Silica nanoparticles have been great attention as it being evaluated for used in abundant fields and applications. Due to this significance, this research was conducted to synthesis silica nanoparticles using local agricultural waste, sugarcane bagasse. We executed extraction and precipitation process as it involved low cost, less toxic and low energy process compared to other methods. The Infrared (IR) spectra showed the vibration peak of Si-O-Si, which clearly be the evidence for the silica characteristics in the sample. In this research, amorphous silica nanoparticles with spherical morphology with an average size of 30 nm, and specific surface area of 111 m²/g⁻¹ have been successfully synthesized. The XRD patterns showed the amorphous nature of silica nanoparticles. As a comparison, the produced silica nanoparticles from sugarcane bagasse are compared with the respective nanoparticles synthesized using Stӧber method.

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.

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.

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.

Imperata cylindrica, often known as cogon grass, is a low-cost and useful sorbent for absorbing oil and optimising processes. The effects of temperature, time, packing density and oil concentration on oil absorption efficiency were investigated and optimised utilising one-factor-at-a-time (OFAT) and response surface methodology (RSM) approaches. Temperature and oil concentration are two important variables in the oil absorption process. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) analysis were used to characterise cogon grass. After treatment and oil absorption, the FTIR method indicated new formation and deformation of functional groups, while SEM revealed changes in the surface and texture of cogon grass, including a roughened and jagged surface. Validation of the RSM model yielded 93.54% efficiency with 22.45 mL oil absorbed at 128 °C temperature and 36 (v/v)% oil concentration while keeping packing density and time constant at 30 min and 0.20 g/cm³, respectively. This study may provide an insight into the usefulness of a statistical approach to maximise the oil absorption of cogon grass as an oil sorbent.