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ORIGINAL RESEARCH article

Front. Public Health

Sec. Environmental Health and Exposome

Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1550395

Understanding the Environmental Health Implications of Tourism on Carbon Emissions in China

Provisionally accepted
  • 1 Anhui University of Science and Technology, Huainan, Anhui, China
  • 2 Hainan Tropical Ocean University, Sanya, China

The final, formatted version of the article will be published soon.

    Tourism development is important for the formulation of the national carbon reduction policy. China has put forward the goals of carbon peaking and carbon neutrality. Studying the impact of China's tourism industry on carbon emissions is of great significance in scientifically formulating emission reduction policies and helping China to realize its carbon reduction goals. In this study, we simulate the complex relationship between the tourism industry and carbon emissions in China using machine learning models. This study is the first to employ interpretable machine learning to analyze the impact of the tourism industry on carbon emissions in China. Our findings demonstrate that sparrow search algorithm and random forest (SSA-RF) hybrid model can model the relationship between carbon emissions and tourism factors with low error.The expansion of the tourism industry positively contributes to the increase in carbon emissions. Our study highlights the need to consider tourism factors when formulating national carbon reduction policy.

    Keywords: Tourism industry, carbon emission, machine learning, Decoupling index, Environmental Health

    Received: 23 Dec 2024; Accepted: 27 Feb 2025.

    Copyright: © 2025 Shao, Fang, Zhao, QIAN and Wang. 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:
    Sheng Fang, Anhui University of Science and Technology, Huainan, 232001, Anhui, China
    Meiling Zhao, Hainan Tropical Ocean University, Sanya, China

    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.

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