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https://doi.org/10.5194/egusphere-2024-1671
https://doi.org/10.5194/egusphere-2024-1671
18 Jun 2024
 | 18 Jun 2024

Automated compound speciation, cluster analysis, and quantification of organic vapours and aerosols using comprehensive two-dimensional gas chromatography and mass spectrometry

Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, and Ye Wu

Abstract. The advancement of analytical techniques, such as comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC-MS), enables the efficient separation of complex organic matrix. Developing innovative methods for data processing and analysis is crucial to unlock the full potential of GC×GC-MS in understanding intricate chemical mixtures. In this study, we proposed an innovative method for the semi-automated identification and quantification of complex organic mixtures using GC×GC-MS. The method was formulated based on self-constructed mass spectrum patterns and the traversal algorithms and was applied to organic vapor and aerosol samples collected from tailpipe emissions of heavy-duty diesel vehicles and the ambient atmosphere. Thousands of compounds were filtered, speciated, and clustered into 26 categories, including aliphatic and cyclic hydrocarbons, aromatic hydrocarbons, aliphatic oxygenated species, phenols and alkyl-phenols, and heteroatom containing species. The identified species accounted for over 80 % of all the eluted chromatographic peaks at the molecular level. A comprehensive analysis of quantification uncertainty was undertaken. Using representative compounds, quantification uncertainties were found to be less than 37.67 %, 22.54 %, and 12.74 % for alkanes, polycyclic aromatic hydrocarbons (PAHs), and alkyl-substituted benzenes, respectively, across the GC×GC space, excluding the first and the last time intervals. From source apportionment perspective, adamantane was clearly isolated as a potential tracer for heavy-duty diesel vehicles (HDDVs) emission. The systematic distribution of N-containing compounds in oxidized and reduced valences was discussed and many of them served as critical tracers for secondary nitrate formation processes. The results highlighted the benefits of developing self-constructed model for the enhanced peak identification, automated cluster analysis, robust uncertainty estimation, and source apportionment and achieving the full potential of GC×GC-MS in atmospheric chemistry.

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Journal article(s) based on this preprint

24 Sep 2024
Automated compound speciation, cluster analysis, and quantification of organic vapors and aerosols using comprehensive two-dimensional gas chromatography and mass spectrometry
Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, and Ye Wu
Atmos. Chem. Phys., 24, 10655–10666, https://doi.org/10.5194/acp-24-10655-2024,https://doi.org/10.5194/acp-24-10655-2024, 2024
Short summary
Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, and Ye Wu

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1671', Yutong Liang, 07 Jul 2024
  • RC2: 'Comment on egusphere-2024-1671', Anonymous Referee #2, 20 Jul 2024

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1671', Yutong Liang, 07 Jul 2024
  • RC2: 'Comment on egusphere-2024-1671', Anonymous Referee #2, 20 Jul 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Xiao He on behalf of the Authors (02 Aug 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (02 Aug 2024) by Ivan Kourtchev
AR by Xiao He on behalf of the Authors (03 Aug 2024)

Journal article(s) based on this preprint

24 Sep 2024
Automated compound speciation, cluster analysis, and quantification of organic vapors and aerosols using comprehensive two-dimensional gas chromatography and mass spectrometry
Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, and Ye Wu
Atmos. Chem. Phys., 24, 10655–10666, https://doi.org/10.5194/acp-24-10655-2024,https://doi.org/10.5194/acp-24-10655-2024, 2024
Short summary
Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, and Ye Wu
Xiao He, Xuan Zheng, Shuwen Guo, Lewei Zeng, Ting Chen, Bohan Yang, Shupei Xiao, Qiongqiong Wang, Zhiyuan Li, Yan You, Shaojun Zhang, and Ye Wu

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Short summary
This study introduces an innovative method for identifying and quantifying complex organic vapors and aerosols. By combining advanced analytical techniques and new algorithms, we categorized thousands of compounds from heavy-duty diesel vehicles and ambient air and highlighted specific tracers for emission sources. The innovative approach enhances peak identification, reduces quantification uncertainties, and offers new insights for air quality management and atmospheric chemistry.