This study examines the drivers and long-run dynamics of agricultural greenhouse gas (GHG) emissions in Nigeria using annual time-series data from 1990 to 2021. The analysis integrates three complementary approaches: Logarithmic Mean Divisia Index (LMDI) decomposition, Tapio decoupling elasticity analysis, and an Autoregressive Distributed Lag (ARDL)-based Environmental Kuznets Curve (EKC) regression. The LMDI results show that population growth and agricultural emission intensity emerged as the co-dominant positive drivers of emissions, while agricultural energy intensity provided the only substantial mitigating effect. Tapio decoupling analysis identifies weak decoupling as the dominant state; however, the frequency of expansive negative decoupling episodes increased markedly after 2005, signalling a deteriorating emission–growth relationship. The ARDL bounds test supports a stable long-run cointegrating relationship, and the long-run coefficients are consistent with a U-shaped income–emission relationship. Taken together, the results indicate that scale effects currently outpace efficiency gains, suggesting that continued income growth may not translate into lower emission intensity without structural intervention. The decomposition evidence highlights biological intensification as a priority policy target. These findings carry direct implications for Nigeria’s Nationally Determined Contribution (NDC) commitments and for the broader challenge of achieving development while decarbonising agricultural systems in Sub-Saharan Africa.
Taiwo et al. (Wed,) studied this question.