Understanding the environmental health implications of tourism on carbon emissions in China.

Abstract

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.