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Emerging micropollutants determination by NIR spectroscopy using pseudo-univariate calibration and TF-SPME coupled with 96-well plate system
Microchemical Journal ( IF 4.9 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.microc.2020.104789
Leonardo Valderrama , Josias Merib , Paulo Henrique Março , Patrícia Valderrama , Eduardo Carasek

Abstract In this study, an innovative approach was developed to determine simultaneously the emerging micropollutants bisphenol A (BPA), 3-(4-methylbenzylidene) camphor (4-MBC), triclocarban (TCC), benzophenone (BZP) and 2-ethyl-hexyl-4-trimethoxycinnamate (EHMC) in water employing near infrared spectroscopy (NIR) coupled with thin film solid-phase microextraction (TF-SPME) using the chemometric tool of multivariate curve resolution with alternating least squares (MCR-ALS). In addition, a 96-well plate system was employed to increase the analysis throughput of the proposed methodology. Samples were submitted to TF-SPME procedure (previously optimized in previous work to exhibit the best performance for extraction and desorption conditions) and its extracts were analyzed by NIR. A pseudo-univariate calibration model for each analyte was developed by associating the relative concentration obtained using MCR-ALS with the reference concentration (i.e. theoretical concentration). The correlation coefficients obtained were 0.9238, 0.8722, 0.7872, 0.8856 and 0.9128 for BPA, 4-MBC, TCC, BZP and EHMC, respectively. With the use of these pseudo-univariate models, the determination of the analytes exhibited absolute errors lowers than those of the chromatographic technique for BZP and TCC. For BPA, 4-MBC and EHMC the absolute error was lower than 10 µg L − 1. This approach can provide a cheap and rapid strategy for the direct quantification of these micropollutants in water samples.

中文翻译:

使用伪单变量校准和 TF-SPME 结合 96 孔板系统通过 NIR 光谱法测定新兴微污染物

摘要 在本研究中,开发了一种创新方法来同时测定新兴微污染物双酚 A (BPA)、3-(4-甲基亚苄基) 樟脑 (4-MBC)、三氯卡班 (TCC)、二苯甲酮 (BZP) 和 2-乙基-使用近红外光谱 (NIR) 结合薄膜固相微萃取 (TF-SPME) 使用具有交替最小二乘法 (MCR-ALS) 的多元曲线分辨率的化学计量工具,在水中提取 4-三甲氧基肉桂酸己酯 (EHMC)。此外,采用 96 孔板系统来提高所提出方法的分析吞吐量。将样品提交给 TF-SPME 程序(之前在之前的工作中进行了优化,以展示最佳的提取和解吸条件性能),并通过 NIR 分析其提取物。通过将使用 MCR-ALS 获得的相对浓度与参考浓度(即理论浓度)相关联,开发了每个分析物的伪单变量校准模型。BPA、4-MBC、TCC、BZP 和 EHMC 的相关系数分别为 0.9238、0.8722、0.7872、0.8856 和 0.9128。使用这些伪单变量模型,分析物的绝对误差低于 BZP 和 TCC 色谱技术的绝对误差。对于 BPA、4-MBC 和 EHMC,绝对误差低于 10 µg L - 1。这种方法可以为水样中这些微污染物的直接定量提供一种廉价且快速的策略。BPA、4-MBC、TCC、BZP 和 EHMC 的相关系数分别为 0.9238、0.8722、0.7872、0.8856 和 0.9128。使用这些伪单变量模型,分析物的绝对误差低于 BZP 和 TCC 色谱技术的绝对误差。对于 BPA、4-MBC 和 EHMC,绝对误差低于 10 µg L - 1。这种方法可以为水样中这些微污染物的直接定量提供一种廉价且快速的策略。BPA、4-MBC、TCC、BZP 和 EHMC 的相关系数分别为 0.9238、0.8722、0.7872、0.8856 和 0.9128。使用这些伪单变量模型,分析物的绝对误差低于 BZP 和 TCC 色谱技术的绝对误差。对于 BPA、4-MBC 和 EHMC,绝对误差低于 10 µg L - 1。这种方法可以为水样中这些微污染物的直接定量提供一种廉价且快速的策略。
更新日期:2020-06-01
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