Direct determination of organic and inorganic oxygen in coals from the Argonne Premium sample program by solid sampling electrothermal vaporization inductively coupled plasma optical emission spectrometry. (15th May 2017)

• Record Type: Journal Article
• Authors: Vogt, Daniela; Vogt, Thomas; Wolf, Bianca; Neuroth, Markus; Otto, Matthias
• Is Part Of: Fuel. Volume 196(2017)
• Page Start: 185
• Page End: 194
• Publication Date: 2017-05-15
• Subjects: Oxygen -- Coal analysis -- ETV-ICP OES -- Solid sampling -- Argonne Premium Coals; Fuel -- Periodicals; Coal -- Periodicals; Coal; Fuel; Periodicals; 662.6
• DOI: 10.1016/j.fuel.2017.01.043
• Languages: English
• ISSNs: 0016-2361

Abstract

Graphical abstract: Highlights: Direct determination of organic and inorganic oxygen in coals. Suitable for coals varying in rank from lignite to semi-anthracite. Simultaneous quantification of trace to major elements in whole coal samples. Solid sampling method - no need for any further sample pretreatment. Applicable for process-accompanying analyses. Abstract: This paper presents a new analysis method for directly determining organic and inorganic oxygen in coals, varying in rank from lignite to semi-anthracite. By means of Electrothermal Vaporization Inductively Coupled Plasma Optical Emission Spectrometry (ETV-ICP OES) the coals are thermally decomposed in an argon atmosphere up to a temperature of 2400 °C and the released oxygen is continuously detected throughout the temperature range. The study presented mainly focuses on assigning the obtained peaks in the transient emission signal to organic or inorganic oxygen, then evaluating the accuracy of this method. To assign the peaks, the raw coals were demineralized and the resulting changes were analyzed using ETV-ICP OES and FTIR spectroscopy. The precision of the analysis was evaluated by comparing the obtained oxygen values with published data for the total set of Argonne Premium Coals. The analysis method described is time- and cost-efficient and well suited to the fast characterization of coal, enabling the rapid recognition even of the critical silicate-rich coals. It can be automated to a large extent and applied in process-accompanying analyses.