Method for analyzing influence factors of carbon emission in regional traffic transportation industry

By combining the LMDI factor decomposition model and the LASSO algorithm method, the influencing factors of carbon emissions in different regions are analyzed and identified, and the shortcomings of collinearity and regional differences analysis between factors in the existing technology are solved, and detailed analysis and differentiation exploration of the influencing factors of carbon emissions are realized, providing support for the formulation of low-carbon policies.

CN119721489APending Publication Date: 2025-03-28DALIAN UNIV OF TECH
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Patent Information

Application Number
CN202411897480.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-23
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

The prior art is difficult to effectively analyze and identify the factors influencing carbon emissions in transportation industries in different regions, especially in eliminating collinearity among factors and exploring inter-regional differences.

Method used

The LMDI factor decomposition model is used to combine the LASSO algorithm to analyze the impact of influencing factors on carbon emissions in the transportation industry from both static and dynamic aspects, eliminate the collinearity between factors, and screen out the key influencing factors for the differences between regions.

Benefits of technology

A detailed analysis of the factors affecting carbon emissions in the transportation industry in different regions has been achieved, the collinearity between factors has been eliminated, and the differences between regions have been explored, providing theoretical and data support for the formulation of targeted low-carbon transportation policies.

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Abstract

The invention belongs to the technical field of traffic carbon emission, particularly relates to a regional traffic transportation industry carbon emission influence factor analysis method, and provides a regional traffic transportation industry carbon emission influence factor analysis method based on LMDI and LASSO. The method comprises the following steps: firstly, acquiring related data to measure and calculate regional traffic transportation carbon emission, secondly, determining a carbon emission influence factor, constructing an LMDI traffic transportation industry carbon emission influence factor identical equation, then substituting the data into a decomposition model to calculate a static contribution value of each effect on the regional traffic transportation industry carbon emission, analyzing regional difference, and finally, calculating the carbon emission of the regional traffic transportation industry according to the static contribution value. And finally, exploring a dynamic action rule between the influence factors and carbon emission by using an LASSO algorithm, screening out key influence factors of different regions, and providing suggestions in combination with an analysis result.
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