Optimization of the source apportionment solution using the rotational tools in US EPA PMF 5.0 software
Конференцијски прилог (Објављена верзија)
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Positive matrix factorization (PMF) is a dimension reduction method used to model the covariance structures of observable variables in order to impel a smaller number of latent nonnegative factors. It resolves receptor modeling problem, which is based on the chemical mass balance equation (CMB) and may discover hidden patterns in the environmental data, where each extracted factor is accompanied by an actual source of emission. In this paper, PMF source apportionment analyses of fine aerosol fraction (PM2.5 mode) at Belgrade suburban background site, in 2016/17 year, have been performed by processing a data set of 130 PM2.5 mass concentrations and twenty-one elemental concentrations and soot concentrations in each PM2.5 sample (mode). The PM2.5 mass concentrations in collected samples have been determined following SRPS EN 12341:201 procedure, elemental concentrations were obtained by PIXE alanytical technique in the frame of the regional IAEA project, in the Institute of Nuclear Resea...rch, Hungarian Academy of Sciences, and soot concentrations were analyzed by smoke stain reflectometry in accordance with ISO 9835:1993 (E). The EPA PMF program ver 5.0, was used to solve the PMF model. Since the determination of an optimal PMF solution is a strongly heuristic procedure, there is a necessity of finding a more quantitative ways to reduce the arbitrariness of this technique. In order to reduce the range of possible solutions, we have analyzed how the values of model parameters changes as a function of the number of factors. PMF modeling was performed in a robust mode. For the purpose of finding the best fit solution wich minimize the object function Q, we varied the number of factors in the range from 4 to 8. Additionally, influence of rotations are also analyzed in iterative steps by varying FPEAK function in the range -1 to +1 with an increment of 0.5. Obtained results indicated significant role of Q/Qexp ratio analysis for optimal solution choice. In optimization process, number of factors with Q/Qexp ratio less than 1, were rejected as a possible solutions. This paper shows that optimization procedure should include examination of rotational matrix in which the rotational degree of freedom of solution is considered. Solutions with a steep change in their rotational degree of freedom were rejected. Finally, the additional improvement can be done by optimizing the parameters representing the scaled mean value (IM) and the scaled standard deviation (IS) of the each individual column in scaled residual matrix.
Извор:
RAD 2021 : 9th International Conference on Radiation in Various Fields of Research : book of abstracts; June 14-18; Herceg Novi, Montenegro, 2021, 68-Издавач:
- RAD Centre, Niš, Serbia
Напомена:
- IX International Conference on Radiation in Various Fields of Research : RAD 2021 : book of abstracts; June 14-18, 2021; Herceg Novi, Montenegro
Институција/група
VinčaTY - CONF AU - Topalović, Dušan AU - Radenković, Mirjana AU - Tasić, Viša AU - Stanić, Vojislav AU - Božović, Predrag PY - 2021 UR - https://vinar.vin.bg.ac.rs/handle/123456789/11124 AB - Positive matrix factorization (PMF) is a dimension reduction method used to model the covariance structures of observable variables in order to impel a smaller number of latent nonnegative factors. It resolves receptor modeling problem, which is based on the chemical mass balance equation (CMB) and may discover hidden patterns in the environmental data, where each extracted factor is accompanied by an actual source of emission. In this paper, PMF source apportionment analyses of fine aerosol fraction (PM2.5 mode) at Belgrade suburban background site, in 2016/17 year, have been performed by processing a data set of 130 PM2.5 mass concentrations and twenty-one elemental concentrations and soot concentrations in each PM2.5 sample (mode). The PM2.5 mass concentrations in collected samples have been determined following SRPS EN 12341:201 procedure, elemental concentrations were obtained by PIXE alanytical technique in the frame of the regional IAEA project, in the Institute of Nuclear Research, Hungarian Academy of Sciences, and soot concentrations were analyzed by smoke stain reflectometry in accordance with ISO 9835:1993 (E). The EPA PMF program ver 5.0, was used to solve the PMF model. Since the determination of an optimal PMF solution is a strongly heuristic procedure, there is a necessity of finding a more quantitative ways to reduce the arbitrariness of this technique. In order to reduce the range of possible solutions, we have analyzed how the values of model parameters changes as a function of the number of factors. PMF modeling was performed in a robust mode. For the purpose of finding the best fit solution wich minimize the object function Q, we varied the number of factors in the range from 4 to 8. Additionally, influence of rotations are also analyzed in iterative steps by varying FPEAK function in the range -1 to +1 with an increment of 0.5. Obtained results indicated significant role of Q/Qexp ratio analysis for optimal solution choice. In optimization process, number of factors with Q/Qexp ratio less than 1, were rejected as a possible solutions. This paper shows that optimization procedure should include examination of rotational matrix in which the rotational degree of freedom of solution is considered. Solutions with a steep change in their rotational degree of freedom were rejected. Finally, the additional improvement can be done by optimizing the parameters representing the scaled mean value (IM) and the scaled standard deviation (IS) of the each individual column in scaled residual matrix. PB - RAD Centre, Niš, Serbia C3 - RAD 2021 : 9th International Conference on Radiation in Various Fields of Research : book of abstracts; June 14-18; Herceg Novi, Montenegro T1 - Optimization of the source apportionment solution using the rotational tools in US EPA PMF 5.0 software SP - 68 DO - 10.21175/rad.abstr.book.2021.12.3 ER -
@conference{ author = "Topalović, Dušan and Radenković, Mirjana and Tasić, Viša and Stanić, Vojislav and Božović, Predrag", year = "2021", abstract = "Positive matrix factorization (PMF) is a dimension reduction method used to model the covariance structures of observable variables in order to impel a smaller number of latent nonnegative factors. It resolves receptor modeling problem, which is based on the chemical mass balance equation (CMB) and may discover hidden patterns in the environmental data, where each extracted factor is accompanied by an actual source of emission. In this paper, PMF source apportionment analyses of fine aerosol fraction (PM2.5 mode) at Belgrade suburban background site, in 2016/17 year, have been performed by processing a data set of 130 PM2.5 mass concentrations and twenty-one elemental concentrations and soot concentrations in each PM2.5 sample (mode). The PM2.5 mass concentrations in collected samples have been determined following SRPS EN 12341:201 procedure, elemental concentrations were obtained by PIXE alanytical technique in the frame of the regional IAEA project, in the Institute of Nuclear Research, Hungarian Academy of Sciences, and soot concentrations were analyzed by smoke stain reflectometry in accordance with ISO 9835:1993 (E). The EPA PMF program ver 5.0, was used to solve the PMF model. Since the determination of an optimal PMF solution is a strongly heuristic procedure, there is a necessity of finding a more quantitative ways to reduce the arbitrariness of this technique. In order to reduce the range of possible solutions, we have analyzed how the values of model parameters changes as a function of the number of factors. PMF modeling was performed in a robust mode. For the purpose of finding the best fit solution wich minimize the object function Q, we varied the number of factors in the range from 4 to 8. Additionally, influence of rotations are also analyzed in iterative steps by varying FPEAK function in the range -1 to +1 with an increment of 0.5. Obtained results indicated significant role of Q/Qexp ratio analysis for optimal solution choice. In optimization process, number of factors with Q/Qexp ratio less than 1, were rejected as a possible solutions. This paper shows that optimization procedure should include examination of rotational matrix in which the rotational degree of freedom of solution is considered. Solutions with a steep change in their rotational degree of freedom were rejected. Finally, the additional improvement can be done by optimizing the parameters representing the scaled mean value (IM) and the scaled standard deviation (IS) of the each individual column in scaled residual matrix.", publisher = "RAD Centre, Niš, Serbia", journal = "RAD 2021 : 9th International Conference on Radiation in Various Fields of Research : book of abstracts; June 14-18; Herceg Novi, Montenegro", title = "Optimization of the source apportionment solution using the rotational tools in US EPA PMF 5.0 software", pages = "68", doi = "10.21175/rad.abstr.book.2021.12.3" }
Topalović, D., Radenković, M., Tasić, V., Stanić, V.,& Božović, P.. (2021). Optimization of the source apportionment solution using the rotational tools in US EPA PMF 5.0 software. in RAD 2021 : 9th International Conference on Radiation in Various Fields of Research : book of abstracts; June 14-18; Herceg Novi, Montenegro RAD Centre, Niš, Serbia., 68. https://doi.org/10.21175/rad.abstr.book.2021.12.3
Topalović D, Radenković M, Tasić V, Stanić V, Božović P. Optimization of the source apportionment solution using the rotational tools in US EPA PMF 5.0 software. in RAD 2021 : 9th International Conference on Radiation in Various Fields of Research : book of abstracts; June 14-18; Herceg Novi, Montenegro. 2021;:68. doi:10.21175/rad.abstr.book.2021.12.3 .
Topalović, Dušan, Radenković, Mirjana, Tasić, Viša, Stanić, Vojislav, Božović, Predrag, "Optimization of the source apportionment solution using the rotational tools in US EPA PMF 5.0 software" in RAD 2021 : 9th International Conference on Radiation in Various Fields of Research : book of abstracts; June 14-18; Herceg Novi, Montenegro (2021):68, https://doi.org/10.21175/rad.abstr.book.2021.12.3 . .