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Water quality criteria derivation and ecological risk assessment for triphenyltin in China
Ecotoxicology and Environmental Safety 161 (2018) 397–401
Contents lists available at ScienceDirect
Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv
Water quality criteria derivation and ecological risk assessment for triphenyltin in China Jingjing Wena, Xiaoying Cuia,b, Mark Gibsonc, Zhengyan Lia,b,
T
⁎
a
College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, PR China Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Qingdao 266100, PR China c Department of Process Engineering and Applied Science, Dalhousie University, Halifax, NS, Canada B3J 2X4 b
A R T I C LE I N FO
A B S T R A C T
Keywords: TPT Species sensitivity distribution Ecological risk assessment Criterion maximum concentration Criterion continuous concentration
Triphenyltin (TPT) is one of the most toxic chemicals artificially discharged into aquatic environment with human activities. Due to its intensive use in antifouling paints and adverse effects on non-target species, TPT has aroused wide concern in both saltwater and freshwater environment. Nevertheless, the water quality criteria (WQC) are not available in China, which impedes the risk assessment for this emerging pollutant. This study aims to establish the WQC of TPT for both freshwater and saltwater ecosystems. With the derived WQC, a fourlevel tiered ecological risk assessment (ERA) approach was employed to assess the ecological risks of this emerging pollutant in Chinese waters. Through the species sensitivity distribution (SSD) methodology, the freshwater criterion maximum concentration (CMC) and criterion continuous concentration (CCC) were derived as 396 ng Sn L-1 and 5.60 ng Sn L-1, respectively, whereas the saltwater CMC and CCC were 66.5 ng Sn L-1 and 4.11 ng Sn L-1, respectively. The ecological risk assessment for TPT demonstrated that the acute risk was negligible whereas the chronic risk was significant with HQ (Hazard Quotient) values of up to 5.669 and 57.1% of coastal waters in China facing clear risk. TPT contamination in coastal environment, therefore, warrants further concern.
1. Introduction Triphenyltin (TPT) compounds are triphenyl derivatives of tetravalent tin with a general formula of (C6H5)3Sn-X, typically existing as chloride, hydroxide and acetate compounds (Yi et al., 2012). TPT, together with TBT (tributyltin), has been widely applied in antifouling paints and fungicides since 1960s. In European countries and USA, TBT was the main ingredient in organotin based antifouling paints. In China, however, TPT was the mainly used organotin product with an annual manufacturing amount of 150–200 t (Hu et al., 2006; 2009). Due to its properties of persistence, bioaccumulation and toxicity, TPT has received wide concern. TPT exerts endocrine disrupting effects on various aquatic species including gastropods and fishes (Horiguchi et al., 1994; Santos et al., 2006; Zhang et al., 2008; Sun et al., 2011), causing reproductive failure and population decrease at extremely low concentrations of nanogram per liter. Consequently, the usage of organotin-based antifouling paints was prohibited in many countries and regions throughout the world (Chau et al., 1997). The international ban for organotins was also initiated by IMO (International Maritime Organization) in 2001 (IMO, 2001). In China, although TBT is regulated, TPT is not restricted except for its usage as pesticides being prohibited ⁎
in 1999 in Taiwan (Meng et al., 2009). Due to the increasing demand for its usage in both industrial and agricultural sectors in China, TPT contamination in natural waters is to be expected (Cao et al., 2009). TPT in coastal waters of China was reported with concentrations from undetected to 17.2 ng Sn-1 (Wang et al., 2008, Liu et al., 2011, Hu et al., 2006, Huang, 1999). TPT was also reported in fresh water in the Yangtze River and Jialing River with a concentration of up to 37.2 ng Sn-1 (Gao et al., 2013). Water quality criteria (WQC) are defined as the permitted maximum concentration of chemicals without negative effects on organisms in aquatic environment (Yang et al., 2014). The two-number criteria system, including criterion continuous concentration (CCC) and criterion maximum concentration (CMC) is most commonly used in various countries, which is also adopted in this study. The combination of CMC and CCC provides an appropriate extent of protection for aquatic organisms from both acute and chronic toxicity (USEPA, 1985). According to the guidelines of US EPA, the ecological risk assessment (ERA) is aimed to determine the probability and degree of harmful ecological outcome of risk sources such as chemical exposure (USEPA, 1998). The most rudimentary approach of ERA is hazard quotients (HQ), usually expressed as a ratio between exposure and
Corresponding author at: College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, PR China. E-mail address: [email protected] (Z. Li).
https://doi.org/10.1016/j.ecoenv.2018.06.012 Received 18 July 2017; Received in revised form 25 December 2017; Accepted 23 January 2018 Available online 12 June 2018 0147-6513/ © 2018 Elsevier Inc. All rights reserved.
Ecotoxicology and Environmental Safety 161 (2018) 397–401
J. Wen et al.
Level 2 assessment calculates the likelihood that the measured concentrations exceed the preselected effect threshold by comparing the exposure concentration distribution (ECD) with the WQC. The log-normal model was adopted for constructing ECD after Kolmogorov-Smirnov test for normality. Level 3 assessment characterizes the risk through the overlap between SSD and ECD. Firstly, MOS10 (Margin of Safety at 10%) was quantified via the 10th percentile of SSD (SSD10) divided by the 90th percentile of ECD (ECD90). MOS10 values of < 1 indicate significant risk, whereas values of > 1 represent minimal risk to aquatic organisms. The MOS10 method therefore only provides general information of risk. To further characterize the risk, the Joint Probability Curve (JPC) generated from SSD and Exceedance Probability Function (EPF, or the reverse ECD) represents the probability of exceeding the pollutant concentration causing a certain degree of ecological effect (Wang et al., 2002). Based on JPC, the Overall Risk Probability (ORP) can be calculated as the area of JPC enclosed by the X-axis to identify the overall ecological risk. The risk level is ranked as negligible, potential and clear if the ORP value is < 0.1%, 0.1–1.0% and ≥1.0%, respectively (Wang et al., 2009). Level 4 assessment adopts Monte Carlo random sampling from ECD and SSD for 20,000 times and consequently calculates the distribution-based quotient (DBQ). The risk is expressed as the likelihood of exceeding the preselected HQ values (0.3 or 1.0).
toxicity concentrations. Despite its simplicity and effectiveness, the quotients do not allow spatial or temporal analysis of the probability and magnitude of ecological risks (ECOFRAM, 1999). To obtain more reliable estimates of risks, ERA based on probabilistic analysis, which quantifies the risk through probability distributions of both exposure and effect, are recommended for higher level assessment (Solomon and Sibley, 2002). This study aims to develop the WQC of TPT considering both exposure duration (acute and chronic) and water types (saltwater and freshwater). Based on the WQC, the ecological risk of TPT in aquatic environment of China were comprehensively evaluated with a tiered ERA approach. 2. Materials and methods 2.1. Screening of toxicity data The toxicity data of TPT were screened from open databases and literature in this study. Only the toxicity data tested with Chinese resident species were selected. For acute toxicity data, short-term (48 h or 96 h) LC50 or EC50 (median lethal or effective concentration) values were adopted. While for chronic data, long-term (≥14 days) NOEC (no observed effect concentration) values referring to traditional toxicity endpoints such as survival and growth were used. The toxicity data referring to molecular biomarker endpoints were however excluded. The geometric mean was employed when multiple data was available tested with the same species (Guo et al., 2015). The toxicity values of TPT selected for criteria derivation in this study is listed in Supplementary Material S1–S2.
3. Results and discussion 3.1. Acute and chronic toxicity data of TPT Table 1 presents the statistical parameters for acute and chronic datasets of TPT to both freshwater and saltwater species. The AndersonDarling test showed that the toxicity data could be fit with log-normal distribution. A two-sample t test indicated that both acute and chronic data showed significant difference between freshwater and saltwater (Pacute < 0.01, Pchronic < 0.05). It is, therefore, necessary to derive saltwater and freshwater criteria separately to avoid over or under protection of aquatic species.
2.2. The derivation of water quality criteria Nowadays, the SSD (species sensitivity distribution) methodology is increasingly adopted in water quality criteria derivation (Wik, 2008). This methodology is based on the hypothesis that the tested species are representative, in terms of sensitivity, of the total species in an ecosystem (Ciffroy and Brebbia, 2007). SSD is used to predict Hazardous Concentration affecting p% of all species in an ecosystem (HCp), usually selecting 5% as the acceptable fraction affected and therefore 95% species being protected. Based on the value of HC5 derived with the SSD model, the Predicted No Effect Concentration (PNEC) could be determined through being divided by an Assessment Factor (AF). The choice of AF depends on the richness of toxicity data and the goodness of model simulation (ECB, 2003; Gao et al., 2014). Currently an AF of 2 is used in most studies when the toxicity data covers at least three phylum and eight families (USEPA, 1985; Guo et al., 2015; Park et al., 2018). The same AF value was also applied in the criterion derivation process in this study to ensure the consistency of results. Although various distributions have been utilized to construct SSD models, the log-normal distribution is most commonly used with its advantage of in depth analysis for various uncertainties, which is also adopted in this study for SSD construction.
3.2. Acute WQC for TPT The SSD models were constructed based on the acute data of TPT to saltwater and freshwater species, respectively (Fig. 1a). The HC5 (hazardous concentration to 5% of species) values were calculated as 0.133 μg Sn L-1 (90% confidence interval: 0.039–0.290 μg Sn L-1) and 0.791 μg Sn L-1 (90% confidence interval: 0.273–1.652 μg Sn L-1) respectively for saltwater and freshwater species. With the HC5 values, the PNEC values could be calculated by being divided with an AF of 2, which is also defined as WQC for TPT. Consequently, the CMC (criterion maximum concentration) in saltwater and freshwater was derived as 0.067 μg Sn L-1 and 0.396 μg Sn L-1, respectively. 3.3. Chronic water quality criteria of TPT
2.3. Ecological risk assessment
Considering the scarcity of chronic toxicity data, the method of Acute to Chronic Ratio (ACR) was used to supplement saltwater chronic data. A final ACR value of 18.1 was adopted as the geometric mean of all ACR values (Supplementary Material S3). During the simulation of SSD curves for saltwater species, both the raw data and ACR extrapolated data were pooled (Supplementary Material S4). During the simulation of SSD curves for freshwater species, however, only the raw data was used since they were sufficient for model simulation. Based on SSD simulation, the HC5 values for saltwater and freshwater species were quantified as 0.0082 μg Sn L-1 and 0.011 μg Sn L-1, respectively (Fig. 1b). Consequently, the CCC (criterion continuous concentration) was derived as 0.0041 μg Sn L-1 and 0.0056 μg Sn L-1 for saltwater and freshwater environment.
The risk assessment of TPT was conducted based on a four-level tiered ERA approach recommended by ECOFRAM (1999) and developed by Zolezzi et al. (2005) and Wang et al. (2009). The assessment approach is as follows: Level 1 assessment involves a deterministic hazard quotient (HQ), i.e., a ratio between MEC (measured environmental concentration) and PNEC values. The PNEC was referred to the derived criteria of TPT. The risk level is determined as negligible, potential and clear based on HQ values with the corresponding range of 0–0.3, 0.3–1.0 and over 1.0, respectively. 398
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Fig. 1. The SSD curves for acute (left) and chronic (right) toxicity of TPT (circle, square and triangle representing algal, invertebrate and vertebrate species, respectively).
showed a similar phenomenon. This difference in response to TPT toxicity is probably related to discrepancy in taxonomic composition and chemical bioavailability between saltwater and freshwater ecosystems. First, the saltwater toxicity data contains a high proportion of algal (46.7%) and invertebrate species (33.3%) whereas the freshwater data covers more invertebrate (52.4%) and vertebrate species (28.6%). Algal species are usually not sensitive to organic pollutants, although direct comparison on relative vulnerability among algal, invertebrate and vertebrate species upon TPT toxicity is not available. Second, chemical speciation of TPT in aquatic environment is influenced by various factors of the medium, especially pH value and chloride (Cl-) content. In aquatic environment, TPT (e.g. TPT chloride) exists in both neutral forms (TPTOH and TPTCl) and ionic form (TPT+). The pH value influences the proportion of these two forms. With the increase of pH values, the proportion of neutral forms is higher (Tsuda et al., 1990). With a PKa value of 5.2 for TPT+ (Arnold et al., 1997), the proportion of these two forms can be calculated. When pH value changes from 6.5 to 8.0 (covering the scope of pH in all toxicity tests as shown in Supplementary Material S1–2), the proportion of neutral forms increases from 95.2% to 99.8%, whereas that of ionic form decreases from 4.76% to 0.16%. The neutral forms of TPT are more toxic than ionic form (Looser et al., 1998; White and Tobin, 2004). TPT in saltwater with higher pH values is therefore more toxic than that in freshwater. In addition, the neutral form of TPT can further be separated into two species, TPTOH and TPTCl. In fresh water, TPTCl is negligible, whereas in saltwater, TPTCl can reach up to a half of total neutral forms (White and Tobin, 2004). Considering the higher toxicity of TPTCl than TPTOH (White and Tobin, 2004), the high Cl- concentration in saltwater also enhances the toxicity of TPT. It can therefore be assumed that high pH value and Cl- concentration in saltwater would increase the toxicity of TPT. Saltwater species, therefore, show higher sensitivity to TPT than freshwater organisms.
Fig. 2. The comparison of TPT criteria among different countries and regions (a DEFRA, 2017; b Yi et al., 2012; c CCME, 1992; d Roessink et al., 2006).
The WQC of TPT derived in this study were listed in Table 2 and compared with the published studies (Fig. 2). The HC5 values were used for comparison for acute criterion among different countries and regions, while the PNEC values and published regulation limits were employed for chronic criterion. The HC5 values of 117 ng Sn L-1 derived by Yi et al. (2012) and 3.1 μg Sn L-1 (930 ng Sn L-1) quantified by Roessink et al. (2006) were approximate to the corresponding value of 133 ng Sn L-1 and 791 ng Sn L-1 derived in this study, for marine and freshwater species, respectively, which indicates that the toxicity threshold levels were similar among different countries and regions. Significant difference in chronic criteria was however observed ranging from 0.3 ng Sn L-1 in UK (DEFRA, 2017) to 6.78 ng Sn L-1 in Canada (CCME, 1992). As shown in Fig. 2, both saltwater and freshwater PNEC values (4.11 and 5.60 ng Sn L-1) in this study were close to the water quality limit in Canada. The saltwater PNEC value in this study (4.11 ng Sn L-1) is however much higher than the limit of 0.64 ng Sn L-1 reported in Yi et al. (2012), probably due to the different selection of ACR and AF values.
3.5. The ecological risk of TPT in aquatic environment of China TPT concentrations in surface waters of China were presented in Supplementary Material S5. The concentrations in saltwater range from not detected to 17.2 ng Sn L-1 with an average of 8.21 ng Sn L-1, while those in freshwater range from not detected to 37.2 ng Sn L-1 with an average of 4.70 ng Sn L-1. TPT pollution in marine environment is therefore more serious than in freshwater system. Based on the exposure data, the derived criteria and the species sensitivity distribution curves of TPT, a four-level approach of tiered ecological risk assessment was presented as follows:
3.4. Disparity between saltwater and freshwater criteria As shown in Fig. 1, the SSD curves for saltwater species lied far to the left of those for freshwater species. Consequently, the derived acute saltwater CMC value was only about one sixth of the freshwater CMC, indicating higher sensitivity of saltwater species. The chronic criteria 399
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Level 1: Based on the derived acute and chronic saltwater criteria of TPT (66.5 ng Sn L-1 and 4.11 ng Sn L-1), the first-level ecological risk assessment was conducted through Hazard Quotient method. The acute HQ values ranged from 0.001 to 0.350 in coastal environment of China, reflecting negligible risk to saltwater species except in Yangtze River estuarine area. The chronic HQ values ranged from 0.014 to 5.669. The percentage of potential risk (0.3≤HQ≤1) and clear risk (HQ > 1) accounted for 28.6% and 57.1%, respectively. Similarly, based on acute and chronic freshwater criteria (396 and 5.60 ng Sn L-1), the acute risk was also ranked as negligible with an HQ value of < 0.3, whereas the chronic risk was much more serious with HQ values ranging from 0.348 to 1.33, indicating potential risk or even clear risk. The results of HQ method demonstrated that both freshwater and saltwater species are under serious risk in case of long-term exposure. Nevertheless, the HQ method could not provide detailed information on probability or magnitude of ecological risks (Wang et al., 2009). Probabilistic methods were therefore applied for further assessment. Due to a shortage of TPT exposure data in freshwater environment, the following risk assessment based on exposure concentration distribution (ECD) were applied only for saltwater environment.
Fig. 4. The joint probability curves (JPC) for acute and chronic exposure of TPT in coastal waters of China.
Level 2: The exposure concentration distribution (ECD) of TPT in coastal waters of China was shown in Fig. 3. Based on the ECD, the cumulative distribution probability at the point of saltwater criteria (SCMC and SCCC) was calculated as 93.0% and 54.1%, respectively. The probability of exceeding SCMC and SCCC was, therefore, 7.0% and 45.9%, respectively. Chronic risk of TPT in coastal waters of China was considerably higher than acute risk. Level 3: The margin of safety (MOS10) values were calculated as 5.21 and 0.32, for acute and chronic risk, respectively (Fig. 3). The chronic risk of TPT in coastal waters of China was again much higher than the acute risk. The overall probability (ORP) was calculated as 0.71% and 9.44% considering acute and chronic risk, respectively (Fig. 4). The chronic risk of TPT was therefore categorized as clear level, whereas the acute risk as potential level. The exceedance probability for 5% of species was quantified as 3.02% and 31.9% for acute and chronic toxicity, respectively. Level 4: Based on Monte Carlo simulation, the distribution-based quotient (DBQ) value for potential risk (HQ=0.3) was calculated as 2.40% and 20.79% for acute and chronic effect, respectively (Fig. 5). The DBQ value for clear risk (HQ=1.0) was quantified as 0.68% and 9.69% for acute and chronic effect, respectively. The chronic risk of TPT in coastal waters of China was again
Fig. 5. The exceedance probability curves of TPT in coastal waters of China based on Monte Carlo simulation.
demonstrated as being much higher than the acute risk. 4. Conclusion With wide application and high toxicity, TPT may pose threats to numerous non-target species. Up to date, the ecological risk assessment could not be performed for this emerging contaminant without suitable criteria. This study aimed to establish water quality criteria for TPT through model simulation with toxicity data tested on aquatic organisms of China. Through the construction of species sensitivity distribution models, the acute (CMC) and chronic (CMC) criteria in saltwater environment were derived as 66.5 and 4.11 ng Sn L-1, respectively. The CMC and CCC in freshwater were derived as 396 and 5.60 ng Sn L-1, respectively. The saltwater criteria are lower than freshwater counterparts, indicating stronger bioavailability and toxicity of TPT related to higher salinity and pH values in marine environment. A tiered ERA approach demonstrated that the chronic risk of TPT was clear in coastal waters. Mitigation measures for this emerging pollutant therefore warrants further concern. Acknowledgement
Fig. 3. The cumulative frequency distribution curves for exposure and effective concentrations of TPT in coastal waters of China.
This work was supported by the National Natural Science Foundation of China (No. 41476090) and the Chinese Major Science 400
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and Technology Program for Water Pollution Control and Treatment (No. 2017ZX07301-002).
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Contents lists available at ScienceDirect
Ecotoxicology and Environmental Safety journal homepage: www.elsevier.com/locate/ecoenv
Water quality criteria derivation and ecological risk assessment for triphenyltin in China Jingjing Wena, Xiaoying Cuia,b, Mark Gibsonc, Zhengyan Lia,b,
T
⁎
a
College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, PR China Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, Qingdao 266100, PR China c Department of Process Engineering and Applied Science, Dalhousie University, Halifax, NS, Canada B3J 2X4 b
A R T I C LE I N FO
A B S T R A C T
Keywords: TPT Species sensitivity distribution Ecological risk assessment Criterion maximum concentration Criterion continuous concentration
Triphenyltin (TPT) is one of the most toxic chemicals artificially discharged into aquatic environment with human activities. Due to its intensive use in antifouling paints and adverse effects on non-target species, TPT has aroused wide concern in both saltwater and freshwater environment. Nevertheless, the water quality criteria (WQC) are not available in China, which impedes the risk assessment for this emerging pollutant. This study aims to establish the WQC of TPT for both freshwater and saltwater ecosystems. With the derived WQC, a fourlevel tiered ecological risk assessment (ERA) approach was employed to assess the ecological risks of this emerging pollutant in Chinese waters. Through the species sensitivity distribution (SSD) methodology, the freshwater criterion maximum concentration (CMC) and criterion continuous concentration (CCC) were derived as 396 ng Sn L-1 and 5.60 ng Sn L-1, respectively, whereas the saltwater CMC and CCC were 66.5 ng Sn L-1 and 4.11 ng Sn L-1, respectively. The ecological risk assessment for TPT demonstrated that the acute risk was negligible whereas the chronic risk was significant with HQ (Hazard Quotient) values of up to 5.669 and 57.1% of coastal waters in China facing clear risk. TPT contamination in coastal environment, therefore, warrants further concern.
1. Introduction Triphenyltin (TPT) compounds are triphenyl derivatives of tetravalent tin with a general formula of (C6H5)3Sn-X, typically existing as chloride, hydroxide and acetate compounds (Yi et al., 2012). TPT, together with TBT (tributyltin), has been widely applied in antifouling paints and fungicides since 1960s. In European countries and USA, TBT was the main ingredient in organotin based antifouling paints. In China, however, TPT was the mainly used organotin product with an annual manufacturing amount of 150–200 t (Hu et al., 2006; 2009). Due to its properties of persistence, bioaccumulation and toxicity, TPT has received wide concern. TPT exerts endocrine disrupting effects on various aquatic species including gastropods and fishes (Horiguchi et al., 1994; Santos et al., 2006; Zhang et al., 2008; Sun et al., 2011), causing reproductive failure and population decrease at extremely low concentrations of nanogram per liter. Consequently, the usage of organotin-based antifouling paints was prohibited in many countries and regions throughout the world (Chau et al., 1997). The international ban for organotins was also initiated by IMO (International Maritime Organization) in 2001 (IMO, 2001). In China, although TBT is regulated, TPT is not restricted except for its usage as pesticides being prohibited ⁎
in 1999 in Taiwan (Meng et al., 2009). Due to the increasing demand for its usage in both industrial and agricultural sectors in China, TPT contamination in natural waters is to be expected (Cao et al., 2009). TPT in coastal waters of China was reported with concentrations from undetected to 17.2 ng Sn-1 (Wang et al., 2008, Liu et al., 2011, Hu et al., 2006, Huang, 1999). TPT was also reported in fresh water in the Yangtze River and Jialing River with a concentration of up to 37.2 ng Sn-1 (Gao et al., 2013). Water quality criteria (WQC) are defined as the permitted maximum concentration of chemicals without negative effects on organisms in aquatic environment (Yang et al., 2014). The two-number criteria system, including criterion continuous concentration (CCC) and criterion maximum concentration (CMC) is most commonly used in various countries, which is also adopted in this study. The combination of CMC and CCC provides an appropriate extent of protection for aquatic organisms from both acute and chronic toxicity (USEPA, 1985). According to the guidelines of US EPA, the ecological risk assessment (ERA) is aimed to determine the probability and degree of harmful ecological outcome of risk sources such as chemical exposure (USEPA, 1998). The most rudimentary approach of ERA is hazard quotients (HQ), usually expressed as a ratio between exposure and
Corresponding author at: College of Environmental Science and Engineering, Ocean University of China, Qingdao 266100, PR China. E-mail address: [email protected] (Z. Li).
https://doi.org/10.1016/j.ecoenv.2018.06.012 Received 18 July 2017; Received in revised form 25 December 2017; Accepted 23 January 2018 Available online 12 June 2018 0147-6513/ © 2018 Elsevier Inc. All rights reserved.
Ecotoxicology and Environmental Safety 161 (2018) 397–401
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Level 2 assessment calculates the likelihood that the measured concentrations exceed the preselected effect threshold by comparing the exposure concentration distribution (ECD) with the WQC. The log-normal model was adopted for constructing ECD after Kolmogorov-Smirnov test for normality. Level 3 assessment characterizes the risk through the overlap between SSD and ECD. Firstly, MOS10 (Margin of Safety at 10%) was quantified via the 10th percentile of SSD (SSD10) divided by the 90th percentile of ECD (ECD90). MOS10 values of < 1 indicate significant risk, whereas values of > 1 represent minimal risk to aquatic organisms. The MOS10 method therefore only provides general information of risk. To further characterize the risk, the Joint Probability Curve (JPC) generated from SSD and Exceedance Probability Function (EPF, or the reverse ECD) represents the probability of exceeding the pollutant concentration causing a certain degree of ecological effect (Wang et al., 2002). Based on JPC, the Overall Risk Probability (ORP) can be calculated as the area of JPC enclosed by the X-axis to identify the overall ecological risk. The risk level is ranked as negligible, potential and clear if the ORP value is < 0.1%, 0.1–1.0% and ≥1.0%, respectively (Wang et al., 2009). Level 4 assessment adopts Monte Carlo random sampling from ECD and SSD for 20,000 times and consequently calculates the distribution-based quotient (DBQ). The risk is expressed as the likelihood of exceeding the preselected HQ values (0.3 or 1.0).
toxicity concentrations. Despite its simplicity and effectiveness, the quotients do not allow spatial or temporal analysis of the probability and magnitude of ecological risks (ECOFRAM, 1999). To obtain more reliable estimates of risks, ERA based on probabilistic analysis, which quantifies the risk through probability distributions of both exposure and effect, are recommended for higher level assessment (Solomon and Sibley, 2002). This study aims to develop the WQC of TPT considering both exposure duration (acute and chronic) and water types (saltwater and freshwater). Based on the WQC, the ecological risk of TPT in aquatic environment of China were comprehensively evaluated with a tiered ERA approach. 2. Materials and methods 2.1. Screening of toxicity data The toxicity data of TPT were screened from open databases and literature in this study. Only the toxicity data tested with Chinese resident species were selected. For acute toxicity data, short-term (48 h or 96 h) LC50 or EC50 (median lethal or effective concentration) values were adopted. While for chronic data, long-term (≥14 days) NOEC (no observed effect concentration) values referring to traditional toxicity endpoints such as survival and growth were used. The toxicity data referring to molecular biomarker endpoints were however excluded. The geometric mean was employed when multiple data was available tested with the same species (Guo et al., 2015). The toxicity values of TPT selected for criteria derivation in this study is listed in Supplementary Material S1–S2.
3. Results and discussion 3.1. Acute and chronic toxicity data of TPT Table 1 presents the statistical parameters for acute and chronic datasets of TPT to both freshwater and saltwater species. The AndersonDarling test showed that the toxicity data could be fit with log-normal distribution. A two-sample t test indicated that both acute and chronic data showed significant difference between freshwater and saltwater (Pacute < 0.01, Pchronic < 0.05). It is, therefore, necessary to derive saltwater and freshwater criteria separately to avoid over or under protection of aquatic species.
2.2. The derivation of water quality criteria Nowadays, the SSD (species sensitivity distribution) methodology is increasingly adopted in water quality criteria derivation (Wik, 2008). This methodology is based on the hypothesis that the tested species are representative, in terms of sensitivity, of the total species in an ecosystem (Ciffroy and Brebbia, 2007). SSD is used to predict Hazardous Concentration affecting p% of all species in an ecosystem (HCp), usually selecting 5% as the acceptable fraction affected and therefore 95% species being protected. Based on the value of HC5 derived with the SSD model, the Predicted No Effect Concentration (PNEC) could be determined through being divided by an Assessment Factor (AF). The choice of AF depends on the richness of toxicity data and the goodness of model simulation (ECB, 2003; Gao et al., 2014). Currently an AF of 2 is used in most studies when the toxicity data covers at least three phylum and eight families (USEPA, 1985; Guo et al., 2015; Park et al., 2018). The same AF value was also applied in the criterion derivation process in this study to ensure the consistency of results. Although various distributions have been utilized to construct SSD models, the log-normal distribution is most commonly used with its advantage of in depth analysis for various uncertainties, which is also adopted in this study for SSD construction.
3.2. Acute WQC for TPT The SSD models were constructed based on the acute data of TPT to saltwater and freshwater species, respectively (Fig. 1a). The HC5 (hazardous concentration to 5% of species) values were calculated as 0.133 μg Sn L-1 (90% confidence interval: 0.039–0.290 μg Sn L-1) and 0.791 μg Sn L-1 (90% confidence interval: 0.273–1.652 μg Sn L-1) respectively for saltwater and freshwater species. With the HC5 values, the PNEC values could be calculated by being divided with an AF of 2, which is also defined as WQC for TPT. Consequently, the CMC (criterion maximum concentration) in saltwater and freshwater was derived as 0.067 μg Sn L-1 and 0.396 μg Sn L-1, respectively. 3.3. Chronic water quality criteria of TPT
2.3. Ecological risk assessment
Considering the scarcity of chronic toxicity data, the method of Acute to Chronic Ratio (ACR) was used to supplement saltwater chronic data. A final ACR value of 18.1 was adopted as the geometric mean of all ACR values (Supplementary Material S3). During the simulation of SSD curves for saltwater species, both the raw data and ACR extrapolated data were pooled (Supplementary Material S4). During the simulation of SSD curves for freshwater species, however, only the raw data was used since they were sufficient for model simulation. Based on SSD simulation, the HC5 values for saltwater and freshwater species were quantified as 0.0082 μg Sn L-1 and 0.011 μg Sn L-1, respectively (Fig. 1b). Consequently, the CCC (criterion continuous concentration) was derived as 0.0041 μg Sn L-1 and 0.0056 μg Sn L-1 for saltwater and freshwater environment.
The risk assessment of TPT was conducted based on a four-level tiered ERA approach recommended by ECOFRAM (1999) and developed by Zolezzi et al. (2005) and Wang et al. (2009). The assessment approach is as follows: Level 1 assessment involves a deterministic hazard quotient (HQ), i.e., a ratio between MEC (measured environmental concentration) and PNEC values. The PNEC was referred to the derived criteria of TPT. The risk level is determined as negligible, potential and clear based on HQ values with the corresponding range of 0–0.3, 0.3–1.0 and over 1.0, respectively. 398
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Fig. 1. The SSD curves for acute (left) and chronic (right) toxicity of TPT (circle, square and triangle representing algal, invertebrate and vertebrate species, respectively).
showed a similar phenomenon. This difference in response to TPT toxicity is probably related to discrepancy in taxonomic composition and chemical bioavailability between saltwater and freshwater ecosystems. First, the saltwater toxicity data contains a high proportion of algal (46.7%) and invertebrate species (33.3%) whereas the freshwater data covers more invertebrate (52.4%) and vertebrate species (28.6%). Algal species are usually not sensitive to organic pollutants, although direct comparison on relative vulnerability among algal, invertebrate and vertebrate species upon TPT toxicity is not available. Second, chemical speciation of TPT in aquatic environment is influenced by various factors of the medium, especially pH value and chloride (Cl-) content. In aquatic environment, TPT (e.g. TPT chloride) exists in both neutral forms (TPTOH and TPTCl) and ionic form (TPT+). The pH value influences the proportion of these two forms. With the increase of pH values, the proportion of neutral forms is higher (Tsuda et al., 1990). With a PKa value of 5.2 for TPT+ (Arnold et al., 1997), the proportion of these two forms can be calculated. When pH value changes from 6.5 to 8.0 (covering the scope of pH in all toxicity tests as shown in Supplementary Material S1–2), the proportion of neutral forms increases from 95.2% to 99.8%, whereas that of ionic form decreases from 4.76% to 0.16%. The neutral forms of TPT are more toxic than ionic form (Looser et al., 1998; White and Tobin, 2004). TPT in saltwater with higher pH values is therefore more toxic than that in freshwater. In addition, the neutral form of TPT can further be separated into two species, TPTOH and TPTCl. In fresh water, TPTCl is negligible, whereas in saltwater, TPTCl can reach up to a half of total neutral forms (White and Tobin, 2004). Considering the higher toxicity of TPTCl than TPTOH (White and Tobin, 2004), the high Cl- concentration in saltwater also enhances the toxicity of TPT. It can therefore be assumed that high pH value and Cl- concentration in saltwater would increase the toxicity of TPT. Saltwater species, therefore, show higher sensitivity to TPT than freshwater organisms.
Fig. 2. The comparison of TPT criteria among different countries and regions (a DEFRA, 2017; b Yi et al., 2012; c CCME, 1992; d Roessink et al., 2006).
The WQC of TPT derived in this study were listed in Table 2 and compared with the published studies (Fig. 2). The HC5 values were used for comparison for acute criterion among different countries and regions, while the PNEC values and published regulation limits were employed for chronic criterion. The HC5 values of 117 ng Sn L-1 derived by Yi et al. (2012) and 3.1 μg Sn L-1 (930 ng Sn L-1) quantified by Roessink et al. (2006) were approximate to the corresponding value of 133 ng Sn L-1 and 791 ng Sn L-1 derived in this study, for marine and freshwater species, respectively, which indicates that the toxicity threshold levels were similar among different countries and regions. Significant difference in chronic criteria was however observed ranging from 0.3 ng Sn L-1 in UK (DEFRA, 2017) to 6.78 ng Sn L-1 in Canada (CCME, 1992). As shown in Fig. 2, both saltwater and freshwater PNEC values (4.11 and 5.60 ng Sn L-1) in this study were close to the water quality limit in Canada. The saltwater PNEC value in this study (4.11 ng Sn L-1) is however much higher than the limit of 0.64 ng Sn L-1 reported in Yi et al. (2012), probably due to the different selection of ACR and AF values.
3.5. The ecological risk of TPT in aquatic environment of China TPT concentrations in surface waters of China were presented in Supplementary Material S5. The concentrations in saltwater range from not detected to 17.2 ng Sn L-1 with an average of 8.21 ng Sn L-1, while those in freshwater range from not detected to 37.2 ng Sn L-1 with an average of 4.70 ng Sn L-1. TPT pollution in marine environment is therefore more serious than in freshwater system. Based on the exposure data, the derived criteria and the species sensitivity distribution curves of TPT, a four-level approach of tiered ecological risk assessment was presented as follows:
3.4. Disparity between saltwater and freshwater criteria As shown in Fig. 1, the SSD curves for saltwater species lied far to the left of those for freshwater species. Consequently, the derived acute saltwater CMC value was only about one sixth of the freshwater CMC, indicating higher sensitivity of saltwater species. The chronic criteria 399
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Level 1: Based on the derived acute and chronic saltwater criteria of TPT (66.5 ng Sn L-1 and 4.11 ng Sn L-1), the first-level ecological risk assessment was conducted through Hazard Quotient method. The acute HQ values ranged from 0.001 to 0.350 in coastal environment of China, reflecting negligible risk to saltwater species except in Yangtze River estuarine area. The chronic HQ values ranged from 0.014 to 5.669. The percentage of potential risk (0.3≤HQ≤1) and clear risk (HQ > 1) accounted for 28.6% and 57.1%, respectively. Similarly, based on acute and chronic freshwater criteria (396 and 5.60 ng Sn L-1), the acute risk was also ranked as negligible with an HQ value of < 0.3, whereas the chronic risk was much more serious with HQ values ranging from 0.348 to 1.33, indicating potential risk or even clear risk. The results of HQ method demonstrated that both freshwater and saltwater species are under serious risk in case of long-term exposure. Nevertheless, the HQ method could not provide detailed information on probability or magnitude of ecological risks (Wang et al., 2009). Probabilistic methods were therefore applied for further assessment. Due to a shortage of TPT exposure data in freshwater environment, the following risk assessment based on exposure concentration distribution (ECD) were applied only for saltwater environment.
Fig. 4. The joint probability curves (JPC) for acute and chronic exposure of TPT in coastal waters of China.
Level 2: The exposure concentration distribution (ECD) of TPT in coastal waters of China was shown in Fig. 3. Based on the ECD, the cumulative distribution probability at the point of saltwater criteria (SCMC and SCCC) was calculated as 93.0% and 54.1%, respectively. The probability of exceeding SCMC and SCCC was, therefore, 7.0% and 45.9%, respectively. Chronic risk of TPT in coastal waters of China was considerably higher than acute risk. Level 3: The margin of safety (MOS10) values were calculated as 5.21 and 0.32, for acute and chronic risk, respectively (Fig. 3). The chronic risk of TPT in coastal waters of China was again much higher than the acute risk. The overall probability (ORP) was calculated as 0.71% and 9.44% considering acute and chronic risk, respectively (Fig. 4). The chronic risk of TPT was therefore categorized as clear level, whereas the acute risk as potential level. The exceedance probability for 5% of species was quantified as 3.02% and 31.9% for acute and chronic toxicity, respectively. Level 4: Based on Monte Carlo simulation, the distribution-based quotient (DBQ) value for potential risk (HQ=0.3) was calculated as 2.40% and 20.79% for acute and chronic effect, respectively (Fig. 5). The DBQ value for clear risk (HQ=1.0) was quantified as 0.68% and 9.69% for acute and chronic effect, respectively. The chronic risk of TPT in coastal waters of China was again
Fig. 5. The exceedance probability curves of TPT in coastal waters of China based on Monte Carlo simulation.
demonstrated as being much higher than the acute risk. 4. Conclusion With wide application and high toxicity, TPT may pose threats to numerous non-target species. Up to date, the ecological risk assessment could not be performed for this emerging contaminant without suitable criteria. This study aimed to establish water quality criteria for TPT through model simulation with toxicity data tested on aquatic organisms of China. Through the construction of species sensitivity distribution models, the acute (CMC) and chronic (CMC) criteria in saltwater environment were derived as 66.5 and 4.11 ng Sn L-1, respectively. The CMC and CCC in freshwater were derived as 396 and 5.60 ng Sn L-1, respectively. The saltwater criteria are lower than freshwater counterparts, indicating stronger bioavailability and toxicity of TPT related to higher salinity and pH values in marine environment. A tiered ERA approach demonstrated that the chronic risk of TPT was clear in coastal waters. Mitigation measures for this emerging pollutant therefore warrants further concern. Acknowledgement
Fig. 3. The cumulative frequency distribution curves for exposure and effective concentrations of TPT in coastal waters of China.
This work was supported by the National Natural Science Foundation of China (No. 41476090) and the Chinese Major Science 400
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and Technology Program for Water Pollution Control and Treatment (No. 2017ZX07301-002).
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