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Influencing factors and spatiotemporal heterogeneity of livestock greenhouse gas emission: Evidence from the Yellow River Basin of China

牲畜 温室气体 环境科学 中国 生命周期评估 城市化 自然资源经济学 农业经济学 地理 生态学 经济 生产(经济) 林业 经济增长 考古 生物 宏观经济学
作者
Xiao Zhang,Shuhui Sun,Shunbo Yao
出处
期刊:Journal of Environmental Management [Elsevier BV]
卷期号:358: 120788-120788 被引量:1
标识
DOI:10.1016/j.jenvman.2024.120788
摘要

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from ××carbon dioxide equivalent (CO2e) in 2000 to 77.568 Mt CO2e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively.
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