Nadiah, Mokhtar (2021) Biosorption of methylene blue dye using seaweed biomass. PhD thesis, Universiti Malaysia Pahang (Contributors, Thesis advisor: A. Aziz, Edriyana).
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08.Biosorption of methylene blue dye using seaweed biomass.pdf - Accepted Version Download (428kB) | Preview |
Abstract
Azo dye has been extensively used in textile dyeing processes due to its simplicity in production, cost effectiveness, ease of application, durability, and availability in various colours.. At present, investigation on treatment system that promoting environmental and economic sustainability for the remove dyes from industries have received numerous attentions among researchers. Therefore, this study is aimed to investigate the potential of Malaysian seaweed to be used as a biosorbent for the removal of azo-dye, methylene blue (MB) in aqueous solutions. The screening of five indigenous species was based on their maximum biosorption capacity (qmax) and affinity (b) and the effect of pre-treatment. Characterisation of potential seaweed was determined by fourier transform infrared spectrophotometer (FT-IR), Scanning electron microscopy with energy dispersive X-Ray analysis (SEM-EDX), thermogravimetric analysis (TGA), Brunauer-Emmett-Teller (BET), and points zero charge (pHpzc). The effect of various operational parameters such as contact time (5–360 min), pH (2–11), biosorbent dosage (0.2–1.2 g/L), initial concentration (50–200 mg/L) and temperature (30–50C) on biosorption was investigated further using batch mode study under One-factor-at-time (OFAT) approach. Upon optimisation, the experimental design for the biosorption process was carried out via Response Surface Methodology-Central Composite Design (RSM-CCD). A total of 20 runs were carried out to generate a quadratic model. A desorption study was performed to investigate the reusability of E.spinosum. Non-linear models of equilibrium isotherm (consisting of two-parameter models and three-parameter models) and kinetic isotherm were applied to analyse the biosorption mechanism. Model verification using Artificial Neural Networks (ANN) was adopted for an accurate prediction of dye removal. The results reveal that the equilibrium time for all seaweed species can be achieved within 60–80 min at 27°C. At lower MB initial concentrations (< 1000 mg/L), E. spinosum from red seaweed had the highest qmax and b. The pre-treatment process did not enhance the uptake capacity of E. spinosum, raw E.spinosum was used for the entire experiment. From optimisation through statistical model, it was observed that the maximum uptake capacity of 399 mg/g (> 95%) is obtained at the equilibrium time of 60 min, pH solution of 6.9–7.1, dosage of 0.72 g/L, and initial dye concentration of 300 g/L. Experimental data complied with the following equilibrium isotherms: Toth > Sips = Hill = Brouers-Sotolongo > Freundlich> Redlich-Peterson > Koble-Corrigan > Langmuir > Temkin, Dubidin-Radushkevich. The kinetic data, however, were better fitted to the pseudo-second-order kinetic model. After four consecutive biosorption/desorption cycles, the MB dye biosorption efficiency decreased from 94.5% to 48.5%, and the dye desorption efficiency decreased from 51.5% to 23.4%. Finally, model verification using ANN demonstrated that the ANN model (R2 = 0.9994, adj-R2 = 0.9916, MSE = 0.19, RMSE = 0.4391, MAPE = 0.087, and AARE = 0.001) is able to provide an accurate prediction. As a conclusion, red seaweed of E.spinosum was found to have great potential as an alternative natural occurring biosorbent specifically for MB dye removal.
| Item Type: | Thesis (PhD) |
|---|---|
| Additional Information: | Thesis (Doctor of Philosophy) -- Universiti Malaysia Pahang – 2021, SV: TS. DR. EDRIYANA BT A. AZIZ, CD: 13067 |
| Uncontrolled Keywords: | Biosorption, biomass |
| Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) |
| Faculty/Division: | Institute of Postgraduate Studies College of Engineering |
| Depositing User: | Mr. Nik Ahmad Nasyrun Nik Abd Malik |
| Date Deposited: | 14 Oct 2022 03:03 |
| Last Modified: | 01 Nov 2023 09:09 |
| URI: | http://umpir.ump.edu.my/id/eprint/34697 |
| Download Statistic: | View Download Statistics |
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