RESUMEN
Phosphorus in wastewater poses a significant environmental threat, leading to water pollution and eutrophication. However, it plays a crucial role in the water-energy-resource recovery-environment (WERE) nexus. Recovering Phosphorus from wastewater can close the phosphorus loop, supporting circular economy principles by reusing it as fertilizer or in industrial applications. Despite the recognized importance of phosphorus recovery, there is a lack of analysis of the cyber-physical framework concerning the WERE nexus. Advanced methods like automatic control, optimal process technologies, artificial intelligence (AI), and life cycle assessment (LCA) have emerged to enhance wastewater treatment plants (WWTPs) operations focusing on improving effluent quality, energy efficiency, resource recovery, and reducing greenhouse gas (GHG) emissions. Providing insights into implementing modeling and simulation platforms, control, and optimization systems for Phosphorus recovery in WERE (P-WERE) in WWTPs is extremely important in WWTPs. This review highlights the valuable applications of AI algorithms, such as machine learning, deep learning, and explainable AI, for predicting phosphorus (P) dynamics in WWTPs. It emphasizes the importance of using AI to analyze microbial communities and optimize WWTPs for different various objectives. Additionally, it discusses the benefits of integrating mechanistic and data-driven models into plant-wide frameworks, which can enhance GHG simulation and enable simultaneous nitrogen (N) and Phosphorus (P) removal. The review underscores the significance of prioritizing recovery actions to redirect Phosphorus from effluent to reusable products for future considerations.
Asunto(s)
Fósforo , Eliminación de Residuos Líquidos , Aguas Residuales , Fósforo/análisis , Aguas Residuales/química , Aguas Residuales/análisis , Eliminación de Residuos Líquidos/métodos , Inteligencia Artificial , Purificación del Agua/métodos , Contaminantes Químicos del Agua/análisis , Contaminantes Químicos del Agua/químicaRESUMEN
Algae cultivation and bioprocessing are important due to algae's potential to effectively tackle crucial environmental challenges like climate change, soil and water pollution, energy security, and food scarcity. To realize these benefits high algal biomass production and valuable compound extraction are necessary. Nanotechnology can significantly improve algal cultivation through enhanced nutrient uptake, catalysis, CO2 utilization, real-time monitoring, cost-effective harvesting, etc. Synthetic nanoparticles are extensively used due to ease of manufacturing and targeted application. Nonetheless, there is a growing interest in transitioning to environmentally friendly options like natural and 'green' nanoparticles which are produced from renewable/biological sources by using eco-friendly solvents. Presently, natural, and 'green' nanoparticles are predominantly utilized in algal harvesting, with limited application in other areas, the reasons for which remain unclear. This review aims to critically evaluate research on nanotechnology-based algae system enhancement, identify research gaps and propose solutions using natural and 'green' nanoparticles for a sustainable future.