Spatio-Temporal Dynamics, Driving Mechanisms, and Decoupling Evaluation of Farmland Carbon Emissions: A Case Study of Shandong Province, China

Tao Sun, Ran Li, Zichao Zhao, Bing Guo, Meng Ma, Li Yao and Xinhao Gao ()
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Tao Sun: State Key Laboratory of Nutrient Use and Management, Key Laboratory of Wastes Matrix Utilization, Ministry of Agriculture and Rural Affair, Institute of Agricultural Resources and Environment, Shandong Academy of Agricultural Sciences, Jinan 250100, China
Ran Li: State Key Laboratory of Nutrient Use and Management, Key Laboratory of Wastes Matrix Utilization, Ministry of Agriculture and Rural Affair, Institute of Agricultural Resources and Environment, Shandong Academy of Agricultural Sciences, Jinan 250100, China
Zichao Zhao: State Key Laboratory of Nutrient Use and Management, Key Laboratory of Wastes Matrix Utilization, Ministry of Agriculture and Rural Affair, Institute of Agricultural Resources and Environment, Shandong Academy of Agricultural Sciences, Jinan 250100, China
Bing Guo: State Key Laboratory of Nutrient Use and Management, Key Laboratory of Wastes Matrix Utilization, Ministry of Agriculture and Rural Affair, Institute of Agricultural Resources and Environment, Shandong Academy of Agricultural Sciences, Jinan 250100, China
Meng Ma: State Key Laboratory of Nutrient Use and Management, Key Laboratory of Wastes Matrix Utilization, Ministry of Agriculture and Rural Affair, Institute of Agricultural Resources and Environment, Shandong Academy of Agricultural Sciences, Jinan 250100, China
Li Yao: State Key Laboratory of Nutrient Use and Management, Key Laboratory of Wastes Matrix Utilization, Ministry of Agriculture and Rural Affair, Institute of Agricultural Resources and Environment, Shandong Academy of Agricultural Sciences, Jinan 250100, China
Xinhao Gao: State Key Laboratory of Nutrient Use and Management, Key Laboratory of Wastes Matrix Utilization, Ministry of Agriculture and Rural Affair, Institute of Agricultural Resources and Environment, Shandong Academy of Agricultural Sciences, Jinan 250100, China

Sustainability, 2025, vol. 17, issue 15, 1-17

Abstract: Understanding the spatio-temporal evolution of farmland carbon emissions, disentangling their underlying driving forces, and exploring the decoupling relationship between these emissions and economic development are pivotal to advancing low-carbon and high-quality agricultural development in Shandong Province, China. Using the Logarithmic Mean Divisia Index (LMDI) and Tapio decoupling model, this study conducted a comprehensive analysis of panel data from 16 cities in Shandong Province spanning 2004–2023. This research reveals that the total farmland carbon emissions in Shandong Province followed a trajectory of “initial fluctuating increase and subsequent steady decline” during the study period. The emissions peaked at 29.4 million tons in 2007 and then declined to 20.2 million tons in 2023, representing a 26.0% reduction compared to the 2004 level. Farmland carbon emission intensity in Shandong Province showed an overall downward trend over the period 2004–2023, with the 2023 intensity registering a 68.9% decline compared to 2004. The carbon emission intensity, agricultural structure, and labor effects acted as inhibiting factors on farmland carbon emissions in Shandong Province, while the economic development effect exerted a positive driving impact on the growth of such emissions. Over the 20-year period, these four factors cumulatively contributed to a reduction of 2.1 × 10 5 tons in farmland carbon emissions. During 2004–2013, the farmland carbon emissions in Zaozhuang, Yantai, Jining, Linyi, Dezhou, Liaocheng, and Heze showed a weak decoupling state, while in 2014–2023, the farmland carbon emissions and economic development in all cities of Shandong Province showed a strong decoupling state. In the future, it is feasible to reduce farmland carbon emissions in Shandong Province by improving agricultural resource utilization efficiency through technological progress, adopting advanced low-carbon technologies, and promoting the transformation of agricultural industrial structures towards “high-value and low-carbon” designs.

Keywords: farmland carbon emission; LMDI model; driving factors; Tapio decoupling model; carbon emission reduction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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