中国农业科学2025，Vol.58Issue(11)：2190-2205,16.DOI:10.3864/j.issn.0578-1752.2025.11.009
农田土壤固碳与温室气体排放计量研究进展
A Review of Soil Carbon Sequestration and Greenhouse Gas Emissions Quantification in Cropland
摘要
Abstract
As significant sources and sinks of greenhouse gases in terrestrial ecosystems,cropland can effectively mitigate climate change through scientific management practices.Developing methods for quantifying soil carbon sequestration and greenhouse gas emissions is crucial for accurately measuring the contribution of agriculture to carbon neutrality strategies.These methods are also essential for greenhouse gas inventory preparation,evaluating carbon sequestration and emission reduction effects,voluntary emission reduction trading,and carbon-related certification.This paper systematically reviewed the methods for quantifying soil carbon sequestration and greenhouse gas emissions in cropland,comparing the differences among various methods in terms of data requirements,acquisition costs,estimation accuracy,and the challenges faced.It focused on the applicability of these methods in different scenarios and their optimization pathways.The methods discussed for soil carbon sequestration and greenhouse gas emissions included the Two-Period Difference Method(for soil carbon sequestration only),Data Integration Method(for soil carbon sequestration only),Parameter Method/Emission Factor Method,Empirical Models,and Process Models.The Two-Period Difference Method and Data Integration Method estimate changed in soil organic carbon using empirical data,but their accuracy was directly affected by the matching of datasets and the amount of data.The Parameter Method/Emission Factor Method estimated soil carbon sequestration and greenhouse gas emissions with minimal data requirements,but its accuracy depended on the localization and refinement of parameters/emission factors.Due to these limitations,the Parameter Method/Emission Factor Method was more suitable for low-resolution estimates at regional scales and could not accurately capture high-resolution spatial variations.Empirical Models and Process Models considered the effects of meteorological,soil,and management factors on soil carbon sequestration and greenhouse gas emissions,making them suitable for high-resolution spatial simulations and field-scale measurements.The performance of empirical models depended on the quantity,quality,and accuracy of variable selection in the modeling database.In contrast,Process-based Models could capture the spatiotemporal dynamics of soil organic carbon and greenhouse gases under complex conditions,but required local parameter optimization for accurate performance.Given the challenges of different methods,this paper highlighted the importance of balancing data requirements,costs,and estimation accuracy in specific-scenarios.It noteed that model simulation methods would become the main trend in future agricultural carbon quantification.Addressing how to balance data requirements,acquisition costs,and estimation accuracy for different scenarios was a significant challenge.Future research should focus on building comprehensive field monitoring networks,promoting standardized database construction and sharing,deepening the localization and refinement of emission factors,and exploring innovative applications of machine learning in multi-algorithm integration and process model parameter adjustment.关键词
土壤固碳/温室气体/农田/排放因子/模型模拟/碳中和Key words
soil carbon sequestration/greenhouse gas/cropland/emission factor/model simulation/carbon neutrality引用本文复制引用
孙建飞,程琨..农田土壤固碳与温室气体排放计量研究进展[J].中国农业科学,2025,58(11):2190-2205,16.基金项目
中央级公益性科研院所基本科研业务专项(GYZX240410)、国家自然科学基金(42277020,42407658) （GYZX240410）
