Driving fatigue is a serious issue for the transportation sector, decreasing the driver’s performance and increasing accident risk. This study aims to investigate how fatigue mediates the relationship between the nature of work factors and driving performance. The approach included a review of the previous studies to select the dimensional items for the data collection instrument. A pilot test to identify potential modification to the questionnaire was conducted, then structural equation modelling (SEM) was performed on a stratified sample of 307 drivers, to test the suggested hypotheses. Based on the results, five hypotheses have indirect relationships, four of which have a significant effect. Besides, the results show that driving fatigue partially mediates the relationship between the work schedule and driving performance and fully mediates in the relationship between work activities and driving performance. The nature of work and human factors is the most common reason related to road accidents. Therefore, the emphasis on driving performance and fatigue factors would thereby lead to preventing fatal crashes and life loss.

Pollution from dye containing wastewater leads to a variety of environmental problems, which can destroy plant life and eco-systems. This study reports development of a seaweed-based biochar as an adsorbent material for efficient adsorption of methylene blue (MB) dye from synthetic wastewater. The Eucheuma cottonii seaweed biochar was developed through pyrolysis using a tube furnace with N2 gas, and the properties were later improved by sulfuric acid treatment. The adsorption studies were conducted in a batch experimental setup under initial methylene blue concentrations of 50 to 200 mg/L, solution pH of 2 to 10, and temperature of 25 to 75 °C. The characterization results show that the developed biochar had a mesoporous pore morphology. The adsorbent possessed the surface area, pore size, and pore volume of 640 m2/g, 2.32 nm, and 0.54 cm3/g, respectively. An adsorption test for 200 mg/L of initial methylene blue at pH 4 showed the best performance. The adsorption data of the seaweed-based biochar followed the Langmuir isotherm adsorption model and the pseudo-second-order kinetic model, with the corresponding R2 of 0.994 and 0.995. The maximum adsorption capacity of methylene blue using the developed seaweed‑based biochar was 133.33 mg/g. The adsorption followed the chemisorption mechanism, which occurred via the formation of a monolayer of methylene blue dye on the seaweed-based biochar surface. The adsorption performance of the produced seaweed biochar is comparable to that of other commercial adsorbents, suggesting its potential for large-scale applications.

An agricultural waste-based source of energy in the form of briquettes from rice husk has emerged as an alternative energy source. However, rice husk-based briquette has a low bulk density and moisture content, resulting in low durability. This study investigated the effect of initial moisture contents of 12%, 14%, and 16% of rice husk-based briquettes blended with 10 wt% of kraft lignin on their chemical and physical characteristics. The briquetting was done using a hand push manual die compressor. The briquette properties were evaluated by performing chemical (ultimate and proximate analysis, thermogravimetric analysis), physical (density, durability, compressive strength, and surface morphology) analyses. The durability values of all briquette samples were above 95%, meeting the standard with good compressive strength, surface morphology, and acceptable density range. The briquette made from the blend with 14% moisture content showed the highest calorific value of 17.688 MJ kg−1, thanks to its desirable morphology and good porosity range, which facilitates the transport of air for combustion. Overall, this study proved the approach of enhancing the quality of briquettes from rice husk by controlling the moisture content.

Cadmium is one of the most hazardous metals in the environment, even when present at very low concentrations. This study reports the systematic development of Kenaf fiber biochar as an adsorbent for the removal of cadmium (Cd) (II) ions from water. The adsorbent development was aided by an optimization tool. Activated biochar was prepared using the physicochemical activation method, consisting of pre-impregnation with NaOH and nitrogen (N2) pyrolysis. The influence of the preparation parameters—namely, chemical impregnation (NaOH: KF), pyrolysis temperature, and pyrolysis time on biochar yield, removal rate, and the adsorption capacity of Cd (II) ions—was investigated. From the experimental data, some quadratic correlation models were developed according to the central composite design. All models demonstrated a good fit with the experimental data. The experimental results revealed that the pyrolysis temperature and heating time were the main factors that affected the yield of biochar and had a positive effect on the Cd (II) ions’ removal rate and adsorption capacity. The impregnation ratio also showed a positive effect on the specific surface area of the biochar, removal rate, and adsorption capacity of cadmium, with a negligible effect on the biochar yield. The optimal biochar-based adsorbent was obtained under the following conditions: 550 °C of pyrolysis temperature, 180 min of heating time, and a 1:1 NaOH impregnation ratio. The optimum adsorbent showed 28.60% biochar yield, 69.82% Cd (II) ions removal, 23.48 mg/g of adsorption capacity, and 160.44 m2/g of biochar-specific area.

Several agro-waste materials have been utilized for sustainable engineering and environmental application over the past decades, showing different degrees of effectiveness. However, information concerning the wider use of palm oil clinker (POC) and its performance is still lacking. Therefore, as a solid waste byproduct produced in one of the oil palm processing stages, generating a huge quantity of waste mostly dumped into the landfill, the waste-to-resource potential of POC should be thoroughly discussed in a review. Thus, this paper provides a systematic review of the current research articles on the several advances made from 2005 to 2021 regarding palm oil clinker physical properties and performances, with a particular emphasis on their commitments to cost savings during environmental and engineering applications. The review begins by identifying the potential of POC application in conventional and geopolymer structural elements such as beams, slabs, and columns made of concrete, mortar, or paste for coarse aggregates, sand, and cement replacement. Aspects such as performance of POC in wastewater treatment processes, fine aggregate and cement replacement in asphaltic and bituminous mixtures during highway construction, a bio-filler in coatings for steel manufacturing processes, and a catalyst during energy generation are also discussed. This review further describes the effectiveness of POC in soil stabilization and the effect of POC pretreatment for performance enhancement. The present review can inspire researchers to find research gaps that will aid the sustainable use of agroindustry wastes. The fundamental knowledge contained in this review can also serve as a wake-up call for researchers that will motivate them to explore the high potential of utilizing POC for greater environmental benefits associated with less cost when compared with conventional materials.

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Man-made organic waste leads to the rapid proliferation of pollution around the globe. Effective bio-waste management can help to reduce the adverse effects of organic waste while contributing to the circular economy at the same time. The toxic oily-biological sludge generated from oil refineries’ wastewater treatment plants is a potential source for biogas energy recovery via anaerobic digestion. However, the oily-biological sludge’s carbon/nitrogen (C/N) ratio is lower than the ideal 20–30 ratio required by anaerobic digestion technology for biogas production. Sugarcane bagasse can be digested as a high C/N co-substrate while the oily-biological sludge acts as a substrate and inoculum to improve biogas production. In this study, the best C/N with co-substrate volatile solids (VS)/inoculum VS ratios for the co-digestion process of mixtures were determined empirically through batch experiments at temperatures of 35–37 °C, pH (6–8) and 60 rpm mixing. The raw materials were pre-treated mechanically and thermo-chemically to further enhance the digestibility. The best condition for the sugarcane bagasse delignification process was 1% (w/v) sodium hydroxide, 1:10 solid-liquid ratio, at 100 °C, and 150 rpm for 1 h. The results from a 33-day batch anaerobic digestion experiment indicate that the production of biogas and methane yield were concurrent with the increasing C/N and co-substrate VS/inoculum VS ratios. The total biogas yields from C/N 20.0 with co-substrate VS/inoculum VS 0.06 and C/N 30.0 with co-substrate VS/inoculum VS 0.18 ratios were 2777.0 and 9268.0 mL, respectively, including a methane yield of 980.0 and 3009.3 mL, respectively. The biogas and methane yield from C/N 30.0 were higher than the biogas and methane yields from C/N 20.0 by 70.04 and 67.44%, respectively. The highest biogas and methane yields corresponded with the highest C/N with co-substrate VS/inoculum VS ratios (30.0 and 0.18), being 200.6 mL/g VSremoved and 65.1 mL CH4/g VSremoved, respectively.

Membrane fouling significantly hinders the widespread application of membrane technology. In the current study, a support vector machine (SVM) and artificial neural networks (ANN) modelling approach was adopted to optimize the membrane permeability in a novel membrane rotating biological contactor (MRBC). The MRBC utilizes the disk rotation mechanism to generate a shear rate at the membrane surface to scour off the foulants. The effect of operational parameters (disk rotational speed, hydraulic retention time (HRT), and sludge retention time (SRT)) was studied on the membrane permeability. ANN and SVM are machine learning algorithms that aim to predict the model based on the trained data sets. The implementation and efficacy of machine learning and statistical approaches have been demonstrated through real-time experimental results. Feed-forward ANN with the back-propagation algorithm and SVN regression models for various kernel functions were trained to augment the membrane permeability. An overall comparison of predictive models for the test data sets reveals the model’s significance. ANN modelling with 13 hidden layers gives the highest R2 value of >0.99, and the SVM model with the Bayesian optimizer approach results in R2 values higher than 0.99. The MRBC is a promising substitute for traditional suspended growth processes, which aligns with the stipulations of ecological evolution and environmentally friendly treatment.