Chemosphere 95 (2014) 353–362
Contents lists available at ScienceDirect
Chemosphere journal homepage: www.elsevier.com/locate/chemosphere
Characterization and spacial distribution variability of chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary Ying Wang a,b,⇑, Di Zhang a, Zhenyao Shen a,b, Jing Chen b, Chenghong Feng a a b
The Key Laboratory of Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, PR China State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, PR China
h i g h l i g h t s The distribution and sources of CDOM in the Yangtze Estuary were studied. 3D fluorescence spectra combined with PARAFAC–PCA analysis was developed. Two humic-like components and one tryptophan-like component were identified. Pore water CDOM was mainly from the sediment release and deposition effects. Surface and bottom water CDOM was from microbial degradation of external wastes.
a r t i c l e
i n f o
Article history: Received 16 April 2013 Received in revised form 6 September 2013 Accepted 8 September 2013 Available online 14 October 2013 Keywords: DOM quality variation Fluorescence comoponents Spatial distributions Yangtze Estuary EEM–PARAFAC PCA
a b s t r a c t The spatial characteristics and the quantity and quality of the chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary, based on the abundance, degree of humification and sources, were studied using 3D fluorescence excitation emission matrix spectra (F-EEMs) with parallel factor and principal component analysis (PARAFAC–PCA). The results indicated that the CDOM abundance decreased and the aromaticity increased from the upstream to the downstream areas of the estuary. Higher CDOM abundance and degrees of humification were observed in the pore water than that in the surface and bottom waters. Two humic-like components (C1 and C3) and one tryptophan-like component (C2) were identified using the PARAFAC model. The separation of the samples by PCA highlighted the differences in the DOM properties. Components C1 and C3 concurrently displayed positive factor 1 loadings with nearly zero factor 2 loadings, while C2 showed highly positive factor 2 loadings. The C1 and C3 were very similar and exhibited a direct relationship with A355 and DOC. The CDOM in the pore water increased along the river to the coastal area, which was mainly influenced by C1 and C3 and was significantly derived from sediment remineralization and deposition from the inflow of the Yangtze River. The CDOM in the surface and bottom waters was dominated by C2, especially in the inflows of multiple tributaries that were affected by intensive anthropogenic activities. The microbial degradation of exogenous wastes from the tributary inputs and shoreside discharges were dominant sources of the CDOM in the surface and bottom waters. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Dissolved organic matter (DOM) consists of a heterogeneous mixture of organic compounds in bodies of water. Reactive groups in DOM, such as carboxylic and phenolic groups, facilitate its interactions with a variety of organic and inorganic pollutants in aquatic systems; DOM thus plays an important role in the distribution, bioavailability and toxicity of these pollutants in natural water bodies (Hur et al., 2011). The light-absorbing fraction of DOM, ⇑ Corresponding author at: The Key Laboratory of Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, PR China. Tel./fax: +86 10 5880 0398. E-mail address: [email protected] (Y. Wang). 0045-6535/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.chemosphere.2013.09.044
known as chromophoric dissolved organic matter (CDOM), is a fraction of DOM that possesses observable optical properties (Andrew et al., 2013). It commonly occurs in aquatic environments and affects surface color (Hayakawa and Sugiyama, 2008), the cycling of photoproducts (Shank and Evans, 2011) and the transformation of contaminants (Yamashita et al., 2008). Thus, the chemical characteristics and variations of CDOM have extensive implications in aquatic ecology. Estuarine ecosystems are hot spots of CDOM cycling because their CDOM compositions are controlled by the relative abundances of many different CDOM sources and the complex interactions of physical, photochemical and microbial processes, allowing the transfer of organic and inorganic substances from the continental to the oceanic environment. The Yangtze Estuary, the largest
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estuary in China, is a subtropical muddy estuary that holds considerable value within the international marine and estuarine environments research field. In recent years, the industrial, agricultural and port pollution from the entire Yangtze River basin has become the main source of pollution in the Yangtze Estuary due to the rapid industrialization and urbanization of the surrounding regions. Additionally, the flow rate and sediment discharge from the upstream and middle reaches of the Yangtze River have dramatically decreased because of the large-scale exploitation (e.g., the Deep Waterway Regulation Project, the South-to-North Water Transfer Project and the Three Gorges Project) of the Yangtze River since the 1990s (Wang et al., 2012a). All of these factors have likely affected the material cycle processes. Many research programs have conducted studies on nutrient elements (Chen et al., 2012), POPs (Gao et al., 2013) and metals (Wang et al., 2012b). However, to date, there have been few reports on the characterization of the CDOM in the Yangtze Estuary. CDOM is generally introduced into estuarine ecosystems via two pathways. One pathway involves the influx of river and overland runoff as an exogenous source (i.e., originating from decomposition and leaching of plant and soil organic matter). The other origin involves the release of leachate from phytoplankton or the microbial degradation of organic detritus known as internal source. Wastewater has recently been discharged into the estuary due to the rapid urbanization of the estuary delta. This has led to higher microbial metabolism activities and thus increased the amount of CDOM (Hong et al., 2005; Yang et al., 2007). Therefore, a number of physical, chemical and biological processes influence the distribution of CDOM in the Yangtze Estuary. Wherein, the most important factors are the mixing processes between river and marine waters, export of terrestrially-derived CDOM to oceans and its dilution effect, bacterial degradation and autochthonous production of CDOM. Besides above factors, CDOM distribution in the Yangtze Estuary could also be affected by large-scale activities and wastewater discharges. Therefore, it is necessary to study the source and distribution of the CDOM in the Yangtze Estuary. The spectroscopic characterization of CDOM is very useful for evaluating the source and quality of CDOM (Stedmon et al., 2011). As a result, several optical parameters, such as UV absorbance (Carter et al., 2012), the maximum emission wavelength (Sierra et al., 2001) and the fluorescence index (Huguet et al., 2009), have been reported to successfully characterize CDOM. Recently, an advanced approach, the combined technique of fluorescence excitation–emission matrix spectra (F-EEMs) with parallel factor analysis (PARAFAC) (Yamashita et al., 2010; Yao et al., 2011), was used to detect small but potentially significant variations in CDOM compositions in apparently similar aquatic environments. This advanced approach is thus considered an ideal technique for understanding DOM dynamics in water systems. To date, few studies have discussed the distribution of CDOM in the Yangtze Estuary, including the surface and bottom waters in the river channel (YANG et al., 2007) and the surface water in the tidal marshes (Gao et al., 2011) of Chongming Island. In these studies, only traditional CDOM coefficients and the ‘peak picking’ technique of EEMs were used, and thus the CDOM characteristics at different interfaces were not clearly identified from the river to the sea. Therefore, it is necessary to further study the combined quantitative and qualitative characterization of CDOM at the interfaces of the surface, bottom and pore water of the Yangtze Estuary using advanced F-EEMs with PARAFAC approach. This study aimed to identify the multiple sources and characterizations of CDOM in different regions and interfaces of the Yangtze Estuary in China. The main objectives were (1) to characterize the vertical and horizontal spatial distributions of the components and abundance of CDOM in the Yangtze Estuary and (2) to explore the origin of CDOM and the effects of allochthonous and autochthonous
materials on the Yangtze Estuary. These data can complement previous studies and improve our understanding of the abundance, spatial variability and spectrochemical characteristics of CDOM in the Yangtze Estuary. 2. Materials and methods 2.1. Study area and sample collection The Yangtze Estuary is the largest estuary in China, and it is home to approximately 15 million people. Industrial and domestic sewage from the coastal cities, such as Shanghai, and tributaries runs through the estuary to the East China Sea. There are more than thirty tributaries in the Yangtze Estuary, and the longest tributary is the Huangpu River. The annual average flux of the estuary is 10 billion m3. The sedimentation rate of the Yangtze Estuary is 6.3–6.6 cm yr1 (Wang et al., 2012a). Within the Yangtze Estuary, the Yangtze River is divided into two large river systems, the South Branch and the North Branch, by Chongming Island, based on the island distribution characteristics. The South Branch constitutes the main stream of the estuary and receives more than 95% of the total estuarine runoff, whereas the North Branch accounts for only approximately 5% (Li et al., 2012). The South Branch is divided into the South Channel and the North Channel by Changxing Island. The samples in our study were chosen from the main stream of the estuary, i.e., the South Branch. According to the spatial distribution (Fig. 1), a total of 16 sites in two regions, the inner estuary and the coastal areas, from the south branch of the Yangtze Estuary to the sea were chosen for surface water, bottom water and pore water collection in May 2011. Specifically, 9 sites were from the south branch (R1–R9) of the river channel, and 7 sites were from the coastal areas (C1–C7). The surface sediments were sampled to a depth of 0–2 cm using a Van Veen stainless steel grab sampler (Eijkelamp, Netherlands) and then centrifuged at 5000 rpm for 10 min to extract the pore waters. All water samples were filtered through 0.22 lm pre-combusted fiberglass filters and then stored in amber glass vials in the dark at 4 °C until they were analyzed. 2.2. Characterization of DOM 2.2.1. DOC measurements The DOC concentrations of all pre-filtered samples were determined by the combustion method using a Shimadzu TOC-VCPN organic carbon analyzer (Shimadzu, Co., Japan). 2.2.2. Optical measurements The UV absorption spectra were determined with a Cary 50 UV– Vis spectrophotometer (UV–Vis) (Varian, Inc., Australia). Measurements were baseline corrected using Milli-Q water and by running a new blank before each sample. The measured absorbances (a) were converted to revised absorption coefficients according to the method used by Zhang et al. (2009). Three-dimensional excitation–emission matrix (EEM) fluorescence spectra were recorded using a Hitachi F-4600 fluorescence spectrometer (Hitachi High-Technologies, Tokyo, Japan). Briefly, the EEM spectroscopy scanning ranges were 200–400 nm for excitation and 290–550 nm for emission. The readings were collected at 5 nm intervals for the excitation, with 3 nm emission wavelengths using a scanning speed of 2400 nm min1. These measurements were completed within 2 d. The stability of the lamp intensity in the instrument was monitored by measuring a series of quinine bisulfate solutions in 0.05 M H2SO4 daily at Ex/Em wavelengths of 350/450 nm. Fluorescence intensities were reported using the arbitrary fluorescence units (A.U.) provided by
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Fig. 1. Map of sampling sites in the river channel (R1–R9) and coastal areas (C1–C7) from the Yangtze Estuary.
the instrument. All spectra were obtained by subtracting Milli-Q water blank spectra, which were recorded under the same conditions to eliminate water Raman peaks. Rayleigh scattering effects were eliminated according to the method used by Yao et al. (2011). 2.2.3. Optical indices CDOM is an important but highly variable component of the DOM pool. The UV absorbance of DOM (e.g., at 254 nm or 355 nm) is typically related to CDOM. Because of the chemical complexity of CDOM, the adsorption coefficient at 355 nm (A355) was selected as the index for CDOM abundance (Zhang et al., 2009). The E3/E4 index, the ratio of A(300) and A(400), was used to indicate the humification of the samples. According to (Artinger et al., 2000), a decrease in the absorption ratio of E3/E4 indicates an increase in the humification and aromaticity of humic substances. The simple indicator of SUVA was used to characterize and differentiate DOM, which was determined by dividing A(254) by the corresponding DOC concentration. Relatively high SUVA values (>3 L mg1 m1) are associated with higher degrees of aromaticity and unsaturation (Rosario-Ortiz et al., 2007). Fluorescence indices can also characterize DOM. The humification index (HIX) has recently been applied to a variety of aquatic samples (Guéguen et al., 2012). It is the ratio of two scanned emission spectral regions following an excitation at 254 nm. The two emission regions are calculated between emission wavelengths 300 and 345 nm and between 435 and 480 nm. The HIX has been shown to increase when the degree of aromaticity of DOM increases. Another fluorescence index, BIX, is associated with recently produced OM, which allows an estimation of autochthonous biological activity in aquatic environments. It is scanned at excitation of 310 nm and is calculated by the ratio of the fluorescence intensity at emission of 380 nm (characteristic of autochthonous production) and 430 nm (characteristic of humic-like materials). An increase in BIX is related to an increase in the concentration of the autochthonous production of OM in water samples (Huguet et al., 2009).
The approach of PARAFAC analysis of EEMs has been described in detail elsewhere (Stedmon and Bro, 2008). If fluorescence EEMs are arranged in a three-way array X of dimensions i j k, the data signals can be decomposed into a set of three linear terms and a residual array:
X jik ¼
XF
a b c f ¼1 if jf kf
þ ejik i ¼ 1; 2; . . . ; I j ¼ 1; 2; . . . ; J k ¼ 1; 2; . . . ; K ð3Þ
where i is the number of samples, j is the number of emission wavelengths, and k is the number of excitation wavelengths. PARAFAC then decomposes these data into three matrices. The variable aif is directly proportional to the concentration of the fth fluorophore in the ith sample (scores), and bjf and ckf are estimates of the emission and excitation spectra, respectively, for the fth fluorophore (loadings). The variable F is the number of fluorophores (components), and eijk is the residual noise, which represents the variability not accounted for by the model (Stedmon et al., 2011). 2.4. Statistical analyses In this study, PARAFAC analysis was conducted using MATLAB 7.0 with the DOMFluor toolbox. A series of PARAFAC models consisting of between three and seven components were generated using the DOMFluor toolbox. A determination of the correct number of components was primarily based on split half analysis, residual analysis, and visual inspection (Stedmon and Bro, 2008). Statistical analyses (mean value, standard deviations), correlation analyses (CA) and principal component analyses (PCA) were performed with SPSS 13.0 software. The correlation analyses were used to examine the relationships between the variables. PCA was conducted using the relative abundances of the PARAFAC components from two principal components analyses. 3. Results and discussion
2.3. PARAFAC modeling
3.1. Variations in the quality of DOM in Yangtze Estuary
PARAFAC decomposes N-way arrays into N-loading matrices. Therefore, PARAFAC was used to model the dataset of F-EEMs.
Table 1 shows a summary of the properties of the water samples collected from the inner estuary to the coastal area of
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the Yangtze Estuary. The values of DOC and A355 for the surface, bottom and pore water samples in the coastal area were all lower than those in the inner estuary, which was consistent with the results from the Pearl River Estuary (Hong et al., 2005) and the Baltic Sea (Kowalczuk et al., 2005). This trend reflected that the CDOM concentrations were controlled by conservative mixing of the dilution effect during estuarine mixing. Additionally, the decrease of A355 was noticeable from inner to the outside in the surface and bottom water, while no obvious difference was observed in the pore water. CDOM in surface and bottom water was greatly influenced by the dilution effect because it existed in the main water body of the estuary. However, CDOM in pore water was less affected by waterflow gradients compared to upper layers (Huguet et al., 2009) and could be intercepted by sediment. Therefore, different phenomena were observed in three layers for A355. Besides, the levels of DOC and A355 were more variable in the inner estuary than in the coastal area. Multiple tributaries, such as Gujing River, Liuhe River and Huangpu River, flow through the city of Shanghai and thus carry a large number of pollutants into the southern branch. Additionally, the industries along the nearshore areas of the southern branch, such as petrochemical and wharf industries, are quite prosperous. This prosperity causes the discharge of a great quantity of industrial sewage into the southern branch. Therefore, the higher variability in the DOC and A355 values in the inner estuary could have been due to increased anthropogenic influences from the nearby regions. The vertical distribution of the DOM abundance showed that the levels of DOC and A355 in the pore water were much higher than those in the surface and bottom water. Similar phenomena were also observed in previous reports (Sierra et al., 2001; Burdige et al., 2004; Huguet et al., 2009). This phenomenon can be attributed to some reasons. First of all, the release of adsorbed DOM in sediments (Servais and Garnier, 2006) will lead to the increase of DOM in the pore water. In our study, the trend of sediment TOC was similar with the results of the DOC content in pore water, indicating a release effect from the sediments. Besides, it was reported that photobleaching was likely to cause the loss of CDOM in the surface water (Shank et al., 2009). The surface water samples in our study were obtained from the unshaded environment, so sunlight bleaching may contribute to the CDOM loss in the surface layer. Additionally, the DOM abundance in pore water was more variable than that in the surface and bottom waters, which might have been caused by bioturbation and organic matter diagenesis/ remineralization in the sediment. Higher values of DOC and A355 in pore water were observed at sites R2, R4, R7 and C4. The sites R2, R4 and R7 were near the inflows of three tributaries, Qianjing River, Liuhe River and Huangpu River, indicating that the tributaries contributed considerably to the CDOM pool in the Yangtze Estuary. Site C4 is located in the estuarine maximum turbidity zone, where higher concentrations of particles can adsorb more organic matter. Therefore, higher water–sediment CDOM exchanges most likely play a role here. The SUVA, E3/E4, HIX and BIX were used to reflect the CDOM compositional changes. The average SUVA for the surface, bottom and pore waters in the river were 1.53, 1.82 and 1.98 L mg1 m1
(less than 2 L mg1 m1), respectively, an indication of low aromaticity and higher relative abundances of autochthonous DOM (Rosario-Ortiz et al., 2007). Comparably, the average SUVA values in the coastal area were 2.41, 2.59 and 2.7 L mg1 m1 for the surface, bottom and pore waters, respectively, which are associated with moderate aromaticity. Additionally, the higher measured E3/ E4 values in the river channel than those in the coastal area demonstrated that the samples in the river were characteristic of lower aromaticity. The HIX indices were all less than 4 except for the pore water from the coastal area, and the BIX values ranged from 0.76 to 0.99, indicating that they were associated with weakly humified OM and autochthonous biological activity (Huguet et al., 2009). With regard to the vertical distribution of the CDOM index, both the humification and molecular weights were observed to increase from the surface down to the pore water. Burdige et al. (2004) reported that during the solid organic matter (SOM) remineralization, smaller molecular weight and lower humified materials were produced as DOM intermediates. This then leads to an imbalance between sediment DOM production and consumption. Therefore, the accumulation of DOM humification with depth was observed, which was consistent with the results in our study. Higher SUVA and lower E3/E4 values were identified in the pore water of the coastal area. In addition, the mean HIX was greater than 4, which was indicative of higher humification and aromatic characteristics of the OM in the pore water of the coastal area. 3.2. EEM–PARAFAC components of CDOM In this study, three fluorescent components (C1–C3) were validated by PARAFAC analysis using a total of 48 EEMs from water samples from the Yangtze Estuary. Table 2 shows the excitation and emission wavelength pairs of the main peaks of the three components and descriptions of similar components that were identified in previous studies. A comparison of previously identified components with the spectral contours in Fig. 2 indicated that the samples in this study contained humic-like and protein-like fluorophores. The EEM spectral characteristics of C1 were characterized by peaks at 235 nm excitation with emission at 425 nm, which was similar to the terrestrial humic-like fluorescence peak A (Coble et al., 1998; Burdige et al., 2004) that is traditionally defined in CDOM and the PARAFAC components of terrestrial humic-like materials (Murphy et al., 2008; Yamashita et al., 2008). In the C2 component, there were two excitation maxima at 230 nm and 280 nm with emission at 344 nm, which was confirmed as an autochthonous tryptophan-like fluorescence peak T (Coble et al., 1998). These wavelengths agreed with a protein-like fluorescent compound in the PARAFAC components (Murphy et al., 2008). The C3 component was also composed of two peaks at 250 nm and 360 nm excitation with emission at 475 nm. This component was categorized as a mixture of the traditional terrestrial humiclike peaks A and C (Fang et al., 2011). The spectral features were consistent with identified terrestrial-derived humic-like PARAFAC components from previous reports (Yamashita et al., 2008; Yao et al., 2011).
Table 1 Variation of DOM quality indices of samples from the Yangtze Estuary. Sample
pH
DOC (mg L1)
A355 (m1)
SUVA (L mg1 m1)
E3/E4
HIX
BIX
Inner surface Bottom Pore Outside surface Bottom Pore
7.85 ± 0.37 7.91 ± 0.29 7.79 ± 0.32 8.29 ± 0.09 8.27 ± 0.12 8.33 ± 0.15
29.7 ± 1.59 28.6 ± 1.82 81.5 ± 23.6 26.5 ± 0.60 26.3 ± 1.26 72.8 ± 15.9
6.26 ± 1.63 5.25 ± 2.47 13.8 ± 6.06 2.99 ± 0.45 2.64 ± 1.14 13.7 ± 3.49
1.53 ± 0.93 1.82 ± 0.98 1.98 ± 0.85 2.41 ± 0.18 2.59 ± 0.63 2.70 ± 0.32
5.43 ± 3.72 4.25 ± 2.33 2.39 ± 0.67 3.98 ± 0.55 3.14 ± 0.67 1.88 ± 0.32
1.55 ± 0.33 1.92 ± 0.59 3.10 ± 0.60 1.43 ± 0.09 1.35 ± 0.17 5.06 ± 1.18
0.90 ± 0.04 0.89 ± 0.1 0.99 ± 0.13 0.89 ± 0.07 0.89 ± 0.02 0.76 ± 0.04
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Table 2 The comparison of the spectral characteristics of the 3 components identified in this study with those of similar components from previous studies. Values in brackets represent secondary peaks or shoulders.
a b c d
Component of this study
Excitation/emission wavelength
Description and probable source
Comparison with other studies
C1
235/425
Terrestrial humic substances
‘‘A’’peak: 230–260/380–460a C1:
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Chemosphere journal homepage: www.elsevier.com/locate/chemosphere
Characterization and spacial distribution variability of chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary Ying Wang a,b,⇑, Di Zhang a, Zhenyao Shen a,b, Jing Chen b, Chenghong Feng a a b
The Key Laboratory of Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, PR China State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, PR China
h i g h l i g h t s The distribution and sources of CDOM in the Yangtze Estuary were studied. 3D fluorescence spectra combined with PARAFAC–PCA analysis was developed. Two humic-like components and one tryptophan-like component were identified. Pore water CDOM was mainly from the sediment release and deposition effects. Surface and bottom water CDOM was from microbial degradation of external wastes.
a r t i c l e
i n f o
Article history: Received 16 April 2013 Received in revised form 6 September 2013 Accepted 8 September 2013 Available online 14 October 2013 Keywords: DOM quality variation Fluorescence comoponents Spatial distributions Yangtze Estuary EEM–PARAFAC PCA
a b s t r a c t The spatial characteristics and the quantity and quality of the chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary, based on the abundance, degree of humification and sources, were studied using 3D fluorescence excitation emission matrix spectra (F-EEMs) with parallel factor and principal component analysis (PARAFAC–PCA). The results indicated that the CDOM abundance decreased and the aromaticity increased from the upstream to the downstream areas of the estuary. Higher CDOM abundance and degrees of humification were observed in the pore water than that in the surface and bottom waters. Two humic-like components (C1 and C3) and one tryptophan-like component (C2) were identified using the PARAFAC model. The separation of the samples by PCA highlighted the differences in the DOM properties. Components C1 and C3 concurrently displayed positive factor 1 loadings with nearly zero factor 2 loadings, while C2 showed highly positive factor 2 loadings. The C1 and C3 were very similar and exhibited a direct relationship with A355 and DOC. The CDOM in the pore water increased along the river to the coastal area, which was mainly influenced by C1 and C3 and was significantly derived from sediment remineralization and deposition from the inflow of the Yangtze River. The CDOM in the surface and bottom waters was dominated by C2, especially in the inflows of multiple tributaries that were affected by intensive anthropogenic activities. The microbial degradation of exogenous wastes from the tributary inputs and shoreside discharges were dominant sources of the CDOM in the surface and bottom waters. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Dissolved organic matter (DOM) consists of a heterogeneous mixture of organic compounds in bodies of water. Reactive groups in DOM, such as carboxylic and phenolic groups, facilitate its interactions with a variety of organic and inorganic pollutants in aquatic systems; DOM thus plays an important role in the distribution, bioavailability and toxicity of these pollutants in natural water bodies (Hur et al., 2011). The light-absorbing fraction of DOM, ⇑ Corresponding author at: The Key Laboratory of Water and Sediment Sciences, Ministry of Education, School of Environment, Beijing Normal University, Beijing 100875, PR China. Tel./fax: +86 10 5880 0398. E-mail address: [email protected] (Y. Wang). 0045-6535/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.chemosphere.2013.09.044
known as chromophoric dissolved organic matter (CDOM), is a fraction of DOM that possesses observable optical properties (Andrew et al., 2013). It commonly occurs in aquatic environments and affects surface color (Hayakawa and Sugiyama, 2008), the cycling of photoproducts (Shank and Evans, 2011) and the transformation of contaminants (Yamashita et al., 2008). Thus, the chemical characteristics and variations of CDOM have extensive implications in aquatic ecology. Estuarine ecosystems are hot spots of CDOM cycling because their CDOM compositions are controlled by the relative abundances of many different CDOM sources and the complex interactions of physical, photochemical and microbial processes, allowing the transfer of organic and inorganic substances from the continental to the oceanic environment. The Yangtze Estuary, the largest
354
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estuary in China, is a subtropical muddy estuary that holds considerable value within the international marine and estuarine environments research field. In recent years, the industrial, agricultural and port pollution from the entire Yangtze River basin has become the main source of pollution in the Yangtze Estuary due to the rapid industrialization and urbanization of the surrounding regions. Additionally, the flow rate and sediment discharge from the upstream and middle reaches of the Yangtze River have dramatically decreased because of the large-scale exploitation (e.g., the Deep Waterway Regulation Project, the South-to-North Water Transfer Project and the Three Gorges Project) of the Yangtze River since the 1990s (Wang et al., 2012a). All of these factors have likely affected the material cycle processes. Many research programs have conducted studies on nutrient elements (Chen et al., 2012), POPs (Gao et al., 2013) and metals (Wang et al., 2012b). However, to date, there have been few reports on the characterization of the CDOM in the Yangtze Estuary. CDOM is generally introduced into estuarine ecosystems via two pathways. One pathway involves the influx of river and overland runoff as an exogenous source (i.e., originating from decomposition and leaching of plant and soil organic matter). The other origin involves the release of leachate from phytoplankton or the microbial degradation of organic detritus known as internal source. Wastewater has recently been discharged into the estuary due to the rapid urbanization of the estuary delta. This has led to higher microbial metabolism activities and thus increased the amount of CDOM (Hong et al., 2005; Yang et al., 2007). Therefore, a number of physical, chemical and biological processes influence the distribution of CDOM in the Yangtze Estuary. Wherein, the most important factors are the mixing processes between river and marine waters, export of terrestrially-derived CDOM to oceans and its dilution effect, bacterial degradation and autochthonous production of CDOM. Besides above factors, CDOM distribution in the Yangtze Estuary could also be affected by large-scale activities and wastewater discharges. Therefore, it is necessary to study the source and distribution of the CDOM in the Yangtze Estuary. The spectroscopic characterization of CDOM is very useful for evaluating the source and quality of CDOM (Stedmon et al., 2011). As a result, several optical parameters, such as UV absorbance (Carter et al., 2012), the maximum emission wavelength (Sierra et al., 2001) and the fluorescence index (Huguet et al., 2009), have been reported to successfully characterize CDOM. Recently, an advanced approach, the combined technique of fluorescence excitation–emission matrix spectra (F-EEMs) with parallel factor analysis (PARAFAC) (Yamashita et al., 2010; Yao et al., 2011), was used to detect small but potentially significant variations in CDOM compositions in apparently similar aquatic environments. This advanced approach is thus considered an ideal technique for understanding DOM dynamics in water systems. To date, few studies have discussed the distribution of CDOM in the Yangtze Estuary, including the surface and bottom waters in the river channel (YANG et al., 2007) and the surface water in the tidal marshes (Gao et al., 2011) of Chongming Island. In these studies, only traditional CDOM coefficients and the ‘peak picking’ technique of EEMs were used, and thus the CDOM characteristics at different interfaces were not clearly identified from the river to the sea. Therefore, it is necessary to further study the combined quantitative and qualitative characterization of CDOM at the interfaces of the surface, bottom and pore water of the Yangtze Estuary using advanced F-EEMs with PARAFAC approach. This study aimed to identify the multiple sources and characterizations of CDOM in different regions and interfaces of the Yangtze Estuary in China. The main objectives were (1) to characterize the vertical and horizontal spatial distributions of the components and abundance of CDOM in the Yangtze Estuary and (2) to explore the origin of CDOM and the effects of allochthonous and autochthonous
materials on the Yangtze Estuary. These data can complement previous studies and improve our understanding of the abundance, spatial variability and spectrochemical characteristics of CDOM in the Yangtze Estuary. 2. Materials and methods 2.1. Study area and sample collection The Yangtze Estuary is the largest estuary in China, and it is home to approximately 15 million people. Industrial and domestic sewage from the coastal cities, such as Shanghai, and tributaries runs through the estuary to the East China Sea. There are more than thirty tributaries in the Yangtze Estuary, and the longest tributary is the Huangpu River. The annual average flux of the estuary is 10 billion m3. The sedimentation rate of the Yangtze Estuary is 6.3–6.6 cm yr1 (Wang et al., 2012a). Within the Yangtze Estuary, the Yangtze River is divided into two large river systems, the South Branch and the North Branch, by Chongming Island, based on the island distribution characteristics. The South Branch constitutes the main stream of the estuary and receives more than 95% of the total estuarine runoff, whereas the North Branch accounts for only approximately 5% (Li et al., 2012). The South Branch is divided into the South Channel and the North Channel by Changxing Island. The samples in our study were chosen from the main stream of the estuary, i.e., the South Branch. According to the spatial distribution (Fig. 1), a total of 16 sites in two regions, the inner estuary and the coastal areas, from the south branch of the Yangtze Estuary to the sea were chosen for surface water, bottom water and pore water collection in May 2011. Specifically, 9 sites were from the south branch (R1–R9) of the river channel, and 7 sites were from the coastal areas (C1–C7). The surface sediments were sampled to a depth of 0–2 cm using a Van Veen stainless steel grab sampler (Eijkelamp, Netherlands) and then centrifuged at 5000 rpm for 10 min to extract the pore waters. All water samples were filtered through 0.22 lm pre-combusted fiberglass filters and then stored in amber glass vials in the dark at 4 °C until they were analyzed. 2.2. Characterization of DOM 2.2.1. DOC measurements The DOC concentrations of all pre-filtered samples were determined by the combustion method using a Shimadzu TOC-VCPN organic carbon analyzer (Shimadzu, Co., Japan). 2.2.2. Optical measurements The UV absorption spectra were determined with a Cary 50 UV– Vis spectrophotometer (UV–Vis) (Varian, Inc., Australia). Measurements were baseline corrected using Milli-Q water and by running a new blank before each sample. The measured absorbances (a) were converted to revised absorption coefficients according to the method used by Zhang et al. (2009). Three-dimensional excitation–emission matrix (EEM) fluorescence spectra were recorded using a Hitachi F-4600 fluorescence spectrometer (Hitachi High-Technologies, Tokyo, Japan). Briefly, the EEM spectroscopy scanning ranges were 200–400 nm for excitation and 290–550 nm for emission. The readings were collected at 5 nm intervals for the excitation, with 3 nm emission wavelengths using a scanning speed of 2400 nm min1. These measurements were completed within 2 d. The stability of the lamp intensity in the instrument was monitored by measuring a series of quinine bisulfate solutions in 0.05 M H2SO4 daily at Ex/Em wavelengths of 350/450 nm. Fluorescence intensities were reported using the arbitrary fluorescence units (A.U.) provided by
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Fig. 1. Map of sampling sites in the river channel (R1–R9) and coastal areas (C1–C7) from the Yangtze Estuary.
the instrument. All spectra were obtained by subtracting Milli-Q water blank spectra, which were recorded under the same conditions to eliminate water Raman peaks. Rayleigh scattering effects were eliminated according to the method used by Yao et al. (2011). 2.2.3. Optical indices CDOM is an important but highly variable component of the DOM pool. The UV absorbance of DOM (e.g., at 254 nm or 355 nm) is typically related to CDOM. Because of the chemical complexity of CDOM, the adsorption coefficient at 355 nm (A355) was selected as the index for CDOM abundance (Zhang et al., 2009). The E3/E4 index, the ratio of A(300) and A(400), was used to indicate the humification of the samples. According to (Artinger et al., 2000), a decrease in the absorption ratio of E3/E4 indicates an increase in the humification and aromaticity of humic substances. The simple indicator of SUVA was used to characterize and differentiate DOM, which was determined by dividing A(254) by the corresponding DOC concentration. Relatively high SUVA values (>3 L mg1 m1) are associated with higher degrees of aromaticity and unsaturation (Rosario-Ortiz et al., 2007). Fluorescence indices can also characterize DOM. The humification index (HIX) has recently been applied to a variety of aquatic samples (Guéguen et al., 2012). It is the ratio of two scanned emission spectral regions following an excitation at 254 nm. The two emission regions are calculated between emission wavelengths 300 and 345 nm and between 435 and 480 nm. The HIX has been shown to increase when the degree of aromaticity of DOM increases. Another fluorescence index, BIX, is associated with recently produced OM, which allows an estimation of autochthonous biological activity in aquatic environments. It is scanned at excitation of 310 nm and is calculated by the ratio of the fluorescence intensity at emission of 380 nm (characteristic of autochthonous production) and 430 nm (characteristic of humic-like materials). An increase in BIX is related to an increase in the concentration of the autochthonous production of OM in water samples (Huguet et al., 2009).
The approach of PARAFAC analysis of EEMs has been described in detail elsewhere (Stedmon and Bro, 2008). If fluorescence EEMs are arranged in a three-way array X of dimensions i j k, the data signals can be decomposed into a set of three linear terms and a residual array:
X jik ¼
XF
a b c f ¼1 if jf kf
þ ejik i ¼ 1; 2; . . . ; I j ¼ 1; 2; . . . ; J k ¼ 1; 2; . . . ; K ð3Þ
where i is the number of samples, j is the number of emission wavelengths, and k is the number of excitation wavelengths. PARAFAC then decomposes these data into three matrices. The variable aif is directly proportional to the concentration of the fth fluorophore in the ith sample (scores), and bjf and ckf are estimates of the emission and excitation spectra, respectively, for the fth fluorophore (loadings). The variable F is the number of fluorophores (components), and eijk is the residual noise, which represents the variability not accounted for by the model (Stedmon et al., 2011). 2.4. Statistical analyses In this study, PARAFAC analysis was conducted using MATLAB 7.0 with the DOMFluor toolbox. A series of PARAFAC models consisting of between three and seven components were generated using the DOMFluor toolbox. A determination of the correct number of components was primarily based on split half analysis, residual analysis, and visual inspection (Stedmon and Bro, 2008). Statistical analyses (mean value, standard deviations), correlation analyses (CA) and principal component analyses (PCA) were performed with SPSS 13.0 software. The correlation analyses were used to examine the relationships between the variables. PCA was conducted using the relative abundances of the PARAFAC components from two principal components analyses. 3. Results and discussion
2.3. PARAFAC modeling
3.1. Variations in the quality of DOM in Yangtze Estuary
PARAFAC decomposes N-way arrays into N-loading matrices. Therefore, PARAFAC was used to model the dataset of F-EEMs.
Table 1 shows a summary of the properties of the water samples collected from the inner estuary to the coastal area of
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the Yangtze Estuary. The values of DOC and A355 for the surface, bottom and pore water samples in the coastal area were all lower than those in the inner estuary, which was consistent with the results from the Pearl River Estuary (Hong et al., 2005) and the Baltic Sea (Kowalczuk et al., 2005). This trend reflected that the CDOM concentrations were controlled by conservative mixing of the dilution effect during estuarine mixing. Additionally, the decrease of A355 was noticeable from inner to the outside in the surface and bottom water, while no obvious difference was observed in the pore water. CDOM in surface and bottom water was greatly influenced by the dilution effect because it existed in the main water body of the estuary. However, CDOM in pore water was less affected by waterflow gradients compared to upper layers (Huguet et al., 2009) and could be intercepted by sediment. Therefore, different phenomena were observed in three layers for A355. Besides, the levels of DOC and A355 were more variable in the inner estuary than in the coastal area. Multiple tributaries, such as Gujing River, Liuhe River and Huangpu River, flow through the city of Shanghai and thus carry a large number of pollutants into the southern branch. Additionally, the industries along the nearshore areas of the southern branch, such as petrochemical and wharf industries, are quite prosperous. This prosperity causes the discharge of a great quantity of industrial sewage into the southern branch. Therefore, the higher variability in the DOC and A355 values in the inner estuary could have been due to increased anthropogenic influences from the nearby regions. The vertical distribution of the DOM abundance showed that the levels of DOC and A355 in the pore water were much higher than those in the surface and bottom water. Similar phenomena were also observed in previous reports (Sierra et al., 2001; Burdige et al., 2004; Huguet et al., 2009). This phenomenon can be attributed to some reasons. First of all, the release of adsorbed DOM in sediments (Servais and Garnier, 2006) will lead to the increase of DOM in the pore water. In our study, the trend of sediment TOC was similar with the results of the DOC content in pore water, indicating a release effect from the sediments. Besides, it was reported that photobleaching was likely to cause the loss of CDOM in the surface water (Shank et al., 2009). The surface water samples in our study were obtained from the unshaded environment, so sunlight bleaching may contribute to the CDOM loss in the surface layer. Additionally, the DOM abundance in pore water was more variable than that in the surface and bottom waters, which might have been caused by bioturbation and organic matter diagenesis/ remineralization in the sediment. Higher values of DOC and A355 in pore water were observed at sites R2, R4, R7 and C4. The sites R2, R4 and R7 were near the inflows of three tributaries, Qianjing River, Liuhe River and Huangpu River, indicating that the tributaries contributed considerably to the CDOM pool in the Yangtze Estuary. Site C4 is located in the estuarine maximum turbidity zone, where higher concentrations of particles can adsorb more organic matter. Therefore, higher water–sediment CDOM exchanges most likely play a role here. The SUVA, E3/E4, HIX and BIX were used to reflect the CDOM compositional changes. The average SUVA for the surface, bottom and pore waters in the river were 1.53, 1.82 and 1.98 L mg1 m1
(less than 2 L mg1 m1), respectively, an indication of low aromaticity and higher relative abundances of autochthonous DOM (Rosario-Ortiz et al., 2007). Comparably, the average SUVA values in the coastal area were 2.41, 2.59 and 2.7 L mg1 m1 for the surface, bottom and pore waters, respectively, which are associated with moderate aromaticity. Additionally, the higher measured E3/ E4 values in the river channel than those in the coastal area demonstrated that the samples in the river were characteristic of lower aromaticity. The HIX indices were all less than 4 except for the pore water from the coastal area, and the BIX values ranged from 0.76 to 0.99, indicating that they were associated with weakly humified OM and autochthonous biological activity (Huguet et al., 2009). With regard to the vertical distribution of the CDOM index, both the humification and molecular weights were observed to increase from the surface down to the pore water. Burdige et al. (2004) reported that during the solid organic matter (SOM) remineralization, smaller molecular weight and lower humified materials were produced as DOM intermediates. This then leads to an imbalance between sediment DOM production and consumption. Therefore, the accumulation of DOM humification with depth was observed, which was consistent with the results in our study. Higher SUVA and lower E3/E4 values were identified in the pore water of the coastal area. In addition, the mean HIX was greater than 4, which was indicative of higher humification and aromatic characteristics of the OM in the pore water of the coastal area. 3.2. EEM–PARAFAC components of CDOM In this study, three fluorescent components (C1–C3) were validated by PARAFAC analysis using a total of 48 EEMs from water samples from the Yangtze Estuary. Table 2 shows the excitation and emission wavelength pairs of the main peaks of the three components and descriptions of similar components that were identified in previous studies. A comparison of previously identified components with the spectral contours in Fig. 2 indicated that the samples in this study contained humic-like and protein-like fluorophores. The EEM spectral characteristics of C1 were characterized by peaks at 235 nm excitation with emission at 425 nm, which was similar to the terrestrial humic-like fluorescence peak A (Coble et al., 1998; Burdige et al., 2004) that is traditionally defined in CDOM and the PARAFAC components of terrestrial humic-like materials (Murphy et al., 2008; Yamashita et al., 2008). In the C2 component, there were two excitation maxima at 230 nm and 280 nm with emission at 344 nm, which was confirmed as an autochthonous tryptophan-like fluorescence peak T (Coble et al., 1998). These wavelengths agreed with a protein-like fluorescent compound in the PARAFAC components (Murphy et al., 2008). The C3 component was also composed of two peaks at 250 nm and 360 nm excitation with emission at 475 nm. This component was categorized as a mixture of the traditional terrestrial humiclike peaks A and C (Fang et al., 2011). The spectral features were consistent with identified terrestrial-derived humic-like PARAFAC components from previous reports (Yamashita et al., 2008; Yao et al., 2011).
Table 1 Variation of DOM quality indices of samples from the Yangtze Estuary. Sample
pH
DOC (mg L1)
A355 (m1)
SUVA (L mg1 m1)
E3/E4
HIX
BIX
Inner surface Bottom Pore Outside surface Bottom Pore
7.85 ± 0.37 7.91 ± 0.29 7.79 ± 0.32 8.29 ± 0.09 8.27 ± 0.12 8.33 ± 0.15
29.7 ± 1.59 28.6 ± 1.82 81.5 ± 23.6 26.5 ± 0.60 26.3 ± 1.26 72.8 ± 15.9
6.26 ± 1.63 5.25 ± 2.47 13.8 ± 6.06 2.99 ± 0.45 2.64 ± 1.14 13.7 ± 3.49
1.53 ± 0.93 1.82 ± 0.98 1.98 ± 0.85 2.41 ± 0.18 2.59 ± 0.63 2.70 ± 0.32
5.43 ± 3.72 4.25 ± 2.33 2.39 ± 0.67 3.98 ± 0.55 3.14 ± 0.67 1.88 ± 0.32
1.55 ± 0.33 1.92 ± 0.59 3.10 ± 0.60 1.43 ± 0.09 1.35 ± 0.17 5.06 ± 1.18
0.90 ± 0.04 0.89 ± 0.1 0.99 ± 0.13 0.89 ± 0.07 0.89 ± 0.02 0.76 ± 0.04
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Table 2 The comparison of the spectral characteristics of the 3 components identified in this study with those of similar components from previous studies. Values in brackets represent secondary peaks or shoulders.
a b c d
Component of this study
Excitation/emission wavelength
Description and probable source
Comparison with other studies
C1
235/425
Terrestrial humic substances
‘‘A’’peak: 230–260/380–460a C1:
