SYSTEMATIC REVIEW article
Front. Oncol.
Sec. Thoracic Oncology
Mapping Three Decades of Air Pollution–Lung Cancer Research: Trends, Hotspots, and Networks (1990-2025)
Provisionally accepted
- 1First Hospital of Shanxi Medical University, Taiyuan, China
- 2Second College of Clinical Medicine Shanxi Medical University, Taiyuan, China
- 3Shanxi Medical University, Taiyuan, China
- 4Second Hospital of Shanxi Medical University, Taiyuan city, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Background: The relationship between air pollution and lung cancer has attracted considerable attention from researchers worldwide. To systematically assess the scholarly landscape and pinpoint research fronts, this study employs bibliometric analysis to delineate global trends, collaborative networks, and key publications within this field. Methods: Publications from 1990 to 2025 were extracted from Web of Science Core Collection and Scopus databases. Bibliometric tools including VOSViewer, Citespace, and Bibliometrix R were used to examine trends, key contributors, research themes, and prominent journals. Results: Among 4,238 publications, citation rates rose significantly. China produced the most publications, with leading institutions such as Harvard University and the Chinese Academy of Sciences. Key researchers included Lan Q, Rothman N, and Vermeulen R. Major journals were Environmental Health Perspectives and Atmospheric Environment. Frequently used keywords like "Lung Cancer" and "Particulate Matter" indicate core themes, while emerging terms such as "Covid-19" and "Machine Learning" reflect evolving interests. Conclusion: Fine particulate matter is an established environmental risk factor for lung cancer, and research on polycyclic aromatic hydrocarbons and asbestos remains active. The field has shifted from exposure assessment to mechanistic investigations focusing on oxidative stress, gene expression, and machine learning applications, defining key future research directions.
Keywords: Air Pollution, lung cancer, Risk factors, PM2.5, bibliometric analysis
Received: 03 Sep 2025; Accepted: 05 Dec 2025.
Copyright: © 2025 Fan, Wang, Zhai, Deng, Li, Niu, Zhao, Gao and Gao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiaoling Gao
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.