使用以类为导向的化学测量和综合的二维气体染色学与质谱学相结合的生产水样品的分类
Julián Eduardo Ballén Castiblanco1, Victor Hugo Calvacanti Ferreira1, Carlos Alberto Teixeira1
1Institute of Chemistry, University of Campinas, Campinas, Brazil; National Institute of Science and Technology in Bioanalytics (INCTBio), Brazil.
Talanta
|November 1, 2023
概括
一种新方法使用头部空间固态微提取和气相色谱来根据总油脂含量 (TOG) 分类产生的水 (PW). 这种方法为石油和天然气废水的环境监测提供了准确和有效的替代方案.
科学领域:
- 环境化学环境化学
- 分析化学 分析化学
- 石油工程是石油工程中的一个.
背景情况:
- 生产水 (PW) 是石油和天然气运营中的重要废水流.
- 在PW中总油脂 (TOG) 是一个关键的环境指标.
- 传统的TOG分析方法往往耗时且不环保.
研究的目的:
- 根据TOG含量开发和验证一种基于PW样本分类的替代方法.
- 在PW样本分类中使用一类分类器 (OCC) 模型.
- 为了有效地评估PW样本的环境合规性.
主要方法:
- 头部空间固体相微提取 (HS-SPME) 与全面的二维气相色谱 (GC×GC) 结合起来,用于TOG分析.
- 使用Doehlert设计 (80°C,70分钟) 优化HS-SPME.
- 数据驱动软独立建模通过类类类比 (DD-SIMCA) 来进行分类.
主要成果:
- 聚二甲基素 (PDMS) 纤维证明了有效的分析物提取.
- 优化的HS-SPME-GC×GC方法实现了高分类性能.
- 该DD-SIMCA模型的灵敏度为94.3%,特异性为95.0%,准确度为94.5%.
结论:
- 一级分类器 (OCC) 模型有效地根据TOG内容对PW样本进行分类.
- 这种HS-SPME-GC×GC-DD-SIMCA方法为PW分析提供了准确有效的方法.
- 拟议的方法支持石油行业遵守环境法规.
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