Understanding Transportation Carbon Emission Prediction: Methods, Trends, and Reflections

In the context of the global response to climate change, transportation has received increasing attention as an important source of carbon emissions. The prediction methods for transportation carbon emissions have continued to develop over the past decade, forming a variety of research paths. This paper reviews the primary research methods on transportation carbon emission prediction in the past decade. Based on the systematic sorting and analysis of the existing literature, this paper classifies the mainstream methods into three categories: traditional mathematical models, simulation methods represented by system dynamics, and intelligent models and their coupled models. This paper systematically summarizes the theoretical foundations, applicable scenarios, and technical characteristics of each type of method, points out the advantages and limitations of different methods. At the same time, this paper proposes that future modeling research can be directed toward model coupling, standardization of the construction process, and other development paths. By comparing the applicability of different prediction methods, the results of this paper can help scholars quickly identify and compare different methods for solving specific research problems.