Large errors in soil carbon measurements attributed to inconsistent sample processing

IF 5.8 2区 农林科学 Q1 SOIL SCIENCE
Soil Pub Date : 2025-01-08 DOI:10.5194/soil-11-17-2025
Rebecca J. Even, Megan B. Machmuller, Jocelyn M. Lavallee, Tamara J. Zelikova, M. Francesca Cotrufo
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Abstract

Abstract. To build confidence in the efficacy of soil carbon (C) crediting programs, precise quantification of soil organic carbon (SOC) is critical. Detecting a true change in SOC after a management shift has occurred, specifically in agricultural lands, is difficult as it requires robust soil sampling and soil processing procedures. Informative and meaningful comparisons across spatial and temporal timescales can only be made with reliable soil C measurements and estimates, which begin on the ground and in soil testing facilities. To gauge soil C measurement inter-variability, we conducted a blind external service laboratory comparison across eight laboratories selected based on status and involvement in SOC data curation used to inform C market exchanges, which could include demonstration projects, model validation, and project verification activities. Further, to better understand how soil processing procedures and quantification methods commonly used in soil testing laboratories affect soil C concentration measurements, we designed an internal experiment assessing the individual effect of several alternative procedures (i.e., sieving, fine grinding, and drying) and quantification methods on total (TC), inorganic (SIC), and organic (SOC) soil C concentration estimates. We analyzed 12 different agricultural soils using 11 procedures that varied in either the sieving, fine-grinding, drying, or quantification step. We found that a mechanical grinder, the most commonly used method for sieving in service laboratories, did not effectively remove coarse materials (i.e., roots and rocks) and thus resulted in higher variability and significantly different C concentration measurements from the other sieving procedures (i.e., 8 + 2, 4, and 2 mm with a rolling pin). A finer grind generally resulted in a lower coefficient of variance, where the finest grind to < 125 µm had the lowest coefficient of variance, followed by the < 250 µm grind and, lastly, the < 2000 µm grind. Not drying soils in an oven prior to elemental analysis on average resulted in a 3.5 % lower TC and 5 % lower SOC relative to samples dried at 105 °C due to inadequate removal of moisture. Compared to the reference method used in our study where % TC was quantified by dry combustion on an elemental analyzer, % SIC was measured using a pressure transducer, and % SOC was calculated by the difference in % TC and % SIC, predictions of all three soil properties (% TC, % SIC, and % SOC) using Fourier-transformed infrared spectroscopy (FTIR) were in high agreement (R2 = 0.97, 0.99, and 0.90, respectively). For % SOC, quantification by loss on ignition had a relatively low coefficient of variance (5.42 ± 3.06 %) but the least agreement (R2 = 0.83) with the reference method. We conclude that sieving to < 2 mm with a mortar and pestle or rolling pin to remove coarse materials, drying soils at 105 °C, and fine-grinding soils prior to elemental analysis are required to improve accuracy and precision of soil C measurements. Moreover, we show promising results using FTIR spectroscopy coupled with predictive modeling for estimating % TC, % SIC, and % SOC in regions where spectral libraries exist.
由于样品处理不一致,土壤碳测量误差大
摘要。为了建立对土壤碳(C)信用计划有效性的信心,土壤有机碳(SOC)的精确量化至关重要。在管理转变发生后,特别是在农业用地,检测有机碳的真正变化是困难的,因为它需要强大的土壤采样和土壤处理程序。只有在地面和土壤测试设施中进行可靠的土壤C测量和估计,才能在空间和时间尺度上进行信息丰富和有意义的比较。为了测量土壤碳测量的内部变异,我们在8个实验室之间进行了盲目的外部服务实验室比较,这些实验室是根据土壤碳含量数据管理的状态和参与情况选择的,这些数据管理用于为碳市场交流提供信息,包括示范项目、模型验证和项目验证活动。此外,为了更好地了解土壤检测实验室常用的土壤处理程序和定量方法如何影响土壤C浓度测量,我们设计了一个内部实验,评估几种替代程序(即筛分、细磨和干燥)和定量方法对总(TC)、无机(SIC)和有机(SOC)土壤C浓度估算的单个影响。我们分析了12种不同的农业土壤,使用了11种程序,这些程序在筛分、细磨、干燥或定量步骤中有所不同。我们发现,机械研磨机(服务实验室中最常用的筛分方法)并不能有效地去除粗料(即树根和岩石),因此导致更高的可变性,并且与其他筛分程序(即8 + 2,4和2毫米)的C浓度测量结果显著不同。磨粒越细,方差系数越低,其中< 125µm的磨粒的方差系数最低,其次是< 250µm的磨粒,最后是< 2000µm的磨粒。在元素分析之前,没有在烤箱中干燥土壤,相对于在105°C下干燥的样品,由于水分去除不足,平均导致TC降低3.5%,SOC降低5%。与我们研究中使用的参考方法(在元素分析仪上通过干燃烧量化% TC,使用压力传感器测量% SIC,通过% TC和% SIC的差异计算% SOC)相比,使用傅里叶变换红外光谱(FTIR)预测所有三种土壤性质(% TC, % SIC和% SOC)的一致性很高(R2分别= 0.97,0.99和0.90)。对于% SOC,燃烧损失量化的方差系数相对较低(5.42±3.06%),但与参考方法的一致性最小(R2 = 0.83)。我们得出的结论是,为了提高土壤C测量的准确性和精度,需要用研钵和杵或擀擀杖筛分至< 2mm以去除粗料,在105°C下干燥土壤,并在元素分析之前对土壤进行细磨。此外,我们还展示了使用FTIR光谱结合预测建模在光谱库存在的区域估计% TC, % SIC和% SOC的有希望的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Soil
Soil Agricultural and Biological Sciences-Soil Science
CiteScore
10.80
自引率
2.90%
发文量
44
审稿时长
30 weeks
期刊介绍: SOIL is an international scientific journal dedicated to the publication and discussion of high-quality research in the field of soil system sciences. SOIL is at the interface between the atmosphere, lithosphere, hydrosphere, and biosphere. SOIL publishes scientific research that contributes to understanding the soil system and its interaction with humans and the entire Earth system. The scope of the journal includes all topics that fall within the study of soil science as a discipline, with an emphasis on studies that integrate soil science with other sciences (hydrology, agronomy, socio-economics, health sciences, atmospheric sciences, etc.).
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