Spatial and seasonal changes of arsenic species in Lake Taihu in relation to eutrophication

Spatial and seasonal changes of arsenic species in Lake Taihu in relation to eutrophication

Science of the Total Environment 563–564 (2016) 496–505 Contents lists available at ScienceDirect Science of the Total Environment journal homepage:...

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Science of the Total Environment 563–564 (2016) 496–505

Contents lists available at ScienceDirect

Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Spatial and seasonal changes of arsenic species in Lake Taihu in relation to eutrophication Changzhou Yan a,⁎,1, Feifei Che a,b,1, Liqing Zeng a,b, Zaosheng Wang a, Miaomiao Du a, Qunshan Wei c, Zhenhong Wang d, Dapeng Wang a,b, Zhuo Zhen a a

Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China Graduate University of Chinese Academy of Sciences, Beijing 100049, China College of Environmental Science & Engineering, Donghua University, Songjiang District, Shanghai 201620, China d College of Chemistry and Environment, Minnan Normal University, Zhangzhou 363000, China b c

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• All As species exhibited higher levels in eutrophic waters during warm seasons. • Eutrophic environment facilitated biogeochemical cycling of As in freshwater. • Conversion of As speciation was derived by biological activity and abiotic factors.

a r t i c l e

i n f o

Article history: Received 9 January 2016 Received in revised form 18 April 2016 Accepted 18 April 2016 Available online xxxx Editor: F.M. Tack Keywords: Speciation Algal blooms Transformation Water quality parameters Redundancy analysis

⁎ Corresponding author. E-mail address: [email protected] (C. Yan). 1 These authors are co-first authors on this work.

http://dx.doi.org/10.1016/j.scitotenv.2016.04.132 0048-9697/© 2016 Elsevier B.V. All rights reserved.

a b s t r a c t Spatial and seasonal variations of arsenic species in Lake Taihu (including Zhushan Bay, Meiliang Bay, Gonghu Bay, and Southern Taihu) were investigated. Relatively high levels of total arsenic (TAs) and arsenate (As(V)) were observed in hyper-eutrophic regions during summer and autumn, which is attributed to exogenous contamination and seasonal endogenous release from sediments. The distributions of TAs and As(V) were significantly affected by total phosphorus, iron, manganese, and dissolved organic carbon. Arsenite (As(III)) and methylarsenicals (the sum of monomethylarsenic acid (MMA(V)) and dimethylarsenic acid (DMA(V))), mainly from biotransformation of As(V), were affected by temperature-controlled microalgae activities and local water quality parameters, exhibiting significantly higher concentrations and proportions in hyper-eutrophic and middle eutrophic regions during summer compared to mesotrophic region. The eutrophic environment, which induces changes in the main water quality parameters such as phosphorus, chlorophyll-a, iron, manganese, and dissolved organic carbon, can favor the biogeochemical cycling of arsenic in the aquatic systems. © 2016 Elsevier B.V. All rights reserved.

C. Yan et al. / Science of the Total Environment 563–564 (2016) 496–505

1. Introduction The widespread occurrence of arsenic (As) in the aquatic environment, especially in freshwater, has attracted extensive concern, because of its potential environmental risk to human health. Arsenic in aquatic systems mainly includes inorganic As and organoarsenicals. Inorganic As is generally more toxic and prevalent than organoarsenicals (Smedley and Kinniburgh, 2002). Arsenate (As(V)) is the most stable state in oxic waters, while arsenite (As(III)) dominates in a reducing environment (Cullen and Reimer, 1989). By contrast, methylarsenicals (mostly including monomethylarsenic acid (MMA(V)) and dimethylarsenic acid (DMA(V))) are generally considered to be of lower toxicities and occur in lower levels in aquatic ecosystems (Akter et al., 2005). In view of the different toxicities of As species to the biota, it is essential to understand the cycling of As species and the controlling factors in the aquatic environment in order to further evaluate the potential environmental risk to human health. The transport and transformation of As in the aquatic environment is governed by local geochemical and biological processes (Cullen and Reimer, 1989; Hasegawa et al., 1999). As is well known, eutrophication caused by over-utilization of nutrients can accelerate the growth of phytoplankton and enhance bacterial activities in water column (Hasegawa et al., 2009), and influence the water quality and the cycling of many elements. However, until now, little has been studied regarding the influence of eutrophication on the biogeochemical cycle of As species in aquatic environment. Eutrophication may play an important role in the transport and transformation of As in aquatic environment. Firstly, eutrophication can stimulate the excessive growth of microalgae (Hasegawa et al., 2009), which may accumulate a large amount of arsenic in the aquatic environment, as a result of its large capacity to bind trace metals (Radway et al., 2001). When microalgae move with the water flow or settle to the sediment, the distribution of As can change accordingly in the aquatic environment. More importantly, microalgae can tolerate high levels of inorganic As, and biotransform and detoxify it to organoarsenicals (Pawlik-Skowronska et al., 2004; Z.H. Wang et al., 2013; Yin et al., 2012). Furthermore, algal blooms can alter the pH and redox potential, and affect the concentrations of dissolved organic carbon and Fe/Mn compounds (Eggleton and Thomas, 2004). These changes strongly influence the chemical forms of As in the aquatic environment. Although the distribution characteristics of As species in lake waters in relation to eutrophication has been discussed in previous studies (dos Anjos et al., 2012; Hasegawa et al., 2010), it was difficult to illustrate the influence of eutrophication on As speciation because of its complexity and limited literature data. Therefore, the effect of eutrophication on the biogeochemical cycling of As in aquatic systems is still an issue deserving further study. Lake Taihu, located in the Yangtze River Delta, is the second largest shallow freshwater lake in China. It is an important resource for drinking water, shipping, freshwater aquaculture, and farming. As a result of more than one hundred inflow and outflow rivers around Lake Taihu, which received a large amount of industrial effluent, agricultural wastewater, and municipal sewage, the lake has been heavily contaminated and changed into an eutrophic and metal polluted water body (Qu et al., 2001; Zeng et al., 2012). About 61.2% and 70.7% of the annual input of total nitrogen and total phosphorus were derived from the northwest region of the catchment (Yuan et al., 2011), which resulted in a eutrophic and partially hyper-eutrophic water body in Lake Taihu. Large masses of algae (algal blooms) repeatedly appeared in northwest of Lake Taihu since the end of the 1980s, turning the eutrophication into an important concern (Chen et al., 2003; James et al., 2009; Qin et al., 2007; Xu et al., 2010). After a long period of eutrophication control, the water quality of the lake improved partially in recent years, leading to the occurrence of different trophic status in Lake Taihu. Additionally, anthropogenic inputs have been reported to largely increase As contamination in aquatic ecosystems (Morin and Calas, 2006; Ren et al., 2010;

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Smedley and Kinniburgh, 2002). Because of increasing anthropogenic activities in surrounding areas and the impact of polluted inlet water mostly from west and north regions, As contamination in Lake Taihu, especially in the northwest parts, has gradually become another serious environmental issue (Jiang et al., 2012; Qu et al., 2001). Considering the coexistence of eutrophication and As contamination in Lake Taihu, it provides us a good opportunity to study the relationship between eutrophication and the distribution of As species. In this paper, we chose Zhushan Bay, Meiliang Bay, Gonghu Bay and Southern Taihu as representative regions with different trophic status, and reported the spatial and seasonal distributions of different As species in the water of Lake Taihu to better understand the effect of eutrophication on the distribution of As in the lake and to reveal its controlling factors. 2. Materials and methods 2.1. Sampling sites Three sampling sites in each lake region, including Zhushan Bay, Meiliang Bay, Gonghu bay and Southern Taihu, were chosen as shown in Fig. 1. According to previous studies (Sun et al., 2013; Y.C. Wang et al., 2013; Ye et al., 2012; Yuan et al., 2011), Zhushan Bay and Meiliang Bay are thought as hyper-eutrophic waters; Gonghu Bay and Southern Taihu are classified as middle eutrophic and mesotrophic waters, respectively. 2.2. Sample collection and pretreatment Surface water samples from 12 field sites were collected in triplicate during 18–19 September 2013, 22–23 July 2014, and 14–16 January and 7–8 May 2015 in selected four regions of Lake Taihu, representing autumn, summer, winter, and spring, respectively. Water samples were collected within 20 cm of the water surface. For As analysis, 100 mL of the samples was filtered through 0.45 μm cellulose acetate membrane, acidified to pH 3–4 with HNO3, and stored in a refrigerator at −20 °C until measurement; iron (Fe) and manganese (Mn) were also obtained for the filtered water samples. For the analysis of dissolved organic carbon (DOC), another 100 mL of filtered samples was acidified to pH 2 with H2SO4, stored at 4 °C, and measured within a week. For the analysis of total nitrogen (TN) and total phosphorus (TP), 500 mL of the samples was collected and stored at 4 °C, and measured within 24 h. Surface sediment samples were collected at each site in autumn, summer, and winter, respectively, for analysis of total arsenic (TAs) in sediments. Samples collected in spring were chosen for analysis of As fractions in sediments. The samples were then freeze-dried and ground to pass through 200-mesh nylon sieve for the determination of TAs and As fractions in sediments. The standard stock solutions for the measurement of As speciation (As(III), As(V), MMA(V) and DMA(V)) were prepared with NaAsO2 (Alfa Aesar), Na3AsO4·12H2O (Fluka), NaCH4AsO3 (Fluka) and NaC2H6AsO2 (Sigma), respectively. The mobile phase for As speciation analysis was prepared by 10 mM NH4H2PO4 (HPLC, CNW Technologies GmbH) and 10 mM NH4NO3 (guaranteed grade), and was adjusted to pH 6.2 by ultrapure nitric acid or ammonia. Other reagents used during the pretreatment and determination were of analytical reagent or better grade. 2.3. Arsenic measurement and quality control Total As in surface water was detected by inductively coupled plasma mass spectrometry (ICP-MS, Agilent 7500cx) operating in the helium gas mode. Arsenic species (As(III), As(V), MMA(V) and DMA(V)) were measured by HPLC–ICP-MS (Agilent LC1100 series and Agilent ICP-MS 7500cx; Agilent Technologies) through anionexchange column as described (Zhu et al., 2008). Chromatographic

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Fig. 1. Water samples were collected from the four regions of Lake Taihu. Z, M, G, and S represented Zhushan Bay, Meiliang Bay, Gonghu Bay and South Lake Taihu, respectively. A, B, and C represented sampling site in each region.

columns purchased from Hamilton consisted of a pre-column (11.2 mm, 12–20 μm) and a PRP-X100 10 μm anion exchange column (250 × 4.1 mm). Arsenic species in samples were separated using the mobile phase and flowed isocratically through the column at 1.0 mL/ min by a peristaltic pump. Sediment samples were digested following the slightly modified method described by Jiang et al. (2012) for TAs analysis. A sequential As fractionation procedure based on modified methods (Keon et al., 2001; Seddique et al., 2008) was employed to determine the following As fractions: (F1) ionically bound As (extracted with 1 M MgCl2); (F2) strongly adsorbed As (extracted with 1 M NaH2PO4 + 0.1 M ascorbic acid); (F3) As coprecipitated with sulfides, carbonates, Mn oxides, and very amorphous Fe oxyhydroxides (extracted with 1 N HCl); (F4) As coprecipitated with amorphous Fe oxyhydroxides (extracted with 0.2 M ammonium oxalate/oxalic acid); (F5) As coprecipitated with crystalline Fe oxyhydroxides (extracted with 0.05 M Ti(III)–citrate– EDTA–bicarbonate); (F6) organo-As compounds (extracted with 0.1 M Na pyrophosphate); and (F7) insoluble form (extracted with HNO3/ HClO4). Concentrations of TAs and As fractions were also measured by ICP-MS. Quality control was carried out by internal standards, blanks, duplicates, and reference material. 72Ge and 103Rh were chosen as internal standards for signal stability. A standard for As species was analyzed every 15 samples to ensure analytical accuracy. The detection limits were 0.01, 0.20, 0.07, 0.12, and 0.07 μg/L for TAs, As(V), As(III), MMA(V), and DMA(V), respectively (three times the standard deviation of the blank measurement). The precision (relative standard deviation) estimated from replicate standards ranged from 2.4% to 4.5% for methylarsenicals, and were less than 4.7% for inorganic As and TAs. The accuracy of TAs in sediments was controlled by the use of certified reference material GSD-9. The recovery of TAs was within 93–100%. The recovery of As fractionation ((fractions sum / TAs) × 100%) was within 85–110%. 2.4. Measurement of water quality parameters Water quality parameters including water temperature (WT), pH, dissolved oxygen (DO), chlorophyll-a (Chl-a), and total dissolved solids (TDS) were monitored by multiple water quality analyzer (YSI 6600v2) in situ. Total nitrogen was determined after digestion with alkaline potassium persulfate, followed by UV spectrophotometric analysis

(Thermo Evolution 300). Total phosphorus was determined by ammonium molybdate spectrophotometric method. Iron and manganese were determined by ICP-MS. Dissolved organic carbon was measured by total organic carbon analyzer (TOC-Vcph). 2.5. Statistical analysis Variance analysis (ANOVA) with post-hoc multiple comparisons (Duncan's test) was performed to compare As speciation and water quality parameters among different regions as well as different seasons. Pearson's correlation coefficient was calculated to reveal the relationship between As speciation and various water quality parameters. Both of the statistical analyses were computed using SPSS 19.0 software (Y.C. Wang et al., 2013). Redundancy analysis (RDA) was used to correlate the distribution of As speciation and various environmental factors in the sampling sites using Canoco for Windows 4.5 software (Ter Braak and Šmilauer, 2002). All of the variables were firstly normalized through log (X + 1) transformation for RDA. A significant level of p b 0.05 was accepted for all statistical analyses. 3. Results 3.1. Physical and chemical characteristics of the water in Lake Taihu The distributions of the main water quality parameters in the four lake regions are shown in Table 1. According to the monitoring results, the concentrations of TN, TP, Chl-a, DOC, and TDS exhibited a consistent order as follows: Southern Taihu b Gonghu Bay b Meiliang Bay and Zhushan Bay, reflecting significant spatial differences and the relationship between the water quality and eutrophic status. As shown in Table 1, the seasonal variations of water quality parameters were evident. The contents of TN exhibited the highest average concentration of 3.41 mg/L in spring and the lowest average concentration of 2.00 mg/L in summer. Frequent application of fertilizers with relatively low freshwater inflow led to increasing TN in spring. By contrast, decreased TN in summer was attributed to increased activity of denitrification and phytoplankton uptake during the alga bloom period. Average TP concentrations varied between 0.09 mg/L and 0.15 mg/L, with peaks in autumn. Besides, there was no obvious fluctuation for average TP concentration in summer, winter, and spring. The highest average value of TP in autumn was due to agricultural pollution

1.81c 0.08c 3.4c 3.35c 0.30d 8.2a 9.24 21.76 101.0 30.3b 3.01 0.09 2.9 2.30 0.26 8.3 9.04 21.94 82.9 41.7 1.37 0.09 2.7 3.35 0.32 7.6 11.46 6.51 35.8 26.0 1.00 0.09 5.2 3.60 0.39 8.3 8.39 27.10 254.0 36.9 1.85 0.04 2.9 4.14 0.24 8.5 8.08 31.48 225.0 16.7 2.39 0.09c 5.5bc 3.37c 0.32c 8.0b 9.30 20.98 125.0 24.7b 5.84 0.17 8.5 5.35 0.53 6.9 13.72 6.67 71.1 35.3 6.74 0.18 8.5 5.56 0.37 8.2 7.41 26.47 223.0 71.0 TN (mg/L) TP (mg/L) Chl-a (μg/L) DOC (mg/L) TDS (g/L) pH DO (mg/L) WT (°C) Fe (μg/L) Mn (μg/L)

3.2. Arsenic distribution in surface water of Lake Taihu Different superscripts indicate significant differences in the parameters among the four regions (p b 0.05) according to two-way ANOVA.

2.93 0.09 3.6 2.44 0.31 7.2 12.42 6.54 41.9 18.7 2.02 0.13 7.8 3.22 0.26 8.8 8.05 26.15 293.0 48.4 2.60 0.12b 8.0ab 4.18b 0.36b 8.2a 9.59 21.52 180.0 31.6b

1.29 0.05 4.9 4.93 0.37 8.5 7.37 30.40 289.0 18.8

3.33 0.07 5.9 2.87 0.36 7.4 9.37 20.84 94.8 13.0

Spring Winter Autumn

3.29 0.17 10.3 6.57 0.32 8.5 10.26 32.61 328.0 37.1

3.91 0.17 2.5 4.42 0.41 8.1 6.87 22.57 118.0 36.2

4.94 0.17a 7.5a 5.48a 0.40a 7.9b 9.57 22.08 185.0 44.9a

1.60 0.09 11.8 4.77 0.35 8.8 7.45 31.04 307.0 23.6

3.13 0.22 6.6 4.16 0.37 8.7 8.06 26.58 267.0 71.3

2.28 0.07 8.0 4.49 0.35 7.4 13.55 6.50 47.7 16.4

3.40 0.09 5.3 3.30 0.36 7.9 9.30 21.95 99.5 15.1

b a

Southern Taihu

Summer Average Spring Winter Autumn

Gonghu Bay

Summer Average Spring Winter Autumn

Meiliang Bay

Summer Average Spring Winter Autumn Summer

Zhushan Bay Parameters

Table 1 Distribution of the main water quality parameters in the four regions of Lake Taihu.

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and sediment release. Relatively lower TP concentration in summer (especially in Gonghu Bay and Southern Taihu) might be a consequence of phytoplankton uptake during the alga bloom period and rainfall dilution. The average concentration of Chl-a appeared a peak value in summer as well as the lowest value in spring, indicating seasonal algal blooms in Lake Taihu, especially in Zhushan Bay and Meiliang Bay. The concentrations of DOC showed a similar seasonal variation compared to Chl-a, and were detected a maximum average in summer of 5.10 mg/L. The pH appeared the maximum values in summer because of the algal blooms and the minimum values in winter. Differently, the average value of DO ranged from 8.0 mg/L in autumn to 12.8 mg/L in winter, reflecting an inverse seasonal pattern. The consumption of DO in warm seasons can be due to water temperature and the decomposition of massive phytoplankton debris. Water temperature appeared the highest values in summer and the lowest values in winter. The greatest average concentrations of Fe and Mn were detected in summer and autumn, respectively. The distributions of physical and chemical characteristics of surface water showed spatial and seasonal variations as there are many different internal and external contamination sources in Lake Taihu. During the warm seasons, the average concentrations of TP, TN, Chl-a and DOC in Zhushan Bay and Meiliang Bay were obviously higher than those in Gonghu Bay and Southern Taihu. These variations suggested that the eutrophication in Zhushan Bay and Meiliang Bay was more developed than that in Gonghu Bay and Southern Taihu.

b

Average

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Table 2 shows the significant differences in the concentrations of TAs and As speciation among the four lake regions with different eutrophic status. Total As in the water of Lake Taihu ranged from 0.92 μg/L to 6.75 μg/L, exhibiting the obvious variability of As concentrations in Lake Taihu. The concentrations of TAs in Zhushan Bay and Meiliang Bay were significantly higher (p b 0.05) than those in Gonghu Bay and Southern Taihu, corresponding to hyper-eutrophic level in Zhushan Bay and Meiliang Bay. Arsenate was the dominant speciation in Lake Taihu, ranging from 0.52 μg/L in Southern Taihu to 4.78 μg/L in Meiliang Bay. Furthermore, the distribution of As(V) in the four regions was similar to TAs distribution with the greater values of As(V) in Zhushan Bay and Meiliang Bay. Arsenite was the minor inorganic speciation and accounted for 3–36% of TAs in the lake water. Statistical analysis indicated that the level of As(III) in the north parts of the lake (including Zhushan Bay, Meiliang Bay, and Gonghu Bay) was significantly higher (p b 0.05) than that in Southern Taihu (Table 2). The lowest content of As(III) in Southern Taihu was consistent with its mesotrophic level. Methylarsenicals (sum of MMA and DMA) were detected at lower concentrations compared to inorganic arsenic, only accounting for 4–20% of TAs in the four regions. Additionally, the content of DMA(V) was much higher than that of MMA(V), since DMA(V) is more stable than MMA(V). The content of methylarsenicals followed the order: Meiliang Bay N Zhushan Bay N Gonghu Bay N Southern Taihu. Especially, the average concentration of methylarsenicals in Meiliang Bay reached the greatest value (0.30 μg/L), which might be due to hyper-eutrophic status and cyanobacteria domination in this region. 3.3. Seasonal variation of As distribution in surface water of Lake Taihu Obvious seasonal changes in As distribution among the four regions are shown in Figs. 2 and 3. The concentration of TAs in summer and autumn was significantly higher (p b 0.05) than that in winter and spring. Especially, the concentration of TAs in Meiliang Bay showed a wide variability during the four seasons (from 6.75 μg/L in autumn to 1.60 μg/L in spring). Aberrant As in autumn can be due to the effect of strong hydraulic turbulence affected by wind in Meiliang Bay during

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Table 2 Range and average of As in the four regions of Lake Taihu. Arsenic

TAs (μg/L) As(V) (μg/L) As(III) (μg/L) MMA (μg/L) DMA (μg/L)

Zhushan Bay

Meiliang Bay

Gonghu Bay

Southern Taihu

Range

Average

Range

Average

Range

Average

Range

Average

1.96–5.06 0.89–3.83 0.09–0.84 N.D.–0.20 0.14–0.25

3.11a 2.16a 0.34a 0.06 0.18b

1.60–6.75 0.50–4.78 0.10–0.85 N.D.–0.23 0.12–0.46

3.29a 2.03a 0.39a 0.03 0.27a

1.31–3.19 0.58–2.27 0.07–1.23 N.D.–0.14 N.D.–0.29

2.18b 1.25b 0.38a 0.01 0.17b

0.92–2.56 0.52–1.93 0.07–0.56 N.D.–0.16 N.D.–0.18

1.60c 0.97b 0.21b 0.01 0.10c

Different superscripts indicate significant differences of the parameters among the four regions (p b 0.05) according to two-way ANOVA. N.D. “not detected” because the value was below the detection limit.

sampling period. The wind-wave disturbance promoted As release from sediments. Similar to seasonal changes of TAs concentration, there was significantly greater concentration (p b 0.05) of As(V) in summer and autumn than that in winter and spring, except for As(V) concentration in Gonghu Bay with the maximum value occurring in winter. Arsenite concentration in Lake Taihu reached the highest level in summer, particularly with the maximum value (1.14 μg/L) in Gonghu Bay. In winter, As(III) concentration maintained a relatively high level in Zhushan Bay and Meiliang Bay, while it showed little fluctuation among the four regions in spring and autumn. The average concentration of methylarsenicals in summer also demonstrated a significantly greater value (p b 0.05) compared to the other three seasons, exhibiting obvious seasonal difference of methylarsenicals in Lake Taihu. In Gonghu Bay and Southern Taihu, the concentration of methylarsenicals in the four seasons increased in the following order: winter b spring b autumn b summer. In Zhushan Bay and Meiliang Bay, however, the content of methylarsenicals in winter still maintained a relatively high level. It should be noted that seasonal regularities of As variation in Lake Taihu might not be clearly evident due to the limitation of only one sampling per season in this study. 3.4. Total arsenic and As fractions in sediments from Lake Taihu As seen from Table 3, concentration of TAs in surface sediments displayed large spatial variation in spite of little seasonal changes. The average concentration of TAs in sediments from the four regions followed the order: Zhushan Bay (15.98 μg/g) N Southern Taihu (14.34 μg/g) N Meiliang Bay (11.77 μg/g) N Gonghu Bay (8.44 μg/g). Notably, the distribution of TAs in sediments was different from TAs distribution in surface water of Lake Taihu. However, although average TAs concentration was higher in sediments from Southern Taihu than

Fig. 2. Concentrations of TAs in surface water collected from Zhushan Bay, Meiliang Bay, Gonghu Bay, and Southern Taihu during summer, autumn, winter and spring. Mean and standard deviation of three sampling sites in each region are shown.

that from Meiliang Bay and Gonghu Bay, the potential mobility of As in sediments from Southern Taihu was relatively lower. According to Fig. 4, the percentage of easily available As in sediments from Southern Taihu (including F1, F2, F3, and F4) was about 40%, obviously lower than that from northern regions (47–58%). Moreover, insoluble proportion of As (F7) in sediments from Southern Taihu (39%) was also significantly higher compared to that from northern regions (18–30%). Arsenic release from the sediments was closely associated with As fractionation in sediments, to a great extent resulting in significant As distribution in surface water of Lake Taihu. 3.5. The relationship between As distribution and the main water quality parameters in Lake Taihu Eutrophication is a phenomenon accompanied with the changes of water quality. In order to reveal the controlling factors which influence the distribution of arsenic in Lake Taihu, the relationships between the main water quality parameters and As concentrations were analyzed by calculating Pearson's correlation coefficient (Table 4). The results indicated that TAs and As(V) were positively correlated with TP, pH, WT, DOC, Fe, and Mn. At the same time, TAs was negatively correlated with DO concentrations. Arsenite and methylarsenicals showed positive correlations with DOC and Fe. Notably, methylarsenicals showed positive correlations with Chl-a, reflecting the role of phytoplankton on As methylation. RDA is necessary to further analyze the influences of the controlling factors on As distribution. In the RDA with As species and the main water quality parameters, the first and second axes contributed 55.3% and 11.0% of the total variation, respectively. Among the main water quality parameters, TP (F = 18.791, p = 0.001), Fe (F = 18.009, p = 0.001), DOC (F = 7.241, p = 0.002), Chl-a (F = 3.926, p = 0.032), and Mn (F = 3.604, p = 0.040) were selected as significant environmental factors by Monte Carlo permutation to explain As distribution, accounting for 94.3% of the amount of explanation of total explanatory variables (water quality parameters) (Fig. 5). Sampling sites from the four lake regions during four seasons were clustered in different quadrants according to different eutrophic status, reflecting clear spatial and temporal distribution. In the first and fourth quadrants, water samples from hyper-eutrophic Zhushan Bay and Meiliang Bay contained a large amount of As during summer and autumn. By contrast, the sampling sites during winter and spring, especially from Gonghu Bay and Southern Taihu, were always clustered in the second and third quadrants and composed of a minor proportion of As. The distributions of TAs and As(V) were significantly affected by TP, Fe, Mn, and DOC, according to the positive correlation among them (Fig. 5). Arsenite and methylarsenicals were significantly positively correlated by Chl-a, DOC and Fe, and thus generally occurred in hypereutrophic regions during summer. The conversion of As species as well as their relationship with the main water quality parameters measured in this study (including TN, TP, Chl-a, DOC, TDS, pH, DO, WT, Fe, and Mn) was also analyzed. The stepwise regression analysis was used to determine significant environmental factors which affected the conversion of As(V) to As(III) and

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Fig. 3. Concentrations of As(V), As(III), and methylarsenicals (sum of MMA and DMA) in surface water collected from Zhushan Bay, Meiliang Bay, Gonghu Bay, and Southern Taihu during summer, autumn, winter and spring. Mean and standard deviation of three sampling sites in each region are shown.

methylarsenicals. Based on the regression models in Table 5, the conversion of As(V) to As(III) was negatively correlated with TP while it was positively correlated with DOC. Additionally, TP also exhibited negative correlation with the conversion of As(V) to methylarsenicals, while Chl-a exhibited significantly positive correlation with the conversion process. The relationships between As(III) or methylarsenicals/ As(V) and the above water quality parameters were consistent with the results shown in Figs. 6 and 7. 4. Discussion The concentration range of TAs observed in our results is consistent with the finding (1.39–5.65 μg/L) by Zhang et al. (2013), usually dominated by As(V) in Lake Taihu. Furthermore, the concentrations of TAs and As(V) were significantly higher in the water of hyper-eutrophic regions than in middle eutrophic and mesotrophic regions, especially during summer and autumn. These spatial and seasonal variations in Lake Taihu, similar to the reports by Wei et al. (2011) (especially the As distribution in autumn 2009 and spring 2010) and Yang et al. (2015), suggested that the distributions of TAs and As(V) were influenced by exogenous pollution and endogenous release (Qu et al., 2001; Wei et al., 2011). The inflow rivers, which received a large amount of wastewater from the surrounding areas, are normally located around the west and north parts of Lake Taihu (including Liangxi River, Taige River, Wangyu River, etc.) (Paerl et al., 2011; Yuan et al., 2011); the wastewater inputs caused a relatively high level of As contamination in the north parts of the lake. However, the rivers with large

outflow water fluxes such as Changdou River are mostly located around the south parts of Lake Taihu, and the wastewater discharge has been controlled (Sun et al., 2013), leading to little impact on the external inputs of As in Southern Taihu. Similarly, the high levels of TP also occurred in the northwestern parts of Lake Taihu, suggesting probably the same exogenous inputs with As. In addition to external inputs, internal As release from sediments was an important factor driving the seasonal variations of TAs and As(V) in Lake Taihu, which has also been reported by Yang et al. (2015), according to the findings by Zeng et al. (2012) that river input cannot be regarded as a main reason for seasonal changes of heavy metal concentrations in Lake Taihu. Based on As distribution in surface sediments observed in our results (Table 3), average TAs concentration was higher in Zhushan Bay, similar to the findings by Jiang et al. (2012). More importantly, proportion of readily available As was higher in sediments from the north parts of Lake Taihu compared to that from Southern Taihu (Fig. 4), resulting in relatively higher As release from the sediments to overlying water in northern regions, especially under the effects of biological and physical disturbances. During warm seasons in eutrophic environment, vigorous microbial activities lowered the redox potential and DO at the sediment–water interface, which consequently triggered As release from the sediments accompanying the reductive dissolution of Fe/Mn oxides under reducing condition; while during winter, As was re-adsorbed to Fe/Mn oxides and settled to the bottom (Hasegawa et al., 2009). The process can be observed with a significant positive correlation between TAs, As(V), Fe, and Mn (Table 4, Fig. 5), in accordance with the results reported by

Table 3 Water depth and TAs concentration in surface sediments at each sampling site in Lake Taihu. Sampling site

Zhushan Bay

Meiliang Bay

Gonghu Bay

Southern Taihu

Water depth (m)

Z-A Z-B Z-C M-A M-B M-C G-A G-B G-C S-A S-B S-C

TAs concentrations in surface sediments (μg/g)

Range

Average

Summer

Autumn

Spring

1.88–2.30 2.18–2.63 2.28–2.77 2.40–2.96 2.61–2.90 2.44–2.98 2.00–2.54 2.10–2.65 2.30–2.86 1.22–2.02 1.87–2.65 1.89–2.72

2.11 2.36 2.52 2.69 2.74 2.68 2.29 2.37 2.53 1.59 2.22 2.28

18.40 ± 0.34 10.18 ± 0.58 10.27 ± 0.31 9.81 ± 0.45 13.01 ± 0.40 15.99 ± 0.08 8.08 ± 0.63 9.95 ± 0.93 9.34 ± 0.43 17.00 ± 0.94 11.82 ± 0.33 12.83 ± 0.22

18.10 ± 0.94 17.82 ± 0.26 13.60 ± 0.43 7.34 ± 0.42 9.93 ± 0.59 13.90 ± 0.71 7.85 ± 0.32 7.23 ± 0.21 7.56 ± 0.32 14.99 ± 0.39 14.79 ± 0.16 15.50 ± 0.58

22.28 ± 0.84 – 17.21 ± 0.45 – 12.53 ± 0.50 11.66 ± 0.50 9.73 ± 0.45 – 7.90 ± 0.33 14.28 ± 0.52 – 13.53 ± 0.56

Concentrations of TAs are expressed as mean ± standard deviation (n = 3). – Sample missing.

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Fig. 4. Proportions of As fractions in surface sediments collected from Zhushan Bay, Meiliang Bay, Gonghu Bay, and Southern Taihu in spring.

previous studies (Baeyens et al., 2007; Sohrin et al., 1997). Moreover, upgraded pH observed during photosynthetically vigorous summer algal blooms, caused by eutrophication, can obviously induce As release from the sediments (Dzombak and Morel, 1990). Its mediation on As release is similar to the effects on phosphorus release reported in previous studies (Jin et al., 2006; Xu et al., 2010), because of the physicochemical 3− similarities between phosphate (PO3− 4 ) and As(V) (AsO4 ) (Cullen and Reimer, 1989). High levels of phosphate and organic matter will also enhance As release from sediments as a result of competition for adsorption sites (Gan et al., 2014; Smedley and Kinniburgh, 2002). The positive relationships of TAs and As(V) with TP and DOC in the present study further confirm the idea (Table 4). Additionally, some other physical conditions, such as strong hydraulic turbulence affected by wind, would also promote As release from sediment (Wei et al., 2011), possibly leading to the aberrant As in Meiliang Bay in autumn. Arsenite comprised about 4–26%, 5–36%, and 3–22% of TAs in hypereutrophic, middle eutrophic, and mesotrophic regions of Lake Taihu, respectively, with highest levels of As(III) concentrations observed in summer. It can be hypothesized that increased As(III) was mainly linked to eutrophication-mediated reduction of As(V) to As(III), in agreement with the reports that local biological and geochemical processes can significantly mediate the conversion between As(V) and As(III) in freshwater (Smedley and Kinniburgh, 2002). Many studies have shown that increasing microbial biomass in the eutrophic environment effectively reduces As(V) into As(III) and releases it into the water (dos Anjos et al., 2012; Ren et al., 2010). In our results, harmful algal bloom (Chl-a) showed a strong positive influence on As(III) occurrence

Fig. 5. RDA ordination showing the distribution of TAs and As speciation (As(V), As(III), and methylarsenicals) in relation to the main water quality parameters. The solid arrows represent As species. The dashed arrows represent significant environmental factors. * represent the significant water quality parameters (p b 0.05). Circle, triangle, square, and diamond represent the sampling sites in Zhushan Bay, Meiliang Bay, Gonghu Bay, and South Taihu, respectively. Light gray, white, black and dark gray represent the four sampling seasons — summer, autumn, winter, and spring, respectively.

(Fig. 5), with its proportion being higher in eutrophic regions (the north parts of the lake). Moreover, our investigation exhibited that the contents of As(III) during summer were lower in Zhushan Bay and Meiliang Bay, compared to that in Gonghu Bay. It might be due to stronger transformation of inorganic As to methylarsenicals and more complex organoarsenic compounds by organisms (such as trimethylarsine, trimethylarsine oxide, arsenobetaine, arsenocholine and arsenosugars) in hyper-eutrophic regions (Hasegawa et al., 2010), leading to relatively lower levels of As(III) in Zhushan Bay and Meiliang Bay. In Southern Taihu, however, the average minimum value of As(III) was in response to lower microalgal density (average Chl-a concentration at 3.4 μg/L). Water temperature plays an important role in seasonal changes of As(III) in aquatic systems, because of its regulation on microbial activities (Jiang et al., 2008). In our results, the average content of As(III) was elevated up to 23% of TAs in summer, reflecting strong effect of temperature-controlled microbial reduction on As(III) proportion. Furthermore, it corresponded to relatively lower average level of TP in summer. The results suggested that the microbial reduction of As(V) to As(III) was significantly enhanced in low phosphate condition (Fig. 6(A)), similar to a laboratory study by Zhang et al. (2014). As(V) was rapidly taken up by microalgae via phosphate transporter and reduced to As(III), with consequent increasing mobility of As(III) in water. Besides, as a thermodynamically unstable speciation in oxic

Table 4 Correlation analysis between As species concentrations and the main water quality parameters. Correlation

TP

TN

Chl-a

pH

DO

TDS

WT

DOC

Fe

Mn

TAs As(V) As(III) Methylarsenicals

0.599⁎⁎ 0.650⁎⁎ −0.234 0.256

0.147 0.204 −0.192 −0.010

0.253 0.136 0.287 0.516⁎⁎

0.481⁎⁎ 0.384⁎⁎ 0.197 0.269

−0.316⁎ −0.242 −0.076 −0.215

0.105 0.027 0.213 0.210

0.484⁎⁎ 0.381⁎⁎ 0.294⁎ 0.266

0.517⁎⁎ 0.383⁎⁎ 0.524⁎⁎ 0.476⁎⁎

0.621⁎⁎ 0.514⁎⁎ 0.372⁎⁎ 0.287⁎

0.458⁎⁎ 0.461⁎⁎ −0.208 0.190

Methylarsenicals: sum of MMA and DMA. ⁎ p b 0.05. ⁎⁎ p b 0.01.

C. Yan et al. / Science of the Total Environment 563–564 (2016) 496–505 Table 5 Linear regression models explaining the conversion of As speciation. Dependent variable

Linear model

R2 values

F values

As(III)/As(V)

0.047 − 3.461⁎⁎⁎TP +

0.44

17.520

0.25

7.312

0.150⁎⁎⁎DOC Methylarsenicals/As(V) 0.180⁎⁎⁎ − 0.962⁎⁎TP + 0.016⁎⁎Chl-a

The models result from a forward stepwise selection procedure and explain the conversion of As(V) to As(III) and methylarsenicals by the three water quality parameters: TP, Chl-a, and DOC.

water, As(III) increased in summer was possibly associated with decreased DO contents during decomposing of algal blooms (Fig. 5), which may benefit to As(III) presence (Baeyens et al., 2007; Hasegawa et al., 2010). In addition, As(III) concentration varied presumably due to anthropogenic input and its internal release from the sediments. Compared to it in Southern Taihu, appreciable As(III) in the north parts of the lake might be partly due to more intensive inflow rivers with industrial effluent around the northwest of Lake Taihu (Qin et al., 2007). Distinct correlation of As(III) with DOC, consistent with previous studies (Chowdhury et al., 2012; Grafe et al., 2001), also suggested the competitive effect of DOC on adsorption sites to facilitate As(III) release from the sediments. Besides, relatively high concentrations of As(III) in Zhushan Bay and Meiliang Bay during winter might be attributed to re-suspended solids related to wave forcing (during sampling period) and consequent release of non-trapped As(III) into the water. Relatively high TDS values in the two regions during winter provide indirect evidence in support of this hypothesis. In this investigation, methylarsenicals ranged from 6 to 20% of TAs for hyper-eutrophic regions, 5–12% for middle eutrophic region, and 5–9% for mesotrophic region, with its significant increase during summer. Similarly, the highly elevated average concentration of Chl-a also occurred in summer in hyper-eutrophic regions, which indicated higher primary production in hyper-eutrophic environment during summer. The positive correlation of Chl-a with methylarsenicals and methylarsenicals/As(V) observed in Lake Taihu (Table 4, Fig. 7(B)) indicated that the biological-mediated conversion of inorganic As to methylarsenicals is intensified in eutrophic regions. Previous studies also confirmed that microalgae play an essential role in As methylation (Maki et al., 2009; Sanders, 1980). As is well known, the high nutrient loading in northwest parts of Lake Taihu as well as the impacts of southeast monsoon during summer resulted in heavy blooms occurring annually in Zhushan Bay and Meiliang Bay (Paerl et al., 2011; Wu et al., 2015). A substantial amount of cyanobacteria accumulated inorganic As and strongly transformed it into methylarsenicals and even more

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complex organoarsenic compounds, being responsible for higher concentrations and proportions of organoarsenic in hyper-eutrophic regions during summer. A similar finding in Paranaguá Estuarine Complex (Southern Brazil) was also reported by dos Anjos et al. (2012). Furthermore, the seasonal changes of methylarsenicals are related to the ability of microalgae on As biomethylation, which depend on various water quality parameters including phosphorus concentration, water temperature, light intensity, etc. (Karadjova et al., 2008). Similar to the impact on the conversion between inorganic As, there was more frequent As methylation under low phosphate condition (Fig. 6(B)). Improved As(V) uptake by microalgae under low phosphate condition accelerated As methylation, and resulted in the significantly elevated concentrations of methylarsenicals in summer, which is in agreement with previous studies (Hellweger et al., 2003; Yan et al., 2014). Especially, the increasing trend of methylarsenicals in summer was obvious in Gonghu Bay and Southern Taihu. However, there were no significant differences (p N 0.05) in methylarsenical distribution among the four seasons in hyper-eutrophic regions. In addition to further biotransformation of methylarsenical to more complex organoarsenic compounds in warm seasons (Hasegawa et al., 2010), it might also be attributed to the degradation of methylarsenicals in relatively high water temperature (Maki et al., 2009). The results confirmed that the temperature is also responsible for the seasonal variations of methylarsenical concentration in aquatic systems (Howard et al., 1995). Besides, the positive correlation between methylarsenicals and DOC was observed in this investigation, similar to the relationship between methylmercury and DOC reported in previous studies (Hall et al., 2008; MacMillan et al., 2015), suggesting the promotion of DOC on metal mobility and bioavailability. In particular, it should be pointed out that only one sampling per season caused the occurrence of aberrant As concentrations. It might be due to the impact of accidental events (for example, wind-wave, rainfall, etc.) during the sampling period. More sampling during each season can exhibit more regular seasonal variations of As and provide more data to interpret the correlations between seasonal changes of As and eutrophication. 5. Conclusion In this study, spatial and seasonal characteristics of As species in the water of Lake Taihu and the effect of main water quality parameters on As distribution have been analyzed. The concentrations of TAs and As(V) were stimulated by higher contents of TP, Fe, and Mn, and showed higher levels in hyper-eutrophic regions during warm seasons. A substantial amount of microalgae exhibited larger capacity to accumulate As(V) and contributed to transform it to As(III) and methylarsenicals in eutrophic environment when compared to

Fig. 6. Correlation between TP and the ratio of As(III)/As(V) (A) or methylarsenicals/As(V) (B) (n = 48).

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Fig. 7. Correlation between DOC (A) or Chl-a (B) and the ratio of As(III)/As(V) or methylarsenicals/As(V) (n = 48).

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