Net Greenhouse Gas Emissions from Agriculture in China: Estimation, Spatial Correlation and Convergence

Haoyue Wu, Hanjiao Huang, Jin Tang, Wenkuan Chen and Yanqiu He
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Haoyue Wu: College of Management, Sichuan Agricultural University, Chengdu 611130, China
Hanjiao Huang: College of Forestry, Northwest A&F University, Xianyang 712100, China
Jin Tang: College of Management, Sichuan Agricultural University, Chengdu 611130, China
Wenkuan Chen: College of Management, Sichuan Agricultural University, Chengdu 611130, China
Yanqiu He: College of Management, Sichuan Agricultural University, Chengdu 611130, China

Sustainability, 2019, vol. 11, issue 18, 1-19

Abstract: The agricultural ecosystem has dual attributes of greenhouse gas (GHG) emission and absorption, which both influence the net amount of GHG. To have a clearer understanding of the net GHG effect, we linked up the emission and absorption of the agricultural ecosystem, estimated the net emissions of 30 provinces in China from 2007 to 2016, then explored the spatial correlation from global and local perspectives by Moran’s I, and finally tested the convergence of the net emissions by α convergence test, conditional β convergence test and spatial econometric methods. The results were: (1) The average of provincial agricultural net GHG emissions was around 4999.916 × 10 4 t, showing a fluctuating trend in the 10 years. Meanwhile, the gaps among provinces were gradually widening, as the provinces with high emissions were mainly agglomerated in the middle reaches of the Yangtze River, while those with less emissions mainly sat in the northwest. (2) The net emissions correlated spatially in close provinces. The agglomeration centers were located in the middle reaches of the Yangtze River and the northern coastal region, showing “high–high” and “low–low” agglomeration, respectively. (3) The net emissions did not achieve α convergence or conditional β convergence in the whole country, but the growth rate had a significant positive spillover effect among adjacent provinces, and two factors, the quantity of the labor force and the level of agricultural economy, had a negative impact on the rate. It is suggested that all provinces could strengthen regional cooperation to reduce agricultural net GHG emissions.

Keywords: net greenhouse gas emissions; agriculture; spatial correlation; Moran’s I; α convergence; conditional β convergence (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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