Food Waste Materials as Low-Cost Adsorbents for the Removal of Volatile Organic Compounds from Wastewater

Abstract

The aim of this work was to study the potential of food waste materials (banana peel, potato peel, apple peel, lemon peel, coffee waste, decaf coffee waste, grape waste, and carob peel) as low-cost adsorbents for the removal of aliphatic and aromatic volatile organic compounds (VOCs) from wastewater. The ability of examined food waste materials to adsorb VOCs from synthetic multi-component standard solutions was evaluated and the examined food waste materials showed high removal efficiency. Performances of coffee waste, grape waste, and lemon peel were detailed by using Trichloroethylene and p-Xylene in mono-component standard solutions. The adsorption capacity of the three selected food wastes was determined by using linear Langmuir and Freundlich isotherm models. Two errors functions, average percentage error (APE) and the chi-square test (χ2), were used for isotherm optimization prediction. Freundlich isotherm well described the adsorption of VOCs on the considered materials. According to the obtained results, a multilayer, physical, and cooperative adsorption process was hypothesized, particularly evident when the VOCs’ concentrations are high. This was confirmed by the high adsorption efficiency percentages (E% > 80%) of VOCs from a real polluted matrix (urban solid waste leachate), containing high concentrations of total organic content.

Municipal Sewage Sludge as a Source for Obtaining Efficient Biosorbents: Analysis of Pyrolysis Products and Adsorption Tests

“…The error functions were employed to evaluate the fit of the isotherm to the experimental equilibrium data. In this study, the residual root mean square error ( RMSE —Equation (9)), the chi-square test (Equation (10)) and the linear regression were used [ 36 , 37 ]: where n is the number of observations in the experimental isotherm, and q e,exp and q e,cal stand for experimental and calculated values, respectively. The better the curve fitting, the smaller the RMSE and χ 2 values.…”