Heavy metal contamination in wastewater is a significant concern for human health and the environment, prompting increased efforts to develop efficient and sustainable removal methods. Despite significant efforts in the last few decades, further research initiatives remain vital to comprehensively address the long-term performance and practical scalability of various adsorption methods and adsorbents for heavy metal remediation. This article aims to provide an overview of the mechanisms, kinetics, and applications of diverse adsorbents in remediating heavy metal-contaminated effluents. Physical and chemical processes, including ion exchange, complexation, electrostatic attraction, and surface precipitation, play essential roles in heavy metal adsorption. The kinetics of adsorption, influenced by factors such as contact time, temperature, and concentration, directly impact the rate and effectiveness of metal removal. This review presents an exhaustive analysis of the various adsorbents, categorized as activated carbon, biological adsorbents, agricultural waste-based materials, and nanomaterials, which possess distinct advantages and disadvantages that are linked to their surface area, porosity, surface chemistry, and metal ion concentration. To overcome challenges posed by heavy metal contamination, additional research is necessary to optimize adsorbent performance, explore novel materials, and devise cost-effective and sustainable solutions. This comprehensive overview of adsorption mechanisms, kinetics, and diverse adsorbents lays the foundation for further research and innovation in designing optimized adsorption systems and discovering new materials for sustainable heavy metal remediation in wastewater.

Dietary fiber (DF) significantly affects the quality attributes of food matrices. Depending on its chemical composition, molecular structure, and degree of hydration, the behavior of DF may differ. Numerous reports confirm that incorporating DF derived from food waste into food products has significant effects on textural, sensory, rheological, and antimicrobial properties. Additionally, the characteristics of DF, modification techniques (chemical, enzymatic, mechanical, thermal), and processing conditions (temperature, pH, ionic strength), as well as the presence of other components, can profoundly affect the functionalities of DF. This review aims to describe the interactions between DF and water, focusing on the effects of free water, freezing-bound water, and unfreezing-bound water on the hydration capacity of both soluble and insoluble DF. The review also explores how the structural, functional, and environmental properties of DF contribute to its hydration capacity. It becomes evident that the interactions between DF and water, and their effects on the rheological properties of food matrices, are complex and multifaceted subjects, offering both opportunities and challenges for further exploration. Utilizing DF extracted from food waste exhibits promise as a sustainable and viable strategy for the food industry to create nutritious and high-value-added products, while concurrently reducing reliance on primary virgin resources.

Mobilization of heavy metals in the environment has been a matter of concern for several decades due to their toxicity for humans, environments, and other living organisms. In recent years, use of inexpensive and abundantly available biosorbents generated from fibrous plant-based food-waste materials to remove heavy metals has garnered considerable research attention. The aim of this review is to investigate the applicability of using fibrous plant-based food waste, which comprises different components such as pectin, hemicellulose, cellulose, and lignin, to remove heavy metals from wastewater. This contribution confirms that plant-fiber-based food waste has the potential to bind heavy metals from wastewater and aqueous solutions. The binding capacities of these biosorbents vary depending on the source, chemical structure, type of metal, modification technology applied, and process conditions used to improve functionalities. This review concludes with a discussion of arguments and prospects, as well as future research directions, to support valorization of fibrous plant-based food waste as an efficient and promising strategy for water purification.

Due to environmental concerns and economic value, the adsorption process using agricultural wastes is one of the promising methods to remove lead (Pb) from contaminated water. The relationships between agricultural waste properties, adsorption conditions, and the maximum Pb adsorption capacity of selected adsorbents have not been adequately explored. A thorough understanding of these interactions is crucial for optimizing adsorption processes and enhancing the efficiency of agricultural wastes as sustainable adsorbents. To assess Pb adsorption by agricultural wastes and identify the key influencing factors, three artificial intelligence techniques, namely Extreme Learning Machine (ELM), Adaptive Nuro-Fuzzy Inference Systems (ANFIS), and Group Method of Data Handling (GMDH) have been employed in this study. Seven input variables, namely time, ratio, initial ion concentration, type of adsorbents from agricultural wastes, pH, temperature, and agitation speed, from 771 data points were used as inputs for model development, while the quantity of Pb adsorbed was chosen as target parameter. To identify the best input combinations with one to seven variables, 127 models were defined and analyzed using ELM integrated with the cross-validation technique. The results highlighted that the initial ion concentration is the most critical factor in enhancing heavy metal adsorption, and temperature is the least important factor. The top models, utilizing one to seven input variable(s), were then modeled with ANFIS and GMDH. Subsequently, all three models were compared. The GMDH model with four input variables (initial ion concentration, type of adsorbent, time, and agitation speed) demonstrated the highest performance in terms of accuracy and simplicity.