ReviewMolecules (Basel, Switzerland)2023
Agricultural Solid Wastes Based Adsorbent Materials in the Remediation of Heavy Metal Ions from Water and Wastewater by Adsorption: A Review.
Review in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 95 citations in OpenAlex.
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- Potential of Wood Processing Residues as Eco-Friendly Adsorbents for Wastewater Treatment.Materials (Basel, Switzerland) · 2026Article
- Activated sludge recovered from wastewater provides a sustainable approach for removing dyes and heavy metals from effluents.Scientific reports · 2025Article
- Utilization of valorised wood bark waste as an adsorbent for the uptake of Pb(II) ions.Scientific reports · 2025Article
- Cobalt Ion Removal by Activated Carbon and Biochar Derived fromInternational journal of molecular sciences · 2025Article
- Fabrication of (amino)thiol chelating agents on SBA-15 and MCM-41 and applications in the extraction of Cd(II), Pb(II) and Cr(VI) cations from aqueous solutions.Environmental science and pollution research international · 2025Article
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- Phycomediation of cadmium contaminated aqueous solutions usingFrontiers in bioengineering and biotechnology · 2025Article
- Wastewater Treatments Based on Adsorption, Catalysis, Biodegradation, and Beyond.Molecules (Basel, Switzerland) · 2024Article
- Enhanced capacity of thiol-functionalized sugarcane bagasse and rice husk biochars for arsenite sorption in aqueous solutions.Environmental science and pollution research international · 2024Article
- Comprehensive assessment of carbon-, biomaterial- and inorganic-based adsorbents for the removal of the most hazardous heavy metal ions from wastewater.RSC advances · 2024Review
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adsorption has become the most popular and effective separation technique that is used across the water and wastewater treatment industries. However, the present research direction is focused on the development of various solid waste-based adsorbents as an alternative to costly commercial activated carbon adsorbents, which make the adsorptive separation process more effective, and on popularising the sustainable options for the remediation of pollutants. Therefore, there are a large number of reported results available on the application of raw or treated agricultural biomass-based alternatives as effective adsorbents for aqueous-phase heavy metal ion removal in batch adsorption studies. The goal of this review article was to provide a comprehensive compilation of scattered literature information and an up-to-date overview of the development of the current state of knowledge, based on various batch adsorption research papers that utilised a wide range of raw, modified, and treated agricultural solid waste biomass-based adsorbents for the adsorptive removal of aqueous-phase heavy metal ions. Metal ion pollution and its source, toxicity effects, and treatment technologies, mainly via adsorption, have been reviewed here in detail. Emphasis has been placed on the removal of heavy metal ions using a wide range of agricultural by-product-based adsorbents under various physicochemical process conditions. Information available in the literature on various important influential physicochemical process parameters, such as the metal concentration, agricultural solid waste adsorbent dose, solution pH, and solution temperature, and importantly, the adsorbent characteristics of metal ion removal, have been reviewed and critically analysed here. Finally, from the literature reviewed, future perspectives and conclusions were presented, and a few future research directions have been proposed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.