Role of Correlation among Physical Factors in Probabilistic Simulation of Emissions of Volatile Organic Compounds from Floating Storage and Offloading Vent Stack

Abstract

This research investigated the roles of correlations among physical factors in the probabilistic simulation of volatile organic compounds (VOCs) emitted from a marine vessel (known as floating storage and offloading, FSO), located in the Gulf of Thailand. The physical factors in this study were wave height, ambient temperature, storage temperature, storage quantity, Reid vapor pressure, and the daily incoming rate. These physical factors were transformed into normally distributed data and a second-order multiple linear regression (MLR) with interaction effects, that were then used to determine the relationship between the transformed physical factors and the VOC venting volume from the FSO. The dataset of relevant predictors (transformed physical factors and interactions) that provided the maximum adjusted coefficient of determination was chosen for inclusion in the MLR. After that, two datasets of 1,000 venting volumes (one with and one without correlations among physical factors) were simulated. In the simulation, 1,000 datasets of six physical factors were generated according to observed averages and standard deviations. Cholesky randomization was used to generate the correlated physical factors for the simulation with correlation among physical factors. The averages of VOC venting volumes calculated from the generated physical factors when correlations among physical factors were and were not applied were 211,610 and 210,906 ft3, respectively (observed average was 210,984 ft3), with standard deviations of 38,828 and 40,787 ft3, respectively (observed standard deviation was 67,961 ft3), and skewness values of 0.74 and 0.51, respectively (observed skewness was 0.71). Therefore, correlation among the physical factors improved the skewness and provided better simulation results for VOC emission.

Keywords

• floating storage and offloading (fso)
• multiple linear regression (mlr)
• probabilistic simulation
• volatile organic compound (voc) emission