Science and Technology for Water Purification (2nd Edition)

1. Introduction

Water scarcity, pollution, and increasingly complex contaminant mixtures continue to challenge conventional treatment processes and management paradigms. In parallel, more stringent discharge standards and the broader transition toward circular economy models are driving renewed interest in technologies that can not only remove pollutants but also recover resources (e.g., nutrients, salts, and critical elements) from wastewater and brines. At the same time, advances in modeling, sensing, and artificial intelligence (AI) are enabling more proactive operation and control of water infrastructure, from distribution-network leak localization to system-level environmental assessment.

Against this backdrop, this Special Issue “Science and Technology for Water Purification (2nd Edition)” provides a snapshot of recent progress across materials, processes, and data-driven methods relevant to water and wastewater purification. The published papers cover topics ranging from photocatalytic and catalytic oxidation technologies to adsorption and biological process intensification, as well as multiple strands of resource recovery. This editorial offers a concise overview of the eleven contributions, emphasizing the links between treatment performance, matrix effects, energy demand, and the practical requirements of engineering implementation.

2. Overview of Contributions

This Special Issue comprises ten research papers (Contributions 1–10) and one review paper (Contribution 11). For clarity, we group the contributions into several thematic directions: system-level assessment and data-driven water management; advanced oxidation and photocatalysis; adsorption using engineered biomass-derived materials; biological nitrogen removal enhancement; and resource recovery from wastewater and brines.

2.1. System-Level Assessment and Data-Driven Water Management

Wang and colleagues (Contribution 1) developed a coupled framework for the integrated assessment of anthropogenic carbon (C), nitrogen (N), and phosphorus (P) inputs, using Panjin City as a case study. Their results illustrate how the dynamics of C, N, and P cycles can be interpreted jointly to support environmental governance: net anthropogenic carbon inputs increased by 33% from 2016 to 2020, while net anthropogenic nitrogen and phosphorus inputs decreased by 14% and 28%, respectively. The study further quantifies pathways to receiving waters (approximately 4.5% of N and 2.9% of P inputs were discharged) and highlights the need for systemic strategies combining energy structure optimization, ecological restoration, and pollution source reduction.

At the infrastructure scale, Xi and colleagues (Contribution 10) addressed pipeline leakage in urban water supply networks by integrating deep learning artificial neural networks with an optimization-assisted District Metering Area (DMA) strategy. Using the simplified Net2 benchmark network, the proposed DMA-CS method improved leak localization accuracy to 97.43%, compared with 92.67% for the baseline DMA approach. This work exemplifies how data-driven algorithms can enhance real-time decision support and reduce non-revenue water through more precise fault identification.

2.2. Photocatalysis and Catalytic Oxidation

Photocatalysis and catalytic oxidation remain central routes for degrading recalcitrant organic pollutants. Wei and Ren (Contribution 2) proposed a visible-light-responsive TiO₂/layered double hydroxide (TiO₂/LDHs) heterostructure, prepared by co-precipitation, to address the limited visible-light utilization and charge recombination of conventional TiO₂. The best-performing composite (Al:Ti = 1:1, denoted AT11) achieved 98.2% methylene blue degradation within 70 min under simulated sunlight, with an optimal catalyst dosage of 1 g/L. Notably, the material retained appreciable activity over multiple cycles (78.93% degradation after four cycles), indicating stability relevant to practical reuse.

Al-Essa and colleagues (Contribution 7) reported a graphitic carbon nitride-loaded ceria (CeO₂/GCN) nanocomposite for sunlight-driven methyl red degradation. The composite exhibited a reduced band gap (2.97 eV) relative to CeO₂ nanoparticles (3.90 eV), consistent with enhanced visible-light response. As a result, the CeO₂/GCN catalyst achieved 99.92% dye removal within 40 min, substantially outperforming CeO₂ nanoparticles alone (69.47%).

Beyond photocatalysis, Zhang and colleagues (Contribution 6) integrated catalytic functionality into silicon carbide membrane filters by coating Co/Al layered double hydroxides (Co/Al-LDHs) onto SiC and applying a heating treatment that increased persulfate activation ability. In a flow-through configuration, the catalytic membrane system removed approximately 95% of aniline within 20 min at a flow velocity of 0.7 m/s and a persulfate-to-aniline ratio of 8:1, demonstrating a promising pathway for combining separation and oxidative degradation in a compact process unit.

2.3. Adsorption Using Engineered Biomass-Derived Materials

Developing low-cost adsorbents from waste biomass is a practical strategy for dye-laden industrial effluents and other organic pollutants. Kanwal and co-authors (Contribution 5) prepared nickel-modified orange peel biochar for the adsorption of Eriochrome Black T (EBT). The study evaluated key operating variables (adsorbent dose, pH, temperature, contact time, and initial dye concentration) and applied isotherm and kinetic models to interpret the uptake behavior. Under the reported optimum conditions (0.1 g adsorbent dose, 25 ppm dye, 90 min, 35 °C, and pH 4), the modified biochar delivered high removal performance. Model fitting suggested monolayer adsorption consistent with the Langmuir isotherm (R² = 0.99) and pseudo-second-order kinetics (R² = 0.99), while thermodynamic analysis indicated a spontaneous, exothermic process. These results reinforce the potential of waste-derived biochars as scalable and sustainable adsorption media.

2.4. Biological Treatment Intensification

Biological nitrogen removal is often constrained in municipal wastewaters with low carbon-to-nitrogen (C/N) ratios, where denitrification may require costly external carbon sources. Diao and colleagues (Contribution 3) investigated heterotrophic nitrification and aerobic denitrification (HN-AD) bacterial agents combined with modified basalt fiber carriers to enhance simultaneous nitrification and denitrification. Among three tested reactors, the mixed-strain plus activated sludge system achieved the best median performance, reaching removal efficiencies of 82.2% for NH₄⁺-N, 52.9% for total nitrogen, and 51.6% for COD. Importantly, the enhanced system reduced COD consumption per unit of total nitrogen removed by ~40% relative to the activated-sludge control, indicating a pathway to lower operational cost and improved robustness under carbon-limited conditions.

2.5. Resource Recovery and Valorization

Resource recovery is increasingly viewed as a core objective of modern water treatment. Yan and co-authors (Contribution 9) designed a coupled electrolysis–microfiltration process to recover phosphorus as iron phosphate compounds, using steel pickling wastewater as an iron source. The system achieved phosphorus recovery of 42–80% at current densities of 5–20 mA/cm², with reported energy consumption of 5.78–9.15 kWh/(kg P) and current efficiency ranging from 79% to 43%. After microfiltration, an aeration step further reduced residual phosphorus to 0.5 mg/L within 30 min, meeting discharge requirements while enabling circular use of the extracted acid stream in pickling.

In high-salinity industrial effluents, More and colleagues (Contribution 8) reported four-year operational insights into pipe freeze-crystallization for Na₂SO₄ recovery and water production. The study contrasts the process energy demand (~330 kJ/kg) with conventional evaporation/distillation approaches (~2200 kJ/kg) and demonstrates significant improvements in recovered salt purity (from 50% to 84.9%) and recovery rate (from 3.5 to 9.1 t/month) through iterative engineering modifications. These results highlight freeze-based separations as viable routes toward near-zero-waste brine management.

Critical element recovery from produced waters is another emerging direction. Shan and colleagues (Contribution 4) systematically evaluated how common coexisting ions and organic components influence lithium solvent extraction from oil and gas field water. They found that Ca²⁺ and Mg²⁺ can strongly interfere and should be removed prior to extraction, while several anions (e.g., Cl⁻, SO₄²⁻, and NO₃⁻) exerted limited influence. After a two-step process combining impurity-ion precipitation and solvent extraction, lithium extraction efficiency exceeded 90%, and a lithium carbonate product purity of 99.28% was reported for a 15 L field-water sample.

2.6. Review Article: Dissolved Organic Matter and Eutrophication

In addition to the research papers, Yan and co-authors (Contribution 11) provided a mini review on how dissolved organic matter (DOM) optical and molecular properties vary across freshwater eutrophication gradients. The review summarizes evidence from UV–Vis absorption, fluorescence spectroscopy, and Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and employs generalized additive model analysis to examine correlations between DOM indicators and trophic state index. The synthesis highlights that several optical metrics (including DOC, a254, SUVA254, and FI) tend to increase with eutrophication, while molecular-composition indicators can exhibit nonlinear behavior, reflecting shifts in DOM sources from terrestrial/macrophyte-derived inputs toward algal- and sediment-derived fractions. Such insight supports improved monitoring strategies and informs upstream control of eutrophication-driven water-quality deterioration.

3. Conclusions and Outlook

The eleven contributions in this Special Issue collectively demonstrate that progress in water purification increasingly depends on the integration of materials innovation, process engineering, and data-driven management. Several cross-cutting messages emerge. First, modeling and analytics—from coupled C–N–P accounting frameworks to machine-learning-assisted leak localization—can convert complex environmental and operational data into actionable guidance for system optimization. Second, advanced oxidation and photocatalytic materials continue to improve via heterojunction construction and process integration, enabling high-efficiency dye degradation under solar or simulated solar irradiation and supporting more compact treatment units. Third, biomass-derived adsorbents and targeted bioaugmentation strategies provide pragmatic, potentially low-cost options for industrial and municipal wastewaters, particularly under matrix constraints such as low C/N ratios. Finally, resource recovery (phosphorus, salts, and lithium) is moving closer to implementation as studies increasingly quantify energy demand, interference effects, and product purity.

Future research should prioritize (i) scale-up and long-term stability under realistic water matrices, (ii) standardized performance metrics and by-product risk assessment for advanced oxidation systems, (iii) life cycle and techno-economic analyses to benchmark emerging processes against conventional baselines, and (iv) digital-twin and control frameworks that integrate sensors, models, and AI to enable real-time optimization. We hope this Special Issue will stimulate further interdisciplinary progress toward resilient, energy-efficient, and circular water purification systems.

We thank all contributing authors for sharing their research and the reviewers for their constructive comments, which helped strengthen the published papers.