Open AccessEstimating species concentration in CO2-loaded monoethanolamine using Raman spectroscopy
Author(s) -
Ahmad Syukri Na’im Bin Mohd Hanafiah,
Abdulhalim Shah Maulud
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/778/1/012162
Subject(s) - bicarbonate , raman spectroscopy , chemistry , amine gas treating , carbamate , calibration , aqueous solution , mean squared error , analytical chemistry (journal) , carbonate , protonation , biological system , thermodynamics , environmental chemistry , mathematics , organic chemistry , statistics , ion , physics , optics , biology
Operation of amine plant for CO 2 removal had long been plagued with inefficiencies due to suboptimal operating parameter leading to losses in operational expenditure. Improving the system requires understanding into thermodynamics and kinetics of the process which can be made possible through having information on the qualitative and quantitative speciation in the alkanolamine system. In this work, potential of Raman spectroscopy as a monitoring tool for species concentration in CO 2 -loaded aqueous monoethanolamine (MEA) system was investigated. CO 2 loading data from experimental work were used with Kent Eisenberg model to estimate species concentrations (dissolved CO 2 , Protonated amine, Bicarbonate, Carbonate, Carbamate and unreacted MEA). Each species concentration were fitted to experimentally-acquired Raman spectrum using Partial Least Square Regression (PLSR) technique to develop calibration model. Evaluation of regression plots, R 2 and Root Mean Square Error (RMSE) shows good predictive accuracy compared to the thermodynamically-predicted species concentration.