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Carbon Emission Prediction of the Transportation Industry in Jiangsu Province Based on the WOA-SVM Model

Author

Listed:
  • Bing Zhang

    (College of Building Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Yiling Zong

    (College of Building Science and Engineering, Yangzhou University, Yangzhou 225127, China)

  • Fang Liu

    (College of Building Science and Engineering, Yangzhou University, Yangzhou 225127, China)

Abstract

The global environment has been facing sustainability threats recently owing to industrial and economic expansion. Hence, achieving the goals of carbon peak and carbon neutrality is crucial for promoting sustainable economic growth. To help the transportation industry achieve these goals, this study selects eight variables, including population size, per capita GDP, personal vehicle ownership, passenger and freight turnover, and green space coverage, as factors influencing the carbon emissions of the transportation industry in Jiangsu Province. This research uses these variables as the basis for predicting and analyzing transportation carbon emission trends from 2000 to 2021. In addition, the current study forecasts the future carbon emissions of the transportation industry and estimates the time of carbon emission peak in Jiangsu Province. To verify the accuracy of the results, this study compares the predicted results with those from other models. The whale optimization algorithm–support vector machine model is found to have the fewest errors among several models. On this basis, targeted measures are proposed to accelerate the carbon peak process and ensure the smooth achievement of carbon neutrality goals in Jiangsu Province. Results indicate that under the current policy measures, peak carbon emissions in Jiangsu Province will occur in 2038, with a peak of 48.72 million tons. Jiangsu Province should actively adopt energy-saving and emission-reduction measures, build a green and low-carbon transportation development model, and achieve the carbon peak target ahead of schedule. Findings from this study will provide valuable insights and practical recommendations for policy makers and stakeholders to formulate effective strategies for carbon reduction in the transportation sector, contributing to the sustainable development of China and the world.

Suggested Citation

  • Bing Zhang & Yiling Zong & Fang Liu, 2025. "Carbon Emission Prediction of the Transportation Industry in Jiangsu Province Based on the WOA-SVM Model," Sustainability, MDPI, vol. 17(10), pages 1-19, May.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:10:p:4612-:d:1658381
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