The carbon emissions from countries participating in the Belt and Road Initiative (BRI) account for over half of global emissions, yet the carbon footprint (CF) of cropping systems in these countries remains insufficiently studied. This study quantifies the life cycle carbon footprint (LCCF) of three major grain crops, maize, rice, and wheat, in BRI countries from 2006 to 2019, using a hybrid approach that integrates machine learning (ML) models and life cycle assessment (LCA). This work systematically quantified cradle-to-farm-gate CF, incorporating emissions from upstream inputs, transportation, and field operations. Emission factors (EF) and CF compositions for the three crops were assessed across different time periods. To evaluate the impact of BRI on crops’ CF, a novel Supply-Demand Balanced Carbon Footprint Tracing Model (SD-CTM) was developed to trace the sources and flows of upstream CF. Due to the expansion of cropland, changes in agricultural management practices (AMPs), and shifts in sources of upstream input, a gradual increase in crops’ CF was noted over time, with significant regional differences in EF and CF composition. Following the implementation of the BRI, internal upstream CF flows within BRI countries intensified, with key internal international upstream correlated carbon footprint (IUCCF) suppliers gaining greater dominance, while reliance on external suppliers weakened. The present study provides critical insights into the environmental impacts of agricultural production under the BRI framework, offering guidance for sustainable agricultural policies, carbon responsibilities allocation, and international low-carbon cooperation.

Click here for more content.