H 2 S removal from an off-gas stream was performed in a spray column by H 2 S reactive absorption into a NaOH solution. The individual and interactive effects of three independent operating variables on the percentage of absorbed H 2 S were investigated: the initial pH of the scrubbing solution, the initial scrubbing solution temperature, and the volumetric liquid-to-gas ratio. The optimum operating variables were determined by response surface methodology (RSM) attaining a percentage of absorbed H 2 S of 98.7 ± 0.2 %. Additionally, the process performance was modeled by an artificial neural network (ANN) to predict the percentage of absorbed H 2 S. The results showed that the experimental data agreed better with the ANN model than with the RSM results.

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-The existence of hydrogen sulfide (H 2 S) in the gas effluents of oil, gas and petrochemical industries causes environmental pollution and equipment corrosion. These gas streams, called offgas, have high H 2 S concentration, which can be used to produce sodium sulfide (Na 2 S) by H 2 S reactive absorption. Na 2 S has a wide variety of applications in chemical industries. In this study, the reactive absorption process was performed using a spray column. Response Surface Methodology (RSM) was applied to design and optimize experiments based on Central Composite Design (CCD). The individual and interactive effects of three independent operating conditions on the weight percent of the produced Na 2 S (Y) were investigated by RSM: initial NaOH concentration (10-20% w/w), scrubbing solution temperature (40-60°C) and liquid-to-gas volumetric ratio (15 9 10 À3 to 25 9 10 À3 ). Furthermore, an Artificial Neural Network (ANN) model was used to predict Y. The results from RSM and ANN models were compared with experimental data by the regression analysis method. The optimum operating conditions specified by RSM resulted in Y of 15.5% at initial NaOH concentration of 19.3% w/w, scrubbing solution temperature of 40°C and liquid-to-gas volumetric ratio of 24.6 9 10 À3 v/v.Résumé -Optimisation expérimentale et modélisation de la production de sulfure de sodium à partir d'H 2 S riche en gaz provenant de la surface d'intervention méthodologique et de réseau de neurones artificiels -La présence de sulfure d'hydrogène (H 2 S) dans les effluents gazeux rejetés par l'industrie pétrolière, gazière et pétrochimique entraîne une pollution de l'environnement ainsi que la corrosion des équipements. Ces flux gazeux, appelés effluents gazeux, présentent une forte concentration de H 2 S qui peut être employée pour produire du sulfure de sodium (Na 2 S) par absorption réactive de H 2 S. Le Na 2 S trouve une multitude d'applications dans les industries chimiques. Dans cette étude, le processus d'absorption réactive a été réalisé avec une colonne à pulvérisation. La méthode des surfaces de réponses (Response Surface Methodology, RSM) a été appliquée pour concevoir et optimiser des expériences basées sur les plans composites centrés (Central Composite Design, CCD). Les effets individuels et interactifs de trois conditions d'exploitation indépendantes sur le pourcentage en poids de Na 2 S produit (Y) ont été analysés par RSM, à savoir : la concentration de NaOH initiale (10 à 20 % p/p), la température de la solution de lavage (40 à 60°C) et le rapport du volume liquide/gaz (15 9 10

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A rate-based mathematical model was developed for the reactive absorption of H 2 S in NaOH, with NaOCl or H 2 O 2 as the chemical oxidant solutions in a packed column. A modified mass transfer coefficient in the gas phase was obtained by genetic algorithm and implemented in the model to correct the assumption of instantaneous reactions. The effects of different operating variables including the inlet H 2 S concentration, inlet gas mass flux, initial NaOH, concentrations of the chemical oxidants in the scrubbing solutions, and liquid-to-gas ratio on the H 2 S removal efficiency were studied. A genetic algorithm was employed to optimize the operating variables in order to obtain maximum removal efficiency of H 2 S. The model results were in good agreement with the experimental data.