Dataset Information

Characterization of organic matter of plants from lakes by thermal analysis in a N2 atmosphere.

ABSTRACT: Organic matter (OM) has been characterized using thermal analysis in O2 atmospheres, but it is not clear if OM can be characterized using slow thermal degradation in N2 atmospheres (STDN). This article presents a new method to estimate the behavior of OM in anaerobic environment. Seventeen different plants from Tai Lake (Ch: Taihu), China were heated to 600?°C at a rate of 10?°C min(-1) in a N2 atmosphere and characterized by use of differential scanning calorimetry (DSC) and thermal gravimetric analysis (TGA). DSC chromatograms were compared with 9 standard compounds. Seven peaks were observed in DSC chromatograms, 2 main peaks strongly correlated with biochemical indices, and one main peak was a transitional stage. Energy absorbed by a peak at approximately 200?°C and total organic carbon were well correlated, while energy absorbed at approximately 460?°C was negatively correlated with lignin content. Presence of peaks at approximately 350 and 420?°C varied among plant biomass sources, providing potential evidence for biomass identification. Methods of STDN reported here were rapid and accurate ways to quantitatively characterize OM, which may provide useful information for understanding anaerobic behaviors of natural organic matters.

SUBMITTER: Guo F

PROVIDER: S-EPMC4782168 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Characterization of organic matter of plants from lakes by thermal analysis in a N2 atmosphere.

Guo Fei F Wu Fengchang F Mu Yunsong Y Hu Yan Y Zhao Xiaoli X Meng Wei W Giesy John P JP Lin Ying Y

Scientific reports 20160308

Organic matter (OM) has been characterized using thermal analysis in O2 atmospheres, but it is not clear if OM can be characterized using slow thermal degradation in N2 atmospheres (STDN). This article presents a new method to estimate the behavior of OM in anaerobic environment. Seventeen different plants from Tai Lake (Ch: Taihu), China were heated to 600 °C at a rate of 10 °C min(-1) in a N2 atmosphere and characterized by use of differential scanning calorimetry (DSC) and thermal gravimetric ...[more]

PMID: 26953147

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Project description:Terrestrial ecosystems are simultaneously the largest source and a major sink of volatile organic compounds (VOCs) to the global atmosphere, and these two-way fluxes are an important source of uncertainty in current models. Here, we apply high-resolution mass spectrometry (proton transfer reaction-quadrupole interface time-of-flight; PTR-QiTOF) to measure ecosystem-atmosphere VOC fluxes across the entire detected mass range (m/z 0-335) over a mixed temperate forest and use the results to test how well a state-of-science chemical transport model (GEOS-Chem CTM) is able to represent the observed reactive carbon exchange. We show that ambient humidity fluctuations can give rise to spurious VOC fluxes with PTR-based techniques and present a method to screen for such effects. After doing so, 377 of the 636 detected ions exhibited detectable gross fluxes during the study, implying a large number of species with active ecosystem-atmosphere exchange. We introduce the reactivity flux as a measure of how Earth-atmosphere fluxes influence ambient OH reactivity and show that the upward total VOC (∑VOC) carbon and reactivity fluxes are carried by a far smaller number of species than the downward fluxes. The model underpredicts the ∑VOC carbon and reactivity fluxes by 40-60% on average. However, the observed net fluxes are dominated (90% on a carbon basis, 95% on a reactivity basis) by known VOCs explicitly included in the CTM. As a result, the largest CTM uncertainties in simulating VOC carbon and reactivity exchange for this environment are associated with known rather than unrepresented species. This conclusion pertains to the set of species detectable by PTR-TOF techniques, which likely represents the majority in terms of carbon mass and OH reactivity, but not necessarily in terms of aerosol formation potential. In the case of oxygenated VOCs, the model severely underpredicts the gross fluxes and the net exchange. Here, unrepresented VOCs play a larger role, accounting for ~30% of the carbon flux and ~50% of the reactivity flux. The resulting CTM biases, however, are still smaller than those that arise from uncertainties for known and represented compounds.

Dataset Information

Characterization of organic matter of plants from lakes by thermal analysis in a N2 atmosphere.

Publications

Characterization of organic matter of plants from lakes by thermal analysis in a N2 atmosphere.

Similar Datasets

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