Akademik Veri Yönetim Sistemi
SUSTAINABLE DEVELOPMENT, 2026 (SSCI, Scopus)
This study examines the socioeconomic determinants of agricultural CO2 emissions in the 10 highest-emitting agricultural economies from 1992 to 2022. Using the LM bootstrap cointegration method and the method of moments quantile regression (MMQR), the analysis identifies long-run relationships and heterogeneous effects across the emissions distribution. The results indicate that agricultural energy use is the most significant driver of CO2 emissions, with its impact intensifying at higher quantiles, where environmental pressures are more severe. Agricultural value added also increases emissions, showing that productivity gains in these economies remain carbon-intensive. Additionally, agricultural trade openness and rural population size contribute positively to emissions, reflecting structural constraints in agricultural production systems. These findings directly relate to several Sustainable Development Goals (SDGs), particularly SDG 2 (zero hunger) through the need for resilient and low-carbon food systems, SDG 7 (affordable and clean energy) via the transition to renewable energy use in agriculture, SDG 12 (responsible consumption and production) through improved resource efficiency, and SDG 13 (climate action) by highlighting the urgency of reducing agricultural emissions. The quantile results indicate the need for stricter renewable energy mandates in high-emission groups, efficiency-focused technology support in middle groups, and targeted measures to ease trade and population-driven pressures in lower groups. The findings indicate that improving energy efficiency in agricultural production and implementing environmentally aligned trade regulations can deliver measurable reductions in sectoral carbon intensity, directly supporting SDG 13 while maintaining productivity gains consistent with SDG 2 objectives.