Herein, a quinoline-linked ultrastable 2D covalent organic framework (COF-CN) coated fiber was successfully prepared and used for highly-sensitive headspace solid-phase microextraction (HS-SPME) of organochlorine pesticides (OCPs) in environmental water. The extraction efficiency of the COF-CN coating for all 14 OCPs was higher than that of four commercial SPME fiber coatings and most of the published works, with enrichment factors ranging from 540 to 5065. In combination with gas chromatography-tandem mass spectrometry (GC-MS/MS), a wide linear range (0.05–200 ng/L), low detection limits (LODs, 0.0010–13.54 ng/L) and satisfactory reproducibility and repeatability were obtained under optimal conditions. Compared with the published works, the LODs of the developed technique were improved 2–5.9 times, and the enrichment factors (EFs) of the developed method were enhanced at least 2 times. The COF-CN coated fiber can be easily recycled and reused at least 70 times without any washing step. The adsorption mechanism was first characterized by density functional theory calculations and X-ray photoelectron spectroscopy analysis. Besides, the established method was successfully applied to the analysis of the distribution of trace OCPs in real water samples from Henan Province. All these results proved the promising application of the developed HS-SPME-GC-MS/MS method for organic pollutants analysis in water samples.

在此，成功制备了一种喹啉连接的超稳定二维共价有机骨架 (COF-CN) 涂层纤维，并将其用于环境水中有机氯农药 (OCP) 的高灵敏度顶空固相微萃取 (HS-SPME)。COF-CN 涂层对所有 14 种 OCP 的提取效率高于四种商业 SPME 纤维涂层和大多数已发表的作品，富集因子范围为 540 至 5065。结合气相色谱 - 串联质谱（GC -MS/MS）、宽线性范围（0.05–200 ng/L）、低检测限（LOD，0.0010–13.54 ng/L）以及在最佳条件下获得令人满意的重现性和重复性。与已发表的作品相比，所开发技术的 LOD 提高了 2-5.9 倍，并且所开发方法的富集因子 (EF) 至少提高了 2 倍。COF-CN 涂层纤维无需任何洗涤步骤即可轻松回收和重复使用至少 70 次。吸附机理首先通过密度泛函理论计算和X射线光电子能谱分析进行了表征。此外，该方法成功应用于河南省实际水样中痕量OCPs的分布分析。所有这些结果证明了所开发的 HS-SPME-GC-MS/MS 方法在水样中有机污染物分析中的应用前景。吸附机理首先通过密度泛函理论计算和X射线光电子能谱分析进行了表征。此外，该方法成功应用于河南省实际水样中痕量OCPs的分布分析。所有这些结果证明了所开发的 HS-SPME-GC-MS/MS 方法在水样中有机污染物分析中的应用前景。吸附机理首先通过密度泛函理论计算和X射线光电子能谱分析进行了表征。此外，该方法成功应用于河南省实际水样中痕量OCPs的分布分析。所有这些结果证明了所开发的 HS-SPME-GC-MS/MS 方法在水样中有机污染物分析中的应用前景。