A decision support system for cooling tower technologies evaluation in the oil and gas industry

Mitigating the impacts of thermal pollution caused by the oil and natural gas (O&G) industry by applying the appropriate cooling tower technology has advantages for environmental, economic, and health goals. We aim at implementing an intelligent decision support system (DSS). The DSS involves the Delphi and criteria importance through intercriteria correlation (CRITIC) integrated method (DEACRIM) and ranking of alternatives through functional mapping of criterion sub-intervals into a single interval (RAFSI) model under the linear Diophantine fuzzy set (LDFS). Ten criteria based on water-energy nexus and circularity policies and four cooling tower technologies including Natural draft cooling tower technology, Induced draft cooling tower technology, Crossflow cooling tower technology, and Forced draft cooling tower technology have been chosen for evaluation. The evaluation results reveal that the Natural draft cooling tower technology is the most suitable scenario for Iran's O&G energy system facilities in order to mitigate thermal pollution.