Correspondence/Rebuttal pubs.acs.org/est
Comment on “Identifying Well Contamination through the use of 3‑D Fluorescence Spectroscopy to Classify Coalbed Methane Produced Water”
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as the shorter wavelength can be more easily absorbed by other nonfluorescence molecular structure. This newly accepted article is a recent case affected by the incorrect region classification, of which the interpretations for EEM spectra in this article are also inappropriate, such as the identified Peak P, M1, M2 and H. Besides, the author related the peaks P and M2 to acetate EEM spectra to study their possible origins. However, interference from fluorescent proteinaceous DOM or compounds containing the fluorescent structure aniline or phenol should also be considered. Identifying indicators of anthropogenic contamination due to well production additives from naturally occurring organic signatures is one of the highlights. Friction reducer, a foaming agent, produced the distinct fluorescent signatures. If the fluorescent structure of the foaming agent could be further discussed, the discoveries in this study would be of more scientific meaning. The FRI method has been extensively cited in the past decade, and resulted in a lot of inaccurate interpretations of EEM in both ES&T and other journals. However, making mistakes is not serious; it is just human. But if a mistake is not a stepping stone, it is a mistake. Here we restate that EEM interpretation with region classification and integration strategy is virtually incorrect, just for avoiding the possible repetitive mistakes in future.
luorescence excitation−emission matrix (EEM) spectroscopy has been extensively used to track and characterize dissolved organic matter (DOM) in both natural and engineered water systems.1 EEM spectra in this article2 were used as the major fingerprint tool to characterize the coalbed methane produced water. The EEM interpretation was mainly according the region classification defined in the fluorescence regional integration (FRI) method, which was developed 10 years ago.3 Using FRI, EEMs are divided into different regions, of which each represent a DOM fraction, including tyrosine and tyrosine-like, tryptophan and tryptophan-like, soluble microbial byproduct-like, humic acid-like, and fulvic acid-like substances.3 This region classification and integration method has been widely recognized and used in DOM evaluations. However, in our recent work, we directly verified the prevalence of multiexcitation-peak fluorophores in EEM using high performance liquid chromatography with fluorescence detector.4 FRI method has been misleading the interpretation of EEM in the past decade, and resulted in a lot of inaccurate interpretations of EEM in both ES&T and other journals. For fluorescence regional integration (FRI), there are three fatal flaws in this strategy. First, FRI technique divides EEM into five or six regions according to standard solutions or literatures,3,5 which is based on empirical evidence rather than theoretical knowledge. Phenol, aniline, tyrosine, tryptophan, Orange-G, and quinones are all of multiexcitation-peaks.4,6 EEM of tryptophan also showed dual-excitation-peaks in that FRI paper.3 Known as Kasha’s rule, emission spectra are usually independent of the excitation wavelength.7 It is the reason for the phenomena of multiexcitation-peaks at the same emission wavelength. In natural or engineered water systems, due to the prevalent existence of multiexcitation-peak fluorophores, it is very likely to integrate fluorescence emitted from one fluorophore into different regions. Second, as described in literature,8 fluorescence intensity at each point (Ex/Em) is the sum of fluorescence from different fluorophores. With regard to intensity and interference (signal/ noise, S/N), fluorescence at the curve peak would be the ideal signal rather than at the curve slope. Thus it is not likely to improve S/N by the integration technique. The peak-picking method is enough to represent the fluorescence intensity of a PARAFAC component. Third, it is not advisable to compare the integration results between different fluorophores. Although different ratios of peak intensities have been calculated, however, results might convey little meaningful or innovative information, because the fluorescence efficiencies of different fluorophores are generally different. As to peaks of the same fluorophore, the peak at shorter excitation wavelength is doomed to be more intensive than that at higher excitation wavelength, which is determined by the energy wavelength. If not, the inner-filter effect occurred, © 2012 American Chemical Society
Wen-Tao Li Zi-Xiao Xu Ai-Min Li*
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State Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China
AUTHOR INFORMATION
Corresponding Author
*Phone: +86 25 83318402; fax: +86 25 86269876; e-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS We thank the support provided by Program for Changjiang Scholars and Innovative Research Team in University, NSFC (51178215) and Jiangsu Nature Science Fund (BK2010006 and BK2011032) P. R. China.
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REFERENCES
(1) Ishii, S. K. L.; Boyer, T. H. Behavior of reoccurring PARAFAC components in fluorescent dissolved organic matter in natural and
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Environmental Science & Technology
Correspondence/Rebuttal
engineered systems: A critical review. Environ. Sci. Technol. 2012, 46 (4), 2006−2017. (2) Dahm, K. G.; Van Straaten, C. M.; Munakata Marr, J.; Drewes, J. E. Identifying well contamination through the use of 3-D fluorescence spectroscopy to classify coalbed methane produced water. Environ. Sci. Technol. 2013, 47, 649−656. (3) Chen, W.; Westerhoff, P.; Leenheer, J. A.; Booksh, K. Fluorescence excitation−emission matrix regional integration to quantify spectra for dissolved organic matter. Environ. Sci. Technol. 2003, 37 (24), 5701−5710. (4) Li, W.-T.; Xu, Z.-X.; Li, A.-M.; Zhou, Q.; Wang, J.-N. HPLC/ HPSEC-FLD with multi-excitation/emission scan for EEM interpretation and DOM analysis. Water R es. DOI:1 0.1016/ j.watres.2012.11.040. (5) Wang, Z.-P.; Zhang, T. Characterization of soluble microbial products (SMP) under stressful conditions. Water Res. 2010, 44 (18), 5499−5509. (6) Cory, R. M.; McKnight, D. M. Fluorescence spectroscopy reveals ubiquitous presence of oxidized and reduced quinones in dissolved organic matter. Environ. Sci. Technol. 2005, 39 (21), 8142−8149. (7) Lakowicz, J. R. Principles of Fluorescence Spectroscopy, 2nd ed.; Springer Science: New York, 2006. (8) Marhaba, T. F.; Bengraine, K.; Pu, Y.; Arago, J. Spectral fluorescence signatures and partial least squares regression: Model to predict dissolved organic carbon in water. J. Hazard. Mater. 2003, 97 (1−3), 83−97.
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