氢热解、核磁共振、重铬酸盐氧化和MIR-PLSR对粗质土热原碳丰度的比较

IF 6.6 1区 农林科学 Q1 SOIL SCIENCE
Jonathan Sanderman , Jordahna Haig , Sourav Das , Colleen Partida , Christina Asanopoulos , Michael I. Bird
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引用次数: 0

摘要

土壤热原碳(PyC)作为一种抗矿化的碳库,对全球碳循环具有重要意义,从而为促进净碳固存提供了机会。定量土壤PyC库的大小和动态受到大量技术的阻碍,这些技术即使在应用于同一样品时也会产生大范围的丰度。我们利用氢热解技术量化了全球分布的粗质土壤中稳定的多环芳香族碳(SPAC),其中小于53µm的颗粒百分比为0.1 ~ 24.1%(平均= 7.2±5.8% 1σ)。PyCSPAC值范围为0 ~ 0.37%(平均= 0.08±0.06%)。我们将PyCSPAC值与核磁共振波谱(PyCNMR)的估价值进行了比较,发现两者之间存在很强的相关性(r = 0.90)。然而,PyCNMR估价值比PyCSPAC高7倍,部分原因是核磁共振测量了更大范围的热原分子,但也可能是由于包含了非热原的芳香“抗性”土壤碳。相比之下,PyCSPAC或PyCNMR与重铬酸盐氧化(PyCOREC)测定的丰度之间几乎没有对应关系。中红外(MIR)光谱的偏最小二乘模型能够以较高的置信度预测PyCSPAC和PyCNMR值(r分别为0.77和0.94)。研究表明,在适当的比例因子下,PyCSPAC和PyCNMR可以直接进行比较,两者都可以用MIR进行预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of pyrogenic carbon abundance in coarse-textured soil by hydrogen pyrolysis, NMR and dichromate oxidation and MIR-PLSR
Soil pyrogenic carbon (PyC) is of considerable significance to the global carbon cycle as a carbon pool which is resistant to mineralization and thus offers opportunities to facilitate net carbon sequestration. Quantifying the size and dynamics of the soil PyC pool is hampered by the large number of techniques that yield a wide range of abundances even when applied to the same sample. We used hydrogen pyrolysis to quantify stable polycyclic aromatic carbon (SPAC) of pyrogenic origin (PyCSPAC) in a globally distributed set of coarse-textured soils, in which the percentage of particles finer than 53 µm ranged from 0.1 to 24.1 % (mean = 7.2 ± 5.8 % 1σ). PyCSPAC values ranged from 0 to 0.37 % (mean = 0.08 ± 0.06 %). We compared the PyCSPAC values with estimates derived from nuclear magnetic resonance spectroscopy (PyCNMR) and found a strong correlation between the two (r = 0.90). However, the PyCNMR estimates were ∼7 times higher than PyCSPAC values, attributed partly to NMR measuring a wider range of pyrogenic molecules but also likely due to the inclusion of aromatic ‘resistant’ soil carbon of non-pyrogenic origin. In contrast, there was little correspondence between either PyCSPAC or PyCNMR and abundances determined by dichromate oxidation (PyCOREC). Partial least squares modelling of the mid-infrared (MIR) spectra was able to predict both PyCSPAC and PyCNMR values with high confidence (r = 0.77 and 0.94 respectively). The study suggests that, with appropriate scaling factors, PyCSPAC and PyCNMR can be directly compared, and both can be predicted by MIR.
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来源期刊
Geoderma
Geoderma 农林科学-土壤科学
CiteScore
11.80
自引率
6.60%
发文量
597
审稿时长
58 days
期刊介绍: Geoderma - the global journal of soil science - welcomes authors, readers and soil research from all parts of the world, encourages worldwide soil studies, and embraces all aspects of soil science and its associated pedagogy. The journal particularly welcomes interdisciplinary work focusing on dynamic soil processes and functions across space and time.
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