Food waste is a matter of deep concern as it is creating multidimensional threats to the environment. Though these are potential sources of plant nutrients, a detailed investigation has not yet been conducted. Hence, a physico-chemical characterization of non-edible food waste such as brinjal waste, potato peels, banana peels, orange peels, eggshells, cow bones, chicken bones, fish bones, and their combined waste was accomplished using FTIR, TGA, XGT-5000, CHN corder, etc. The present study revealed that plant waste samples had lower ash contents (1.36–7.79%) but higher volatile matter (72.33–80.04%), and the reverse was true in animal waste. In addition, animal waste, except eggshells (22.48%), had lower fixed carbon (1.01–2.83%). On the other hand, fruit waste was documented with higher fixed carbon (11.33–14.27%). Results also indicated that animal waste and their combined samples, except eggshells, contained more nitrogen (3.82–5.06%). The concentration of P was statistically significant in the combined fruit sample (28.21% ± 8.451), followed by banana peels (24.96% ± 11.644). Vegetable waste contained a significantly higher amount of K (24.90% ± 28.311–37.92% ± 24.833) than other waste. Maximum Ca (68.82% ± 10.778) and Mg (15.37% ± 29.88) were recorded in eggshell and fish bone waste, respectively. Except for Zn and Mn in eggshells, the waste studied contained a significant amount of micronutrients. FTIR demonstrated the presence of different functional groups such as alcoholic group (OH), aliphatic chain (C–H), aromatic chain (C–H), alkyl aryl ether (C–O), carbonyl group (C=O), alkene (C=C), thiocyanate (S–CN), isothiocyanate (N=C=S), allene (C=C=C), sulphate (S=O), amine (N–H), and NO stretching band, which varied with the waste used. Thermogravimetric analysis revealed that plant waste degraded more quickly than animal waste. Eggshells were found to be less degradable by increased temperature, followed by cow bones > fish bones > chicken bones. The waste material used in the study was slightly acidic (6.67–6.82) in nature. Correlation analysis of the nutrients showed mainly positive relations in all samples for macro and micronutrients. Therefore, non-edible food waste can be a possible source of plant nutrients.

Ibuprofen is a significant nonsteroidal anti-inflammatory drug that poses environmental and health risks when present in wastewater because of its persistence and probable toxicity. This study investigates the use of banana peel biochar (BPB) made at 600 °C to 900 °C to eliminate ibuprofen from aqueous solutions. The uniqueness of this work lies in the high-temperature pyrolysis process, which has not been previously explored for the ibuprofen removal efficiency using BPB. The batch experiment was conducted considering initial concentrations, pH, and contact time. The data were compared with different algorithms, with Linear Regression (LR), Support Vector Machines (SVM), Decision Trees (DT), Random Forest (RF), and k-Nearest Neighbor (k-NN) to forecast the performance. The results revealed that banana peel biochar at 900 °C exhibited the highest ibuprofen removal efficiency (69.28 ± 0.83%) at 125 mg/L concentration with the sequence of BPB900 > BPB800 > BPB700 > BPB600. A maximum removal efficiency of 72.67 ± 0.75% was observed at pH 9. Adsorption behavior was analyzed using isotherm and kinetic models, with the Freundlich isotherm model (R² value 0.9620) indicating heterogeneous adsorption and the pseudo-second-order (PSO) kinetic model (R² value 0.9969) suggesting that physicochemical interactions govern the process. FTIR analysis ensured the existence of functional groups (hydroxyl, carboxylic, carbonyl, and aromatic rings) responsible for adsorption. Machine learning algorithms, especially RF, demonstrated outstanding performance with 90.07% accuracy in predicting the experimental data. In comparison to other adsorbents, BPB demonstrated superior removal efficiency, underscoring its effectiveness. The study suggests that BPB, particularly at 900 °C, is effective in removing ibuprofen, and due to its sustainable production, it offers a potential solution for wastewater treatment.

Heavy metal pollution is a growing public health concern owing to rising environmental pollution throughout the world. The situation is more vulnerable in Bangladesh; therefore, this study assessed contamination levels in different land use categories such as rural, local market, industrial, research, and coastal areas, as well as the related health risks for farmers in Bangladesh. A total of 45 soil samples were considered from three depths (0–5 cm, 5–10 cm, and 10–15 cm) across five different areas, with three replications per depth, following the monsoon season. Samples were prepared using a diacid mixture, and heavy metals (Cu, Ni, Mn, Cr, Zn, Pb) were investigated using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Health risks were evaluated using standard assessment models. The results showed that coastal agricultural soils had the highest heavy metal concentrations (except Pb), while rural areas had the lowest (except Cu and Ni), with no clear depth-based pattern. Two contamination sources were identified: component 1 (Cu, Ni, Mn, Cr, Zn) and component 2 (Pb, Zn), indicating mixed and anthropogenic sources, respectively. The Pollution Load Index (PLI) was highest in coastal areas and lowest in rural areas. The average daily intake of metals followed the order of inhalation > dermal > ingestion, with inhalation being the primary exposure route. The highest cumulative cancer risk (CCR) was observed in coastal agricultural soils (5.82 × 10⁻⁹), while rural soils had the lowest CCR (8.24 × 10⁻¹⁰), highlighting significant regional differences in health risks.

Nutritional disparity is a crucial impediment to agricultural productivity that interferes with soil structural stability and plant growth since more than one-fourth of the total land area is affected, especially by sodicity globally. This study assesses the mathematical models of non-edible food waste, including brinjal waste, potato peel, banana peel, orange peel, eggshell, cow bone, chicken bone, and fish bone. After consumption of the food, the resulting non-edible food waste was cleaned, dried, crushed, and stored separately in aluminum zipper bags. Cation concentrations of the considered waste materials were measured using ion chromatography systems. Then the mathematical models such as Exchangeable Sodium Percentage (ESP), Exchangeable Potassium Percentage (EPP), Sodium Adsorption Ratio (SAR), Potassium Adsorption Ratio (PAR), and Cation Ratio of Soil Structural Stability (CROSS) were assessed considering cation concentrations. The results revealed that Na+ concentrations ranged from 0.17±0.001 mg/kg in orange peel to 5.21±0.005 mg/kg in chicken bone; K+ ranged from 0.28±0.003 mg/kg in eggshell to 56.50±0.216 mg/kg in banana peel; Ca2+ ranged from 0.30±0.004 mg/kg in potato peel to 1.37±0.049 mg/kg in eggshell; and Mg2+ ranged from 0.06±0.004 mg/kg in eggshell to 1.12±0.006 mg/kg in banana peel. The overall concentration sequence was K+>Na+>Ca2+>Mg2+. In addition, animal waste biomass had comparatively high ESP and EPP values for the studied waste biomasses. SAR, PAR, and CROSS models for all studied wastes are suitable for application to sodic and saline soils. In conclusion, non-edible food waste biomass might be a reliable source of cations that is important for soil structural stability and ultimately for plant growth and could be utilized in sodic and saline soils based on the analysis of cationic parameters and mathematical models.