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Global mapping of disaggregated international trade-linked transportation CO2 emissions
Zhenyu Luo1, Yuhan Soo1, Zhaofeng Lv1
1State Key Laboratory of Regional Environment and Sustainability, School of Environment, Tsinghua University, Beijing 100084, China.
Abstract:
A comprehensive understanding of international trade-linked transportation CO2 emissions is essential for achieving net-zero emission goals. However, the current simplified representation of transportation patterns obscures the heterogeneity of these CO2 emissions in international trade and limits the development of targeted decarbonization policies. This study developed an integrated and highly detailed model that incorporated commodity-scale modal shares and shipping carbon intensities for each trade pair, assisted by machine learning and observed voyage signals, respectively. The results indicate that transportation modal shares vary considerably across different scales. In 2021, trade-linked transportation contributed 971 million tonnes of CO2 emissions globally. When attributing CO2 emissions to countries and commodities, the simplification of modal share can lead to substantial biases through carbon-intensity weighting. By shifting the focus from end-of-pipe emissions to upstream demand, this study identified a decarbonization potential of 41.6% through optimizing transportation distances. The findings offer valuable insights for designing targeted mitigation policies for international freight transportation.
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