- 期刊
- OpenAccess
Effect of Uncertainty on Source Contributions from the Positive Matrix Factorization Model for a Source Apportionment Study
並列摘要
Uncertainty estimation plays an important role in source apportionment models such as the positive matrix factorization (PMF) model. In this study, synthetic datasets were generated and analyzed using PMF with specified uncertainties at different levels to investigate the impact of uncertainty inputs on the results of PMF model, as well as the benefits and risks of emphasizing on certain species. The results showed that: (1) uncertainties for the PMF model should be estimated based on characteristics of the dataset being analyzed; (2) emphasizing on correct tracers will improved model performance; and (3) emphasizing on unsuitable tracers may lead to disruptive consequences that might not be captured by the Q metric. Tests were also performed on collected ambient PM_(2.5) samples and similar conclusions were drawn: emphasizing on correct tracers was shown to improve the separation of important source categories from mixed sources. When emphasizing on incorrect tracers, a counterfeit factor of Fe industrial source was extracted, which are inconsistent with field observations. Results from this study provide insights on how uncertainties should be estimated for the PMF model.
被引用紀錄
延伸閱讀
- Li, Y. Q., & Yin, B. S. (2014). Conservation Laws and Self-Consistent Sources for an Integrable Lattice Hierarchy Associated with a Three-by-Three Discrete Matrix Spectral Problem. Abstract and Applied Analysis, 2014(), 301-306-231. https://doi.org/10.1155/2014/235159
- 龔千芬（2017）。On Partial Multiple Correlation Coefficients in Managerial Studies -- The Combined Application of Control Variable and Software。人力資源管理學報，17(2)，73-92。https://doi.org/10.6147/JHRM.2017.1702.04
- Jin, G. (2014). A Valuation Model of Financial Derivatives under the Influence of Multiple Correlated Factors with Sudden and Rare Uncertainty. 財務金融學刊, 22(4), 37-53. https://doi.org/10.6545/JFS.2014.22(4).2
- Perkgoz, C., Sakawa, M., Kato, K., & Katagiri, H. (2005). An Interactive Fuzzy Satisficing Method for Multiobjective Stochastic Integer Programming Problems through a Probability Maximization Model. Asia Pacific Management Review, 10(1), 29-35. https://doi.org/10.6126/APMR.2005.10.1.04
- Luo, R., & He, L. (2014). The Control and Modified Projective Synchronization of a Class of 2,3,4-Dimensional (Chaotic) Systems with Parameter and Model Uncertainties and External Disturbances Via Adaptive Control. Chinese Journal of Physics, 52(2), 830-851. https://doi.org/10.6122/CJP.52.830