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Equal Treatment of Different EEM Data on PARAFAC Modeling Produces Artifact Fluorescent Components That Have Misleading Biogeochemical Consequences Khan M.G. Mostofa,*,† Yuan Jie,‡ Hiroshi Sakugawa,§ and Cong-Qiang Liu† †
Institute of Surface-Earth System Science, Tianjin University, 92 Weijin Road, Tianjin 300072, China Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beitucheng Western Road, Chaoyang District-100029, Beijing, China § Graduate School of Biosphere Science, Department of Environmental Dynamics and Management, Hiroshima University, 1-7-1, Kagamiyama, Higashi-Hiroshima 739-8521, Japan streams and rivers, which gradually degrade during their transportation into lakes, estuaries and oceans.1,2 Conversely, autochthonous humic-like substances (C type), autochthonous humic-like substances (M type) and aromatic amino acids (e.g. tryptophan-like, tyrosine-like or phenylalanine-like) or proteinlike substances of phytoplankton origin are predominant in lakes, estuaries and oceans; they are largely absent in forest streams and subsequent downstream waters.1,2 After successful application of PARAFAC modeling in EEM data analyses in 2003,1 most of EEM researchers, apart from a few studies2,5 equally treat all water samples together collected from diverse water environments (n = 90), such as forest streams, downstream rivers, lakes, wastewaters, and estuarine mixing.1 Similar examples can be referred to all aerosol samples (n = 63), including aerosols from urban, forest, and marine sources,3 and all experimental samples (n = 54) which observed in four separate adsorption experiments.4 In essence, considering the significant variation of allochthonous and autochthonous DOM in a variety of surface waters,1,2,5 it is inconsistent to bin all samples, considering that they were likely altered not only the authentic sources of FDOM components but also produced artifact FDOM components. hree-dimensional fluorescence (excitation−emission maConcurrently, such analyses are certainly misleading to trix, EEM) spectroscopy (EEMS) coupled with parallel ascertain the true biogeochemical facts regarding fluorescent factor (PARAFAC), EEM-PARAFAC modeling is a precise, components and their respective mechanisms. fast, powerful and easy tool that can identify sources, However, EEM researchers have not categorized selective characterize biogeochemical signatures and their transformawater samples when considering all EEM data together, which tion mechanisms of fluorescent dissolved organic matter appears to be for two reasons: the complexity of PARAFAC (FDOM) in surface waters, soil and atmospheric aerosols.1−3 modeling on EEM data analysis leads to a lack of detailed This EEM-PARAFAC modeling is widely applied to ascertain understanding on the sources of various FDOM components characteristic transformations of FDOM components in terms and their transformation mechanisms sourced from various environmental processes. Considering the significance of of either EEM images or fluorescence properties (fluorescence FDOM studies in various research fields, it is thus crucial to peaks and their respective intensities). They are useful reveal the most precise pathway for application and practices of indicators that can identify and characterize many biogeoEEM-PARAFAC analysis on water samples in order to chemical processes, including spatial-temporal-vertical distridetermine the biogeochemical facts of the fluorescent butions and seasonal changes in both fresh and marine waters. components and their transformation mechanisms. To They also include photochemical changes, microbial alterations exemplify this issue at different stages of the watercourse, and diurnal variations in surface water.1,2 Correspondingly, EEM-PARAFAC modeling was conducted on the Kurose River FDOM components are a major fraction of bulk dissolved (Hiroshima, Japan) which subsequently flows into Seto Inland organic matter (DOM), which subsequently plays an Sea. The samples used in this analysis have distinct important role in many biogeochemical processes in surface water, soil, and atmospheric aerosols.1−5 Key FDOM components, such as humic substances (fulvic and humic Received: December 10, 2018 acids) of terrestrial origin predominantly occur in forest
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© XXXX American Chemical Society
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DOI: 10.1021/acs.est.8b06647 Environ. Sci. Technol. XXXX, XXX, XXX−XXX
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Environmental Science & Technology
Figure 1. Fluorescent components identified in the EEM spectra of two forest streams in the Kurose river, Kurose downstream water, inshore and offshore seawater individually as well as all samples together using PARAFAC modeling. Labels of each fluorescent component and their respective peaks are overlaid on the respective fluorescent component.
river water (Figure 1E) was not detected in the fivecomponent model, yet produced one artifact component (Figure 1M). Finally, the degraded terrestrial humic-like substances in inshore and offshore seawater (Figure 1F,E) were entirely missing in the five-component model (Figure 1K−O). In fact, terrestrial humic-like substances from source to offshore location were gradually altered, first at inshore seawater and then highly degraded at offshore seawater, which is the true phenomena in surface water.2 Therefore, any biogeochemical facts and their transformation mechanisms regarding these five fluorescent components are apparently unfeasible and inconsistent when pertaining to individual characteristic water sample. These results suggest that mixing of any diverse water samples on the EEM-PARAFAC modeling would create distinct artifact fluorescent components using the “cut and paste” method from disintegration of various mixed EEM data. Note that PARAFAC modeling is a three-way statistical analytical tool to disintegrate the EEM or fluorescence intensity into trilinear components.1 It is therefore particularly important to input selective EEM data of each characteristic water sample and individually run the PARAFAC model. To ascertain the selective characteristics of the sample-water, EEM researchers could randomly conduct the PARAFAC model on their samples repeatedly to distinguish key differences among samples in terms of fluorescent components and their images. Note that two freshwater samples, six inshore samples and 12 offshore seawater samples are sufficient to run the PARAFAC
characteristics, yet are collected from the same source waters. The sampling locations include two forest streams (n = 10), a downstream location in Kurose River that affected by urban sewerage (n = 12), inshore seawater (0−10 m, n = 12, stations 0−2) and offshore seawater (0−20 m, n = 12, stations 21−23). The models were assessed with individual selective EEM as well as considering all 56 samples together. Results of EEM-PARAFAC modeling on individual characteristic water demonstrated that FDOM components were identified with one (A) and two (B,C) fluorescent components in two respective forest streams, two components in Kurose downstream water (D,E), three components in inshore seawater (F−H) and two components in offshore seawater (I,J) (Figure 1). Conversely, EEM-PARAFAC modeling on all 56 water samples together identified five fluorescent components (Figure 1 K−O). Excitation−emission peak maxima of each fluorescent component and their characteristic sources were depicted on the respective fluorescent component based on reported studies (Figure 1).2 These results precisely indicate that five fluorescent components for all 56 samples were amalgamated and identical, thereby resolving any artifact components for forest stream, downstream river, inshore, and offshore seawater, which do not represent authentic sources or characteristic. For example, stream fluorescent components were not identified for the fivecomponent model; that model instead produced three artifact components (Figure 1K,L,N). Similarly, the sewerageimpacted detergent-like fluorescent component in downstream B
DOI: 10.1021/acs.est.8b06647 Environ. Sci. Technol. XXXX, XXX, XXX−XXX
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Environmental Science & Technology model.2,5 Finally, mixing of all samples together since 20031 until now3,4 did not distinguish the individual sources of FDOM components, thereby missing the overall defining biogeochemical processes and their mechanisms. These results suggest that for future work on this topic, EEM researchers need to use selective EEM data analyses to assess specific characteristics in individual samples.
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AUTHOR INFORMATION
Corresponding Author
*Phone: +8618322560509; e-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS This work was financially supported by the National Natural Science Foundation of China (U1612441) and National Key R & D Program of China (2016YFA0601000) and also by the Key Construction Program of the National “985” Project, Tianjin University, China.
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REFERENCES
(1) Stedmon, C. A.; Markager, S.; Bro, R. Tracing dissolved organic matter in aquatic environments using a new approach to fluorescence spectroscopy. Mar. Chem. 2003, 82, 239−54. (2) Photobiogeochemistry of Organic Matter: Principles and Practices in Water Environments; Mostofa, K. M. G., Yoshioka, T., Mottaleb, A., Vione, D., Eds.; Springer: Berlin Heidelberg, 2013. (3) Chen, Q.; Miyazaki, Y.; Kawamura, K.; Matsumoto, K.; Coburn, S.; Volkamer, R.; Iwamoto, Y.; Kagami, S.; Deng, Y.; Ogawa, S.; Ramasamy, S.; Kato, S.; Ida, A.; Kajii, Y.; Mochida, M. Characterization of chromophoric water-soluble organic matter in urban, forest, and marine aerosols by HR-ToF-AMS analysis and excitation− emission matrix spectroscopy. Environ. Sci. Technol. 2016, 50, 10351− 10360. (4) Phong, D. D.; Hur, J. Using two-dimensional correlation size exclusion chromatography (2D-CoSEC) and EEM-PARAFAC to explore the heterogeneous adsorption behavior of humic substances on nanoparticles with respect to molecular sizes. Environ. Sci. Technol. 2018, 52, 427−435. (5) Mostofa, K. M. G.; Wu, F. C.; Liu, C. Q.; Fang, W. L.; Yuan, J.; Ying, W. L.; Wen, L.; Yi, M. Characterization of Nanming River (Southwestern China) impacted by sewerage pollution using excitation-emission matrix and PARAFAC. Limnology 2010, 11, 217−231.
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DOI: 10.1021/acs.est.8b06647 Environ. Sci. Technol. XXXX, XXX, XXX−XXX
