Desenvolvimento de índice de biodegradação de hidrocarbonetos em água do mar baseado em análise cromatográfica e lógica fuzzy.

Abstract

A Mamdani Fuzzy Inference System (SIF) is designed to capture the theoretical and practical knowledge of hydrocarbon biodegradation process efficiency specialists from gas chromatographic mass spectrometry (GC-MS) analysis. As input variables of the SIF were provided the biodegradation efficiencies of short chain, medium chain, isopropenoid and long chain hydrocarbons. The output variable was a fuzzy index of total hydrocarbon biodegradation efficiency based on CG-MS, called IFEBHC_CGEM. Input and output variables were fuzzified using trapezoidal pertinence functions (low, medium and high). Eighty-one fuzzy rules were developed with expert support. Four defuzification methods were used to defuzify the output variable. The developed fuzzy index was applied to evaluate the efficiencies of seawater diesel oil biodegradation processes by Candida lipolytica UCP 0988 and its evaluations were compared to that of a control biodegradation efficiency index. For this purpose, a case study was conducted, using data from a complete factorial design 22, consisting of seven trials, including three repetitions at the central point, having as independent variables pH and temperature and as response variable the biodegradation efficiency of. total hydrocarbons. The model has been validated and tested. IFEBHC_CGEM evaluations proved to be more stringent and flexible than the deterministic control method. The results obtained suggest that IFEBHC_CGEM can be used for intelligent monitoring and decision-making on the quality and extent of petroleum hydrocarbon biodegradation and can prevent early process interruption or excessive prolongation and reduce economic and environmental costs unnecessary.