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Evaluating the Spatiotemporal Characteristics of Agricultural Eco-Efficiency Alongside China’s Carbon Neutrality Targets

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  • Changming Cheng

    (College of Economics and Management, Nanjing Forestry University, Nanjing 210037, China
    School of Economics and Management, Chuzhou University, Chuzhou 239000, China)

  • Jieqiong Li

    (Science and Technology Department, Nanjing Forestry University, Nanjing 210037, China)

  • Yuqing Qiu

    (College of Economics and Management, Nanjing Forestry University, Nanjing 210037, China)

  • Chunfeng Gao

    (School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Qiang Gao

    (College of Economics and Management, Nanjing Forestry University, Nanjing 210037, China)

Abstract

Agriculture has the dual effect of contributing to both carbon emissions and sequestration, and thus plays a critical role in mitigating global climate change and achieving carbon neutrality. Agricultural eco-efficiency (AEE) is an important measurement through which we can assess the efforts toward reduced emissions and increased sequestration. The purpose of this study was to understand the relationship between China’s target of carbon neutrality and AEE through an evaluative model, so as to improve AEE and ultimately achieve sustainable agricultural development. The Super-SBM model scientifically measures the AEE based on provincial panel data collected between 2000 and 2020. We selected kernel density function and spatial distribution to explore the spatial and temporal evolutionary trends, and used a Tobit model to identify the drivers of AEE. The research shows that (1) China’s agricultural system functions as a net carbon sink, with all provinces’ agricultural carbon sequestration levels recorded as higher than their carbon emissions from 2000 to 2020. (2) Despite sequestration levels, the level of AEE in China is not high enough, and the average efficiency level from 2000 to 2020 is 0.7726, showing an overall trend where AEE decreased at first and then increased. (3) The AEE of each province is clearly polarized; there are obvious core–periphery characteristics and spatial distribution of clustered contiguous areas. Central provinces generally have lower efficiency, eastern and northeastern provinces have higher efficiency, and northeastern provinces always remain in the high-efficiency group. (4) Influencing factors show that urbanization, upgrading of industrial structure, financial support for agriculture, and mechanization have a significant positive impact on AEE. These findings have important implications for the promotion of the low-carbon green development of Chinese agriculture.

Suggested Citation

  • Changming Cheng & Jieqiong Li & Yuqing Qiu & Chunfeng Gao & Qiang Gao, 2022. "Evaluating the Spatiotemporal Characteristics of Agricultural Eco-Efficiency Alongside China’s Carbon Neutrality Targets," IJERPH, MDPI, vol. 19(23), pages 1-18, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15478-:d:980738
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    References listed on IDEAS

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    3. Jiang Zhu & Xiang Li & Huiming Huang & Xiangdong Yin & Jiangchun Yao & Tao Liu & Jiexuan Wu & Zhangcheng Chen, 2023. "Spatiotemporal Evolution of Carbon Emissions According to Major Function-Oriented Zones: A Case Study of Guangdong Province, China," IJERPH, MDPI, vol. 20(3), pages 1-20, January.
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    5. Yunfei Feng & Yi Zhang & Zhaodan Wu & Quanliang Ye & Xinchun Cao, 2023. "Evaluation of Agricultural Eco-Efficiency and Its Spatiotemporal Differentiation in China, Considering Green Water Consumption and Carbon Emissions Based on Undesired Dynamic SBM-DEA," Sustainability, MDPI, vol. 15(4), pages 1-26, February.

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