4.6 Article

Spatial correlations and driving mechanisms of low-carbon agricultural development in china

Journal

FRONTIERS IN ENVIRONMENTAL SCIENCE
Volume 10, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fenvs.2022.1014652

Keywords

agriculture; low-carbon total factor productivity; spatially linked networks; social network analysis; super-efficiency ray slacks-based model

Funding

  1. National Social Science Foundation of China Research on intellectual property innovation mechanism of rural tourism cultural industry [19XJY018]
  2. Graduate Silk Road Research Innovation Project of Xinjiang University Regional Differences and Dynamic Evolution of Agricultural Green Total Factor Productivity [SL2022007]

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This paper explores the network characteristics and driving mechanisms of low-carbon synergistic development in agriculture in China. The study reveals that the spatially linked network of agricultural low-carbon total factor productivity exhibits multi-threaded characteristics, with the eastern regions at the core and the western regions at the periphery. The findings provide reference suggestions for the development of regionally differentiated agricultural low-carbon development plans.
Low-carbon agricultural development in China is a prerequisite for rural revitalization and a key to achieving socio-economic green transformation. This paper used agricultural data from 30 Chinese provinces from 2001 to 2020, considering both carbon emissions from farming and livestock, agricultural low-carbon total factor productivity (ALTFP) was measured using the RSBM-GML index. Based on this, the network characteristics and driving mechanisms of low-carbon synergistic development in agriculture were explored with the help of an improved gravity model and social network analysis, and the dominant provinces in low-carbon synergistic development in agriculture are identified. The study revealed that the spatially linked network of ALTFP in China exhibits multi-threaded characteristics of spillover to non-adjacent provinces, and the whole network has a sparse structure and hierarchy. The eastern regions such as Beijing, Tianjin, Shanghai, Jiangsu, and Zhejiang are at the core of the network, with closer ties to other regions and a stronger role in allocating resources. While the western regions such as Xinjiang, Qinghai, and Gansu are located at the periphery of the network, with weaker access to the resources. Meanwhile, the spatial proximity of provinces, the widening of differences in urbanization levels and differences in financial support for agriculture, and the narrowing of differences in the educational attainment of rural labor have significantly contributed to the formation of provincial spatial linkages. This study reveals that China's government needs to give full play to the role of core regions as leaders , and promote the balanced and coordinated regional development of low-carbon agriculture in China. In addition, policy makers should further optimize the spatial allocation of agricultural resource elements between provinces. The findings of the study provide reference suggestions for the development of regionally differentiated agricultural low-carbon development plans.

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