Supporting Information. Fluorescence and quenching assessment (EEM-PARAFAC) of de facto potable reuse in the Neuse River, North Carolina, USA

Transcription

1 Supporting Information Fluorescence and quenching assessment (EEM-PARAFAC) of de facto potable reuse in the Neuse River, North Carolina, USA Martha J.M. Wells a*, Gene A. Mullins b, Katherine Y. Bell c,1, Allegra K. Da Silva d,2, Eileen M. Navarrete e a EnviroChem Services, Cookeville, TN, USA b Chemistry Department, Tennessee Technological University, Cookeville, TN, USA c CDM Smith, Nashville, TN, USA d CDM Smith, Denver, CO, USA e Public Utilities Department, City of Raleigh, Raleigh, NC, USA * Corresponding author. address: info@envirochemservices.net or mjmwells@tntech.edu (M.J.M. Wells). Phone: EnviroChem Services, 224 Windsor Drive, Cookeville, TN 3856, USA Additional data are presented including sample location maps of the study site, river flow and precipitation, total organic carbon (TOC) concentration, experimental methods, inner filtering effects (IFEs) correction, first-order Rayleigh scattering spectra, analysis of variance (ANOVA) comparisons, 2D and 3D parallel factor analysis (PARAFAC) components, model fitting, and split-half analysis. The supporting information consists of 33 pages, 12 figures, and 9 tables. 1 Current Address: MWH Global/Stantec, Brentwood, TN 2 Current Address: MWH Global/Stantec, Denver, CO S1

2 Table of Contents Sample Locations in the Neuse River Basin... S4 Table S1. River Travel Time and Distance between Sites... S4 Table S2. Site Identification by Latitude and Longitude Coordinates... S5 Figure S1a. Neuse River Basin, North Carolina, USA... S5 Figure S1b. Sample Sites A H in the main stem of the Neuse River, North Carolina, USA.... S6 Physical and Chemical Water Parameters... S7 Figure S2. River flow and precipitation during sampling events.... S7 Figure S3. Total organic carbon (TOC) averaged by site over three sampling events.... S7 Experimental Methods... S8 Depiction of excitation-emission (EEM) spectra and inner filtering effects (IFEs) correction... S9 Importance of Inner Filtering Effect (IFE) Correction Even at Low TOC Concentration.... S1 Figure S4. Excitation spectra collected at site A event 2 comparing data uncorrected (dashed line) or corrected (solid line) for primary and secondary IFEs at a constant emission wavelength = 424 nm.. S1 First-order Rayleigh scattering... S11 Figure S5a. Representative Rayleigh scattering spectra (EX = EM; Δλsync = )... S12 Figure S5b. Representative Rayleigh scattering spectra (EX = EM; Δλsync = )... S13 Box and Whisker Charts... S14 Figure S6. Box and whisker charts... S15 Analysis of Variance (ANOVA)... S16 Table S3. Statistical comparison of mean amino acid-like fluorescence intensity for sites averaged over three events.... S17 Table S4. Statistical comparison of mean fulvic/humic-like fluorescence intensity for sites averaged over three events.... S18 Modeled PARAFAC Components... S19 Figure S7. Modeled PARAFAC components in 2D and 3D... S19 PARAFAC Split-half Analysis variance, residual sums of squares, scores, and loadings... S2 Table S5. Complete dataset sample identification... S2 Table S6. Random assignment of samples into two data sets A and B... S2 Table S7. Percent Variance Captured by PARAFAC Model: Full Model (n = 24)... S22 S2

3 Table S8. Percent Variance Captured by PARAFAC Model: Split-half Model A (n = 12)... S22 Table S9. Percent Variance Captured by PARAFAC Model: Split-half Model B (n = 12)... S22 Figure S8. Assessment of residual sums of squares... S23 Figure S9. Overlaid graphic assessment of residual sums of squares... S24 Figure S1. PARAFAC score values for the Full Model and the Split Models A and B.... S27 Figure S11. PARAFAC loading values for the emission and excitation modes of the Full Model and the Split Models A and B.... S28 Actual spectra compared to PARAFAC-modeled spectra... S29 Figure S12. Emission spectra at constant excitation wavelength (EX = 224 nm).... S3 S32 REFERENCES... S33 S3

4 Sample Locations in the Neuse River Basin There are three wastewater treatment plants (WWTPs) and two drinking water treatment plants (WTPs) with permitted discharges or intakes directly to/from this reach of the river. One small WWTP (permitted for a biological treatment capacity of 3 mgd) is located just downstream of site A. Site B is located upstream of the Neuse River WWTP (permitted for a biological treatment capacity of 6 mgd) at site C. Sites D, E, and F are downstream of the WWTP at site C with site F located just upstream of the Johnston County WTP. Site G is located just downstream of the Smithfield WTP and just upstream of the Central Johnston County WWTP (permitted for a biological treatment capacity of 9.5 mgd). Table S1. River Travel Time and Distance between Sites sites travel time (h) (a) approximate river distance (miles) between sites cumulative from site A between sites cumulative from site A A B B C (b) C D (b) D E E F F G G H a Travel time at 25th percentile river flow conditions b Estimated travel time; data are given from site B to D S4

5 Table S2. Site Identification by Latitude and Longitude Coordinates Site ID Latitude Longitude Description Monitoring Station A Neuse River at SR Falls Dam Ambient Monitoring Site J189 B Neuse River at SR 2555 Auburn Knightdale Rd LNBA Site J C At Neuse River WWTP D Neuse River at Mial Plantation Rd E Neuse River at NC42 Clayton LNBA Site J4 F Neuse River at SR 198 Fire Dept Wilsons Mills LNBA Site J419 G Neuse River at US 7 Smithfield Ambient Monitoring Site J4 H Komegay Farms Figure S1a. Neuse River Basin, North Carolina, USA DLFE pdf S5

6 Figure S1b. Sample Sites A H in the main stem of the Neuse River, North Carolina, USA. S6

7 Physical and Chemical Water Parameters Figure S2. River flow and precipitation during sampling events. Figure S3. Total organic carbon (TOC) averaged by site over three sampling events. S7

8 Experimental Methods Ultraviolet (UV) Visible and Fluorescence Spectroscopy. Samples were processed randomly without prior knowledge of the identity/location of the sample sites. Samples were filtered pore size.45 µm and 33 mm diameter (Fisher Scientific, Pittsburgh, PA, USA) prior to analysis. All samples and trip blanks were analyzed for UV-visible absorbance and fluorescence. UV-visible absorbance spectra were recorded from to nm using a Varian Cary 3E UV-visible spectrophotometer (Agilent Technologies, Inc., Santa Clara, CA, USA) and a quartz cuvette having a 1 cm path length. Three-dimensional EEM spectra were generated by collecting emission spectra over a range of excitation wavelengths ( nm in increments of 3 nm) and emission wavelengths ( 85 nm in increments of 2 nm). A Varian Cary Eclipse fluorescence spectrophotometer (Agilent Technologies, Inc.) with a full spectrum xenon pulse single source lamp was employed. The excitation and emission slit width was set to 1 nm. Second-order Rayleigh scattering was removed instrumentally. Further, the fluorescence intensity of a sealed cell of pure water was subtracted from the EEMs of samples and controls to correct for the Raman spectrum of water. Measured Raman values were used for QA/QC. Statistical analysis of variance by Duncan s Separation of Means test was performed using the Statistical Analysis System (SAS, Cary, NC, USA). A trip blank (TB) consisting of distilled water was transported in identical sample containers to those used to collect actual samples. The trip blanks were shipped with the samples collected for each sampling event and processed identically to the river water samples. The trip blank samples indicated no background interferences. S8

9 Depiction of excitation-emission (EEM) spectra and inner filtering effects (IFEs) correction The spectra of the river samples were corrected for second-order Rayleigh scattering, for the Raman spectrum of water, for the first-order Rayleigh scattering spectrum of water, and for primary and secondary inner filtering. Three-dimensional (3D) EEM fluorescence spectra; twodimensional (2D) spectra prepared at either constant excitation wavelength or constant emission wavelength; and one-dimensional (1D) data derived from specific excitation/emission wavelength pairs were prepared to interpret the fluorescence data graphically. Statistical analysis of variance was performed to interpret the spatial and temporal changes in fluorescent indicators of anthropogenic influence. In the three-dimensional (3D) EEM spectra presented in this manuscript, the x-axis represents emission wavelengths, the y-axis represents excitation wavelengths, and the z-axis indicates the intensity of the corrected fluorescence at a specific excitation-emission wavelength pair (x, y data point). Other useful graphical depictions two-dimensional (2D) spectra were derived from the 3D (EEM) or parallel factor analysis (PARAFAC) data: (1) by collecting data points at constant excitation wavelength as the emission wavelength varies (parallel to the 3D x- axis) or (2) by collecting data points at constant emission wavelength as the excitation wavelength varies (parallel to the 3D y-axis). Additionally, it was also useful to gather onedimensional (1D) data from the 3D EEM matrix by comparing individual x, y data points, i.e., specific excitation (EX) emission (EM) pairs, among the spectra obtained for various samples. In this report, the 1D data are represented as bar graphs. S9

10 Importance of Inner Filtering Effect (IFE) Correction Even at Low TOC Concentration. All data in this research were corrected for inner filtering effects (IFEs). The importance of correcting for IFEs in fluorescence spectra is illustrated using the 2D spectra for the primary and secondary fulvic acid peaks for site A event 2 obtained at a constant emission wavelength of 424 nm. As demonstrated in Figure S4, the degree of correction is non-uniform over the wavelength range depicted. Additionally, the TOC concentration of this sample is approximately 6 mg/l, which is below the concentration at which some authors assume no corrections for IFEs are necessary. Inner filter correction of the spectra allows proper utilization of the more intensely fluorescing fluorophores that are observed at lower excitation wavelengths. Fluorescence Intensity F 1 F 2 Excitation Wavelength (nm) at Constant Emission Wavelength (424 nm) Uncorrected Corrected Figure S4. Excitation spectra collected at site A event 2 comparing data uncorrected (dashed line) or corrected (solid line) for primary and secondary IFEs at a constant emission wavelength = 424 nm. S1

11 First-order Rayleigh scattering The first-order Rayleigh scattering of light (not fluorescence) can be extracted from EEM spectra where EX = EM. First-order Rayleigh scattering is a nephelometric measurement of colloidal material. Nephelometry a measure of the intensity of the scattered light is related to, but is not the same as turbidimetry, which is the intensity of light transmitted through a sample. First-order Rayleigh scattering is illustrated as 2D plots of intensity (also known in the literature as synchronous plots at which Δλ=) in Figures S5a,b. The scattering data depicted here were corrected for primary and secondary IFEs, and for the background Rayleigh scattering of water. When sites A and C were compared (Figure S5a), the scattering at site C near the WWTP outfall was greatest during event 1 (highest precipitation/flow rate). Rayleigh scattering spectra are depicted for all samples in Figure S5b. S11

12 1 1 a b c 1 Corrected Intensity Corrected Intensity Corrected Intensity Wavelength (nm) Wavelength (nm) Wavelength (nm) Figure S5a. Representative Rayleigh scattering spectra (EX = EM; Δλsync = ) for (a) event 1, (b) event 2, and (c) event 3; site A (solid blue line) and site C (dotted red line). S12

13 1 1 a 1 1 b 1 1 c Corrected Intensity Corrected Intensity Corrected Intensity Wavelength (nm) Wavelength (nm) Wavelength (nm) Event 1 Site A Event 1 Site B Event 2 Site A Event 2 Site B Event 3 Site A Event 3 Site B Event 1 Site C Event 1 Site D Event 2 Site C Event 2 Site D Event 3 Site C Event 3 Site D Event 1 Site E Event 1 Site F Event 2 Site E Event 2 Site F Event 3 Site E Event 3 Site F Event 1 Site G Event 1 Site H Event 2 Site G Event 2 Site H Event 3 Site G Event 3 Site H Figure S5b. Representative Rayleigh scattering spectra (EX = EM; Δλsync = ) for (a) Event 1, (b) Event 2, and (c) Event 3. S13

14 Box and Whisker Charts Box and whisker charts (Figure S6) were prepared using Excel for the EEM data of selected wavelength pairs (refer to Figure 3) to evaluate how the increased fluorescence observed at site C compared to the data population. The tyrosine-like and tryptophan-like data for samples from site C during sampling events 1 and 3 were inside the interquartile range, whereas the tyrosinelike and tryptophan-like data for samples from site C during sampling event 2 were outside the interquartile range. The fulvic-like and humic-like data from the same samples were within the interquartile range. Each individual data point represents one excitation/emission wavelength pair out of a data array for each sample containing 62,1 data points. The determination was made that the data from site C (closest to the WWTP discharge) were not anomalous data, but contained valuable information about the impact of an engineered system on a natural system. Therefore, all data were included in these analyses; no data were eliminated as outliers. S14

15 Figure S6. Box and whisker charts of the corrected intensity of EEM data for selected wavelength pairs (complementary analysis of the data in Figure 3 in the primary manuscript). S15

16 Analysis of Variance (ANOVA) A statistical analysis of variance (ANOVA) for the 1D spectral data is presented in Tables S3 and S4. Data for EX224/EM (B1) and EX224/EM35 (T1) in Table S3 indicated that the anthropogenic fluorescence at Site C was greater than at the upstream Sites A and B. At EEM Region T1 (EX224/EM35), the mean fluorescence at (a) Sites A, B, D, E, F, G, and H was not significantly different from each other, (b) Site C was significantly different from Sites A, B, F, G, and H, and (c) Sites D and E were not significantly different from Sites A, B, F, G, and H nor were they significantly different from Site C therefore, Sites D and E are considered to be intermediary in anthropogenic influence between Site C (more) and Sites A, B, F, G, and H (less) at EX224/EM35. At EEM Region B1 (EX224/EM), the fluorescence at (a) Sites A, B, D, E, F, G, and H was not significantly different from each other, (b) Site C was significantly different from Sites A, B, and H, and (c) Sites D, E, F, and G were not significantly different from Sites A, B, and H nor were they significantly different from Site C therefore, Sites D, E, F, and G are considered to be intermediary in anthropogenic influence between Site C (more) and Sites A, B, and H (less) at EX224/EM. Statistical evaluation of the data in Table S4 at EX224/EM424 (F1) indicated that fulvic acid influence was least at Site B and greatest at Sites A, C, and H; similarly, the data at EX224/EM474 (H1) indicated that humic acid influence was least at Site B and greatest at Site H. S16

17 Table S3. Statistical comparison of mean amino acid-like fluorescence intensity for sites averaged over three events. Site Mean Corrected Fluorescence Intensity ± SD * EX224/EM EEM Region B 1 EX224/EM35 EEM Region T 1 A ± 4.97 a ± 4.65 a B ± 4.18 a ± a C ± b ± 92.8 b D ± 15.8 ab ± ab 23.3 E ± 16.2 ab river ± 22.6 ab F ± 9.37 ab miles ± 8.51 a 8.8 river miles G ± 14.1 ab ± 14.4 a H ± a ±.55 a * Means in each column followed by the same letter are not significantly different from other values in the same column with the same letter (α =.1). S17

18 Table S4. Statistical comparison of mean fulvic/humic-like fluorescence intensity for sites averaged over three events. Site Mean Corrected Fluorescence Intensity ± SD * EX224/EM424 EEM Region F 1 EX224/EM474 EEM Region H 1 A ± a ± ab B ± b ± 33.8 c C ± a ± abc D ± ab ± abc E ± ab ± 14.2 bc F ± ab ± bc G ± ab ± abc H ± a ± a * Means in each column followed by the same letter are not significantly different from other values in the same column with the same letter (α =.1). S18

19 Modeled PARAFAC Components Figure S7. Modeled PARAFAC components in 2D and 3D S19

20 PARAFAC Split-half Analysis variance, residual sums of squares, scores, and loadings The split-half analysis was used in conjunction with the core consistency parameter to assess the adequacy of two PARAFAC components for modeling the data. The original dataset (full model) consisting of 24 samples (identified in Figure 5 and reproduced in Table S5) was randomly divided (using Excel) in the sample mode into two sub-datasets consisting of 12 samples each identified as Split A and Split B, respectively (Table S6). The variance (Tables S7 S9), residual sums of squares (Figures S8 S9), scores in the sample mode (Figure S1), and loadings in the emission and excitation modes (Figure S11) were compared among the full model and the split models, A and B. Table S5. Complete dataset sample identification event Full Model sample number by event/site site A B C D E F G H Table S6. Random assignment of samples into two data sets A and B Sample number Random Split A Random Split B event site event site 1 1 A 1 B 2 1 C 1 E 3 1 D 1 F 4 1 G 1 H 5 2 D 2 A 6 2 E 2 B 7 2 F 2 C 8 2 G 3 C 9 2 H 3 D 1 3 A 3 E 11 3 B 3 G 12 3 F 3 H S2

21 The objective of performing a split-half analysis is that the correctness of the model is empirically verified if the solution replicates over sets A and B (Smilde et al., 4). Two purposes motivated examination of this PARAFAC model by split-half analysis: (1) to verify that the unusually low number of PARAFAC components appropriately models the data and (2) to determine if the negative regions in the emission and excitation component modes are replicated across Split Model A and Split Model B. The PARAFAC variances for the full model, split-half model A, and split-half model B are tabulated in Tables S7, S8, and S9, respectively. Examination of the PARAFAC variances of the full and split models indicates that most, but not all data were appropriately modeled by the two-component PARAFAC models. Visual examination of the residual sums of squares in the emission and excitation modes (Figure S8) demonstrated that the pattern of the profiles for the Split Models A and B were similar to the profile for the Full Model. Differences in the magnitude of the residual sums of squares exist among the three models; however, comparison of the Full Model to the simple addition of the residual sums of squares for Split Model A and Split Model B by wavelength (overlay in Figure S9) demonstrated that the sum of the residual sums of squares for the split models was nearly identical to that of the full model. S21

22 Table S7. Percent Variance Captured by PARAFAC Model: Full Model (n = 24) Component Fit Fit Unique Fit Unique Fit (% X) * (% Model) * (% X) * (% Model) * The orthogonalized PARAFAC variance captured by a three-component model of all data was tested (component 1 = 49.25%, component 2 = 12.31%; component 3 = 3.6%), but it was less than that captured by the two-component model (component 1 = 74.49%; component 2 = 7.12%) indicating that the two-component model fitted better than the three-component model. Table S8. Percent Variance Captured by PARAFAC Model: Split-half Model A (n = 12) Component Fit Fit Unique Fit Unique Fit (% X) (% Model) (% X) (% Model) Table S9. Percent Variance Captured by PARAFAC Model: Split-half Model B (n = 12) Component Fit (% X) Fit (% Model) Unique Fit (% X) Unique Fit (% Model) * Fit (% X) and Fit (% Model) give the sum squared signal relative to the total signal in the data and to the total amount of signal captured in the model. Unique Fit (% X) and Unique Fit (% Model) as the same as above except the components are first orthogonalized to each other so that you are seeing the amount of signal that is unique to the given component. (Eigenvector Documentation Wiki). S22

23 Residual Sums of Squares Residual Sums of Squares Residual Sums of Squares Sample Mode: Full Model (n = 24) 8.E+6 6.E+6 4.E+6 2.E+6.E Sample number Emission Mode: Full Model (n = 24) 7.E+5 6.E+5 5.E+5 4.E+5 3.E+5 2.E+5 1.E+5.E+ Wavelength (nm) Excitation Mode: Full Model (n = 24) 2.5E+6 2.E+6 1.5E+6 1.E+6 5.E+5.E+ Wavelength (nm) Residual Sums of Squares Residual Sums of Squares Residual Sums of Squares Sample Mode: Split Model A (n = 12) 8.E+6 6.E+6 4.E+6 2.E+6.E+ 6.E+5 5.E+5 4.E+5 3.E+5 2.E+5 1.E Sample number Emission Mode: Split Model A (n = 12) 7.E+5.E+ Wavelength (nm) Excitation Mode: Split Model A (n = 12) 2.5E+6 2.E+6 1.5E+6 1.E+6 5.E+5.E+ Wavelength (nm) Residual Sums of Squares Residual Sums of Suares Residual Sums of Squares Sample Mode: Split Model B (n = 12) 8.E+6 6.E+6 4.E+6 2.E+6.E+ 6.E+5 5.E+5 4.E+5 3.E+5 2.E+5 1.E Sample number Emission Mode: Split Model B (n = 12) 7.E+5.E+ Wavelength (nm) Excitation Mode: Split Model B (n = 12) 2.5E+6 2.E+6 1.5E+6 1.E+6 5.E+5.E+ Wavelength (nm) Figure S8. Assessment of residual sums of squares: Full Model (left column), Split Model A (middle column), Split Model B (right column), Sample Mode (top row), Emission Mode (middle row), Excitation Mode (bottom row), residual profiles (blue), 95% confidence limit (green), 99% confidence limit (red). S23

24 Emission Mode Excitation Mode 7.E+5 4.5E+6 Residual Sums of Squares 6.E+5 5.E+5 4.E+5 3.E+5 2.E+5 Residual Sums of Squares 4.E+6 3.5E+6 3.E+6 2.5E+6 2.E+6 1.5E+6 1.E+6 1.E+5 5.E+5.E+.E+ Wavelength (nm) Wavelength (nm) Full Model Split Model A plus Split Model B Full Model Split Model A plus Split Model B Figure S9. Overlaid graphic assessment of residual sums of squares: Full Model (blue) compared to the simple addition of the residual sums of squares for Split Model A and Split Model B by wavelength (red). S24

25 Scores in the sample mode, and the emission and excitation loading for the Split Models, are compared to the Full Model in Figures S1 and S11, respectively. The emission and excitation loading for the humiclike Component 1 are virtually identical among Split Model A, Split Model B, and the Full Model. The excitation loading for the nonhumic-like Component 2 is virtually identical among Split Model A, Split Model B, and the Full Model. However, in the emission mode, a slight red-shifted offset is observed for the nonhumic-like Component 2 in Split Model A relative to Split Model B and the Full Model. To meet the objectives of a split-half analysis, the two data subsets in the split should have representative information of all chemical analytes (Smilde et al., 4). However, this requirement is challenged in these data, because the sample size is small (24 samples), only 3 of 24 samples were collected in the river at the WWTP discharge at site C, and only 2 of those 3 samples were collected in reduced flow (lower precipitation) conditions that accentuate the fluorescence of wastewater-derived compounds. Assessment of the residual sum of squares in the sample mode (Figure S8) and the sample mode scores (Figure S1) of the full and split models, clearly indicates that the greatest deviation from the empirical values of the data (particularly for the nonhumic-like component 2) was exhibited by the two samples collected in the river at the WWTP discharge under reduced flow (lower precipitation) conditions, i.e., event 2 site C and event 3 site C. These samples are identified as sample numbers 11 and 19 representing 8.3% of the samples in the Full Model, and as sample numbers 7 and 8 representing 16.7% of the samples in Split Model B. By happenstance, both samples (event 2 site C and event 3 site C) were randomly assigned to Split Model B, which implies that some of the directly wastewater-derived information embodied in these samples was absent in Split Model A. Therefore, the slight red-shifted offset in the emission mode observed for the nonhumic-like Component 2 in Split Model A relative to Split Model B and the Full Model, is attributed to the variability in the tyrosine-like and tryptophan-like differences in the anthropogenic chemicals introduced to the Neuse River at site C from the WWTP effluent, when the event 2 site C and event 3 site C samples were not represented in Split Model A, and to the subsequent difference in quenching that occurred. This analysis led to an interesting observation excitation was not altered, but emission was S25

26 affected (Figure S11) when the two data subsets in the split were not well replicated and means that, in these samples, emission was more affected by quenching than excitation. Importantly, the observation of similar profiles of positive and negative loadings in both components are replicated in Split Model A and Split Model B relative to the Full Model. Based on the data presented in the split-half analysis, and the comparison of the Full Model predictions to that of the actual data (Figures 6 and S12), we conclude that the two-component Full Model (n = 24) adequately describes most of the data, with the exception of a non-modeled wastewater-derived contribution to fluorescence that was revealed by visual examination and is described in the main manuscript (see the arrows in Figures 6 and S12). S26

27 Full Model (n = 24) Split Model A (n = 12) Split Model B (n = 12) Score 1 Score 1 Score Sample number Sample number Sample number Component 1 (humic-like) Component 2 (nonhumic-like) Component 1 (humic-like) Component 2 (nonhumic-like) Component 1 (humic-like) Component 2 (nonhumic-like) Figure S1. PARAFAC score values for the Full Model and the Split Models A and B. S27

28 Loading Split-half Analysis Split A Component 1 (humic-like) Split A Component 2 (nonhumic-like) Split B Component 1 (humic-like) Split B Component 2 (nonhumic-like) Loading Split-half Analysis Split A Component 1 (humic-like) Split A Component 2 (nonhumic-like) Split B Component 1 (humic-like) Split B Component 2 (nonhumic-like) Full Model Component 1 (humic-like) Full Model Component 2 (nonhumic-like) Loading Split-half Analysis -.5 Excitation (nm) Split A Component 1 (humic-like) Split A Component 2 (nonhumic-like) Split B Component 1 (humic-like) Loading Split-half Analysis Split B Component 2 (nonhumic-like) -.5 Excitation (nm) Split A Component 1 (humic-like) Split A Component 2 (nonhumic-like) Split B Component 1 (humic-like) Split B Component 2 (nonhumic-like) Full Model Component 1 (humic-like) Full Model Component 2 (nonhumic-like) Figure S11. PARAFAC loading values for the emission and excitation modes of the Full Model and the Split Models A and B. S28

29 Actual spectra compared to PARAFAC-modeled spectra Representative actual (IFE-corrected) and PARAFAC- modeled emission spectra are compared at a constant excitation wavelength (224 nm) for all 24 samples in Figure S12. The actual data were nearly perfectly fitted by the two-component PARAFAC model for the 6 samples from sites A and B for events 1, 2, and 3. However, for site C that was sampled near the outfall of a WWTP, the B1 and T1 fluorescing regions at EM < 35 nm were not as well fitted. The less fitted EM < 35 nm region of the spectra was observed for all sites C H in all sampling events (18 samples) and is indicated in Figure S12 by arrows. The differences between the actual and modeled spectra in these 18 samples at EM < 35 nm were designated a nonmodeled contribution. Conversely, the EM > 35 nm spectral regions of these samples were very well-fitted by the two-component PARAFAC model. Figure S12. Emission spectra at constant excitation wavelength (EX = 224 nm). Black curves represent actual spectra. Red curves represent spectra predicted by the two-component PARAFAC model. Arrows indicate the region of nonmodeled wastewater-derived contribution. (See pages S3 S32). S29

30 Event 1 Site A Event 2 Site A Event 3 Site A Event 1 Site B Event 2 Site B Event 3 Site B Event 1 Site C Event 2 Site C Event 3 Site C Figure S12. S3

31 Event 1 Site D Event 2 Site D Event 3 Site D Event 1 Site E Event 2 Site E Event 3 Site E Corrrected/Modeled Intensity Event 1 Site F Event 2 Site F Event 3 Site F Figure S12 (continued). S31

32 Event 1 Site G Event 2 Site G Event 3 Site G Event 1 Site H Event 2 Site H Event 3 Site H Figure S12 (continued). S32

33 REFERENCES Smilde, A.; Bro, R.; Geladi, P. Multi-way Analysis: Applications in the Chemical Sciences; John Wiley & Sons, Ltd: West Sussex, U.K., 4. Eigenvector Documentation Wiki. MCR and PARAFAC Variance Captured. (Accessed October, 217). S33