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Conservative behavior of fluorescence EEM-PARAFAC components in resin fractionation processes and its applicability for characterizing dissolved organic matter
Accepted Manuscript Conservative behavior of fluorescence EEM-PARAFAC components in resin fractionation processes and its applicability for characterizing dissolved organic matter Wei He, Jin Hur PII:
S0043-1354(15)30093-2
DOI:
10.1016/j.watres.2015.06.044
Reference:
WR 11386
To appear in:
Water Research
Received Date: 13 May 2015 Revised Date:
23 June 2015
Accepted Date: 26 June 2015
Please cite this article as: He, W., Hur, J., Conservative behavior of fluorescence EEM-PARAFAC components in resin fractionation processes and its applicability for characterizing dissolved organic matter, Water Research (2015), doi: 10.1016/j.watres.2015.06.044. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Conservative behavior of fluorescence EEM-PARAFAC components in resin
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fractionation processes and its applicability for characterizing dissolved organic matter
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Wei He and Jin Hur*
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Department of Environment and Energy, Sejong University, Seoul, South Korea, 143-747
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Revised and Resubmitted to Water Research, June, 2015
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*Corresponding author. Tel.:+82-2-3408-3826; fax:+82-2-3408-4320.
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E-mail addresses:[email protected] (J. Hur)
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Abstract
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In this study, the applicability of the fluorescence excitation-emission matrix combined with
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parallel factor analysis (EEM-PARAFAC) was verified for resin fractionation processes, in
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which bulk dissolved organic matter (DOM) is separated into several fractions presumably
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having similar chemical structures. Here, four PARAFAC components, including three humic-
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like and one protein-like components, were identified from the EEMs of all DOM samples
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through fractionation procedures and the subtracted EEMs between before and after resins for
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different DOM sources (effluent, limnic, and riverine). The PARAFAC components exhibited
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conservative behavior upon resin fractionation, as indicated by the minimal difference in the
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PARAFAC components retained on resins calculated based on the direct subtraction of the
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components and the subtracted EEMs. The conservative behavior of PARAFAC components
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was more obvious compared with other fluorescent DOM (FDOM) indicators derived from peak-
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picking and fluorescence regional integration (FRI) methods. Humic-like components were more
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insensitive to resin fractionation than protein-like component. No consistency was found in the
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relative abundances of the PARAFAC components for the same resin fractions with different
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DOM sources, suggesting that the FDOM composition is more affected by DOM sources rather
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than by the resin fractions. Our study demonstrated that EEM-PARAFAC coupled with resin
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fractionation could provide detailed information on DOM by quantitatively comparing the
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individual PARAFAC components within different resin fractions.
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Key words: Natural organic matter; Resin fractionation; Parallel factor analysis (PARAFAC);
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Fluorescence regional integration; Spectral subtraction.
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1. Introduction Fluorescence excitation-emission matrix combined with parallel factor analysis (EEMPARAFAC) has become a popular tool for probing the fate of dissolved organic matter (DOM)
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and understanding its environmental behaviors in natural and engineered systems (Borisover et
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al., 2009; Ishii and Boyer, 2012; Stedmon et al., 2003; Yang et al., 2015). PARAFAC modeling
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makes it possible to extract dissimilar fluorescent components with minimum residuals from a
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given EEM dataset (Stedmon et al., 2003). The identified components have been successfully
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applied for exploring the biogeochemical dynamics of fluorescent DOM (FDOM) in aquatic
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ecosystems, and the temporal and spatial variations. The individual components have their own
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sources and characteristics, displaying different sensitivities to varying environmental factors
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like light, salinity, pH, temperature, and microorganisms (Borisover et al., 2009; Jørgensen et al.,
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2011; Meng et al., 2013; Saadi et al., 2006; Yamashita et al., 2008; Yang and Hur, 2014; Zhang
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et al., 2009). They also have great potential for assessing water quality and the efficiency of
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DOM removal during treatment systems (Cohen et al., 2014; Gone et al., 2009; Henderson et al.,
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2009; Murphy et al., 2011; Seredyńska-Sobecka et al., 2011).
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To date, several techniques have been suggested for fluorescence data decomposition,
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which included PARAFAC, fluorescence regional integration (FRI), principal component
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analysis (PCA), and self-organizing map (SOM). Among those, PARAFAC and FRI have been
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the most popularly used due to the easy quantification of different FDOM components. The
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interpretation and source assignment of PARAFAC components were primarily based on a
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traditional peak-picking method (Coble, 1996) in which different fluorescence peaks were
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selected from several defined wavelength ranges of EEM. The FRI method has been often
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utilized to differentiate different FDOM components within an EEM, in which EEM was divided
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into several assigned regions and their integrated regional volumes under the EEM surface were
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calculated and treated as the individual FDOM components (Chen et al., 2003; Xue et al., 2012;
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Zhou et al., 2014), although it is often criticized for the physical meaningfulness of the
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integration.
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Resin fractionation has been long used as a DOM characterizing method to obtain
relatively homogeneous fractions from a bulk DOM inherently consisting of heterogeneous
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chemical structures and functional groups (He et al., 2011; Schwede-Thomas et al., 2005; Wu et
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al., 2003; Xue et al., 2012; Zhou et al., 2014). The conventional practices for resin fractionation
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involve the use of acid and base solutions for pH control to retain the desired DOM fractions on
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resins or to elute them from the resins (Imai et al., 2001; Thurman and Malcolm, 1981). Recently,
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a new resin fractionation method was proposed to offer more stable DOM fractions with respect
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to the chemical properties without the pH manipulation (Kim and Dempsey, 2012). Through
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both resin fractionation processes, DOM can be separated into hydrophobics (HPO) and/or
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transphilics (TPI), and hydrophilics (HPI), and further into acidic, basic, and neutral fractions
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(Chen et al., 2003; Imai et al., 2001; Kim and Dempsey, 2012; Li et al., 2014). In general,
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dissolved organic carbon (DOC) and ultraviolet (UV) absorbance have been employed to track
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and quantify the DOM fractions retained on resins and/or eluted from the resins (Imai et al.,
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2002; Kim and Dempsey, 2012). However, such DOM parameters represent only the bulk
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quantity of DOM, providing limited information on the chemical composition of resin fractions
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(Kim and Dempsey, 2012). Addition of other DOM analyses would be more beneficial for
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acquiring detailed information on the fraction’s characteristics.
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In resin fractionation, the subtraction of DOM quantity parameters (i.e. DOC and UV) between before and after resins is simply applied to estimate the fractions retained on resins
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based on mass balance (Imai et al., 2001; Imai et al., 2002; Imai et al., 2003; Kim and Dempsey,
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2012). In the same manner, the spectral subtraction for the fluorescent components distributed
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over EEM could be applied to track the FDOM through the resin fractionation. However, no
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effort has been made to extend the simple subtraction approach into EEM-PARAFAC for
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characterizing different DOM fractions obtained from resin fractionation processes. In fact, this
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is an attempt to test the feasibility of EEM-PARAFAC for tracking DOM in fractionation
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systems where DOM constantly interacts with the solid phase (e.g., resins). There may be two
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approaches available to utilize EEM-PARAFAC to track FDOM in resin fractionation processes.
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One is to obtain the PARAFAC components based on the subtracted EEMs between before and
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after resin (Patra and Mishra, 2002) based on the Beer-Lambert law. The other relies on the
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direct subtraction of the PARAFAC components between before and after resins. It is not clear
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whether or not the two different subtraction approaches would produce the same results for the
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DOM retained on resins.
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In an effort to verify the quantitative applicability of fluorescence EEM-PARAFAC for
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resin fractionation, the two types of resin fractionation methods were employed in this study to
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characterize aquatic DOM with diverse sources (i.e., effluent, limnic, and riverine DOM). The
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main objectives of this study were 1) to verify the applicability of EEM-PARAFAC for
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characterizing DOM in resin fractionation processes, and 2) to compare the differences in the
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FDOM composition of DOM resin fractions among different sources via EEM-PARAFAC.
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2. Materials and methods
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2.1. Sample collection and pretreatment
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Effluent, limnic, and riverine waters were collected three times from a water reclamation
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center in Seoul, Lake Uiam in Gangwon province, and Han River in Seoul, Korea, respectively,
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during the period between November 2014 and January 2015. The in-situ water quality
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parameters of the samples are shown in the supplementary materials (Table S1). The samples
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were filtered through a pre-washed 0.45 µm membrane filter (cellulose acetate, Toyo Roshi
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Kaisha, Ltd., Japan) for further fractionation and analyses.
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2.2. Rein fractionation procedures
The two frequently used DOM fractionation procedures, named Imai’s (Imai et al., 2001)
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and Kim’s (Kim and Dempsey, 2008; 2012) methods, were adopted for this study (Fig. 1). In
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Imai’s method, 1.0 L of DOM sample was fractionated into HPO acids (HPO(a)), HPO neutrals
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(HPO(n)), organic bases (i.e. HPO bases, HPI bases, and TPI bases; HPO/HPI/TPI(b)), TPI/HPI
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acids (TPI/HPI(a)), and TPI/HPI neutrals (TPI/HPI(n)) (Fig. 1a). Before the fractionation, the pH
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of samples was adjusted to 2 by adding concentrated HCl solution. HPO(a) and the HPO(n) were
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retained by the first column (7 cm depth, inner diameter 1.8 cm) packed with nonionic Amberlite
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DAX-8 resin (20-60 mesh), and the retained fraction was subsequently eluted by 100 mL of 0.1
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N NaOH. The DAX-8 resin, poly(methyl methacrylate) resin, is known to have nearly the same
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capability of capturing humic substances (HS) as XAD-8 resin (Peuravuori et al., 2002). It was
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previously demonstrated that the recovery rate of HPO(a) by the alkaline solution was
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approximately 100% (Kim and Dempsey, 2012; Thurman and Malcolm, 1981). HPO/HPI/TPI(b)
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were retained by the second column filled with strong cation-exchange resin (Bio-Rad AG-MP-
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50, 50–100 mesh). TPI/HPI(a) were adsorbed onto strong anion-exchange resin (Bio-Rad AG-
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MP-1, 50–100 mesh) in the third column (Fig. 1a). The surface flow rate was maintained at a rate
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of 4 L min-1 m-2. The initial DOM samples and the DOM fractions eluted from each column (i.e.,
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IF0: NaOH-eluted fraction, and IF1, IF2, and IF3 refer to the DOM fractions eluted from XAD-8,
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AG-MP-50, and AG-MP-1 in Fig. 1a, respectively) were collected to determine DOC, UV, and
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fluorescence EEM.
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In Kim’s method (Fig. 1b), the original DOM samples (1.0 L) were separated into
HPO/TPI/HPI acids (HPO/TPI/HPI (a)), HPO bases/neutrals (HPO(b/n)), TPI bases/neutrals
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(TPI(b/n)), and HPI bases/neutrals (HPI(b/n)) upon resin fractionation. The diethylaminoethyl
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(DEAE) resin used in Kim and Dempsey (2008) was replaced by a weakly basic anion-exchange
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resin (Amberlite IRA-67, 500-750 µm) for this study because of the higher capacity to retain
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HPO/TPI/HPI(a) (Peuravuori and Pihlaja, 1998). DAX-8 and XAD-4 resins were filled in the
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next two columns sequentially to obtain the HPO(b/n) and the TPI(b/n), respectively. The
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surface flow rate was set at the same rate as in Imai’s method. The initial DOM and the eluted
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fractions from the resins of IRA-67, DAX-8, and XAD-4, denoted as KF1, KF2, and KF3 in Fig.
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1b, respectively, were collected for further analyses.
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In order to minimize adverse effects of the resins on the eluted DOM fractions, all the resins were previously cleaned using Soxhlet extraction with methanol for 24 h. For Imai’s
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method, DAX-8 resin was cleaned with 0.1 N NaOH and pre-conditioned with 0.1 N HCl before
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use. The AG-MP-1 and the AG-MP-50 were converted into free-base and free-acid forms using
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1 N NaOH and 1 N HCl, respectively, and rinsed with ultrapure water to adjust the pH into ~7.0.
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The blank samples for DAX-8, AG-MP-50, and AG-MP-1 (B1, B2, and B3, respectively) were
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also collected from each column. The DAX-8 and XAD-4 resins used in Kim’s method were
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similarly cleaned and conditioned except for the maintenance of the neutral pH condition. The
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IRA-67 was conditioned with 1 N NaOH, and rinsed with ultrapure water. In the same manner as
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in Imai’s method, the blank samples for IRA-67, DAX-8, and XAD-4 (B4, B5, and B6,
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respectively) were collected from each column. After the blank of the resins and the eluted
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volumes were all taken into account, the targeted DOM fractions were quantified using the
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formula provided in Table S2. The information on DOC, fluorescence EEMs, and PARAFAC
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components of the alkaline solution (i.e., 0.1 N NaOH) and the resin blanks are shown in Table
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S3 and Fig. S1. The blank correction was needed because some DOM resin fractions were eluted
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in low concentrations (Table S3).
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2.3. Analytical methods
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The pH of all DOM samples including the resin fractions was re-adjusted to ~ 7.0 prior to further analyses (Yang and Hur, 2014). DOC concentrations were measured by a Shimadzu V-
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CPH TOC analyzer with a relative precision of <3% (Yang and Hur, 2014). The absorption
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spectra were scanned by a Shimadzu UV-1300 spectrometer at the wavelengths from 200 nm to
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800 nm. The absorption coefficient at 254 nm (a254) was chosen as a UV indictor for DOM
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monitoring (Imai et al., 2001; Kim and Dempsey, 2012). A luminescence spectrometer (Perkin
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Elmer LS55) was used to obtain fluorescence EEMs with the emission spectra from 280 to 550
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nm at 0.5 nm increments and the excitation wavelengths from 250 to 500 nm at 5 nm increments.
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Both excitation and emission slits were adjusted to 5 nm, and the scanning speed was 1,200 nm
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min-1 (Hur and Cho, 2012). The EEM data was corrected according to the inter-laboratory
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standard method suggested by Murphy et al. (2010). In brief, EEM was corrected with water
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blank, and the inner filter effect was also considered. The fluorescence intensity was calibrated
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using a quinine sulfate dehydrate solution (10 µg L-1). The data was automatically corrected by a
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Matlab code, namely, FDOMcorrect (Murphy et al., 2010).
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2.4. EEM spectral subtraction and PARAFAC modeling Three groups of the FDOM quantity indicators, including those based on peak-picking, FRI, and PARAFAC methods (Chen et al., 2003; Coble, 1996; Stedmon et al., 2003), were
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obtained to test the feasibility of FDOM for the indicator subtraction upon resin fractionation.
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For specific peak-picking (SP) and FRI methods, five different specific regions (B, T, A, M, and
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C) were assigned to each measured EEM as shown in Fig. S2. They represent tyrosine-like,
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tryptophan-like, humic (fulvic)-like, marine humic-like, and humic-like DOM, respectively
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(Chen et al., 2003; Coble, 1996). The emission (ex) and excitation (em) wavelength ranges
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corresponding to the regions of B, T, A, M, and C were ex 250-300 / em 280-330, ex 250-300 /
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em 330-380, ex 250-300 / em 380-480, ex 300-320 / em 380-420, and ex 320-370 / em 420-480,
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respectively. The peak intensities and the integrated volumes were calculated using a self-written
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Matlab code (namely, F_specific_FRI.m in Script S1) for the FDOM indicators based on the SP
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and FRI methods, respectively. The integrated value was divided by the corresponding area
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under the surface of EEM so that the values would be expressed in the same unit as the other
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FDOM quantity parameters.
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PARAFAC modeling was performed using a Matlab toolbox, namely, DOMFluor
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(Stedmon and Bro, 2008), with a combined EEM data set of all collected DOM fractions and the
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subtracted EEMs between before and after elution through the resins (n = 142). The number of
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components was identified based on the split-half validation (Bro, 1997). The modified Turker’s
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Congruence Coefficient (mTCC) was employed to compare the identified components with a
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library containing 38 PARAFAC models (Parr et al., 2014). The mTCC values of >0.95 indicate
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the exact match between the two PARAFAC components (Table S4). The related Matlab code
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(namely, comPARAFAC.m) is contained in Script S2. The relative concentration of each
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PARAFAC component was estimated by the Fmax output from DOMFluor.
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The individual FDOM indicators retained on the resins of the fractionation processes were estimated based on the two approaches: by directly subtracting the FDOM quantity
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indicators between before and after elution (Indd), in which the indicators were previously
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determined based on the EEMs of all collected DOM fractions, and by obtaining the indictors
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(Inds) based on the subtracted EEM spectra between DOM before and after resins. The ratios of
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Indd to Inds were used here to evaluate the stability (or conservativeness) of the three indicator
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groups to DOM resin fractionation. If the ratios approach to 1.0 (i.e., Indd is similar to Inds), it is
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assumed that the indicator subtraction has the same effects as the EEM spectral subtraction on
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characterizing the resin-fractionated DOM and also that the FDOM quantity indicator is
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conservative through the resin fractionation processes.
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3. Results and discussion
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3.1. PARAFAC components
Four different PARAFAC components were identified for this study (Fig. 2): three
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humic-like components (C1, C2, and C3) and one protein-like component (C4). The quantitative
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comparison was made using mTCC values for the identified components versus those previously
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reported in the literature (Table S4). The compared components in the literature with mTCC >
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0.95 indicated excellent coincidence with those of this study. C1, with the ex/em ranges of <250-
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280 (325-360) nm and 370-480 nm, encompasses peaks A and C (Coble, 1996). It is dominated
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by UVC humic-like (Peak A) fluorescence, similar to a humic-like component reported by
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Stedmon et al. (2003) and Fellman et al. (2011). This component has a potential terrestrial
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source such as DOM derived from soils, forested streams, and wetlands. It is often observed as
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negatively correlated with salinity in estuarine ecosystems (Fellman et al., 2011; Ishii and Boyer,
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2012). C2, with the ex/em ranges of 260-300 (350-400) nm and 420-520 nm, had some overlaps
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with Peak A and C. This component can absorb light in the UVA and UVB bands, and it is
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associated with large molecular-sized and hydrophobic compounds (Cook et al., 2009; Ishii and
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Boyer, 2012). C3, with the ex/em ranges of 275-350 nm and 350-450 nm, corresponds to marine
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humic-like substances (Peak M) (Coble, 1996). This component is resistant to photo-degradation
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in surface waters (Jørgensen et al., 2011), and it has shown no correlation with quinine-like
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substances (Cory and McKnight, 2005). C4, with the ex/em ranges of <250-300 nm and 320-400
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nm, is generally assigned to a tryptophan-like component (Peak T) in many aquatic environments
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such as streams (Cory and Kaplan (2012), rivers (Massicotte and Frenette (2011), estuaries
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(Fellman et al. (2011), coast (Kowalczuk et al. (2010), and open seas (Murphy et al. (2008). It is
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identical to free tryptophan, and can be derived from autochthonous microorganisms (Stedmon
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and Markager, 2005).
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3.2. Comparison of different FDOM indicators regarding conservative behavior upon resin
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fractionation
To evaluate the stability of the FDOM quantity indicators upon resin fractionation, the
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indicators determined based on the two aforementioned subtraction approaches (i.e., the indicator
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subtraction and the EEM subtraction) were all plotted together, and their relationships were
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compared according to the three groups of the FDOM indicators in Fig. 3. Compared with the
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FRI and PARAFAC methods (slope, 1.00, R2 = 1.000), the FDOM indicator group from the SP
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method was more vulnerable to resin fractionation as indicated by the higher degree of the
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deviation from the 1:1 lines and also by the lower coefficients of determination (R2 =0.945 and
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0.926 for Imai’s and Kim’s fractionation methods, respectively) for the linear fitting. The
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Indd/Inds ratios of the three indicator groups were calculated and compared in Table S5 and
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summarized in Table 1. As a result, the PARAFAC components were the most conservative
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indicator group applicable for resin fractionation, as indicated by their average Indd/Inds ratios of
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0.99 ± 0.17, followed by those based on the FRI (0.94 ± 0.15) and SP methods (0.80 ± 0.20). The conservative behavior was further examined regarding the relationships between the
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Indd/Inds ratios and Inds for the three FDOM indicator groups (Figs. S3 and S4). In general, the
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Indd/Inds ratios displayed an increasing trend with the intensity of Inds, implying that the FDOM
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indicators calculated by direct subtraction become more consistent with those based on EEM
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spectral subtraction with a higher FDOM intensity. As expected, the tolerant limits, referring to
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the minimum indicator intensity corresponding to the Indd/Inds ratios approaching 1.0, were the
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highest for the SP indicators. The poor tolerance of the SP indicators can be attributed to the
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changes of the peak locations after EEM spectral subtraction upon the resin fractionation (Fig.
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S5). The FRI method seems to partially avoid this problem because most of the peak changes
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occurred within individually defined regions (Chen et al., 2003). The indicators from both FRI
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and PARAFAC methods displayed good tolerance to the subtraction upon resin fractionation, but
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the PARAFAC indicators are more preferable in that the PARAFAC components can represent
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independent fluorescent groups. In addition, PARAFAC components were the most insensitive
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to the peak changes resulting from EEM spectral subtraction (Figs. S3 and S4). It is a significant
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finding that the direct subtraction of PARAFAC components is applicable in quantitatively
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tracking FDOM during resin fractionation processes.
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Irrespective of the indicator groups, the humic-like FDOM indicators (Indd/Inds, 0.95 ± 0.16) exhibited higher consistency between the two subtraction approaches than the protein-like
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indicators (Indd/Inds, 0.85 ± 0.22). In detail, the Indd/Inds ratios of the humic-like indicators
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based on both FRI and PARAFAC methods were much closer to 1.00 than those of the SP
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method (p < 0.05). No significant difference was found in the ratios of all FDOM indicators
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between FRI and PARAFAC methods (independent t-test: p= 0.19 and 0.69 for Imai’s and
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Kim’s methods, respectively). However, the difference in the ratios of the protein-like indicators
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depended on the fractionation methods (p = 0.04 and 0.09 for Imai’s and Kim’s methods,
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respectively). The tolerant limits were mostly higher for the protein-like versus the humic-like
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indicators, and the humic-like indicators were more insensitive to the direct subtraction than the
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protein-like indicators as shown by more data points exhibiting the Indd/Inds ratios close to 1.00
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for each indicator group (Figs. S3 and S4).
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3.3. PARAFAC components of different resin fractions
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3.3.1. Fractionation using Imai’s method
DOC concentrations and the intensities of PARAFAC components for different DOM
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fractions are summarized in Table 2, and their relative abundances were compared for EfOM,
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LiOM, and RiOM in Figs. 4 and S6. The organic acids (i.e., HPO(a) and TPI/HPI(a)) were the
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dominant fractions in all the DOM sources (Table 2 and Fig. S6a), constituting more than 50% of
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the DOM as DOC, which is in accordance with previous studies (Imai et al., 2001; Imai et al.,
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2002). In LiOM and RiOM, HPO(a) was more abundant than TPI/HPI (a), while the opposite
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trend was found for EfOM. Organic bases were the lowest fractions for all the DOM sources,
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accounting for 6%~17% of DOM. Organic neutrals (i.e., HPO(n) and TPI/HPI(n)) was the
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second largest fractions, responsible for ~35% in DOC for DOM samples, and the HPO(n)
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fractions were present in low quantities (7%~13%), which agreed with the previous studies (Imai
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et al., 2002). A representative humic-like fluorescence component, C1, was consistently higher than
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the protein-like component (i.e., C4) for all the resin fractions irrespective of DOM sources
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(Table 2 and Fig. 4a-c) except for HPO(n) of LiOM. It can be hypothesized that humic-like and
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protein-like components are enriched in HPO(a) and organic bases, respectively, considering the
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chemical characteristics of the resins (Imai et al., 2001). However, our results revealed no
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significant correlations (p >0.05) between the intensities of the two fluorescence components and
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DOC concentrations of the corresponding fractions. This inconsistency may suggest that non-
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fluorescent DOM components are more dominant in the fractions of HPO(a) and organic bases
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and/or that FDOM composition depends more on the DOM sources than on the resin
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characteristics. Our results are in line with a previous study of Chen et al. (2003), in which the
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FDOM composition was not consistent with the types of the resin fractions but instead varied
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with DOM sources.
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Similar to DOC, organic acids were the most dominant fractions for all the PARAFAC
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components regardless of DOM source (Fig. S6b-e). They corresponded to 48%, 51%, 47%, and
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46% for C1, C2, C3, and C4, respectively, on average for all collected samples. The fraction of
312
TPI/HPI(n) accounted for only below 6% of the PARAFAC components even though it
313
corresponded to ~25% of DOM on the basis of DOC. The differences in the FDOM composition
314
among the resin fractions with various DOM sources were better illustrated by normalizing the
315
PARAFAC component of each fraction to its DOC concentration (Fig. 5). In EfOM, the HPO(n)
316
fractions displayed the highest level of FDOM per organic carbon, which were 48.3-114.8 µg QS
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mg-1 C-1 for humic-like components (C1, C2, and C3, Fig. 5a-c) and 107.2 µg QS mg-1 C-1 for
318
protein-like component (C4, Fig. 5d), respectively, followed by organic bases. In both LiOM and
319
RiOM, however, the organic bases exhibited the highest DOC-normalized FDOM, followed by
320
HPO(n). The abundances of the DOC-normalized PARAFAC components were similar for the
321
HPO(a) fractions of EfOM, LiOM, and RiOM, indicating that the HPO(a) might have similar
322
FDOM composition independent of the DOM sources. Among the resin fractions, TPI/HPI(n)
323
had the lowest levels of DOC-normalized FDOM, which were 1.4, 1.0, 1.1, and 0.6 µg QS mg-1
324
C-1 of C1, C2, C3, and C4, respectively, on average for all collected samples. The order of the
325
resin fractions in the levels of DOC-normalized FDOM appears to be more affected by the DOM
326
sources rather than by the PARAFAC components. For example, all the DOC-normalized
327
PARAFAC components on average were higher in the order of HPO(n) > organic bases >
328
TPI/HPI(a) ~ HPO(a) > TPI/HPI(n) for EfOM, which was not the case for the other DOM
329
sources.
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3.3.2. Fractionation using Kim’s method
The sum of organic acids (HPO/TPI/HPI(a)) and HPI(b/n) dominated in all DOM
333
samples (Fig. S6f), constituting more than 68% of the DOM on the basis of DOC. Only ~18% of
334
organic acids were found in EfOM, which was similar to the value (15%) previously reported for
335
effluent DOM in a previous study (Kim and Dempsey, 2012). Both LiOM and RiOM exhibited
336
more abundance of organic acids than EfOM. This may be attributed to the higher conductivity
337
or the higher total dissolved solids (TDS) of the effluents versus limnic and riverine water (Table
338
S1), because the inorganic matter may participate in the competitive exchange with organic acids
339
for the anionic resin (IRA-67). Note that the same type of the resin was placed in the last column
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of Imai’s method, in which the greater abundance of organic acids was exhibited for the same
341
DOM source compared with those in Kim’s method. Similar relative abundances of PARAFAC components were found between HPO(b/n)
343
and TPI(b/n) fractions in LiOM, and between organic acids and HPO(b/n) fractions in RiOM.
344
For both EfOM and RiOM, either C1 or C4 was dominantly present in the HPO/TPI/HPI(a) and
345
the HPO(b/n) fractions, and the overall FDOM composition was similar for the HPI(b/n)
346
fractions. Among the four resin fractions, the organic acids (HPO/TPI/HPI(a)) discriminated the
347
three DOM sources the most as shown by the highest abundance of C4 in EfOM, followed by
348
RiOM and LiOM (Figs. 4d-4f).
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Except for EfOM, organic acids dominated in FDOM (Fig. S6g-i), accounting for 44%,
350
48%, 38%, and 53% of C1, C2, C3, and C4, respectively, on average for all collected samples.
351
Meanwhile, the compositions of C1 and C2 were similar to each other irrespective of DOM
352
source, implying the similarity between the two humic-like components with respect to the
353
source and/or the tendency of the interactions with the resins. When all collected samples were
354
taken into account, the FDOM composition of the organic bases/neutrals were higher on the
355
order of HPO > TPI > HPI for C1 and C2, while the opposite trend was found for C3. C4 was
356
predominantly present in the organic acid fractions for all the DOM sources.
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DOC-normalized humic-like components did not exhibit major differences in the organic
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acids (HPO/TPI/HPI(a)) among the three DOM sources (Fig. 5e-f) with the average values of
359
10.9, 5.7, and 4.7 µg QS mg-1 C-1 for C1, C2 and C3, respectively. In contrast, DOC-normalized
360
protein-like components in the organic acids showed large variability with the DOM sources.
361
The highest value (52.3 µg QS mg-1 C-1) was found in EfOM, followed by RiOM and LiOM.
362
DOC-normalized PARAFAC components in the HPO(b/n) for EfOM and RiOM were similar to
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each other (p > 0.05). The highest normalized PARAFAC components in the TPI(b/n) fractions
364
were observed in RiOM, followed by LiOM and EfOM. The HPI(b/n) fractions had the least
365
abundance of FDOM per organic carbon. On average, DOC-normalized humic-like components
366
were higher on the order of TPI(b/n) ~ HPO(b/n) > organic acids ~ HPI(b/n), while the DOC-
367
normalized protein-like component, in the order of organic acids > HPO(b/n) > TPI(b/n) > HPI
368
(b/n) (Fig. 5e-f).
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3.4. Implications of conservative behavior of PARAFAC components to resin fractionation
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and its applicability for other environmental systems
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DOM fractionation combined with EEM-PARAFAC has been successfully applied to understand the dynamics of DOM in complex environmental systems, owing to the enhancement
374
of the resolution in DOM characterization (Murphy et al., 2011; Xue et al., 2012). This study
375
demonstrated that PARAFAC components are stable under spectral subtraction upon resin
376
fractionation processes and thus can be quantitatively treated like DOC and a254 for
377
characterizing DOM resin fractions with different chemical structures/reactivities. In detail, the
378
conservative behavior of PARAFAC components was more pronounced for humic-like versus
379
protein-like FDOM as revealed by the relatively smaller differences between the Indd and Inds
380
values for the humic-like components. This finding suggests that humic-like fluorescence
381
components can be used as a more robust quantity parameter for tracking FDOM when DOM is
382
fractionated upon adsorption. This also provides further insight into the potential applicability of
383
EEM-PARAFAC for other environmental systems requiring the tracking of the individual DOM
384
fractions with different chemical compositions. For example, the approach used for Indd can be
385
applied to study the fate and the behaviors of different FDOM components constantly contacting
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with solid phase (e.g., adsorption and membrane filtration). As shown in this study, however,
387
FDOM is not always coupled with DOC in resin fractionation because FDOM constitutes only a
388
small portion of the total DOM (Table S7). This limitation points out the necessity of combining
389
FDOM indicators with DOC for the full understanding of DOM changes upon fractionation.
390
Although similar carbon structures were previously reported for the same resin fractions from
391
different DOM sources based on nuclear magnetic resonance (NMR) and FT-IR measurements
392
(Chen et al., 2003), our results clearly demonstrated that the chemical composition of resin
393
fractions revealed by EEM-PARAFAC might differ by DOM sources. EEM-PARAFAC coupled
394
with resin fractionation can be a promising tool to provide further information on DOM resin
395
fractions with respect to their chemical composition and the environmental functionalities
396
associated with the individual PARAFAC components. It would be even more beneficial for
397
examining the complex systems with diverse DOM sources mixed together.
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4. Conclusions
Based on the major findings and environmental significance of our results, the following
400 401 402
conclusions can be made. •
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SP method. However, because of the low tolerance limit to the indicator subtraction, the
404
PARAFAC components appear more suitable for the quantity parameter in tracking the
405
individual FDOM components.
406
408
The FDOM indicators calculated from FRI and PARAFAC methods both showed higher stability to the indicator subtraction upon resin fractionation compared with those of the
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•
Humic-like components showed more conservative behavior to resin fractionation than the protein-like component as indicated by the smaller differences between the Indd and
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Inds values. Among the resin fractions, organic acid fractions only exhibited similar
410
FDOM composition between Imai’s and Kim’s methods.
411
•
No consistent trends in the relative abundances of PARAFAC components were found for the same resin fractions from different DOM sources, suggesting that the chemical
413
composition of DOM revealed by EEM-PARAFAC is more greatly affected by DOM
414
sources rather than by the types of resin fractions. •
The relative abundances of different resin fractions in DOM as DOC were completely
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different from those on the basis of the FDOM. Furthermore, the distributions of the
417
FDOM resin fractions varied with the individual PARAFAC components, suggesting that
418
EEM-PARAFAC could provide additional information on resin fractions with respect to
419
the environmental fate and reactivity associated with each PARAFAC component.
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Acknowledgements
This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No.2014R1A2A2A09049496).
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Figure Captions
558
Fig. 1. Schematic diagrams of the resin fractionation procedures based on Imai’s method (a) and
559
Kim and Dempsey (2008, 2012) (b). EEMs of the fractions eluted from resins as well as those
560
retained on resins are shown for effluent DOM (EfOM).
561
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Fig. 2. Representative EEMs and the spectral loadings of four identified PARAFAC components.
563
Individual excitation and emission loading are shown for the comparison of the modeled and the
564
split-half (split 1-2 and 3-4) validated results.
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Fig. 3. Comparison of the FDOM indicators from the subtracted EEM spectra (Inds) versus those
567
from the direct subtraction between the two indicators before and after resins (Indd) for Imai’s
568
fractionation method (chart a-c) and Kim’s fractionation method (chart d-f). Chart a and d are
569
based on the FDOM indicators from the peak-picking method; Chart b and e are based the
570
FDOM indicators from the FRI method; Chart c and f are based on PARAFAC components.
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Fig. 4. Relative abundance (%) of four PARAFAC components for different resin fractions of
573
EfOM, LiOM, and RiOM based on Imai’s method (chart a-c) and Kim’s method (chart d-f).
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Fig. 5. DOC-normalized intensities of PARAFAC components in different resin fractions for
576
EfOM, LiOM, and RiOM. Fractions were obtained by Imai’s method (chart a-d) and Kim’s
577
method (chart e-h). “All” in the x-axis represents the average values of each fraction over EfOM,
578
LiOM, and RiOM.
579
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Tables
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Table 1. Ratios of Indd to Inds for the fractions retained on various resins based on Imai’s and Kim’s fractionation methods. FDOM quantity indicator groups are obtained from Coble (1996)’s specific peak-picking (SP) method (SPprotein: the peaks of B and T, SPhumic: the peaks of A, M, and C), fluorescent regional integration (FRI) method (FRIprotein: the regions of B and T, FRIhumic: the regions of A, M, and C), and PARAFAC components (PARAFAChumic: C1, C2, and C3, and PARAFACprotein: C4). Indicator
Fractions on 1st resin
Fractions on 2nd resin
groups
n
n
Imai’s method
HPO (n)
SPtotal
39
0.74 (26)
0.28-0.98
44
0.79 (26)
SPprotein
15
0.68 (28)
0.28-0.98
17
0.68 (40)
SPhumic
24
0.78 (24)
0.31-0.98
27
0.86 (12)
FRItotal
38
0.95 (14)
0.28-1.00
45
FRIprotein
15
0.94 (13)
0.63-1.00
FRIhumic
38
0.95 (14)
0.28-1.00
PARAFACtotal
30
1.07 (36)
0.72-3.04
PARAFACprotein
8
0.96 (10)
0.72-1.00
PARAFAChumic
22
1.11 (39)
0.96-3.04
Kim’s method
HPO/TPI/ HPI (a)
SPtotal
45
0.86 (25)
0.00-1.00
44
0.78 (26)
0.11-1.00
43
0.78 (27)
0.22-1.00
SPprotein
18
0.87 (18)
0.35-1.00
17
0.72 (38)
0.11-1.00
17
0.67 (36)
0.22-1.00
SPhumic
27
0.85 (29)
0.00-0.99
27
0.82 (16)
0.53-0.98
26
0.85 (17)
0.45-1.00
FRItotal
45
0.99 (4)
0.80-1.00
44
0.96 (13)
0.38-1.00
45
0.91 (19)
0.35-1.00
FRIprotein
18
0.98 (5)
0.80-1.00
17
0.89 (20)
0.38-1.00
18
0.79 (28)
0.35-1.00
FRIhumic
45
0.99 (4)
0.80-1.00
44
0.96 (13)
0.38-1.00
45
0.91 (19)
0.35-1.00
PARAFACtotal
35
1.02 (7)
1.00-1.32
36
0.97 (11)
0.42-1.07
36
0.97 (12)
0.42-1.02
PARAFACprotein
9
1.00 (1)
1.00-1.02
9
0.90 (22)
0.42-1.00
9
0.95 (13)
0.62-1.00
PARAFAChumic
26
1.02 (8)
1.00-1.32
27
1.00 (4)
0.83-1.07
27
0.98 (11)
0.42-1.02
Min-Max
Mean(RSD)
HPO/TPI/HPI (b)
n
Mean(RSD)
Min-Max
TPI/ HPI (a) 44
0.86 (16)
0.36-1.00
0.01-1.00
17
0.78 (23)
0.36-1.00
0.61-1.00
27
0.91 (8)
0.70-0.99
0.92 (20)
0.31-1.00
44
0.94 (17)
0.12-1.00
18
0.80 (32)
0.31-1.00
17
0.84 (27)
0.12-1.00
45
0.92 (20)
0.31-1.00
44
0.94 (17)
0.12-1.00
36
0.99 (3)
0.84-1.03
36
0.96 (15)
0.29-1.09
9
0.97 (5)
0.84-1.00
9
0.83 (31)
0.29-1.00
27
1.00 (2)
0.94-1.03
27
1.00 (2)
0.97-1.09
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HPO (b/n)
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Min-Max
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Mean(RSD)
Fractions on 3rd resin
TPI (b/n)
Note: n – number of samples; RSD – relative standard deviation (%); Min – minimum; Max – maximum.
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Fractionation methods Organic matter
Imai's method HPO (a)a
HPO (n)
HPO/TPI/HPI (b)
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Table 2. DOC concentrations and the intensities of PARAFAC components for different resin fractions obtained from Imai’s and Kim’s fractionation methods. Kim's method
TPI/HPI (a)
TPI/ HPI (n)
HPO/TPI/HPI (a)
HPO (b/n)
TPI (b/n)
HPI (b/n)
1.68±1.26 22.84±18.36
0.88±0.60 22.70±18.61
1.66±1.24 29.70±15.92
4.03±1.04 23.36±13.47
15.53±12.21
15.42±12.39
13.97±9.69
14.57±8.10
2.04±0.56 0.65±0.80 14.83±7.45 23.86±5.76
1.43±1.35 36.14±6.86
2.41±1.18 29.75±19.29
1.60±0.06 5.06±3.99
C2 (µg QS L-1)
7.76±2.40
14.30±5.82
18.77±1.91
16.59±8.53
2.81±2.08
C3 (µg QS L ) C4 (µg QS L-1)
4.38±2.62 5.76±4.79
16.29±8.94 23.17±7.20
21.49±7.92 16.38±9.17
19.85±6.28 24.65±4.10
3.11±2.51 2.50±2.05
11.59±13.27 31.75±2.22
12.56±11.70 31.55±2.51
10.76±6.99 12.65±7.29
18.79±10.84 10.54±9.63
Limnic DOC (mg L-1) C1 (µg QS L-1)
0.99±0.36 5.78±1.25
0.23±0.05 6.52±8.71
0.36±0.31 6.14±2.34
0.66±0.27 5.03±3.05
0.93±0.44 0.55±0.36
1.28±0.55 12.62±2.11
0.50±0.74 3.07±1.92
0.10±0.14 3.93±1.54
1.16±0.09 2.19±0.93
C2 (µg QS L-1)
3.33±0.49
1.34±2.18
1.99±1.09
2.01±1.35
0.54±0.21
5.27±1.49
1.27±0.88
1.30±0.56
0.79±0.21
C3 (µg QS L ) C4 (µg QS L-1)
1.89±0.53 2.01±0.88
2.10±2.97 4.47±4.36
3.13±0.39 4.04±1.38
2.60±1.41 2.89±3.04
0.44±0.25 0.00±0.00
5.42±0.81 4.92±1.19
1.07±1.09 1.11±1.34
1.67±1.41 1.63±1.07
2.36±1.28 1.49±0.28
Riverine DOC (mg L-1) C1 (µg QS L-1)
1.01±0.26 7.47±1.47
0.43±0.08 6.67±4.10
0.24±0.17 5.07±3.49
0.80±0.14 9.36±5.45
0.96±0.25 0.65±0.77
1.58±0.08 15.74±6.78
0.21±0.14 7.21±5.31
0.24±0.23 5.21±4.26
1.37±0.14 3.45±1.97
C2 (µg QS L-1)
3.14±1.50
1.88±2.03
2.37±1.61
3.82±2.42
0.62±0.52
6.74±2.72
2.50±2.16
1.83±1.61
1.28±0.57
2.54±0.32 3.96±0.57
2.23±1.79 4.97±3.84
2.42±1.02 3.26±2.10
5.02±2.76 6.66±3.72
0.61±0.44 0.18±0.16
6.24±2.48 10.41±5.66
2.57±1.88 4.35±3.70
3.24±2.50 2.28±1.84
3.11±1.93 1.93±0.53
-1
C3 (µg QS L ) C4 (µg QS L-1)
M AN U
TE D
EP
-1
AC C
-1
SC
Effluent DOC (mg L-1) C1 (µg QS L-1)
Note: Data are expressed by average ± standard deviation.
2
ACCEPTED MANUSCRIPT
a. Imai’s fractionation method
b. Kim’s fractionation method 500 KE1(2) (DOM)
500
500
120
40
250
IF0 300
350
DAX-8
20
400 450 Em. (nm)
500
550
500
500
550
500
0
70
Elute with 0.1 M NaOH
100
400
50 40
350
20
500
550
0
60 350
120
60 350
IF2 500
550
KE3(2) (TPI/HPI b/n)
400 450 Em. (nm)
500
550
0
AG-MP-1
0
TPI/HPI (acids)
450 400
100
80
80 60
350 300
120
40
350
300
350
300
80 60
350 40 300
300
350
400 450 Em. (nm)
500
300
20
350
400 450 Em. (nm)
500
0
550
400 450 Em. (nm)
500
550
EP
10
90
450 400
XAD-4
60 50
20
300
350
400 450 Em. (nm)
500
550
90
400
TPI (bases/neutrals)
80 70 60 50 40
350
30 20
300
10 90
HPI (bases/neutrals)
70 60 50
30
350
20 10 400 450 Em. (nm)
500
550
250
80
40
KF3
300
70
40
KE(2) (TPI b/n) 450
350
250
80
10
500
300
Fig. 1
20
550
30
550
0
TE D
250
IF3
350
500
HPO (bases/neutrals)
500
10
Ex. (nm)
250
QS µg/L
400
100
400 450 Em. (nm)
350
250
KE4(2) (HPI b/n)
TPI /HPI (neutrals)
450
400
20
KF2
20
IE5(1) (HiN)
30
300
60
40
500
40
70
50
250
50
KE(2) (HPO b/n) 450
DAX-8
400
300
120
IE(1) (BaS)
Ex. (nm)
400 450 Em. (nm)
Ex. (nm)
350
350
500
20
300
300
550
30
40
300 250
QS µg/L
400
AC C
Ex. (nm)
80
500
60
500
10
400 450 Em. (nm)
90
20
100
250
350
450
300
20
KF1 300
500
40
IE4(1) (HiA/HiN) 450
250
80
Ex. (nm)
500
400 450 Em. (nm)
AG-MP-50
400
100
70
350
250
QS µg/L
350
300
HPO/TPI/HPI (bases)
M AN U
300
120 IE(1) (HoN)
450
Ex. (nm)
250
500
40
IF1
QS µg/L
60 350
400
30
QS µg/L
Ex. (nm)
80 400
80
HPO/TPI/HPI (acids)
300
60
SC
Ex. (nm)
120
450
300
80
450
IE3(1) (HiA/BaS/HiN)
IRA-67
90
Ex. (nm)
400 450 Em. (nm)
90
KE(2) (HPO/TPI/HPI a)
Ex. (nm)
350
550
QS µg/L
300
500
450
0
KE2(2) (HPO/TPI/HPI b/n)
250
400 450 Em. (nm)
500
20
QS µg/L
300
40 300
60 350
350
QS µg/L
60 350
QS µg/L
Ex. (nm)
80
400
QS µg/L
100
400
10
300
80 Ex. (nm)
HPO(neutrals)
20
250 100
HPO(acids)
450
IE(1) (HoN) 450
40
300
120 IE2(1) (AHS)
0
550
50
QS µg/L
400 450 Em. (nm)
60
350
QS µg/L
350
70
30
DOM
20
300
400
300
350
400 450 Em. (nm)
500
550
QS µg/L
300
80
Filtrated water (DOM)
QS µg/L
Ex. (nm)
60 350
250
500
80 QS µg/L
Ex. (nm)
400
450
100
Ex. (nm)
Filtrated water (DOM)
40
DOM
90
120 IE1(1) (DOM)
450
RI PT
500
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
Fig. 2
ACCEPTED MANUSCRIPT
30 20
25
50
c
Protein Humic Fitting Curve
20 15 10
10
10
20 30 Ind (SP, µg QS/L) s
40
0 0
50
Ind (FRI, µg QS/L) d
e 30
20
40
25
Protein Humic Fitting Curve
20 15 10
20 30 40 Ind (SP, µg QS/L) s
50
60
0 0
40
y= 1.00x + -0.03 n= 134, R2= 1.000, p= 0.0000
10
20 30 Ind (FRI, µg QS/L) s
TE D
Fig. 3
EP
f
50
Protein Humic Fitting Curve
30 20 10
M AN U
5
y= 0.85x + 0.17 n= 132, R2= 0.926, p= 0.0000
10
y= 1.00x + -0.05 n= 102, R2= 1.000, p= 0.0000 20 30 40 Ind (PFC, µg QS/L) s
50
10
10
10
SC
Protein Humic Fitting Curve
30
0 0
20
0 0
35
AC C
Ind (SP, µg QS/L) d
40
30
s
50
d
y= 1.00x + -0.09 n= 127, R2= 1.000, p= 0.0000 10 20 30 Ind (FRI, µg QS/L)
Ind (PFC, µg QS/L) d
0 0
5
y= 0.90x + -0.66 n= 127, R2= 0.945, p= 0.0000
Protein Humic Fitting Curve
40
RI PT
Ind (FRI, µg QS/L) d
Ind (SP, µg QS/L) d
40
35
b 30
Protein Humic Fitting Curve
Ind (PFC, µg QS/L) d
50
a
40
0 0
y= 1.00x + -0.01 n= 107, R2= 1.000, p= 0.0000
10
20 30 Ind (PFC, µg QS/L) s
40
50
80 70 60 50 40 30 20
b
100
80
10 Fr1
Fr2
Fr3
HPO(n)
HPO/TPI/ HPI (b)
Fr4
30 20
80
Fr2
HPO(a)
Fr3
HPO(n)
HPO/TPI/ HPI (b)
Fr4
PARAFAC component (%)
e
60 50 40 30 20 10
90 80
HPO/TPI/ HPI (a)
Fr2
HPO (b/n)
Fr3
TPI (b/n)
Fr4
Limnic
C1 C2 C3 C4
60 50 40 30 20
HPI(b/n)
30 20
Fr1
HPO(a)
f
90 80
Fr2
Fr3
HPO(n)
HPO/TPI/ HPI (b)
Fr4
Fr5
TPI/HPI (a) TPI/ HPI (n)
Riverine
C1 C2 C3 C4
70 60 50 40 30 20 10
Fr1
HPO/TPI/ HPI (a)
Fr2
HPO (b/n)
TE D
Fr3
TPI (b/n)
Fig. 4
EP
40
TPI/HPI (a) TPI/ HPI (n)
70
0
50
100
10 Fr1
60
SC
Effluent
C1 C2 C3 C4
70
0
Fr5
Riverine
C1 C2 C3 C4
90
10 Fr1
100
70
0
40
TPI/HPI (a) TPI/ HPI (n)
AC C
PARAFAC component (%)
80
50
0
Fr5
100 90
60
100
10
HPO(a)
d
70
c
PARAFAC component (%)
0
Limnic
C1 C2 C3 C4
90
RI PT
Effluent
C1 C2 C3 C4
90
PARAFAC component (%)
100
M AN U
PARAFAC component (%)
a
PARAFAC component (%)
ACCEPTED MANUSCRIPT
Fr4
HPI(b/n)
0
Fr1
HPO/TPI/ HPI (a)
Fr2
HPO (b/n)
Fr3
TPI (b/n)
Fr4
HPI(b/n)
ACCEPTED MANUSCRIPT
200
C2 (ug QS/(mg C)
150
100
50
Effluent
Limnic
Ri verine
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
150
Effluent
Ri verine
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
100
0
Effluent
250
150
Limnic
Ri verine
All
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
AC C
100
All
50
0
100
0
f 250
Riverine
All
Effluent
Limnic
h
Effluent
Limnic
Riverine
All
Riverine
All
Riverine
All
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
150
100
50
0
Effluent
Limnic
250
200
EP
200
Limnic
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
150
200
150
50
C3 (ug QS/(mg C)
Limnic
TE D
C1 (ug QS/(mg C)
200
Effluent
50
C2 (ug QS/(mg C)
0
0
d 250
M AN U
100
e 250
100
200
50
g
All
C4 (ug QS/(mg C)
C3 (ug QS/(mg C)
200
150
50
C4 (ug QS/(mg C)
0
c 250
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
SC
C1 (ug QS/(mg C)
200
b 250 HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
RI PT
a 250
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
150
100
50
Ri verine
All
0
Fig. 5
Effluent
Limnic
ACCEPTED MANUSCRIPT
Highlights
► Rigorous tests on the applicability of EEM-PARAFAC for resin fractionation of
RI PT
DOM.
►PARAFAC components were the superior to other FDOM indicators in the
SC
conservativeness.
M AN U
►Lower sensitivity to spectral subtraction for humic-like vs. protein-like components.
►FDOM composition of resin fractions is more affected by DOM sources rather than
AC C
EP
TE D
resins.
ACCEPTED MANUSCRIPT
Conservative behavior of fluorescence EEM-PARAFAC components in resin fractionation
Wei He and Jin Hur*
RI PT
processes and its applicability for characterizing dissolved organic matter
M AN U
SC
Department of Environment and Energy, Sejong University, Seoul 143-747, South Korea
Pages: 19; Tables: 7; Figures: 6;
AC C
EP
TE D
Script: 2.
1
ACCEPTED MANUSCRIPT
Table S1. In-situ water quality parameters of effluent, limnic, and riverine water samples and selected parameters for the DOM (Mean±standard deviation, n=3). Effluent water
Limnic water
pH EC (µs cm-1) TDS (mg L-1) DOC a254 (m-1) C1 (µg QS L-1) C2 (µg QS L-1) C3 (µg QS L-1) C4 (µg QS L-1) C1 (%) C2 (%) C3 (%) C4 (%)
6.90±0.13 523±35 335±22 8.19±1.41 31.93±14.73 106.09±15.52 59.36±7.13 63.93±8.53 69.67±14.70 35.49±1.14 19.92±0.70 21.44±1.42 23.15±1.82
7.12±0.16 76±2 49±1 3.10±0.29 8.01±1.17 22.20±3.52 8.24±1.20 10.01±1.36 10.13±2.71 43.92±1.12 16.35±1.31 19.90±1.54 19.82±2.86
Riverine water
RI PT
Parameters
M AN U
SC
7.31±0.21 182±4 116±3 3.41±0.24 15.38±13.04 30.52±7.88 11.56±3.44 14.09±3.33 18.57±6.69 41.05±1.23 15.41±0.53 19.09±1.46 24.46±2.24
AC C
EP
TE D
Note: EC – Electrical conductivity; TDS – Total dissolved solids
2
ACCEPTED MANUSCRIPT
Table S2. Formula used for calculating each DOM resin fractions. Fractions
Formula
RI PT
Imai’s method IF0,cor IF1,cor IF2,cor IF3,cor HPO acids HPO neutrals HPO/TPI/HPI bases TPI/HPI acids TPI/HPI neutrals Kim’s method KF1,cor KF2,cor KF3,cor HPO/TPI/HPI acids HPO bases/neutrals TPI bases/neutrals HPI bases/neutrals
M AN U
SC
(IF0 – BNaOH) × (Velutant) / (Vsample) IF1 – B1 (IF2 – B2) / [(Vsample – Vmonitoring) / Vsample] (IF3 – B3) / [(Vsample – 2Vmonitoring) / Vsample] IF0,cor DOM – IF0,cor – IF1,cor IF1,cor – IF2,cor IF2,cor – IF3,cor IF3,cor
KF1 – B4 (KF2 – B5) / [(Vsample – Vmonitoring) / Vsample] (KF3 – B6) / [(Vsample – 2Vmonitoring) / Vsample] DOM – KF1,cor KF1,cor – KF2,cor KF2,cor – KF3,cor KF3,cor
AC C
EP
TE D
Note: DOM, IF0, IF1, IF2, IF3, KF1, KF2, and KF3 are the fractions shown in Fig. 1. BNaOH denotes the concentration of NaOH. Vsample, Vmonitoring, and Velutant are the volumes of the initial sample (1000 mL), monitored samples (50 mL per time), and elutants (100 mL).
3
ACCEPTED MANUSCRIPT
Table S3. DOC concentrations and the intensities of fluorescence EEM-PARAFAC components for an alkaline solvent and the resin blanks, and the minimum DOC and PARAFAC components of each fraction based on Imai’s and Kim’s methods C2 (µg QS L-1)
5.80 1.37 1.15 0.54 0.43 (7.4%) 0.20 (14.8%) 0.13 (11.6%) 0.12 (21.7%)
44.50 6.74 3.74 0.79 0.99 (2.2%) 0.12 (1.8%) 0.88 (23.6%) 0.78 (98.7%)
16.08 2.42 1.48 0.15 0.35 (2.2%) 0.02 (1.0%) 0.00 (0.0%) 0.00 (0.0%)
1.31 1.07 1.11 0.11 (8.0%) 0.20 (19.0%) 0.16 (16.8%)
5.10 3.80 1.61 0.01 (0.1%) 0.12 (3.3%) 0.20 (14.0%)
1.54 1.22 0.52 0.00 (0.2%) 0.02 (1.9%) 0.01 (2.9%)
C3 (µg QS L-1)
C4 (µg QS L-1)
13.17 4.70 1.80 0.20 0.47 (3.5%) 0.02 (0.3%) 0.07 (4.0%) 0.07 (35.8%)
12.66 3.39 1.77 1.64 2.26 (17.9%) 0.12 (3.6%) 1.66 (93.6%) 1.64 (100.0%)
3.47 2.82 0.80 0.00 (0.0%) 0.02 (0.5%) 0.00 (0.0%)
2.61 2.19 1.43 0.32 (12.2%) 0.12 (5.6%) 0.27 (23.7%)
RI PT
C1 (µg QS L-1)
SC
Imai’s method IF0sample,min IF1sample,min IF2sample,min IF3sample,min BNaOH B1 B2 B3 Kim’s method KF1sample,min KF2sample,min KF3sample,min B1 B2 B3
DOC mg L-1
M AN U
Fractions
AC C
EP
TE D
Note: Values in the brackets denote the percentage of the blank to the minimum quantity of the fractions, i.e., IF0sample,min / BNaOH × 100% or IF1sample,min / B1 × 100%.
4
ACCEPTED MANUSCRIPT
Table S4. Modified Turker’s Congruence Coefficient (mTCC) for the PARAFAC components between the present study and 38 PARAFAC models summarized by Parr et al. 2014. mTCC
RI PT
Sample (Component) / Database (Component)
AC C
EP
TE D
M AN U
SC
MySample (1) / Fellman 2011 (1) 0.968 MySample (1) / Parr 2014 (1) 0.975 MySample (1) / Stedmon 2003 (1) 0.964 MySample (2) / Burrows 2013 (2) 0.959 MySample (2) / Chen 2010 (1) 0.987 MySample (2) / Kowalczuk 2010 (1) 0.957 MySample (2) / Parr 2014 (2) 0.979 MySample (2) / Singh 2013 (1) 0.971 MySample (2) / Yamashita 2011 (2) 0.958 MySample (3) / CM 2005 (10) 0.964 MySample (3) / Kothawala 2012 (2) 0.972 MySample (3) / Murphy 2006 (2) 0.966 MySample (3) / Murphy 2008 (1) 0.953 MySample (3) / Osburn 2012 (2) 0.955 MySample (4) / Cory 2012 (4) 0.952 MySample (4) / Fellman 2011 (4) 0.981 MySample (4) / Kowalczuk 2010 (6) 0.953 MySample (4) / Massicotte 2011 (5) 0.957 MySample (4) / Murphy 2008 (7) 0.957 MySample (4) / Osburn 2011 (5) 0.963 MySample (4) / Stedmon 2005 (7) 0.962 MySample (4) / Yamashita 2011 (5) 0.956 MySample (4) / Yang 2012 (3) 0.986 MySample (4) / Yang 2013 MC (3) 0.954 Note: Reference list of the database names is included in the literature by Parr et al., (2014)
5
ACCEPTED MANUSCRIPT
Table S5. Ratios of Indd to Inds for the resin fractions based on Imai’s and Kim’s methods. The fluorescence indicators are obtained from Coble (1996)’s specific peak method (SP) (including B, T, A, M, and C), fluorescent regional index (FRI) (including B, T, A, M, C and sum of those indicators), and PARAFAC components (including C1, C2, C3, and C4).
n Mean(RSD) Min-Max TPI/ HPI(a)
8 9 9 9 9
8 9 9 9 9
0.76 (29) 0.80 (18) 0.88 (11) 0.93 (6) 0.94 (6)
0.36-1.00 0.58-1.00 0.70-0.98 0.85-0.99 0.81-0.99
0.90 (12) 0.84 (23) 0.82 (27) 0.88 (24) 0.86 (37)
9 9 9 9 9
0.96 (7) 1.00 (0) 1.00 (1) 0.99 (4) 0.99 (4)
9 1.04 (10) 9 1.03 (8) 8 1.00 (0)
M AN U
SC
0.01-1.00 0.51-0.95 0.61-0.98 0.74-0.97 0.87-1.00
0.63 (41) 0.97 (5) 1.00 (0) 1.00 (0) 1.00 (0)
0.31-0.98 0.84-1.00 0.99-1.00 1.00-1.00 1.00-1.00
8 9 9 9 9
0.81 (36) 0.87 (20) 0.99 (1) 1.00 (1) 1.00 (0)
0.12-0.98 0.53-1.00 0.97-1.00 0.98-1.00 1.00-1.00
9 9 9 9
1.00 (1) 0.99 (2) 1.01 (1) 0.97 (5)
0.97-1.01 0.94-1.00 1.00-1.03 0.84-1.00
9 9 9 9
1.00 (1) 1.00 (1) 1.02 (3) 0.83 (31)
0.97-1.02 0.98-1.00 1.00-1.09 0.29-1.00
HPO (b/n)
TPI (b/n)
0.68-0.99 0.35-1.00 0.26-0.98 0.34-0.99 0.00-0.99
8 9 9 9 9
0.69 (42) 0.75 (37) 0.84 (14) 0.79 (20) 0.83 (16)
0.11-0.97 0.11-1.00 0.62-0.96 0.54-0.98 0.53-0.94
8 9 9 8 9
0.58 (46) 0.75 (25) 0.79 (24) 0.89 (8) 0.89 (16)
0.22-1.00 0.42-0.93 0.45-0.98 0.74-0.98 0.62-1.00
0.80-1.00 1.00-1.00 0.96-1.00 0.89-1.00 0.89-1.00
8 9 9 9 9
0.83 (26) 0.93 (14) 1.00 (0) 1.00 (1) 1.00 (0)
0.38-0.98 0.62-1.00 0.99-1.00 0.98-1.00 1.00-1.00
9 9 9 9 9
0.63 (30) 0.96 (11) 1.00 (1) 0.98 (5) 1.00 (0)
0.35-0.90 0.67-1.00 0.98-1.00 0.85-1.00 1.00-1.00
1.00-1.32 1.00-1.23 1.00-1.00
9 1.00 (0) 9 0.98 (6) 9 1.01 (2)
1.00-1.01 0.83-1.00 0.97-1.07
9 1.00 (0) 9 1.00 (0) 9 0.94 (21)
0.99-1.00 0.99-1.00 0.42-1.02
EP
9 9 9 9 9
0.57 (58) 0.77 (23) 0.78 (17) 0.85 (8) 0.93 (5)
9 9 9 9 9
HPO/TPI/ HPI (a)
AC C
Kim’s method SP B T A M C FRI B T A M C PARAFAC C1 C2 C3
Fractions on 3rd resin
n Mean(RSD) Min-Max HPO/TPI/HPI(b)
TE D
n Mean(RSD) Min-Max Imai’s method HPO(n) SP B 7 0.69 (34) 0.28-0.98 T 8 0.67 (24) 0.46-0.90 A 8 0.77 (21) 0.42-0.92 M 8 0.75 (32) 0.31-0.95 C 8 0.83 (18) 0.60-0.98 FRI B 7 0.89 (18) 0.63-0.99 T 8 0.98 (4) 0.89-1.00 A 8 0.91 (28) 0.28-1.00 M 8 1.00 (0) 0.99-1.00 C 7 0.99 (3) 0.92-1.00 PARAFAC C1 8 1.04 (9) 0.98-1.28 C2 6 0.99 (1) 0.96-1.00 C3 8 1.26 (57) 1.00-3.04 C4 8 0.96 (10) 0.72-1.00
Fractions on 2nd resin
RI PT
Fractions on 1st resin
Indicators
6
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AC C
EP
TE D
M AN U
SC
RI PT
9 1.00 (1) 1.00-1.02 9 0.90 (22) 0.42-1.00 9 0.95 (13) 0.62-1.00 C4 Note: n – number of samples; RSD – relative standard deviation (unit, %); Min – minimums; Max – Maximums.
7
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Table S6. DOC concentrations, and the intensities of a254 and PARAFAC components of sequentially fractionated DOM fractions for effluent, limnic, and riverine DOM samples based on Imai’s and Kim’s methods Supernatant
Remaining organic matter
DOM
After DAX-8 After AG-MP-50 After AG-MP-1 HPO(b), TPI and HPI TPI and HPI TPI(a/b/n), and (a/n) (n) HPI(a/b/n) Imai’s method
Supernatant
After IRA-67
After DAX-8
After XAD-4
DOM
HPO, TPI, and HPI (b/n)
TPI and HPI (b/n)
HPI (b/n)
RI PT
Fractionation step
Kim’s method
8.12±1.27 31.91±16.49
5.44±0.93 25.25±16.70
4.22±1.28 19.95±20.20
1.68±0.07 10.63±16.87
8.25±1.84 31.94±16.44
6.58±0.64 24.62±15.62
6.00±1.30 19.44±20.68
4.25±1.10 10.65±16.93
C1 (µg QS L-1)
109.46±13.80 70.89±13.94
34.76±17.76
5.06±3.99
102.86±19.41 80.02±37.64
50.33±21.75
26.97±11.56
C2 (µg QS L ) C3 (µg QS L-1) C4 (µg QS L-1) Limnic DOC (mg L-1) a254 (m-1)
60.14±4.89 65.15±3.23 72.03±15.13
38.15±9.54 44.49±12.92 43.20±9.67
19.40±7.76 22.97±5.10 26.96±3.20
3.16±0.43 8.01±1.32
1.95±0.77 5.97±0.87
1.67±0.57 4.40±1.47
C1 (µg QS L-1)
22.48±5.30
11.69±4.44
C2 (µg QS L ) C3 (µg QS L-1)
7.84±1.76 9.59±1.92
C4 (µg QS L-1)
M AN U
-1
SC
Effluent DOC (mg L-1) a254 (m-1)
58.48±10.04 63.59±13.12 66.86±16.90
42.95±21.36 52.00±23.66 35.11±18.58
28.98±11.69 41.24±16.79 22.47±11.86
14.42±6.25 22.45±12.54 11.96±2.37
0.98±0.46 0.86±0.35
3.04±0.14 8.01±1.29
1.75±0.67 5.47±0.42
1.32±0.19 4.40±1.46
1.22±0.10 0.87±0.35
5.55±2.64
0.55±0.36
21.80±1.50
9.18±3.55
6.10±2.17
2.19±0.93
4.53±1.89 6.26±1.41
2.55±1.16 3.12±1.36
0.54±0.21 0.44±0.25
8.62±0.24 10.51±0.60
3.34±1.58 5.10±1.41
2.09±0.78 4.02±1.64
0.79±0.21 2.36±1.28
11.25±3.63
6.17±2.81
2.21±2.99
0.00±0.00
9.01±1.10
4.10±1.57
3.09±1.36
1.49±0.28
Riverine DOC (mg L-1) a254 (m-1) C1 (µg QS L-1) C2 (µg QS L-1)
3.44±0.24 15.37±14.58 29.30±10.18 10.72±4.22
2.00±0.54 12.94±15.11 14.96±8.40 6.79±3.30
1.85±0.39 12.38±16.45 9.89±5.02 4.44±2.11
1.01±0.26 9.96±17.13 0.65±0.77 0.62±0.52
3.39±0.29 15.39±14.58 31.60±6.87 12.35±3.11
1.81±0.22 12.42±15.56 15.86±6.97 5.61±2.56
1.69±0.10 12.33±16.47 8.65±5.99 3.11±2.19
1.44±0.15 9.97±17.14 3.45±1.97 1.28±0.57
C3 (µg QS L-1) C4 (µg QS L-1)
13.15±3.22 18.18±9.04
8.13±3.13 9.44±4.94
5.69±2.33 6.27±3.43
0.61±0.44 0.18±0.16
15.15±3.82 18.88±5.38
8.92±3.42 8.48±3.95
6.35±3.80 4.15±2.07
3.11±1.93 1.93±0.53
EP
AC C
-1
TE D
2.81±2.08 3.11±2.51 2.50±2.05
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Table S7 Removal efficiencies of different resins used on the basis of DOC and PARAFAC components (based on all the samples). Resins
DOC (%)
C1 (%)
C2 (%)
C3 (%)
C4 (%)
AC C
EP
TE D
M AN U
SC
RI PT
Imai's method XAD-8 25.9(11.3) 43.1(19.1)* 36.2(25.9) 34.0(18.4) 40.7(27.8) AG-MP-50 26.7(18.8) 45.9(15.8)* 41.6(13.8) 43.3(12.1)* 47.7(26.9) AG-MP-1 70.8(33.4) 85.1(15.9) 78.7(17.2) 84.4(12.7) 95.5(6.1)* Kim's method IRA-67 35.9(17.6) 44.3(22.3) 48.3(23.1) 37.9(20.1) 53.0(15.4)* XAD-8 15.6(16.3) 37.9(14.0)** 35.6(16.2)* 23.7(14.9) 34.9(21.4)* XAD-4 16.6(15.1) 55.0(15.7)** 54.9(12.1)** 44.8(26.4)* 44.8(19.9)** Note: Values in the bracket is the relative standard deviations. * Significance of independent t-test between PARAFAC components and DOC is < 0.05; ** Significance of independent t-test between PARAFAC components and DOC is < 0.01.
9
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500
3
2.5
2.5
450
1.5 350
1.5 350
1 300
35 0
400 450 E m. (nm)
5 00
550
500
0.5
300
0
250
3
500
300
350
4 00 45 0 Em. ( nm)
500
550
0.5
300
0
250
3
500
2.5
2.5
400
1.5
350
0.5
35 0
400 450 E m. (nm)
5 00
0
550
450
500
5 50
250
0.5
300
350
0
3
4 00 45 0 Em. ( nm)
500
550
0
2.5 2 1.5
350
1
300
0.5
400
M AN U
1 300
400 450 E m. (nm)
2
µ g Q S/L Ex. ( nm)
1.5 350
350
SC
450
µ g Q S/L Ex. ( nm)
400
30 0
1
AG-MP-01
2 Ex. ( nm)
1.5 350
AG-MP -50
450
300
400
1
NaO H
250
2
400
RI PT
400
2.5
450
2 µg Q S/L Ex. (nm)
Ex. (nm)
2
300
3 IRA-67
µg Q S/L Ex. (nm)
450
250
500
XAD- 4
µg Q S/L
3 XAD-8 DAX-8
1
300
250
µ g Q S/L
500
0.5
30 0
350
400 450 E m. (nm)
500
5 50
0
Fig. S1. Fluorescence EEMs of the solvent blank and the resin blanks
120
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500 450
100
) 400 m n (. x E350
80
EP AC C
300 250
40 M
B
300
60 C
/L S Q g ♦
T 350
20
A 400 450 Em. (nm)
500
550
0
Fig. S2. Five defined regions of fluorescence EEMs. The emission (ex) and the excitation (em) wavelength ranges for B, T, A, M, and C are ex 250-300 / em 280-330, ex 250-300 / em 330-380, ex 250-300 / em 380-480, ex 300-320 / em 380-420, and ex 320-370 / em 420-480.
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1
a. Protein-like indicators (B and T)
0
-0.5
-1 -1
2
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L)
1
d. Humic-like indicators (A, M, and C)
0.5 1 1.5 log10(SP (Inds), µg QS/L) g. Protein- and humic-like indicators 2
y= -0.12x + 0.36x + -0.33 2
0.5 n= 127, R = 0.092, p= 0.0000
0
y= -0.19x + 0.33x + -0.11 2
0.5 n= 127, R = 0.539, p= 0.0000
0
TE D
-0.5
2
-1 -1
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L)
1.5
f. Humic-like indicators (C1, C2, and C3)
0.5
n= 76, R2= 0.311, p= 0.0000
SC
0.5 1 1.5 log10(FRI (Inds ), µg QS/L)
h. Protein- and humic-like indicators
0 0.5 1 log10(PFC (Inds ), µg QS/L)
y= 0.10x2 + -0.18x + 0.07
log10(Indd/Inds ,%)
-0.5
2
-0.5
0.5 1 1.5 log10(SP (Inds), µg QS/L)
0
1 Pro Hum FC
n= 77, R2= 0.096, p= 0.0000
0.5
-1 -0.5
2
0
-1 0
1
0
-0.5
-1 -0.5
2
1
Pro Hum FC
1.5
log10(Indd/Inds ,%)
-0.5
1
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
n= 78, R2= 0.156, p= 0.0000
0
-1 0
-0.5
y= -0.07x2 + 0.12x + -0.05
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
0.5
0
-1 -0.5
1.5
e. Humic-like indicators (A, M, and C)
y= -0.11x2 + 0.27x + -0.21
n= 26, R2= 0.720, p= 0.0000
0.5
RI PT
0.5 1 1.5 log10(SP (Inds), µg QS/L)
n= 50, R2= 0.639, p= 0.0000
0.5
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
n= 49, R2= 0.189, p= 0.0000
-0.5
1
y= -0.32x2 + 0.66x + -0.31
y= -0.21x + 0.36x + -0.13
0
-1 0
c. Protein-like indicators (C4)
2
y= -0.27x + 0.79x + -0.67 0.5
1
b. Protein-like indicators (B and T)
2
M AN U
1
0.5
0
0.5 1 1.5 log10(PFC (Inds ), µg QS/L)
i. Protein- and humic-like indicators y= 0.04x2 + -0.05x + 0.00 2
n= 102, R = 0.016, p= 0.0407
2
Pro Hum FC
0
-0.5
-1 -0.5
0
0.5 1 1.5 log10(PFC (inds), µg QS/L)
2
AC C
EP
Fig. S3. Relationships between the ratios of Indd/Inds and Inds for three FDOM indicator groups based on Imai’s fractionation procedures. The charts a, b, and c are protein-like indicators in SP, FRI, and PARAFAC; the charts d, e, and f are humic-like indicators in SP, FRI, and PARAFAC methods; the charts g, h, and i are both above indicators in SP, FRI, and PARAFAC methods. Pro, Hum, and FC in the legends denotes protein-like indicators, humiclike indicators, and fitting curves, respectively. The red arrow represents the lowest concentrations with the Indd/Inds ratios approaching 1.0.
11
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2
2
y= -0.13x + 0.19x + -0.04
0
-0.5
0.5 1 1.5 log10(SP (Inds), µg QS/L)
0
-0.5
-1 -1
2
1
d. Humic-like indicators (A, M, and C) 2
1
0
0.5 1 1.5 log10(SP (Inds), µg QS/L)
g. Protein- and humic-like indicators 2
y= -0.23x + 0.59x + -0.41 0.5 n= 132, R2= 0.142, p= 0.0000
0.5 1 1.5 log10(SP (Inds), µg QS/L)
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L) h. Protein- and humic-like indicators 2
y= -0.11x + 0.15x + -0.04
-0.5
0
0.5 n= 134, R2= 0.629, p= 0.0000
0
2
-0.5
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L)
-0.5
0 0.5 1 1.5 log10(PFC (Inds ), µg QS/L)
2
f. Humic-like indicators (C1, C2, and C3)
y= -0.07x2 + 0.10x + -0.02 0.5 n= 80, R2= 0.569, p= 0.0000
0
-0.5
-1 -2
1.5
1
Pro Hum FC
-0.5
-1 -1
0
SC log10(Indd/Inds ,%)
-0.5
1 Pro Hum FC
0
-1 -0.5
0
-1 -1
2
n= 81, R2= 0.303, p= 0.0000
TE D
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
-0.5
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
0
0.5
y= -0.13x2 + 0.23x + -0.08 0.5 n= 27, R2= 0.840, p= 0.0000
1
e. Humic-like indicators (A, M, and C) y= -0.01x + 0.02x + -0.01
0.5 n= 80, R2= 0.066, p= 0.0004
c. Protein-like indicators (C4)
-1 -1
1.5
2
y= -0.09x + 0.31x + -0.29
-1 -0.5
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L)
1.5
-1 0 1 log10(PFC (Inds ), µg QS/L)
i. Protein- and humic-like indicators y= -0.08x2 + 0.13x + -0.04
log10(Indd/Inds ,%)
1
0.5 n= 53, R2= 0.729, p= 0.0000
log10(Indd/Inds ,%)
0.5 n= 52, R2= 0.492, p= 0.0000
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
y= -0.54x + 1.20x + -0.67
-1 0
1
b. Protein-like indicators (B and T)
RI PT
1
a. Protein-like indicators (B and T)
M AN U
1
0.5 n= 107, R2= 0.573, p= 0.0000
2
Pro Hum FC
0
-0.5
-1 -2
-1 0 1 log10(PFC (inds), µg QS/L)
2
AC C
EP
Fig. S4. Relationships between the ratios of Indd/Inds and Inds for three fluorescence indicator groups based on the Kim’s fractionation procedures. The charts a, b, and c are protein-like indicators in SP, FRI, and PARAFAC; the charts d, e, and f are humic-like indicators in SP, FRI, and PARAFAC methods; the charts g, h, and i are both above indicators in SP, FRI, and PARAFAC methods. Pro, Hum, and FC in the legends denotes protein-like indicators, humic-like indicators, and fitting curves, respectively. The red arrow represents the lowest concentrations with the Indd/Inds ratios approaching 1.0.
12
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380 360
Ex (nm)
320 M
300
T B
280
300
350 400 Em (nm)
450
500
M AN U
240 250
SC
A
260
RI PT
C
340
AC C
EP
TE D
Fig. S5. Peak changes in the original (□) and the subtracted (○) EEM spectra upon resin fractionation
13
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45 40
50 40
30
C1 (%)
DOC (%)
35
60
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
25
c 45
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
35 30
30
20 20
15
20 15
10 5
5 Limnic
Riverine
All
d
60 50
C3 (%)
40
Effluent
Limnic
Ri verine
All
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
60
Effluent
Limnic
Riverine
All
Riverine
All
Riverine
All
Riverine
All
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
50
30
20
40 30
M AN U
20
10 0
0
e
SC
Effluent
0
C4 (%)
0
25
10
10
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
40
RI PT
b 50
C2 (%)
a
10
Effluent
Limnic
Ri verine
0
All
Effluent
Limnic
Imai’s method
70 60
h
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
80 70
30
60
40 30
20
Riverine
0
All
EP
h
60
C3 (%)
AC C
50
Effluent
Limnic
10 Riverine
0
All
i
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
80 70
Effluent
Limnic
HPO, TPI, and HPI HPO TPI HPI
60
40
C4 (%)
Limnic
40
20
10
Effluent
50
30
20
10 0
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
50
40
C1 (%)
DOC (%)
50
g
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
C2 (%)
60
TE D
f
30
50 40 30
20 20 10 0
10 Effluent
Limnic
Riverine
All
0
Effluent
Limnic
Kim’s method Fig. S6. Relative abundances of different resin fractions on the basis of DOC and PARAFAC components. The fractions were obtained by Imai’s (chart a-e) and Kim’s (chart f-i) fractionation methods. The word “All” in the x-axis denotes the average of EfOM, LiOM, and RiOM. 14
ACCEPTED MANUSCRIPT
Script S1. Matlab codes for the peak identification and volume integration in the specific zone.
RI PT
function F_specific=F_specific_FRI(X,Ex,Em,dataname)
M AN U
SC
%% Coble (1996)'s peaks finding and Chen (2003)'s regional integration % ------Description of this code-----% The specific zones, where the peak finding and volume integration are % carried, is shown in Fig. S2 in the supplementary materials. The largest % intensity value in the specific zone will be assigned as the peak. The % volume under the surface of the EEM of specific zone will be integrated % and assigned as the FRI. % ------Description of the input-----% X - 3D data cube (No headers, i.e. samples*Em*Ex) of fluorescence % intensities, which is also the dataset XcQS or XcRU output from % FDOMcorrect.m. % Em - 1D row vector of emission wavelengths corresponding to EEMs. % Ex - 1D row vector of excitation wavelengths corresponding to EEMs. % dataname - 1D row cell of samples' name corresponding to the first % dimension (also known as the samples)
TE D
%% About this Matlab file % Please cite this program as: F_specific_FRI.m % in He and Hur. 2015 ' Conservative hehaviors of fluorescence EEM-PARAFAC % components in resin fractionation processes and its applicability for % characterizing dissolved organic matter% Copyright(C) 2015 W He, % Copyright (C) 2015 W He, % Sejong University % Department of Environment and Energy % Seoul 143-747, South Korea % [email protected]
EP
%% Data pretreatment % Build a similar struct dataset used in the FDOMFluor toolbox. SP=size(X,1); Data_Input=struct('X',X,'Em',Em,'Ex',Ex,'nEm',length(Em),'nEx',length(Ex),'nS ample',SP);
AC C
% Obtain the interval of the emission and excitation wavelength Ex_inv=Ex(2)-Ex(1); Em_inv=Em(2)-Em(1); % Use he EEMCut.m in the FDOMFluor toolbox to cut the 1st and 2nd Rayleigh % scatter [Data_Cut]=EEMCut(Data_Input,25,0,30,0,''); % Cut the Raman scatter from the EEM for w=1:length(Data_Cut.Em); Excitation(w)=1e7/((1e7/Data_Cut.Em(w))+3600); v=find((Data_Cut.Ex>Excitation(w)+0)&(Data_Cut.Ex
15
ACCEPTED MANUSCRIPT
AC C
EP
TE D
M AN U
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%% Peaks finding and regional integration % The emission (ex) and excitation (em) wavelength ranges for B, T, A, M, % and C are: % B ex 250-300 / em 280-330 % T ex 250-300 / em 330-380 % A ex 250-300 / em 380-480 % M ex 300-320 / em 380-420 % C ex 320-370 / em 420-480 % The zone or region division Em_s=[280,330;330,380;380,480;380,420;420,480]; Ex_s=[250,300;250,300;250,300;300,320;320,370]; for s=1:SP F_specific{s+2,1}=dataname{s}; Bigtemp{s,1}=squeeze(Data_Cut.X(s,:,:)); for k=1:5 % Peaks finding Ex_t=[]; Em_t=[]; F_specific{s+2,3*k+1}=max(max(Bigtemp{s,1}((Em_s(k,1)Em(1))/Em_inv+1:(Em_s(k,2)-Em(1))/Em_inv+1,(Ex_s(k,1)Ex(1))/Ex_inv+1:(Ex_s(k,2)-Ex(1))/Ex_inv+1))); [Em_temp,Ex_temp]=find(F_specific{s+2,3*k+1}==Bigtemp{s,1}((Em_s(k,1)Em(1))/Em_inv+1:(Em_s(k,2)-Em(1))/Em_inv+1,(Ex_s(k,1)Ex(1))/Ex_inv+1:(Ex_s(k,2)-Ex(1))/Ex_inv+1)); Ex_t=(Ex_temp-1)*Ex_inv+Ex_s(k,1); Em_t=(Em_temp-1)*Em_inv+Em_s(k,1); F_specific{s+2,3*k-1}=Ex_t(1); F_specific{s+2,3*k}=Em_t(1); % Regional intergration Em_r=[];Ex_r=[]; Em_range=[Em_s(k,1):Em_inv:Em_s(k,2)]; Ex_range=[Ex_s(k,1):Ex_inv:Ex_s(k,2)]; for p1=1:length(Em_range) Em_r(p1)=find(Data_Cut.Em==Em_range(p1)); end for p2=1:length(Ex_range) Ex_r(p2)=find(Data_Cut.Ex==Ex_range(p2)); end F_specific{s+2,k+16}=trapz(Ex_range,trapz(Em_range,Bigtemp{s,1}(Em_r,Ex_r)))/ ((Em_s(k,2)-Em_s(k,1))*((Ex_s(k,2)-Ex_s(k,1)))); end end % Header F_specific{1,2}='Coble (1996)'; F_specific{2,2}='B'; F_specific{2,5}='T'; F_specific{2,8}='A'; F_specific{2,11}='M'; F_specific{2,14}='C'; F_specific{1,17}='Chen (2003)'; F_specific{2,17}='B'; F_specific{2,18}='T'; F_specific{2,19}='A'; F_specific{2,20}='M'; F_specific{2,21}='C'; % Output data including peak wavelengths and integrated volume in the
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% specific zone xlswrite('F_specific(BTAMC)_FRI.xlsx',F_specific);
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Script S2. Quantitive comparsion between the present PARAFAC model with a library which included 38 PARAFAC models.
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function DataBase=comPARAFAC(p,Plot_ID,Plot_id,Parafac_Output_Excel_Name) %% Introduction % Parr et al. (2014) recently proposed a quantitative method for % comparision of the components of various PARAFAC models. They built a % DataBase that selects 38 dataset. They also offer a edited R codes to % conduct the comparision. However, some researcher are not familiar with % that software. After figuring out their R codes, I try to give a MATLAB % code named comPARAFAC.m and a DataBase named DataBase(38).mat for the % researches who are familiar with that language. Before using this % function, the database and 'MyparafacResults.xlsx' should be copied into % the same folder. % The calculation is based on the modified Tucker's Congruence Coefficient % (mTCC) % ------Description-----% DataBase=comPARAFAC(p,Plot,Parafac_Output_Excel_Name) % p - Modified Tucker's Congruence Coefficient (mTCC). When p=0.95, it % means the target PARAFAC components is nearly an exact match with the one % in the database. % Plot_ID - when 1 is assigned, it means showing the standardized PARAFAC % components and original ones of the yours data in figures; when 0 is % assigned, no figures will be shown. % Plot_id - when 1 is assigned, it means showing the comparing figures; % when 0 is assigned, no figures will be shown % Parafac_Output_Excel_Name - the excel file output from the DOMFluor in % the format as 'MyparafacResults.xlsx' %% About this Matlab file % Please cite this program as: comPARAFAC.m % in He and Hur. 2015 ' Conservative behaviors of fluorescence EEM-PARAFAC % components in resin fractionation processes and its applicability for % characterizing dissolved organic matter % Copyright(C) 2015 W He, % Sejong University % Department of Environment and Energy % Seoul 143-747, South Korea % [email protected]
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%% Main function % Input of the data mkdir(['Figure(p=' num2str(p) ')']); % DataBase input load(['DataBase(38).mat']); % Your data input. Just use the "MyparafacResults.xlsx" excel file produced % by DOMFluor package Ex_loading=xlsread(Parafac_Output_Excel_Name,'Ex Loadings'); Em_loading=xlsread(Parafac_Output_Excel_Name,'Em Loadings'); [nD,mD]=size(DataBase); [nEx,~]=size(Ex_loading); [nEm,~]=size(Em_loading); [~,nC]=size(Ex_loading); % Resample the data to a standard set of wavelengths % The wavelength of Ex and Em are both [200 600]. The zero data and missing % data was assigned as NaN. To make the data better, the data was first % smoothed by locally weighted scatterplot smoothing (LOESS). The weighted % least square (WLS) values is assigned as 0.15 as Parr et al. (2014)
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% suggested. for nc=1:nC-1 % Smooth Ex_loading_temp=smooth(Ex_loading(:,1),Ex_loading(:,nc+1),0.15,'loess'); Em_loading_temp=smooth(Em_loading(:,1),Em_loading(:,nc+1),0.15,'loess'); % Spline Ex_loading_sp(:,nc)=spline(Ex_loading(:,1),Ex_loading_temp,Ex_loading(1,1):Ex _loading(nEx,1)); Em_loading_sp(:,nc)=spline(Em_loading(:,1),Em_loading_temp,Em_loading(1,1):Em _loading(nEm,1)); end Ex_loading(Ex_loading==0)=NaN; Em_loading(Em_loading==0)=NaN; Ex_loading_sp(Ex_loading_sp
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DataBase{nd,9}(nc,ns)= (DataBase{nd,7}(nc,ns)*DataBase{nd,8}(nc,ns))^0.5; end end tpp=[]; tpp=DataBase{nd,9}; tpp(tpp=p)=1; DataBase{nd,10}=tpp; [R,C]=find(tpp==1); DataBase{nd,11}{1,1}='Sample (Component) / Database (Component)'; DataBase{nd,11}{1,2}='mTCC'; cal=1; for i=1:length(R) cal=cal+1; DataBase{nd,11}{cal,1}=['MySample (' num2str(R(i)) ') / '... DataBase{nd,2} ' (' num2str(C(i)) ')']; DataBase{nd,11}{cal,2}=DataBase{nd,9}(R(i),C(i)); % Plot the similar dataset if Plot_id FS=15; h=figure(i);
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plot(200:600,DataBase{nd,6}(:,C(i)),'b',200:600,Em_loading_S(:,R(i)),'r','Lin eWidth',2);hold on; plot(200:600,DataBase{nd,5}(:,C(i)),':b',200:600,Ex_loading_S(:,R(i)),':r','L ineWidth',2); axis([200 600 0 1]) title([DataBase{nd,11}{cal,1} ' (' '\itp= ' num2str(roundn(DataBase{nd,11}{cal,2},-3)) ')'],'FontSize',FS); xlabel('Wavelength (nm)','FontSize',FS); ylabel('Relative intensity','FontSize',FS); set(gca,'Fontsize',FS); legend([DataBase{nd,2} ' (' num2str(C(i)) ') Em'],... ['MySample (' num2str(R(i)) ')Em'],... [DataBase{nd,2} ' (' num2str(C(i)) ') Ex'],... ['MySample (' num2str(R(i)) ') Ex']);
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print(gcf,'-dbmp',['Figure(p=' num2str(p) ')\MySample (' num2str(R(i)) ') vs '... DataBase{nd,2} ' (' num2str(C(i)) ')' '.bmp']); close(h); end end % Export the similar dataset in Excel format xlswrite(['comPARAFAC(p=' num2str(p) ')' '.xlsx'], DataBase{nd,11},DataBase{nd,2}); end % Save the database save Analysis_Results.mat DataBase end %% Subfunction about the sumd function [Sigmal]=sumd(s) s(isnan(s))=0; Sigmal=sum(s); end
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References
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Parr, T.B., Ohno, T., Cronan, C.S., Simon, K.S., 2014. comPARAFAC: a library and tools for rapid and quantitative comparison of dissolved organic matter components resolved by Parallel Factor Analysis. Limnol Oceanogr-Meth 12, 114-125.
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S0043-1354(15)30093-2
DOI:
10.1016/j.watres.2015.06.044
Reference:
WR 11386
To appear in:
Water Research
Received Date: 13 May 2015 Revised Date:
23 June 2015
Accepted Date: 26 June 2015
Please cite this article as: He, W., Hur, J., Conservative behavior of fluorescence EEM-PARAFAC components in resin fractionation processes and its applicability for characterizing dissolved organic matter, Water Research (2015), doi: 10.1016/j.watres.2015.06.044. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Conservative behavior of fluorescence EEM-PARAFAC components in resin
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fractionation processes and its applicability for characterizing dissolved organic matter
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Wei He and Jin Hur*
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Department of Environment and Energy, Sejong University, Seoul, South Korea, 143-747
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Revised and Resubmitted to Water Research, June, 2015
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*Corresponding author. Tel.:+82-2-3408-3826; fax:+82-2-3408-4320.
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E-mail addresses:[email protected] (J. Hur)
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Abstract
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In this study, the applicability of the fluorescence excitation-emission matrix combined with
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parallel factor analysis (EEM-PARAFAC) was verified for resin fractionation processes, in
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which bulk dissolved organic matter (DOM) is separated into several fractions presumably
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having similar chemical structures. Here, four PARAFAC components, including three humic-
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like and one protein-like components, were identified from the EEMs of all DOM samples
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through fractionation procedures and the subtracted EEMs between before and after resins for
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different DOM sources (effluent, limnic, and riverine). The PARAFAC components exhibited
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conservative behavior upon resin fractionation, as indicated by the minimal difference in the
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PARAFAC components retained on resins calculated based on the direct subtraction of the
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components and the subtracted EEMs. The conservative behavior of PARAFAC components
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was more obvious compared with other fluorescent DOM (FDOM) indicators derived from peak-
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picking and fluorescence regional integration (FRI) methods. Humic-like components were more
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insensitive to resin fractionation than protein-like component. No consistency was found in the
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relative abundances of the PARAFAC components for the same resin fractions with different
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DOM sources, suggesting that the FDOM composition is more affected by DOM sources rather
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than by the resin fractions. Our study demonstrated that EEM-PARAFAC coupled with resin
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fractionation could provide detailed information on DOM by quantitatively comparing the
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individual PARAFAC components within different resin fractions.
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Key words: Natural organic matter; Resin fractionation; Parallel factor analysis (PARAFAC);
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Fluorescence regional integration; Spectral subtraction.
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1. Introduction Fluorescence excitation-emission matrix combined with parallel factor analysis (EEMPARAFAC) has become a popular tool for probing the fate of dissolved organic matter (DOM)
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and understanding its environmental behaviors in natural and engineered systems (Borisover et
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al., 2009; Ishii and Boyer, 2012; Stedmon et al., 2003; Yang et al., 2015). PARAFAC modeling
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makes it possible to extract dissimilar fluorescent components with minimum residuals from a
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given EEM dataset (Stedmon et al., 2003). The identified components have been successfully
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applied for exploring the biogeochemical dynamics of fluorescent DOM (FDOM) in aquatic
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ecosystems, and the temporal and spatial variations. The individual components have their own
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sources and characteristics, displaying different sensitivities to varying environmental factors
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like light, salinity, pH, temperature, and microorganisms (Borisover et al., 2009; Jørgensen et al.,
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2011; Meng et al., 2013; Saadi et al., 2006; Yamashita et al., 2008; Yang and Hur, 2014; Zhang
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et al., 2009). They also have great potential for assessing water quality and the efficiency of
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DOM removal during treatment systems (Cohen et al., 2014; Gone et al., 2009; Henderson et al.,
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2009; Murphy et al., 2011; Seredyńska-Sobecka et al., 2011).
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To date, several techniques have been suggested for fluorescence data decomposition,
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which included PARAFAC, fluorescence regional integration (FRI), principal component
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analysis (PCA), and self-organizing map (SOM). Among those, PARAFAC and FRI have been
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the most popularly used due to the easy quantification of different FDOM components. The
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interpretation and source assignment of PARAFAC components were primarily based on a
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traditional peak-picking method (Coble, 1996) in which different fluorescence peaks were
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selected from several defined wavelength ranges of EEM. The FRI method has been often
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utilized to differentiate different FDOM components within an EEM, in which EEM was divided
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into several assigned regions and their integrated regional volumes under the EEM surface were
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calculated and treated as the individual FDOM components (Chen et al., 2003; Xue et al., 2012;
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Zhou et al., 2014), although it is often criticized for the physical meaningfulness of the
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integration.
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Resin fractionation has been long used as a DOM characterizing method to obtain
relatively homogeneous fractions from a bulk DOM inherently consisting of heterogeneous
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chemical structures and functional groups (He et al., 2011; Schwede-Thomas et al., 2005; Wu et
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al., 2003; Xue et al., 2012; Zhou et al., 2014). The conventional practices for resin fractionation
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involve the use of acid and base solutions for pH control to retain the desired DOM fractions on
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resins or to elute them from the resins (Imai et al., 2001; Thurman and Malcolm, 1981). Recently,
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a new resin fractionation method was proposed to offer more stable DOM fractions with respect
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to the chemical properties without the pH manipulation (Kim and Dempsey, 2012). Through
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both resin fractionation processes, DOM can be separated into hydrophobics (HPO) and/or
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transphilics (TPI), and hydrophilics (HPI), and further into acidic, basic, and neutral fractions
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(Chen et al., 2003; Imai et al., 2001; Kim and Dempsey, 2012; Li et al., 2014). In general,
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dissolved organic carbon (DOC) and ultraviolet (UV) absorbance have been employed to track
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and quantify the DOM fractions retained on resins and/or eluted from the resins (Imai et al.,
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2002; Kim and Dempsey, 2012). However, such DOM parameters represent only the bulk
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quantity of DOM, providing limited information on the chemical composition of resin fractions
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(Kim and Dempsey, 2012). Addition of other DOM analyses would be more beneficial for
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acquiring detailed information on the fraction’s characteristics.
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In resin fractionation, the subtraction of DOM quantity parameters (i.e. DOC and UV) between before and after resins is simply applied to estimate the fractions retained on resins
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based on mass balance (Imai et al., 2001; Imai et al., 2002; Imai et al., 2003; Kim and Dempsey,
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2012). In the same manner, the spectral subtraction for the fluorescent components distributed
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over EEM could be applied to track the FDOM through the resin fractionation. However, no
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effort has been made to extend the simple subtraction approach into EEM-PARAFAC for
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characterizing different DOM fractions obtained from resin fractionation processes. In fact, this
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is an attempt to test the feasibility of EEM-PARAFAC for tracking DOM in fractionation
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systems where DOM constantly interacts with the solid phase (e.g., resins). There may be two
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approaches available to utilize EEM-PARAFAC to track FDOM in resin fractionation processes.
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One is to obtain the PARAFAC components based on the subtracted EEMs between before and
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after resin (Patra and Mishra, 2002) based on the Beer-Lambert law. The other relies on the
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direct subtraction of the PARAFAC components between before and after resins. It is not clear
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whether or not the two different subtraction approaches would produce the same results for the
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DOM retained on resins.
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In an effort to verify the quantitative applicability of fluorescence EEM-PARAFAC for
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resin fractionation, the two types of resin fractionation methods were employed in this study to
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characterize aquatic DOM with diverse sources (i.e., effluent, limnic, and riverine DOM). The
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main objectives of this study were 1) to verify the applicability of EEM-PARAFAC for
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characterizing DOM in resin fractionation processes, and 2) to compare the differences in the
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FDOM composition of DOM resin fractions among different sources via EEM-PARAFAC.
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2. Materials and methods
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2.1. Sample collection and pretreatment
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Effluent, limnic, and riverine waters were collected three times from a water reclamation
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center in Seoul, Lake Uiam in Gangwon province, and Han River in Seoul, Korea, respectively,
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during the period between November 2014 and January 2015. The in-situ water quality
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parameters of the samples are shown in the supplementary materials (Table S1). The samples
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were filtered through a pre-washed 0.45 µm membrane filter (cellulose acetate, Toyo Roshi
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Kaisha, Ltd., Japan) for further fractionation and analyses.
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2.2. Rein fractionation procedures
The two frequently used DOM fractionation procedures, named Imai’s (Imai et al., 2001)
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and Kim’s (Kim and Dempsey, 2008; 2012) methods, were adopted for this study (Fig. 1). In
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Imai’s method, 1.0 L of DOM sample was fractionated into HPO acids (HPO(a)), HPO neutrals
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(HPO(n)), organic bases (i.e. HPO bases, HPI bases, and TPI bases; HPO/HPI/TPI(b)), TPI/HPI
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acids (TPI/HPI(a)), and TPI/HPI neutrals (TPI/HPI(n)) (Fig. 1a). Before the fractionation, the pH
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of samples was adjusted to 2 by adding concentrated HCl solution. HPO(a) and the HPO(n) were
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retained by the first column (7 cm depth, inner diameter 1.8 cm) packed with nonionic Amberlite
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DAX-8 resin (20-60 mesh), and the retained fraction was subsequently eluted by 100 mL of 0.1
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N NaOH. The DAX-8 resin, poly(methyl methacrylate) resin, is known to have nearly the same
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capability of capturing humic substances (HS) as XAD-8 resin (Peuravuori et al., 2002). It was
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previously demonstrated that the recovery rate of HPO(a) by the alkaline solution was
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approximately 100% (Kim and Dempsey, 2012; Thurman and Malcolm, 1981). HPO/HPI/TPI(b)
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were retained by the second column filled with strong cation-exchange resin (Bio-Rad AG-MP-
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50, 50–100 mesh). TPI/HPI(a) were adsorbed onto strong anion-exchange resin (Bio-Rad AG-
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MP-1, 50–100 mesh) in the third column (Fig. 1a). The surface flow rate was maintained at a rate
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of 4 L min-1 m-2. The initial DOM samples and the DOM fractions eluted from each column (i.e.,
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IF0: NaOH-eluted fraction, and IF1, IF2, and IF3 refer to the DOM fractions eluted from XAD-8,
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AG-MP-50, and AG-MP-1 in Fig. 1a, respectively) were collected to determine DOC, UV, and
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fluorescence EEM.
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In Kim’s method (Fig. 1b), the original DOM samples (1.0 L) were separated into
HPO/TPI/HPI acids (HPO/TPI/HPI (a)), HPO bases/neutrals (HPO(b/n)), TPI bases/neutrals
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(TPI(b/n)), and HPI bases/neutrals (HPI(b/n)) upon resin fractionation. The diethylaminoethyl
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(DEAE) resin used in Kim and Dempsey (2008) was replaced by a weakly basic anion-exchange
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resin (Amberlite IRA-67, 500-750 µm) for this study because of the higher capacity to retain
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HPO/TPI/HPI(a) (Peuravuori and Pihlaja, 1998). DAX-8 and XAD-4 resins were filled in the
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next two columns sequentially to obtain the HPO(b/n) and the TPI(b/n), respectively. The
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surface flow rate was set at the same rate as in Imai’s method. The initial DOM and the eluted
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fractions from the resins of IRA-67, DAX-8, and XAD-4, denoted as KF1, KF2, and KF3 in Fig.
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1b, respectively, were collected for further analyses.
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In order to minimize adverse effects of the resins on the eluted DOM fractions, all the resins were previously cleaned using Soxhlet extraction with methanol for 24 h. For Imai’s
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method, DAX-8 resin was cleaned with 0.1 N NaOH and pre-conditioned with 0.1 N HCl before
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use. The AG-MP-1 and the AG-MP-50 were converted into free-base and free-acid forms using
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1 N NaOH and 1 N HCl, respectively, and rinsed with ultrapure water to adjust the pH into ~7.0.
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The blank samples for DAX-8, AG-MP-50, and AG-MP-1 (B1, B2, and B3, respectively) were
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also collected from each column. The DAX-8 and XAD-4 resins used in Kim’s method were
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similarly cleaned and conditioned except for the maintenance of the neutral pH condition. The
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IRA-67 was conditioned with 1 N NaOH, and rinsed with ultrapure water. In the same manner as
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in Imai’s method, the blank samples for IRA-67, DAX-8, and XAD-4 (B4, B5, and B6,
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respectively) were collected from each column. After the blank of the resins and the eluted
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volumes were all taken into account, the targeted DOM fractions were quantified using the
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formula provided in Table S2. The information on DOC, fluorescence EEMs, and PARAFAC
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components of the alkaline solution (i.e., 0.1 N NaOH) and the resin blanks are shown in Table
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S3 and Fig. S1. The blank correction was needed because some DOM resin fractions were eluted
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in low concentrations (Table S3).
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2.3. Analytical methods
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The pH of all DOM samples including the resin fractions was re-adjusted to ~ 7.0 prior to further analyses (Yang and Hur, 2014). DOC concentrations were measured by a Shimadzu V-
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CPH TOC analyzer with a relative precision of <3% (Yang and Hur, 2014). The absorption
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spectra were scanned by a Shimadzu UV-1300 spectrometer at the wavelengths from 200 nm to
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800 nm. The absorption coefficient at 254 nm (a254) was chosen as a UV indictor for DOM
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monitoring (Imai et al., 2001; Kim and Dempsey, 2012). A luminescence spectrometer (Perkin
172
Elmer LS55) was used to obtain fluorescence EEMs with the emission spectra from 280 to 550
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nm at 0.5 nm increments and the excitation wavelengths from 250 to 500 nm at 5 nm increments.
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Both excitation and emission slits were adjusted to 5 nm, and the scanning speed was 1,200 nm
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min-1 (Hur and Cho, 2012). The EEM data was corrected according to the inter-laboratory
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standard method suggested by Murphy et al. (2010). In brief, EEM was corrected with water
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blank, and the inner filter effect was also considered. The fluorescence intensity was calibrated
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using a quinine sulfate dehydrate solution (10 µg L-1). The data was automatically corrected by a
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Matlab code, namely, FDOMcorrect (Murphy et al., 2010).
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2.4. EEM spectral subtraction and PARAFAC modeling Three groups of the FDOM quantity indicators, including those based on peak-picking, FRI, and PARAFAC methods (Chen et al., 2003; Coble, 1996; Stedmon et al., 2003), were
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obtained to test the feasibility of FDOM for the indicator subtraction upon resin fractionation.
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For specific peak-picking (SP) and FRI methods, five different specific regions (B, T, A, M, and
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C) were assigned to each measured EEM as shown in Fig. S2. They represent tyrosine-like,
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tryptophan-like, humic (fulvic)-like, marine humic-like, and humic-like DOM, respectively
188
(Chen et al., 2003; Coble, 1996). The emission (ex) and excitation (em) wavelength ranges
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corresponding to the regions of B, T, A, M, and C were ex 250-300 / em 280-330, ex 250-300 /
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em 330-380, ex 250-300 / em 380-480, ex 300-320 / em 380-420, and ex 320-370 / em 420-480,
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respectively. The peak intensities and the integrated volumes were calculated using a self-written
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Matlab code (namely, F_specific_FRI.m in Script S1) for the FDOM indicators based on the SP
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and FRI methods, respectively. The integrated value was divided by the corresponding area
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under the surface of EEM so that the values would be expressed in the same unit as the other
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FDOM quantity parameters.
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PARAFAC modeling was performed using a Matlab toolbox, namely, DOMFluor
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(Stedmon and Bro, 2008), with a combined EEM data set of all collected DOM fractions and the
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subtracted EEMs between before and after elution through the resins (n = 142). The number of
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components was identified based on the split-half validation (Bro, 1997). The modified Turker’s
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Congruence Coefficient (mTCC) was employed to compare the identified components with a
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library containing 38 PARAFAC models (Parr et al., 2014). The mTCC values of >0.95 indicate
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the exact match between the two PARAFAC components (Table S4). The related Matlab code
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(namely, comPARAFAC.m) is contained in Script S2. The relative concentration of each
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PARAFAC component was estimated by the Fmax output from DOMFluor.
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The individual FDOM indicators retained on the resins of the fractionation processes were estimated based on the two approaches: by directly subtracting the FDOM quantity
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indicators between before and after elution (Indd), in which the indicators were previously
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determined based on the EEMs of all collected DOM fractions, and by obtaining the indictors
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(Inds) based on the subtracted EEM spectra between DOM before and after resins. The ratios of
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Indd to Inds were used here to evaluate the stability (or conservativeness) of the three indicator
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groups to DOM resin fractionation. If the ratios approach to 1.0 (i.e., Indd is similar to Inds), it is
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assumed that the indicator subtraction has the same effects as the EEM spectral subtraction on
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characterizing the resin-fractionated DOM and also that the FDOM quantity indicator is
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conservative through the resin fractionation processes.
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3. Results and discussion
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3.1. PARAFAC components
Four different PARAFAC components were identified for this study (Fig. 2): three
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humic-like components (C1, C2, and C3) and one protein-like component (C4). The quantitative
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comparison was made using mTCC values for the identified components versus those previously
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reported in the literature (Table S4). The compared components in the literature with mTCC >
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0.95 indicated excellent coincidence with those of this study. C1, with the ex/em ranges of <250-
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280 (325-360) nm and 370-480 nm, encompasses peaks A and C (Coble, 1996). It is dominated
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by UVC humic-like (Peak A) fluorescence, similar to a humic-like component reported by
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Stedmon et al. (2003) and Fellman et al. (2011). This component has a potential terrestrial
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source such as DOM derived from soils, forested streams, and wetlands. It is often observed as
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negatively correlated with salinity in estuarine ecosystems (Fellman et al., 2011; Ishii and Boyer,
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2012). C2, with the ex/em ranges of 260-300 (350-400) nm and 420-520 nm, had some overlaps
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with Peak A and C. This component can absorb light in the UVA and UVB bands, and it is
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associated with large molecular-sized and hydrophobic compounds (Cook et al., 2009; Ishii and
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Boyer, 2012). C3, with the ex/em ranges of 275-350 nm and 350-450 nm, corresponds to marine
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humic-like substances (Peak M) (Coble, 1996). This component is resistant to photo-degradation
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in surface waters (Jørgensen et al., 2011), and it has shown no correlation with quinine-like
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substances (Cory and McKnight, 2005). C4, with the ex/em ranges of <250-300 nm and 320-400
235
nm, is generally assigned to a tryptophan-like component (Peak T) in many aquatic environments
236
such as streams (Cory and Kaplan (2012), rivers (Massicotte and Frenette (2011), estuaries
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(Fellman et al. (2011), coast (Kowalczuk et al. (2010), and open seas (Murphy et al. (2008). It is
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identical to free tryptophan, and can be derived from autochthonous microorganisms (Stedmon
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and Markager, 2005).
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3.2. Comparison of different FDOM indicators regarding conservative behavior upon resin
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fractionation
To evaluate the stability of the FDOM quantity indicators upon resin fractionation, the
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indicators determined based on the two aforementioned subtraction approaches (i.e., the indicator
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subtraction and the EEM subtraction) were all plotted together, and their relationships were
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compared according to the three groups of the FDOM indicators in Fig. 3. Compared with the
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FRI and PARAFAC methods (slope, 1.00, R2 = 1.000), the FDOM indicator group from the SP
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method was more vulnerable to resin fractionation as indicated by the higher degree of the
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deviation from the 1:1 lines and also by the lower coefficients of determination (R2 =0.945 and
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0.926 for Imai’s and Kim’s fractionation methods, respectively) for the linear fitting. The
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Indd/Inds ratios of the three indicator groups were calculated and compared in Table S5 and
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summarized in Table 1. As a result, the PARAFAC components were the most conservative
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indicator group applicable for resin fractionation, as indicated by their average Indd/Inds ratios of
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0.99 ± 0.17, followed by those based on the FRI (0.94 ± 0.15) and SP methods (0.80 ± 0.20). The conservative behavior was further examined regarding the relationships between the
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Indd/Inds ratios and Inds for the three FDOM indicator groups (Figs. S3 and S4). In general, the
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Indd/Inds ratios displayed an increasing trend with the intensity of Inds, implying that the FDOM
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indicators calculated by direct subtraction become more consistent with those based on EEM
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spectral subtraction with a higher FDOM intensity. As expected, the tolerant limits, referring to
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the minimum indicator intensity corresponding to the Indd/Inds ratios approaching 1.0, were the
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highest for the SP indicators. The poor tolerance of the SP indicators can be attributed to the
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changes of the peak locations after EEM spectral subtraction upon the resin fractionation (Fig.
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S5). The FRI method seems to partially avoid this problem because most of the peak changes
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occurred within individually defined regions (Chen et al., 2003). The indicators from both FRI
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and PARAFAC methods displayed good tolerance to the subtraction upon resin fractionation, but
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the PARAFAC indicators are more preferable in that the PARAFAC components can represent
267
independent fluorescent groups. In addition, PARAFAC components were the most insensitive
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to the peak changes resulting from EEM spectral subtraction (Figs. S3 and S4). It is a significant
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finding that the direct subtraction of PARAFAC components is applicable in quantitatively
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tracking FDOM during resin fractionation processes.
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Irrespective of the indicator groups, the humic-like FDOM indicators (Indd/Inds, 0.95 ± 0.16) exhibited higher consistency between the two subtraction approaches than the protein-like
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indicators (Indd/Inds, 0.85 ± 0.22). In detail, the Indd/Inds ratios of the humic-like indicators
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based on both FRI and PARAFAC methods were much closer to 1.00 than those of the SP
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method (p < 0.05). No significant difference was found in the ratios of all FDOM indicators
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between FRI and PARAFAC methods (independent t-test: p= 0.19 and 0.69 for Imai’s and
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Kim’s methods, respectively). However, the difference in the ratios of the protein-like indicators
278
depended on the fractionation methods (p = 0.04 and 0.09 for Imai’s and Kim’s methods,
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respectively). The tolerant limits were mostly higher for the protein-like versus the humic-like
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indicators, and the humic-like indicators were more insensitive to the direct subtraction than the
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protein-like indicators as shown by more data points exhibiting the Indd/Inds ratios close to 1.00
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for each indicator group (Figs. S3 and S4).
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3.3. PARAFAC components of different resin fractions
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3.3.1. Fractionation using Imai’s method
DOC concentrations and the intensities of PARAFAC components for different DOM
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fractions are summarized in Table 2, and their relative abundances were compared for EfOM,
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LiOM, and RiOM in Figs. 4 and S6. The organic acids (i.e., HPO(a) and TPI/HPI(a)) were the
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dominant fractions in all the DOM sources (Table 2 and Fig. S6a), constituting more than 50% of
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the DOM as DOC, which is in accordance with previous studies (Imai et al., 2001; Imai et al.,
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2002). In LiOM and RiOM, HPO(a) was more abundant than TPI/HPI (a), while the opposite
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trend was found for EfOM. Organic bases were the lowest fractions for all the DOM sources,
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accounting for 6%~17% of DOM. Organic neutrals (i.e., HPO(n) and TPI/HPI(n)) was the
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second largest fractions, responsible for ~35% in DOC for DOM samples, and the HPO(n)
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fractions were present in low quantities (7%~13%), which agreed with the previous studies (Imai
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et al., 2002). A representative humic-like fluorescence component, C1, was consistently higher than
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the protein-like component (i.e., C4) for all the resin fractions irrespective of DOM sources
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(Table 2 and Fig. 4a-c) except for HPO(n) of LiOM. It can be hypothesized that humic-like and
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protein-like components are enriched in HPO(a) and organic bases, respectively, considering the
301
chemical characteristics of the resins (Imai et al., 2001). However, our results revealed no
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significant correlations (p >0.05) between the intensities of the two fluorescence components and
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DOC concentrations of the corresponding fractions. This inconsistency may suggest that non-
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fluorescent DOM components are more dominant in the fractions of HPO(a) and organic bases
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and/or that FDOM composition depends more on the DOM sources than on the resin
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characteristics. Our results are in line with a previous study of Chen et al. (2003), in which the
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FDOM composition was not consistent with the types of the resin fractions but instead varied
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with DOM sources.
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components regardless of DOM source (Fig. S6b-e). They corresponded to 48%, 51%, 47%, and
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46% for C1, C2, C3, and C4, respectively, on average for all collected samples. The fraction of
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TPI/HPI(n) accounted for only below 6% of the PARAFAC components even though it
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corresponded to ~25% of DOM on the basis of DOC. The differences in the FDOM composition
314
among the resin fractions with various DOM sources were better illustrated by normalizing the
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PARAFAC component of each fraction to its DOC concentration (Fig. 5). In EfOM, the HPO(n)
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fractions displayed the highest level of FDOM per organic carbon, which were 48.3-114.8 µg QS
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mg-1 C-1 for humic-like components (C1, C2, and C3, Fig. 5a-c) and 107.2 µg QS mg-1 C-1 for
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protein-like component (C4, Fig. 5d), respectively, followed by organic bases. In both LiOM and
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RiOM, however, the organic bases exhibited the highest DOC-normalized FDOM, followed by
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HPO(n). The abundances of the DOC-normalized PARAFAC components were similar for the
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HPO(a) fractions of EfOM, LiOM, and RiOM, indicating that the HPO(a) might have similar
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FDOM composition independent of the DOM sources. Among the resin fractions, TPI/HPI(n)
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had the lowest levels of DOC-normalized FDOM, which were 1.4, 1.0, 1.1, and 0.6 µg QS mg-1
324
C-1 of C1, C2, C3, and C4, respectively, on average for all collected samples. The order of the
325
resin fractions in the levels of DOC-normalized FDOM appears to be more affected by the DOM
326
sources rather than by the PARAFAC components. For example, all the DOC-normalized
327
PARAFAC components on average were higher in the order of HPO(n) > organic bases >
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TPI/HPI(a) ~ HPO(a) > TPI/HPI(n) for EfOM, which was not the case for the other DOM
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sources.
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3.3.2. Fractionation using Kim’s method
The sum of organic acids (HPO/TPI/HPI(a)) and HPI(b/n) dominated in all DOM
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samples (Fig. S6f), constituting more than 68% of the DOM on the basis of DOC. Only ~18% of
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organic acids were found in EfOM, which was similar to the value (15%) previously reported for
335
effluent DOM in a previous study (Kim and Dempsey, 2012). Both LiOM and RiOM exhibited
336
more abundance of organic acids than EfOM. This may be attributed to the higher conductivity
337
or the higher total dissolved solids (TDS) of the effluents versus limnic and riverine water (Table
338
S1), because the inorganic matter may participate in the competitive exchange with organic acids
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for the anionic resin (IRA-67). Note that the same type of the resin was placed in the last column
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of Imai’s method, in which the greater abundance of organic acids was exhibited for the same
341
DOM source compared with those in Kim’s method. Similar relative abundances of PARAFAC components were found between HPO(b/n)
343
and TPI(b/n) fractions in LiOM, and between organic acids and HPO(b/n) fractions in RiOM.
344
For both EfOM and RiOM, either C1 or C4 was dominantly present in the HPO/TPI/HPI(a) and
345
the HPO(b/n) fractions, and the overall FDOM composition was similar for the HPI(b/n)
346
fractions. Among the four resin fractions, the organic acids (HPO/TPI/HPI(a)) discriminated the
347
three DOM sources the most as shown by the highest abundance of C4 in EfOM, followed by
348
RiOM and LiOM (Figs. 4d-4f).
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Except for EfOM, organic acids dominated in FDOM (Fig. S6g-i), accounting for 44%,
350
48%, 38%, and 53% of C1, C2, C3, and C4, respectively, on average for all collected samples.
351
Meanwhile, the compositions of C1 and C2 were similar to each other irrespective of DOM
352
source, implying the similarity between the two humic-like components with respect to the
353
source and/or the tendency of the interactions with the resins. When all collected samples were
354
taken into account, the FDOM composition of the organic bases/neutrals were higher on the
355
order of HPO > TPI > HPI for C1 and C2, while the opposite trend was found for C3. C4 was
356
predominantly present in the organic acid fractions for all the DOM sources.
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DOC-normalized humic-like components did not exhibit major differences in the organic
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acids (HPO/TPI/HPI(a)) among the three DOM sources (Fig. 5e-f) with the average values of
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10.9, 5.7, and 4.7 µg QS mg-1 C-1 for C1, C2 and C3, respectively. In contrast, DOC-normalized
360
protein-like components in the organic acids showed large variability with the DOM sources.
361
The highest value (52.3 µg QS mg-1 C-1) was found in EfOM, followed by RiOM and LiOM.
362
DOC-normalized PARAFAC components in the HPO(b/n) for EfOM and RiOM were similar to
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each other (p > 0.05). The highest normalized PARAFAC components in the TPI(b/n) fractions
364
were observed in RiOM, followed by LiOM and EfOM. The HPI(b/n) fractions had the least
365
abundance of FDOM per organic carbon. On average, DOC-normalized humic-like components
366
were higher on the order of TPI(b/n) ~ HPO(b/n) > organic acids ~ HPI(b/n), while the DOC-
367
normalized protein-like component, in the order of organic acids > HPO(b/n) > TPI(b/n) > HPI
368
(b/n) (Fig. 5e-f).
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3.4. Implications of conservative behavior of PARAFAC components to resin fractionation
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and its applicability for other environmental systems
372
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DOM fractionation combined with EEM-PARAFAC has been successfully applied to understand the dynamics of DOM in complex environmental systems, owing to the enhancement
374
of the resolution in DOM characterization (Murphy et al., 2011; Xue et al., 2012). This study
375
demonstrated that PARAFAC components are stable under spectral subtraction upon resin
376
fractionation processes and thus can be quantitatively treated like DOC and a254 for
377
characterizing DOM resin fractions with different chemical structures/reactivities. In detail, the
378
conservative behavior of PARAFAC components was more pronounced for humic-like versus
379
protein-like FDOM as revealed by the relatively smaller differences between the Indd and Inds
380
values for the humic-like components. This finding suggests that humic-like fluorescence
381
components can be used as a more robust quantity parameter for tracking FDOM when DOM is
382
fractionated upon adsorption. This also provides further insight into the potential applicability of
383
EEM-PARAFAC for other environmental systems requiring the tracking of the individual DOM
384
fractions with different chemical compositions. For example, the approach used for Indd can be
385
applied to study the fate and the behaviors of different FDOM components constantly contacting
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with solid phase (e.g., adsorption and membrane filtration). As shown in this study, however,
387
FDOM is not always coupled with DOC in resin fractionation because FDOM constitutes only a
388
small portion of the total DOM (Table S7). This limitation points out the necessity of combining
389
FDOM indicators with DOC for the full understanding of DOM changes upon fractionation.
390
Although similar carbon structures were previously reported for the same resin fractions from
391
different DOM sources based on nuclear magnetic resonance (NMR) and FT-IR measurements
392
(Chen et al., 2003), our results clearly demonstrated that the chemical composition of resin
393
fractions revealed by EEM-PARAFAC might differ by DOM sources. EEM-PARAFAC coupled
394
with resin fractionation can be a promising tool to provide further information on DOM resin
395
fractions with respect to their chemical composition and the environmental functionalities
396
associated with the individual PARAFAC components. It would be even more beneficial for
397
examining the complex systems with diverse DOM sources mixed together.
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4. Conclusions
Based on the major findings and environmental significance of our results, the following
400 401 402
conclusions can be made. •
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SP method. However, because of the low tolerance limit to the indicator subtraction, the
404
PARAFAC components appear more suitable for the quantity parameter in tracking the
405
individual FDOM components.
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408
The FDOM indicators calculated from FRI and PARAFAC methods both showed higher stability to the indicator subtraction upon resin fractionation compared with those of the
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•
Humic-like components showed more conservative behavior to resin fractionation than the protein-like component as indicated by the smaller differences between the Indd and
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Inds values. Among the resin fractions, organic acid fractions only exhibited similar
410
FDOM composition between Imai’s and Kim’s methods.
411
•
No consistent trends in the relative abundances of PARAFAC components were found for the same resin fractions from different DOM sources, suggesting that the chemical
413
composition of DOM revealed by EEM-PARAFAC is more greatly affected by DOM
414
sources rather than by the types of resin fractions. •
The relative abundances of different resin fractions in DOM as DOC were completely
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different from those on the basis of the FDOM. Furthermore, the distributions of the
417
FDOM resin fractions varied with the individual PARAFAC components, suggesting that
418
EEM-PARAFAC could provide additional information on resin fractions with respect to
419
the environmental fate and reactivity associated with each PARAFAC component.
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Acknowledgements
This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No.2014R1A2A2A09049496).
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Stedmon, C.A., Markager, S., Bro, R., 2003. Tracing dissolved organic matter in aquatic environments using a new approach to fluorescence spectroscopy. Mar. Chem. 82(3-4), 239-254. Thurman, E.M., Malcolm, R.L., 1981. Preparative isolation of aquatic humic substances. Environ. Sci. Technol. 15(4), 463-466. Wu, F.C., Evans, R.D., Dillon, P.J., 2003. Separation and characterization of NOM by highperformance liquid chromatography and on-line three-dimensional excitation emission matrix fluorescence detection. Environ. Sci. Technol. 37(16), 3687-3693. Xue, S., Zhao, Q.L., Wei, L.L., Hui, X.J., Ma, X.P., Lin, Y.Z., 2012. Fluorescence spectroscopic studies of the effect of granular activated carbon adsorption on structural properties of dissolved organic matter fractions. Front. Env. Sci. Eng. 6(6), 784-796. Yamashita, Y., Jaffe, R., Maie, N., Tanoue, E., 2008. Assessing the dynamics of dissolved organic matter (DOM) in coastal environments by excitation emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC). Limnol. Oceanogr. 53(5), 1900-1908. Yang, L., Hur, J., 2014. Critical evaluation of spectroscopic indices for organic matter source tracing via end member mixing analysis based on two contrasting sources. Water Res. 59, 80-89. Yang, L., Hur, J., Zhuang, W., 2015. Occurrence and behaviors of fluorescence EEMPARAFAC components in drinking water and wastewater treatment systems and their applications: a review. Environ. Sci. Pollut. Res., DOI: 10.1007/s11356-11015-1421411353. Zhang, Y.L., van Dijk, M.A., Liu, M.L., Zhu, G.W., Qin, B.Q., 2009. The contribution of phytoplankton degradation to chromophoric dissolved organic matter (CDOM) in eutrophic shallow lakes: Field and experimental evidence. Water Res. 43(18), 4685-4697. Zhou, S.Q., Shao, Y.S., Gao, N.Y., Li, L., Deng, J., Tan, C.Q., Zhu, M.Q., 2014. Influence of hydrophobic/hydrophilic fractions of extracellular organic matters of Microcystis aeruginosa on ultrafiltration membrane fouling. Sci. Total Environ. 470, 201-207.
AC C
528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554
21
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Figure Captions
558
Fig. 1. Schematic diagrams of the resin fractionation procedures based on Imai’s method (a) and
559
Kim and Dempsey (2008, 2012) (b). EEMs of the fractions eluted from resins as well as those
560
retained on resins are shown for effluent DOM (EfOM).
561
RI PT
557
Fig. 2. Representative EEMs and the spectral loadings of four identified PARAFAC components.
563
Individual excitation and emission loading are shown for the comparison of the modeled and the
564
split-half (split 1-2 and 3-4) validated results.
M AN U
SC
562
565
Fig. 3. Comparison of the FDOM indicators from the subtracted EEM spectra (Inds) versus those
567
from the direct subtraction between the two indicators before and after resins (Indd) for Imai’s
568
fractionation method (chart a-c) and Kim’s fractionation method (chart d-f). Chart a and d are
569
based on the FDOM indicators from the peak-picking method; Chart b and e are based the
570
FDOM indicators from the FRI method; Chart c and f are based on PARAFAC components.
TE D
566
571
Fig. 4. Relative abundance (%) of four PARAFAC components for different resin fractions of
573
EfOM, LiOM, and RiOM based on Imai’s method (chart a-c) and Kim’s method (chart d-f).
AC C
574
EP
572
575
Fig. 5. DOC-normalized intensities of PARAFAC components in different resin fractions for
576
EfOM, LiOM, and RiOM. Fractions were obtained by Imai’s method (chart a-d) and Kim’s
577
method (chart e-h). “All” in the x-axis represents the average values of each fraction over EfOM,
578
LiOM, and RiOM.
579
22
ACCEPTED MANUSCRIPT
Tables
RI PT
Table 1. Ratios of Indd to Inds for the fractions retained on various resins based on Imai’s and Kim’s fractionation methods. FDOM quantity indicator groups are obtained from Coble (1996)’s specific peak-picking (SP) method (SPprotein: the peaks of B and T, SPhumic: the peaks of A, M, and C), fluorescent regional integration (FRI) method (FRIprotein: the regions of B and T, FRIhumic: the regions of A, M, and C), and PARAFAC components (PARAFAChumic: C1, C2, and C3, and PARAFACprotein: C4). Indicator
Fractions on 1st resin
Fractions on 2nd resin
groups
n
n
Imai’s method
HPO (n)
SPtotal
39
0.74 (26)
0.28-0.98
44
0.79 (26)
SPprotein
15
0.68 (28)
0.28-0.98
17
0.68 (40)
SPhumic
24
0.78 (24)
0.31-0.98
27
0.86 (12)
FRItotal
38
0.95 (14)
0.28-1.00
45
FRIprotein
15
0.94 (13)
0.63-1.00
FRIhumic
38
0.95 (14)
0.28-1.00
PARAFACtotal
30
1.07 (36)
0.72-3.04
PARAFACprotein
8
0.96 (10)
0.72-1.00
PARAFAChumic
22
1.11 (39)
0.96-3.04
Kim’s method
HPO/TPI/ HPI (a)
SPtotal
45
0.86 (25)
0.00-1.00
44
0.78 (26)
0.11-1.00
43
0.78 (27)
0.22-1.00
SPprotein
18
0.87 (18)
0.35-1.00
17
0.72 (38)
0.11-1.00
17
0.67 (36)
0.22-1.00
SPhumic
27
0.85 (29)
0.00-0.99
27
0.82 (16)
0.53-0.98
26
0.85 (17)
0.45-1.00
FRItotal
45
0.99 (4)
0.80-1.00
44
0.96 (13)
0.38-1.00
45
0.91 (19)
0.35-1.00
FRIprotein
18
0.98 (5)
0.80-1.00
17
0.89 (20)
0.38-1.00
18
0.79 (28)
0.35-1.00
FRIhumic
45
0.99 (4)
0.80-1.00
44
0.96 (13)
0.38-1.00
45
0.91 (19)
0.35-1.00
PARAFACtotal
35
1.02 (7)
1.00-1.32
36
0.97 (11)
0.42-1.07
36
0.97 (12)
0.42-1.02
PARAFACprotein
9
1.00 (1)
1.00-1.02
9
0.90 (22)
0.42-1.00
9
0.95 (13)
0.62-1.00
PARAFAChumic
26
1.02 (8)
1.00-1.32
27
1.00 (4)
0.83-1.07
27
0.98 (11)
0.42-1.02
Min-Max
Mean(RSD)
HPO/TPI/HPI (b)
n
Mean(RSD)
Min-Max
TPI/ HPI (a) 44
0.86 (16)
0.36-1.00
0.01-1.00
17
0.78 (23)
0.36-1.00
0.61-1.00
27
0.91 (8)
0.70-0.99
0.92 (20)
0.31-1.00
44
0.94 (17)
0.12-1.00
18
0.80 (32)
0.31-1.00
17
0.84 (27)
0.12-1.00
45
0.92 (20)
0.31-1.00
44
0.94 (17)
0.12-1.00
36
0.99 (3)
0.84-1.03
36
0.96 (15)
0.29-1.09
9
0.97 (5)
0.84-1.00
9
0.83 (31)
0.29-1.00
27
1.00 (2)
0.94-1.03
27
1.00 (2)
0.97-1.09
TE D
M AN U
0.01-1.00
HPO (b/n)
EP
AC C
Min-Max
SC
Mean(RSD)
Fractions on 3rd resin
TPI (b/n)
Note: n – number of samples; RSD – relative standard deviation (%); Min – minimum; Max – maximum.
1
ACCEPTED MANUSCRIPT
Fractionation methods Organic matter
Imai's method HPO (a)a
HPO (n)
HPO/TPI/HPI (b)
RI PT
Table 2. DOC concentrations and the intensities of PARAFAC components for different resin fractions obtained from Imai’s and Kim’s fractionation methods. Kim's method
TPI/HPI (a)
TPI/ HPI (n)
HPO/TPI/HPI (a)
HPO (b/n)
TPI (b/n)
HPI (b/n)
1.68±1.26 22.84±18.36
0.88±0.60 22.70±18.61
1.66±1.24 29.70±15.92
4.03±1.04 23.36±13.47
15.53±12.21
15.42±12.39
13.97±9.69
14.57±8.10
2.04±0.56 0.65±0.80 14.83±7.45 23.86±5.76
1.43±1.35 36.14±6.86
2.41±1.18 29.75±19.29
1.60±0.06 5.06±3.99
C2 (µg QS L-1)
7.76±2.40
14.30±5.82
18.77±1.91
16.59±8.53
2.81±2.08
C3 (µg QS L ) C4 (µg QS L-1)
4.38±2.62 5.76±4.79
16.29±8.94 23.17±7.20
21.49±7.92 16.38±9.17
19.85±6.28 24.65±4.10
3.11±2.51 2.50±2.05
11.59±13.27 31.75±2.22
12.56±11.70 31.55±2.51
10.76±6.99 12.65±7.29
18.79±10.84 10.54±9.63
Limnic DOC (mg L-1) C1 (µg QS L-1)
0.99±0.36 5.78±1.25
0.23±0.05 6.52±8.71
0.36±0.31 6.14±2.34
0.66±0.27 5.03±3.05
0.93±0.44 0.55±0.36
1.28±0.55 12.62±2.11
0.50±0.74 3.07±1.92
0.10±0.14 3.93±1.54
1.16±0.09 2.19±0.93
C2 (µg QS L-1)
3.33±0.49
1.34±2.18
1.99±1.09
2.01±1.35
0.54±0.21
5.27±1.49
1.27±0.88
1.30±0.56
0.79±0.21
C3 (µg QS L ) C4 (µg QS L-1)
1.89±0.53 2.01±0.88
2.10±2.97 4.47±4.36
3.13±0.39 4.04±1.38
2.60±1.41 2.89±3.04
0.44±0.25 0.00±0.00
5.42±0.81 4.92±1.19
1.07±1.09 1.11±1.34
1.67±1.41 1.63±1.07
2.36±1.28 1.49±0.28
Riverine DOC (mg L-1) C1 (µg QS L-1)
1.01±0.26 7.47±1.47
0.43±0.08 6.67±4.10
0.24±0.17 5.07±3.49
0.80±0.14 9.36±5.45
0.96±0.25 0.65±0.77
1.58±0.08 15.74±6.78
0.21±0.14 7.21±5.31
0.24±0.23 5.21±4.26
1.37±0.14 3.45±1.97
C2 (µg QS L-1)
3.14±1.50
1.88±2.03
2.37±1.61
3.82±2.42
0.62±0.52
6.74±2.72
2.50±2.16
1.83±1.61
1.28±0.57
2.54±0.32 3.96±0.57
2.23±1.79 4.97±3.84
2.42±1.02 3.26±2.10
5.02±2.76 6.66±3.72
0.61±0.44 0.18±0.16
6.24±2.48 10.41±5.66
2.57±1.88 4.35±3.70
3.24±2.50 2.28±1.84
3.11±1.93 1.93±0.53
-1
C3 (µg QS L ) C4 (µg QS L-1)
M AN U
TE D
EP
-1
AC C
-1
SC
Effluent DOC (mg L-1) C1 (µg QS L-1)
Note: Data are expressed by average ± standard deviation.
2
ACCEPTED MANUSCRIPT
a. Imai’s fractionation method
b. Kim’s fractionation method 500 KE1(2) (DOM)
500
500
120
40
250
IF0 300
350
DAX-8
20
400 450 Em. (nm)
500
550
500
500
550
500
0
70
Elute with 0.1 M NaOH
100
400
50 40
350
20
500
550
0
60 350
120
60 350
IF2 500
550
KE3(2) (TPI/HPI b/n)
400 450 Em. (nm)
500
550
0
AG-MP-1
0
TPI/HPI (acids)
450 400
100
80
80 60
350 300
120
40
350
300
350
300
80 60
350 40 300
300
350
400 450 Em. (nm)
500
300
20
350
400 450 Em. (nm)
500
0
550
400 450 Em. (nm)
500
550
EP
10
90
450 400
XAD-4
60 50
20
300
350
400 450 Em. (nm)
500
550
90
400
TPI (bases/neutrals)
80 70 60 50 40
350
30 20
300
10 90
HPI (bases/neutrals)
70 60 50
30
350
20 10 400 450 Em. (nm)
500
550
250
80
40
KF3
300
70
40
KE(2) (TPI b/n) 450
350
250
80
10
500
300
Fig. 1
20
550
30
550
0
TE D
250
IF3
350
500
HPO (bases/neutrals)
500
10
Ex. (nm)
250
QS µg/L
400
100
400 450 Em. (nm)
350
250
KE4(2) (HPI b/n)
TPI /HPI (neutrals)
450
400
20
KF2
20
IE5(1) (HiN)
30
300
60
40
500
40
70
50
250
50
KE(2) (HPO b/n) 450
DAX-8
400
300
120
IE(1) (BaS)
Ex. (nm)
400 450 Em. (nm)
Ex. (nm)
350
350
500
20
300
300
550
30
40
300 250
QS µg/L
400
AC C
Ex. (nm)
80
500
60
500
10
400 450 Em. (nm)
90
20
100
250
350
450
300
20
KF1 300
500
40
IE4(1) (HiA/HiN) 450
250
80
Ex. (nm)
500
400 450 Em. (nm)
AG-MP-50
400
100
70
350
250
QS µg/L
350
300
HPO/TPI/HPI (bases)
M AN U
300
120 IE(1) (HoN)
450
Ex. (nm)
250
500
40
IF1
QS µg/L
60 350
400
30
QS µg/L
Ex. (nm)
80 400
80
HPO/TPI/HPI (acids)
300
60
SC
Ex. (nm)
120
450
300
80
450
IE3(1) (HiA/BaS/HiN)
IRA-67
90
Ex. (nm)
400 450 Em. (nm)
90
KE(2) (HPO/TPI/HPI a)
Ex. (nm)
350
550
QS µg/L
300
500
450
0
KE2(2) (HPO/TPI/HPI b/n)
250
400 450 Em. (nm)
500
20
QS µg/L
300
40 300
60 350
350
QS µg/L
60 350
QS µg/L
Ex. (nm)
80
400
QS µg/L
100
400
10
300
80 Ex. (nm)
HPO(neutrals)
20
250 100
HPO(acids)
450
IE(1) (HoN) 450
40
300
120 IE2(1) (AHS)
0
550
50
QS µg/L
400 450 Em. (nm)
60
350
QS µg/L
350
70
30
DOM
20
300
400
300
350
400 450 Em. (nm)
500
550
QS µg/L
300
80
Filtrated water (DOM)
QS µg/L
Ex. (nm)
60 350
250
500
80 QS µg/L
Ex. (nm)
400
450
100
Ex. (nm)
Filtrated water (DOM)
40
DOM
90
120 IE1(1) (DOM)
450
RI PT
500
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT
AC C
EP
TE D
Fig. 2
ACCEPTED MANUSCRIPT
30 20
25
50
c
Protein Humic Fitting Curve
20 15 10
10
10
20 30 Ind (SP, µg QS/L) s
40
0 0
50
Ind (FRI, µg QS/L) d
e 30
20
40
25
Protein Humic Fitting Curve
20 15 10
20 30 40 Ind (SP, µg QS/L) s
50
60
0 0
40
y= 1.00x + -0.03 n= 134, R2= 1.000, p= 0.0000
10
20 30 Ind (FRI, µg QS/L) s
TE D
Fig. 3
EP
f
50
Protein Humic Fitting Curve
30 20 10
M AN U
5
y= 0.85x + 0.17 n= 132, R2= 0.926, p= 0.0000
10
y= 1.00x + -0.05 n= 102, R2= 1.000, p= 0.0000 20 30 40 Ind (PFC, µg QS/L) s
50
10
10
10
SC
Protein Humic Fitting Curve
30
0 0
20
0 0
35
AC C
Ind (SP, µg QS/L) d
40
30
s
50
d
y= 1.00x + -0.09 n= 127, R2= 1.000, p= 0.0000 10 20 30 Ind (FRI, µg QS/L)
Ind (PFC, µg QS/L) d
0 0
5
y= 0.90x + -0.66 n= 127, R2= 0.945, p= 0.0000
Protein Humic Fitting Curve
40
RI PT
Ind (FRI, µg QS/L) d
Ind (SP, µg QS/L) d
40
35
b 30
Protein Humic Fitting Curve
Ind (PFC, µg QS/L) d
50
a
40
0 0
y= 1.00x + -0.01 n= 107, R2= 1.000, p= 0.0000
10
20 30 Ind (PFC, µg QS/L) s
40
50
80 70 60 50 40 30 20
b
100
80
10 Fr1
Fr2
Fr3
HPO(n)
HPO/TPI/ HPI (b)
Fr4
30 20
80
Fr2
HPO(a)
Fr3
HPO(n)
HPO/TPI/ HPI (b)
Fr4
PARAFAC component (%)
e
60 50 40 30 20 10
90 80
HPO/TPI/ HPI (a)
Fr2
HPO (b/n)
Fr3
TPI (b/n)
Fr4
Limnic
C1 C2 C3 C4
60 50 40 30 20
HPI(b/n)
30 20
Fr1
HPO(a)
f
90 80
Fr2
Fr3
HPO(n)
HPO/TPI/ HPI (b)
Fr4
Fr5
TPI/HPI (a) TPI/ HPI (n)
Riverine
C1 C2 C3 C4
70 60 50 40 30 20 10
Fr1
HPO/TPI/ HPI (a)
Fr2
HPO (b/n)
TE D
Fr3
TPI (b/n)
Fig. 4
EP
40
TPI/HPI (a) TPI/ HPI (n)
70
0
50
100
10 Fr1
60
SC
Effluent
C1 C2 C3 C4
70
0
Fr5
Riverine
C1 C2 C3 C4
90
10 Fr1
100
70
0
40
TPI/HPI (a) TPI/ HPI (n)
AC C
PARAFAC component (%)
80
50
0
Fr5
100 90
60
100
10
HPO(a)
d
70
c
PARAFAC component (%)
0
Limnic
C1 C2 C3 C4
90
RI PT
Effluent
C1 C2 C3 C4
90
PARAFAC component (%)
100
M AN U
PARAFAC component (%)
a
PARAFAC component (%)
ACCEPTED MANUSCRIPT
Fr4
HPI(b/n)
0
Fr1
HPO/TPI/ HPI (a)
Fr2
HPO (b/n)
Fr3
TPI (b/n)
Fr4
HPI(b/n)
ACCEPTED MANUSCRIPT
200
C2 (ug QS/(mg C)
150
100
50
Effluent
Limnic
Ri verine
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
150
Effluent
Ri verine
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
100
0
Effluent
250
150
Limnic
Ri verine
All
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
AC C
100
All
50
0
100
0
f 250
Riverine
All
Effluent
Limnic
h
Effluent
Limnic
Riverine
All
Riverine
All
Riverine
All
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
150
100
50
0
Effluent
Limnic
250
200
EP
200
Limnic
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
150
200
150
50
C3 (ug QS/(mg C)
Limnic
TE D
C1 (ug QS/(mg C)
200
Effluent
50
C2 (ug QS/(mg C)
0
0
d 250
M AN U
100
e 250
100
200
50
g
All
C4 (ug QS/(mg C)
C3 (ug QS/(mg C)
200
150
50
C4 (ug QS/(mg C)
0
c 250
HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
SC
C1 (ug QS/(mg C)
200
b 250 HPO(a) HPO(n) HPO/TPI/HPI (b) TPI/HPI (a) TPI/HPI (n)
RI PT
a 250
HPO/TPI/HPI (a) HPO (b/n) TPI (b/n) HPI (b/n)
150
100
50
Ri verine
All
0
Fig. 5
Effluent
Limnic
ACCEPTED MANUSCRIPT
Highlights
► Rigorous tests on the applicability of EEM-PARAFAC for resin fractionation of
RI PT
DOM.
►PARAFAC components were the superior to other FDOM indicators in the
SC
conservativeness.
M AN U
►Lower sensitivity to spectral subtraction for humic-like vs. protein-like components.
►FDOM composition of resin fractions is more affected by DOM sources rather than
AC C
EP
TE D
resins.
ACCEPTED MANUSCRIPT
Conservative behavior of fluorescence EEM-PARAFAC components in resin fractionation
Wei He and Jin Hur*
RI PT
processes and its applicability for characterizing dissolved organic matter
M AN U
SC
Department of Environment and Energy, Sejong University, Seoul 143-747, South Korea
Pages: 19; Tables: 7; Figures: 6;
AC C
EP
TE D
Script: 2.
1
ACCEPTED MANUSCRIPT
Table S1. In-situ water quality parameters of effluent, limnic, and riverine water samples and selected parameters for the DOM (Mean±standard deviation, n=3). Effluent water
Limnic water
pH EC (µs cm-1) TDS (mg L-1) DOC a254 (m-1) C1 (µg QS L-1) C2 (µg QS L-1) C3 (µg QS L-1) C4 (µg QS L-1) C1 (%) C2 (%) C3 (%) C4 (%)
6.90±0.13 523±35 335±22 8.19±1.41 31.93±14.73 106.09±15.52 59.36±7.13 63.93±8.53 69.67±14.70 35.49±1.14 19.92±0.70 21.44±1.42 23.15±1.82
7.12±0.16 76±2 49±1 3.10±0.29 8.01±1.17 22.20±3.52 8.24±1.20 10.01±1.36 10.13±2.71 43.92±1.12 16.35±1.31 19.90±1.54 19.82±2.86
Riverine water
RI PT
Parameters
M AN U
SC
7.31±0.21 182±4 116±3 3.41±0.24 15.38±13.04 30.52±7.88 11.56±3.44 14.09±3.33 18.57±6.69 41.05±1.23 15.41±0.53 19.09±1.46 24.46±2.24
AC C
EP
TE D
Note: EC – Electrical conductivity; TDS – Total dissolved solids
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Table S2. Formula used for calculating each DOM resin fractions. Fractions
Formula
RI PT
Imai’s method IF0,cor IF1,cor IF2,cor IF3,cor HPO acids HPO neutrals HPO/TPI/HPI bases TPI/HPI acids TPI/HPI neutrals Kim’s method KF1,cor KF2,cor KF3,cor HPO/TPI/HPI acids HPO bases/neutrals TPI bases/neutrals HPI bases/neutrals
M AN U
SC
(IF0 – BNaOH) × (Velutant) / (Vsample) IF1 – B1 (IF2 – B2) / [(Vsample – Vmonitoring) / Vsample] (IF3 – B3) / [(Vsample – 2Vmonitoring) / Vsample] IF0,cor DOM – IF0,cor – IF1,cor IF1,cor – IF2,cor IF2,cor – IF3,cor IF3,cor
KF1 – B4 (KF2 – B5) / [(Vsample – Vmonitoring) / Vsample] (KF3 – B6) / [(Vsample – 2Vmonitoring) / Vsample] DOM – KF1,cor KF1,cor – KF2,cor KF2,cor – KF3,cor KF3,cor
AC C
EP
TE D
Note: DOM, IF0, IF1, IF2, IF3, KF1, KF2, and KF3 are the fractions shown in Fig. 1. BNaOH denotes the concentration of NaOH. Vsample, Vmonitoring, and Velutant are the volumes of the initial sample (1000 mL), monitored samples (50 mL per time), and elutants (100 mL).
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ACCEPTED MANUSCRIPT
Table S3. DOC concentrations and the intensities of fluorescence EEM-PARAFAC components for an alkaline solvent and the resin blanks, and the minimum DOC and PARAFAC components of each fraction based on Imai’s and Kim’s methods C2 (µg QS L-1)
5.80 1.37 1.15 0.54 0.43 (7.4%) 0.20 (14.8%) 0.13 (11.6%) 0.12 (21.7%)
44.50 6.74 3.74 0.79 0.99 (2.2%) 0.12 (1.8%) 0.88 (23.6%) 0.78 (98.7%)
16.08 2.42 1.48 0.15 0.35 (2.2%) 0.02 (1.0%) 0.00 (0.0%) 0.00 (0.0%)
1.31 1.07 1.11 0.11 (8.0%) 0.20 (19.0%) 0.16 (16.8%)
5.10 3.80 1.61 0.01 (0.1%) 0.12 (3.3%) 0.20 (14.0%)
1.54 1.22 0.52 0.00 (0.2%) 0.02 (1.9%) 0.01 (2.9%)
C3 (µg QS L-1)
C4 (µg QS L-1)
13.17 4.70 1.80 0.20 0.47 (3.5%) 0.02 (0.3%) 0.07 (4.0%) 0.07 (35.8%)
12.66 3.39 1.77 1.64 2.26 (17.9%) 0.12 (3.6%) 1.66 (93.6%) 1.64 (100.0%)
3.47 2.82 0.80 0.00 (0.0%) 0.02 (0.5%) 0.00 (0.0%)
2.61 2.19 1.43 0.32 (12.2%) 0.12 (5.6%) 0.27 (23.7%)
RI PT
C1 (µg QS L-1)
SC
Imai’s method IF0sample,min IF1sample,min IF2sample,min IF3sample,min BNaOH B1 B2 B3 Kim’s method KF1sample,min KF2sample,min KF3sample,min B1 B2 B3
DOC mg L-1
M AN U
Fractions
AC C
EP
TE D
Note: Values in the brackets denote the percentage of the blank to the minimum quantity of the fractions, i.e., IF0sample,min / BNaOH × 100% or IF1sample,min / B1 × 100%.
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Table S4. Modified Turker’s Congruence Coefficient (mTCC) for the PARAFAC components between the present study and 38 PARAFAC models summarized by Parr et al. 2014. mTCC
RI PT
Sample (Component) / Database (Component)
AC C
EP
TE D
M AN U
SC
MySample (1) / Fellman 2011 (1) 0.968 MySample (1) / Parr 2014 (1) 0.975 MySample (1) / Stedmon 2003 (1) 0.964 MySample (2) / Burrows 2013 (2) 0.959 MySample (2) / Chen 2010 (1) 0.987 MySample (2) / Kowalczuk 2010 (1) 0.957 MySample (2) / Parr 2014 (2) 0.979 MySample (2) / Singh 2013 (1) 0.971 MySample (2) / Yamashita 2011 (2) 0.958 MySample (3) / CM 2005 (10) 0.964 MySample (3) / Kothawala 2012 (2) 0.972 MySample (3) / Murphy 2006 (2) 0.966 MySample (3) / Murphy 2008 (1) 0.953 MySample (3) / Osburn 2012 (2) 0.955 MySample (4) / Cory 2012 (4) 0.952 MySample (4) / Fellman 2011 (4) 0.981 MySample (4) / Kowalczuk 2010 (6) 0.953 MySample (4) / Massicotte 2011 (5) 0.957 MySample (4) / Murphy 2008 (7) 0.957 MySample (4) / Osburn 2011 (5) 0.963 MySample (4) / Stedmon 2005 (7) 0.962 MySample (4) / Yamashita 2011 (5) 0.956 MySample (4) / Yang 2012 (3) 0.986 MySample (4) / Yang 2013 MC (3) 0.954 Note: Reference list of the database names is included in the literature by Parr et al., (2014)
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Table S5. Ratios of Indd to Inds for the resin fractions based on Imai’s and Kim’s methods. The fluorescence indicators are obtained from Coble (1996)’s specific peak method (SP) (including B, T, A, M, and C), fluorescent regional index (FRI) (including B, T, A, M, C and sum of those indicators), and PARAFAC components (including C1, C2, C3, and C4).
n Mean(RSD) Min-Max TPI/ HPI(a)
8 9 9 9 9
8 9 9 9 9
0.76 (29) 0.80 (18) 0.88 (11) 0.93 (6) 0.94 (6)
0.36-1.00 0.58-1.00 0.70-0.98 0.85-0.99 0.81-0.99
0.90 (12) 0.84 (23) 0.82 (27) 0.88 (24) 0.86 (37)
9 9 9 9 9
0.96 (7) 1.00 (0) 1.00 (1) 0.99 (4) 0.99 (4)
9 1.04 (10) 9 1.03 (8) 8 1.00 (0)
M AN U
SC
0.01-1.00 0.51-0.95 0.61-0.98 0.74-0.97 0.87-1.00
0.63 (41) 0.97 (5) 1.00 (0) 1.00 (0) 1.00 (0)
0.31-0.98 0.84-1.00 0.99-1.00 1.00-1.00 1.00-1.00
8 9 9 9 9
0.81 (36) 0.87 (20) 0.99 (1) 1.00 (1) 1.00 (0)
0.12-0.98 0.53-1.00 0.97-1.00 0.98-1.00 1.00-1.00
9 9 9 9
1.00 (1) 0.99 (2) 1.01 (1) 0.97 (5)
0.97-1.01 0.94-1.00 1.00-1.03 0.84-1.00
9 9 9 9
1.00 (1) 1.00 (1) 1.02 (3) 0.83 (31)
0.97-1.02 0.98-1.00 1.00-1.09 0.29-1.00
HPO (b/n)
TPI (b/n)
0.68-0.99 0.35-1.00 0.26-0.98 0.34-0.99 0.00-0.99
8 9 9 9 9
0.69 (42) 0.75 (37) 0.84 (14) 0.79 (20) 0.83 (16)
0.11-0.97 0.11-1.00 0.62-0.96 0.54-0.98 0.53-0.94
8 9 9 8 9
0.58 (46) 0.75 (25) 0.79 (24) 0.89 (8) 0.89 (16)
0.22-1.00 0.42-0.93 0.45-0.98 0.74-0.98 0.62-1.00
0.80-1.00 1.00-1.00 0.96-1.00 0.89-1.00 0.89-1.00
8 9 9 9 9
0.83 (26) 0.93 (14) 1.00 (0) 1.00 (1) 1.00 (0)
0.38-0.98 0.62-1.00 0.99-1.00 0.98-1.00 1.00-1.00
9 9 9 9 9
0.63 (30) 0.96 (11) 1.00 (1) 0.98 (5) 1.00 (0)
0.35-0.90 0.67-1.00 0.98-1.00 0.85-1.00 1.00-1.00
1.00-1.32 1.00-1.23 1.00-1.00
9 1.00 (0) 9 0.98 (6) 9 1.01 (2)
1.00-1.01 0.83-1.00 0.97-1.07
9 1.00 (0) 9 1.00 (0) 9 0.94 (21)
0.99-1.00 0.99-1.00 0.42-1.02
EP
9 9 9 9 9
0.57 (58) 0.77 (23) 0.78 (17) 0.85 (8) 0.93 (5)
9 9 9 9 9
HPO/TPI/ HPI (a)
AC C
Kim’s method SP B T A M C FRI B T A M C PARAFAC C1 C2 C3
Fractions on 3rd resin
n Mean(RSD) Min-Max HPO/TPI/HPI(b)
TE D
n Mean(RSD) Min-Max Imai’s method HPO(n) SP B 7 0.69 (34) 0.28-0.98 T 8 0.67 (24) 0.46-0.90 A 8 0.77 (21) 0.42-0.92 M 8 0.75 (32) 0.31-0.95 C 8 0.83 (18) 0.60-0.98 FRI B 7 0.89 (18) 0.63-0.99 T 8 0.98 (4) 0.89-1.00 A 8 0.91 (28) 0.28-1.00 M 8 1.00 (0) 0.99-1.00 C 7 0.99 (3) 0.92-1.00 PARAFAC C1 8 1.04 (9) 0.98-1.28 C2 6 0.99 (1) 0.96-1.00 C3 8 1.26 (57) 1.00-3.04 C4 8 0.96 (10) 0.72-1.00
Fractions on 2nd resin
RI PT
Fractions on 1st resin
Indicators
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AC C
EP
TE D
M AN U
SC
RI PT
9 1.00 (1) 1.00-1.02 9 0.90 (22) 0.42-1.00 9 0.95 (13) 0.62-1.00 C4 Note: n – number of samples; RSD – relative standard deviation (unit, %); Min – minimums; Max – Maximums.
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Table S6. DOC concentrations, and the intensities of a254 and PARAFAC components of sequentially fractionated DOM fractions for effluent, limnic, and riverine DOM samples based on Imai’s and Kim’s methods Supernatant
Remaining organic matter
DOM
After DAX-8 After AG-MP-50 After AG-MP-1 HPO(b), TPI and HPI TPI and HPI TPI(a/b/n), and (a/n) (n) HPI(a/b/n) Imai’s method
Supernatant
After IRA-67
After DAX-8
After XAD-4
DOM
HPO, TPI, and HPI (b/n)
TPI and HPI (b/n)
HPI (b/n)
RI PT
Fractionation step
Kim’s method
8.12±1.27 31.91±16.49
5.44±0.93 25.25±16.70
4.22±1.28 19.95±20.20
1.68±0.07 10.63±16.87
8.25±1.84 31.94±16.44
6.58±0.64 24.62±15.62
6.00±1.30 19.44±20.68
4.25±1.10 10.65±16.93
C1 (µg QS L-1)
109.46±13.80 70.89±13.94
34.76±17.76
5.06±3.99
102.86±19.41 80.02±37.64
50.33±21.75
26.97±11.56
C2 (µg QS L ) C3 (µg QS L-1) C4 (µg QS L-1) Limnic DOC (mg L-1) a254 (m-1)
60.14±4.89 65.15±3.23 72.03±15.13
38.15±9.54 44.49±12.92 43.20±9.67
19.40±7.76 22.97±5.10 26.96±3.20
3.16±0.43 8.01±1.32
1.95±0.77 5.97±0.87
1.67±0.57 4.40±1.47
C1 (µg QS L-1)
22.48±5.30
11.69±4.44
C2 (µg QS L ) C3 (µg QS L-1)
7.84±1.76 9.59±1.92
C4 (µg QS L-1)
M AN U
-1
SC
Effluent DOC (mg L-1) a254 (m-1)
58.48±10.04 63.59±13.12 66.86±16.90
42.95±21.36 52.00±23.66 35.11±18.58
28.98±11.69 41.24±16.79 22.47±11.86
14.42±6.25 22.45±12.54 11.96±2.37
0.98±0.46 0.86±0.35
3.04±0.14 8.01±1.29
1.75±0.67 5.47±0.42
1.32±0.19 4.40±1.46
1.22±0.10 0.87±0.35
5.55±2.64
0.55±0.36
21.80±1.50
9.18±3.55
6.10±2.17
2.19±0.93
4.53±1.89 6.26±1.41
2.55±1.16 3.12±1.36
0.54±0.21 0.44±0.25
8.62±0.24 10.51±0.60
3.34±1.58 5.10±1.41
2.09±0.78 4.02±1.64
0.79±0.21 2.36±1.28
11.25±3.63
6.17±2.81
2.21±2.99
0.00±0.00
9.01±1.10
4.10±1.57
3.09±1.36
1.49±0.28
Riverine DOC (mg L-1) a254 (m-1) C1 (µg QS L-1) C2 (µg QS L-1)
3.44±0.24 15.37±14.58 29.30±10.18 10.72±4.22
2.00±0.54 12.94±15.11 14.96±8.40 6.79±3.30
1.85±0.39 12.38±16.45 9.89±5.02 4.44±2.11
1.01±0.26 9.96±17.13 0.65±0.77 0.62±0.52
3.39±0.29 15.39±14.58 31.60±6.87 12.35±3.11
1.81±0.22 12.42±15.56 15.86±6.97 5.61±2.56
1.69±0.10 12.33±16.47 8.65±5.99 3.11±2.19
1.44±0.15 9.97±17.14 3.45±1.97 1.28±0.57
C3 (µg QS L-1) C4 (µg QS L-1)
13.15±3.22 18.18±9.04
8.13±3.13 9.44±4.94
5.69±2.33 6.27±3.43
0.61±0.44 0.18±0.16
15.15±3.82 18.88±5.38
8.92±3.42 8.48±3.95
6.35±3.80 4.15±2.07
3.11±1.93 1.93±0.53
EP
AC C
-1
TE D
2.81±2.08 3.11±2.51 2.50±2.05
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Table S7 Removal efficiencies of different resins used on the basis of DOC and PARAFAC components (based on all the samples). Resins
DOC (%)
C1 (%)
C2 (%)
C3 (%)
C4 (%)
AC C
EP
TE D
M AN U
SC
RI PT
Imai's method XAD-8 25.9(11.3) 43.1(19.1)* 36.2(25.9) 34.0(18.4) 40.7(27.8) AG-MP-50 26.7(18.8) 45.9(15.8)* 41.6(13.8) 43.3(12.1)* 47.7(26.9) AG-MP-1 70.8(33.4) 85.1(15.9) 78.7(17.2) 84.4(12.7) 95.5(6.1)* Kim's method IRA-67 35.9(17.6) 44.3(22.3) 48.3(23.1) 37.9(20.1) 53.0(15.4)* XAD-8 15.6(16.3) 37.9(14.0)** 35.6(16.2)* 23.7(14.9) 34.9(21.4)* XAD-4 16.6(15.1) 55.0(15.7)** 54.9(12.1)** 44.8(26.4)* 44.8(19.9)** Note: Values in the bracket is the relative standard deviations. * Significance of independent t-test between PARAFAC components and DOC is < 0.05; ** Significance of independent t-test between PARAFAC components and DOC is < 0.01.
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500
3
2.5
2.5
450
1.5 350
1.5 350
1 300
35 0
400 450 E m. (nm)
5 00
550
500
0.5
300
0
250
3
500
300
350
4 00 45 0 Em. ( nm)
500
550
0.5
300
0
250
3
500
2.5
2.5
400
1.5
350
0.5
35 0
400 450 E m. (nm)
5 00
0
550
450
500
5 50
250
0.5
300
350
0
3
4 00 45 0 Em. ( nm)
500
550
0
2.5 2 1.5
350
1
300
0.5
400
M AN U
1 300
400 450 E m. (nm)
2
µ g Q S/L Ex. ( nm)
1.5 350
350
SC
450
µ g Q S/L Ex. ( nm)
400
30 0
1
AG-MP-01
2 Ex. ( nm)
1.5 350
AG-MP -50
450
300
400
1
NaO H
250
2
400
RI PT
400
2.5
450
2 µg Q S/L Ex. (nm)
Ex. (nm)
2
300
3 IRA-67
µg Q S/L Ex. (nm)
450
250
500
XAD- 4
µg Q S/L
3 XAD-8 DAX-8
1
300
250
µ g Q S/L
500
0.5
30 0
350
400 450 E m. (nm)
500
5 50
0
Fig. S1. Fluorescence EEMs of the solvent blank and the resin blanks
120
TE D
500 450
100
) 400 m n (. x E350
80
EP AC C
300 250
40 M
B
300
60 C
/L S Q g ♦
T 350
20
A 400 450 Em. (nm)
500
550
0
Fig. S2. Five defined regions of fluorescence EEMs. The emission (ex) and the excitation (em) wavelength ranges for B, T, A, M, and C are ex 250-300 / em 280-330, ex 250-300 / em 330-380, ex 250-300 / em 380-480, ex 300-320 / em 380-420, and ex 320-370 / em 420-480.
10
ACCEPTED MANUSCRIPT
1
a. Protein-like indicators (B and T)
0
-0.5
-1 -1
2
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L)
1
d. Humic-like indicators (A, M, and C)
0.5 1 1.5 log10(SP (Inds), µg QS/L) g. Protein- and humic-like indicators 2
y= -0.12x + 0.36x + -0.33 2
0.5 n= 127, R = 0.092, p= 0.0000
0
y= -0.19x + 0.33x + -0.11 2
0.5 n= 127, R = 0.539, p= 0.0000
0
TE D
-0.5
2
-1 -1
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L)
1.5
f. Humic-like indicators (C1, C2, and C3)
0.5
n= 76, R2= 0.311, p= 0.0000
SC
0.5 1 1.5 log10(FRI (Inds ), µg QS/L)
h. Protein- and humic-like indicators
0 0.5 1 log10(PFC (Inds ), µg QS/L)
y= 0.10x2 + -0.18x + 0.07
log10(Indd/Inds ,%)
-0.5
2
-0.5
0.5 1 1.5 log10(SP (Inds), µg QS/L)
0
1 Pro Hum FC
n= 77, R2= 0.096, p= 0.0000
0.5
-1 -0.5
2
0
-1 0
1
0
-0.5
-1 -0.5
2
1
Pro Hum FC
1.5
log10(Indd/Inds ,%)
-0.5
1
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
n= 78, R2= 0.156, p= 0.0000
0
-1 0
-0.5
y= -0.07x2 + 0.12x + -0.05
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
0.5
0
-1 -0.5
1.5
e. Humic-like indicators (A, M, and C)
y= -0.11x2 + 0.27x + -0.21
n= 26, R2= 0.720, p= 0.0000
0.5
RI PT
0.5 1 1.5 log10(SP (Inds), µg QS/L)
n= 50, R2= 0.639, p= 0.0000
0.5
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
n= 49, R2= 0.189, p= 0.0000
-0.5
1
y= -0.32x2 + 0.66x + -0.31
y= -0.21x + 0.36x + -0.13
0
-1 0
c. Protein-like indicators (C4)
2
y= -0.27x + 0.79x + -0.67 0.5
1
b. Protein-like indicators (B and T)
2
M AN U
1
0.5
0
0.5 1 1.5 log10(PFC (Inds ), µg QS/L)
i. Protein- and humic-like indicators y= 0.04x2 + -0.05x + 0.00 2
n= 102, R = 0.016, p= 0.0407
2
Pro Hum FC
0
-0.5
-1 -0.5
0
0.5 1 1.5 log10(PFC (inds), µg QS/L)
2
AC C
EP
Fig. S3. Relationships between the ratios of Indd/Inds and Inds for three FDOM indicator groups based on Imai’s fractionation procedures. The charts a, b, and c are protein-like indicators in SP, FRI, and PARAFAC; the charts d, e, and f are humic-like indicators in SP, FRI, and PARAFAC methods; the charts g, h, and i are both above indicators in SP, FRI, and PARAFAC methods. Pro, Hum, and FC in the legends denotes protein-like indicators, humiclike indicators, and fitting curves, respectively. The red arrow represents the lowest concentrations with the Indd/Inds ratios approaching 1.0.
11
ACCEPTED MANUSCRIPT
2
2
y= -0.13x + 0.19x + -0.04
0
-0.5
0.5 1 1.5 log10(SP (Inds), µg QS/L)
0
-0.5
-1 -1
2
1
d. Humic-like indicators (A, M, and C) 2
1
0
0.5 1 1.5 log10(SP (Inds), µg QS/L)
g. Protein- and humic-like indicators 2
y= -0.23x + 0.59x + -0.41 0.5 n= 132, R2= 0.142, p= 0.0000
0.5 1 1.5 log10(SP (Inds), µg QS/L)
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L) h. Protein- and humic-like indicators 2
y= -0.11x + 0.15x + -0.04
-0.5
0
0.5 n= 134, R2= 0.629, p= 0.0000
0
2
-0.5
-0.5 0 0.5 1 log10(FRI (Inds ), µg QS/L)
-0.5
0 0.5 1 1.5 log10(PFC (Inds ), µg QS/L)
2
f. Humic-like indicators (C1, C2, and C3)
y= -0.07x2 + 0.10x + -0.02 0.5 n= 80, R2= 0.569, p= 0.0000
0
-0.5
-1 -2
1.5
1
Pro Hum FC
-0.5
-1 -1
0
SC log10(Indd/Inds ,%)
-0.5
1 Pro Hum FC
0
-1 -0.5
0
-1 -1
2
n= 81, R2= 0.303, p= 0.0000
TE D
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
-0.5
log10(Indd/Inds ,%)
log10(Indd/Inds ,%)
0
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y= -0.13x2 + 0.23x + -0.08 0.5 n= 27, R2= 0.840, p= 0.0000
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a. Protein-like indicators (B and T)
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Fig. S4. Relationships between the ratios of Indd/Inds and Inds for three fluorescence indicator groups based on the Kim’s fractionation procedures. The charts a, b, and c are protein-like indicators in SP, FRI, and PARAFAC; the charts d, e, and f are humic-like indicators in SP, FRI, and PARAFAC methods; the charts g, h, and i are both above indicators in SP, FRI, and PARAFAC methods. Pro, Hum, and FC in the legends denotes protein-like indicators, humic-like indicators, and fitting curves, respectively. The red arrow represents the lowest concentrations with the Indd/Inds ratios approaching 1.0.
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Fig. S5. Peak changes in the original (□) and the subtracted (○) EEM spectra upon resin fractionation
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Kim’s method Fig. S6. Relative abundances of different resin fractions on the basis of DOC and PARAFAC components. The fractions were obtained by Imai’s (chart a-e) and Kim’s (chart f-i) fractionation methods. The word “All” in the x-axis denotes the average of EfOM, LiOM, and RiOM. 14
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Script S1. Matlab codes for the peak identification and volume integration in the specific zone.
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function F_specific=F_specific_FRI(X,Ex,Em,dataname)
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%% Coble (1996)'s peaks finding and Chen (2003)'s regional integration % ------Description of this code-----% The specific zones, where the peak finding and volume integration are % carried, is shown in Fig. S2 in the supplementary materials. The largest % intensity value in the specific zone will be assigned as the peak. The % volume under the surface of the EEM of specific zone will be integrated % and assigned as the FRI. % ------Description of the input-----% X - 3D data cube (No headers, i.e. samples*Em*Ex) of fluorescence % intensities, which is also the dataset XcQS or XcRU output from % FDOMcorrect.m. % Em - 1D row vector of emission wavelengths corresponding to EEMs. % Ex - 1D row vector of excitation wavelengths corresponding to EEMs. % dataname - 1D row cell of samples' name corresponding to the first % dimension (also known as the samples)
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%% About this Matlab file % Please cite this program as: F_specific_FRI.m % in He and Hur. 2015 ' Conservative hehaviors of fluorescence EEM-PARAFAC % components in resin fractionation processes and its applicability for % characterizing dissolved organic matter% Copyright(C) 2015 W He, % Copyright (C) 2015 W He, % Sejong University % Department of Environment and Energy % Seoul 143-747, South Korea % [email protected]
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%% Data pretreatment % Build a similar struct dataset used in the FDOMFluor toolbox. SP=size(X,1); Data_Input=struct('X',X,'Em',Em,'Ex',Ex,'nEm',length(Em),'nEx',length(Ex),'nS ample',SP);
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% Obtain the interval of the emission and excitation wavelength Ex_inv=Ex(2)-Ex(1); Em_inv=Em(2)-Em(1); % Use he EEMCut.m in the FDOMFluor toolbox to cut the 1st and 2nd Rayleigh % scatter [Data_Cut]=EEMCut(Data_Input,25,0,30,0,''); % Cut the Raman scatter from the EEM for w=1:length(Data_Cut.Em); Excitation(w)=1e7/((1e7/Data_Cut.Em(w))+3600); v=find((Data_Cut.Ex>Excitation(w)+0)&(Data_Cut.Ex
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%% Peaks finding and regional integration % The emission (ex) and excitation (em) wavelength ranges for B, T, A, M, % and C are: % B ex 250-300 / em 280-330 % T ex 250-300 / em 330-380 % A ex 250-300 / em 380-480 % M ex 300-320 / em 380-420 % C ex 320-370 / em 420-480 % The zone or region division Em_s=[280,330;330,380;380,480;380,420;420,480]; Ex_s=[250,300;250,300;250,300;300,320;320,370]; for s=1:SP F_specific{s+2,1}=dataname{s}; Bigtemp{s,1}=squeeze(Data_Cut.X(s,:,:)); for k=1:5 % Peaks finding Ex_t=[]; Em_t=[]; F_specific{s+2,3*k+1}=max(max(Bigtemp{s,1}((Em_s(k,1)Em(1))/Em_inv+1:(Em_s(k,2)-Em(1))/Em_inv+1,(Ex_s(k,1)Ex(1))/Ex_inv+1:(Ex_s(k,2)-Ex(1))/Ex_inv+1))); [Em_temp,Ex_temp]=find(F_specific{s+2,3*k+1}==Bigtemp{s,1}((Em_s(k,1)Em(1))/Em_inv+1:(Em_s(k,2)-Em(1))/Em_inv+1,(Ex_s(k,1)Ex(1))/Ex_inv+1:(Ex_s(k,2)-Ex(1))/Ex_inv+1)); Ex_t=(Ex_temp-1)*Ex_inv+Ex_s(k,1); Em_t=(Em_temp-1)*Em_inv+Em_s(k,1); F_specific{s+2,3*k-1}=Ex_t(1); F_specific{s+2,3*k}=Em_t(1); % Regional intergration Em_r=[];Ex_r=[]; Em_range=[Em_s(k,1):Em_inv:Em_s(k,2)]; Ex_range=[Ex_s(k,1):Ex_inv:Ex_s(k,2)]; for p1=1:length(Em_range) Em_r(p1)=find(Data_Cut.Em==Em_range(p1)); end for p2=1:length(Ex_range) Ex_r(p2)=find(Data_Cut.Ex==Ex_range(p2)); end F_specific{s+2,k+16}=trapz(Ex_range,trapz(Em_range,Bigtemp{s,1}(Em_r,Ex_r)))/ ((Em_s(k,2)-Em_s(k,1))*((Ex_s(k,2)-Ex_s(k,1)))); end end % Header F_specific{1,2}='Coble (1996)'; F_specific{2,2}='B'; F_specific{2,5}='T'; F_specific{2,8}='A'; F_specific{2,11}='M'; F_specific{2,14}='C'; F_specific{1,17}='Chen (2003)'; F_specific{2,17}='B'; F_specific{2,18}='T'; F_specific{2,19}='A'; F_specific{2,20}='M'; F_specific{2,21}='C'; % Output data including peak wavelengths and integrated volume in the
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% specific zone xlswrite('F_specific(BTAMC)_FRI.xlsx',F_specific);
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Script S2. Quantitive comparsion between the present PARAFAC model with a library which included 38 PARAFAC models.
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function DataBase=comPARAFAC(p,Plot_ID,Plot_id,Parafac_Output_Excel_Name) %% Introduction % Parr et al. (2014) recently proposed a quantitative method for % comparision of the components of various PARAFAC models. They built a % DataBase that selects 38 dataset. They also offer a edited R codes to % conduct the comparision. However, some researcher are not familiar with % that software. After figuring out their R codes, I try to give a MATLAB % code named comPARAFAC.m and a DataBase named DataBase(38).mat for the % researches who are familiar with that language. Before using this % function, the database and 'MyparafacResults.xlsx' should be copied into % the same folder. % The calculation is based on the modified Tucker's Congruence Coefficient % (mTCC) % ------Description-----% DataBase=comPARAFAC(p,Plot,Parafac_Output_Excel_Name) % p - Modified Tucker's Congruence Coefficient (mTCC). When p=0.95, it % means the target PARAFAC components is nearly an exact match with the one % in the database. % Plot_ID - when 1 is assigned, it means showing the standardized PARAFAC % components and original ones of the yours data in figures; when 0 is % assigned, no figures will be shown. % Plot_id - when 1 is assigned, it means showing the comparing figures; % when 0 is assigned, no figures will be shown % Parafac_Output_Excel_Name - the excel file output from the DOMFluor in % the format as 'MyparafacResults.xlsx' %% About this Matlab file % Please cite this program as: comPARAFAC.m % in He and Hur. 2015 ' Conservative behaviors of fluorescence EEM-PARAFAC % components in resin fractionation processes and its applicability for % characterizing dissolved organic matter % Copyright(C) 2015 W He, % Sejong University % Department of Environment and Energy % Seoul 143-747, South Korea % [email protected]
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%% Main function % Input of the data mkdir(['Figure(p=' num2str(p) ')']); % DataBase input load(['DataBase(38).mat']); % Your data input. Just use the "MyparafacResults.xlsx" excel file produced % by DOMFluor package Ex_loading=xlsread(Parafac_Output_Excel_Name,'Ex Loadings'); Em_loading=xlsread(Parafac_Output_Excel_Name,'Em Loadings'); [nD,mD]=size(DataBase); [nEx,~]=size(Ex_loading); [nEm,~]=size(Em_loading); [~,nC]=size(Ex_loading); % Resample the data to a standard set of wavelengths % The wavelength of Ex and Em are both [200 600]. The zero data and missing % data was assigned as NaN. To make the data better, the data was first % smoothed by locally weighted scatterplot smoothing (LOESS). The weighted % least square (WLS) values is assigned as 0.15 as Parr et al. (2014)
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% suggested. for nc=1:nC-1 % Smooth Ex_loading_temp=smooth(Ex_loading(:,1),Ex_loading(:,nc+1),0.15,'loess'); Em_loading_temp=smooth(Em_loading(:,1),Em_loading(:,nc+1),0.15,'loess'); % Spline Ex_loading_sp(:,nc)=spline(Ex_loading(:,1),Ex_loading_temp,Ex_loading(1,1):Ex _loading(nEx,1)); Em_loading_sp(:,nc)=spline(Em_loading(:,1),Em_loading_temp,Em_loading(1,1):Em _loading(nEm,1)); end Ex_loading(Ex_loading==0)=NaN; Em_loading(Em_loading==0)=NaN; Ex_loading_sp(Ex_loading_sp
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DataBase{nd,9}(nc,ns)= (DataBase{nd,7}(nc,ns)*DataBase{nd,8}(nc,ns))^0.5; end end tpp=[]; tpp=DataBase{nd,9}; tpp(tpp
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plot(200:600,DataBase{nd,6}(:,C(i)),'b',200:600,Em_loading_S(:,R(i)),'r','Lin eWidth',2);hold on; plot(200:600,DataBase{nd,5}(:,C(i)),':b',200:600,Ex_loading_S(:,R(i)),':r','L ineWidth',2); axis([200 600 0 1]) title([DataBase{nd,11}{cal,1} ' (' '\itp= ' num2str(roundn(DataBase{nd,11}{cal,2},-3)) ')'],'FontSize',FS); xlabel('Wavelength (nm)','FontSize',FS); ylabel('Relative intensity','FontSize',FS); set(gca,'Fontsize',FS); legend([DataBase{nd,2} ' (' num2str(C(i)) ') Em'],... ['MySample (' num2str(R(i)) ')Em'],... [DataBase{nd,2} ' (' num2str(C(i)) ') Ex'],... ['MySample (' num2str(R(i)) ') Ex']);
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print(gcf,'-dbmp',['Figure(p=' num2str(p) ')\MySample (' num2str(R(i)) ') vs '... DataBase{nd,2} ' (' num2str(C(i)) ')' '.bmp']); close(h); end end % Export the similar dataset in Excel format xlswrite(['comPARAFAC(p=' num2str(p) ')' '.xlsx'], DataBase{nd,11},DataBase{nd,2}); end % Save the database save Analysis_Results.mat DataBase end %% Subfunction about the sumd function [Sigmal]=sumd(s) s(isnan(s))=0; Sigmal=sum(s); end
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References
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Parr, T.B., Ohno, T., Cronan, C.S., Simon, K.S., 2014. comPARAFAC: a library and tools for rapid and quantitative comparison of dissolved organic matter components resolved by Parallel Factor Analysis. Limnol Oceanogr-Meth 12, 114-125.
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