Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Linear and Non-linear Regression Analysis for the Adsorption Kinetics of SO2 in a Fixed Carbon Bed Reactor – A Case Study

Version 1 : Received: 29 November 2021 / Approved: 1 December 2021 / Online: 1 December 2021 (10:55:30 CET)

A peer-reviewed article of this Preprint also exists.

Kisiela-Czajka, A.M.; Dziejarski, B. Linear and Non-Linear Regression Analysis for the Adsorption Kinetics of SO2 in a Fixed Carbon Bed Reactor—A Case Study. Energies 2022, 15, 633. Kisiela-Czajka, A.M.; Dziejarski, B. Linear and Non-Linear Regression Analysis for the Adsorption Kinetics of SO2 in a Fixed Carbon Bed Reactor—A Case Study. Energies 2022, 15, 633.

Abstract

Kinetic parameters of SO2 adsorption on unburned carbons from lignite fly ash and activated carbons based on hard coal dust were determined. The model studies were performed using the linear and non-linear regression method for the following models: pseudo first and second-order, intraparticle diffusion, and chemisorption on a heterogeneous surface. The quality of the fitting of a given model to empirical data was assessed based on: R2, R, Δq, SSE, ARE, χ2, HYBRID, MPSD, EABS, and SNE. It was clearly shown that it is the linear regression that more accurately reflects the behaviour of the adsorption system, which is consistent with the first-order kinetic reaction – for activated carbons (SO2+Ar) or chemisorption on a heterogeneous surface – for unburned carbons (SO2+Ar and SO2+Ar+H2O(g)+O2) and activated carbons (SO2+Ar+H2O(g)+O2). Importantly, usually, each of the approaches (linear/non-linear) indicated a different mechanism of the studied phenomenon. A certain universality of the χ2 and HYBRID functions has been proved, the minimization of which repeatedly led to the lowest SNE values for the indicated models. Fitting data by any of the non-linear equations based on the R or R2 functions only, cannot be treated as evidence/prerequisite of the existence of a given adsorption mechanism.

Keywords

SO2; unburned carbon; fly ash; activated carbon; adsorption kinetics; kinetics models; linear regression; non-linear regression; statistical error functions; the sum of normalized error method

Subject

Engineering, Energy and Fuel Technology

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