From Mineral Salts to Smart Hybrids: Coagulation–Flocculation at the Nexus of Water, Energy, and Resources—A Critical Review
Abstract
1. Introduction
1.1. Global Context: Challenges Linked to Wastewater Pollution
1.2. Limitations of Conventional Wastewater Treatment Technologies
1.3. The Role of Coagulants in Wastewater Treatment Chains
1.4. Objective of the Review
- Identify recent progress in the development of multifunctional, hybrid, or composite coagulants capable of broadening the range of pollutants removed while minimizing environmental impact-such as magnetic or bio-functional coagulants;
- Assess emerging technological potentials, including assisted electrocoagulation, high-turbulence processes optimized through Computational Fluid Dynamics (CFD), and real-time adaptive dosing systems;
- Highlight sustainability criteria, including treatment efficiency, reduced coagulant toxicity, ease of sludge valorization, and compatibility with biological or membrane processes.
- Explore the integration of intelligent systems, notably coupling coagulation with automated technologies, IoT-enabled monitoring, and artificial intelligence to dynamically adjust treatment parameters according to load variability;
- Compare findings from applied studies on representative effluents—such as textile, agro-industrial, and petrochemical wastewater—to provide a rigorous synthesis of the optimal conditions for next-generation coagulation–flocculation technologies;
2. Evolution of Coagulant Technologies for Wastewater Treatment
2.1. Traditional Mineral Coagulants (Before the 1960s)
2.2. Emergence of Synthetic Organic Coagulants and Improved Mineral Formulations (1960–1990)
2.3. Revival of Natural and Bio-Based Coagulants (1990–2010)
2.4. Recent Innovative and Hybrid Technologies (2010–2025)
3. Coagulation/Flocculation Mechanisms and Performance Criteria
3.1. Fundamentals of Coagulation/Flocculation Mechanisms
3.2. Comparative Performance of Different Categories of Coagulants
3.3. Criteria for Selecting a Coagulant (Efficiency, Cost, Sustainability, Toxicity, Etc.)
4. Scientific Gaps, Technological Limits and Current Challenges
4.1. Scientific Gaps in the Understanding of Coagulation/Flocculation Mechanisms
- Advanced molecular characterization of natural and hybrid coagulants;
- Multi-scale analysis of floc structures using microscopy, spectroscopy, and modeling;
- Development of robust kinetic models, experimentally validated across different effluent types;
- Integration of experiments, online sensing, and simulation to enable real-time process optimization.
4.2. Technological Limitations and Application Constraints
4.3. Current Challenges and Open Questions
5. Recommendations and Future Perspectives
5.1. Immediate and Practical Recommendations
5.1.1. Research Directions
Development of Innovative Coagulants
Integration into Industrial Treatment Trains
5.2. Long-Term Perspectives
5.2.1. Toward Intelligent Coagulation
5.2.2. Disruptive Innovation: Electrocoagulation and Biocoagulation
5.2.3. Toward a Circular Economy of Coagulants
5.2.4. Interdisciplinary Approach and Multi-Stakeholder Partnerships
5.3. Digital Transformation, Circular Economy, and SDG Synergies in Coagulant Development
5.3.1. Digital Transformation and Smart Coagulation Systems
5.3.2. Circular and Green Economy Synergies, SDGs, and Indigenous Biomaterial Coagulants
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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| Category | Typical Efficacy | Usual Dose (mg L−1) | Optimum pH | Indicative Cost (€/kg) | Advantages | Disadvantages | Typical Applications | Key References |
|---|---|---|---|---|---|---|---|---|
| Minerals (alun, PAC, FeCl3/Fe2(SO4)3) | Turbidity > 90%, MES > 85%, DCO 20–60%, heavy metals 40–80% | 10–60 (Al2(SO4)3)/15–25 (PAC)/20–60 (Fe3+) | 5.5–7.5 (Al, PAC); 4–6 (Fe3+) | 0.1–0.4 | Low cost—Availability—Fast kinetics | Abundant sludge—Sensitive to pH and alkalinity | Urban processing, metallurgy, textiles | [97,98,99,100,101] |
| Synthetic polymers (PAM, polyDADMAC, polyamines) | Turbidity > 95%, MES > 90%, DCO 30–70%, good performance on colorants | 0.2–10 | 4–9 (large) | 2–3 | Very low dosage—Wide pH range—Dense flocs | High price—Organic residual potential—Sensitivity to shear | Refineries, paper and cardboard, activated sludge | [102,103,104,105,106] |
| Natural (chitosan, Moringa, mucilage, lignin) | Turbidity 70–95%, MES 60–90%, metals 40–70% | 10–300 (variable depending on biomass) | 5–8 (chitosan ≤ 7) | 1–2 (seeds) à >50 (chitosan) | Biodegradable—Low toxicity—Renewable source | Batch variability—Limited storage—Extra cost (chitosan) | Decentralized processes, agro-industries, micropollutants | [107,108,109,110,111] |
| Advanced hybrids (chitosan–Fe3O4, MOF, PAC-AC, GO-nano-Fe) | Turbidity > 95%, MES > 90%, DCO 40–80%, metals > 90% | 5–30 | 6–8 (Often) | >5 | Multifunctional (adsorption + coag.)—Magnetic separation—Low sludge | Synthesis cost—Large-scale validation missing | Complex industrial discharges, drilling water, reuse. | [90,112,113,114] |
| Coagulant Type | Representative Feedwater | pH Range | Typical Dosage (mg L−1) | Turbidity Removal (%) | COD Removal (%) | References |
|---|---|---|---|---|---|---|
| Alum (Al2(SO4)3) | Municipal wastewater | 6–8 | 40–80 | 90–96 | 70–80 | [101,122] |
| FeCl3 | Textile effluent | 4–7 | 30–60 | 88–94 | 65–75 | [123] |
| Chitosan | Dairy wastewater | 6–8 | 15–30 | 91–97 | 75–85 | [124,125] |
| Moringa oleifera extract | Surface water | 6–7 | 20–40 | 92–98 | 70–82 | [126,127] |
| Polymeric–metal hybrid (Fe–PAA) | Industrial leachate | 5–8 | 10–25 | 95–99 | 80–88 | [128,129] |
| Magnetic nanocomposite (Fe3O4–Chitosan) | Municipal wastewater | 5–8 | 5–15 | 96–99 | 82–90 | [130,131,132] |
| Scientific Gaps (Missing Knowledge) | Technological Limitations (of the Current Process) | Current Challenges (Improvement Directions) |
|---|---|---|
| Incomplete understanding of microscopic mechanisms of coagulation–flocculation (precise roles of active chemical species, interfacial interactions) | Partial effectiveness on certain pollutants: conventional coagulants poorly remove dissolved organic matter and micropollutants (pharmaceuticals, microplastics, etc.) | Combining coagulation–flocculation with other processes to treat refractory pollutants (coupling with advanced oxidation, membranes, etc.) |
| Limited predictive modeling—dependence on empirical jar tests for optimal dosage due to lack of robust mathematical models capturing the process complexity | Generation of large volumes of chemical sludge, concentrating pollutants instead of destroying them, causing treatment/disposal issues | Sludge valorization within a circular economy (reuse as fertilizer if non-toxic, recovery of metals, etc.) |
| Lack of standardization in experimental protocols (pH, mixing speed, contact time), making comparison across studies difficult | Dependence on strict conditions: requires optimal pH and precise doses (otherwise efficiency drops), secondary impacts (pH shifts, added salts in treated water) | Development of alternative “green” coagulants (biopolymers, plant extracts, magnetic nanomaterials) that are efficient and stable to reduce reliance on metal salts |
| Poorly studied multi-contaminant interactions: how the simultaneous presence of diverse pollutants in industrial effluents influences floc formation and removal efficiency | Reduced effectiveness on highly loaded or recalcitrant effluents: coagulation–flocculation alone cannot handle wastewater with low biodegradability or high toxicity | Adaptation to variable effluents: designing flexible systems (sensors, real-time control, AI) capable of adjusting dosing in response to fluctuations in industrial wastewater quality |
| Unclear mechanisms of natural/bio-based coagulants: difficulty identifying the dominant active principle and predicting large-scale performance | Risks associated with chemical coagulants: residual metals (Al, Fe) in treated water may pose health risks (e.g., aluminum neurotoxicity) and ecological issues (increased salinity) | Compliance with stricter regulations: meeting new discharge standards (heavy metals, CMR, etc.) and integrating tertiary treatments (activated carbon, ozonation, membranes) |
| Insufficient pilot/full-scale data: most studies are lab-scale; more real-world evidence is needed to validate long-term performance and reliability | High reagent consumption and costs: heavy use of alum, ferric chloride, and polymers with significant economic and carbon footprint (production, transport) | Economic and environmental optimization: lifecycle assessment and cost–benefit analysis to minimize reagents, energy use, and global environmental impact |
| Strategic Axes | Short-Term Recommendations | Medium/Long-Term Perspectives |
|---|---|---|
| Mechanistic understanding | Molecular studies of coagulant–pollutant interactions (simulation, spectroscopies) to identify active sites. Standardized protocols (zeta potential, DoE) to optimize doses.–Introduce co-adsorption to model multi-mechanism effects. | Online sensors + AI models to track floc formation in real time (texture, predicted turbidity) and refine kinetics. Hybrid AI + mechanistic models (e.g., PHREEQC) to forecast coagulation chemistry versus conditions. |
| Innovative coagulants | Chemical modification of biopolymers (modified chitosan, tannins) to improve stability/reactivity. Organo-mineral hybrids (e.g., chitosan–silica) combining adsorption & flocculation. Embed nanoparticles (magnetic, etc.) to add functionalities (magnetic recovery). | Smart, stimuli-responsive coagulants adapting to pH, T, magnetic field (in development). Targeted nanosystems to selectively coagulate specific micropollutants. |
| Process integration | Coagulation + membranes (UF/NF) to reduce fouling and improve water quality. Coagulation + AOP (Fenton, ozone) for refractory pollutants. Technical guides: optimal combined conditions, automation, monitoring KPIs. | Modular integrated trains where coagulation is co-optimized with biological/membrane/AOP steps in an intelligent plant (“Coagulation 4.0”). AI-based, whole-train optimization (predict membrane fouling, adjust coagulant dose, etc.). |
| Intelligent control | Deploy multi-parameter sensors (turbidity, TOC, UV254) on raw water to quickly adjust dosing; pilot experiences. Advanced control (e.g., MPC) using real-time signals to minimize effluent variability. | Predictive, adaptive dosing via AI: ~30% coagulant savings observed at full scale. IoT/Cloud platforms integrating sensor data and decision models into plant SCADA. Soft sensors delivering instant estimates (e.g., effluent turbidity) to boost control responsiveness. |
| Disruptive alternatives | Electrocoagulation (EC) pilots assessing feasibility across effluents. Trials of biocoagulants (plant extracts, algal/microbial polymers) as partial substitutes for metal salts. | Hybrid EC + biocoagulant systems: near-total removals for organics in case studies (≥99% COD/turbidity for brewery wastewater), with lower sludge and chemical footprint. Energy-optimized EC (renewables, durable electrodes) for sustainable industrial rollout.– Microbial/enzymatic biocoagulation targeting specific pollutants (microplastics, PFAS). |
| Circular economy | Valorize local wastes as coagulants: chitosan from crustacean shells; fly ash/biochars as coagulant–adsorbents. Pilot reuse of coagulation sludges: characterize potential as soil amendment or construction material. | Local closed loops: coagulant from local by-products, used in treatment, sludges recycled into bricks/cement or agriculture—zero-waste loops. Recover critical metals (Al, Fe, rare earths) from sludges via hydrometallurgy for reuse (incl. re-manufacturing coagulants). |
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© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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El Ouadrhiri, F.; Saleh, E.A.M.; Lahkimi, A. From Mineral Salts to Smart Hybrids: Coagulation–Flocculation at the Nexus of Water, Energy, and Resources—A Critical Review. Processes 2025, 13, 3405. https://doi.org/10.3390/pr13113405
El Ouadrhiri F, Saleh EAM, Lahkimi A. From Mineral Salts to Smart Hybrids: Coagulation–Flocculation at the Nexus of Water, Energy, and Resources—A Critical Review. Processes. 2025; 13(11):3405. https://doi.org/10.3390/pr13113405
Chicago/Turabian StyleEl Ouadrhiri, Faiçal, Ebraheem Abdu Musad Saleh, and Amal Lahkimi. 2025. "From Mineral Salts to Smart Hybrids: Coagulation–Flocculation at the Nexus of Water, Energy, and Resources—A Critical Review" Processes 13, no. 11: 3405. https://doi.org/10.3390/pr13113405
APA StyleEl Ouadrhiri, F., Saleh, E. A. M., & Lahkimi, A. (2025). From Mineral Salts to Smart Hybrids: Coagulation–Flocculation at the Nexus of Water, Energy, and Resources—A Critical Review. Processes, 13(11), 3405. https://doi.org/10.3390/pr13113405

