# Mapping three decades of air pollution–lung cancer research: trends, hotspots, and networks (1990-2025)

## TL;DR

This paper maps 35 years of research on air pollution and lung cancer, highlighting trends, key players, and emerging topics like machine learning and oxidative stress.

## Contribution

A comprehensive bibliometric analysis of air pollution–lung cancer research from 1990 to 2025, identifying evolving themes and future directions.

## Key findings

- China led in publications, with rising citation rates and key institutions like Harvard and the Chinese Academy of Sciences.
- Research shifted from exposure assessment to mechanistic studies on oxidative stress and gene expression.
- Emerging topics include machine learning and the impact of particulate matter and polycyclic aromatic hydrocarbons.

## Abstract

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.

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.

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.

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.