张建杰, 原韶雨, 何宁波, 韩诗卉. 山西省农牧生产体系温室气体排放特征与影响因素[J]. 中国生态农业学报 (中英文), 2024, 32(7): 1148−1158. DOI: 10.12357/cjea.20240144
引用本文: 张建杰, 原韶雨, 何宁波, 韩诗卉. 山西省农牧生产体系温室气体排放特征与影响因素[J]. 中国生态农业学报 (中英文), 2024, 32(7): 1148−1158. DOI: 10.12357/cjea.20240144
ZHANG J J, YUAN S Y, HE N B, HAN S H. Greenhouse gas emission characteristics and influencing factors of the crop and livestock production systems, Shanxi Province[J]. Chinese Journal of Eco-Agriculture, 2024, 32(7): 1148−1158. DOI: 10.12357/cjea.20240144
Citation: ZHANG J J, YUAN S Y, HE N B, HAN S H. Greenhouse gas emission characteristics and influencing factors of the crop and livestock production systems, Shanxi Province[J]. Chinese Journal of Eco-Agriculture, 2024, 32(7): 1148−1158. DOI: 10.12357/cjea.20240144

山西省农牧生产体系温室气体排放特征与影响因素

Greenhouse gas emission characteristics and influencing factors of the crop and livestock production systems, Shanxi Province

  • 摘要: 分析山西省农牧生产体系碳排放时空分布特征, 并明确其主要影响因素, 是促进山西实现农牧业绿色发展的关键, 也是山西发展有机旱作农业的重要依据。本研究收集了山西省1985年与2018年县域尺度农牧业生产数据, 使用生命周期评价方法(LCA)结合最新温室气体清单指南, 编制了山西农牧生产体系温室气体(GHG)排放清单; 结合GIS手段, 刻画了县域尺度农牧生产体系GHG排放的时空分布特征; 分别研究了基于单位耕地面积与生产单位农产品能量的GHG排放强度, 识别了GHG排放的热点区域; 并进一步基于随机森林定量了不同年份GHG排放强度的主要影响因素。结果表明: 1985—2018年间, 山西省农牧生产体系GHG排放总量从1742.47万t(CO2 eq)增加至2075.29万t(CO2 eq), 增幅达19.10%; 不同年份种植业生产农业投入品均为整个农牧体系GHG排放的主要贡献者, 占41.08%~54.23%; 秸秆焚烧产生的GHG从1985年的443.56万t(CO2 eq)降低至2018年的321.13万t(CO2 eq), 占比由25.46%降低至15.47%, 是整个农牧体系第二大GHG排放源; 从土壤排放的GHG由151.17万t(CO2 eq)增加至231.97万t(CO2 eq), 占比也由8.68%增至11.18%; 畜牧业生产体系动物肠道发酵与粪尿管理环节产生的GHG排放增加了2.30倍, 由202.75万t(CO2 eq)快速增加至668.92万t(CO2 eq), GHG排放占比也由原来的11.64%增加至32.23%。整个农牧业单位耕地面积GHG排放强度由4.63 t(CO2 eq)·hm−2增加至5.12 t(CO2 eq)·hm−2, 但生产单位农产品能量的GHG排放强度大幅下降, 由0.15 kg(CO2 eq)·MJ−1降低至0.08 kg(CO2 eq)·MJ−1。随机森林分析结果表明, 氮肥施用与种植结构是影响GHG排放强度与效率的主要影响因素, 但不同年份之间的影响因素存在差异。氮肥的优化管理、作物结构与畜牧业管理的改善对于GHG排放至关重要。本研究为理解与改善农牧业绿色发展提供了有价值的参考。

     

    Abstract: Analysis of the spatial and temporal distribution characteristics of carbon emissions in the crop and livestock production systems in Shanxi Province, and clarifying the main factors influencing these systems are key to promoting the green development of crop and livestock production systems in Shanxi Province, and this provide a foundation for the development of organic dry farming in Shanxi Province. Herein, we collected crop and livestock production data at county level in Shanxi Province in 1985 and 2018, and used the life cycle assessment method combined with the latest greenhouse gas (GHG) inventory guidelines to compile a GHG emission inventory for the crop and livestock production systems. In addition, we used GIS to characterize the spatial and temporal distribution characteristics of GHG emissions in the crop and livestock production systems at county scale. We also examined the intensity of GHG emissions based on unit cultivated land area and unit energy in crop and livestock products, and accordingly identified GHG emission hotspots. Furthermore, the main influencing factors in different years were quantified based on random forest analysis. The results revealed that from 1985 to 2018, total GHG emissions from the crop and livestock production systems in Shanxi Province increased from 17.42 to 20.75 million t(CO2 eq), representing an increase of 19.10%. The agricultural input for the crop system in different years were the main contributors to GHG emissions within the overall crop and livestock production systems, accounting for 41.08%−54.23% of the total emissions. We found that the production of GHG by burning straw decreased from 4.44 million t(CO2 eq) in 1985 to 3.21 million t(CO2 eq) in 2018, with the total emissions proportion decreasing from 25.46% to 15.47%, which was the second largest GHG emission source in the entire crop and livestcok prodcution system. Contrastingly, GHG emissions from soil increased from 1.51 to 2.32 million t(CO2 eq), with the total emissions proportion increasing from 8.68% to 11.18%. Similarly, we detected a 2.30 fold increase in the GHG emissions derived from animal enteric fermentation and manure management system in the livestock production system, from 2.03 to 6.69 million t(CO2 eq), with the proportion of total emissions increasing from 11.64% to 32.23%. With respect to the entire crop and livestock production systems, the intensity of GHG emissions increased from 4.63 to 5.12 t·hm−2, although we detected a significant reduction in the GHG emissions per energy in crop and livestock products from 0.15 to 0.08 kg(CO2 eq)·MJ−1. Furthermore, the results of random forest analysis revealed that nitrogen fertilizer application and planting structure were the main factors influencing GHG emission intensity and efficiency, although the nature of the influencing factors was found to differ in different years. The optimal management of nitrogen fertilization and improvements in crop structure and animal husbandry management were identified as key factors for reducing GHG emissions. Our findings in this study will provide a valuable reference for understanding and enhancing the green development of crop and livestock production systems.

     

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