مقایسه دو مدل برای جذب زیستی سرب با استفاده از هسته زیتون فراوری شده شیمیایی و فراوری نشده: روش طرح آزمایشات و سیستم استنتاج تطبیقی فازی Comparison of two models for the biosorption of Pb(II) using untreated and chemically treated olive stone: Experimental design methodology and adaptive neural fuzzy inference system (ANFIS)

۱٫ Introduction The pollution of environment with toxic heavy metals is spreading through the world along with industrial progress. Heavy metal ions can accumulate in the food chain, which posed a severe danger to human health [1]. The World Health Organization (WHO) recommends that the maximum acceptable concentration levels of lead in drinking water is 10 μg/L. Taking into consideration the necessity to reduce the emission of this metal to environment to diminish its negative impacts and its possible repercussion in the health of the population, it becomes necessary to look for feasible economic and environmental alternatives that allow keeping the levels of these polluting agents in the permissible range [2]. In this context, biosorption is an alternative to lead removal, because it has significant advantages in comparison with conventional methods, especially from economical and environmental viewpoints [3–۶]. High number of agricultural waste materials have been utilized as adsorbents of heavy metals: tea and cactus leaves, almond shells, olive tree pruning waste, pine cone, black cumin, coconut shell, hyacinth roots, wastes of rice, etc. [7–۱۰]. Agriculture waste materials contain proteins, polysaccharides and lignin, which containing multifunctional groups such as hydroxyl, carbonyl and carboxyl, play vital role for metal uptake purpose [10,11]. Moreover, chemical treatment of wastes determines an increase of active sites concentration and waste biosorbing capacity [12–۲۰]. Rivera et al., in 1986 [21], were the first to use the chemically treated olive stone to obtain a activated carbons to remove lead from water. They crushed and sieved raw olive stones and then they treated them with 10% sulphuric acid. They obtained an increase in biosorption capacity. Recently, activated carbons have been considered unique adsorbents because of their extended surface area, microporous structure, high adsorption capacity and high degree of surface reactivity [22]. As current, nanotubes has been studied as biosorbent to heavy metals [23,24]. However, these materials are expensive and they have a complex preparation process. The use of chemically treated wastes has emerged as one of the most effective and most cheapest technologies for removing metals ions from wastewater. In this study the untreated and chemically treated olive stone are compared to remove Pb(II) ions. Spain, Italy and Greece account for about 97% of Europe Union olive oil production, with Spain producing approximately 62% of this amount. Nowadays, the production of olive oil generates a high amount of olive stones. Taking into account that the olive cultivation is the fifth most cultivated product in Spain (the Spanish olive production in 2011 was nearly 7 million tons), high amount of olive stone as agroindustrial waste is produced in this country. Olive stone remains available as a waste product, for which no important industrial use has been developed, so it is normally incinerated or dumped without control. Although nowadays the olive stone is being used as fuel, a high amount of this waste remains without any application. Therefore the utilization, the study of other alternative uses, and the environmental concerns it presents are all extremely important [18]. The conventional studies during the development of a process involve variation of one factor at a time, keeping all other factors constant. In order to elucidate the influence of several operational variables jointly in a studied response, the experimental factorial design and statistical analysis by adaptive neural fuzzy inference system were used in this work. The factorial design [25] involves changing all variables from one experiment to the next. The design determines which factors have important effects on the response as well as how the effect of one factor varies with the level of the other factors [26]. The statistical analysis by adaptive neural fuzzy inference system (ANFIS) was originally developed by Jang [27] and it has been successfully used to simulate and control various processes [28,29]. The main objectives of the present study include the following: • To study the effect of chemical treatment of olive stone to improve its biosorption capacity. • To study all main individual and interaction effects on biosorption capacity of three operational parameters: concentration of chemical agent, pH and initial lead concentration. • To model experimental data by two models: full factorial design to obtain a second-order regression equation and adaptive neural fuzzy inference system. • To explain the biosorption capacity in two mathematical models. • To compare both models by representing experimental and modeled data.