Literature DB >> 29946837

Coupling and decoupling effects of agricultural carbon emissions in China and their driving factors.

Haibin Han1, Zhangqi Zhong2, Yu Guo3, Feng Xi4, Shuangliang Liu4.   

Abstract

The relationship between agricultural carbon emissions and agricultural economic growth has attracted a significant research attention. A key issue to address in the development of agriculture is the reduction of agricultural carbon emissions while maintaining agricultural economic growth. This study investigated the interactions between agricultural carbon emissions and agricultural economic growth from multiple perspectives based on agricultural carbon emission data from 30 provinces in China measured from 1997 to 2015. Using this dataset, the coupling and decoupling effects of agricultural carbon emissions and the underlying driving factors were explored using a coupling development degree model, the Tapio decoupling assessment model, and a logarithmic mean Divisia index (LMDI) decomposition model. The results were as follows: (1) at the regional scale, the degree of coupling development between agricultural carbon emissions and agricultural economic growth is high in the central region of China and low in the western region. At the provincial scale, the coupling effects of agricultural carbon emissions exhibited four levels: minimal, low, moderate, and high coupling. (2) With the exceptions of Beijing, Zhejiang, Fujian, Guangdong, Inner Mongolia, and Shanghai, the relationships between agricultural carbon emissions and agricultural economic growth in the other 24 provinces were in a weak decoupling state. (3) The effects of agricultural development scale and agricultural technical progress were the major driving factors associated with increases and decreases in agricultural carbon emissions, respectively.

Entities:  

Keywords:  Agricultural carbon emissions; Coupling effect; Decoupling effect; LMDI decomposition model

Mesh:

Substances:

Year:  2018        PMID: 29946837     DOI: 10.1007/s11356-018-2589-7

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


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Journal:  PLoS One       Date:  2020-11-04       Impact factor: 3.240

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