A united framework modeling of spatial-temporal characteristics for county-level agricultural carbon emission with an application to Hunan in China

Effectively tackling extreme climate change requires sound knowledge about carbon emissions and their driving forces. Currently, agricultural carbon emission assessment often deals with its inventory, efficiency, determinants, and response independently, which will leave out the complex interactions among its various components, thus there is a lack of comprehensive, scalable, comparable explanations for agricultural carbon emissions. Herein, we introduce an integrated agricultural carbon emission assessment framework (IEDR): Inventory (I) × Efficiency (E) × Determinants (D) × Response (R), which was then applied to an illustration for the county-level agricultural carbon emissions in Hunan Province, China. Results show that: (1) Agricultural carbon emission inventory (ACEI) increased from 20.06 × 10