Study on the Spatial Structure and Drivers of Agricultural Carbon Emission Efficiency in Belt and Road Initiative Countries

被引:2
|
作者
Shu, Qin [1 ]
Su, Yang [1 ]
Li, Hong [1 ]
Li, Feng [2 ]
Zhao, Yunjie [3 ]
Du, Chen [4 ]
机构
[1] Xinjiang Agr Univ, Coll Econ & Management, Urumqi, Peoples R China
[2] Xinjiang Univ Finance & Econ, Coll Business Adm, Urumqi 830012, Peoples R China
[3] Xinjiang Agr Univ, Coll Comp & Informat Engn, Urumqi 830052, Peoples R China
[4] Xinjiang Inst Engn, Coll Informat Engn, Urumqi 830023, Peoples R China
基金
中国国家自然科学基金;
关键词
Belt and Road Initiative; agricultural carbon efficiency; climate change; sustainable development; social network analysis method; ENERGY; IMPACT;
D O I
10.3390/su151310720
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Agricultural carbon emissions are one of the major causes of global climate change. As some of the world's largest agricultural producers and consumers, countries along the route of the Belt and Road initiative produce significant agricultural carbon emissions. An in-depth study on the efficiency of agricultural carbon emissions in countries along the route can help countries reduce environmental load while improving agricultural production, optimizing resource use, improving agricultural production efficiency, and achieving sustainable development goals, which is significant for global climate change mitigation. Based on the relational data and network perspective, this paper takes the agricultural carbon emission efficiency of 34 countries along the route of the Belt and Road Initiative from 1995 to 2020 as the research object. It integrates the social network analysis method and other methods to realize the expansion of agricultural carbon emission efficiency in the research method. The study shows that (1) agricultural carbon emission efficiency has more room for improvement and presents complex spatially linked network characteristics; (2) the spatial correlation network of agricultural carbon emission efficiency is relatively well connected, and there is a general spatial correlation and spatial spillover effect among countries; and (3) similar differences in the proportion of primary industries and differences in informatization levels help establish spatial correlations between regions and produce spatial spillover effects. It is imperative to change global economic growth, social development, and lifestyles through green development. This study is conducive to the international community's formulation of differentiated agricultural carbon emission reduction support mechanisms for different countries to help the countries realize the transformation of agriculture and even overall economic development as soon as possible. At the same time, accelerating the pace of emission reduction and reducing the negative impact of agricultural carbon emissions are conducive to better responding to the challenges posed by global climate change.
引用
收藏
页数:27
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