Li Jing, Zheng Zhican, Xu Yan, Hang Sheng, Gong Huarui
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, Anhui Agricultural University, Hefei 230036, China.
Sci Total Environ. 2024 Apr 15;921:170852. doi: 10.1016/j.scitotenv.2024.170852. Epub 2024 Feb 10.
Under the twin pressures of global food security and dual‑carbon strategies, improving farm eco-efficiency is critical for achieving China's goal of a 50 Pg increase in grain production, meeting the ambitious climate mitigation targets set by the Paris Agreement, and meeting seven of the seventeen Sustainable Development Goals (SDGs) set by the United Nations. However, there is limited research on eco-efficiency measures supported by localised fine-scale data and coupling mechanisms for the structure, production process, efficiency improvement, and carbon reduction synergies of integrated farming systems in China. This study used the Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methods to assess eco-efficiency at the farm level in northern China, included in the National Coupling Crop and Livestock Production Pilot Programs, to improve the eco-efficiency of farms to achieve increased production and emission reductions. The results showed that the overall eco-efficiency of farms was in the lower-middle range, with only 20.18 % of the farms having a technical efficiency exceeding 1. Problems included a backward level of pure technical efficiency and a return to scale. Non-integrated farms have the lowest profitability (41.33 %) and the highest carbon emission intensity of 3.03 kg COeq/USD. The global warming potential impact of non-integrated farms optimization could be reduced by 25 Pg COeq. Implementing the integrated farming mode has a significant advantage in reducing carbon emissions and improving productivity. Overall, farm fodder optimization can be increased by up to 42.41 %. Simultaneously, farms with sufficient farmland are more likely to realise a highly integrated business mode for crop cultivation and livestock breeding. Therefore, constructing a new type of green integrated farming system will help farms achieve increased production and emission reductions, promote the development of sustainable agriculture, and provide a Chinese model for the realisation of global SDGs.
在全球粮食安全和双碳战略的双重压力下,提高农场生态效率对于实现中国粮食产量增加50亿吨的目标、实现《巴黎协定》设定的宏伟气候减排目标以及实现联合国设定的17个可持续发展目标(SDGs)中的7个至关重要。然而,关于中国综合农业系统的结构、生产过程、效率提升和碳减排协同效应的本地化精细尺度数据支持的生态效率措施及耦合机制的研究有限。本研究采用生命周期评估(LCA)和数据包络分析(DEA)方法,对纳入国家作物与畜牧生产耦合试点项目的中国北方农场层面的生态效率进行评估,以提高农场生态效率,实现增产减排。结果表明,农场整体生态效率处于中低水平,仅有20.18%的农场技术效率超过1。存在纯技术效率水平落后和规模报酬问题。非综合经营农场盈利能力最低(41.33%),碳排放强度最高,为3.03千克二氧化碳当量/美元。非综合经营农场优化后的全球变暖潜能值影响可降低25亿吨二氧化碳当量。实施综合农业模式在减少碳排放和提高生产力方面具有显著优势。总体而言,农场饲料优化最多可提高42.41%。同时,拥有充足农田的农场更有可能实现作物种植和畜牧养殖的高度一体化经营模式。因此,构建新型绿色综合农业系统将有助于农场实现增产减排,促进可持续农业发展,并为实现全球可持续发展目标提供中国模式。