This pioneering work explores the immense potential of young coconut waste, a continuously marginalized residue of the food and beverage industry, to serve as an indispensable feedstock in the production of biochar. Through an examination of the key carbonization factors that include time, temperature, and concentrations of the activating agent, KOH, the outcomes offer relevant insights that could be leveraged to maximize biochar production for tailored applications. This study stands out for its innovative use of Artificial Neural Network (ANN) approaches for predictive modeling. Fifty datasets, supplemented with secondary data obtained from the literature and experiments, were utilized for the purposes of training, testing, and validating the neural network model. Here, the datasets were processed utilizing the Deep Neural Network (DNN) framework, which was designed and implemented with the minimal loss function framework feasible. The architectural configuration comprises the following; an input layer, four hidden layers (128-neuron dense layer, batch normalization, and 64-neuron dense layer, batch normalization), a dropout layer, and an output layer. With an R2 of 0.8238 for biochar yield and 0.7324 for iodine number, the trained DNN model showed a relatively high degree of accuracy in making predictions.
The reason for such enormous efforts in palm oil mill effluent research would be what has been singled out as one of the major sources of pollution in Malaysia, and perhaps the most costly and complex waste to manage. Palm oil mill final discharge, which is the treated effluent, will usually be discharged to nearby land or river since it has been the least costly way to dispose of. Irrefutably, the quality level of the treated effluent does not always satisfy the surface water quality in conformity to physicochemical characteristics. To work on improving the treated effluent quality, a vertical surface-flow constructed wetland system was designed with Pennisetum purpureum (Napier grass) planted on the wetland floor. The system effectively reduced the level of chemical oxygen demand by 62.2 ± 14.3%, total suspended solid by 88.1 ± 13.3%, ammonia by 62.3 ± 24.8%, colour by 66.6 ± 13.19%, and tannin and lignin by 57.5 ± 22.3%. Heat map depicted bacterial diversity and relative abundance in life stages from the wetland soil, whereby bacterial community associated with the pollutant removal was found to be from the families Anaerolineaceae and Nitrosomonadaceae, and phyla Cyanobacteria and Acidobacteria.
Application of sewage sludge as fertilizer can be beneficial for sustainable agriculture as it could largely account for nitrogen and phosphorus demand for crops and has lower costs compared to other disposal routes, e.g., incineration, and sanitary landfills. This study evaluates the feasibility of pilot-scale pelletization of sewage sludge for non-food crops (e.g., ornamental plants). The co-pelletization method was designed by mixing sewage sludge and binder (tapioca starch) at a 9:1 sludge-to-starch weight ratio. The amount of nitrogen (N), phosphorus (P), and potassium (K) of the resultant pellets were determined at 5.7%, 4.9%, and 0.2%, respectively. Following Malaysian and US Standards, non-essential elements and pathogenicity of the pelletized sewage sludge were measured below the predetermined limits and hence safe for agricultural application. The planting trial using 50% inorganic fertilizer + 50% sewage sludge pellets exhibited a promising result on the growth of the flowering plant Celosia plumosa, with having better dimension and color, 20% higher in height, 4% more chlorophyll content, 54% more leaf, 43% greater stem growth, and 27% more flowers compared to control. Likewise, the planting trial on Tagetes erecta resulted in 10.5% wider leaf, 10.6% heavier leaf dry weight, and 12.5% more chlorophyll content compared to control with full usage of inorganic fertilizer. By considering liquidities to operate the production facility, the economic analysis estimated that the production cost per ton of pelletized sewage sludge produced was USD 0.98.
The utilization of lignocellulosic biomass in various applications has a promising potential as advanced technology progresses due to its renowned advantages as cheap and abundant feedstock. The main drawback in the utilization of this type of biomass is the essential requirement for the pretreatment process. The most common pretreatment process applied is chemical pretreatment. However, it is a non-eco-friendly process. Therefore, this review aims to bring into light several greener pretreatment processes as an alternative approach for the current chemical pretreatment. The main processes for each physical and biological pretreatment process are reviewed and highlighted. Additionally, recent advances in the effect of different non-chemical pretreatment approaches for the natural fibres are also critically discussed with a focus on bioproducts conversion.