关键词: 农业碳排放, Tapio脱钩, LMDI模型, 濮阳市

Abstract:

Based on time−series data from the Puyang Statistical Yearbook, this study employed the carbon emission coefficient method to estimate agricultural carbon emissions in Puyang city over the past 13 years (2009−2021). The Tapio decoupling model was applied to analyze the decoupling relationship between agricultural carbon emissions and economic growth, while the LMDI decomposition method was used to identify key driving factors, providing theoretical references for the development of green and low−carbon agriculture. The results showed that agricultural carbon emissions exhibited a fluctuating trend of "increase−decrease−increase−decrease," with an annual average of 33.55×10⁴t. Emissions peaked in 2018 (43.70×10⁴t) and declined to 30.23×10⁴t by 2021 (a 30.82% reduction from 2018). Carbon emission intensity showed a consistent downward trend from 2009 to 2016 followed by a temporary rebound during the 2017−2018 period. Subsequently, it continued to decline from 2018 to 2021, reaching the study−period minimum of 0.1078t·10⁻⁴yuan in 2021, reflecting significant progress in Puyang's agricultural low−carbon transformation. The emission structure was dominated by chemical fertilizers (73.51%), followed by agricultural plastic films (11.35%), diesel (5.88%) and pesticides (5.78%) and so on. The decoupling relationship evolved in stages: weak decoupling dominated in 2010−2014, followed by strong decoupling (2015–2016), negative decoupling (2017−2018) and a return to strong decoupling (2019−2021). LMDI decomposition revealed that agricultural production efficiency (33.78%), regional industrial structure (10.02%) and labor scale (3.15%) were the primary drivers of emission reduction, whereas regional economic growth (44.69%), urbanization (7.02%) and agricultural structure (1.34%) contributed to emission increases. Based on the research findings, it is recommended to promote low−carbon and high−quality agricultural development in Puyang city through technological innovation, structural optimization and enhancing the low−carbon production capacity of farmers.

Key words: Agricultural carbon emissions, Tapio decoupling, LMDI model, Puyang city