Systematic Review of Polymer Selection for Dewatering and Conditioning in Chemical Sludge Processing

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@article{1708817,
      author = {Matluck Afolabi, Ogechi Amanda Onukogu, Thompson Odion Igunma, Adeniyi K. Adeleke, Zamathula Q. Sikhakhane Nwokediegwu},
      title = {Systematic Review of Polymer Selection for Dewatering and Conditioning in Chemical Sludge Processing},
      journal = {Iconic Research And Engineering Journals},
      year = {2020},
      volume = {4},
      number = {5},
      pages = {163-180},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1708817.pdf},
      abstract = {This systematic review explores the selection of polymers for dewatering and conditioning in chemical sludge processing, a critical step in optimizing sludge volume reduction, improving handling, and minimizing environmental impact. Chemical sludge, primarily generated from industrial effluent treatment, poses significant management challenges due to its complex physicochemical properties. The efficiency of dewatering and conditioning processes is heavily influenced by the type, charge density, and molecular weight of the polymer used. This review consolidates findings from over 100 peer-reviewed studies and industrial reports published between 2000 and 2020, focusing on polymer categories such as cationic polyacrylamides, anionic flocculants, and natural polymer derivatives. Key selection criteria include sludge characteristics (pH, solids concentration, and particle size distribution), process configuration (gravity thickening, centrifugation, or filter press), and operational parameters such as dosage, mixing energy, and residence time. The review identifies cationic polymers with medium to high charge density as the most effective for treating sludge with high colloidal content, particularly in aluminum- and ferric-based chemical sludges. Conversely, anionic polymers demonstrated optimal performance when used as co-polymers or in dual conditioning strategies with inorganic coagulants. Bio-based polymers, while promising for sustainable sludge treatment, show inconsistent performance and require further optimization. Comparative analyses reveal that polymer performance varies widely depending on specific sludge matrices, underlining the importance of pilot-scale testing for accurate polymer selection. Furthermore, the integration of machine learning and chemometric tools for predictive polymer selection is emerging as a powerful approach, enabling data-driven decision-making in sludge management practices. This review underscores the need for standardization in polymer testing protocols and highlights emerging trends in green chemistry for sludge treatment. By synthesizing global research findings, the study provides actionable insights for wastewater treatment plant operators, environmental engineers, and policymakers seeking cost-effective and sustainable sludge processing strategies. Future research directions should explore hybrid polymer systems, long-term effects on sludge cake reuse, and lifecycle assessments of polymer use in sludge conditioning.},
      keywords = {Polymer Selection, Chemical Sludge, Dewatering, Conditioning, Cationic Polyacrylamide, Sludge Treatment, Bio-Based Flocculants, Wastewater Management, Charge Density, Sludge Characteristics.},
      month = {November},
  }