## 8 Future Perspectives
Overall, Figure 16 emphasizes the synergy between clean energy input and closed-loop water management. It highlights the potential of photocatalysis not just as a stand-alone treatment technology, but as a core component in integrated environmental solutions aimed at optimizing energy use, minimizing waste, and advancing sustainable development goals. While photocatalytic processes are being explored not only for pollutants degradation, but also for resource recovery, such as nutrient (e.g., nitrogen and phosphorus) and metal reclamation, their feasibility at scale remains debated. Although promising results have been achieved in laboratory studies, including enhanced recovery from synthetic and real wastewater matrices, significant challenges in selectivity, separation efficiency, and cost-effectiveness persist when integrating such processes into existing infrastructure. In particular, the low concentration of target elements, co-existing matrix complexity, and post-recovery purification needs can hinder practical implementation and economic viability. Table 9 summarizes these obstacles, including issues related to catalyst reuse, variability in real matrices, and energy consumption [126; 128; 130; 132]. Future work must address these limitations through system-level optimization, pilot-scale trials, and the development of selective, regenerable materials to support both pollutant degradation and resource recovery in sustainable treatment frameworks. (d) Standardization and real-world validation  
A major gap in the field remains the lack of standardized protocols for evaluating the photocatalytic performance. Variability in experimental conditions--such as light intensity, pollutant type, pH, and reactor configuration--frequently results in non-comparable outcomes across studies, limiting the reproducibility and hindering the benchmarking of photocatalysts [134]. To overcome these discrepancies, there is increasing consensus on the importance of long-term, pilot-scale testing under realistic environmental conditions, as well as the standardization of test matrices and performance metrics [131; 132]. Furthermore, techno-economic assessments and life cycle analyses (LCAs) are essential to evaluate the cost-effectiveness, environmental footprint, and energy demand of full-scale systems [133]. Benchmarking catalyst stability, reusability, and regeneration using internationally accepted standards is crucial for transitioning photocatalytic technologies from lab-scale success to real-world implementation [135]. For these reasons, to ensure transition from research to practice, it is essential to standardize testing protocols and validate performance in real water matrices. Future research should prioritize the following:  
* Long-term pilot-scale demonstrations under diverse environmental conditions. * Techno-economic analysis and life cycle assessment (LCA) to evaluate cost, environmental impact, and feasibility. * Benchmarking of catalyst stability, reusability, and regeneration using internationally accepted standards. Greater collaboration among academia, industry, and regulatory bodies will be critical to establishing safe and effective guidelines for implementation. Figure 17 offers a conceptual overview of the foundational elements required to transition photocatalytic technologies from experimental settings to practical use. It emphasizes the interconnected roles of performance validation, system-level evaluation, and collabora  
tive engagement in ensuring reliable, scalable, and accountable deployment in real water treatment scenarios. (e) Data-driven discovery and process optimization  
The application of artificial intelligence (AI), machine learning (ML), and computational modeling is poised to transform the design and deployment of photocatalytic systems. These tools can be used to achieve the following:  
* Accelerate the material discovery through predictive modeling. * Optimize the process parameters based on complex datasets. * Enable intelligent control systems for autonomous operation.