Seasonal and spatial constraints of fluorophores in the midwestern Bay of Bengal by PARAFAC analysis of excitation emission matrix spectra

Estuarine, Coastal and Shelf Science 100 (2012) 162e171

Contents lists available at SciVerse ScienceDirect

Estuarine, Coastal and Shelf Science journal homepage: www.elsevier.com/locate/ecss

Seasonal and spatial constraints of fluorophores in the midwestern Bay of Bengal by PARAFAC analysis of excitation emission matrix spectra N.V.H.K. Chari a, Nittala S. Sarma a, *, Sudarsana Rao Pandi a, K. Narasimha Murthy a, b a b

Marine Chemistry Laboratory, School of Chemistry, Andhra University, Visakhapatnam 530003, India Department of Zoology, Andhra University, Visakhapatnam 530003, India

a r t i c l e i n f o

a b s t r a c t

Article history: Received 21 September 2011 Accepted 31 January 2012 Available online 6 February 2012

Dissolved organic matter (DOM) fluorescence was measured along with hydrochemical constituents and chlorophyll a of water collected monthly from the midwestern Bay of Bengal (Indian Ocean) that included the Godavari estuary and its adjoining coastal region during the period MarcheOctober 2009. By applying parallel factor (PARAFAC) modelling of the excitation emission matrix spectral data, five components e three humic (A, C, and M peaks) and two protein (B and T) were noticed. The tyrosine like component (B) is the most abundant throughout except for the estuary during monsoon when the UV humic like component (A) surpassed it. During the pre-monsoon season, the B, C and M fluorophores are enriched due to a higher bacterial decay of organic matter. The fluorescence index (FI) was higher and the humification index (HIX) lower during pre-monsoon. Similarly, the FI was higher and HIX lower for the coastal region than the estuary. The A:C ratio and A:M ratio are essentially seasonal indicators e they were <1 in the pre-monsoon and >5 during monsoon. The M:C ratio is essentially a spatial indicator, being <1 in the estuary and >1 in the coastal region during both seasons. Ó 2012 Elsevier Ltd. All rights reserved.

Keywords: dissolved organic matter optical properties coastal waters statistical models fluorescence index A:C, M:C and A:M ratios

1. Introduction Dissolved organic matter (DOM) is a complex mixture of organic compounds introduced by terrestrial and internal sources and is continuously reworked by photochemical, biochemical and geochemical reactions (Benner, 2002). Structural characterization of the molecules in DOM has so far been successful to identify components amounting to only <15%, of lipids, carbohydrates, fatty acids, amino acids and phenols. A majority of the DOM is in the form of a polymer matrix containing among others, aromatic, i.e., humic and trace metal components with no definite but well classified nominal molecular weight ranges (Repeta et al., 2002). The DOM was called “gelbstoff” or “yellow substance” by Kalle (1938), due to its colour. In recent literature, the DOM fraction of natural waters with absorption covering the UVeVisible range of radiation is called as “colored dissolved organic matter” or more appropriately as “chromophoric dissolved organic matter” (CDOM). A subfraction of CDOM exhibits fluorescence when excited with ultraviolet light, and this fraction is referred as fluorescent dissolved organic matter (FDOM) (Coble, 2007). Due to their greater reactivity compared to the bulk DOM and environmental

* Corresponding author. E-mail address: [email protected] (N.S. Sarma). 0272-7714/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.ecss.2012.01.012

significance, CDOM and FDOM structural study has been an important objective in several aquatic studies. For the structural exploration of CDOM and FDOM, optical methods that are noninvasive and require small sample, namely absorption spectra for CDOM and fluorescence spectra for FDOM are employed. The utility of fluorescence spectra got a breakthrough with the introduction by Coble et al. (1990) of excitation emission matrix (EEM) spectra by which various fluorophores causing fluorescence of natural waters were identified. A second breakthrough was the application of parallel factor (PARAFAC) analysis of the three dimensional EEM data by Stedmon et al. (2003) through which both qualitative assignments and quantitative estimation of each fluorophore could be made. Studies made by several other research groups have extended understanding of the sources, cycling and structure of FDOM as well as the potential of FDOM in unravelling mixing locally, e.g., in estuaries (cf., Maie et al., 2006) and large scale circulation (Nelson et al., 2010; Jørgensen et al., 2011). Studies have been extended to the tropical seas, e.g., Chinese estuaries (Guo et al., 2007), and the Gulf of Mexico (Boehme et al., 2004; Conmy et al., 2004; Milbrandt et al., 2010) where the FDOM turnover is likely to be faster due to enhanced levels of bacterial action but controlled by photodegradation (Moran et al., 2000). Studies on dilution basins such as the Baltic (e.g., Kowalczuk et al., 2010) and Arctic (e.g., Guéguen et al., 2007) that receive sizable levels of FDOM from rivers, and the inland rivers and lakes contaminated

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171

with organic pollutants have further expanded our knowledge about FDOM. In natural waters, fluorescence is mainly caused by the humic and protein structural moieties of FDOM. The humic fluorophores are the UV humic like (A), visible-humic like (C) and marine humic like (M) and the protein fluorophores are the tryptophan-like (T) and tyrosine-like (B) components (Coble, 1996). The abundance of these fluorophores, shifts in their excitation/ emission maxima, and modelling have been the focus of recent studies as they are helpful in provenance characterization, and for an understanding of the carbon cycling. There exists a gap in the FDOM cataloguing of the Indian Ocean. A few studies do exist in the case of the northwestern Arabian Sea (Coble et al., 1998; Breves and Reuter, 2001; Breves et al., 2003a, b). The Bay of Bengal, to our knowledge, remains unexplored despite being the world’s largest bay. A semi-enclosed basin with atypical oceanographic conditions, the Bay receives 6.6% of world river discharge (UNESCO, 1979) and 9% of SPM flux (Subramanian, 1993) for an area of only 1.13% of the ocean surface. The Indian coastline that borders it on the western side supports several major estuaries Ganga, Mahanadi, Godavari, Krishna and Cauvery that are sources of organic matter. These rivers are of different sizes and exhibit extensive seasonal variability in terms of discharge. Consequently, the effect of spatial and seasonal changes taking place in the western Bay should influence largely, and be predictable from, the fluorescence behaviour of its waters. The FDOM optical characterization is helpful in the estimation of marine biological resources by remote sensing as it can give an estimate of CDOM, more accurately than the absorbance measurement, and a correction for CDOM is mandatory for chlorophyll (phytoplankton) retrieval as chlorophyll’s major absorption band in the blue region of the solar spectrum is within range of CDOM’s absorption. The main objective of the SATellite Coastal and Oceanographic REsearch (SATCORE) project of Indian National Centre for Ocean Information Services (INCOIS) is to conduct field surveys to characterize inherent optical properties of the western Bay of Bengal and eastern Arabian Sea for constraining satellite ocean colour algorithms for the retrieval of chlorophyll a (chl a) concentrations and achieve better accuracy of their predictions for the region. As a part of this programme, we undertook a study of the fluorescence behaviour of the surface waters of an area comprising the Godavari estuary and its adjacent continental shelf in the Midwestern Bay of Bengal. The objective of this initial report was to examine the utility of fluorescence EEM spectra followed by PARAFAC analysis for differentiating temporal and spatial distribution of different fluorophore groups characteristic to this dynamic water body. 2. Materials and methods 2.1. Study area The study was done in an area comprising different aquatic conditions of the coastal and estuarine region (Fig. 1). The coastal transect T1 is off Visakhapatnam and out of reach for any major Indian peninsular river. The nearest estuary to it is the Godavari estuary towards south by 200e250 km (this study), and the Mahanadi estuary, towards north by 300e350 km. The other coastal transect T2 is directly opposite the Godavari estuary, and hence influenced by the river influx particularly during monsoon season. The third transect is the estuary (E) itself. The Godavari estuarine system is located at w16
11.500 N and 82
15.00 E and covers an area of 30 km2. The Godavari is one of the major rivers in India with a basin of 0.31*106 km2 and 25 tributaries and an annual discharge of 105 km3 (Rao, 1975), of which as much as 90% occurs during the monsoon season consisting of the major i.e., southwest

163

Fig. 1. Study Area with Transects (T1 off Visakhapatnam, T2 off Godavari estuary) and Stations (C).

(summer: JuneeSeptember; CPCB, 1995) monsoon and northeast (winter: OctobereDecember) monsoon. This river ranks 34th and 32nd in terms of catchment area and water discharge, respectively, amongst the 60 largest rivers of the world (Ludwig et al., 1996; Gaillard et al., 1999). The basin climate is generally dry with an average annual rainfall of 1512 mm y1 of which more than 75% of the annual mean is received during the summer monsoon. The Godavari estuary is well mixed in the pre-monsoon season when the (semi-diurnal) tidal effect (tidal amplitude: 0.5e2 m) dominates. A salt wedge begins to develop in the early monsoon (late May) and by September the estuary is well stratified as the runoff becomes maximal. The flushing time is inversely proportional to the discharge. It is only w4 tidal cycles (48 h) in SeptembereOctober (Reddy and Ranga Rao, 1993). Field campaigns were done monthly in the coastal transects, March through May representing pre-monsoon condition, and August through October 2009 representing (southwest) monsoon condition, and twice a month during these months in the estuary (Fig. 1), except when the collections had to be called off due to adverse weather, or due to nonavailability of craft. Sampling of the estuarine water was done additionally during June and July 2009 twice each month. A hired vessel MFV Srinivasa or RK Katadi improvised for scientific cruises was used for field campaigns in the coastal region (T1 and T2) and a smaller boat in the estuary. Water samples were collected from surface (1 m) using Teflon inner lined Niskin bottles. A total number of 15 stations were occupied, 6 of T1 (10, 20, 30, 50, 75 and 100 m isobaths), 5 of T2 (20, 30, 50, 75 and 100) and 4 of E. The estuary stations are at the landmarks, three covering the lower estuary (Yanam, St. 2; Vriddha Gautami, St. 3 and Bhairavapalem, St. 4), and one representing the upper estuary (Kotipalli, St. 1; Fig. 1). The average depth at the estuarine stations is 10e12 (St. 1), 15e18 (2), 5e6 (3) and 5e6 m (4). Immediately after collection, a subsample (60 ml) was drawn for dissolved oxygen estimation (followed by fixing with reagent), and another subsample (50 ml) was filtered (0.22 m Millipore membrane filter, soaked in MilliQ organic free water) into amber coloured bottles under low light for CDOM and FDOM measurements. Temperature was read from a calibrated clean thermometer (0.1
C precision) suspended in the Niskin by opening its lid. One

164

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171

litre water was filtered separately onto GF/F Whatman filters for the estimation of chl a. These filters and the samples meant for optical measurements were kept in a refrigerated container (4e8
C) until analysis in the shore laboratory. The filtered water was used for hydrochemical analysis in the shore laboratory. Each campaign lasted for 6e8 h, the samples reached the laboratory in 4e12 h from the time they were collected and the analyses started immediately. 2.2. Analytical measurements 2.2.1. Hydrochemical constituents The pH was measured with a Thermo Scientific Orion Star benchtop pH metre with accuracy of 0.01. Salinity was determined by argentometric titration, and dissolved oxygen was estimated by the modified Winkler’s method (Grasshoff et al., 1999). For the determination of chl a, the filters containing the particulate matter were extracted in 90% acetone overnight at 4
C, and the absorption spectrum of the supernatant measured using Shimadzu 1800 double beam UVeVisible spectrophotometer. The concentration of chl a was calculated using Jeffery equations (Jeffrey and Humphrey, 1975). 2.2.2. EEM spectra The Excitation Emission Matrix spectra were taken on a Horiba Jobin Yvon Fluoromax-4 spectrofluorometer equipped with 150 W ozone-free xenon arc-lamp and R928P detector. The EEMs were collected by using excitation wavelengths between 250 nm and 400 nm at 5 nm interval and emission wavelengths from 290 to 550 nm also at 5 nm interval. The instrument was set up to collect the signal from sample (S) normalized to the signal from reference detector (R), which is known as ratio mode (S/R) using 5 nm bandwidth on both excitation and emission monochromators with integration time 0.2 s. The EEM spectra were corrected for instrumental biases by applying excitation and emission correction factors provided by the manufacturer. The EEM spectra were then normalized with respect to the area under the Raman scatter peak (ex: 350 nm, em: 381e426 nm; Murphy et al., 2010). The Raman normalized MilliQ water EEM spectrum was subtracted from the EEM spectra of samples to remove the water Raman scattering. The resultant spectra are in Raman Units (RU). The RU is preferred as it is helpful for a global comparison (Stedmon et al., 2003; Murphy et al., 2010). 2.2.3. Fluorescence index (FI) and humification index (HIX) calculation Fluorescence Index (FI) is used to infer the DOM origin e whether microbiologically derived or terrestrially derived (McKnight et al., 2001). It was calculated as the ratio of emission intensity at 450 nm and 500 nm at excitation of 370 nm. Humification Index (HIX) is the ratio of two areas (H/L) of emission spectrum at lex of 255 nm (254 nm in literature). These two areas are calculated between 300 and 345 nm for L and between 435 and 480 nm for H. The HIX is considered an indicator of the extent of humification and organic matter maturation (Zsolnay et al., 1999). 2.2.4. PARAFAC modelling The Parallel factor (PARAFAC) analysis extracts components that represent individual fluorophores and their concentrations from the large dataset of three dimensional EEM spectra. The Components are mathematically independent, and each can be considered as a chemical analyte or a group of strongly covarying analytes (Bro, 1997). The PARAFAC was done in MATLAB R2007a using the DOMFluor, which contains N way toolbox ver 3.1 (Stedmon and Bro, 2008). Before the PARAFAC analysis, high intensity EEM data attributable to the second order Rayleigh scattering were replaced

with nil values (Andersen and Bro, 2003; Ohno and Bro, 2006). Determination of the optimum number of Components was done by split half analysis and random initialization (Stedmon and Bro, 2008), as a part of the program. The PARAFAC analysis was applied to our dataset (136 samples) from T1 (44), T2 (40) and the Estuary (52). The PARAFAC analysis gives the relative intensities (Scores) of the components, from which the absolute intensities (I) were calculated by multiplying with the corresponding excitation and emission loadings at their lmax (Stedmon et al., 2003; Kowalczuk et al., 2009): For the nth component: In ¼ Scoren*Exn (lmax)*Emn(lmax) where Scoren is the relative intensity of the nth component, Exn(lmax) is the maximum of the excitation loading of the nth component, and Emn(lmax) is the maximum of the emission loading of the nth component derived from the model. 3. Results A summary of the results of hydrochemical parameters is given in Table 1. Salinity, at the upper estuary was low (0.03e1.5) during the monsoon season (AugusteOctober) and higher (13.9e14.9) in the pre-monsoon season (MarcheMay). In the lower estuary, salinity was higher (2.3e14 and 33e34 respectively) in the two seasons. The mean salinity of coastal waters of T1 transects in premonsoon and monsoon seasons (33.77 and 31.11 respectively) was higher than those of T2 (32.72, 30.14). The estuarine water was warmer (0.2e1.4
C) than coastal (T1 and T2) waters. Within the estuary, the pre-monsoon water was warmer by 1
C in the lower estuary and 1.5
C in the upper estuary. The behaviour was the opposite in coastal water. The pre-monsoon water was cooler by 1.9
C (T1) and 1
C (T2) than the monsoon water. The pH (range: 7.95e8.5) was higher (>8.2) in T2 during both seasons and in T1 during monsoon. It was also high (8.21) during pre-monsoon in the lower estuary. Chl a (range: 0.8e11.15 ppb) was higher in the estuary compared to the coastal water especially during premonsoon season. Between the two coastal transects, T1 had higher chl a. The parallel factor (PARAFAC) analysis of the EEM spectra identified five primary Components. The correspondence of these Components (Fig. 2), following the Coble designation (Coble, 1996) is to the C, A, B, M and T fluorophores respectively (Table 2) e C, A and M being humic and B and T being protein fluorophores. 3.1. Spatial and seasonal changes of fluorescence The mean intensities in Raman Units (RU) of the five Components averaged regionally for the pre-monsoon and monsoon Table 1 Summary of hydrochemical parameters (Mean  SD). Constituent Transect T1 (unit) Season*/ 6 No. of stations S (%o)


T ( C) pH Chl a (mg/m3) *

pM M pM M pM M pM M

33.77 31.11 28.12 30.06 8.11 8.24 1.59 1.59

       

0.95 2.50 6.61 0.78 0.09 0.07 1.65 1.12

pM, pre-monsoon; M, monsoon.

T2

Lower estuary

Upper estuary

5

3

1

32.72 30.14 28.78 29.82 8.22 8.24 1.25 0.90

       

1.47 10.17  7.39 24.00  4.81 3.81 3.32  5.16 12.80  12.72 1.67 32.25  0.35 31.68  0.87 0.61 31.24  2.38 30.13  1.46 0.22 8.21  0.20 8.02  0.13 0.05 8.07  0.35 8.08  0.16 0.82 9.11  4.31 6.49  2.22 0.42 4.91  5.04 3.62  2.75

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171

Fig. 2. EEM spectra of Components identified by PARAFAC analysis (aee), and Excitation and Emission loadings of each component (fej).

165

166

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171

Table 2 Correspondence of the components in the present study with PARAFAC Components reported in literature. This study

Correspondence*

Component

Ex/Em (nm)

Characterization

C1 C2 C3 C4 C5

270, 365/470 <250/440 270/295 290/405 275/325

Visible Humic like UV humic like Tyrosine Protein like Marine humic like Tryptophan protein like

C3 C1 C4 C5 C5

(1), C2 (10), C4 (2) (1), C2 (9), C5 (8), C3 (11), C1 (2), C2 (6) (11), C6 (10), C8 (2), C1 (7), C5 (12) (2), C4 (5), C3 (4) (11), C5 (10), C7 (2), C5 (6), C8 (5), C5 (7), C4 (4)

* 1. Stedmon et al., 2003; 2. Stedmon and Markager, 2005a; 3. Murphy et al., 2006; 4. Luciani et al., 2008; 5. Yamashita et al., 2008; 6. Kowalczuk et al., 2009; 7. Dubnick et al., 2010; 8. Guo et al., 2010; 9. Singh et al., 2010; 10. Yamashita et al., 2011; 11. Yao et al., 2011; 12. Jørgensen et al., 2011.

seasons separately are shown in Fig. 3. During the pre-monsoon (Fig. 3a), Component 3 (tyrosine like, B) is by far the more dominant in all regions, ranging from 0.04 RU in the upper estuary to 0.09 RU in T2. In the monsoon season (Fig. 3b), Component 2 (UV humic like, A) was the more dominant in the estuary (0.096 RU in the upper estuary and 0.08 RU in the lower estuary), and closely followed by Component 3 (tyrosine like, B; 0.030 and 0.045 RU respectively). Besides, the Component 3 (tyrosine like, B) was significantly higher than Component 2 in T1 and T2. The fluorescence index (FI) was higher in the coastal water (range: 1.45e1.13) than the estuarine water (1.27e0.97). It showed a clear seasonal pattern in the estuary and T2 which is under its influence (Fig. 4a), but no significant trend in T1. The index showed a decreasing trend from the pre-monsoon season to the monsoon season. The HIX ranged from 0.24 to 9.24 in the estuary and from 0.17 to 2.7 in the coastal water, and showed opposite trend to that of FI (Fig. 4b). The seasonal mean of HIX in the estuary was w1.78 for the premonsoon season, only a half of the monsoon season’s mean of 3.65. In the coastal region, the mean was correspondingly w0.7 and 1.5. The Component 1 is negatively correlated significantly with salinity (R2 ¼ 0.70, N ¼ 108, Fig. 5a). The Component 2 is also

Fig. 3. Seasonal variation of mean intensities of components: a) Pre-monsoon, b) Monsoon (T1 ¼ Off Visakhapatnam, T2 ¼ Off Godavari estuary, LE ¼ Lower Estuary, UE ¼ Upper Estuary).

correlated negatively to salinity, but less significantly (0.57, 108, Fig. 5b). Both C1 and C2 are positively correlated to chl a (0.70, 108; 0.71, 108) during the pre-monsoon (Fig. 6a). A significant relationship during the monsoon season is for pH with C1 and C2 (Fig. 6b). Strong correlation exists between C1 and C2 for the premonsoon and monsoon seasons separately (Fig. 7). The mean seasonal ratio of Components 2 (A) and 1 (C) was 0.61  0.16 and 0.16  0.14 for the estuary and coastal region respectively during pre-monsoon, and 5.9  1.44 and 7.26  0.82 during monsoon. 4. Discussion 4.1. Components 1 and 2 Component 1 in this study corresponds to the red shifted UV humic like peak associated with visible humic like peak, noticed in the north Atlantic and Pacific Oceans in low concentration (Murphy et al., 2008) and the South Atlantic Bight in high concentration (Kowalczuk et al., 2009). Component 2 excitation maximum (lmax(ex)) lies below 250 nm. Since our minimum excitation wavelength was 250 nm, this maximum could not be captured. However, from the shape, the maximum may be lying in the 230e240 nm range. The emission peak is very broad with maxima at 440 nm and this corresponds to UV humic like peak “A” (Coble, 1996) observed in CDOM of both marine and terrestrial origin (Yamashita et al., 2008; Dubnick et al., 2010). Component 1 because of its significant inverse relationship with salinity (Fig. 5a) is a terrestrially derived component as observed in a wide range of environments, including recently in lake water (Yao et al., 2011) and sewage (Guo et al., 2010). Component 1 is a combination of two subcomponents inseparable by PARAFAC analysis, namely the UVA (350/450 nm) subcomponent (C fluorophore) and the UVC (270/450 nm) subcomponent (Coble et al., 1998; Stedmon et al., 2003) derived from terrestrial sources (A fluorophore). Component 2 is also derived from terrestrial inputs (Kowalczuk et al., 2009) (A fluorophore). The UVA subcomponent of Component 1 has a red shifted emission maximum compared to Component 2, and this phenomenon has been explained as due to the presence of larger aromatic content and of conjugation in the fluorescent compounds (Stedmon et al., 2003). These components are common in various estuarine, marine and oceanic environments (Stedmon et al., 2003; Stedmon and Markager, 2005a; Murphy et al., 2006; Luciani et al., 2008; Yamashita et al., 2008, 2011; Kowalczuk et al., 2009; Dubnick et al., 2010; Guo et al., 2010; Singh et al., 2010; Jørgensen et al., 2011; Yao et al., 2011). The designation of Component 1 as C fluorophore is based on its UVC subcomponent. Both the subcomponents of Component 1 are formed by microbial degradation of Component 2 (Cory and McKnight, 2005; Yamashita et al., 2010), since the larger A to C ratio is larger during monsoon when the bacterial activity is lower

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171

167

Fig. 4. Seasonal mean of Fluorescence Index (FI) and HIX, (a) Pre-monsoon (pM) and (b) Monsoon (M).

due to dilution. The two subcomponents of Component 1 participate in geochemical processes in the estuarine and coastal region in an identical manner that the two subcomponents have remained conservative with respect to each other in their cycling, and hence identified by PARAFAC analysis as one single component. The two subcomponents did not undergo separation during ultrafiltration likely meaning that they represent two different fluorophoric structural moieties of the same humic entities (Huguet et al., 2010 and our unpublished results), rather than two different structural formations (molecular weights). The tight correlation between Component 1 and Component 2 (Fig. 7) separately for the two seasons yields highly significant linear regression fits passing almost through origin. A uniqueness of these relationships is that they are applicable over a wide range of concentrations of the two components. This information cannot be captured by resorting to the ratio of the two components as the ratio might be of concentrations that varied in narrow limits. The A (Component 2) to C (Component 1) peak ratios have been reported to be characteristic of the drainage basin’s organic matter composition and maturing. Higher A:C ratio was observed in the nearshore than the offshore water (Coble, 1996). The ratio reported is w1.8 in the Black Sea (Coble, 1996) and the Mediterranean and North Seas (De Souza Sierra et al., 1994). A ratio of w1.6 is reported for the Amazon river water (Patel-Sorrentino et al., 2002). Similar ratio has also been reported for different stream and estuary samples (Stedmon et al., 2003). The A:C ratio is in the increasing order: pre-monsoon coastal (0.16) < pre-monsoon estuarine (0.61) < monsoon coastal (5.9) < monsoon estuarine (7.26) (Fig. 8). The means of the A:C ratio for the estuarine and coastal regions separately for the two seasons is associated with small standard

a

0.03

b

2

C1 = -0.0005*Salinity + 0.0203, R = 0.70

0.025 0.02

C1 (R.U.)

C1 (R.U.)

deviation (Fig. 8a). The ratio between Component 2 (A) and Component 1 (C) remaining constant intra-season but increasing abruptly from pre-monsoon season to the monsoon season characterizes this study. Phytoplankton degradation experiments have demonstrated that peak C is formed under conditions of bacterial decay (Determann et al., 1998; Rochelle-Newall and Fisher, 2002; Zhang et al., 2009). In the absence of bacteria too, the monospecific species excrete fluorescent compounds (C peak) during growth and decay (our unpublished results, Romera-Castillo et al., 2010). Positive correlation between chl a and FDOM (C peak) was noticed in the Baltic and Nordic Seas (Drozdowska, 2007), and a lake water (Zhang et al., 2009). The correlation of Component 1 (C peak) with chl a (Fig. 6a) agrees with these studies. A first observation of this study, to our knowledge, is the significant positive relationship between A peak (Component 2) and chl a (Fig. 6a). In an axenic culture experiment on three commonly found phytoplankton species isolates from the study area, we observed liberation of the A fluorophore in addition to the C and M fluorophores (our unpublished results). Thus, a significant part of Component 1 (C peak), and Component 2 (A peak), during pre-monsoon, are likely contributed by phytoplankton. The influence of pH on the concentration of A and C fluorophores occurs particularly during the monsoon season, as an inverse relationship (Fig. 6b). This might be inferred as due to a corresponding increase of salinity. But, since there is no (positive) relationship between salinity and pH, a direct role for pH is argued. An important effect of the increased pH is a physical loss of the CDOM in the estuary by flocculation and/or sedimentation (Sholkovitz et al., 1978; Zepp et al., 2004), as the Ca/Mg salts of

0.015 0.01 0.005 0 0

5

10

15

20

Salinity

25

30

35

0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0

2

C1 = -0.0031*Salinity + 0.1167, R = 0.57

0

5

10

15

20

Salinity

Fig. 5. Relationship with salinity of (a) Component 1 and (b) Component 2.

25

30

35

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171

a 0.016

0.014

2

C1 = 0.001*Chl a + 0.0021, R = 0.69 2

0.014

C2 = 0.0008*Chl a - 0.0003, R = 0.70

b

0.012

0.012

0.01

2

0.2

2

0.18

C1 = -0.0373*pH +0.3127, R = 0.58 C2 = -0.2089*pH +1.7584, R = 0.52

0.025

0.16 0.14

0.02

0.01

0.12

0.008

C1

0.008 C2

C1

0.03

0.015

0.1

0.006 0.006 0.004

0.004

0.002

0.002 0

2

4

6 Chl a

8

10

0.08 0.01

0.06 0.04

0.005

0.02 0

0

0

0

7.8

12

C2

168

7.9

8

8.1

8.2

8.3

8.4

pH

Fig. 6. Relation with Components 1 and 2 of (a) Chlorophyll a during Pre-monsoon season, and (b) with pH during Monsoon season.

humic acids and fulvic acids formed at higher salinities (increased pH) are insoluble (Stewart and Wetzel, 1981). 4.2. HIX and FI

0.018 0.016 0.014 0.012 0.01 0.008 0.006 0.004 0.002 0

pM M

0

2

C2 (pM) = 0.6794*C1 - 0.0015, R = 0.85 2 C2 (M) = 5.6747*C1 + 0.0062, R = 0.97

0.005

0.01

0.015

0.02

0.025

0.2 0.18 0.16 0.14 0.12 0.1 0.08 0.06 0.04 0.02 0 0.03

C1 Fig. 7. Seasonal relationship of Component 2 with Component 1.

C2 (M)

C2 (pM)

Humification index (HIX) ranged from 0.17 to 9.24. The index does not indicate a strong humification of organic matter, in the case of which the range should be higher ca., 10e16 (Zsolnay et al., 1999). For many estuarine samples, during the monsoon season, an intermediate degree of humification for which the 4e10 range applies (Zsolnay et al., 1999) is noticed. A low level of humification (HIX < 4) is associated for the coastal water. The HIX, by its strong positive correlation, during pre-monsoon with C1 (r ¼ 0.81, n ¼ 48), C2 (r ¼ 0.87, n ¼ 48) and chl a (0.68, n ¼ 45) and a negative correlation with salinity (0.78, n ¼ 30) during the pre-monsoon season support this line of argument. Corresponding correlation coefficients during monsoon season are not as strong (0.71, 0.53, 0.18, and 0.69) as the in situ humification process is masked by external inputs of DOM with different, variable levels of humification. The fluorescence index (FI, Fig. 4a) is a strong and unique descriptor of the two seasons (pre-monsoon and monsoon), and the two regions (coastal and estuarine). Higher FI in pre-monsoon may be because the humic acid (HA) component of DOM is from melanoidins formed in situ from plankton (Nissenbaum and Kaplan, 1972). The estuarine region is distinguishable (mean FI, 1.18) from the adjacent coastal region particularly during the monsoon season (T1, 1.25). Chromophores would become fluorophores when the excited state resulted from the ground energy state by radiation absorption has life times >1 ns, a condition that is achieved for conformationally rigid molecules, when due to loss of coplanarity, the absorption decreases. Hence, the condensed, i.e.,

higher molecular weight HAs and HAs of increased aromaticity (Berger et al., 1984; Alberts et al., 2002) have more fluorescence efficiency and a greater Stokes’ shift. Correspondingly, the estuarine water likely contains a greater range of FDOM structural variation from the less fluorescence efficient carbohydrates, amino acids, and carboxylic acids (Fischer et al., 2007) to the more efficient aromatic and/or heterocyclic compounds (Kiem and Kögel-Knabner, 2003). The origin of aromatic structures may be, in addition to the terrestrial source, the mangrove vegetation with which the Godavari estuary is richly endowed (Tripathy et al., 2005) that release lignin and its degradation products (Benner et al., 1990), and tannins (Maie et al., 2008) that are better transported in dissolved phase compared to terrestrial humic acids that are readily precipitated (Sholkovitz et al., 1978). 4.3. Components 3 and 5 Component 3 is similar to tyrosine protein like peak (B) with Ex/ Em of 270 nm/300 nm also noticed routinely as a major component, e.g., in a mesocosm experiment in a Norwegian fjord (Stedmon and Markager, 2005b), the North Atlantic and Pacific Oceans (Murphy et al., 2008), and in a bay in the eastern Irish Sea (Yamashita et al., 2011). Fluorescence by the tyrosine-like component has been observed as major in several coastal environments (Mayer et al., 1999; Murphy et al., 2008; Kowalczuk et al., 2009; Para et al., 2010). Tyrosine fluorescence as well as tryptophan fluorescence (Component 5; Ex/Em: 270 nm/345 nm) have traditionally been attributed to autochthonous inputs (Mopper and Schultz, 1993; Determann et al., 1996; Coble et al., 1998; Stedmon and Markager, 2005b; Yamashita et al., 2011). Tannins and lignin have also been considered to contribute significantly to the fluorescence in the region of C3 and C5 in the EEM spectra (Maie et al., 2008). Component 3 is related to Component 5, significantly during monsoon (r ¼ 0.68, N ¼ 53) when their intensities were low, and their presence should be attributed to in situ primary production, as observed for the north Atlantic and Pacific waters (Murphy et al., 2008 e C1 and C6 components). It is now believed that tyrosine owes its presence to allochthonous sources also (Stedmon and Markager, 2005b; Murphy et al., 2008). Intact proteins (DOM of higher MW) containing both tryptophan and tyrosine with folded geometry show tryptophan fluorescence only, as tyrosine fluorescence is quenched (Lakowicz, 1999; Mayer et al., 1999) due to internal resonance energy transfer. Such proteins present in freshly produced DOM of phytoplankton and less degraded peptides show only tryptophan fluorescence (Mayer et al., 1999; Stedmon and Markager, 2005b; Our unpublished results). When the DOM degrades (low MW), tyrosine residues are exposed and the two peaks of tryptophan and

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171

a

4.4. Component 4

10 8

A/C

6 4 2 0

b

pM E

ME

pM C

MC

pM E

ME

pM C

MC

4.0 3.5 3.0

M/C

2.5 2.0 1.5 1.0 0.5 0.0

c

14 12 10

A/M

169

8 6 4

Component 4 is similar to the marine humic like FDOM with Ex/ Em of 290 nm/405 nm (Coble et al., 1998; Parlanti et al., 2000), formed in situ and observed in marine (Murphy et al., 2008) and an Atlantic bay (Luciani et al., 2008). It is designated as “M” fluorophore (Coble et al., 1998), and observed as a minor component in a number of PARAFAC analyses of EEM data (e.g., Luciani et al., 2008). A strong relationship exists between Components 4 (M) and 1 (C) for the data segregated region-wise (estuarine and coastal regions) and season-wise (pre-monsoon and monsoon seasons) (Figure not given). The slopes of the linear regression equations of M against C are highly significant during monsoon (R2 ¼ 0.89, n ¼ 31 for the coastal region, and 0.79, n ¼ 25 for the estuary). During the pre-monsoon season also, a highly significant relation existed between M and C in the coastal region (0.80, n ¼ 31). High concentrations of M fluorophore have been observed for high saline water (S > 36.5) of a coastal embayment and in water of the nearby coastal region with which it mixed (Milbrandt et al., 2010). As the presence of M is noticed even at low salinities in the Study area, alternative mechanism of the enrichment of M are explored. Although termed originally as “marine” humic peak, the M fluorophore’s origin, recently, is also attributed to terrestrial source (Murphy et al., 2008), likely by bacterial action, as in the case of C and B fluorophores. The M/C ratio has been used as an indicator of new to old CDOM in the Mediterranean surface waters with a mean value of w2 (Para et al., 2010). From the mean M/C values shown in Fig. 8b, the relative extent to which M is formed from DOM containing C fluorophore appears to be: Pre-monsoon coastal (M/C, 2.1) > Monsoon coastal (1.3) > Pre-monsoon estuary (0.9) > Monsoon estuary (0.6). A further observation in this study is the significant relationship between Component 2 (A fluorophore) and Component 4 (M fluorophore) during monsoon season for the coastal region (R2 ¼ 0.94, n ¼ 31) and the estuary (0.79, n ¼ 24). The mean A/M ratio is higher during monsoon (estuary, 9.4; coastal, 5.9) than pre-monsoon (0.6, 0.1 respectively; Fig. 8c). The important implication is that the M fluorophore is also formed from A containing DOM, in the same way it is formed from C containing DOM so that the monsoon water is carrying M along with the A fluorophore. 5. Conclusion

2 0 pM E

ME

pM C

MC

Fig. 8. Seasonal mean ratios: (a) A/C (Component 2/Component 1), (b) M/C (Component 4/Component 1), and (c) A/M (Component 2/Component 4) (pME, Pre-monsoon Estuary; ME, Monsoon Estuary; pMC, Pre-monsoon Coastal; MC: Monsoon Coastal).

tyrosine appear separately (Yamashita and Tanoue, 2003), the latter with higher intensity due to its much higher concentration. Our results suggest that degraded (protein containing) DOM dominates throughout but more particularly during pre-monsoon in the study area. During monsoon season, in situ formation of DOM is low and microbial activity reduced due to dilution particularly in the estuary. A similar conclusion has been made for the formation of C from A fluorophore (see above). In the Godavari estuary, low levels of DOC are reported (0.2e1 mg L1) compared to the global average (w5 mg L1) even during peak terrestrial discharge period, attributed to heterotrophy (Sarma et al., 2009). Despite this, the effect of river discharge can be seen in T2 over T1 in the form of a greater tyrosine like fluorescence because of the volume of Godavari discharge (105 km3 yr1) involved.

The Bay of Bengal is a dilution basin exhibiting significant seasonality. The coupled investigation of hydrochemical and hydroptical properties of the Midwestern Bay of Bengal during two successive seasons is first of its kind for the tropical Indian Ocean. The study encompassing regions of three different environmental niches e an estuary, the coastal region affected by inputs through it, and a coastal region that is free from this input, has shown that the optical properties are unique for the area. The fluorescence index (FI) and humification index (HIX) both exhibit distinct seasonal and spatial variation. The dissolved fluorescence excitation emission matrix spectra have the power, via PARAFAC modelling to distinguish the monsoon from the pre-monsoon water and the estuarine region from the coastal region, and within the coastal region the region under the influence of the river from the region that is not under its influence. The protein fraction of DOM belongs to the degraded type. The humic fluorophores, via their ratios have diagnostic value. The A:C ratio, seasonally constant, but much higher during the monsoon season indicates that the ecosystem changes from one of bacteria-replete during the pre-monsoon to one of bacteria-free ecosystem during the monsoon season. The M:C ratio and A:M ratio reveal that the “marine” humic M

170

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171

fluorophore is not only of marine origin but should also be sourced to terrestrial humic matter by bacterial decay, although the extent to which M is formed under terrestrial conditions is low. Acknowledgements This work is an outcome of the vision of Dr. Shailesh Nayak, Secretary, MoES and advice by Dr. T. Srinivasa Kumar and Dr. A. A. Lotlikar, Indian National Centre for Ocean Information Services (INCOIS). Authors thank Director, INCOIS for financial assistance (INCOIS/093/2007) and are grateful to CSIR for further financial assistance (NSS: Emeritus Scientist; NVHKC: Senior Research Fellow). The authors highly appreciate the anonymous reviewers for their critical comments and suggestions for improvement of the manuscript. This paper is dedicated to Professor A. Satyanarayana, Principal Investigator of CDOM (INCOIS) project for support. References Alberts, J.J., Takács, M., Egeberg, P.K., 2002. Total luminescence spectral characteristics of natural organic matter (NOM) size fractions as defined by ultrafiltration and high performance size exclusion chromatography (HPSEC). Organic Geochemistry 33, 817e828. Andersen, C.M., Bro, R., 2003. Practical aspects of PARAFAC modelling of fluorescence excitation emission data. Journal of Chemometrics 17, 200e215. Benner, R., 2002. Chemical composition and reactivity. In: Hansell, D.A., Carlson, C.A. (Eds.), Biogeochemistry of Marine Dissolved Organic Matter. Academic Press. Benner, R., Weliky, K., Hedges, J.I., 1990. Early diagenesis of mangrove leaves in a tropical estuary: molecular-level analyses of neutral sugars and lignin-derived phenols. Geochimica et Cosmochimica Acta 54, 1991e2001. Berger, P., Ewald, M., Liu, D., Weber, J.H., 1984. Application of the fluorescence quenching titration method to the complexation of copper (II) in the Gironde Estuary (France). Marine Chemistry 14, 289e295. Boehme, A.B., Shellenberger, G.G., Paytan, A., 2004. Groundwater discharge: potential association with fecal indicator bacteria in the surf zone. Environmental Science and Technology 38, 3558e3566. Breves, W., Heuermann, R., Reuter, R., 2003b. Enhanced red fluorescence emission in the oxygen minimum zone of the Arabian Sea. Ocean Dynamics 53, 86e97. Breves, W., Reuter, R., 2001. Bio-optical properties of gelbstoff in the Arabian Sea at the onset of the southwest monsoon. Earth and Planetary Science, Proceedings of Indian Academy of Sciences, 1e15. Breves, W., Reuter, R., Delling, N., Michaelis, W., 2003a. Fluorophores in the Arabian Sea and their relationship to hydrographic conditions. Ocean Dynamics 53, 73e85. Bro, R., 1997. PARAFAC: tutorial and applications. Chemometrics and Intelligent Laboratory Systems 38, 149e171. Central Pollution Control Board (CPCB), 1995. Basin Sub-basin Inventory of Water Pollution Godavari Basin. CPCB, New Delhi. Coble, P.G., 1996. Characterization of marine and terrestrial DOM in seawater using excitation-emission matrix spectroscopy. Marine Chemistry 51, 325e346. Coble, P.G., 2007. Marine optical biogeochemistry e the chemistry of ocean color. Chemical Reviews 107, 402e418. Coble, P.G., Del Castillo, C.E., Avril, B., 1998. Distribution and optical properties of CDOM in the Arabian Sea during the 1995 southwest monsoon. Deep-Sea Research Part II 45, 2195e2223. Coble, P.G., Green, S., Blough, N.V., Gagosian, R.B., 1990. Characterization of dissolved organic matter in the Black sea by fluorescence spectroscopy. Nature 348, 432e435. Conmy, R.N., Coble, P.G., Chen, R.F., Gardner, G.B., 2004. Optical properties of colored dissolved organic matter in the Northern Gulf of Mexico. Marine Chemistry 89, 127e144. Cory, R.M., McKnight, D.M., 2005. Fluorescence spectroscopy reveals ubiquitous presence of oxidized and reduced quinones in dissolved organic matter. Environmental Science and Technology 39, 8142e8149. De Souza Sierra, M.M., Donard, O.F.X., Lamotte, M., Belin, C., Ewald, M., 1994. Fluorescence spectroscopy of coastal and marine waters. Marine Chemistry 47, 127e144. Determann, S., Lobbes, J.M., Reuter, R., Rullkötter, J., 1998. Ultraviolet fluorescence excitation and emission spectroscopy of marine algae and bacteria. Marine Chemistry 62, 137e156. Determann, S., Reuter, R., Willkomm, R., 1996. Fluorescent matter in the eastern Atlantic Ocean. Part 2: vertical profiles and relation to water masses. Deep Sea Research Part I 43, 345e360. Drozdowska, V., 2007. Seasonal and spatial variability of surface seawater fluorescence properties in the Baltic and Nordic Seas: results of lidar experiments. Oceanologia 49, 59e69. Dubnick, A., Barker, J., Sharp, M., Wadham, J., Lis, G., Telling, J., Fitzsimons, S., Jackson, M., 2010. Characterization of dissolved organic matter (DOM) from

glacial environments using total fluorescence spectroscopy and parallel factor analysis. Annals of Glaciology 51, 111e122. Fischer, H., Meyer, A., Fischer, K., Kuzyakov, Y., 2007. Carbohydrate and amino acid composition of dissolved organic matter leached from soil. Soil Biology and Biochemistry 39, 2926e2935. Gaillard, J., Dupré, B., Louvat, P., Allegre, C., 1999. Global silicate weathering and CO2 consumption rates deduced from the chemistry of large rivers. Chemical Geology 159, 3e30. Grasshoff, K., Ehrhardt, M., Kremling, K. (Eds.), 1999. Methods of Seawater Analysis, third ed. Verlag Chemie, Weinheim (pub), 603 pp. Guéguen, C., Guo, L., Yamamoto-Kawai, M., Tanaka, N., 2007. Colored dissolved organic matter dynamics across the shelf/basin interfaces in the western Arctic Ocean. Journal of Geophysical Research 112, C05038. Guo, W., Stedmon, C.A., Han, Y., Wu, F., Yu, X., Hu, M., 2007. The conservative and non-conservative behavior of chromophoric dissolved organic matter in Chinese estuarine waters. Marine Chemistry 107, 357e366. Guo, W., Xu, J., Wang, J., Wen, Y., Zhuo, J., Yan, Y., 2010. Characterization of dissolved organic matter in urban sewage using excitation emission matrix fluorescence spectroscopy and parallel factor analysis. Journal of Environmental Science 22, 1728e1734. Huguet, A., Vacher, L., Saubusse, S., Etcheber, H., Abril, G., Relexans, S., Ibalot, F., Parlanti, E., 2010. New insights into the size distribution of fluorescent dissolved organic matter in estuarine waters. Organic Geochemistry 41, 595e610. Jeffrey, S.W., Humphrey, G.F., 1975. New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochemie und Physiologie der Pflanzen 167, 1e194. Jørgensen, L., Stedmon, C.A., Kragh, T., Markager, S., Middelboe, M., Søndergaardv, M., 2011. Global trends in the fluorescence characteristics and distribution of marine dissolved organic matter. Marine Chemistry 126, 139e148. Kalle, K., 1938. Zum problem der meereswasserfarbe. Annalen der Hydrographie und Maritimen Meteorologie 66, 1e13. Kiem, R., Kögel-Knabner, I., 2003. Contribution of lignin and polysaccharides to the refractory carbon pool in C-depleted arable soils. Soil Biology and Biochemistry 35, 101e118. Kowalczuk, P., Durako, M.J., Young, H., Kahn, A.E., Cooper, W.J., Gonsior, M., 2009. Characterization of dissolved organic matter fluorescence in the South Atlantic Bight with use of PARAFAC model: inter-annual variability. Marine Chemistry 113, 182e196. Kowalczuk, P., Zablocka, M., Sagan, S., Kulinski, K., 2010. Fluorescence measured in situ as a proxy of CDOM absorption and DOC concentration in the Baltic Sea. Oceanologia 52, 431e471. Lakowicz, J.R., 1999. Principles of Fluorescence Spectroscopy. Kluwer/Plenum, New York. Luciani, X., Mounier, S., Paraquetti, H.H.M., Redon, R., Lucas, Y., Bois, A., Lacerda, L.D., Raynaud, M., Ripert, M., 2008. Tracing of dissolved organic matter from the SEPETIBA Bay (Brazil) by PARAFAC analysis of total luminescence matrices. Marine Environmental Research 65, 148e157. Ludwig, W., Probst, J.L., Kemp, S., 1996. Predicting the oceanic input of organic carbon by continental erosion. Global Biogeochemical Cycles 10, 23e41. Maie, N., Boyer, J.N., Yang, C., Jaffe, R., 2006. Spatial, geomorphological, and seasonal variability of CDOM in estuaries of the Florida Coastal Everglades. Hydrobiologia 569, 135e150. Maie, N., Pisani, O., Jaffé, R., 2008. Mangrove tannins in aquatic ecosystems: their fate and possible influence on dissolved organic carbon and nitrogen cycling. Limnology and Oceanography 53, 160e171. Mayer, L.M., Schick, L.L., Loder III, T.C., 1999. Dissolved protein fluorescence in two Maine estuaries. Marine Chemistry 64, 171e179. McKnight, B.E.W., Westerhoff, P.K., Doran, P.T., Andersen, D.T., 2001. Spectrofluorometric characterization of dissolved organic matter for indication of precursor organic material and aromaticity. Limnology and Oceanography 46, 38e48. Milbrandt, E.C., Coble, P.G., Conmy, R.N., Martignette, A.J., Siwicke, J.J., 2010. Evidence for the production of marine fluorescent dissolved organic matter in coastal environments and a possible mechanism for formation and dispersion. Limnology and Oceanography 55, 2037e2051. Mopper, K., Schultz, C.A., 1993. Fluorescence as a possible tool for studying the nature and water column distribution of DOC components. Marine Chemistry 41, 229e238. Moran, M.A., Sheldon Jr., W.M., Zepp, R.G., 2000. Carbon loss and optical property changes during long-term photochemical and biological degradation of estuarine dissolved organic matter. Limnology and Oceanography 45, 1254e1264. Murphy, K.R., Ruiz, G.M., Dunsmuir, W.T.M., Waite, T.D., 2006. Optimized parameters for fluorescence-based verification of Ballast water exchange by ships. Environmental Science and Technology 40, 2357e2362. Murphy, K.R., Butler, K., Spencer, R.M., Stedmon, C.A., Boehme, J., Aiken, G.R., 2010. Measurement of dissolved organic matter fluorescence in aquatic environments: an interlaboratory comparison. Environmental Science and Technology 44, 9405e9412. Murphy, K.R., Stedmon, C.A., Waite, T.D., Ruiz, G.M., 2008. Distinguishing between terrestrial and autochthonous organic matter sources in marine environments using fluorescence spectroscopy. Marine Chemistry 108, 40e58. Nelson, N.B., Siegel, D.A., Carlson, C.A., Swan, C., 2010. Tracing global biogeochemical cycles and meridional overturning circulation using chromophoric dissolved organic matter. Geophysical Research Letters 37, L03610. doi:10.1029/ 2009GL042325.

N.V.H.K. Chari et al. / Estuarine, Coastal and Shelf Science 100 (2012) 162e171 Nissenbaum, A., Kaplan, I., 1972. Chemical and isotopic evidence for the in situ origin of marine humic substances. Limnology and Oceanography 17, 570e582. Ohno, T., Bro, R., 2006. Dissolved organic matter characterization using multiway spectral decomposition of fluorescence landscapes. Soil Science Society of America Journal 70, 2028. Para, J., Coble, P.G., Charriere, B., Tedetti, M., Fontana, C., Sempere, R., 2010. Fluorescence and absorption properties of chromophoric dissolved organic matter (CDOM) in coastal surface waters of the northwestern Mediterranean Sea, influence of the Rhône River. Biogeosciences 7, 4083e4103. Parlanti, E., Wörz, K., Geoffroy, L., Lamotte, M., 2000. Dissolved organic matter fluorescence spectroscopy as a tool to estimate biological activity in a coastal zone submitted to anthropogenic inputs. Organic Geochemistry 31, 1765e1781. Patel-Sorrentino, N., Mounier, S., Benaim, J.Y., 2002. Excitationeemission fluorescence matrix to study pH influence on organic matter fluorescence in the Amazon basin rivers. Water Research 36, 2571e2581. Rao, K.L., 1975. India’s Water Wealth: Its Assessment, Uses and Projections. Orient Longman, New Delhi, p. 29. Reddy, B., Ranga Rao, R., 1993. Flushing and dispersion characteristics of Godavari estuary under different river discharge conditions. Indian Journal of Marine Sciences 22, 111e114. Repeta, D.J., Quan, T.M., Aluwihare, L.I., Accardi, A.M., 2002. Chemical characterization of high molecular weight dissolved organic matter in fresh and marine waters. Geochimica et Cosmochimica Acta 66, 955e962. Rochelle-Newall, E.J., Fisher, T.R., 2002. Production of chromophoric dissolved organic matter fluorescence in marine and estuarine environments: an investigation into the role of phytoplankton. Marine Chemistry 77, 7e21. Romera-Castillo, C., Sarmento, H., Alvarez-Salgado, X.A., Gasol, J.M., Marrase, C., 2010. Production of chromophoric dissolved organic matter by marine phytoplankton. Limnology and Oceanography 55, 446e454. Sarma, V.V.S.S., Gupta, S.N.M., Babu, P.V.R., Acharya, T., Harikrishnachari, N., Vishnuvardhan, K., Rao, N.S., Reddy, N.P.C., Sarma, V.V., Sadhuram, Y., Murty, T.V.R., Kumar, M.D., 2009. Influence of river discharge on plankton metabolic rates in the tropical monsoon driven Godavari estuary, India. Estuarine, Coastal and Shelf Science 85, 515e524. Sholkovitz, E.R., Boyle, E.R., Price, N.B., 1978. Removal of dissolved humic acid and iron during estuarine mixing. Earth and Planetary Science Letters 40, 130e136. Singh, S., D’Sa, E.J., Swenson, E.M., 2010. Chromophoric dissolved organic matter (CDOM) variability in Barataria Basin using excitationeemission matrix (EEM) fluorescence and parallel factor analysis (PARAFAC). Science of the Total Environment 408, 3211e3222. Stedmon, C.A., Bro, R., 2008. Characterizing dissolved organic matter fluorescence with parallel factor analysis: a tutorial. Limnology and Oceanography: Methods 6, 1e6.

171

Stedmon, C.A., Markager, S., Bro, R., 2003. Tracing dissolved organic matter in aquatic environments using a new approach to fluorescence spectroscopy. Marine Chemistry 82, 239e254. Stedmon, C.A., Markager, S., 2005a. Resolving the variability in dissolved organic matter fluorescence in a temperate estuary and its catchment using PARAFAC analysis. Limnology and Oceanography 50, 686e697. Stedmon, C.A., Markager, S., 2005b. Tracing the production and degradation of autochthonous fractions of dissolved organic matter by fluorescence analysis. Limnology and Oceanography 50, 1415e1426. Stewart, A.J., Wetzel, R.G., 1981. Asymmetrical relationships between absorbance, fluorescence and dissolved organic carbon. Limnology and Oceanography 26, 590e597. Subramanian, V., 1993. Sediment load of Indian rivers. Current Science 64, 928e930. Tripathy, S., Ray, A., Patra, S., Sarma, V.V., 2005. Water quality assessment of GautamidGodavari mangrove estuarine ecosystem of Andhra Pradesh, India during September 2001. Journal of Earth System Science 114, 185e190. UNESCO, 1979. Discharge of Selected Rivers of the World. Paris. Yamashita, Y., Cory, R.M., Nishioka, J., Kuma, K., Tanoue, E., Jaffé, R., 2010. Fluorescence characteristics of dissolved organic matter in the deep waters of the Okhotsk Sea and the northwestern North Pacific Ocean. Deep-Sea Research Part II 57, 1478e1485. Yamashita, Y., Jaffé, R., Maie, N., Tanoue, E., 2008. Assessing the dynamics of dissolved organic matter (DOM) in coastal environments by excitation emission matrix fluorescence and parallel factor analysis (EEM-PARAFAC). Limnology and Oceanography 53, 1900e1908. Yamashita, Y., Panton, A., Mahaffey, C., Jaffé, R., 2011. Assessing the spatial and temporal variability of dissolved organic matter in Liverpool Bay using excitationeemission matrix fluorescence and parallel factor analysis. Ocean Dynamics 61, 569e579. Yamashita, Y., Tanoue, E., 2003. Chemical characterization of protein-like fluorophores in DOM in relation to aromatic amino acids. Marine Chemistry 82, 255e271. Yao, X., Zhang, Y., Zhu, G., Qin, B., Feng, L., Cai, L., Gao, G., 2011. Resolving the variability of CDOM fluorescence to differentiate the sources and fate of DOM in Lake Taihu and its tributaries. Chemosphere 82, 145e155. Zepp, R.G., Sheldon, W.M., Moran, M.A., 2004. Dissolved organic fluorophores in southeastern US coastal waters: correction method for eliminating Rayleigh and Raman scattering peaks in excitationeemission matrices. Marine Chemistry 89, 15e36. Zhang, Y.L., Van Dijk, M.A., Liu, M.L., Zhu, G.W., Qin, B.Q., 2009. The contribution of phytoplankton degradation to chromophoric dissolved organic matter (CDOM) in eutrophic shallow lakes: field and experimental evidence. Water Research 43, 4685e4697. Zsolnay, A., Baigar, E., Jimenez, M., Steinweg, B., Saccomandi, F., 1999. Differentiating with fluorescence spectroscopy the sources of dissolved organic matter in soils subjected to drying. Chemosphere 38, 45e50.