Articles | Volume 11, issue 2
Atmos. Meas. Tech., 11, 1049–1060, 2018
https://doi.org/10.5194/amt-11-1049-2018
Atmos. Meas. Tech., 11, 1049–1060, 2018
https://doi.org/10.5194/amt-11-1049-2018

Research article 23 Feb 2018

Research article | 23 Feb 2018

Improved source apportionment of organic aerosols in complex urban air pollution using the multilinear engine (ME-2)

Qiao Zhu et al.

Related authors

Differentiating local and regional sources of Chinese urban air pollution based on the effect of the Spring Festival
Chuan Wang, Xiao-Feng Huang, Qiao Zhu, Li-Ming Cao, Bin Zhang, and Ling-Yan He
Atmos. Chem. Phys., 17, 9103–9114, https://doi.org/10.5194/acp-17-9103-2017,https://doi.org/10.5194/acp-17-9103-2017, 2017
Short summary
Atmospheric aerosol compositions and sources at two national background sites in northern and southern China
Qiao Zhu, Ling-Yan He, Xiao-Feng Huang, Li-Ming Cao, Zhao-Heng Gong, Chuan Wang, Xin Zhuang, and Min Hu
Atmos. Chem. Phys., 16, 10283–10297, https://doi.org/10.5194/acp-16-10283-2016,https://doi.org/10.5194/acp-16-10283-2016, 2016
Short summary
Light absorption of brown carbon aerosol in the PRD region of China
J.-F. Yuan, X.-F. Huang, L.-M. Cao, J. Cui, Q. Zhu, C.-N. Huang, Z.-J. Lan, and L.-Y. He
Atmos. Chem. Phys., 16, 1433–1443, https://doi.org/10.5194/acp-16-1433-2016,https://doi.org/10.5194/acp-16-1433-2016, 2016
Short summary

Related subject area

Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Data imputation in in situ-measured particle size distributions by means of neural networks
Pak Lun Fung, Martha Arbayani Zaidan, Ola Surakhi, Sasu Tarkoma, Tuukka Petäjä, and Tareq Hussein
Atmos. Meas. Tech., 14, 5535–5554, https://doi.org/10.5194/amt-14-5535-2021,https://doi.org/10.5194/amt-14-5535-2021, 2021
Short summary
Analysis of mobile monitoring data from the microAeth® MA200 for measuring changes in black carbon on the roadside in Augsburg
Xiansheng Liu, Hadiatullah Hadiatullah, Xun Zhang, L. Drew Hill, Andrew H. A. White, Jürgen Schnelle-Kreis, Jan Bendl, Gert Jakobi, Brigitte Schloter-Hai, and Ralf Zimmermann
Atmos. Meas. Tech., 14, 5139–5151, https://doi.org/10.5194/amt-14-5139-2021,https://doi.org/10.5194/amt-14-5139-2021, 2021
Short summary
New correction method for the scattering coefficient measurements of a three-wavelength nephelometer
Jie Qiu, Wangshu Tan, Gang Zhao, Yingli Yu, and Chunsheng Zhao
Atmos. Meas. Tech., 14, 4879–4891, https://doi.org/10.5194/amt-14-4879-2021,https://doi.org/10.5194/amt-14-4879-2021, 2021
Short summary
Estimating mean molecular weight, carbon number, and OM∕OC with mid-infrared spectroscopy in organic particulate matter samples from a monitoring network
Amir Yazdani, Ann M. Dillner, and Satoshi Takahama
Atmos. Meas. Tech., 14, 4805–4827, https://doi.org/10.5194/amt-14-4805-2021,https://doi.org/10.5194/amt-14-4805-2021, 2021
Short summary
Modeled source apportionment of black carbon particles coated with a light-scattering shell
Aki Virkkula
Atmos. Meas. Tech., 14, 3707–3719, https://doi.org/10.5194/amt-14-3707-2021,https://doi.org/10.5194/amt-14-3707-2021, 2021
Short summary

Cited articles

Alfarra, M. R., Prevot, A. S. H., Szidat, S., Sandradewi, J., Weimer, S., Lanz, V. A., Schreiber, D., Mohr, M., and Baltensperger, U.: Identification of the Mass Spectral Signature of Organic Aerosols from Wood Burning Emissions, Environ Sci. Technol., 41, 5770–5777, https://doi.org/10.1021/es062289b, 2007. 
Allan, J. D., Delia, A. E., Coe, H., Bower, K. N., Alfarra, M. R., Jimenez, J. L., Middlebrook, A. M., Drewnick, F., Onasch, T. B., Canagaratna, M. R., Jayne, J. T., and Worsnop, D. R.: A generalised method for the extraction of chemically resolved mass spectra from Aerodyne aerosol mass spectrometer data, J. Aerosol Sci., 35, 909–922, https://doi.org/10.1016/j.jaerosci.2004.02.007, 2004. 
Bougiatioti, A., Stavroulas, I., Kostenidou, E., Zarmpas, P., Theodosi, C., Kouvarakis, G., Canonaco, F., Prévôt, A. S. H., Nenes, A., Pandis, S. N., and Mihalopoulos, N.: Processing of biomass-burning aerosol in the eastern Mediterranean during summertime, Atmos. Chem. Phys., 14, 4793–4807, https://doi.org/10.5194/acp-14-4793-2014, 2014. 
Bruns, E. A., Krapf, M., Orasche, J., Huang, Y., Zimmermann, R., Drinovec, L., Mocnik, G., El-Haddad, I., Slowik, J. G., Dommen, J., Baltensperger, U., and Prévôt, A. S. H.: Characterization of primary and secondary wood combustion products generated under different burner loads, Atmos. Chem. Phys., 15, 2825–2841, https://doi.org/10.5194/acp-15-2825-2015, 2015. 
Download
Short summary
Organic aerosol constitutes one of the major components of atmospheric particulate matter globally and is emitted from various sources. Therefore, identifying and quantifying the sources of organic aerosol accurately is a key task in the field. In this study, we applied a rather novel procedure for an improved source apportionment method (ME-2) to resolve the less meaningful or mixed factors problems for organic aerosol using the traditional method (PMF).