Temporal and Spatial Dynamics and Drivers of China’s Agriculture Net Carbon Sink

DONG Xiaolong; ZHENG Lanqin; LIAN Haifeng; TIAN Bilian; CHEN Zhiyong

doi:10.13870/j.cnki.stbcxb.2024.04.016

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Temporal and Spatial Dynamics and Drivers of China’s Agriculture Net Carbon Sink

更新时间：2025-03-12

- Temporal and Spatial Dynamics and Drivers of China’s Agriculture Net Carbon Sink
- Vol. 38, Issue 4, Pages: 198-208(2024)
- 作者机构：
  
  1. 福建农林大学计算机与信息学院,福州,350002
  2. 生态与资源统计福建省高校重点实验室,福州,350002
- 作者简介：
- 基金信息：
- DOI：10.13870/j.cnki.stbcxb.2024.04.016
  CLC： X321;F302.5
- Published：2024
- 稿件说明：
移动端阅览
DONG Xiaolong, ZHENG Lanqin, LIAN Haifeng, et al. Temporal and Spatial Dynamics and Drivers of China’s Agriculture Net Carbon Sink[J]. 2024, 38(4): 198-208.
DOI：

DONG Xiaolong, ZHENG Lanqin, LIAN Haifeng, et al. Temporal and Spatial Dynamics and Drivers of China’s Agriculture Net Carbon Sink[J]. 2024, 38(4): 198-208. DOI： 10.13870/j.cnki.stbcxb.2024.04.016.

摘要

[目的] 在"双碳"战略背景下

明确我国农业净碳汇的时空动态及其驱动因素

为促进我国农业低碳发展提供理论依据。[方法] 基于水稻种植、农地利用、农用物资及畜禽养殖4大方面19类主要碳源和7类主要碳汇

测算2002—2022年我国及31个省市区(除港澳台)农业净碳汇

运用Arc GIS统计软件分析其时空动态

并采用LMDI模型分析影响我国农业净碳汇的因素。[结果] 我国农业碳排放的主要碳源已由畜牧业的肠道发酵和粪便管理转向种植业的农用物资;碳汇以水稻和玉米的贡献为主;农业净碳汇和碳汇水平整体呈现波动上升的态势

不同地区的农业净碳汇和碳汇水平表现为东北部高西部低的空间分布格局;农业净碳汇存在显著的全局空间正相关

各地区呈现出高高聚集或低低聚集的特征

且空间聚集呈增长趋势;农业净碳汇强度、农业产业结构和农村人口规模在抑制农业净碳汇方面发挥了重要作用

农业经济发展水平在一定程度上增强了碳汇能力。[结论] 我国农业净碳汇呈现明显向好趋势

提高农业生产水平、优化农业产业结构对推动我国农业低碳发展、实现低碳循环具有重要作用。

Abstract

[Objective] Clarifying the temporal and spatial dynamics and drivers of China’s agriculture net carbon sink provides a theoretical basis for promoting low-carbon development in the agricultural. [Methods] Based on the 19 types of the major carbon sources form four including of rice cultivation

agricultural land use

agricultural materials

and livestock breeding

and 7 types of carbon sinks

this study calculated the agricultural net carbon sink in China and its 31 provinces and cities (excluding Hong Kong

Macau

and Taiwan) from 2002 to 2022

using Arc GIS statistical software analyze temporal and spatial dynamics of agricultural net carbon sink

and using the LMDI model to analyze the drivers agricultural net carbon sink. [Results] The primary source of carbon emissions from agriculture had shifted from enteric fermentation and manure management in the livestock sector to agricultural materials in the plantation sector. Carbon sinks were dominated by the contribution of rice and maize. Overall

there has been fluctuating upward trends in both levels of agricultural net carbon sinks and carbon sinks. There was a spatial distribution pattern with high levels observed in northeast China while low levels were found in western regions. Furthermore

there was a significant positive correlation between net agricultural carbon sinks which exhibited features of high-high or low-low aggregation. Moreover

there was an increasing trend in spatial aggregation. Agricultural net carbon sink could be restrained by factors such as the intensity of the agricultural net carbon sink

the structure of the agricultural industry and the size of the rural population; however

it can be enhanced by economic development. [Conclusion] China’s agriculture showed a positive trend regarding net carbon sinks. Optimizing its industry structure along with improving production methods are crucial for promoting low-carbon development and achieving a sustainable cycle.

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