related studies have shown that PAEs are endocrine-disrupting substances and that long-term exposure to PAEs may result in diseases of the nervous， reproductive， cardiovascular and immune systems. In addition， excessive exposure to PAEs may trigger inflammatory responses and induce tumors. Therefore， establishing a highly sensitive assay for determining PAE levels in the human body following exposure is an important objective. PAEs generally have half-lives of less than 24 h； they are rapidly metabolized through enzymatic hydrolysis after entering the human body and excreted through urine. Therefore， most studies have focused on PAE metabolites as target compounds； hence， human body exposure to PAEs can be assessed by analyzing the types and levels of these metabolites. Herein， we established a method for simultaneously determining ten phthalate （PAE） metabolites in human urine using ultra performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. The ten PAE metabolites in urine were separated using an ACQUITY UPLC BEH Phenyl column （50 mm×2.1 mm， 1.7 μm）. Gradient elution was performed using 0.1% formic acid aqueous solution and 0.1% formic acid in acetonitrile as the mobile phases， at a flow rate of 0.5 mL/min， a column temperature of 40 ℃， and a sample size of 20 μL. Data were acquired in negative-ion electrospray ionization （ESI） and multiple reaction monitoring （MRM） modes， and quantified using the isotope internal standard method. The method was found to be highly specific， with the ten PAE metabolites exhibiting good linearities in their linear ranges， with limits of detection （LODs） and quantification （LOQs） of 0.03–0.3 and 0.1–1 ng/mL， respectively. Under the four quality control （QC） levels， the intra-day and inter-day precisions of the ten PAE metabolites were all ≤8.3%， and the accuracy ranged from ‒10.5% to 7.3%. The method was used to assess the exposure levels of PAE metabolites in the urine samples of 60 volunteers， with 1‒6 kinds of PAE metabolites detected in the urine of each volunteer. This method is sensitive， accurate， simple， efficient， and suitable for the large-scale biological monitoring of PAE metabolites.

Perfluorinated compounds （PFCs） are widely used， persistent， and their presence in water is of significant concern. PFCs， particularly short-chain variants， are highly soluble and mobile in water， which enables their transport over long distances via river systems， potentially leading to extensive contamination. These compounds are resistant to degradation， which is challenging for conventional water-treatment methods that often remove PFCs ineffectively， leading to their prolonged presence in water bodies. This paper establishes a magnetic solid-phase extraction method for 11 PFCs in enriched water using magnetic polystyrene pyrrolidone （Fe₃O₄-PLS） as a magnetic adsorbent. Purified lipophilic PLS magnetic beads were used as the solid-phase extractant， and their surfaces were modified using phenyl and pyrrolidone groups to facilitate the adsorption of PFCs that contain hydrophilic functional groups and hydrophobic alkyl side chains. PFCs in water were determined accurately and sensitively by liquid chromatography-tandem mass spectrometry （LC-MS/MS）. The method involved accurately weighing 50 mg （±0.05 mg） of the Fe₃O₄-PLS into a 500-mL beaker， adding 2 mL of methanol （for activation）， placing the beaker on a magnet for 30 s， and discarding the methanol once the methanol and Fe₃O₄-PLS had been completely separated. A 200-mL aliquot of an aqueous mixed PFC solution was added to the beaker， sonicated for 15 min， and then placed on a strong magnet until the Fe₃O₄-PLS had completely separated at the bottom of the beaker. The upper liquid was discarded. A 4-mL acetonitrile containing 0.1% formic acid was added as the Fe₃O₄-PLS eluent， ultrasonicated for 30 s， after which the beaker was placed on the magnet and the eluate collected. The sample was taken to dryness under a stream of nitrogen， the residue was redissolved in 0.5 mL of acetonitrile， ultrasonicated for 10 s， and then membrane-filtered prior to analysis by LC-MS/MS. The 11 PFCs exhibited good linear relationships ranging from 1 to100 μg/L， with correlation coefficients （R²） ranging from 0.997 6 to 0.999 9. Limits of detection and quantification （LODs and LOQs， respectively） were determined to be 0.001–0.620 ng/L and 0.002–2.065 ng/L， respectively， indicative of high sensitivity. The 11 PFCs exhibited recoveries of 60.8%–120.0% at various concentrations （0.05， 1， 10， and 50 μg/L）. Relative standard deviations （RSDs） ranged from 1.0% to 20.0%， which meet the requirements for PFC analysis in water. The concentrations of the 11 PFCs at 15 sites in the Dongtiaoxi River， Hangzhou （near factories， reservoirs and residential areas） were analyzed using the developed method. A total of six PFCs， namely perfluorooctanoic acid （PFOA）， perfluorononanoic acid （PFNA）， perfluorooctane sulfonic acid （PFOS）， perfluoroheptanoic acid （PFHpS）， perfluorobutanesulfonate （PFBS） and perfluorodecanoic acid （PFDA）， were detected at mass concentrations of 11.4–30.7 ng/L. The highest mass concentration of PFOA was determined to be 25.5 ng/L. The PFCs in the Dongtiaoxi River were found to be mainly associated with precursor degradation and industrial wastewater discharge. A sudden rise in the pollution level was observed near the sampling point with the lowest detected concentration， which is possibly ascribable to the strong hydrodynamic difference between the hydraulic transport process near the river wharf and the highly turbulent flowing water. This difference results in the suspended particles in surface water mixing with re-suspended sediment particles such that PFCs are released back into the surface water. Pollution levels were observed to continuously decrease in the directions of the extended river and its estuary and tributaries. Risk assessments revealed that the PFC levels in the surface water of the Dongtiaoxi River basin are much lower than the official health reference value and have not reached levels that are expected to cause ecological harm and risk human health. The data are expected to support monitoring-system improvements by providing an in-depth understanding of occurrence characteristics， and help formulate a management plan for PFCs in the Dongtiaoxi River.

Brominated flame retardants （BFRs） are widely used as organic flame retardants in plastic products， with most exhibiting strong biological toxicity as well as physical and chemical stability. BFRs inevitably remain in foods consumed on a daily basis through indirect or direct contact， thereby threatening human health. Therefore， establishing a fast and effective method for detecting and analyzing BFRs is imperative. Magnetic solid-phase extraction （MSPE） has been widely used in trace-analysis applications owing to advantages that include operational simplicity and rapid magnetic separability. The key to MSPE lies in the design and preparation of efficient magnetic adsorbents. In this study， a magnetic carbon aerogel （MCA） was prepared using a sol-gel method in combination with calcination. MCA was used as a magnetic solid-phase extractant to establish a new method for the analysis of four BFRs in mineral water and instant-noodle-bowl samples in combination with high performance liquid chromatography. Fourier-transform infrared （FT-IR） spectroscopy revealed peaks at 3 454， 1 590， 757， 1 349， 1 654， and 1 076 cm^-1 that are ascribable to -NH₂， -CH， triazine-ring， C-N， C=N， and C-O-C vibrations， respectively. Brunauer-Emmett-Teller （BET） analysis revealed values of 192.16 m²/g， 0.34 cm³/g， and 7.12 nm for the surface area， pore volume and pore size of the MCA， respectively. X-ray diffractometry （XRD） revealed a characteristic peak at 2θ=34.90° that corresponds to the （110） crystal plane of Fe₂O₃， and peaks at 2θ values of 44.72°， 65.01° and 82.42° that are ascribable to the （110）， （200）， and （211） crystal planes of CoFe/Co₃Fe₇. Vibrating sample magnetometry showed that the MCA is highly magnetic （35 emu/g）， which contributes to fast magnetic solid-liquid separation. The MCA was characterized by transmission electron microscopy （TEM）， which revealed a transparent gauze-like structure with nanometer-sized squares and circular particles evenly distributed between them. High-resolution TEM （HRTEM） showed that the square particles exhibit a 0.191 nm stripe spacing that belongs to the （311） crystal plane of Fe₂O₃， while the 0.245 nm stripe spacing observed for the circular particles corresponds to the （110） crystal plane of the CoFe alloy， in good agreement with the XRD results. X-ray photoelectron spectroscopy （XPS） revealed the presence of Co 2p， Fe 2p， O 1s， N 1s， and C 1s peaks. Taken together， these results show that the MCA， which contains various functional groups， had been successfully prepared. Factors that affect MSPE， such as solution pH， amount of material， adsorption time， the concentration and volume of the elution solvent， and sample volume， were investigated using the static adsorption method. BFR adsorption by the MCA was observed to increase with time， with equilibrium eventually reached. Tetrabromobisphenol A （TBBPA） reached adsorption equilibrium at 1 h with an adsorption rate close to 100%， whereas 3-bromobiphenyl （PBB-2）， 4，4′-dibromobiphenyl （PBB-15）， and 2，2′，4，4′-tetrabromodiphenyl ether （BDE-47） reached adsorption equilibria at 2 h. BDE-47 exhibited an adsorption rate close to 80% when 20 mg/L MCA was used， whereas the remaining three BFRs exhibited values close to 100%. Absorption by the MCA initially exhibited a constant trend with increasing sample volume but began to decline as the sample volume exceeded 100 mL. BFR adsorption by the MCA was found to be almost pH-independent， which indicates that the MCA is stable over a wide pH range. In addition， the analytes were effectively eluted in 30 min using 5 mL of acetonitrile. Based on the results presented above， the optimal adsorption and desorption conditions are： 20 mg/L of adsorbent， a sample volume of 100 mL， an adsorption time of 2 h without pH adjustment， 5 mL of acetonitrile as the eluent， and desorption time of 30 min. TBBPA， PBB-2， and PBB-15 exhibited limits of detection （LODs， S/N≥3） of 0.005 mg/L each under the optimal conditions， while BDE-47 exhibited a value of 0.010 mg/L， with corresponding RSDs of 7.35%， 5.12%， 3.66%， and 5.58% （n=5， C=0.02 mg/L）， respectively， and actual enrichment times of 50， 40， 51， and 61 min， respectively. The developed method was used to determine four BFRs in mineral water and instant-noodle-bowl samples， with satisfactory recoveries obtained， thereby providing a new fast and sensitive method for the analysis of brominated flame retardants.

Polycyclic aromatic hydrocarbons （PAHs） are organic pollutants that are ubiquitous in nature and in environments affected by anthropogenic activities. PAHs enter the human body through inhalation， ingestion， or skin contact， and consequently threaten human health. Urban areas are mostly affected by PAHs pollution， which is ascribable to dense population， heavy traffic， and limited air-pollutant diffusion. In this study， we assessed the current status of PAHs exposure among non-occupationally exposed urban residents using isotope dilution combined with liquid-liquid extraction-gas chromatography-high resolution dual-focus magnetic mass spectrometry （GC-HRMS）. The burden of PAHs of 92 permanent residents aged 2 to 80 years in Beijing was investigated. Ten monohydroxypolycyclic aromatic hydrocarbons （OH-PAHs） were measured in urine samples， namely hydroxynaphthalene （OHNap， including 1-OHNap and 2-OHNap）， hydroxyfluorene （OHFlu， including 2-OHFlu， 3-OHFlu， and 9-OHFlu）， hydroxyphenanthrene （OHPhe， including 1-OHPhe， 2-OHPhe， 3-OHPhe， and 4-OHPhe）， and 1-hydroxypyrene （1-OHPyr）. The OH-PAH levels were corrected with urinary creatinine， with results below LODs replaced with half the value of LODs. Correlations between OH-PAHs were assessed using Spearman’s rank correlation analysis （two-tailed）. The nonparametric Mann-Whitney U test and the Kruskal-Wallis H test were used to compare the distribution of OH-PAH levels in different populations. The results showed that six OH-PAHs （1-OHNap， 2-OHNap， 2-OHFlu， 9-OHFlu， 1-OHPhe， and 2-OHPhe） were detected in all the urine samples. The total contents （ΣOH-PAHs） of the 10 OH-PAHs ranged from 661 to 33 782 ng/g， with an overall geometric mean （GM） of 2 775 ng/g and significant inter-individual differences. The following content-distribution trend was observed： OHNap>OHFlu>OHPhe>1-OHPyr， with a significant negative correlation with molecular size recorded. OHNap was mainly observed， accounting for 62.2% of the total. Complex correlations were found to existed between the OH-PAHs， with 9-OHFlu exhibiting unique exposure patterns. Urinary OH-PAH levels were found to correlate with gender and age， and smoking was also observed to be a significant influencing factor. ΣOH-PAHs peaked in the youth group （0‒15 years）， with a GM of 3 940 ng/g. Levels of ΣOH-PAHs were similar in the working-age group （16‒59 years， GM： 2 598 ng/g） and in the elderly group （≥60 years， GM： 2 639 ng/g）. These suggest that age is a key PAH-exposure factor. Habitual smoking was found to consistently and significantly affect OH-PAH levels， with smokers generally having higher levels of OH-PAH than non-smokers. While males exhibited higher overall exposure levels than females， females exhibited significantly higher levels of 1-OHPyr than males （p=0.03） when smoking was excluded， which suggests that metabolic and behavioral differences between genders impact PAHs exposure. This study revealed the exposure and distribution characteristics of OH-PAHs in Beijing residents. It provides a scientific basis for studying PAHs pollution and its health effect， as well as epidemiological investigations， disease-burden assessments， and policy formulation.

Polychlorinated biphenyls （PCBs） are hazardous， persistent organic pollutants that are widely used industrially. Although the use of PCBs is banned in many countries， they are still present at trace levels in food and the environment. PCBs are highly chemically stable and lipophilic； hence， they are easily enriched and accumulate in the human body through milk and dairy products. PCBs residues pose serious threats to human health； therefore establishing a reliable enrichment method is an important objective. Sample pretreatment is required to efficiently extract target PCBs owing to sample-matrix complexity and their low contents. Efficient adsorbents form the cores of novel sample-pretreatment technologies， and designing new stable adsorbents is crucial for the further development of pretreatment techniques. Zeolitic imidazolate frameworks （ZIFs） are a family of metal-organic frameworks composed of imidazole linkers and metal ions. Their large surface areas， good stabilities， high porosities， and ease of modification are distinct advantages； consequently， ZIFs are widely used to adsorb organic pollutants. However， powdered ZIFs are difficult to separate and collect， which provides reuse challenges； hence， preparing ZIF composites with other functional materials is a highly effective way of addressing this challenge. Chitosan （CS） is an inexpensive and biodegradable natural polysaccharide that gelates easily. The structure of CS contains many free amino and hydroxyl groups that facilitate chemical modification and hybridization； consequently， CS is a matrix commonly used in composite materials. In this study， we prepared CS@ZIF-8 composite beads by the in-situ synthesis of ZIF-8 on chitosan through acid-solubilization/base-fixation. An analytical method for determining 18 PCBs in milk was developed using CS@ZIF-8 composite microspheres as the adsorbent for dispersive solid-phase extraction （DSPE） coupled with gas chromatography-mass spectrometry （GC-MS）.The CS@ZIF-8 composite microspheres were characterized by scanning electron microscopy （SEM）， Fourier-transform infrared （FT-IR） spectroscopy， X-ray diffractometry （XRD）， and nitrogen-adsorption-desorption experiments， which confirmed that the material had been successfully prepared. How adsorbent dosage， extraction and desorption times， and type and volume of the desorption solvent affect the extraction efficiency were investigated， with the following optimal extraction conditions determined： 20 mg of CS@ZIF-8 as the adsorbent， 30 min of extraction by shaking， and 8 min of ultrasonic desorption with 1 mL of n-hexane. The 18 PCBs exhibited good linearities in the 1–200 μg/L under these optimal conditions， with coefficients of determination （r²） exceeding 0.999. Detection limits （S/N=3） ranged between 0.06 and 0.24 μg/L， with quantification limits （S/N=10） of 0.19–0.79 μg/L. Repeatability experiments were performed by the addition of 100 μg/L of the 18 PCBs， which exhibited intra-day and inter-day precisions （n=6） of 2.5%–5.3% and 4.3%–5.9%， respectively， while inter-batch material precisions （n=3） ranged between 4.9% and 9.7%. The applicability of the developed method was investigated by selecting whole milk and skim milk as samples based on PCBs lipophilicity. Spiked recovery experiments were conducted at three concentrations （5， 20， and 100 μg/L）， with the 18 PCBs exhibiting spiked recoveries of 84.8%–114.3%. CS@ZIF-8 not only has a larger specific surface area than CS， but it also adsorbs PCBs through π-π interactions and hydrophobicity， leading to superior extraction efficiency. CS@ZIF-8 exhibited spiked recoveries exceeding 70% for all samples after four adsorption-desorption cycles during reproducibility testing. The developed method provides a simplified extraction process by eliminating the need for centrifugation or filtration steps that are usually associated with conventional DSPE. In addition， the developed method is highly sensitive， precise， and accurate， with adsorbent reusability a noteworthy feature， thereby supporting the simple and efficient detection of PCBs in milk samples.

Crude oils are complex mixtures of thousands of organic compounds that differ significantly in relative molecular mass， volatility， content， and polarity. Traditional methods for analyzing crude oil often involve complicated steps， consume large amounts of organic solvents， and require long sample-preparation times. These limitations lead to inefficient and time-consuming analysis processes. Crude oil is commonly analyzed by gas chromatography-mass spectrometry （GC-MS）. However， this technique is incapable of effectively separating complex crude-oil components owing to its low resolution and peak capacity， resulting in overlapping peaks that can lead to inaccurate compound identification and quantification. These challenges highlight the need for advanced analytical techniques. Comprehensive two-dimensional gas chromatography （GC×GC） is a novel separation technique that has been widely used to analyze complex samples， such as food， environmental samples， natural products， and crude oil. GC×GC has several advantages over traditional GC. Firstly， it offers higher resolution and peak capacity， thereby improving separation efficiency. Secondly， its high separation power reduces the need for complex sample pretreatment. Thirdly， the ordered separation and “tile effect” in a GC×GC chromatogram facilitate easier compound identification and quantification in complex mixtures.

In this study， we developed a gas purge microsyringe extraction （GPMSE） method for the rapid pretreatment of crude-oil samples. This method reduces sample processing time to only 10 min while minimizing organic solvent consumption. The chemical compositions of 45 crude oil samples were analyzed using GC×GC-time-of-flight mass spectrometry （GC×GC-TOFMS）， which helped to establish detailed chemical fingerprints for each sample. The GC×GC-TOFMS data were processed using multivariate statistical methods， including redundancy analysis （RDA） and Monte Carlo permutation testing， which identified 36 biomarkers that are strongly associated with the origin of the crude oil （p<0.05）. A classification model was constructed using a training set of 28 samples. Four single-source and 13 mixed-source samples were used to validate the model. The GPMSE-GC×GC-TOFMS method was demonstrated to be highly efficient and accurate. A discrimination accuracy of 97.8% was achieved during the identification of crude-oil sources. The developed method not only provides a powerful tool for tracing crude oil but also has broad applications potential， including for the detection of adulterated crude oil， tracking oil-spill sources， and monitoring oilfield development. This study offers several significant benefits. For example， it helps to address crude-oil trade fraud and supports national energy security. Additionally， it provides scientific support in relation to crude-oil quality control and risk assessment. The developed method is fast， reliable， and environmentally friendly； hence， it is expected to be a valuable tool for use in the oil industry. The GPMSE-GC×GC-TOFMS method is cost-effective and requires minimal solvent； consequently， it is an attractive option for reducing environmental impacts in laboratory and industrial settings. Furthermore， the high throughput and accuracy of the developed method make it suitable for large-scale analyses. In conclusion， this study demonstrated the effectiveness of combining GPMSE with GC×GC-TOFMS for analyzing crude oil； the ability of the method to identify biomarkers and classify crude-oil sources in a highly accurate manner represents a significant advancement in the field. Future studies are expected to further explore its applications in related areas， such as oil refining and environmental monitoring.

Gel electrophoresis is used to separate and analyze macromolecules （such as DNA， RNA， and proteins） and their fragments， and highly reproducible and efficient automatic band-detection methods have been developed to analyze gel images. Uneven background， low contrast， lane distortion， blurred band edges， and geometric deformation pose detection-accuracy challenges during automatic band detection. In order to address these issues， various correction algorithms have been proposed； however， these algorithms rely on researcher experience to adjust and optimize parameters based on image characteristics， which introduces human error while qualitatively and quantitatively processing bands. Isoelectric focusing （IEF） gel electrophoresis separates proteins with high-resolution based on isoelectric point （pI） differences. Microarray IEF （mIEF） is used for the auxiliary diagnosis of diabetes and adult β-thalassemia owing to operational ease， low sample consumption， and high throughout. This diagnostic method relies on accurately positioning and precisely determining protein bands. To avoid errors associated with correction algorithms during band analysis， this paper introduces a method for rapidly recognizing bands in gel electrophoresis patterns that relies on a deep learning object detection algorithm， and uses it to quantify and classify the IEF electrophoresis pattern of hemoglobin （Hb）. We used mIEF experiments to collect 1 665 pI-marker-free Hb IEF images as a model dataset to train the YOLOv8 model. The trained model accepts a Hb IEF image as input and infers band bounding boxes and classification results. Using inference data， the gray intensities of the pixels in each band area are summed to determine the content of each protein. The background and foreground of the image need to be separated prior to summing the abovementioned gray intensities， and the threshold method is used to achieve this. The threshold is defined as the average intensity of the background area， which is obtained by summing and averaging the background intensities of gel areas between the detection bounding boxes of each protein band. The baseline band areas are unified after removing the background. This method only requires the input image， directly outputs the corresponding electrophoretic band information， and does not rely on the experience of professionals nor is it affected by factors such as lane distortion or band deformation. In addition， the developed method does not depend on pI markers for qualitatively determining bands， thereby reducing experimental costs and improving detection efficiency. YOLOv8n delivered a detection accuracy of 92.9% and an inference time of 0.6 ms while using limited computing resources. Using Hb A2 as an example， we compared its content measured using the developed method with clinical data. The quantitative results were subjected to regression analysis， which delivered a linearity of 0.981 2 and a correlation coefficient of 0.980 0. We also used the Bland-Altman analysis method to verify that these two values are highly consistent. Compared with the traditional automatic band detection methods， the method developed in this study is fast， accurate， more repeatable， and stable， and can be used to determine the Hb A2 content in clinical practice， thereby potentially assisting in the auxiliary diagnosis of adult β-thalassemia.

Organic synthesis experiments are often deficient and involve relatively independent experimental instrumental-analysis methods that lack integration. Accordingly， an open-instrument-analysis experiment was designed to address these shortcomings； this experiment combines organic synthesis with instrumental analysis to deliver an innovative undergraduate experiment that includes material preparation and characterization， investigating the adsorption performance of hydroxylated polychlorinated biphenyl， and exploring detection methods. First， Fe₃O₄ was treated with tetraethyl orthosilicate， after which 3-aminopropyltrimethoxysilane was introduced to prepare amino-modified Fe₃O₄. Trimesoyl chloride and p-phenylenediamine are then added as monomers to synthesize a magnetic covalent organic framework （MCOF）. The surface groups and thermal stability of the MCOF were then characterized using Fourier-transform infrared spectroscopy and thermogravimetric analysis， after which the MCOF was used to determine hydroxylated polychlorinated biphenyl in Liaohe River water samples using liquid chromatography. During this experiment， students master separation and detection methods for hydroxylated polychlorinated biphenyl， while also learning about its levels in the Liaohe River. Students will recognize the important role that instrumental analysis plays in environmental monitoring by analyzing and discussing the experimental results； they will also improve their abilities to comprehensively apply basic inorganic chemistry， organic chemistry， and instrumental-analysis knowledge， while also improving their abilities to operate， analyze， and solve problems. Implementing this open experiment will help to improve the use of laboratory equipment and fully utilize existing laboratory resources.