One possible way to reduce our carbon footprint is using postcombustion capture (PCC) processes to remove CO2 from flue gases. Because of the highly dynamic characteristics of such processes, real-time performance monitoring is a very complex task. This paper presents a method for monitoring the concentrations of CO2, SOx, and a CO2 capturing agent (β-alanine) during a process in a PCC pilot plant. A partial least-squares (PLS) model was built to estimate these concentrations from Fourier transform infrared (FTIR) spectra of the capturing solvent during processing in a model PCC plant. The model predicts the species concentrations to within 0.05 mol/L, provided that the concentrations stayed within the calibration window of the model. Next to that, it is paramount that the solutions used for model calibration consist of the same solution matrix as the real process medium. The model was eventually used to monitor an emulated PCC process online during 24 h of processing. This demonstrated that events such as saturation of the capturing agent with CO2, water replenishment, and switching to safety protocols can be followed accurately. The combination of an FTIR spectrometer and a PLS model can be used to extract process information in real-time.@en