A Bibliometric Analysis of Research on Application of AI in Wastewater Treatment, 1987-2024

AI is now an essential driver of innovation and improvement of wastewater treatment systems due to its ability to use data-driven management for more sustainable operations, reduced energy use, and more effective monitoring of contaminant occurrence. In the last few decades, AI tools have shifted from a theoretical basis to principles of applied research in the world of environmental engineering. This study provides a bibliometric analysis of 2,096 journal articles published between 1987 and 2024 that were obtained from Scopus and Web of Science databases. The analysis used Bibliometrix R package versions examining the intellectual perspective, geographic perspective, and temporal of worldwide AI applications studies focusing on wastewater treatment. The analysis showed exponential growth after 2016 with a steady annual increase of 17.14% confirming rapid growth in this interdisciplinary topic area. China provided the most annual publication output; whereas, Spain provided the most cited articles indicating a varied sense of national priorities in achieving simultaneous publications while achieving impactful research. Saudi Arabian and Chinese universities displayed the most institutional membership. King Fahd University of Petroleum and minerals was the most productive institution in the overall publication dataset obtained. The thematic shift illustrated a move from more narrow model-specific research focused on “artificial neural networks” towards broader models based on more generalized conceptualizations of “machine learning” and “deep learning.” This shift illustrated an overall awareness of the expanding role of artificial intelligence in optimization and sustainability to research processes regarding waste treatment methods. As a whole, this research provides a data-driven perspective of how AI-related research has developed overtime as well as an overview of global collaboration networks and potential research directions for the future to promote a circular economy and sustainable water management.