Process analyzers for in-situ monitoring give advantages over the traditional analytical methods such as their fast response, multi-chemical information from a single measurement unit, minimal errors in sample handing and ability to use for process control. This study discusses the suitability of Raman spectroscopy as a process analytical tool for in-situ monitoring of CO₂ capture using aqueous monoethanolamine (MEA) solution by presenting its performance during a 3-day test campaign at PACT pilot plant in Sheffield, UK. Two Raman immersion probes were installed on lean and rich streams for real time measurements. A multivariate regression model was used to determine the CO₂ loading. The plant performance is described in detail by comparing the CO₂ loading in each solvent stream at different process conditions. The study shows that the predicted CO₂ loading recorded an acceptable agreement with the offline measurements. The findings from this study suggest that Raman Spectroscopy has the capability to follow changes in process variables and can be employed for real time monitoring and control of the CO₂ capture process. In addition, these predictions can be used to optimize process parameters; to generate data to use as inputs for thermodynamic models, plant design and scale-up scenarios.

用于现场监测的过程分析仪具有优于传统分析方法的优势，例如它们的快速响应，来自单个测量单元的多种化学信息，样品处理中的最小错误以及用于过程控制的能力。这项研究通过在英国谢菲尔德的PACT中试工厂进行的为期3天的测试活动中展示其性能，讨论了拉曼光谱法作为过程分析工具使用一乙醇胺水溶液（MEA）现场监测CO ₂捕集的适用性。将两个拉曼浸入式探头安装在稀流和浓流上，以进行实时测量。使用多元回归模型确定CO ₂负荷。通过比较CO ₂来详细描述设备性能在不同的工艺条件下加载到每个溶剂流中。研究表明，预测的CO ₂装载量与离线测量结果一致。这项研究的发现表明，拉曼光谱法具有跟踪过程变量变化的能力，可用于实时监测和控制CO ₂捕获过程。另外，这些预测可以用来优化工艺参数；生成数据以用作热力学模型，工厂设计和放大方案的输入。