Greenhouse gases (GHGs) have sharply increased over the past four decades due to intensifying industrial activities; as a result, the earth has been faced with global warming in which the major contributor is the anthropogenic carbon dioxide (CO 2 ) emissions. Carbon sequestration in unmineable coal seams has been proposed as one of the most attractive technologies to mitigate CO 2 emissions in which CO 2 is stored in the microporous structure of the coal matrix in an adsorbed state. The CO 2 adsorption process is hence considered one of the more effective methodologies in environmental sciences. Thus, adsorption isotherm measurements and modelling are key important scientific measures required in understanding the adsorption system, mechanism, and process optimization in coalbeds. In this paper, three renowned adsorption isotherm models were employed including Langmuir, Freundlich, and Temkin for pure CO 2 adsorption data, and the Extended-Langmuir model for multicomponent, such as flue gas mixture-adsorption data as investigated in this research work. The adsorption data was acquired from a high-pressure volumetric sorption system (HPVSS) experiment involving two South African coal samples from Ermelo and Somkhele coalfields with pure CO 2 and synthetic industrial flue gas to simulate emissions that are representative of a typical coal-fired power plant (12% CO 2 , 5.5% O 2 , 82% N 2 , 0.38% SO 2 , and 0.12% NO 2 ). The adsorption data was measured on 10 g samples with a mean size of 2 mm at temperatures ranging from 30 ºC to 60 ºC and pressure up to 9.0 MPa using the HPVSS. The statistical evaluation of the goodness-of-fit was done using three (3) statistical data analysis methods including correlation coefficient (R 2 ), standard deviation ( σ ), and standard error (SE). The Langmuir isotherm model conventionally fits the pure CO 2 gas experimental data better than Freundlich and Temkin. The Extended Langmuir gives best experimental data fit for the flue gas.