Regional differences in the spatial and temporal characteristics and trend prediction of agricultural carbon emissions in Gansu Province

In this study, the regional differences of agricultural carbon intensity in five typical ecological areas (Minzu, Hexi, Longdong, Longzhong and Longnan) in Gansu Province were examined through Theil index analysis, which uses the R/S method to analyze the developmental trend of agricultural carbon emission intensity by combining it with grey theory forecast to predict the overall strength and value of agricultural carbon emissions in Gansu Province in 2020－2030. The results showed that agricultural carbon emissions initially increased and then decreased from 1991 to 2019 in the five regions of Gansu Province. The cities with low agricultural carbon emission intensity increased, while cities with high agricultural carbon emission intensity decreased. The total regional differences of agricultural carbon emission intensity showed a downward trend, with the intra-regional difference as the main influencing factor. The differences of agricultural carbon emission intensity in other regions were small with little fluctuations, except for ethnic regions. The agricultural carbon emission intensity of the five regions have strong fractal characteristics that will continue to decline in the future. After R/S analysis, the grey prediction of total agricultural carbon emission and its total intensity was carried out in Gansu Province. The average accuracy of the model is high, with a certain reference value. This study provides a theoretical basis for exploring the regional differences and future developmental trends of agricultural carbon emissions at different spatial scales in Gansu Province for the formulation of corresponding energy conservation and emission reduction measures.