Spatiotemporal Patterns and Influencing Factors of Agriculture Methane Emissions in China

Guofeng Wang, Pu Liu, Jinmiao Hu and Fan Zhang ()
Additional contact information
Guofeng Wang: Faculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China
Pu Liu: Faculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China
Jinmiao Hu: Faculty of International Trade, Shanxi University of Finance and Economics, Taiyuan 030006, China
Fan Zhang: Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Agriculture, 2022, vol. 12, issue 10, 1-17

Abstract: Explaining the methane emission pattern of Chinese agriculture and the influencing factors of its spatiotemporal differentiation is of great theoretical and practical significance for carbon neutrality. This paper uses the IPCC coefficient method to measure and analyze the spatial and temporal differentiation characteristics of agricultural methane emission, clarify the dynamic evolution trend of the kernel density function, and reveal the key influencing factors of agricultural methane emission with geographical detectors. The results show that China’s agricultural methane emissions showed a first increasing and then declining trend. Agricultural methane emissions decreased from 21.4587 million tons to 17.6864 million tons, with an upward trend from 2000 to 2005, a significant decline in 2006, a slow change from 2007 to 2015, and a significant decline from 2015 to 2019. In addition, the emissions pattern of the three major grain functional areas is characteristic; in 2019, agricultural methane emissions from main producing area, main sales area, and balance area were 10.8406 million tons, 1.2471 million tons, and 5.599 million tons, respectively. The main grain producing area is the main area of methane emissions, and the emission pattern will not change in the short term. The variability of grain functional areas is the decisive factor for the difference in agricultural methane emissions. The state of industrial structure is the key influencing factor for adjusting the spatial distribution—the explanatory power of the industrial structure to the main producing areas reached 0.549; the level of agricultural development is the most core influencing factor of the spatial pattern of the main grain sales area—the explanatory power reached 0.292; and the level of industrialization and the industrial structure are the core influencing factors of the spatial pattern of the balance area—the explanatory power reached 0.545 and 0.479, respectively.

Keywords: agriculture; methane emission; spatiotemporal pattern; kernel density; influencing factors (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2077-0472/12/10/1573/pdf (application/pdf)
https://www.mdpi.com/2077-0472/12/10/1573/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:12:y:2022:i:10:p:1573-:d:928910

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().