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新疆生产建设兵团农牧业温室气体排放的脱钩与驱动效应分析
引用本文:楚天舒,赖世宣,黄译萱,马红红,吴湘琳,蒲胜海,李晓红. 新疆生产建设兵团农牧业温室气体排放的脱钩与驱动效应分析[J]. 中国农业大学学报, 2023, 28(10): 216-228
作者姓名:楚天舒  赖世宣  黄译萱  马红红  吴湘琳  蒲胜海  李晓红
作者单位:中国农业大学 资源与环境学院, 北京 100193; 新疆农业科学院土壤肥料与农业节水研究所/农业农村部西北绿洲农业环境重点实验室, 乌鲁木齐 830091;中国农业大学 工学院, 北京 100083;中国农业大学 经济管理学院, 北京 100083
基金项目:农业农村部西北绿洲农业环境重点实验室开放基金(XBLZ-20225)
摘    要:为系统性探究区域农牧业温室气体排放特征及驱动因素,以新疆生产建设兵团农牧业生产系统为研究对象,核算农牧业温室气体净排放量,采用Tapio脱钩分析法评估温室气体净排放量与产值、产量的关联程度,运用LMDI分解法解析温室气体净排放量的驱动因素。结果表明:1)2011—2020年新疆生产建设兵团农业和畜牧业温室气体净排放量均呈现“增长—平稳波动”趋势,至2020年农业和畜牧业温室气体净排放量分别为1.02×1010 kg和1.34×109 kg(以CO2计)。2)农牧业温室气体净排放量与产值处于脱钩状态,而与产量逐渐脱钩。3)生产机械化水平、水利现代化水平对农业温室气体净排放量的效应值为-14.87×106、58.25×108 hm2,分别起抑制作用和促进作用。畜禽良种化水平对畜牧业温室气体净排放量的效应值为-4.55×106,起抑制作用;生产机械化水平对畜牧业温室气体净排放量从促进作用转向抑制作用。本研究成果可为新疆生产建设兵团农牧业绿色低碳发展提供参考资料。

关 键 词:农牧业温室气体排放;LMDI分解法;脱钩分析
收稿时间:2023-02-13

Decoupling and driving effects analysis of greenhouse gas emissions from agriculture and animal husbandry in Xinjiang Production and Construction Corps
CHU Tianshu,LAI Shixuan,HUANG Yixuan,MA Honghong,WU Xianglin,PU Shenghai,LI Xiaohong. Decoupling and driving effects analysis of greenhouse gas emissions from agriculture and animal husbandry in Xinjiang Production and Construction Corps[J]. Journal of China Agricultural University, 2023, 28(10): 216-228
Authors:CHU Tianshu  LAI Shixuan  HUANG Yixuan  MA Honghong  WU Xianglin  PU Shenghai  LI Xiaohong
Affiliation:College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China; Research Institute of Soil, Fertilizer and Agricultural Water Conversation, Xinjiang Academy of Agricultural Sciences/Key Laboratory of Agro-Environment in Northwest Oasis, Ministry of Agriculture and Rural Affairs, Urumqi 830091, China;College of Engineering, China Agricultural University, Beijing 100083, China; College of Economics and Management, China Agricultural University, Beijing 100083, China
Abstract:This study aimed to systematically explore the characteristics, correlations, and driving factors of the greenhouse gas emissions from regional agricultural and animal husbandry. The agriculture and animal husbandry production system in Xinjiang Production and Construction Corps was chosen as the research object. The net GHG emissions of agriculture and animal husbandry were calculated according to IPCC technical guidelines. The decoupling status between net GHG emissions and output value, output was evaluated by using the Tapio decoupling model. The driving effects of production mechanization, water conservancy modernization and breed improvement were analyzed by using the LMDI decomposition method. The results showed that: 1)From 2011 to 2020, the net GHG emissions from agriculture and animal husbandry displayed a growth-stable fluctuation trend. The net GHG emissions from agriculture and animal husbandry in 2020 were 1. 02×1010 kg and 1. 34×109 kg(in terms of carbon dioxide), respectively. 2)The correlation between net GHG emissions and output value was mainly in weak decoupling and strong decoupling status. The net GHG emissions from agriculture and animal husbandry were gradually decoupled with the output. 3)From 2011 to 2020, The driving effect values of production mechanization level and water conservancy modernization level were -14. 87×106 and 58. 25×108 hm2. It meant that water conservancy modernization level played a role in promoting the net GHG emissions from agriculture, while water conservancy played a restraining role. The driving effect values of breed improvement level were -4. 55×106, which were inhibitory effects on the net GHG emissions from animal husbandry. Therefore, it was necessary to apply organic and inorganic fertilizers scientifically to save energy and reduce consumption in farmland irrigation, promote the high-quality development of animal husbandry mechanization, and optimize the supply of forage. This study provided reference materials for green and low-carbon development in Xinjiang Production and Construction Corps.
Keywords:greenhouse gas emission in agriculture and animal husbandry   LMDI decomposition method   decoupling analysis
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