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China’s CO 2 Emissions: A Thorough Analysis of Spatiotemporal Characteristics and Sustainable Policy from the Agricultural Land-Use Perspective during 1995–2020

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  • Shuting Liu

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Graduate School, Jiangxi Normal University, Nanchang 330022, China)

  • Junsong Jia

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

  • Hanzhi Huang

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Graduate School, Jiangxi Normal University, Nanchang 330022, China)

  • Dilan Chen

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
    Graduate School, Jiangxi Normal University, Nanchang 330022, China)

  • Yexi Zhong

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

  • Yangming Zhou

    (Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China)

Abstract

Agricultural land use is an important source of CO 2 emissions. Therefore, taking the CO 2 emissions of China’s agricultural land use during 1995–2020 as a case, we firstly calculated its composition and analyzed the spatiotemporal evolution characteristics. Then, the Tapio decoupling model and logarithmic mean Divisia index (LMDI) were, respectively, used to identify the decoupling relationship between the CO 2 emission change and economic growth, and analyze the driving factors for CO 2 emissions. (1) The CO 2 emissions of China’s agricultural land use were composed of two main phases (fluctuating growth phase (1995–2015) and rapid decline phase (2016–2020)). The total CO 2 emissions exhibited a non-equilibrium spatial distribution. The inter-provincial CO 2 emissions differences first expanded and then shrank, but the inter-provincial differences of CO 2 emissions intensity continuously decreased. (2) The total CO 2 emissions of China’s agricultural land use increased from 50.443 Mt in 1995 to 79.187 Mt in 2020, with an average annual growth rate of 1.82%. Fertilizer, agricultural diesel and agricultural (plastic) film were the main sources of anthropogenic agricultural-land-use CO 2 emissions. Controlling the use of fertilizer and agricultural diesel and improving the utilization efficiency of agricultural (plastic) film could be an effective way to reduce CO 2 emissions. (3) The Tapio decoupling relationship between the CO 2 emission change and economic growth was a weak decoupling state during 1995–2015 and a strong decoupling state during 2016–2020. This result indicates that China’s agricultural land use can be effectively controlled. (4) The agricultural economic level is the decisive factor in promoting CO 2 emissions increase, and its cumulative contribution was 476.09%. Inversely, the CO 2 emission intensity, agricultural structure and agricultural labor force were three key factors, with cumulative contributions of −189.51%, −16.86% and −169.72%, respectively. Collectively, based on the findings obtained from the present research, we have proposed some suggestions to promote the sustainable use of agriculture lands in China.

Suggested Citation

  • Shuting Liu & Junsong Jia & Hanzhi Huang & Dilan Chen & Yexi Zhong & Yangming Zhou, 2023. "China’s CO 2 Emissions: A Thorough Analysis of Spatiotemporal Characteristics and Sustainable Policy from the Agricultural Land-Use Perspective during 1995–2020," Land, MDPI, vol. 12(6), pages 1-20, June.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:6:p:1220-:d:1169382
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