| dc.description.abstract | The spatial characteristics of carbon emissions form the basis for exploring carbon neutrality measures for
different regions. As the second largest carbon emission source globally, agricultural carbon emissions should not
be ignored. This paper used panel data from 2009 to 2019 to calculate the agricultural carbon emissions of 30
provinces in China, and used the ML index, spatial Morans’I index and three convergence indices to analyze the
dynamic changes and spatial pattern of China’s agricultural carbon emission performance (ACEP). The results
showed that: (i), China’s ACEP has increased by 1.5% from 2009 to 2019, following a spatial pattern of eastern
(1.041) > western (1.020) > central (0.974);(ii) the contribution of technological progress to China’s ACEP was
1.035, exceeding 1, and thus indicating that technological progress can improve ACEP, while the contribution of
efficiency changes was only 0.991; (iii) China’s ACEP has exhibited a spatial aggregation effect over the last 10
years (P < 0.05), but the value of Moran’s I index dropped from 0.265 in 2009 to 0.202 in 2019, which indicates
that the spatial aggregation of ACEP is weakening; and (iv) the ML index for 30 provinces in China showed σ
convergence, which indicates that the ACEP is improving, while there is absolute β convergence and conditional
β convergence, which indicates a “catch-up effect” among regions. The results indicate that China’s ACEP is
likely to increase further in terms of spatial scope and temporal trends. | en_US |
