Articles | Volume 12, issue 7
https://doi.org/10.5194/amt-12-3761-2019
https://doi.org/10.5194/amt-12-3761-2019
Research article
 | 
11 Jul 2019
Research article |  | 11 Jul 2019

A novel approach for simple statistical analysis of high-resolution mass spectra

Yanjun Zhang, Otso Peräkylä, Chao Yan, Liine Heikkinen, Mikko Äijälä, Kaspar R. Daellenbach, Qiaozhi Zha, Matthieu Riva, Olga Garmash, Heikki Junninen, Pentti Paatero, Douglas Worsnop, and Mikael Ehn

Related authors

Unambiguous identification of N-containing oxygenated organic molecules using a chemical-ionization Orbitrap (CI-Orbitrap) in an eastern Chinese megacity
Yiqun Lu, Yingge Ma, Dan Dan Huang, Shengrong Lou, Sheng'ao Jing, Yaqin Gao, Hongli Wang, Yanjun Zhang, Hui Chen, Yunhua Chang, Naiqiang Yan, Jianmin Chen, Christian George, Matthieu Riva, and Cheng Huang
Atmos. Chem. Phys., 23, 3233–3245, https://doi.org/10.5194/acp-23-3233-2023,https://doi.org/10.5194/acp-23-3233-2023, 2023
Short summary
Atmospheric organic vapors in two European pine forests measured by a Vocus PTR-TOF: insights into monoterpene and sesquiterpene oxidation processes
Haiyan Li, Manjula R. Canagaratna, Matthieu Riva, Pekka Rantala, Yanjun Zhang, Steven Thomas, Liine Heikkinen, Pierre-Marie Flaud, Eric Villenave, Emilie Perraudin, Douglas Worsnop, Markku Kulmala, Mikael Ehn, and Federico Bianchi
Atmos. Chem. Phys., 21, 4123–4147, https://doi.org/10.5194/acp-21-4123-2021,https://doi.org/10.5194/acp-21-4123-2021, 2021
Short summary
Insights into atmospheric oxidation processes by performing factor analyses on subranges of mass spectra
Yanjun Zhang, Otso Peräkylä, Chao Yan, Liine Heikkinen, Mikko Äijälä, Kaspar R. Daellenbach, Qiaozhi Zha, Matthieu Riva, Olga Garmash, Heikki Junninen, Pentti Paatero, Douglas Worsnop, and Mikael Ehn
Atmos. Chem. Phys., 20, 5945–5961, https://doi.org/10.5194/acp-20-5945-2020,https://doi.org/10.5194/acp-20-5945-2020, 2020
Short summary
Evaluating the performance of five different chemical ionization techniques for detecting gaseous oxygenated organic species
Matthieu Riva, Pekka Rantala, Jordan E. Krechmer, Otso Peräkylä, Yanjun Zhang, Liine Heikkinen, Olga Garmash, Chao Yan, Markku Kulmala, Douglas Worsnop, and Mikael Ehn
Atmos. Meas. Tech., 12, 2403–2421, https://doi.org/10.5194/amt-12-2403-2019,https://doi.org/10.5194/amt-12-2403-2019, 2019
Short summary

Related subject area

Subject: Gases | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Intercomparison of fast airborne ozone instruments to measure eddy covariance fluxes: spatial variability in deposition at the ocean surface and evidence for cloud processing
Randall Chiu, Florian Obersteiner, Alessandro Franchin, Teresa Campos, Adriana Bailey, Christopher Webster, Andreas Zahn, and Rainer Volkamer
Atmos. Meas. Tech., 17, 5731–5746, https://doi.org/10.5194/amt-17-5731-2024,https://doi.org/10.5194/amt-17-5731-2024, 2024
Short summary
Field assessments on the impact of CO2 concentration fluctuations along with complex-terrain flows on the estimation of the net ecosystem exchange of temperate forests
Dexiong Teng, Jiaojun Zhu, Tian Gao, Fengyuan Yu, Yuan Zhu, Xinhua Zhou, and Bai Yang
Atmos. Meas. Tech., 17, 5581–5599, https://doi.org/10.5194/amt-17-5581-2024,https://doi.org/10.5194/amt-17-5581-2024, 2024
Short summary
Multi-instrumental analysis of ozone vertical profiles and total columns in South America: comparison between subtropical and equatorial latitudes
Gabriela Dornelles Bittencourt, Hassan Bencherif, Damaris Kirsch Pinheiro, Nelson Begue, Lucas Vaz Peres, José Valentin Bageston, Douglas Lima de Bem, Francisco Raimundo da Silva, and Tristan Millet
Atmos. Meas. Tech., 17, 5201–5220, https://doi.org/10.5194/amt-17-5201-2024,https://doi.org/10.5194/amt-17-5201-2024, 2024
Short summary
Transferability of machine-learning-based global calibration models for NO2 and NO low-cost sensors
Ayah Abu-Hani, Jia Chen, Vigneshkumar Balamurugan, Adrian Wenzel, and Alessandro Bigi
Atmos. Meas. Tech., 17, 3917–3931, https://doi.org/10.5194/amt-17-3917-2024,https://doi.org/10.5194/amt-17-3917-2024, 2024
Short summary
Direct high-precision radon quantification for interpreting high frequency greenhouse gas measurements
Dafina Kikaj, Edward Chung, Alan D. Griffiths, Scott D. Chambers, Grant Foster, Angelina Wenger, Penelope Pickers, Chris Rennick, Simon O'Doherty, Joseph Pitt, Kieran Stanley, Dickon Young, Leigh S. Fleming, Karina Adcock, and Tim Arnold
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-54,https://doi.org/10.5194/amt-2024-54, 2024
Revised manuscript accepted for AMT
Short summary

Cited articles

Allan, J. D., Jimenez, J. L., Williams, P. I., Alfarra, M. R., Bower, K. N., Jayne, J. T., Coe, H., and Worsnop, D. R.: Quantitative sampling using an Aerodyne aerosol mass spectrometer 1. Techniques of data interpretation and error analysis, J. Geophys. Res.-Atmos., 108, 4090, https://doi.org/10.1029/2002JD002358, 2003. 
Bertram, T. H., Kimmel, J. R., Crisp, T. A., Ryder, O. S., Yatavelli, R. L. N., Thornton, J. A., Cubison, M. J., Gonin, M., and Worsnop, D. R.: A field-deployable, chemical ionization time-of-flight mass spectrometer, Atmos. Meas. Tech., 4, 1471–1479, https://doi.org/10.5194/amt-4-1471-2011, 2011. 
Brown, S. G., Eberly, S., Paatero, P., and Norris, G. A.: Methods for estimating uncertainty in PMF solutions: Examples with ambient air and water quality data and guidance on reporting PMF results, Sci. Total Environ., 518–519, 626–635, https://doi.org/10.1016/j.scitotenv.2015.01.022, 2015. 
Canagaratna, M., Jayne, J., Jimenez, J., Allan, J., Alfarra, M., Zhang, Q., Onasch, T., Drewnick, F., Coe, H., and Middlebrook, A.: Chemical and microphysical characterization of ambient aerosols with the aerodyne aerosol mass spectrometer, Mass Spectrom. Rev., 26, 185–222, 2007. 
Canonaco, F., Crippa, M., Slowik, J. G., Baltensperger, U., and Prévôt, A. S. H.: SoFi, an IGOR-based interface for the efficient use of the generalized multilinear engine (ME-2) for the source apportionment: ME-2 application to aerosol mass spectrometer data, Atmos. Meas. Tech., 6, 3649–3661, https://doi.org/10.5194/amt-6-3649-2013, 2013. 
Download
Short summary
Recent advancements in atmospheric mass spectrometry provide large amounts of new information but at the same time present considerable challenges for the data analysis, for example, in high-resolution peak identification and separation. To address these problems, this study presents a simple and novel method, which succeeds in analyzing both synthetic and ambient datasets. We believe it will become a powerful approach in the data analysis of mass spectra.