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Design of Experiments to Optimize Soxhlet-HTP Method to Establish Environmental Diagnostics of Polluted Soil: Optimization of the Soxhlet-HTP Method by DOE
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Author(s): Carlos Mario Morales-Bautista (Universidad Juárez Autónoma de Tabasco, Mexico), Candelario Méndez-Olán (División Académica de Ciencias Básicas, Universidad Juárez Autónoma de Tabasco, Mexico), Sugey López-Martínez (División Académica de Ciencias Biológicas, Universidad Juárez Autónoma de Tabasco, Mexico)and Marcia E. Ojeda-Morales (División Académica de Ingeniería y Arquitectura, Universidad Juárez Autónoma de Tabasco, Mexico)
Copyright: 2020
Pages: 20
Source title:
Design of Experiments for Chemical, Pharmaceutical, Food, and Industrial Applications
Source Author(s)/Editor(s): Eugenia Gabriela Carrillo-Cedillo (Universidad Autónoma de Baja California, Mexico), José Antonio Rodríguez-Avila (Universidad Autónoma del Estado de Hidalgo, Mexico), Karina Cecilia Arredondo-Soto (Universidad Autónoma de Baja California, Mexico)and José Manuel Cornejo-Bravo (Universidad Autónoma de Baja California, Mexico)
DOI: 10.4018/978-1-7998-1518-1.ch002
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Abstract
One of the great challenges of the environmental diagnoses of soils contaminated with hydrocarbons is the optimization of analytical determinations. For this reason, this chapter evaluates the extraction of hydrocarbons by the Soxhlet method through the design of experiments (DOE), variating three different solvents, three soils, and three extraction times. Soil was experimentally contaminated at different concentrations, and hydrocarbons totals relying on conditions organic matter, electrical conductivity, pH and textures, amount of sample, solvents, and NaSO4, were studied. The variables were evaluated by means of an analysis of the Taguchi design and a factorial design, with the results the significant and optimal parameters of the process were determined, which were solvent type and time (10 hours and dielectric constant of 9). Also, the model discards the soil properties. These results will save time and resources, and they reduce errors.
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