生态与农村环境学报 ›› 2024, Vol. 40 ›› Issue (2): 179-190.doi: 10.19741/j.issn.1673-4831.2023.0207

• 区域环境与发展 • 上一篇    下一篇

“双碳”目标下江西省农业碳排放量测算、影响因素分析与预测研究

黄和平1, 李紫霞1, 黄靛2, 谢美辉3, 王智鹏4   

  1. 1. 江西财经大学经济学院, 江西 南昌 330013;
    2. 南昌航空大学信息工程学院, 江西 南昌 330063;
    3. 南昌工程学院工商管理学院, 江西 南昌 330099;
    4. 江西农业大学经济管理学院, 江西 南昌 330045
  • 收稿日期:2023-03-16 出版日期:2024-02-25 发布日期:2024-02-24
  • 通讯作者: 王智鹏,E-mail:wzhipeng1991@163.com E-mail:wzhipeng1991@163.com
  • 作者简介:黄和平(1969-),男,江西吉水人,教授,博士生导师,主要从事生态系统管理与评价、环境规划与管理等方面的研究。E-mail:hphuang2004@163.com
  • 基金资助:
    国家自然科学基金青年基金(42201294);中国博士后面上基金(2023M731433);江西省教育厅科学技术研究项目(GJJ200422)

Research on the Measurement, Analysis and Prediction of Agricultural Carbon Emissions in Jiangxi Province under the “Dual Carbon” Goals

HUANG He-ping1, LI Zi-xia1, HUANG Dian2, XIE Mei-hui3, WANG Zhi-peng4   

  1. 1. School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China;
    2. School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China;
    3. School of Business Administration, Nanchang Institute of Technology, Nanchang 330099, China;
    4. School of Economics and Management, Jiangxi Agricultural University, Nanchang 330045, China
  • Received:2023-03-16 Online:2024-02-25 Published:2024-02-24

摘要: 农业是中国的立国之本,也是重要的碳排放源,发展低碳农业有助于中国总体碳减排目标的实现。选择农资投入、农田利用、畜禽养殖及秸秆焚烧4类碳源,利用IPCC碳排放模型对江西省2000-2020年的农业碳排放量予以测算,利用LMDI模型进行影响因素分解,并运用XGBoost模型预测2021-2050年碳排放量。结果表明:(1)2000-2020年江西省农业碳排放总量呈现先下降后上升再下降的波动趋势,总体呈上升趋势,但农业碳排放强度逐年降低。农业碳排放源中农田土壤利用贡献率最高,其次为畜禽养殖、农资投入和秸秆焚烧。2000-2020年江西省11个地级市农业碳排放量及排放强度均呈现明显的区域差异,且差异不断扩大,其中宜春市的农业碳排放量和平均碳排放强度均居于首位。(2)地区经济发展水平的提高和城镇化率的增加是导致农业碳排放量增加的主要因素,而农业生产效率、农业产业结构、地区产业结构和劳动力对碳减排的作用比较有限。(3)预测结果显示,2030年前江西省农业碳排放总量及11个地级市农业碳排放量已达到峰值。其中,新余市在2005年最早达到峰值,景德镇市和赣州市在2016年最晚达到峰值。2020年后,江西省碳排放量在经历一段时间攀升后呈现出震荡回落的趋势,其中宜春市和新余市震荡幅度较大,南昌市、抚州市及九江市碳排放量有上升趋势,其他地区均在一段时间后趋于较小振幅的回落趋势。

关键词: 农业碳排放, 碳达峰, 碳排放强度, XGBoost模型, 碳减排

Abstract: Agriculture serves as the foundation of China's nation-building while also being an important source of carbon emissions. Promoting the development of low carbon agriculture can contribute to the achievements of China's overall carbon mitigation goals. This study focuses on four main agricultural carbon sources: agricultural inputs, farmland utilization, livestock and poultry farming, and straw burning. The agricultural carbon emissions in Jiangxi Province from 2000 to 2020 was then calibrated with IPCC Carbon Emission Model, the influencing factors was decomposed by the LMDI model to, and the carbon emissions from 2021 to 2050 was predicted by employing the XGBoost model. The research findings of this study are as follows: (1) From 2000 to 2020, the total agricultural carbon emissions in Jiangxi Province fluctuated with a downward trend initially, followed by an increase, and then another decline. Overall, there was an upward trend in total emissions, but the intensity of agricultural carbon emissions decreased annually. Amongst all the four sources, farmland soil utilization contributed the most, followed by livestock and poultry farming, agricultural inputs, and straw burning. From 2000 to 2020, significant regional disparities were observed in emissions and emission intensity across all the prefecture-level 11 cities in Jiangxi Province, and these disparities continued to widen. Yichun City ranked the top in both total amount of emissions and the average carbon emission intensity. (2) The increase in regional economic development and urbanization rate were the main factors leading to the rise in agricultural carbon emissions, while the effects of agricultural production efficiency, agricultural industry structure, regional industrial structure, and labor force on carbon reduction were relatively limited. (3) The 2030 prediction results indicate that agricultural carbon emissions in Jiangxi Province and all its 11 prefecture-level cities have already reached their peaks. Xinyu City reached its peak the earliest in 2005, while Jingdezhen City and Ganzhou City reached their peaks the latest in 2016. According to the prediction, after 2020, the carbon emissions of Jiangxi Province will experience a period of rising followed by oscillating decline. Yichun City and Xinyu City will experience relatively large fluctuations, while Nanchang City, Fuzhou City, and Jiujiang City show an upward trend in carbon emissions. Other cities will experience a minor fluctuation and a subsequent decline in emissions after a certain period.

Key words: agricultural carbon emissions, carbon emission peak, carbon emission intensity, XGBoost model, carbon abatement

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