Spatial dynamics of agricultural carbon emissions in China and the related driving factors

The reduction of carbon emission in agricultural lands is not only important in sustainable agriculture, but also inevitable for China to achieve an overall emission reduction targets and carbon emission control. It is also of great significance to conduct research into the spatial distribution and the driving factors of carbon emissions in agricultural lands in China. Studies that have focused on regional distributions of carbon emissions in agricultural lands adopted different measurement methods and used inconsistent driving indicators, therefore had reached different conclusions in different researches. Moreover, in order to compensate for the deficiency with static analysis methods in dealing with dynamic effects, we combined dynamic grey correlation method with regression model. It not only analyzed the non-linear impacts of carbon emission in agricultural lands and the influencing factors, but also analyzed the dynamic impacts of carbon emission in agricultural lands and the influencing factors. Based on the preceding researches, our study started by analyzing the spatial distribution of carbon emissions in agricultural lands in China, including total amount of carbon emission, carbon emission intensity, carbon emission structure and carbon emission level in agricultural lands. It then discussed in detail the causes of the spatial patterns of inter-provincial carbon emissions in agricultural lands and quantitative relationship between the influencing factors and spatial distribution. The study was a critical source of reference on zonal carbon emission reduction that could be useful in formulating carbon emission policies in China. The main conclusions of this paper were as follows:inter-provincial differences in carbon emission intensities in agricultural lands had increased with time. There was no significant reduction in structural differences in carbon emission among provinces or cities. The polarization of carbon emission level in agricultural lands was ever more severe. The level of carbon emissions in agricultural lands fell in the central region, but increased in the west. In contrast, farmland utilization and mechanization of agricultural production were more important factors driving carbon emission in agricultural lands. Some achievements were made in reducing ruminant emissions, with a widening gap among provinces or cities due to differences in agro-economic level, agricultural mechanization, agricultural structure and agro-human capital. The differences in inter-provincial carbon emissions of agricultural lands increased. Agriculture and animal husbandry, farmland utilization and mechanization of agricultural production technology were the leading factors driving the improvement in carbon emission in agricultural lands in most of the provinces and cities with more attention on agricultural development. In these regions, the development of superior industries, ruminant feeding and agricultural production techniques (human capital) were the dominant factors reducing carbon emissions. Finally, we forwarded three recommendations:First, there was need to focus on long-term carbon emission reduction in farmlands. Specifically, major grain-producing areas were to strengthen innovation of emission reduction technology and push forward with progress in emission reduction projects. Second, there was need for further attention on promoting technology of emission reduction in feeding ruminants and in exploring agricultural development models that combined farming with breeding, especially in pastoral areas. Third, there was need to fully exert the role of agro-economic structure in reducing carbon emission. The eastern, central and western regions were to adjust industrial structure in accordance with the level of development.