Modeling the reaction and transport mechanism for total petroleum hydrocarbon using selected linear and nonlinear error functions

In this article, field pilot study was undertaken to examine the transport mechanism for total petroleum hydrocarbon remediation in varying concentration using pseudo first order, pseudo second order and intra particle diffusion kinetic models in land farming treatment. Soil samples were artific...

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Bibliographic Details
Main Authors: Okonofua, Ehizonomhen Solomon, Lasisi, Kayode Hassan, Egbiki, Sunday
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2020
Online Access:http://journalarticle.ukm.my/17199/1/09.pdf
http://journalarticle.ukm.my/17199/
https://www.ukm.my/jkukm/volume-324-2020/
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Summary:In this article, field pilot study was undertaken to examine the transport mechanism for total petroleum hydrocarbon remediation in varying concentration using pseudo first order, pseudo second order and intra particle diffusion kinetic models in land farming treatment. Soil samples were artificially contaminated in varying concentration of 1,000 mg/kg (low), 3,000 mg/kg (medium) and 5,000 mg/kg (high) and treated using organic and inorganic fertilizers for a period of 150days which is the duration for effective remediation treatment. The results from the treated samples were subjected to kinetics studies while coefficient of determination (R2 ) was applied on the residual total petroleum hydrocarbon (TPH) after 150 days of treatment, pseudo first order had R2 values of 0.7898 (low), 0.6776 (medium) and 0.6131 (high). Pseudo second order had R2 values of 0.9737 (low), 0.9467 (medium), 0.7863 (high) while intra particle diffusion had R2 values of 0.9940 (low), 0.9821 (medium) and 0.9489 (high) respectively. The results indicate that intra particle diffusion model best described the kinetics mechanism of TPH remediation using land farming treatment; but when the alteration in the error structure associated with transforming a nonlinear kinetic equation into linear equation is minimized using nonlinear regression optimization procedure, pseudo first order emerged as the best kinetic model having the least sum of errors as 0.000270 (low), 0.000185 (medium) and 0.000278 (high).