Within their range of applicability both

Within their range of applicability, both approaches matched the phase boundaries and yields generally to within the measurement error. The approaches matched the phase compositions generally to within 11 wt% or less with the average absolute deviations listed below: One advantage of the proposed approaches is that no composition dependent parameters were required to fit the data. Previous work with a cubic equation of state found that it could match the same dataset used in this study only by using composition dependent binary interaction parameters [39]. It is possible that these binary interaction parameters were indirectly accounting for the effect of self-association. The proposed approaches also address a physical inconsistency in previous attempts to use CPA to match yield curves of asphaltene precipitation from n-alkane diluted bitumen [28,31]. Previously, all asphaltene components were characterized identically so that all partitioned equally to the heavy phase. The proposed characterization assigns a range of self-association energies to the asphaltenes so that more strongly self-associating components partition preferentially to the heavy phase. This refinement potentially allows for more accurate prediction of the phase behavior of fractions separated from the original mixture. The number of pseudo-components in either approach could be reduced to 1 non-associating component and 5 associating components with minimal loss of accuracy and a significant improvement in computational speed. However, both approaches have been tuned to match measured data and are not predictive. The approaches can be applied to other solvents by tuning the asphaltene/solvent cross-association energy. They can be applied to other bitumens by adjusting the self-association 98 2 synthesis of the asphaltenes. Caution is advised if other parameters are adjusted because changes in one parameter may require retuning of several other parameters. Previous studies have shown that this type of characterization can easily be extended to live oils [[26], [27], [28], [29], [30]]. Hence, the proposed approaches can be adapted to all of the typically encountered crude oil and solvent phase behavior. Caution is advised when predicting LL behavior above the critical temperature of the solvent.
Acknowledgements The authors would like to thank the sponsors of the Natural Sciences and Engineering Research Council of Canada of Canada (NSERC) Industrial Research Chair in Heavy Oil Properties and Processing, including NSERC, CNRL, Nexen Energy ULC., Petrobras, Schlumberger, Suncor, and Virtual Materials Group (VMG), for their financial support. We are grateful to Dr. Francisco Ramos Pallares for his suggestions.
Introduction Sulfur dioxide (SO2) is among the most dangerous acidic gases and air polluting contaminants. It is actually an important contributor to acid rain, which is a serious danger to human health, as it effects for example, agricultural productions or even directly, human breathing. In other aspects, SO2 as acid rain has a irreversible effects on ecological balance. It can also damage buildings and constructions [1], [2], [3]. The main causes of SO2 emissions to the environment are human and industrial activities of burning sulfur-containing fossil fuels. Therefore, capturing the SO2 before it is vented into the atmosphere is an important task, necessary to minimize the above-mentioned harmful issues. Flue gas desulfurization methods consist of various techniques to capture SO2 and control emissions [2], [4], [5], [6]. Among the different proposed methods, the wet limestone technology makes up more than 90% of the world\'s current desulfurization processes. However, it is not an optimum technique because it is an irreversible process requiring large amounts of water. In addition, gypsum and carbon dioxide are byproducts of the wet limestone process, neither being of great value [7], [8]. Therefore, there was and still is a need for other methods that are superior to the undesirable wet limestone process.