Biomass-to-nanomaterial pathways for sustainable environmental remediation: Advances in green synthesis, functional mechanisms, and circular economy prospects

Abstract

Rapid industrialization and fossil fuel dependency have driven environmental pollution, necessitating innovative and sustainable remediation strategies. Nanomaterials derived from biomass are gaining considerable interest as viable options due to their abundance, renewability, affordability, and easy tunability of surface functionality. Here, the review critically evaluates biomass-to-nanomaterial conversion routes and their applications in green environmental remediation. New synthetic approaches such as hydrothermal carbonization, pyrolysis, sol–gel processing, and bio-assisted templating are discussed in terms of scalability, energy efficiency, and environmental compatibility. Special emphasis is placed on surface chemistry and hierarchical structures from lignocellulosic, algal, and agricultural precursors that enhance adsorption, photocatalysis, and redox-based contaminant removal. The formation of composites with clays, metal oxides, and biochar to create hybrid systems is highlighted for enhancing efficiency and recyclability. Problems like variability of the feedstocks, stability of regeneration, and optimization of the processes are discussed along with future topics like machine learning-directed design and life cycle analyses. This review emphasizes biomass-based nanomaterials as a converging platform that combines green chemistry and environmental engineering toward low-carbon, scalable technologies for wastewater and air pollution control in support of global sustainability goals. • Biomass-derived nanomaterials are explored as sustainable remediation agents. • Conversion routes like pyrolysis, sol–gel, and hydrothermal carbonization are reviewed. • Surface chemistry and hierarchical structures enhance adsorption and photocatalysis. • Hybrid composites with clays, metal oxides, and biochar improve efficiency and reuse. • Future directions include AI-driven material design and life-cycle sustainability analysis.