Journal metrics

Journal metrics

  • IF value: 3.248 IF 3.248
  • IF 5-year value: 3.650 IF 5-year 3.650
  • CiteScore value: 3.37 CiteScore 3.37
  • SNIP value: 1.253 SNIP 1.253
  • SJR value: 1.869 SJR 1.869
  • IPP value: 3.29 IPP 3.29
  • h5-index value: 47 h5-index 47
  • Scimago H index value: 60 Scimago H index 60
Volume 11, issue 2 | Copyright
Atmos. Meas. Tech., 11, 1049-1060, 2018
https://doi.org/10.5194/amt-11-1049-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

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
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
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
Related subject area
Subject: Aerosols | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
Data inversion methods to determine sub-3 nm aerosol size distributions using the particle size magnifier
Runlong Cai, Dongsen Yang, Lauri R. Ahonen, Linlin Shi, Frans Korhonen, Yan Ma, Jiming Hao, Tuukka Petäjä, Jun Zheng, Juha Kangasluoma, and Jingkun Jiang
Atmos. Meas. Tech., 11, 4477-4491, https://doi.org/10.5194/amt-11-4477-2018,https://doi.org/10.5194/amt-11-4477-2018, 2018
A novel method for calculating ambient aerosol liquid water content based on measurements of a humidified nephelometer system
Ye Kuang, Chun Sheng Zhao, Gang Zhao, Jiang Chuan Tao, Wanyun Xu, Nan Ma, and Yu Xuan Bian
Atmos. Meas. Tech., 11, 2967-2982, https://doi.org/10.5194/amt-11-2967-2018,https://doi.org/10.5194/amt-11-2967-2018, 2018
Evaluation of linear regression techniques for atmospheric applications: the importance of appropriate weighting
Cheng Wu and Jian Zhen Yu
Atmos. Meas. Tech., 11, 1233-1250, https://doi.org/10.5194/amt-11-1233-2018,https://doi.org/10.5194/amt-11-1233-2018, 2018
On Aethalometer measurement uncertainties and an instrument correction factor for the Arctic
John Backman, Lauren Schmeisser, Aki Virkkula, John A. Ogren, Eija Asmi, Sandra Starkweather, Sangeeta Sharma, Konstantinos Eleftheriadis, Taneil Uttal, Anne Jefferson, Michael Bergin, Alexander Makshtas, Peter Tunved, and Markus Fiebig
Atmos. Meas. Tech., 10, 5039-5062, https://doi.org/10.5194/amt-10-5039-2017,https://doi.org/10.5194/amt-10-5039-2017, 2017
Aethalometer multiple scattering correction Cref for mineral dust aerosols
Claudia Di Biagio, Paola Formenti, Mathieu Cazaunau, Edouard Pangui, Nicolas Marchand, and Jean-François Doussin
Atmos. Meas. Tech., 10, 2923-2939, https://doi.org/10.5194/amt-10-2923-2017,https://doi.org/10.5194/amt-10-2923-2017, 2017
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.
Publications Copernicus
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).
Organic aerosol constitutes one of the major components of atmospheric particulate matter...
Citation
Share