A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter

Xiang Dong Qing; Lin Da Yin; Xiao Hua Zhang; Yi Huang; Ling Xu; Min He

doi:doi:10.11648/j.sjac.20200803.12

| Peer-Reviewed

A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter

Xiang Dong Qing, Lin Da Yin, Xiao Hua Zhang, Yi Huang, Ling Xu, Min He

Published in Science Journal of Analytical Chemistry (Volume 8, Issue 3)

Received: 16 June 2020 Accepted: 3 July 2020 Published: 13 July 2020

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

A new receptor model based on the alternating trilinear decomposition followed by a score matrix reconstruction (ATLD-SMR) was developed for the source apportionment of urban PM10 for the first time. First, simulated three-way data arrays of gas chromatography-mass spectrometry (GC-MS) were used to verify the feasibility of the ATLD-SMR method. Then, PM10 samples (receptor) at five locations and TSP samples of ten pollution sources were collected during July and August, 2018 in Loudi City, China. The collected samples were measured by GC-MS. PAHs were used as tracers and their concentrations were accurately obtained by the ATLD-SMR analysis of GC-MS data of these samples after the problems of GC-MS including baseline drift, retention-time shift and unexpected peaks overlapping were successfully resolved. The highest concentrations of individual PAH in these samples were for phenanthrene and benzo [a] pyrene (40.76 ng m^-3 and 39.63 ng m^-3 in Liangang steel-making workshop, respectively). Last, a relative contribution matrix of the source to the receptor was estimated by the ATLD-SMR method. The proposed method was employed to apportion the source contributions to PM10 particles at five locations and reasonable results were obtained, thus presenting a promising tool for source apportionment of complex ambient particulate matter.

Published in	Science Journal of Analytical Chemistry (Volume 8, Issue 3)
DOI	10.11648/j.sjac.20200803.12
Page(s)	93-106
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

Source Apportionment, PM10, PAHs, GC-MS, ATLD-SMR

References

[1]	Q. Mu, M. Shiraiwa, M. Octaviani, N. Ma, A. Ding, H. Su, G. Lammel, U. Pöschl, Y. Cheng, Temperature effect on phase state and reactivity controls atmospheric multiphase chemistry and transport of PAHs, Sci. Adv. 4 (2018) 7314-7321.
[2]	Y. Zhang, H. Zheng, L. Zhang, Z. Z. Zhang, X. L. Xing, S. H. Qi, Fine particle-bound polycyclic aromatic hydrocarbons (PAHs) at an urban site of Wuhan, central China: Characteristics, potential sources and cancer risks apportionment, Environ. Pollut. 246 (2019): 319-327.
[3]	X. W. Li, X. Zhang, Z. Q. Zhang, L. Y. Han, D. P. Gong, J. Li, T. Wang, Y. H. Wang, S. Gao, H. W. Duan, F. L. Kong, Air pollution exposure and immunological and systemic inflammatory alterations among schoolchildren in China, Sci. Total Environ. 657 (2019) 1304-1310.
[4]	D. G. Streets, S. Gupta, S. T. Waldhoff, M. Q. Wang, T. C. Bond, Y. Bo, Black carbon emissions in China, Atmos. Environ. 35 (2001) 4281-4296.
[5]	S. Reis, R. W. Pinder, M. Zhang, G. Lijie, M. A. Sutton, Reactive nitrogen in atmospheric emission inventories, J. Geophys. Res: Atmos. 9 (2009) 7657-7677.
[6]	M. J. Kleeman, G. R. Cass, A. Eldering, Modeling the airborne particle complex as a source-oriented external mixture, J. Geophys. Res: Atmos. 102 (1997) 21355-21372.
[7]	P. K. Hopke, Recent developments in receptor modeling, J. Chemom. 17 (2003) 255-265.
[8]	C. A. Belis, D. Pernigotti, F. Karagulian, G. Pirovano, B. R. Larsen, M. Gerboles, P. K. Hopke, A new methodology to assess the performance and uncertainty of source apportionment models in intercomparison exercises, Atmos. Environ. 119 (2015) 35-44.
[9]	C. A. Belis, F. Karagulian, F. Amato, M. Almeida, P. Artaxo, D. C. S. Beddows, V. Bernardoni, M. C. Bove, S. Carbone, D. Cesari, D. Contini, E. Cuccia, E. Diapouli, K. Eleftheriadis, O. Favez, I. El Haddad, R. M. Harrison, S. Hellebust, J. Hovorka, E. Jang, H. Jorquera, T. Kammermeier, M. Karl, F. Lucarelli, D. Mooibroek, S. Nava, J. K. Nøjgaard, P. Paatero, M. Pandolfi, M. G. Perrone, J. E. Petit, A. Pietrodangelo, P. Pokorná, P. Prati, A. S. H. Prevot, U. Quass, X. Querol, D. Saraga, J. Sciare, A. Sfetsos, G. Valli, R. Vecchi, M. Vestenius, E. Yubero, P. K. Hopke, A new methodology to assess the performance and uncertainty of source apportionment models II: The results of two European intercomparison exercises, Atmos. Environ. 123 (2015) 240-250.
[10]	S. Wold, K. Esbensen, P. Geladi, Principal component analysis, Chemom. Intell. Lab. Syst. 2 (1987) 37-52.
[11]	W. C. Ma, L. Y. Tai, Z. Qiao, L. Zhong, Z. Wang, K. X. Fu, G. Y. Chen, Contamination source apportionment and health risk assessment of heavy metals in soil around municipal solid waste incinerator: A case study in North China, Sci. Total Environ. 631–632 (2018) 348-351.
[12]	B. Wu, D. Zhao, Y. Zhang, X. Zhang, S. Cheng, Multivariate statistical study of organic pollutants in Nanjing reach of Yangtze River, J. Hazard. Mater. 169 (2009) 1093-1098.
[13]	I. Salim, R. U. Sajjad, M. C. Paule-Mercado, S. A. Memon, B. Y. Lee, C. Sukhbaatar, C. H. Lee, Comparison of two receptor models PCA-MLR and PMF for source identification and apportionment of pollution carried by runoff from catchment and sub-watershed areas with mixed land cover in South Korea, Sci. Total Environ. 663 (2019) 764-775.
[14]	I. Stanimirova, R. Tauler, B. Walczak, A comparison of positive matrix factorization and the weighted multivariate curve resolution method. Application to environmental data, Environ. Sci. Tech. 45 (2011) 10102-10110.
[15]	M. S. Miller, S. K. Friedlander, G. M. Hidy, A chemical element balance for the Pasadena aerosol, J. Colloid Interf. Sci. 39 (1972) 165-176.
[16]	J. A. Cooper, Review of the chemical receptor model of aerosol source apportionment, in: Atmospheric Aerosol, American Chemical Society, 1981, pp. 75-87.
[17]	H. Wallace, N. P. Sanchez, J. Flynn, M. H. Erickson, Source apportionment of particulate matter and trace gases near a major refinery near the Houston Ship Channel, Atmos. Environ. 173 (2018) 16-29.
[18]	S. M. Mudge, C. Bravo-Linares, L. Ovando-Fuentealba, J. P. Pinaud-Mendoza, A comparison between three unmixing models for source apportionment of PM2.5 using alkanes in air from Southern Chile, Environ. Forensics 18 (2017) 226-240.
[19]	Z. P. Zhao, S. Lv, Y. H. Zhang, Q. B. Zhao, L. Shen, S. Xu, J. Q. Yu, J. W. Hou, C. Y. Jin, Characteristics and source apportionment of PM2.5 in Jiaxing, China, Environ. Sci. Pollut. Res. 26 (2019) 7497-7511.
[20]	D. A. Olson, G. A. Norris, M. S. Landis, A. F. Vette, Chemical characterization of ambient particulate matter near the world trade center: elemental carbon, organic carbon, and mass reconstruction, Environ. Sci. Tech. 38 (2004) 4465.
[21]	G. R. Cass, Organic molecular tracers for particulate air pollution sources, Trends Anal. Chem. 17 (1998) 356-366.
[22]	M. R. Alcaraz, O. Monago-Maraña, H. C. Goicoechea, A. Muñoz de la Peña, Four- and five-way excitation-emission luminescence-based data acquisition and modeling for analytical applications. A review, Anal. Chim. Acta 1083 (2019) 41-57.
[23]	X. D. Qing, H. L. Wu, X. H. Zhang, Y. Li, H. W. Gu, R. Q. Yu, A novel fourth-order calibration method based on alternating quinquelinear decomposition algorithm for processing high performance liquid chromatography-diode array detection- kinetic-pH data of naptalam hydrolysis, Anal. Chim. Acta 861 (2015) 12-24.
[24]	S. M. Azcarate, A. de Araújo Gomes, A. Muñoz de la Peña, H. C. Goicoechea, Modeling second-order data for classification issues: Data characteristics, algorithms, processing procedures and applications, Trends Anal. Chem. 107 (2018) 151-168.
[25]	G. L. Shi, X. Peng, Y. Q. Huangfu, W. Wang, J. Xu, Y. Z. Tian, Y. C. Feng, C. E. Ivey, A. G. Russell, Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data, Atmos. Environ. 160 (2017) 89-96.
[26]	A. A. Karanasiou, P. A. Siskos, K. Eleftheriadis, Assessment of source apportionment by Positive Matrix Factorization analysis on fine and coarse urban aerosol size fractions, Atmos. Environ. 43 (2009) 3385-3395.
[27]	M. H. Nie, X. Huang, C. X. Yan, Y. Yang, J. L. Zhou, M. Liu, Fluorescence characterization of fractionated colloids in different sources of waters based on PARAFAC and SOM, Acta Scien. Circum. 38 (2018) 3672-3681.
[28]	H. L. Wu, M. Shibukawa, K. Oguma, An alternating trilinear decomposition algorithm with application to calibration of HPLC–DAD for simultaneous determination of overlapped chlorinated aromatic hydrocarbons, J. Chemom. 12 (1998) 1-26.
[29]	Z. Liu, H. L. Wu, L. X. Xie, Y. Hu, H. Fang, X. D. Sun, T. Wang, R. Xiao, R. Q. Yu, Chemometrics-enhanced liquid chromatography-full scan-mass spectrometry for interference-free analysis of multi-class mycotoxins in complex cereal samples, Chemom. Intell. Lab. Syst. 160 (2017) 125-138.
[30]	Y. Zhang, H. L. Wu, A. L. Xia, L. H. Hu, H. F. Zou, R. Q. Yu, Trilinear decomposition method applied to removal of three-dimensional background drift in comprehensive two-dimensional separation data, J. Chromatogr. A 1167 (2007) 178-183.
[31]	M. Li, X. R. Wang, Peak alignment of gas chromatography–mass spectrometry data with deep learning, J. Chromatogr. A (2019).
[32]	T. B. Yang, P. Yan, M. He, L. Hong, R. Pei, Z. M. Zhang, L. Z. Yi, X. Y. Yuan, Application of Subwindow Factor Analysis and Mass Spectral information for accurate alignment of non-targeted metabolic profiling, J. Chromatogr. A 1563 (2018) 162-170.
[33]	S. Abou-el-karam, J. Ratel, N. Kondjoyan, C. Truan, E. Engel, Marker discovery in volatolomics based on systematic alignment of GC-MS signals: Application to food authentication, Anal. Chim. Acta 991 (2017) 58-67.
[34]	Y. J. Yu, H. L. Wu, J. F. Niu, J. Zhao, Y. N. Li, C. Kang, R. Q. Yu, A novel chromatographic peak alignment method coupled with trilinear decomposition for three dimensional chromatographic data analysis to obtain the second-order advantage, Analyst, 138 (2012) 627-634.

Cite This Article

Plain Text BibTeX RIS

APA Style

Xiang Dong Qing, Lin Da Yin, Xiao Hua Zhang, Yi Huang, Ling Xu, et al. (2020). A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter. Science Journal of Analytical Chemistry, 8(3), 93-106. https://doi.org/10.11648/j.sjac.20200803.12

Copy | Download

ACS Style

Xiang Dong Qing; Lin Da Yin; Xiao Hua Zhang; Yi Huang; Ling Xu, et al. A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter. Sci. J. Anal. Chem. 2020, 8(3), 93-106. doi: 10.11648/j.sjac.20200803.12

Copy | Download

AMA Style

Xiang Dong Qing, Lin Da Yin, Xiao Hua Zhang, Yi Huang, Ling Xu, et al. A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter. Sci J Anal Chem. 2020;8(3):93-106. doi: 10.11648/j.sjac.20200803.12

Copy | Download

@article{10.11648/j.sjac.20200803.12,
  author = {Xiang Dong Qing and Lin Da Yin and Xiao Hua Zhang and Yi Huang and Ling Xu and Min He},
  title = {A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter},
  journal = {Science Journal of Analytical Chemistry},
  volume = {8},
  number = {3},
  pages = {93-106},
  doi = {10.11648/j.sjac.20200803.12},
  url = {https://doi.org/10.11648/j.sjac.20200803.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjac.20200803.12},
  abstract = {A new receptor model based on the alternating trilinear decomposition followed by a score matrix reconstruction (ATLD-SMR) was developed for the source apportionment of urban PM10 for the first time. First, simulated three-way data arrays of gas chromatography-mass spectrometry (GC-MS) were used to verify the feasibility of the ATLD-SMR method. Then, PM10 samples (receptor) at five locations and TSP samples of ten pollution sources were collected during July and August, 2018 in Loudi City, China. The collected samples were measured by GC-MS. PAHs were used as tracers and their concentrations were accurately obtained by the ATLD-SMR analysis of GC-MS data of these samples after the problems of GC-MS including baseline drift, retention-time shift and unexpected peaks overlapping were successfully resolved. The highest concentrations of individual PAH in these samples were for phenanthrene and benzo [a] pyrene (40.76 ng m-3 and 39.63 ng m-3 in Liangang steel-making workshop, respectively). Last, a relative contribution matrix of the source to the receptor was estimated by the ATLD-SMR method. The proposed method was employed to apportion the source contributions to PM10 particles at five locations and reasonable results were obtained, thus presenting a promising tool for source apportionment of complex ambient particulate matter.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter
AU  - Xiang Dong Qing
AU  - Lin Da Yin
AU  - Xiao Hua Zhang
AU  - Yi Huang
AU  - Ling Xu
AU  - Min He
Y1  - 2020/07/13
PY  - 2020
N1  - https://doi.org/10.11648/j.sjac.20200803.12
DO  - 10.11648/j.sjac.20200803.12
T2  - Science Journal of Analytical Chemistry
JF  - Science Journal of Analytical Chemistry
JO  - Science Journal of Analytical Chemistry
SP  - 93
EP  - 106
PB  - Science Publishing Group
SN  - 2376-8053
UR  - https://doi.org/10.11648/j.sjac.20200803.12
AB  - A new receptor model based on the alternating trilinear decomposition followed by a score matrix reconstruction (ATLD-SMR) was developed for the source apportionment of urban PM10 for the first time. First, simulated three-way data arrays of gas chromatography-mass spectrometry (GC-MS) were used to verify the feasibility of the ATLD-SMR method. Then, PM10 samples (receptor) at five locations and TSP samples of ten pollution sources were collected during July and August, 2018 in Loudi City, China. The collected samples were measured by GC-MS. PAHs were used as tracers and their concentrations were accurately obtained by the ATLD-SMR analysis of GC-MS data of these samples after the problems of GC-MS including baseline drift, retention-time shift and unexpected peaks overlapping were successfully resolved. The highest concentrations of individual PAH in these samples were for phenanthrene and benzo [a] pyrene (40.76 ng m-3 and 39.63 ng m-3 in Liangang steel-making workshop, respectively). Last, a relative contribution matrix of the source to the receptor was estimated by the ATLD-SMR method. The proposed method was employed to apportion the source contributions to PM10 particles at five locations and reasonable results were obtained, thus presenting a promising tool for source apportionment of complex ambient particulate matter.
VL  - 8
IS  - 3
ER  -

Copy | Download

Author Information

Xiang Dong Qing

College of Materials and Chemical Engineering, Hunan City University, Yiyang, China
Lin Da Yin

School of Materials and Environmental Engineering, Hunan University of Humanities, Science and Technology, Loudi, China
Xiao Hua Zhang

Food and Bioengineering College, Xuchang University, Xuchang, China
Yi Huang

College of Materials and Chemical Engineering, Hunan City University, Yiyang, China
Ling Xu

College of Materials and Chemical Engineering, Hunan City University, Yiyang, China
Min He

School of Chemical Engineering, Xiangtan University, Xiangtan, China

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Xiang Dong Qing, Lin Da Yin, Xiao Hua Zhang, Yi Huang, Ling Xu, et al. (2020). A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter. Science Journal of Analytical Chemistry, 8(3), 93-106. https://doi.org/10.11648/j.sjac.20200803.12

Copy | Download

ACS Style

Xiang Dong Qing; Lin Da Yin; Xiao Hua Zhang; Yi Huang; Ling Xu, et al. A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter. Sci. J. Anal. Chem. 2020, 8(3), 93-106. doi: 10.11648/j.sjac.20200803.12

Copy | Download

AMA Style

Xiang Dong Qing, Lin Da Yin, Xiao Hua Zhang, Yi Huang, Ling Xu, et al. A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter. Sci J Anal Chem. 2020;8(3):93-106. doi: 10.11648/j.sjac.20200803.12

Copy | Download

@article{10.11648/j.sjac.20200803.12,
  author = {Xiang Dong Qing and Lin Da Yin and Xiao Hua Zhang and Yi Huang and Ling Xu and Min He},
  title = {A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter},
  journal = {Science Journal of Analytical Chemistry},
  volume = {8},
  number = {3},
  pages = {93-106},
  doi = {10.11648/j.sjac.20200803.12},
  url = {https://doi.org/10.11648/j.sjac.20200803.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjac.20200803.12},
  abstract = {A new receptor model based on the alternating trilinear decomposition followed by a score matrix reconstruction (ATLD-SMR) was developed for the source apportionment of urban PM10 for the first time. First, simulated three-way data arrays of gas chromatography-mass spectrometry (GC-MS) were used to verify the feasibility of the ATLD-SMR method. Then, PM10 samples (receptor) at five locations and TSP samples of ten pollution sources were collected during July and August, 2018 in Loudi City, China. The collected samples were measured by GC-MS. PAHs were used as tracers and their concentrations were accurately obtained by the ATLD-SMR analysis of GC-MS data of these samples after the problems of GC-MS including baseline drift, retention-time shift and unexpected peaks overlapping were successfully resolved. The highest concentrations of individual PAH in these samples were for phenanthrene and benzo [a] pyrene (40.76 ng m-3 and 39.63 ng m-3 in Liangang steel-making workshop, respectively). Last, a relative contribution matrix of the source to the receptor was estimated by the ATLD-SMR method. The proposed method was employed to apportion the source contributions to PM10 particles at five locations and reasonable results were obtained, thus presenting a promising tool for source apportionment of complex ambient particulate matter.},
 year = {2020}
}

Copy | Download

TY  - JOUR
T1  - A New Receptor Model Based on the Alternating Trilinear Decomposition Followed by a Score Matrix Reconstruction for Source Apportionment of Ambient Particulate Matter
AU  - Xiang Dong Qing
AU  - Lin Da Yin
AU  - Xiao Hua Zhang
AU  - Yi Huang
AU  - Ling Xu
AU  - Min He
Y1  - 2020/07/13
PY  - 2020
N1  - https://doi.org/10.11648/j.sjac.20200803.12
DO  - 10.11648/j.sjac.20200803.12
T2  - Science Journal of Analytical Chemistry
JF  - Science Journal of Analytical Chemistry
JO  - Science Journal of Analytical Chemistry
SP  - 93
EP  - 106
PB  - Science Publishing Group
SN  - 2376-8053
UR  - https://doi.org/10.11648/j.sjac.20200803.12
AB  - A new receptor model based on the alternating trilinear decomposition followed by a score matrix reconstruction (ATLD-SMR) was developed for the source apportionment of urban PM10 for the first time. First, simulated three-way data arrays of gas chromatography-mass spectrometry (GC-MS) were used to verify the feasibility of the ATLD-SMR method. Then, PM10 samples (receptor) at five locations and TSP samples of ten pollution sources were collected during July and August, 2018 in Loudi City, China. The collected samples were measured by GC-MS. PAHs were used as tracers and their concentrations were accurately obtained by the ATLD-SMR analysis of GC-MS data of these samples after the problems of GC-MS including baseline drift, retention-time shift and unexpected peaks overlapping were successfully resolved. The highest concentrations of individual PAH in these samples were for phenanthrene and benzo [a] pyrene (40.76 ng m-3 and 39.63 ng m-3 in Liangang steel-making workshop, respectively). Last, a relative contribution matrix of the source to the receptor was estimated by the ATLD-SMR method. The proposed method was employed to apportion the source contributions to PM10 particles at five locations and reasonable results were obtained, thus presenting a promising tool for source apportionment of complex ambient particulate matter.
VL  - 8
IS  - 3
ER  -

Copy | Download