Abstract
In an era where global focus intensifies on sustainable development, in this study, I investigate the interplay between rapid urbanization, rural logistics evolution, and carbon dynamics in China. We aim to bridge the gap in existing literature by examining the tripartite relationship between these areas and their collective impact on sustainable development. I explore the dynamic interaction mechanisms between urban construction, rural logistics development, and carbon emissions, assessing their joint influence on sustainable development. A detailed analysis of demand dynamics and market mechanisms supporting urbanization, rural logistics development, and carbon emissions has been initiated, leading to the establishment of a theoretical framework. This framework adeptly captures the interdependencies and constraints among these variables, offering a mathematical and bioscientific perspective to understand their complex interactions. Furthermore, a sophisticated nonlinear model based on key quantitative indicators like urbanization level, rural logistics development, and carbon emissions has been incorporated. Considering the multivariate nature, uncertainty, and dynamism presented by the nonlinear model, genetic algorithms have been employed for the estimation of model parameters. Through rigorous empirical testing using data from China spanning the years 1991-2021, I not only validate the effectiveness of the model but also accurately the interactions between urbanization processes, rural logistics progression, and carbon emissions. The findings demonstrate that urban construction significantly drives rural logistics development and uncover a pronounced nonlinear relationship among urbanization, rural logistics development (with a significant pull effect of 4.2), and carbon emissions growth. This research highlights the subtle balance between rural-urban development and environmental management, providing theoretical backing for the creation of sustainable policy frameworks in rural contexts and setting a foundation for future research in this domain.
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