Supporting Information

Effects of copper ions on removal of nutrients from swine wastewater and on

release of dissolved organic matter in duckweed systems

Qi Zhoua,b,c,*, Xiang Lib,*, Yan Linb,*, Chunping Yanga,b,c,d,**, Wenchang Tangb, Shaohua

Wub, Dehao Li a,c,**, Wei Loud

a School of Environmental Science and Engineering, Guangdong University of

Petrochemical Technology, Maoming, Guangdong 525000, China

b College of Environmental Science and Engineering, Hunan University and Key

Laboratory of Environmental Biology and Pollution Control (Hunan University),

Ministry of Education, Changsha, Hunan 410082, China

c Guangdong Provincial Key Laboratory of Petrochemcial Pollution Processes and

Control, Guangdong University of Petrochemical Technology, Maoming, Guangdong

525000, China

d Hunan Province Environmental Protection Engineering Center for Organic Pollution

Control of Urban Water and Wastewater, Changsha, Hunan 410001, China

* These authors contribute equally to this paper.

** Corresponding authors. Email addresses: yangc@hnu.edu.cn (C.P. Yang),

de hlee@163.com (D.H. Li).

This supporting information contains 37-page document, including the detailed

description for the First-order kinetic, Michaelis-Menten kinetic, Modified logistic

kinetic and modified Stern–Volmer model cited literatures, procedure of minimizing

the inner filter effect, the PARAFAC and Two-dimensional correlation analysis, the

specific procedure of additional experiment, the specific procedure of spiking

experiment with the water samples dosed with NADH, the pH and metal-spiking

experiments, discussion on the peaks of C4 , 3 tables, 15 figures and this cover page.

The three Degradation kinetics Models

First-order kinetic model:

dCdt

=-rC (1)

Integrated by the boundary condition t = 0, C = A; t = t, C= C, the above equation

1 was transformed to:

C =A e-rt (2)

Michaelis-Menten kinetic model:

dCdt

=-k1Ck2+C

(3)

Integrated by the boundary condition t = 0, C = A; t = t, C= C , the above equation

3 was transformed to:

k2 ln( C)+ C =- k1 t+A (4)

Modified logistic kinetic model:

dCdt

=-r C(1 - aCC0

) (5)

Q =1 - aCC0

(6)

Integrated by the boundary condition t = 0, C = C0; t = t, C= C, the above equation

5 was transformed to:

C=C0

a +(1- a ) ert (7)

where C is nutrient concentration (mg/L), t is time (day), A is the initial amount

of nutrient (mg/L), r is the removal rate constants(day-1), k1 is a maximum rate

approached with increasing concentration (day-1), and k2 is a pseudo-equilibrium

constant (pseudo, because as the reaction occurs, it is constantly unbalancing the

equilibrium represented by the constant). C0 is the initial amount of nutrient

(mg/L), r is the removal rate constants (day-1), a is the parameter to be estimated

(a<1), Q is the external environmental stress.

Modified Stern-Volmer model

In general, two fluorescence quenching titration (FQT) models, Ryan–Weber

non-linear model and the modified Stern–Volmer model, are widely used for

characterizing the metal binding behavior of DOM although the models still have the

limitation that they neglect the potential existence of multidentate metal binding

multiple complexes (Esteves da Silva et al., 1998). The major assumptions of the

Ryan–Weber model are that only 1:1 metal/ligand complexes are formed and that a

linear relationship exists between the metal-bound ligand concentration and the

quenched DOM fluorescence intensity (Ryan and Weber, 1982; Plaza et al., 2006).

However, the linear relationship may not be valid if stable non-fluorescent complexes

are formed and/or if fluorescence quenching data at a particular wavelength pair

represents more than two different binding sites (Smith and Kramer, 2000; Hays et al.,

2004). The modified Stern–Volmer may partially solve the problems associated with

the non-linear fluorescence response for metal–DOM interactions by estimating the

portion of unquenched fluorescence contribution. Therefore, the major assumptions of

the Ryan–Weber model are that stable non-fluorescent complexes are formed and/or

fluorescence quenching data at a particular wavelength pair represents more than two

different binding sites. Based on that, in this study, the modified Stern–Volmer model

was applied to estimate the parameters related to copper binding.

This model can be used to calculate the conditional stability constant KM of Cu

ions to DOM released from the duckweed system (Hur and Lee, 2011):

F0

F0-F= 1

f KMCM+1

f (8)

Here F and F0 are the measured fluorescence component scores (arbitrary units per

unit DOC, A.U./mg/L) at the total Cu2+ concentration CM (mmol/L) and the no Cu ions

addition (0 mmol/L), respectively. The parameter KM was the conditional stability

constant at the certain experimental condition, and f represents the fraction of the

initial fluorescence, which is accessible to quencher. The parameters of f and KM were

solved by plotting F0 /( F0–F) against1/CM. The excitation/emission wavelength pairs

were selected based on the PARAFAC results.

References

Esteves da Silva, J.C., Machado, A.A., Oliveira, C.J.,Pinto, M.S. 1998. Fluorescence quenching of anthropogenic fulvic acids by Cu(II), Fe(III) and UO(2)(2+). Talanta 45(6), 1155-1165.

Hays, M.D., Ryan, D.K.,Stephen, P. 2004. A modified multisite Stern-Volmer equation for the determination of conditional stability constants and ligand concentrations of soil fulvic acid with metal ions. Anal. Chem. 76(3), 848-854.

Plaza, C., Brunetti, G., Senesi, N.,Polo, A. 2006. Molecular and quantitative analysis of metal ion binding to humic acids from sewage sludge and sludge-amended soils by fluorescence spectroscopy. Environ. Sci. Technol. 40(3), 917-923.

Ryan, D.K.,Weber, J.H. 1982. Fluorescence quenching titration for determination of complexing capacities and stability constants of fulvic acid. Anal. Chem. 54(6), 12-22.

Smith, D.S.,Kramer, J.R. 2000. Multisite metal binding to fulvic acid determined using multiresponse fluorescence. Anal. Chim. Acta 416(2), 211-220.

Hur, J.; Lee, B.-M. 2011. Characterization of binding site heterogeneity for copper within dissolved organic matter fractions using two-dimensional correlation fluorescence spectroscopy. Chemosphere. 83 (11), 1603-1611.

Procedure of minimizing the inner filter effect

During the analysis of DOM fluorescence, the dissolved organic carbon (DOC) is

proportional to fluorescence intensities of several specific fluorescent fractions.

However, with the increase of DOC concentration, the fluorescence intensities of

components potentially deviated from a linear relationship. This kind of optical

phenomenon involved in a significant decrease in emission quantum yield as a result

of the absorption of excited and emitted radiation by a sample matrix, which is known

as the “inner filter effect”. Therefore, the deviation of the fluorescence intensity

during the analysis of NOM fluorescence components cannot be neglected. The inner

filter effect often has no significant influence for samples with low absorbance or

concentration, so there are many methods reported for reducing the influence of inner

filter effect (Zhu et al., 2017). And the major method was to dilute the solution in

order to decrease the absorbance or concentration of a given sample. Absorbance can

be used as an indicator for determination of the need for dilution. For example, Poulin

et al. (2014) diluted a solution containing iron (III) to a degree at absorbance of <0.2

at 254 nm to minimize inner filter effects during fluorescence analysis. In this study,

we adopted this method founded by Poulin et al. (2014) due to the similarity of

solution containing metal ions.

In this study, although the FDOM samples were too high in concentration, all of

the samples were diluted with Milli-Q water until the concentration of DOC was less

than 10 mg/L (Abs254<0.2) to minimize the inner filter effect before the measurement

of the EEM spectra. The detailed procedure of the fluorescence measurement was as

follows: 1) DOC concentrations of all samples were measured by using a Shimadzu

TOC-VCPH analyzer (Shimadzu, Japan); 2) building the relation between the DOC

concentrations and UV254 absorbance was established to determine the dilution

multiple of each sample for measurement of 3D fluorescence. The relation between

the DOC concentrations and UV254 absorbance was shown in Figure 5. It was

obvious that there was a good linear relationship between DOC concentrations and

UV254 absorbance (R2>0.998). Based on the calculation results, when UV254

absorbance was less than 0.2, the DOC concentration reached less than 10 mg/L

through calculating. It meant that all the samples need be diluted by Milli-Q water

until the concentration of DOC was less than 10 mg/L according to initial DOC

concentrations of samples, and the aim to minimize the inner filter effect before

measuring EEM spectra. 3) DOM fluorescence spectra were measured by using an F-

4600 fluorescence spectrophotometer equipped with a 150W xenon lamp (Hitachi,

Japan). In a word, high concentrations of FDOM had been diluted to minimize the

inner filter effect before measuring EEM spectra in this study.

PARAFAC analysis

PARAFAC analysis was conducted by using the DOMFluor tool-box

(http://www.models.life.ku.dk/) in MATLAB R2012b (Math-works, Natick, MA)

(Stedmon and Bro, 2008). The toolbox allows one to identify the possible outliers and

an appropriate number of components. Prior to analysis, the Raman and Rayleigh

scatters were removed according to a homemade Matlab program. In addition, the

fluorescence at excitation and emission wavelengths both below 250 nm were not

used for further analysis to avoid the interference of noise signals (Stedmon and

Markager, 2005). PARAFAC was computed using two to seven component models

with non-negativity constraints, and the residual analysis, split half analysis, visual

inspection and model validation were applied to determine the number of

fluorescence components. After that, the obtained maximum fluorescence intensity

(Fmax) (R.U.) was used to estimate the relative levels of individual components. All

the obtained data set were further plotted using Origin 8.5 software. More detailed

information of PARAFAC analysis has been described elsewhere (Stedmon and Bro,

2008).

References

Stedmon, C.A.,Bro, R. 2008. Characterizing dissolved organic matter fluorescence with parallel

factor analysis: a tutorial. Limnol. Oceanogr-Meth. 6, 572-579.

Stedmon, C.A.,Markager, S. 2005. Resolving the variability in dissolved organic matter fluorescence in a aemperate estuary and its catchment using PARAFAC analysis. Limnol. Oceanogr. 50(2), 686-697.

Two-dimensional correlation analysis

Two-dimensional correlation analysis was conducted by using the“2D shige”

software (Kwansei-Gakuin University, Japan) to generate 2D-FTIR-CoS maps

(synchronous and asynchronous maps) and PCMW2D maps by using Cu2+

concentration as the external perturbation. Prior to analysis, the data of FTIR spectra

was corrected by baseline and smoothed, then the corrected data set were analyzed by

the“2D shige” software. After that, the synchronous and asynchronous 2DCoS maps

were generated to analysis binding sites and sequence of DOM according the Noda’s

rule (Noda, 2014). Besides, the obtained synchronous fluorescence MW2D

correlation spectra were applied to analyze conformation changes of DOM such as the

transition point and ranges with Cu2+ perturbation. The window size was selected as 5

to produce clear PCMW2D spectra (Peng et al., 2014). All the obtained data were

further plotted using Origin 8.5 software. More detailed information about the 2D-

FTIR-CoS analysis and the PCMW2D analysis was described elsewhere (Peng et al.,

2014).

References

Noda, I. 2014. Frontiers of two-dimensional correlation spectroscopy. Part 1. new concepts and noteworthy developments. J. Mol. Struct. 1069(1), 3-22.

Peng, L.L., Zhou, T., Huang, Y., Jiang, L.,Dan, Y. 2014. Microdynamics mechanism of thermal-induced hydrogel network destruction of poly(vinyl alcohol) in D2O studied by two-dimensional infrared correlation spectroscopy. J. Phys. Chem. B. 118(31), 9496-9506.

The specific procedure of additional experiment

The initial media was prepared as synthetic swine wastewater and its ionic

concentrations were listed in Table S1. Different volumes CuSO4•5H2O solution was

added into the initial media to simulate different Cu2+ concentrations (0.1, 0.5, 1.0,

2.0, and 5.0 mg/L). The pH value of media was adjusted at 6.30±0.40 by using 0.10

mol/L HCl solution. Then, the initial media was sterilized in an autoclave for 30 min

at 121°C before duckweed was added into the media. 18 beakers (500 mL, 6.4

cm×6.4 cm×12.5 cm) including 2×6 duplicate sample beakers with extra copper ions

were used in six batch tests. Each beaker contained 140 mL (3.4 cm deep in the

beaker) of media, and it was initially seeded with the same amount (0.4±0.1 g fresh

weight) of duckweed to cover the 80% surface area of 6.4 cm×6.4 cm. All beakers

were placed into a light growth chamber with 16 h photoperiod at 25 °C and a

photosynthetic photon flux density of 70±10 μmol m-2 s-1 provided by wide spectrum

fluorescent tubes. Due to the decrease of pH as the duckweed grew, 0.10 mol/L NaOH

solution was added to maintain the pH around 6.30±0.40 every day. And 1 mL water

sample was taken out from each beaker by using 1 mL injector for the DOM analysis

every 24 h for 15 days.

The specific procedure of spiking experiment with the water samples dosed with

NADH

1) 10 mg/L NADH stock solution was prepared by dissolving 0.0107 g NADH-Na2

into 1 L Milli-Q water. Then 5 mg/L NADH solution was prepared by diluting the

stock solution with synthetic wastewater, and thereby its EEM fluorescence spectra

were measured and presented in S15. As shown in Figure S15, the pure NADH peak

was located at Ex/Em=260, 350/450;

2) 5 mL NADH stock solution was added into 5 m L dilution water samples of 0 Cu to

adjust the NADH concentration to 5 mg/L;

3) Then the mixture solution was shook up for the measurement of fluorescence

spectra by using an F-4600 fluorescence spectrophotometer equipped with a 150W

xenon lamp (Hitachi, Japan).

4) Finally, the EEM fluorescence spectra of the water samples dosed with NADH

were also conducted on PARAFAC analysis according the same procedure in

MATLAB R2012b.

The fluorescence maps of component C3 in the water samples dosed with NADH

at 0 Cu2+ concentrations were shown in Figure 9b. The fluorescence peak locations

were similar to those of Figure 9a, while the corresponding fluorescence peak

intensity was strengthened significantly, indicating the dosed analytes were in

accordance with the fluorophores in the water samples from duckweed system. It

convincingly demonstrated that the component C3 was NADH.

In addition, the fluorescence map of four components in the water samples dosed

with NADH at 0 Cu2+ concentrations was shown in Figure 13b. Compared with the

Figure 13a, the Figure 13b appeared some variations on the shape and position of

components. For example, the shape of component C1 has changed, and there

appeared a new peak at Ex/Em=250/420 in component C4. It was indicated that the

increase of fluorescence intensity of component C3 could influence the shape and

position of component C1and C4, which demonstrated that the presence of other

components in DOM could shift the positions of component due to the interaction

between each component in DOM (Murphy et al., 2011). It also provided another

evidence to explain why our peaks are in unusual positions and to help demonstrate

our cause.

The pH and metal-spiking experiments1. In the pH-spiking experiment, 5 mg/L NADH in synthetic wastewater was adjusted at

different pH values (pH=3.15, 4.20, 5.18, 6.07, 7.06 and 8.01) by using 0.10 mol/L

HCl and NaOH solution. Then the adjusted solution was shook up for the

measurement of fluorescence spectra by using an F-4600 fluorescence

spectrophotometer equipped with a 150W xenon lamp (Hitachi, Japan). Their

fluorescence spectra were presented in Figure S11. As shown in Figure S11, the peaks

of NADH were significantly affected at lower pH value (pH≤4.20). For example,

when the pH value of NADH solution was 4.20, there only was one peak of NADH at

Ex/Em=350/450, and another peak at Ex/Em=260/450 was disappeared. It indicated

that peak of NADH at Ex/Em=350/450 was stable, while another peak at

Ex/Em=260/450 was instable. Thus, the peak of NADH at Ex/Em=350/450 was

usually observed in many studies rather than peak at Ex/Em=260/450. Furtherly,

when the pH was lower (pH=3.15), the peak position of NADH have switched into

the Ex/Em=270/390, suggesting the fluorophore of NADH could appear significant

blue-shifted under highly acidic conditions, and the high concentrations of proton ions

could damage the structure of NADH such as the reduction in the extent of the r-

electron system and reduction of conjugated bonds in a chain structure (Senesi, 1990).

Therefore, it was demonstrated that high concentrations of proton ions could affect

the position of fluorescence components, and thereby cause unusual components.

2. In the metal-spiking experiment, 5 mg/L NADH in synthetic wastewater were

adjusted into various Cu2+ concentrations (0, 0.1, 0.5, 1.0, 2.0 and 5.0 mg/L). Then the

adjusted solution was shook up for the measurement of fluorescence spectra by using

an F-4600 fluorescence spectrophotometer equipped with a 150W xenon lamp

(Hitachi, Japan). Their fluorescence spectra were presented in Figure S12. As shown

in Figure S12, the fluorescence intensity of NADH was decreased as the Cu2+

concentrations increased, suggesting that there was apparent interaction between

copper ions and NADH, such as the complexation and oxidation-reduction. In

addition, the fluorescence intensity of NADH would disappear at high Cu2+

concentration, which was in accordance with the phenomenon of component C3 at 5.0

mg/L Cu2+ in our previous experiment and additional experiment. Therefore, it was

demonstrated that high concentrations of copper ions could affect the intensity and

shape fluorescence components, and thereby cause unusual components.

In summary, based on the pH-spiking experiment, metal-spiking experiment and

spiking experiment of water sample dosed with NADH, it was confirmed that the high

concentrations of proton and copper ions as well as the presence of other components

could cause the variation of fluorescence spectra. For example, high concentrations of

proton ions could affect the position of fluorescence components, high concentrations

of copper ions could affect the intensity and shape fluorescence components. And the

presence of other components in DOM could shift the positions of component due to

the interaction between each component in DOM, which was in agreement with the

studies of Murphy et al., (2011) who found that other components in DOM could shift

the positions of component. Therefore, the results of these experiments could help us

explain why their peaks were in unusual positions and demonstrate their cause. For

example, the component C2 missed the 220-240 nm excitation peaks for tyrosine-like

fluorescence, which could be explained that the shadow component (220-240 nm

excitation peaks) was caused by the interactions of pH, copper ions and other

component in DOM from duckweed system.

More discussion on the peaks of C4

Additionally, component C4 exhibited a wide range of emission wavelengths

(420-540 nm) in Figure 3 and Figure S8, suggesting that it had the characteristic of

large molecular weight, conjugated aromatic moieties, and complex structure (Huang

et al, 2018), which also was in accordance with the characteristic of inert products

such as humic acids like substances. Meanwhile, it can be observed that the

fluorescence intensity and shape of component C4 had few changes as the Cu2+

concentrations increased from 0 to 4.0 mg/L (Figure 3 and Figure S8), indicating that

component C4 was a kind of inert products. Therefore, according to the above

inference, the component C4 could be identified as humic-like substance. Moreover,

the peak of C4 was located in the forbidden regions (Em>2Ex), and it should be

excluded in traditional fluorescence analysis. However, due to the continuum of

organic molecules in the longer wavelengths (Chen et al., 2003), the exclusion of

forbidden regions might be arbitrary to some extent, and there may be also underlying

fluorescence spectra in the boundary of forbidden regions. Besides, the peaks

occurred in the boundary of forbidden regions, which could be ascribed to the

responses of secondary or tertiary excitation and emission when exposed to different

environment or the resultant extension of peaks in the form of shoulders into longer

emission scan wavelengths or EEMs. Meanwhile, Murphy et al., (2011) found that

other components in DOM could shift the positions of component. Thus, it remains to

be elucidated whether the peak in the boundary of the forbidden regions actually

existed, or its existence is due to the different constraints or criteria imposed during

modeling, or due to an interaction between each fluorescence component.

References

Chen, W., Westerhoff, P., Leenheer, J.A.,Booksh, K. 2003. Fluorescence excitation-emission

matrix regional integration to quantify spectra for dissolved organic matter. Environ. Sci. Technol. 37(24), 5701-5710.Huang, M., Li, Z.W., Huang, B., Luo, N.L., Zhang, Q., Zhai, X.Q. Zeng, G.M. 2018. Investigating

binding characteristics of cadmium and copper to DOM derived from compost and rice straw using EEM-PARAFAC combined with two-dimensional FTIR correlation analyses. J. Hazard. Mater. 344, 539-548.

Murphy, K.R., Adam, H., Sachin, S., Henderson, R.K., Andy, B., Richard, S.,Khan, S.J. 2011. Organic matter fluorescence in municipal water recycling schemes: toward a unified PARAFAC model. Environ. Sci. Technol. 45(7), 2909-2916.

Table S1Ionic concentrations of synthetic swine wastewater

ionic concentrations(mg/L) Value

COD 220±10.51

NH3-N 75.2±7.62

PO4-P 14.6±2.23

NO3-N 98.3±4.14

Ca2+ 120±5.63

Mg2+ 24.5±2.32

K+ 97.5±3.40

Na+ 175.5±2.42

Cl- 285±4.53

SO42- 123±5.72

Fe-EDTA 39.9±2.51

Minor elements 2.54±0.22

Table S2a The important parameters and statistics indexes of the three models for NH3-N removal at various Cu2+ concentrations

Cu（

mg/L）First-order kinetic model

Michaelis-Menten kinetic model

Modified logistic kinetic model

rf A Rf2 k1 k2 Rh

2 rm a Rn2

0 0.0367 75.775 0.9666 0.9897 -16.54 0.9669 0.0699 0.7125 0.9879

0.1 0.0343 72.213 0.9056 0.8899 -16.02 0.9752 0.0974 0.8913 0.9765

0.5 0.0269 76.253 0.9006 0.8644 -17.01 0.9441 0.0831 0.8945 0.9617

1 0.0211 74.504 0.8689 0.7561 -16.95 0.9495 0.0793 0.9189 0.9407

2 0.0170 83.259 0.9606 0.7515 -18.52 0.9466 0.0314 0.5879 0.9666

5 0.0074 83.458 0.8930 0.4966 -19.03 0.8963 0.0046 -0.842 0.9045

Table S2b The important parameters and statistics indexes of the three models for TP removal at various Cu2+ concentrations

Cu（

mg/L）First-order kinetic model

Michaelis-Menten kinetic model

Modified logistic kinetic model

rf A Rf2 k1 k2 Rh

2 rm a Rn2

0 0.0895 14.810 0.9552 2.8551 16.940 0.9636 0.1926 0.8225 0.9895

0.1 0.0844 15.464 0.9373 2.2575 12.361 0.9776 0.2177 0.8963 0.9897

0.5 0.0725 15.950 0.9358 1.0754 5.6304 0.9429 0.1690 0.8598 0.9817

1 0.0626 15.130 0.9425 0.6530 2.5192 0.9850 0.1412 0.8549 0.9900

2 0.0481 16.365 0.9905 0.1932 -5.561 0.9914 0.0563 0.2280 0.9918

5 0.0109 16.106 0.9647 0.0853 -5.767 0.9399 0.0006 -22.09 0.9688

Table S3 Peaks of traditional DOM and their descriptionComponent plot Ex (nm)

/Em (nm)

Description Reference

350/440

The peak B at excitation–emission maxima of 350/440 nm was attributed to NADH (Lindemann et al. 1998). NADH is usually generated by the catabolism of glucose to pyruvate via glycolysis process (Nath and Das, 2004). In anaerobic hydrogen-producing process, due to the lack of electron transfer chain, NADH could be accumulated (Morel et al., 2004), and the intracellular NADH was released into the solution as the microorganisms died (Li et al., 2011).

selected componen

ts plots were

collected from Li et al., 2011

270/332

The component was considered as tyrosine-like substance belonging to the type of protein-like materials. The component was also found in other aquatic environments such as high-strength nitrogenous wastewater (Kothawala et al., 2012), lake water (Wang et al., 2009), submerged membrane bioreactor (Fellman et al., 2011).

Selected component plot was collected from Zhu et al. 2017

300/390

Components G2 was identified as microbial humic-like Generally, the generation of microbial by-products from the biodegradation within horizontal subsurface flow constructed wetland system, presumably partially from the leaves and roots of the matured plants (Wei et al., 2009). And it usually is a mixture of fluorescent compounds including humic-like fluorescence fulvi-like and protein-like fluorescence, or the presence of a complex fluorophore in which energy can be transferred internally (Coble and Brophy, 1994).

Selected component

plot was collected

from Murphy et al., 2011

250/250, 500

The component was considered as humic-like substances (Rosario-Ortiz et al., 2007).Besides, Components exhibited a wide range of emission wavelength (420-540 nm), it was suggested that they have the characteristic of large molecular weight, conjugated aromatic moieties, and complex structure (Huang et al., 2018).

Selected component plot was collected from Zhu et al. 2014

ReferenceCoble, P.G., Brophy, M.M. 1994. Investigation of the geochemistry of dissolved organic matter in

coastal waters using optical properties, pp. 377-389.Fellman, J.B., Dogramaci, S., Skrzypek, G., Dodson, W.,Grierson, P.F. 2011. Hydrologic control

of dissolved organic matter biogeochemistry in pools of a subtropical dryland river. Water Resour. Res. 47(6), 667-671.

Kothawala, D.N., Von, W.E., Koehler, B.,Tranvik, L.J. 2012. Selective loss and preservation of lake water dissolved organic matter fluorescence during long-term dark incubations. Sci. Total Environ. 433, 238-246.

Li, W.H., Sheng, G.P., Lu, R., Yu, H.Q., Li, Y.Y.,Harada, H. 2011. Fluorescence spectral characteristics of the supernatants from an anaerobic hydrogen-producing bioreactor. Appl. Microbiol. Biotechnol. 89(1), 217-224.

Lindemann, C., Marose, S., Nielsen, H.O.,Scheper, T. 1998. 2-Dimensional fluorescence spectroscopy for on-line bioprocess monitoring. Sensors & Actuators B Chemical 51(1–3), 273-277.

Morel, E., Santamaria, K., Perrier, M., Guiot, S.R.,Tartakovsky, B. 2004. Application of multi-wavelength fluorometry for on-line monitoring of an anaerobic digestion process. Water Res. 38(14), 3287-3296.

Murphy, K.R., Hambly, A., Singh, S., Henderson, R.K., Baker, A., Stuetz, R.,Khan, S.J. 2011. Organic matter fluorescence in municipal water recycling schemes: toward a unified PARAFAC model. Environ. Sci. Technol. 45(7), 2909-2916.

Nath, K.,Das, D. 2004. Improvement of fermentative hydrogen production: various approaches. Appl. Microbiol. Biotechnol. 65(5), 520-529.

Wang, Z.W., Wu, Z.C.,Tang, S.J. 2009. Characterization of dissolved organic matter in a submerged membrane bioreactor by using three-dimensional excitation and emission matrix fluorescence spectroscopy. Water Res. 43(6), 1533-1540.

Wei, L.L., Zhao, Q.L., Xue, S., Jia, T., Tang, F.,You, P.Y. 2009. Behavior and characteristics of DOM during a laboratory-scale horizontal subsurface flow wetland treatment: Effect of DOM derived from leaves and roots. Ecol. Eng. 35(10), 1405-1414.

Zhu, G., Yin, J., Zhang, P., Wang, X., Fan, G., Hua, B., Ren, B., Zheng, H.,Deng, B. 2014. DOM removal by flocculation process: Fluorescence excitation–emission matrix spectroscopy (EEMs) characterization. Desalination 346, 38-45.

Zhu, G.C., Bian, Y.N., Hursthouse, A.S., Wan, P., Szymanska, K., Ma, J., Wang, X.F.,Zhao, Z.L. 2017. Application of 3-D Fluorescence: Characterization of Natural Organic Matter in Natural Water and Water Purification Systems. Journal of Fluorescence 27(9), 1-26.

Rosario-Ortiz, F.L., Snyder, S.A.,Suffet, I.H. 2007. Characterization of dissolved organic matter in drinking water sources impacted by multiple tributaries. Water Res. 41(18), 4115-4128.

Huang, M., Li, Z.W., Huang, B., Luo, N.L., Zhang, Q., Zhai, X.Q.,Zeng, G.M. 2018. Investigating binding characteristics of cadmium and copper to DOM derived from compost and rice straw using EEM-PARAFAC combined with two-dimensional FTIR correlation analyses. J. Hazard. Mater. 344, 539-548.

Figure S1. First-order kinetic model for NH3-N (a), TP (c) respectively; Michaelis-

Menten kinetic model for NH3-N (b), TP (d) respectively, by duckweed under various

Cu2+ concentrations within 38 days.

0 5 10 15 20 25 30 35 40 450

10

20

30

40

50

60

70

80

90 (a)

NH

3-N (m

g/L)

Cultivation (day)

0 Cu 0.1 Cu 0.5 Cu 1.0 Cu 2.0 Cu 5.0 Cu

0 5 10 15 20 25 30 35 40 45

0

3

6

9

12

15

18 (c)

TP (m

g/L)

Cultivation (day)

0

3

6

9

12

15

18

0 5 10 15 20 25 30 35 40 45

(d)

Cultivation (day)

TP (m

g/L)

10

20

30

40

50

60

70

80

90

0 5 10 15 20 25 30 35 40 45

(b)

Cultivation (day)

NH

3-N (m

g/L)

Figure S2. Growth curves for duckweed at various concentrations of Cu2+ within 38

days.

Figure S3. The assimilation of Cu2+ by duckweed at various initial concentrations of

Cu2+ within 38days.

Figure S4. Fluorescence quenching curves of each PARAFAC-derived component at

various initial concentrations of Cu2+. The curve corresponds to the decrease of C3

component.

0

10

20

30

40

50

60

70

80

38 d32 d8 d0 d 26 d21 d12 d4 d

DO

C (m

g/L)

0 Cu 0.1 Cu 0.5 Cu 1.0 Cu 2.0 Cu 5.0 Cu

Figure S5. DOC concentrations at various concentrations of Cu2+ within 38 days.

(a)

(f)(e)

(d)(c)

(b)

Figure S6. The original fluorescence images of sample in 21th day under various Cu2+

concentrations in the duckweed systems. (a) 0 mg/L Cu2+; (b) 0.1 mg/L Cu2+; (c) 0.5

mg/L Cu2+; (d) 1.0 mg/L Cu2+; (e) 2.0 mg/L Cu2+; (f) 5.0 mg/L Cu2+

0 2 4 6 8 10 12 14 160.00

0.05

0.10

0.15

0.20

0.25

0.30

Abs

254

DOC (mg/L)

Equation y = a + b*xAdj. R-Square 0.99873

Value Standard Errora Intercept 0.01876 0.00222b Slope 0.0181 2.89114E-4

Figure S7. The liner fit for the relation between the DOC concentrations and UV254

absorbance.

0 Cu

5 Cu

Figure S8. EEMs of the four components derived from PARAFAC analysis under

various Cu2+ concentrations in the additional experiment.

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

(a) (b)

Figure S9. EEM fluorescence spectra of component C3 at 0 Cu2+ concentrations. (a)

The origin water samples from duckweed system; (b) water samples added with

NADH.

Figure S10. The DO value of duckweed system in various culture times from the

additional experiment.

(a) (c)(b)

(f)(d) (e)

Figure S11. The original fluorescence images of 5 mg/L NADH in synthetic

wastewater at various pH values. (a) pH=3.15; (b) pH=4.20; (c) pH=5.18; (d)

pH=6.07; (e) pH=7.06; (f) pH=8.01

200 250 300 350 400 450 500 550 600

E m

200

250

300

350

400

450

500

Ex

200 250 300 350 400 450 500 550 600

E m

200

250

300

350

400

450

500

Ex

200 250 300 350 400 450 500 550 600

E m

200

250

300

350

400

450

500

Ex

200 250 300 350 400 450 500 550 600

E m

200

250

300

350

400

450

500

Ex

200 250 300 350 400 450 500 550 600

E m

200

250

300

350

400

450

500

Ex

(a) (b) (c)

(e)(d) (f)

Figure S12. The original fluorescence images of 5mg/L NADH under various Cu2+

concentrations in the duckweed systems. (a) 0 mg/L Cu2+; (b) 0.1 mg/L Cu2+; (c) 0.5

mg/L Cu2+; (d) 1.0 mg/L Cu2+; (e) 2.0 mg/L Cu2+; (f) 5.0 mg/L Cu2+.

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em(n

m)

Ex (nm)

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

C1 C2 C3 C4

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

C1 C2 C3 C4

250 300 350 400 450 500250

300

350

400

450

500

550

600

Em (n

m)

Ex (nm)

C3

(a)

(b)

Figure S13. EEM fluorescence spectra of four components at 0 Cu2+ concentrations.

(a) The origin water samples from duckweed system; (b) water samples added with

NADH.

Figure S14. The conformation change process of DOMs with copper ions. The

transition point of conformation occurred at Cu2+concentration of 0.5 mg/L.

200 250 300 350 400 450 500 550 600

E m

200

250

300

350

400

450

500

Ex

Figure S15. The original fluorescence map of pure NADH at 5 mg/L NADH in

synthetic wastewater.