The Impacts and Analysis of Individual and Social Risks of the Stochastic Emission of Benzene from Floating-Roof Tanks Using Response Surface Analysis and MPACT Model.

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In the present study, the researchers used an integrated approach composed of response surface analysis (RSM) and MPACT model to predict fatality rates caused by benzene emitted from floating-roof tanks. RSM scenarios were configured in Expert Design (version 7.0) software using the central composite design (CCD) method and five variables of wind speed, relative humidity, atmospheric temperature, failure diameter, and emission height were considered. Continuous Pasquill-Gifford Gaussian model was used to estimate the results of the RSM scenarios. The response values were considered for exposure concentrations above 50ppm (slight damages), 150ppm (moderate damage), and 1000ppm (high damage). The analysis of individual and social risks for each scenario was done using the MPACT model in SAFETI program (version 8.22) by providing two variables of population characteristics and the frequency of tank wall failure. The results showed that atmospheric temperature, wind speed, failure diameter, and emission height have positive effects on the dispersion of the cloud of toxic benzene vapor with a concentration of 1000ppm. Intolerable individual risk distances were estimated to be lower for indoor environments than for outdoor. Maximum distances of intolerable individual risks for the worst-case scenarios were estimated up to 2500m from the emission point, which resulted from exposure to a concentration of 1000-ppm benzene. Results regarding the estimation of social risks showed that over 1600 fatalities should be expected under the worst-case scenarios. The three factors of high temperature, low wind speed, and low emission height play a major role in the occurrence of scenarios with the highest fatalities. High wind speed and high emission height were the most important factors in most scenarios with zero fatalities rate. Generally, the findings of this study show the necessity to provide an emergency response plan in the studied industry in both autumn and winter due to low wind speed. However, the coupling of the developed statistical models based on regional meteorological conditions with the MPACT model can help researchers to design an emergency response plan to deal with leakage incidents in petrochemical industries.