Have Agricultural Land-Use Carbon Emissions in China Peaked? An Analysis Based on Decoupling Theory and Spatial EKC Model

Haoyue Wu, Bangwen Ding, Lu Liu, Lei Zhou, Yue Meng and Xiangjiang Zheng ()
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Haoyue Wu: School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Bangwen Ding: School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Lu Liu: School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Lei Zhou: School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Yue Meng: College of Business and Tourism, Sichuan Agricultural University, Chengdu 611830, China
Xiangjiang Zheng: School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China

Land, 2024, vol. 13, issue 5, 1-20

Abstract: Assessing the emission-peaking process of agricultural land use provides valuable insights for mitigating global warming. This study calculated agricultural land-use carbon emissions (ALUCEs) in China from 2000 to 2020 and explored the peaking process based on quantitative criteria. Further, we applied the Tapio decoupling index and environmental Kuznets curve (EKC) model to discuss the robustness of the peaking process. The main conclusions are as follows: (1) From 2000 to 2020, China’s average ALUCEs were 368.1 Mt C-eq (1349.7 CO 2 -eq), peaking at 396.9 Mt C-eq (1455.3 Mt CO 2 -eq) in 2015 before plateauing. Emissions from agricultural materials and soil management had entered the declining period, while those from rice cultivation were in the peaking period, those from straw burning were still rising, and those from livestock breeding remained at the plateauing phase. (2) The provinces of Beijing, Tianjin, and nine others saw a decline in ALUCEs, while Hainan, Guizhou, and another nine provinces observed plateauing, and Ningxia, Qinghai, and six other provinces experienced peaking. (3) Decoupling analysis confirmed that emission-peaking states remained stable even with agricultural growth. Instead of an inverted U-shaped relationship, we found an N-shaped relationship between ALUCEs and agricultural GDP. The spatial EKC model indicated that the peaking process had spillover effects between provinces. It is recommended that China accelerate ALUCE mitigation based on the source and phase of emissions, considering the peaking process and magnitude.

Keywords: agricultural land-use carbon emissions; greenhouse gas emissions; emission peak; Tapio decoupling index; environmental Kuznets curve; spatial Durbin model (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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