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中国农学通报

中国农学通报 ›› 2026, Vol. 42 ›› Issue (10): 96-105.doi: 10.11924/j.issn.1000-6850.casb2025-0642

• 资源·环境·生态·土壤·气象 • 上一篇    下一篇

“双碳”背景下广州市农业碳排放特征及发展趋势

刘晓珂1(), 黄红星1(), 吕星辰1, 卢泓雨1, 郑树奎2   

  1. 1 广东省农业科学院农业经济与信息研究所/农业农村部华南都市农业重点实验室， 广州 510640
    2 广州市农业农村科学院， 广州 510335
  • 收稿日期:2026-01-09 修回日期:2026-02-23 出版日期:2026-05-25 发布日期:2026-05-27
  • 通讯作者:
    黄红星，男，1979年出生，广东梅州人，研究员，硕士，主要从事农业大数据、农业经济研究。通信地址：510640 广东省广州市天河区金颖路31号，Tel：020-38319948，E-mail：。
  • 作者简介:

    刘晓珂，女，1986年出生，河南漯河人，副研究员，硕士，主要从事农业经济管理、低碳农业研究。通信地址：510640 广东省广州市天河区金颖路31号，Tel：020-38319172，E-mail：。

  • 基金资助:
    广州市哲学社科规划课题“广州市加快低碳发展推动绿色化转型研究：基于农业碳达峰视角”(2022GZQN17); 广东省基础与应用基础研究基金项目“广东农业碳排放影响因素及峰值预测研究——基于科技进步视角”(2022A1515011134)

Characteristics and Development Trend of Agricultural Carbon Emissions in Guangzhou Under “Dual Carbon” Context

LIU Xiaoke1(), HUANG Hongxing1(), LYU Xingchen1, LU Hongyu1, ZHENG Shukui2   

  1. 1 Institute of Agricultural Economics and Information, Guangdong Academy of Agricultural Sciences/ Key Laboratory of Urban Agriculture in South China, Ministry of Agriculture and Rural Affairs, Guangzhou 510640
    2 Guangzhou Academy of Agricultural and Rural Sciences, Guangzhou 510335
  • Received:2026-01-09 Revised:2026-02-23 Published:2026-05-25 Online:2026-05-27

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摘要：

明确广州市农业碳排放时空特征和影响因素，预测未来农业碳排放趋势，为广州市制定农业碳减排政策提供理论支持。基于农资投入、水稻种植、农地利用、畜禽养殖4类碳源和6种主要农作物，采用联合国政府间气候变化委员会碳排放计算理论，核算广州市2007—2023年农业碳排放量、碳吸收量、净碳排放量，分析其动态演变趋势和时空特征，并利用LMDI(Logarithmic Mean Divisia Index)模型剖析其影响因素，运用灰度预测模型预测未来一段时间广州市农业净碳排放量。结果显示：（1）2023年广州市农业碳排放量、碳吸收量、净碳排放量分别为103.14×104、63.40×104、39.74×104 t。2007—2023年广州市农业碳排放先升高再降低后小幅波动稳定，在2010年达到峰值235.72×104 t，畜禽养殖碳排放占比最高，2023年为40.14%；农业碳吸收量先升高后下降，在2016年达到峰值95.15×104 t，蔬菜年碳吸收量是广州农业年碳吸收量的主要来源；农业净碳排放呈波动下降趋势，空间分布上呈东北高、西南低的特征，增城区和从化区是未来广州市农业碳减排应关注的重点区域。（2）农业生产效率、农业机械总动力、农业产业结构等因素对于广州市减少农业净碳排放具有一定正向推动作用，农业经济发展在一定程度上造成广州市农业净排放增加。（3）广州市农业碳排放已在2010年达峰，要想在2060年实现碳中和的目标还存在一些困难。基于此，本研究提出加强统筹协调、明确农业碳中和目标和路线图、创新绿色低碳技术、开发碳普惠方法学、探索农业碳交易试点等建议。

关键词: 广州, 碳排放, 碳达峰, LMDI, GM(1,1)

Abstract:

The study aims to clarify the spatiotemporal characteristics and influencing factors of agricultural carbon emissions in Guangzhou, predict the future trend of agricultural carbon emissions, and provide theoretical support for formulating agricultural carbon reduction policies. Based on 4 carbon sources (agricultural inputs, rice cultivation, agricultural land use, and livestock farming) and 6 major crops, the paper adopted the carbon emission calculation theories of the Intergovernmental Panel on Climate Change (IPCC) to calculate agricultural carbon emissions, carbon uptake, and net carbon emissions in Guangzhou from 2007 to 2023, analyzed their dynamic evolution trends and spatiotemporal characteristics, dissected the influencing factors by using the Logarithmic Mean Divisia Index (LMDI) model, and predicted the agricultural net carbon emissions of Guangzhou in the coming period using the gray prediction model. The results indicated that: (1) in 2023, Guangzhou’s agricultural carbon emissions, carbon uptake, and net emissions were 103.14×104 tons, 63.40×104 tons, and 39.74×104 tons. From 2007 to 2023, agricultural carbon emissions initially increased, peaked at 235.72×104 tons in 2010, then declined and stabilized with minor fluctuations, livestock farming contributed the highest proportion (40.14% in 2023); agricultural carbon uptake first increased, reaching its peak of 95.15×104 tons in 2016, and then declined, with annual vegetable carbon uptake being the primary source of Guangzhou’s annual agricultural carbon uptake; agricultural net carbon emissions exhibited a fluctuating downward trend overall, with a spatial distribution characterized by higher values in the northeast and lower values in the southwest, Zengcheng District and Conghua District were key areas requiring attention for future agricultural carbon emission reductions; (2) agricultural production efficiency, total agricultural machinery power and industrial structure positively contributed to reducing net emissions, while agricultural economic development partially increased net emissions; (3) agricultural carbon emissions in Guangzhou had reached the peak in 2010, achieving carbon neutrality in 2060 remained challenging. Accordingly, the paper proposes recommendations such as strengthening coordination, clarifying goals and roadmaps of agricultural carbon neutrality, innovating green low carbon technologies, developing carbon inclusive methodologies, and exploring agricultural carbon trading pilots

Key words: Guangzhou, carbon emissions, carbon peaks, LMDI, GM(1,1)

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