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A toxicity monitoring study on identification and reduction of toxicants from a wastewater treatment plant
ARTICLE IN PRESS Ecotoxicology and Environmental Safety 72 (2009) 1919–1924
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Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv
A toxicity monitoring study on identification and reduction of toxicants from a wastewater treatment plant Xianliang Yi a, Eunhee Kim b, Hun-Je Jo a, Daniel Schlenk c, Jinho Jung a, a
Division of Environmental Science & Ecological Engineering, Korea University, Anam-dong, Sungbuk-gu, Seoul 136-713, Republic of Korea Department of Oceanography, Chonnam National University, Gwangju 500-757, Republic of Korea c Department of Environmental Sciences, University of California, Riverside, CA 92521, USA b
a r t i c l e in fo
abstract
Article history: Received 16 December 2008 Received in revised form 10 April 2009 Accepted 13 April 2009 Available online 12 May 2009
In this study, toxicity of effluents in a wastewater treatment plant and of receiving water in an adjacent stream was periodically monitored from November 2007 to June 2008, in order to trace and reduce sources of toxicants. The results showed that toxicity of final effluent (FE) changed greatly over different sampling events, and appeared to have impacts on toxicity of downstream water with a significant correlation (r2 ¼ 0.87, po0.05). In particular, FE toxicity was always higher than that of secondary effluent (SE). Toxicity identification evaluation (TIE) for the FE sample collected in March 2008 showed that FE toxicity was attributed to low quality of Fenton reagent with Zn contamination used for SE treatment. Furthermore, Zn concentrations in FE samples significantly correlated with FE toxicity during the sampling period (r2 ¼ 0.95, po0.05). After changing the Fenton reagent to one containing low Zn, Zn concentration and toxicity of FE greatly decreased in the following months. & 2009 Elsevier Inc. All rights reserved.
Keywords: Bioassay Daphnia magna Effluent Receiving water Wastewater treatment Zinc
1. Introduction Whole effluent toxicity (WET) tests, as a part of water quality monitoring programs, have been applied to regulate discharges in the United States over a decade (USEPA, 2000). Compared to chemical analysis alone, the WET programs have advantages in that it assesses biological effects of chemicals in wastewaters. In 2007, the Korean Ministry of Environment (MOE) announced that a new standard protocol and legislation using Daphnia magna acute toxicity tests would be gradually implemented from 2011 to regulate wastewater effluent (Korean MOE, 2007). For discharging effluents from wastewater treatment plants (WWTPs), the new legislation states that the toxic unit (TU) of 24 h should be less than 1. Whole effluent toxicity at different sampling occasions can be greatly variable because effluents are a mixture of various chemicals (Aguayo et al., 2000; Tarkpea et al., 1998; Mitteregger et al., 2007). However, the new criteria state no specific guidelines of adequate sampling numbers. As suggested by Kim et al. (2008), a single sampling occasion may not be sufficient due to toxicity variability. Additionally, the discharge of effluents can have negative effects on community and population structure of the receiving waterbody (Kosmala et al., 1999; Nedeau et al., 2003;
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E-mail address: [email protected] (J. Jung). 0147-6513/$ - see front matter & 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.ecoenv.2009.04.012
Ntengwe and Maseka, 2006). Thus, for a better assessment of effluent toxicity, toxicity variability in both wastewater effluent and its receiving water should be considered over a long-term period. Wastewater effluents often contain a large number of chemicals and not all of them are responsible for the observed toxicity. Thus, toxicity identification evaluation (TIE) has been developed by USEPA (USEPA, 1991, 1993a, b) and widely used to identify and reduce major toxicants in industrial effluents (Erten-Unal et al., 1998; Jin et al., 1999; Yu et al., 2004; Jo et al., 2008; Park et al., 2008). Given the above, this paper aimed at: (1) monitoring toxicity in samples collected from a WWTP and the adjacent stream on a regular basis to assess impacts of wastewater effluent on its receiving waterbody; and (2) identifying toxicity causing substances in the effluent to reduce its toxic effects.
2. Materials and methods 2.1. Sample collection Monthly sampling was conducted from a WWTP (YJ-WWTP), located in Yangju, Kyunggi do, Republic of Korea, and the adjacent stream (S-stream) from November 2007 to June 2008. The YJ-WWTP daily treats about 23,000 m3 wastewater, which originates from textile and dyeing facilities, and is directly discharged into the S-stream. Fig. 1 shows a flow diagram of the wastewater treatment process in YJ-WWTP. Samples were collected after four different processes, namely, raw wastewater (RW), primary effluent (PE), secondary effluent
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(SE) and final effluent (FE), as well as two points of the adjacent stream water, upstream (US) and downstream (DS), about 50 m distant from the discharge point of FE, respectively. Samples were transported in polyethylene containers on ice to the lab and immediately stored at 4 1C throughout the whole study period. Initial toxicity tests and water quality analysis were conducted upon the arrival of the samples. 2.2. Chemical analyses Samples were filtered using a 0.45 mm syringe filter and analyzed for DOC (dissolved organic carbon) using a Shimadzu TOC analyzer, model 5000A (Kyoto, Japan). Hardness and TSS (total suspended solids) were measured according to the Standard Methods for the Examination of Water and Wastewater (APHA, 1998). Total residual chlorine (TRC) was measured using a residual chlorine electrode (model 97-70, Thermo Electron Inc., USA). Ammonia concentration was measured using an ammonia electrode (model 95-12, Thermo Electron Inc., USA). Metal concentrations were analyzed using a Varian inductively coupled plasma-optical emission spectrophotometer (ICP-OES, Varian Vista PRO, CA, USA). For metal analysis, all the vessels and experimental apparatus were rigorously acid-cleaned before use. Standard solutions were freshly prepared and standard calibration curves with r240.995 were achieved daily. A known concentration of a standard was analyzed every 12 samples to ensure data quality and the recovery ranged 94–107%. Detection limits were calculated based on blank standard deviations 3 and ranged from 4 to 14 mg L1. 2.3. Toxicity test For toxicity tests, D. magna (neonates less than 24 h old) were obtained from cultures at the Korea Research Institute of Chemical Technology. Acute toxicity tests were carried out according to the Organization for Economic Co-operation and Development (OECD) standard procedure (OECD, 2004). In each toxicity test, five or more dilutions of a sample and one control with four replicates were prepared, with 10 mL test solution and five individuals placed in each vessel. Toxicity tests were conducted at 2072 1C with a 16 h light:8 h dark photoperiod for 48 h. Immobilization results of the test species were used to calculate the EC50 (50% effective concentration) values by a graphical method, Probit analysis or the Trimmed Spearman-Karber Method (USEPA, 2002). For comparison, EC50 values were transformed into toxic units (TU ¼ 100/EC50).
2.4. Toxicity identification evaluation Toxicity identification evaluation was conducted for the FE collected in March 2008 according to TIE procedures developed by the USEPA (USEPA, 1991, 1993a, b). In TIE phase I test (USEPA, 1991), baseline test, pH adjustment, pH adjustment/ aeration, pH adjustment/filtration, pH adjustment/C18 solid phase extraction (SPE), graduated pH, EDTA addition and sodium thiosulfate (STS) addition were included to characterize classes of toxicants. In particular, EDTA chelation tests were carried out at different concentrations ranging from 70 to 141.4 mg L1. Similarly, STS reduction tests were also conducted at concentration ranges of 9.48–355 mg L1. Additionally, ion exchange manipulations were conducted to further characterize toxicants (Jo et al., 2008). Cation and anion exchange columns were prepared with 60 mL syringes filled with either cation (Amberlite IR-120, sodium form, Aldrich, USA) or anion (Amberlite IRA-410, chloride form, Aldrich, USA) exchange resins. For mixed ion exchange (cation and anion), samples went through both ion exchange columns sequentially. Except for graduated pH tests, pH of the samples after each manipulation was readjusted to initial pH with NaOH and HCl before toxicity test. In TIE phase II test (USEPA, 1993a), metals suspected as key toxic materials were measured using a Varian ICP-OES (Varian Vista PRO, CA, USA). For metal analyses, aliquot samples were saved and preserved with concentrated nitric acid. From the results of identification, suspect toxicants were confirmed by mass balance and spiking approaches of TIE phase III test (USEPA, 1993b). In the mass balance approach, the same concentration of a suspect toxicant found in the filtered sample was added to samples after manipulations, which showed a toxicity reduction (e.g., ion exchange or pH adjustment to 11). Then, toxicity tests were conducted before and after the addition of the suspect toxicant. For the spiking approach, the same concentration of the suspect toxicant was added to the filtered sample. Then, toxicity tests were performed to check if toxicity increased linearly with the addition of the suspect toxicant.
3. Results 3.1. Toxicity monitoring The results of toxicity and chemical analyses of YJ-WWTP effluents and the adjacent S-stream water are presented in Table 1. The average TUs decreased in order of RW, PE and SE (5.8, 1.6 and 0.3, respectively) while TU for FE increased to 10.1 TU. In addition, the average toxicity of DS (3.6 TU) was lower than that of FEs (10.1 TU), but higher than the average of USs toxicity (0.3 TU). Fig. 2 shows changes in toxicity of effluents and adjacent stream waters over different sampling events. Overall, toxicity of FE showed variable change and was much higher than that of SEs and even RWs until April 2008. In contrast to changes in US toxicity, DS toxicity over the overall sampling events mirrored that of FE, indicating that effluent from the YJ-WWTP may have an impact on toxicity at DS of the S-stream. Additionally, a significant correlation between toxicity in FE and DS was found (r2 ¼ 0.87, po0.05). This further supported that toxicity in DS was affected by the input of FE. 3.2. Toxicity identification
Fig. 1. Wastewater treatment processes and sampling points in YJ-WWTP and the adjacent S-stream. RW: raw wastewater; PE: primary effluent; SE: secondary effluent; FE: final effluent; US: upstream water; DS: downstream water.
TIE procedures were conducted for FE collected in March 2008. TIE phase I results were illustrated in Fig. 3a. There was little
Table 1 Toxicity and chemical characteristics of YJ-WWTP effluents and S-stream water.
pH DO (mg L1) TRC (mg L1) Ammonia (as NH3, mg L1) Hardness (as CaCO3, mg L1) DOC (mg L1) TSS (mg L1) TU (48 h)
RW
PE
SE
FE
US
DS
8.6470.70 0.6570.30 o0.2 24.08718.49 120787 228.64748.98 429.627361.45 5.872.5
8.4270.37 0.8770.54 o0.2 23.30716.96 2167100 158.14737.18 165.02775.80 1.671.2
7.6070.10 7.0270.52 o0.2 2.1672.82 2767168 31.6373.52 24.4177.78 0.370.6
6.9470.24 8.1470.77 o0.2 3.0872.77 3887315 19.7776.83 11.17710.00 10.175.0
7.4570.33 7.5571.84 o0.2 26.96715.77 236756 11.6373.15 32.03714.66 0.370.8
7.3670.15 8.2771.13 o0.2 19.2877.87 3347200 14.1074.85 20.97710.80 3.672.2
RW: raw wastewater; PE: primary effluent; SE: secondary effluent; FE: final effluent; US: upstream water; DS: downstream water; DO: dissolved oxygen; TRC: total residual chlorine; DOV: dissolved organic carbon; TSS: total suspended solid; TU: toxic unit (TU ¼ 100/EC50).Data were collected monthly from November 2007 to April 2008, and the results are expressed a s the mean value7standard deviation .
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18.0 16.0
RW
1921
after changing
PE
Fenton reagent
SE FE
14.0
US DS
Toxicity (TU)
12.0 10.0 8.0 6.0 4.0 2.0 0.0 Dec.07
Nov.07
Jan.08
Feb.08 Mar.08 Time
Apri.08
May.08
June.08
Fig. 2. Toxicity monitoring of YJ-WWTP effluents and S-stream waters. Error bars represent 95% confidential intervals. RW: raw wastewater; PE: primary effluent; SE: secondary effluent; FE: final effluent, US: upstream water; DS: downstream water. The vertical line between April and May indicates the time of changing reagent used in Fenton process.
25
Toxicity (TU)
20
15
10
5
0 pH3
pHi
pH11
pH adjustment
pH3
pHi
pH11 Cation Anion
pH adjustment /filtration
Mix
pH3
Ion exchange
pHi
pH11
pH6
SPE
pH7
pH8
Graduate pH
pH3
pHi
Aeration
pH11
EDTA STS
30
Zn (mg L-1)
25 20 15 10 5 0 pH3
pHi
pH11
pH adjustment
pH3
pHi
pH11 Cation Anion
pH adjustment /filtration
Mix
Ion exchange
pH3
pHi
SPE
pH11
pH6
pH7
pH8
Graduate pH
pH3
pHi
pH11
Aeration
EDTA STS
Fig. 3. (a) Toxicity characterization of final effluent (March 2008) using D. magna. Error bars represent 95% confidential intervals; (b) Residual Zn concentrations after TIE phase I manipulations. The initial pH (pHi) of final effluent was 6.69.
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Table 2 Metal concentrations of YJ-WWTP effluents and S-stream water collected in March 2008.
RW PE SE FE US DS
Cd (mg L1)
Co (mg L1)
Cr (mg L1)
Cu (mg L1)
Fe (mg L1)
Mn (mg L1)
Ni (mg L1)
Zn (mg L1)
0.010 0.013 0.012 0.017 0.050 0.044
0.019 0.010 0.012 0.018 oDL 0.008
0.287 0.009 0.004 oDL 0.014 oDL
1.299 0.016 0.037 0.087 oDL 0.020
1.007 oDL oDL 0.113 oDL 0.148
0.092 0.088 0.179 0.473 0.433 0.503
0.742 0.632 0.371 0.516 0.112 0.288
2.111 2.493 1.156 25.05 oDL 4.259
RW: raw wastewater; PE: primary effluent; SE: secondary effluent; FE: final effluent; US: upstream water; DS: downstream water; DL: Detection limit.
10
42 Before Zn addition
2
r = 0.71
9
After Zn addition
8
30
7 Toxicity (TU)
Toxicity (TU)
36
24 18 12
6 5 4 3
6
April 2008
2
0 Filtration
Cationexchange
Mixed ion exchange
pH11/filtration
1 0 0
1
2
3
4
5
6
7
8
-1
Spiking
Zn (mg L )
Mass balance
Fig. 5. Correlation between dissolved concentration of zinc and toxicity of downstream water (DS). Error bars represent 95% confidential intervals. Fig. 4. Toxicity confirmation by spiking and mass balance tests. Error bars represent 95% confidential intervals. Zinc (25.0 mg L1) found in filtered final effluent (March 2008) was added.
change in toxicity after aeration, pH modifications, anion exchange, C18 SPE and STS reduction. This indicated that volatile, ammonia, anionic chemicals, organic compounds and chlorine did not contribute to the observed toxicity. In contrast, pH adjustment to 11 followed by filtration and EDTA chelation removed toxicity completely, and both cation and mixed ion exchange reduced the toxicity by 92%. This suggested that toxicants may have been cationic compounds such as metals, which likely formed hydroxide precipitate at pH 11. Metal analysis of FE (Table 2) observed Zn concentration of 25.05 mg L1, which far exceeded EC50 concentration for Zn in D. magna (1.54 mg L1). In addition, a substantial reduction in toxicity was observed in accordance with the decrease in Zn concentration after pH adjustment to 11 followed by filtration, cation exchange or mixed ion exchange (Fig. 3b). Thus, the overall results showed that Zn was likely a suspect toxicant in the FE sample. In order to confirm that Zn was a major toxicant in FE, spiking and mass balance studies were conducted. Zn (25.0 mg L1) was added to the filtered FE sample, and toxicity increased about twofold (34.2 TU), compared to that of the filtered sample (16.9 TU) (Fig. 4). Thus, it appeared that toxicity increased proportionally in accordance with doubling the Zn concentration. This was further confirmed by a mass balance experiment. As shown in Fig. 4, toxicity was recovered to a similar level in the filtered FE sample (16.9 TU) with the addition of 25.0 mg L1 Zn into the samples after cation exchange, mixed ion exchange and pH 11/filtration (17.2, 19.7 and 16.0 TU, respectively). Thus, the overall results showed that Zn was a key toxicant in FE collected in March 2008. Additionally, FE toxicity was significantly correlated with Zn concentration (r2 ¼ 0.95, po0.05) over the sampling events (except
for November due to the lack of metal analysis). This further supported that Zn was a major toxicant in FE for the sampling period monitored in this study. Given a significantly positive correlation between toxicity in FE and DS (Fig. 2), as mentioned earlier, the toxicity of DS was likely influenced by Zn. However, as shown in Fig. 5, only a trend between toxicity and Zn concentrations was observed in the DS samples (r2 ¼ 0.71, po0.05). 3.3. Toxicity reduction As mentioned earlier, toxicity in FE dramatically increased compared to SE while toxicity tended to decrease as treatment processes proceeded (Table 1). This led to an assumption that the increased toxicity was likely attributed to the addition of chemicals in the Fenton process used during SE treatment (Fig. 1). Because Zn concentrations in the FE were much higher than other effluent samples (Table 2), the Fenton reagent (FeCl2) was analyzed for the presence of Zn in March 2008. Zn concentrations were 83,900 mg L1 in the reagent, indicating that the increased FE toxicity was due to the addition of Zn during the Fenton treatment process. After changing the Fenton reagent to one containing lower Zn before the May sampling (see the vertical line in Fig. 2), Zn concentrations in FE greatly decreased to 1.90 and 0.92 mg L1 in May and June, respectively (data not shown). As a result, the FE toxicity in May decreased to 1.5 TU and no acute toxicity was found in the following month (Fig. 2).
4. Discussion From TIE procedures for the FE sample collected in March 2008, Zn was identified to be a major toxicant, which originated
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from a reagent used in the Fenton process for SE treatment. Fenton treatment, as a kind of advanced oxidation process, has been shown to be an efficient way of removing organic compounds (Kang and Hwang, 1999; Schrank et al., 2005; Xu et al., 2007). In the YJ-WWTP, the Fenton treatment was used to remove color and COD (chemical oxygen demand) from SE (data not shown). Thus, it is recommended not to use low quality chemical reagents for the wastewater treatments as this may result in unintended effluent toxicity. The overall monitoring results showed that FE toxicity varied over different sampling events (Fig. 2) and was greatly correlated with concentration of Zn originated from Fenton reagent (r2 ¼ 0.95, po0.05). From personal communication with the person in charge of YJ-WWTP operation, it was found that doses of Fenton reagent were critically optimized over wastewater flow rate. Thus, it was unlikely that dose differences were responsible for the observed variation of the FE toxicity. Instead, the toxicity variation seemed to be related to quality of the Fenton reagent, however, this should be further evaluated. The YJ-WWTP changed reagents for the Fenton process after our suggestion about the potential toxic effect caused by the low quality of the reagent and this led to the toxicity reduction in FE after the May sampling. The overall results showed that TIE procedures and toxicity test at different stages of the wastewater treatment processes were useful in detecting toxicity causing substances and reducing effluent toxicity. The monitoring results for the adjacent stream showed that DS toxicity always exceeded US toxicity (Fig. 2) and, thus, the DS toxicity appeared to be affected mainly by FE toxicity. This was further supported by a significant correlation between the toxicity of FE and DS (r2 ¼ 0.87, po0.05). Given that Zn concentrations in DS were mostly above the EC50 concentration and that there is a significant correlation between DS toxicity and Zn concentration (r2 ¼ 0.71, po0.05), it appeared that Zn was likely a major toxicant in DS. However, when compared to the result of FE (r2 ¼ 0.95, po0.05), less significant correlation was found between toxicity and Zn concentration in the DS samples. Toxicity of Zn in the aquatic environment can be modified by a number of water quality parameters such as pH, hardness and organic matter (Clifford and McGeer, 2009; Heijerick et al., 2002). The most outlying sample (April 2008) in Fig. 5 had an elevated DOC value (22.7 mg L1), which was highest among all sampling occasions and much higher than the average values from the other periods (Table 1). It is possible that organic complexation with Zn could have occurred limiting bioavailability of Zn (Udom et al., 2004; Bringolf et al., 2006). When the Zn concentrations were normalized to DOC value, much better correlation with DS toxicity was obtained (r2 ¼ 0.85, po0.05). However, further TIE studies for DS may be necessary to examine the presence of toxicity causing substances other than Zn. The reduction of Zn concentration and no acute toxicity were observed in FE sample after changing the Fenton reagents. It should be noted, however, that the levels of Zn concentration may still have detrimental effects on D. magna for a longer exposure time. According to the work of Jo and Jung (2008), a significant increase in molting-related gene expression in D. magna was observed at concentrations as low as of 0.2 mg L1 Zn. Poynton et al. (2007) also identified reduction in chitinase expression following exposure to concentrations of Zn less than 1 mg L1. Additionally, Muyssen et al. (2006) reported that only 40% and 7% survival was observed after 7-days exposure to Zn at a concentration of 0.25 and 0.34 mg L1, respectively. Thus, further studies are underway to develop more sensitive biomarkers that are relevant to long-term chronic effects of wastewater effluents on D. Magna.
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5. Conclusion Toxicity identification procedures used in this study were effective tools and successfully identified that Zn, originating from a reagent used for Fenton treatment, was the key toxicant in FEs of YJ-WWTP. This suggests that reagents used in the wastewater treatment procedures, such as the Fenton process, should be evaluated for purity to avoid unintended toxicity. In addition, FE toxicity varied over sampling events and toxicity of DS was largely affected by input of toxic effluent. Thus, for a better assessment, toxicity of effluents as well as adjacent streams should be monitored over a long-term period since a single sampling occasion may not be sufficient due to toxicity variability. In this work, only acute toxicity of effluents was assessed based on the new Korean legislation. However, long-term chronic effects of wastewater effluents should be further investigated to adequately evaluate impacts of a persistent discharge of low levels of toxic chemicals to receiving waterbodies. Acknowledgment This study was supported by Korea Ministry of Environment as ‘‘The Eco-technopia 21 project’’. References ˜ oz, M.J., de la Torre, A., Roset, J., de la Pen ˜ a, E., Carballo, M., 2004. Aguayo, S., Mun Identification of organic compounds and ecotoxicological assessment of sewage treatment plants (STP) effluents. Sci. Total Environ. 328, 69–81. APHA (American Public Health Association), 1998. Standard Methods for the Examination of Water and Wastewater, 20th ed. APHA, Washington, DC. Bringolf, R.B., Morris, B.A., Boese, C.J., Santore, R.C., Allen, H.E., Meyer, J.S., 2006. Influence of dissolved organic matter on acute toxicity of zinc to Larval Fathead Minnows (Pimephales promelas). Arch. Environ. Contam. Toxicol. 51, 438–444. Clifford, M., McGeer, J.C., 2009. Development of a biotic ligand model for the acute toxicity of zinc to Daphnia pulex in soft water. Aquat. Toxicol. 91, 26–32. Erten-Unal, M., Gelderloos, A.B., Hunghes, J.S., 1998. A toxicity reduction evaluation for an oily waste treatment plant exhibiting episodic effluent toxicity. Sci. Total Environ. 218, 141–152. Heijerick, D.G., De Schamphelaere, K.A.C., Janssen, C.R., 2002. Predicting acute zinc toxicity for Daphnia magna as a function of key water chemistry characteristics: development and validation of a biotic ligand model. Environ. Toxicol. Chem. 21, 1309–1315. Jin, H., Yang, X., Yin, D., Yu, H., 1999. A case study on identifying the toxicant in effluent discharged from a chemical plant. Mar. Pollut. Bull. 39, 122–125. Jo, H.J., Jung, J., 2008. Quantification of differentially expressed genes in Daphnia magna exposed to rubber wastewater. Chemosphere 73, 261–266. Jo, H.J., Park, E.J., Cho, K., Kim, E.H., Jung, J., 2008. Toxicity identification and reduction of wastewaters from a pigment manufacturing factory. Chemosphere 70, 949–957. Kang, Y.W., Hwang, K.Y., 1999. Effects of reaction conditions on the oxidation efficiency in the Fenton process. Wat. Res. 34, 2786–2790. Kim, E., Jun, Y.R., Jo, H.J., Shim, S.B., Jung, J., 2008. Toxicity identification in metal plating effluent: Implications in establishing effluent discharge limits using bioassays in Korea. Mar. Pollut. Bull. 57, 637–644. Korea MOE. 2007. Introduction of the Whole Effluent Toxicity (WET) Criteria for Industrial Wastewater from 2011 (in Korean). Industrial Wastewater Control Division, Water Quality Management Bureau. Kosmala, A., Charvet, S., Roger, M.C., Faessel, B., 1999. Impact assessment of a wastewater treatment plant effluent using instream invertebrates and the Ceriodaphnia dubia chronic toxicity test. Wat. Res. 33, 266–278. Mitteregger, H.M.J., Silva, J., Arenzon, A., Portela, C.S., Ferreira, I.C.F., Henriques, J.A.P., 2007. Evaluation of genotoxicity and toxicity of water and sediment samples from a Brazilian stream influenced by tannery industries. Chemosphere 67, 1211–1217. Muyssen, B.T.A., De Schamphelaere, K.A.C., Janssen, C.R., 2006. Mechanisms of chronic waterborne Zn toxicity in Daphnia magna. Aquat. Toxicol. 77, 393–401. Nedeau, E.J., Merritt, R.W., Kaufman, M.G., 2003. The effect of an industrial effluent on an urban stream benthic community: water quality vs. habitat quality. Environ. Pollut. 123, 1–13. Ntengwe, F.W., Maseka, K.K., 2006. The impact of effluents containing zinc and nickel metals on stream and river water bodies: the case of Chambishi and Mwambashi streams in Zambia. Phys. Chem. Earth 31, 814–820. OECD (Organization for Economic Co-operation and Development), 2004. Daphnia sp., Acute Immobilisation Test. Guideline for Testing of Chemicals No 202.
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A toxicity monitoring study on identification and reduction of toxicants from a wastewater treatment plant Xianliang Yi a, Eunhee Kim b, Hun-Je Jo a, Daniel Schlenk c, Jinho Jung a, a
Division of Environmental Science & Ecological Engineering, Korea University, Anam-dong, Sungbuk-gu, Seoul 136-713, Republic of Korea Department of Oceanography, Chonnam National University, Gwangju 500-757, Republic of Korea c Department of Environmental Sciences, University of California, Riverside, CA 92521, USA b
a r t i c l e in fo
abstract
Article history: Received 16 December 2008 Received in revised form 10 April 2009 Accepted 13 April 2009 Available online 12 May 2009
In this study, toxicity of effluents in a wastewater treatment plant and of receiving water in an adjacent stream was periodically monitored from November 2007 to June 2008, in order to trace and reduce sources of toxicants. The results showed that toxicity of final effluent (FE) changed greatly over different sampling events, and appeared to have impacts on toxicity of downstream water with a significant correlation (r2 ¼ 0.87, po0.05). In particular, FE toxicity was always higher than that of secondary effluent (SE). Toxicity identification evaluation (TIE) for the FE sample collected in March 2008 showed that FE toxicity was attributed to low quality of Fenton reagent with Zn contamination used for SE treatment. Furthermore, Zn concentrations in FE samples significantly correlated with FE toxicity during the sampling period (r2 ¼ 0.95, po0.05). After changing the Fenton reagent to one containing low Zn, Zn concentration and toxicity of FE greatly decreased in the following months. & 2009 Elsevier Inc. All rights reserved.
Keywords: Bioassay Daphnia magna Effluent Receiving water Wastewater treatment Zinc
1. Introduction Whole effluent toxicity (WET) tests, as a part of water quality monitoring programs, have been applied to regulate discharges in the United States over a decade (USEPA, 2000). Compared to chemical analysis alone, the WET programs have advantages in that it assesses biological effects of chemicals in wastewaters. In 2007, the Korean Ministry of Environment (MOE) announced that a new standard protocol and legislation using Daphnia magna acute toxicity tests would be gradually implemented from 2011 to regulate wastewater effluent (Korean MOE, 2007). For discharging effluents from wastewater treatment plants (WWTPs), the new legislation states that the toxic unit (TU) of 24 h should be less than 1. Whole effluent toxicity at different sampling occasions can be greatly variable because effluents are a mixture of various chemicals (Aguayo et al., 2000; Tarkpea et al., 1998; Mitteregger et al., 2007). However, the new criteria state no specific guidelines of adequate sampling numbers. As suggested by Kim et al. (2008), a single sampling occasion may not be sufficient due to toxicity variability. Additionally, the discharge of effluents can have negative effects on community and population structure of the receiving waterbody (Kosmala et al., 1999; Nedeau et al., 2003;
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E-mail address: [email protected] (J. Jung). 0147-6513/$ - see front matter & 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.ecoenv.2009.04.012
Ntengwe and Maseka, 2006). Thus, for a better assessment of effluent toxicity, toxicity variability in both wastewater effluent and its receiving water should be considered over a long-term period. Wastewater effluents often contain a large number of chemicals and not all of them are responsible for the observed toxicity. Thus, toxicity identification evaluation (TIE) has been developed by USEPA (USEPA, 1991, 1993a, b) and widely used to identify and reduce major toxicants in industrial effluents (Erten-Unal et al., 1998; Jin et al., 1999; Yu et al., 2004; Jo et al., 2008; Park et al., 2008). Given the above, this paper aimed at: (1) monitoring toxicity in samples collected from a WWTP and the adjacent stream on a regular basis to assess impacts of wastewater effluent on its receiving waterbody; and (2) identifying toxicity causing substances in the effluent to reduce its toxic effects.
2. Materials and methods 2.1. Sample collection Monthly sampling was conducted from a WWTP (YJ-WWTP), located in Yangju, Kyunggi do, Republic of Korea, and the adjacent stream (S-stream) from November 2007 to June 2008. The YJ-WWTP daily treats about 23,000 m3 wastewater, which originates from textile and dyeing facilities, and is directly discharged into the S-stream. Fig. 1 shows a flow diagram of the wastewater treatment process in YJ-WWTP. Samples were collected after four different processes, namely, raw wastewater (RW), primary effluent (PE), secondary effluent
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(SE) and final effluent (FE), as well as two points of the adjacent stream water, upstream (US) and downstream (DS), about 50 m distant from the discharge point of FE, respectively. Samples were transported in polyethylene containers on ice to the lab and immediately stored at 4 1C throughout the whole study period. Initial toxicity tests and water quality analysis were conducted upon the arrival of the samples. 2.2. Chemical analyses Samples were filtered using a 0.45 mm syringe filter and analyzed for DOC (dissolved organic carbon) using a Shimadzu TOC analyzer, model 5000A (Kyoto, Japan). Hardness and TSS (total suspended solids) were measured according to the Standard Methods for the Examination of Water and Wastewater (APHA, 1998). Total residual chlorine (TRC) was measured using a residual chlorine electrode (model 97-70, Thermo Electron Inc., USA). Ammonia concentration was measured using an ammonia electrode (model 95-12, Thermo Electron Inc., USA). Metal concentrations were analyzed using a Varian inductively coupled plasma-optical emission spectrophotometer (ICP-OES, Varian Vista PRO, CA, USA). For metal analysis, all the vessels and experimental apparatus were rigorously acid-cleaned before use. Standard solutions were freshly prepared and standard calibration curves with r240.995 were achieved daily. A known concentration of a standard was analyzed every 12 samples to ensure data quality and the recovery ranged 94–107%. Detection limits were calculated based on blank standard deviations 3 and ranged from 4 to 14 mg L1. 2.3. Toxicity test For toxicity tests, D. magna (neonates less than 24 h old) were obtained from cultures at the Korea Research Institute of Chemical Technology. Acute toxicity tests were carried out according to the Organization for Economic Co-operation and Development (OECD) standard procedure (OECD, 2004). In each toxicity test, five or more dilutions of a sample and one control with four replicates were prepared, with 10 mL test solution and five individuals placed in each vessel. Toxicity tests were conducted at 2072 1C with a 16 h light:8 h dark photoperiod for 48 h. Immobilization results of the test species were used to calculate the EC50 (50% effective concentration) values by a graphical method, Probit analysis or the Trimmed Spearman-Karber Method (USEPA, 2002). For comparison, EC50 values were transformed into toxic units (TU ¼ 100/EC50).
2.4. Toxicity identification evaluation Toxicity identification evaluation was conducted for the FE collected in March 2008 according to TIE procedures developed by the USEPA (USEPA, 1991, 1993a, b). In TIE phase I test (USEPA, 1991), baseline test, pH adjustment, pH adjustment/ aeration, pH adjustment/filtration, pH adjustment/C18 solid phase extraction (SPE), graduated pH, EDTA addition and sodium thiosulfate (STS) addition were included to characterize classes of toxicants. In particular, EDTA chelation tests were carried out at different concentrations ranging from 70 to 141.4 mg L1. Similarly, STS reduction tests were also conducted at concentration ranges of 9.48–355 mg L1. Additionally, ion exchange manipulations were conducted to further characterize toxicants (Jo et al., 2008). Cation and anion exchange columns were prepared with 60 mL syringes filled with either cation (Amberlite IR-120, sodium form, Aldrich, USA) or anion (Amberlite IRA-410, chloride form, Aldrich, USA) exchange resins. For mixed ion exchange (cation and anion), samples went through both ion exchange columns sequentially. Except for graduated pH tests, pH of the samples after each manipulation was readjusted to initial pH with NaOH and HCl before toxicity test. In TIE phase II test (USEPA, 1993a), metals suspected as key toxic materials were measured using a Varian ICP-OES (Varian Vista PRO, CA, USA). For metal analyses, aliquot samples were saved and preserved with concentrated nitric acid. From the results of identification, suspect toxicants were confirmed by mass balance and spiking approaches of TIE phase III test (USEPA, 1993b). In the mass balance approach, the same concentration of a suspect toxicant found in the filtered sample was added to samples after manipulations, which showed a toxicity reduction (e.g., ion exchange or pH adjustment to 11). Then, toxicity tests were conducted before and after the addition of the suspect toxicant. For the spiking approach, the same concentration of the suspect toxicant was added to the filtered sample. Then, toxicity tests were performed to check if toxicity increased linearly with the addition of the suspect toxicant.
3. Results 3.1. Toxicity monitoring The results of toxicity and chemical analyses of YJ-WWTP effluents and the adjacent S-stream water are presented in Table 1. The average TUs decreased in order of RW, PE and SE (5.8, 1.6 and 0.3, respectively) while TU for FE increased to 10.1 TU. In addition, the average toxicity of DS (3.6 TU) was lower than that of FEs (10.1 TU), but higher than the average of USs toxicity (0.3 TU). Fig. 2 shows changes in toxicity of effluents and adjacent stream waters over different sampling events. Overall, toxicity of FE showed variable change and was much higher than that of SEs and even RWs until April 2008. In contrast to changes in US toxicity, DS toxicity over the overall sampling events mirrored that of FE, indicating that effluent from the YJ-WWTP may have an impact on toxicity at DS of the S-stream. Additionally, a significant correlation between toxicity in FE and DS was found (r2 ¼ 0.87, po0.05). This further supported that toxicity in DS was affected by the input of FE. 3.2. Toxicity identification
Fig. 1. Wastewater treatment processes and sampling points in YJ-WWTP and the adjacent S-stream. RW: raw wastewater; PE: primary effluent; SE: secondary effluent; FE: final effluent; US: upstream water; DS: downstream water.
TIE procedures were conducted for FE collected in March 2008. TIE phase I results were illustrated in Fig. 3a. There was little
Table 1 Toxicity and chemical characteristics of YJ-WWTP effluents and S-stream water.
pH DO (mg L1) TRC (mg L1) Ammonia (as NH3, mg L1) Hardness (as CaCO3, mg L1) DOC (mg L1) TSS (mg L1) TU (48 h)
RW
PE
SE
FE
US
DS
8.6470.70 0.6570.30 o0.2 24.08718.49 120787 228.64748.98 429.627361.45 5.872.5
8.4270.37 0.8770.54 o0.2 23.30716.96 2167100 158.14737.18 165.02775.80 1.671.2
7.6070.10 7.0270.52 o0.2 2.1672.82 2767168 31.6373.52 24.4177.78 0.370.6
6.9470.24 8.1470.77 o0.2 3.0872.77 3887315 19.7776.83 11.17710.00 10.175.0
7.4570.33 7.5571.84 o0.2 26.96715.77 236756 11.6373.15 32.03714.66 0.370.8
7.3670.15 8.2771.13 o0.2 19.2877.87 3347200 14.1074.85 20.97710.80 3.672.2
RW: raw wastewater; PE: primary effluent; SE: secondary effluent; FE: final effluent; US: upstream water; DS: downstream water; DO: dissolved oxygen; TRC: total residual chlorine; DOV: dissolved organic carbon; TSS: total suspended solid; TU: toxic unit (TU ¼ 100/EC50).Data were collected monthly from November 2007 to April 2008, and the results are expressed a s the mean value7standard deviation .
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18.0 16.0
RW
1921
after changing
PE
Fenton reagent
SE FE
14.0
US DS
Toxicity (TU)
12.0 10.0 8.0 6.0 4.0 2.0 0.0 Dec.07
Nov.07
Jan.08
Feb.08 Mar.08 Time
Apri.08
May.08
June.08
Fig. 2. Toxicity monitoring of YJ-WWTP effluents and S-stream waters. Error bars represent 95% confidential intervals. RW: raw wastewater; PE: primary effluent; SE: secondary effluent; FE: final effluent, US: upstream water; DS: downstream water. The vertical line between April and May indicates the time of changing reagent used in Fenton process.
25
Toxicity (TU)
20
15
10
5
0 pH3
pHi
pH11
pH adjustment
pH3
pHi
pH11 Cation Anion
pH adjustment /filtration
Mix
pH3
Ion exchange
pHi
pH11
pH6
SPE
pH7
pH8
Graduate pH
pH3
pHi
Aeration
pH11
EDTA STS
30
Zn (mg L-1)
25 20 15 10 5 0 pH3
pHi
pH11
pH adjustment
pH3
pHi
pH11 Cation Anion
pH adjustment /filtration
Mix
Ion exchange
pH3
pHi
SPE
pH11
pH6
pH7
pH8
Graduate pH
pH3
pHi
pH11
Aeration
EDTA STS
Fig. 3. (a) Toxicity characterization of final effluent (March 2008) using D. magna. Error bars represent 95% confidential intervals; (b) Residual Zn concentrations after TIE phase I manipulations. The initial pH (pHi) of final effluent was 6.69.
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Table 2 Metal concentrations of YJ-WWTP effluents and S-stream water collected in March 2008.
RW PE SE FE US DS
Cd (mg L1)
Co (mg L1)
Cr (mg L1)
Cu (mg L1)
Fe (mg L1)
Mn (mg L1)
Ni (mg L1)
Zn (mg L1)
0.010 0.013 0.012 0.017 0.050 0.044
0.019 0.010 0.012 0.018 oDL 0.008
0.287 0.009 0.004 oDL 0.014 oDL
1.299 0.016 0.037 0.087 oDL 0.020
1.007 oDL oDL 0.113 oDL 0.148
0.092 0.088 0.179 0.473 0.433 0.503
0.742 0.632 0.371 0.516 0.112 0.288
2.111 2.493 1.156 25.05 oDL 4.259
RW: raw wastewater; PE: primary effluent; SE: secondary effluent; FE: final effluent; US: upstream water; DS: downstream water; DL: Detection limit.
10
42 Before Zn addition
2
r = 0.71
9
After Zn addition
8
30
7 Toxicity (TU)
Toxicity (TU)
36
24 18 12
6 5 4 3
6
April 2008
2
0 Filtration
Cationexchange
Mixed ion exchange
pH11/filtration
1 0 0
1
2
3
4
5
6
7
8
-1
Spiking
Zn (mg L )
Mass balance
Fig. 5. Correlation between dissolved concentration of zinc and toxicity of downstream water (DS). Error bars represent 95% confidential intervals. Fig. 4. Toxicity confirmation by spiking and mass balance tests. Error bars represent 95% confidential intervals. Zinc (25.0 mg L1) found in filtered final effluent (March 2008) was added.
change in toxicity after aeration, pH modifications, anion exchange, C18 SPE and STS reduction. This indicated that volatile, ammonia, anionic chemicals, organic compounds and chlorine did not contribute to the observed toxicity. In contrast, pH adjustment to 11 followed by filtration and EDTA chelation removed toxicity completely, and both cation and mixed ion exchange reduced the toxicity by 92%. This suggested that toxicants may have been cationic compounds such as metals, which likely formed hydroxide precipitate at pH 11. Metal analysis of FE (Table 2) observed Zn concentration of 25.05 mg L1, which far exceeded EC50 concentration for Zn in D. magna (1.54 mg L1). In addition, a substantial reduction in toxicity was observed in accordance with the decrease in Zn concentration after pH adjustment to 11 followed by filtration, cation exchange or mixed ion exchange (Fig. 3b). Thus, the overall results showed that Zn was likely a suspect toxicant in the FE sample. In order to confirm that Zn was a major toxicant in FE, spiking and mass balance studies were conducted. Zn (25.0 mg L1) was added to the filtered FE sample, and toxicity increased about twofold (34.2 TU), compared to that of the filtered sample (16.9 TU) (Fig. 4). Thus, it appeared that toxicity increased proportionally in accordance with doubling the Zn concentration. This was further confirmed by a mass balance experiment. As shown in Fig. 4, toxicity was recovered to a similar level in the filtered FE sample (16.9 TU) with the addition of 25.0 mg L1 Zn into the samples after cation exchange, mixed ion exchange and pH 11/filtration (17.2, 19.7 and 16.0 TU, respectively). Thus, the overall results showed that Zn was a key toxicant in FE collected in March 2008. Additionally, FE toxicity was significantly correlated with Zn concentration (r2 ¼ 0.95, po0.05) over the sampling events (except
for November due to the lack of metal analysis). This further supported that Zn was a major toxicant in FE for the sampling period monitored in this study. Given a significantly positive correlation between toxicity in FE and DS (Fig. 2), as mentioned earlier, the toxicity of DS was likely influenced by Zn. However, as shown in Fig. 5, only a trend between toxicity and Zn concentrations was observed in the DS samples (r2 ¼ 0.71, po0.05). 3.3. Toxicity reduction As mentioned earlier, toxicity in FE dramatically increased compared to SE while toxicity tended to decrease as treatment processes proceeded (Table 1). This led to an assumption that the increased toxicity was likely attributed to the addition of chemicals in the Fenton process used during SE treatment (Fig. 1). Because Zn concentrations in the FE were much higher than other effluent samples (Table 2), the Fenton reagent (FeCl2) was analyzed for the presence of Zn in March 2008. Zn concentrations were 83,900 mg L1 in the reagent, indicating that the increased FE toxicity was due to the addition of Zn during the Fenton treatment process. After changing the Fenton reagent to one containing lower Zn before the May sampling (see the vertical line in Fig. 2), Zn concentrations in FE greatly decreased to 1.90 and 0.92 mg L1 in May and June, respectively (data not shown). As a result, the FE toxicity in May decreased to 1.5 TU and no acute toxicity was found in the following month (Fig. 2).
4. Discussion From TIE procedures for the FE sample collected in March 2008, Zn was identified to be a major toxicant, which originated
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from a reagent used in the Fenton process for SE treatment. Fenton treatment, as a kind of advanced oxidation process, has been shown to be an efficient way of removing organic compounds (Kang and Hwang, 1999; Schrank et al., 2005; Xu et al., 2007). In the YJ-WWTP, the Fenton treatment was used to remove color and COD (chemical oxygen demand) from SE (data not shown). Thus, it is recommended not to use low quality chemical reagents for the wastewater treatments as this may result in unintended effluent toxicity. The overall monitoring results showed that FE toxicity varied over different sampling events (Fig. 2) and was greatly correlated with concentration of Zn originated from Fenton reagent (r2 ¼ 0.95, po0.05). From personal communication with the person in charge of YJ-WWTP operation, it was found that doses of Fenton reagent were critically optimized over wastewater flow rate. Thus, it was unlikely that dose differences were responsible for the observed variation of the FE toxicity. Instead, the toxicity variation seemed to be related to quality of the Fenton reagent, however, this should be further evaluated. The YJ-WWTP changed reagents for the Fenton process after our suggestion about the potential toxic effect caused by the low quality of the reagent and this led to the toxicity reduction in FE after the May sampling. The overall results showed that TIE procedures and toxicity test at different stages of the wastewater treatment processes were useful in detecting toxicity causing substances and reducing effluent toxicity. The monitoring results for the adjacent stream showed that DS toxicity always exceeded US toxicity (Fig. 2) and, thus, the DS toxicity appeared to be affected mainly by FE toxicity. This was further supported by a significant correlation between the toxicity of FE and DS (r2 ¼ 0.87, po0.05). Given that Zn concentrations in DS were mostly above the EC50 concentration and that there is a significant correlation between DS toxicity and Zn concentration (r2 ¼ 0.71, po0.05), it appeared that Zn was likely a major toxicant in DS. However, when compared to the result of FE (r2 ¼ 0.95, po0.05), less significant correlation was found between toxicity and Zn concentration in the DS samples. Toxicity of Zn in the aquatic environment can be modified by a number of water quality parameters such as pH, hardness and organic matter (Clifford and McGeer, 2009; Heijerick et al., 2002). The most outlying sample (April 2008) in Fig. 5 had an elevated DOC value (22.7 mg L1), which was highest among all sampling occasions and much higher than the average values from the other periods (Table 1). It is possible that organic complexation with Zn could have occurred limiting bioavailability of Zn (Udom et al., 2004; Bringolf et al., 2006). When the Zn concentrations were normalized to DOC value, much better correlation with DS toxicity was obtained (r2 ¼ 0.85, po0.05). However, further TIE studies for DS may be necessary to examine the presence of toxicity causing substances other than Zn. The reduction of Zn concentration and no acute toxicity were observed in FE sample after changing the Fenton reagents. It should be noted, however, that the levels of Zn concentration may still have detrimental effects on D. magna for a longer exposure time. According to the work of Jo and Jung (2008), a significant increase in molting-related gene expression in D. magna was observed at concentrations as low as of 0.2 mg L1 Zn. Poynton et al. (2007) also identified reduction in chitinase expression following exposure to concentrations of Zn less than 1 mg L1. Additionally, Muyssen et al. (2006) reported that only 40% and 7% survival was observed after 7-days exposure to Zn at a concentration of 0.25 and 0.34 mg L1, respectively. Thus, further studies are underway to develop more sensitive biomarkers that are relevant to long-term chronic effects of wastewater effluents on D. Magna.
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5. Conclusion Toxicity identification procedures used in this study were effective tools and successfully identified that Zn, originating from a reagent used for Fenton treatment, was the key toxicant in FEs of YJ-WWTP. This suggests that reagents used in the wastewater treatment procedures, such as the Fenton process, should be evaluated for purity to avoid unintended toxicity. In addition, FE toxicity varied over sampling events and toxicity of DS was largely affected by input of toxic effluent. Thus, for a better assessment, toxicity of effluents as well as adjacent streams should be monitored over a long-term period since a single sampling occasion may not be sufficient due to toxicity variability. In this work, only acute toxicity of effluents was assessed based on the new Korean legislation. However, long-term chronic effects of wastewater effluents should be further investigated to adequately evaluate impacts of a persistent discharge of low levels of toxic chemicals to receiving waterbodies. Acknowledgment This study was supported by Korea Ministry of Environment as ‘‘The Eco-technopia 21 project’’. References ˜ oz, M.J., de la Torre, A., Roset, J., de la Pen ˜ a, E., Carballo, M., 2004. Aguayo, S., Mun Identification of organic compounds and ecotoxicological assessment of sewage treatment plants (STP) effluents. Sci. Total Environ. 328, 69–81. APHA (American Public Health Association), 1998. Standard Methods for the Examination of Water and Wastewater, 20th ed. APHA, Washington, DC. Bringolf, R.B., Morris, B.A., Boese, C.J., Santore, R.C., Allen, H.E., Meyer, J.S., 2006. Influence of dissolved organic matter on acute toxicity of zinc to Larval Fathead Minnows (Pimephales promelas). Arch. Environ. Contam. Toxicol. 51, 438–444. Clifford, M., McGeer, J.C., 2009. Development of a biotic ligand model for the acute toxicity of zinc to Daphnia pulex in soft water. Aquat. Toxicol. 91, 26–32. Erten-Unal, M., Gelderloos, A.B., Hunghes, J.S., 1998. A toxicity reduction evaluation for an oily waste treatment plant exhibiting episodic effluent toxicity. Sci. Total Environ. 218, 141–152. Heijerick, D.G., De Schamphelaere, K.A.C., Janssen, C.R., 2002. Predicting acute zinc toxicity for Daphnia magna as a function of key water chemistry characteristics: development and validation of a biotic ligand model. Environ. Toxicol. Chem. 21, 1309–1315. Jin, H., Yang, X., Yin, D., Yu, H., 1999. A case study on identifying the toxicant in effluent discharged from a chemical plant. Mar. Pollut. Bull. 39, 122–125. Jo, H.J., Jung, J., 2008. Quantification of differentially expressed genes in Daphnia magna exposed to rubber wastewater. Chemosphere 73, 261–266. Jo, H.J., Park, E.J., Cho, K., Kim, E.H., Jung, J., 2008. Toxicity identification and reduction of wastewaters from a pigment manufacturing factory. Chemosphere 70, 949–957. Kang, Y.W., Hwang, K.Y., 1999. Effects of reaction conditions on the oxidation efficiency in the Fenton process. Wat. Res. 34, 2786–2790. Kim, E., Jun, Y.R., Jo, H.J., Shim, S.B., Jung, J., 2008. Toxicity identification in metal plating effluent: Implications in establishing effluent discharge limits using bioassays in Korea. Mar. Pollut. Bull. 57, 637–644. Korea MOE. 2007. Introduction of the Whole Effluent Toxicity (WET) Criteria for Industrial Wastewater from 2011 (in Korean). Industrial Wastewater Control Division, Water Quality Management Bureau. Kosmala, A., Charvet, S., Roger, M.C., Faessel, B., 1999. Impact assessment of a wastewater treatment plant effluent using instream invertebrates and the Ceriodaphnia dubia chronic toxicity test. Wat. Res. 33, 266–278. Mitteregger, H.M.J., Silva, J., Arenzon, A., Portela, C.S., Ferreira, I.C.F., Henriques, J.A.P., 2007. Evaluation of genotoxicity and toxicity of water and sediment samples from a Brazilian stream influenced by tannery industries. Chemosphere 67, 1211–1217. Muyssen, B.T.A., De Schamphelaere, K.A.C., Janssen, C.R., 2006. Mechanisms of chronic waterborne Zn toxicity in Daphnia magna. Aquat. Toxicol. 77, 393–401. Nedeau, E.J., Merritt, R.W., Kaufman, M.G., 2003. The effect of an industrial effluent on an urban stream benthic community: water quality vs. habitat quality. Environ. Pollut. 123, 1–13. Ntengwe, F.W., Maseka, K.K., 2006. The impact of effluents containing zinc and nickel metals on stream and river water bodies: the case of Chambishi and Mwambashi streams in Zambia. Phys. Chem. Earth 31, 814–820. OECD (Organization for Economic Co-operation and Development), 2004. Daphnia sp., Acute Immobilisation Test. Guideline for Testing of Chemicals No 202.
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