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How China’s Global Trade Expansion Shapes Transport-Sector CO 2 Emissions: An Export-Driven Analytical Perspective

Author

Listed:
  • Sadig Gachayev

    (School of Humanities and Law (School of Public Administration), Yanshan University, Qinhuangdao 066004, China)

  • Bangfan Liu

    (School of Humanities and Law (School of Public Administration), Yanshan University, Qinhuangdao 066004, China)

  • Ramil I. Hasanov

    (Department of Business and Management, Mingachevir State University, Mingachevir AZ4500, Azerbaijan
    UNEC Research Center on Global Environmental Issues, Azerbaijan State University of Economics (UNEC), Baku AZ1001, Azerbaijan)

  • Dragan Gligoric

    (Faculty of Economics, University of Banja Luka, 78000 Banja Luka, Bosnia and Herzegovina)

  • Sinisa Rajkovic

    (Association of Accountants and Auditors of Republic of Srpska, 78000 Banja Luka, Bosnia and Herzegovina)

  • Veljko Dmitrovic

    (Faculty of Organizational Sciences, Department of Financial Management and Accounting, University of Belgrade, Jove Ilica Street N. 154, 11000 Belgrade, Serbia)

  • Dejan Mikerevic

    (Faculty of Economics, University of Banja Luka, 78000 Banja Luka, Bosnia and Herzegovina)

Abstract

China’s export-oriented economic expansion has substantially influenced transport-sector CO 2 emissions, raising critical concerns about the environmental impacts of sustained industrial growth and global trade integration. Understanding the interplay between macroeconomic dynamics, trade composition, and industrial structure is essential for aligning economic development with climate mitigation objectives. This study examines transport-related CO 2 emissions in China over the period 1990–2023, employing a hybrid methodological framework that combines econometric modeling—including Autoregressive Distributed Lag (ARDL) bounds testing, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS)—with machine-learning techniques using Extreme Gradient Boosting (XGBoost) interpreted through SHapley Additive exPlanations (SHAP). The analysis confirms a long-run cointegration relationship between transport emissions and the selected macroeconomic variables. Short-run dynamics indicate a strong sensitivity of emissions to GDP growth, while long-run estimates reveal that higher export-to-GDP ratios and industrial value added contribute to reducing transport emissions, reflecting the efficiency gains from industrial upgrading and cleaner trade practices. By contrast, the expansion of medium- and high-technology exports increases emissions due to the energy- and logistics-intensive nature of high-value goods. The XGBoost model achieves high predictive performance, with an out-of-sample R 2 of 0.9975 and a Root Mean Square Error (RMSE) of 87.16, confirming the dominant contribution of medium- and high-technology exports to transport-sector emissions. The results underscore the critical role of aligning trade structure, industrial productivity, and low-carbon logistics within China’s policy agenda. Implementing strategies that enhance industrial energy efficiency and develop sustainable transport infrastructure can substantially reduce the environmental impacts associated with export-driven economic expansion.

Suggested Citation

  • Sadig Gachayev & Bangfan Liu & Ramil I. Hasanov & Dragan Gligoric & Sinisa Rajkovic & Veljko Dmitrovic & Dejan Mikerevic, 2026. "How China’s Global Trade Expansion Shapes Transport-Sector CO 2 Emissions: An Export-Driven Analytical Perspective," Sustainability, MDPI, vol. 18(5), pages 1-22, February.
  • Handle: RePEc:gam:jsusta:v:18:y:2026:i:5:p:2192-:d:1870819
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