Study on carbon sink of cropland and influencing factors: A multiscale analysis based on geographical weighted regression model

回归分析 碳汇 环境科学 回归 统计 水槽(地理) 计量经济学 地理加权回归模型 数学 地理 地图学 地质学 气候变化 海洋学
作者
Shixiong Song,Mingli Kong,Mingjian Su,Yongxi Ma
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:447: 141455-141455 被引量:30
标识
DOI:10.1016/j.jclepro.2024.141455
摘要

Analyzing the carbon sink of cropland and its relationship with influencing factors is of great significance to improve carbon sink and develop sustainable agriculture. However, fewer studies evaluated the spatial relationship at multiple scales. In this study, we first quantified the carbon sink of cropland in China in 2020 using empirical model. Then, we used the Geographical Weighted Regression model to quantify the relationship between carbon sink of cropland and influencing factors at the national, agricultural zone and provincial scales. Finally, we discussed potential ways to enhance carbon sink of cropland. The results found that the total carbon sink of cropland in 2020 was in surplus, with 2.56 billion tons, showing a spatial distribution of "high north and low south". There was significant spatial heterogeneity in the relationship between carbon sink of cropland and influencing factors. Labor size and agricultural inputs were most closely related to carbon sink of cropland. The areas with significant correlation were 116.99 and 108.79 million ha, respectively, or 93.17% and 86.64% of the total cropland. Carbon sink of cropland will have strong economic value, with 1.17 trillion yuan in China in 2020, which can increase farmers' per capita income by 1.34%. In order to enhance the carbon sink of cropland, we suggest that China's agricultural sector should reduce farmers' production costs, further improve the carbon trading platform for realizing the economic value of carbon sink of cropland, and then promote the sustainable development of agriculture.
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