Statistical Optimisation of Diesel Biodegradation at Low Temperatures by an Antarctic Marine Bacterial Consortium Isolated from Non-Contaminated Seawater

et al. 2021

Water

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Rice straw, an agricultural waste product generated in huge quantities worldwide, is utilized to remediate diesel pollution as it possesses excellent characteristics as a natural sorbent. This study aimed to optimize factors that significantly influence the sorption capacity and the efficiency of oil absorption from diesel-polluted seawater by rice straw (RS). Spectroscopic analysis by attenuated total reflectance infrared (ATR-IR) spectroscopy and surface morphology characterization by variable pressure scanning electron microscopy (VPSEM) and energy-dispersive X-ray microanalysis (EDX) were carried out in order to understand the sorbent capability. Optimization of the factors of temperature pre-treatment of RS (90, 100, 110, 120, 130 or 140 °C), time of heating (10, 20, 30, 40, 50, 60 or 70 min), packing density (0.08, 0.10, 0.12, 0.14 or 0.16 g cm−3) and oil concentration (5, 10, 15, 20 or 25% (v/v)) was carried out using the conventional one-factor-at-a-time (OFAT) approach. To eliminate any non-significant factors, a Plackett–Burman design (PBD) in the response surface methodology (RSM) was used. A central composite design (CCD) was used to identify the presence of significant interactions between factors. The quadratic model produced provided a very good fit to the data (R2 = 0.9652). The optimized conditions generated from the CCD were 120 °C, 10 min, 0.148 g cm−3 and 25% (v/v), and these conditions enhanced oil sorption capacity from 19.6 (OFAT) to 26 mL of diesel oil, a finding verified experimentally. This study provides an improved understanding of the use of a natural sorbent as an approach to remediate diesel pollution.

Section: Optimization Of Factors Affecting the Sorption Capacities And The Efficiency Of Oil/watermentioning

confidence: 61%

“…Aligned factors from OFAT were further analyzed using Design-Expert software version 13.0 under the Factorial Miscellaneous Design (standard design) [26], with slight modifications. With a minimum of 11 horizontal factors, 6 center points were chosen.…”

Section: Response Surface Methodology (Rsm) Plackett-burman Design (Pbd)mentioning

confidence: 99%

Rice Straw as a Natural Sorbent in a Filter System as an Approach to Bioremediate Diesel Pollution

Taufik

Ahmad

et al. 2021

Water

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“…To establish the settings that were nearest to optimal, each component was examined at two levels: low (−1) and high (+1) of its corresponding values (Table 7). Significant (p < 0.05) values were determined to profoundly impact the efficiency of diesel-seawater sorption and further analysis using CCD [65][66][67][68]. The PB factorial design at two levels was described by the following equation (Equation ( 3)):…”

Section: Plackett-burman (Pb) Designmentioning

confidence: 99%

Coco Peat as Agricultural Waste Sorbent for Sustainable Diesel-Filter System

Verasoundarapandian

Shaharuddin

et al. 2021

Plants

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Oil spill incidents are hazardous and have prolonged damage to the marine environment. Management and spill clean-up procedures are practical and rapid, with several shortcomings. Coco peat (CP) and coco fibre (CF) are refined from coconut waste, and their abundance makes them desirable for diesel spillage treatment. Using a filter-based system, the selectivity of coco peat sorbent was tested using CP, CF and peat-fibre mix (CPM). CP exhibited maximal diesel sorption capacity with minimal seawater uptake, thus being selected for further optimisation analysis. The heat treatment considerably improved the sorption capacity and efficiency of diesel absorbed by CP, as supported by FTIR and VPSEM–EDX analysis. Conventional one-factor-at-a-time (OFAT) examined the performance of diesel sorption by CP under varying parameters, namely temperature, time of heating, packing density and diesel concentration. The significant factors were statistically evaluated using response surface methodology (RSM) via Plackett–Burman design (PB) and central composite design (CCD). Three significant (p < 0.05) factors (time, packing density and diesel concentration) were identified by PB and further analysed for interactions among the parameters. CCD predicted efficiency of diesel absorbed at 59.92% (71.90 mL) (initial diesel concentration of 30% v/v) and the experimental model validated the design with 59.17% (71.00 mL) diesel sorbed at the optimised conditions of 14.1 min of heating (200 °C) with packing density of 0.08 g/cm3 and 30% (v/v) of diesel concentration. The performance of CP in RSM (59.17%) was better than that in OFAT (58.33%). The discoveries imply that natural sorbent materials such as CP in oil spill clean-up operations can be advantageous and environmentally feasible. This study also demonstrated the diesel-filter system as a pilot study for the prospective up-scale application of oil spills.

“…The significant factors were analysed using one-way variance analysis (ANOVA) by GraphPad Prism 8.0.2 software (GraphPad Inc., San Diego, CA, USA). The influence of each parameter was tested using One-way ANOVA where significant and by pairwise post hoc comparisons using Tukey’s test [ 32 ].…”

Section: Methodsmentioning

confidence: 99%

Oil Palm’s Empty Fruit Bunch as a Sorbent Material in Filter System for Oil-Spill Clean Up

Puasa

Ahmad

et al. 2022

Plants

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Oil pollution such as diesel poses a significant threat to the environment. Due to this, there is increasing interest in using natural materials mainly from agricultural waste as organic oil spill sorbents. Oil palm’s empty fruit bunch (EFB), a cost-effective material, non-toxic, renewable resource, and abundantly available in Malaysia, contains cellulosic materials that have been proven to show a good result in pollution treatment. This study evaluated the optimum screening part of EFB that efficiently absorbs oil and the physicochemical characterisation of untreated and treated EFB fibre using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM). The treatment conditions were optimised using one-factor-at-a-time (OFAT), which identified optimal treatment conditions of 170 °C, 20 min, 0.1 g/cm3, and 10% diesel, resulting in 23 mL of oil absorbed. The predicted model was highly significant in statistical Response Surface Methodology (RSM) and confirmed that all the parameters (temperature, time, packing density, and diesel concentration) significantly influenced the oil absorbed. The predicted values in RSM were 175 °C, 22.5 min, 0.095 g/cm3, and 10%, which resulted in 24 mL of oil absorbed. Using the experimental values generated by RSM, 175 °C, 22.5 min, 0.095 g/cm3, and 10%, the highest oil absorption achieved was 24.33 mL. This study provides further evidence, as the data suggested that RSM provided a better approach to obtain a high efficiency of oil absorbed.