Impact of Pollution on Mental Health: A Systematic Review of Associations, Methodological Challenges, and Future Directions

Background and Aim: Environmental pollutants, including contaminated air, harmful chemicals, and excessive noise, are increasingly prevalent in modern society. These contaminants can significantly affect mental well‐being, a fundamental determinant of cognitive functioning, emotional regulation, interpersonal relationships, life satisfaction, and overall physical health. Methods: This systematic review examines the effects of various types of pollution, such as air pollution, noise pollution, and chemical contaminants, as well as their interactions, on mental health outcomes across diverse populations. Results: Our search identified 61 high‐quality studies that met our inclusion criteria. Among quantitative studies, 81% (n = 49) reported a significant association between pollution and mental health outcomes. Air pollution was the most frequently studied factor, with 50% confirming an association. In contrast, chemical pollution showed the lowest positive associations, with only 10% reporting an association. Our analysis reveals critical limitations in current research, particularly regarding data availability and quality, with most mental health data sets being limited in temporal scope and geographical coverage. While we discuss Artificial Intelligence as a prospective methodological framework to improve the precision and efficiency of future studies, we emphasize that its effective implementation fundamentally depends on addressing underlying data limitations. Specifically, spatiotemporal models can address exposure misclassification, attention mechanisms can handle confounding complexity, and deep learning can manage temporal variability, but all require systematic improvements in data collection infrastructure. Conclusion: This review highlights the urgent need for standardized mental health monitoring systems, interdisciplinary collaboration, and the development of comprehensive data collection frameworks as essential prerequisites for leveraging advanced analytical methods in understanding pollution–mental health relationships.