Ying-Ze Tian1, Yan-Qi Huang-Fu1, Guo-Liang Shi1, Xu-Rong Shi1, Bo Han2, Yin-Chang Feng 1

  • 1 State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
  • 2 Tianjin Key Laboratory for Air Traffic Operation Planning and Safety Technology, College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China

Received: May 19, 2016
Revised: July 28, 2016
Accepted: August 28, 2016
Download Citation: ||https://doi.org/10.4209/aaqr.2016.05.0201  

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Cite this article:
Tian, Y.Z., Huang-Fu, Y.Q., Shi, G.L., Shi, X.R., Han, B. and Feng, Y.C. (2016). Accuracy of Advanced and Traditional Three-Way Factor Analysis Models for Determining Source Contributions to Particulate Matter. Aerosol Air Qual. Res. 16: 2512-2522. https://doi.org/10.4209/aaqr.2016.05.0201


  • Scenarios were developed to evaluate performance of three-way factor analysis models.
  • PMF3 performs well with similar source emission pattern and profiles.
  • AAB/ABB models were stable regardless of profiles or emission patterns.
  • AAB/ABB results of ambient data suggest their enhanced ability for estimating sources.



Although three-way factor analysis models can take more information into account, their degree of accuracy must be investigated further. We simulated numerous synthetic datasets to evaluate traditional (PMF3) and advanced three-way models (AAB or ABB). On one hand, scenarios whereby sources share the same profiles but different emission patterns were constructed and introduced into PMF3 and advanced AAB models that can estimate the same source profile matrixes B but different emission pattern matrixes A. On the other hand, datasets with the same emission patterns but different profiles were set to simulate the variability of source profiles and were used to evaluate an advanced ABB model that can estimate the same emission pattern matrix A but different source profile matrixes B. The AAEs of PMF3 under two different conditions ranged from 2.95% to 90.22% and from 2.98% to 90.11%, respectively, while the results of the advanced three-way models were 2.88%–27.51% and 2.89%–29.89%, respectively. We observed that the PMF3 performed well when all sources showed strong emission patterns and source profiles were similar. The application of advanced AAB model was stable under various emission patterns; and ABB model was stable under different variability of source profiles. At the same time, several ambient datasets were estimated by the advanced three-way models. Our findings suggest that the performance of advanced three-way models make full use of spatial or size distribution information to enhance capacities to identify source categories.

Keywords: Three-way factor analysis model; PMF3; Receptor model; Simulation; Source apportionment; ME2

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