Fuzzy set-based decision support system for hydrogen sulfide removal technology selection in natural gas processing: a sustainability and efficiency perspective.

Removing hydrogen sulfide (HS) toxic and corrosive gas from the natural gas processing and utilization industry is a challenging problem for managers of these industries. This problem involves different economic, environmental, and health issues. Various technologies have been employed to remove the HS gas from these industries, and choosing appropriate HS removal technologies is a complex multi-criteria decision-making (MCDM) problem. In this regard, the present research work aims at developing a novel decision support system (DSS) by integrating MCDM techniques based upon the (best worst method) BWM and (alternative ranking order method accounting for two-step normalization) AROMAN methods under the decomposed fuzzy set theory. The DSS is used to assess technologies for removing HS gas and then choose the best scenario for implementing among these technologies. Fourteen criteria in four environmental, social, economic, and efficiency aspects and five technologies of fixed-bed activated carbon technology (A_h2s), biotrickling filter technology (A_h2s), scavenger technology (A_h2s), chemical oxidation scrubber technology (A_h2s), and liquid redox technology (A_h2s) have been chosen for evaluation. The final value of each technology is obtained as A_h2s (0.5550), A_h2s (0.5262), A_h2s (0.5809), A_h2s (0.6357), and A_h2s (0.5790). The results reveal that the chemical oxidation scrubber technology (A_h2s) and biotrickling filter technology (A_h2s) with the values of 0.6357 and 0.5262 are respectively the best and worst scenario for the removal of HS produced by the natural gas processing and utilization plants of Iran. Therefore, the DSS is feasible and applicable and gives reliable and robust findings for acquiring the optimal HS removal technology.