Since many pollutants released into the air are the result of oil and chemical extraction and conversion processes, thus air pollution control technologies (APCTs) play a significant role to control the pollutants emitted from these processes. The sustainability assessment of these technologies for controlling pollutants emitted from industries of oil, gas, and petrochemical industries (OGPIs) can be regarded as a complex multi-criteria decision-making (MCDM) issue that needs investigation of a number of options and conflicting assessment metrics. Moreover, decision-makers often utilize different linguistic expressions for expressing their eva‎luations because of their various contexts and preferences, some of which may be incorrect, uncertain, and imperfect. In response, this study purposes in developing a novel MCDM framework by integrating the analytical network process (ANP), decision-making trial and eva‎luation laboratory (DEMATEL), and multi-objective optimization on the basis of ration analysis (MULTIMOORA) method based on fuzzy set theory to advance the air pollution control and manage supply chain sustainability in the three cases of OGPIs: Petrochemical plant (case A), Gas refinery (case B), and Oil refinery (case C). Also, it assists the stakeholders/ decision-makers to the sustainability prioritization and selection of the clean and control technologies for attaining the targets of the energy and carbon management, green management, and technology management in these industries. Sixteen sub-criteria in four criteria, including technical (Operability and simplicity, Chemical and physical characteristics of the pollutant, Technology maturity, Reliability, and Gas stream characteristics), environmental (Occupied land, Contribution to GHG mitigation, Effect on air quality improvement, and Energy consumption), economic (Transportation capital cost, Operation and maintenance costs, and Capital costs), and social (Innovation on technology, Added jobs, Social acceptability, and Health and safety) were eva‎luated for the study aim. The most common types of APCTs including four options of Electrostatic precipitator, Fabric filter, and Wet scrubber, and Cyclone were assessed by the proposed MCDM algorithm. The results of the analysis to order the sustainability of four technologies in petrochemical are first the use of a wet scrubber, then cyclone and finally the implementation of fabric filter and electrostatic precipitator and in gas and oil refineries are first a cyclone, then wet scrubber and finally fabric filter and electrostatic precipitator. The findings of the study demonstrate that the suggested MCDM algorithm is feasible for group decision-making based on experts’ opinions and sustainability eva‎luation of APCTs for reducing GHG emissions from the OGPIs of Iran. The assessment criteria and sub-criteria and this algorithm could be applied to other industries (such as steel, cement, and etc.) for advancing the development of supply chain management towards the targets of sustainability and green. Finally, sensitivity analysis was fulfilled to peruse the effects of the weights of the assessment sub-criteria on the sustainability prioritization of the options. The managerial insights were also provided to navigate a sustainability and green transition towards the supply chain of the oil & gas sector in Iran.

9/15/2021 12:00:00 AM

305

ESE25

محسن طيبي