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气相色谱-质谱联用仪测定复杂塑料废弃物热解油的成分

Quantification of the composition of pyrolysis oils of complex plastic waste by gas chromatography coupled with mass spectrometer detector.

作者信息

Serras-Malillos A, Perez-Martinez B B, Iriondo A, Acha E, Lopez-Urionabarrenechea A, Caballero B M

机构信息

Chemical and Environmental Engineering Department, Faculty of Engineering of Bilbao, University of the Basque Country (UPV/EHU) Plaza Ingeniero Torres Quevedo, 1 48013-Bilbao Spain

出版信息

RSC Adv. 2024 Mar 25;14(14):9892-9911. doi: 10.1039/d4ra00226a. eCollection 2024 Mar 20.

DOI:10.1039/d4ra00226a
PMID:38528926
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10961955/
Abstract

Waste valorisation through pyrolysis generates solid, liquid and gaseous fractions that need to be deeply characterised in order to try to recover secondary raw materials or chemicals. Depending on the waste and the process conditions, the liquid fraction obtained (so-called pyrolysis oil) can be very complex. This work proposes a method to quantitatively measure the composition of pyrolysis oils coming from three types of polymeric waste: (1) plastic packaging from sorting plants of municipal solid waste, (2) plastic rich fractions rejected from sorting plants of waste of electrical and electronic equipment and (3) end-of-life carbon/glass fibre reinforced thermoset polymers. The proposed methodology uses a gas chromatography (GC) coupled with mass spectrometer detector (MS) analytical technique, a certified saturated alkanes' mix, an internal standard and fourteen model compounds. Validation of the methodology concluded that the average relative error was between -59 wt% and +62 wt% (with standard deviations between 0 wt% and 13 wt%). Considering that the state-of-the-art scenario to quantify complex plastic pyrolysis oils as a whole is almost none and that they are usually evaluated only qualitatively based on the area percentage of the GC-MS chromatograms, the presented quantification methodology implies a clear step forward towards complex pyrolysis oil compositional quantification in a cost-effective way. Besides, this quantification methodology enables determining what proportion is being detected by GC-MS with respect to the total oil. Finally, the presented work includes all the Kováts RI for complex temperature-program gas chromatography of all the signals identified in the analysed pyrolysis oils, to be readily available to other researchers towards the identification of chemical compounds in their studies.

摘要

通过热解实现废物增值会产生固体、液体和气体馏分,为了尝试回收二次原料或化学品,需要对这些馏分进行深入表征。根据废物和工艺条件的不同,所获得的液体馏分(即所谓的热解油)可能非常复杂。本研究提出了一种方法,用于定量测量来自三种类型聚合物废物的热解油的成分:(1)城市固体废物分类厂的塑料包装;(2)电子电气设备废物分类厂拒收的富含塑料的馏分;(3)报废的碳/玻璃纤维增强热固性聚合物。所提出的方法使用气相色谱(GC)与质谱检测器(MS)联用的分析技术、一种经过认证的饱和烷烃混合物、一种内标物和十四种模型化合物。该方法的验证得出,平均相对误差在-59 wt%至+62 wt%之间(标准偏差在0 wt%至13 wt%之间)。鉴于目前几乎没有对复杂塑料热解油进行整体定量的方法,而且通常仅基于GC-MS色谱图的面积百分比进行定性评估,所提出的定量方法意味着在以经济高效的方式对复杂热解油成分进行定量方面向前迈出了明确的一步。此外,这种定量方法能够确定GC-MS检测到的成分占总油的比例。最后,本研究给出了所有分析热解油中鉴定出的信号在复杂程序升温气相色谱中的所有Kováts保留指数,可供其他研究人员在其研究中鉴定化合物时随时使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/d51119dff973/d4ra00226a-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/2ea9a72e468c/d4ra00226a-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/3f0fa36737ae/d4ra00226a-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/3e22fc54427a/d4ra00226a-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/813e164bd3c9/d4ra00226a-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/47affcecfc7d/d4ra00226a-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/d51119dff973/d4ra00226a-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/2ea9a72e468c/d4ra00226a-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/3f0fa36737ae/d4ra00226a-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/3e22fc54427a/d4ra00226a-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/813e164bd3c9/d4ra00226a-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/47affcecfc7d/d4ra00226a-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e40/10961955/d51119dff973/d4ra00226a-f6.jpg

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