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生态学杂志 ›› 2026, Vol. 45 ›› Issue (5): 1713-1723.doi: 10.13292/j.1000-4890.202605.011

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农田生态系统碳排放研究进展及趋势分析

孙小笑1,2,曹罗丹2,李加林1,2,3*   

  1. 1陆海国土空间利用与治理浙江省协同创新中心, 浙江宁波 315211; 2宁波大学地理与空间信息技术系, 浙江宁波 315211; 3宁波大学东海研究院, 浙江宁波 315211)
  • 出版日期:2026-05-10 发布日期:2026-05-12

Progress and trend analysis of carbon emissions in farmland ecosystems.

SUN Xiaoxiao1,2, CAO Luodan2, LI Jialin1,2,3*   

  1. (1Zhejiang Collaborative Innovation Center for Land and Marine Spatial Utilization and Governance Research, Ningbo 315211, Zhejiang, China; 2Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, Zhejiang, China; 3Ningbo University Donghai Academy, Ningbo 315211, Zhejiang, China).

  • Online:2026-05-10 Published:2026-05-12

摘要: 农田生态系统是农业生产与陆地碳循环的核心单元,是全球温室气体排放的重要来源之一,随着农业集约化进程加速与碳中和目标的提出,农田生态系统碳排放管理逐渐成为生态学、农学、地理学等学科的研究焦点。本文综述了农田生态系统碳排放的测算方法、时空格局、影响因素及减排措施的研究进展。在测算方法方面,IPCC清单法提供了全球农田碳排放核算的基础,但测算精度仍需结合本土化因子优化。农田生态系统排放源主要关注二氧化碳(CO2)、甲烷(CH4)和氧化亚氮(N2O),其中农业生产活动产生的CO2和稻田CH4的研究较为深入,但氮肥引发的N2O排放的研究仍不足。农田碳排放的时空分布呈现显著异质性,受自然条件、农业管理和社会经济因素影响,未来研究应加强区域间差异的分析。减排措施方面,虽然技术创新与政策协同已被广泛提及,但针对不同地区和农业模式的具体措施仍显不足。未来的农田生态系统碳排放研究应加强CO2、CH4和N2O协同减排研究,并结合不同地理环境建立各区域适用的农田碳排放核算模型,深入探索自然条件、农业管理和社会经济因素影响的交互作用。同时,还需发展新技术和方法,探索人工智能与遥感技术在高精度碳减排管理中的应用,评估农田生态系统碳汇功能和服务价值,并制定有效的碳汇补偿与激励政策,促进农业的可持续发展。还应推进全国范围的农田碳排放长期动态监测和数据库建设,评估土地利用变化对农田碳源碳汇功能的长期影响,因地制宜制定精准低碳农业减排策略,逐步实现“双碳”目标下全国的农业绿色转型。


关键词: 农田生态系统, 碳排放, 时空分布, 影响因素, 减排措施

Abstract: Farmlands, as critical units of agricultural production and terrestrial carbon cycle, are a major source of greenhouse gas emissions. With the acceleration of agricultural intensification and the goal of carbon neutrality, the management of carbon emissions from farmlands has become a research focus in many disciplines, such as ecology, agronomy, and geography. We reviewed advancements in quantification methods, spatiotemporal patterns, influencing factors, and mitigation strategies of carbon emissions from farmlands. The IPCC inventory methodology provides a foundational framework for global emission accounting, but the accuracy of the measurement should be optimized by localized factor calibration. Current research predominantly focuses on carbon dioxide (CO2) emissions from agricultural activities and methane (CH4) emissions from rice paddies, and less studies focus on nitrous oxide (N2O) emissions driven by nitrogen fertilization. The spatiotemporal distribution of carbon emissions from farmland exhibits significant heterogeneity, influenced by natural conditions, agricultural management practices, and socioeconomic factors, necessitating deeper regional comparative analyses in future. Although technological innovations and policy coordination have been widely proposed, region-specific strategies tailored to diverse agricultural systems remain insufficient. Future research should prioritize integrated mitigation of the emissions of CO2, CH4, and N2O, and establish regionally adaptive farmland carbon emission accounting models to explore the interactive effects of natural, managerial, and socioeconomic factors. Additionally, emerging technologies such as artificial intelligence and remote sensing should be applied to high-precision reduction of carbon emission, while carbon sequestration capacity and ecosystem service value of farmlands require systematic quantification to inform effective compensation mechanisms for promoting the development of sustainable agriculture. Nationwide dynamic monitoring networks and databases should be developed to assess long-term impacts of land use changes on carbon source/sink functions of farmlands, enabling targeted low-carbon strategies to gradually achieve the green transformation of agriculture across China under the “Dual Carbon” goals.


Key words: farmland, carbon emission, spatiotemporal distribution, influencing factor, emission reduction measure