Developing a quantitative analytical framework for carbon neutrality in tourism-dependent regions

Achieving carbon neutrality in tourism-dependent regions poses a critical challenge for global climate governance. However, existing studies lack frameworks to analyze the linkages between tourism and regional carbon neutrality. This study fills the gap by developing an interdisciplinary quantitative framework integrating Logarithmic Mean Divisia Index decomposition and system dynamics modeling. It systematically examines tourism-carbon neutrality interactions across industry, residents, land use, and Carbon Capture and Storage. Using Hainan Island (2010–2021) as a case study, the simulations reveal the following: (1) fluctuating growth in net emissions alongside declining carbon intensity; (2) the tertiary and secondary industries are the main emitters, with the former decarbonizing faster and the latter lagging behind in the green transition, while the primary industry is at a low level of both carbon emissions and carbon intensity; (3) residential emissions are driven by urbanization and living standards; (4) land-use carbon sinks decline slightly despite urban green expansion, due to construction land encroachment; (5) sensitivity analysis shows tourism growth in Hainan currently increases regional emissions but reduces carbon intensity. The novelty of this study lies in mapping dynamic relationships through a coupled approach and providing tools for destination-specific decarbonization strategies. Practical implications emphasize the need for integrated policies that balance tourism growth, industrial decarbonization, residential planning, and ecosystem restoration. By aligning economic objectives with climate resilience, this approach advances climate governance for policymakers in tourism-dependent regions.