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Environmental Science and Pollution Research

, Volume 21, Issue 22, pp 12968–12978 | Cite as

Weighted species sensitivity distribution method to derive site-specific quality criteria for copper in Tai Lake, China

  • Rui Shi
  • Chunhui Yang
  • Runhua Su
  • Jiarui Jin
  • Yi Chen
  • Hongling LiuEmail author
  • John P. Giesy
  • Hongxia Yu
Research Article

Abstract

Tai Lake (Ch: Taihu), which is the largest lake in Jiangsu province, China, has been affected by human activities. As part of a concerted effort to improve water quality to protect the integrity of the Tai Lake ecosystem, a water quality criterion (WQC) was developed for copper (Cu) II. The acute WQC was based on 440 values for acute toxicity of Cu to 24 species from 6 phyla, 16 families, and 20 genera. In addition, 255 values for chronic toxicity of Cu to 10 species from 5 phyla, 8 families, and 9 genera were used to derive chronic WQC. Instead of using a traditional approach based species sensitivity distributions (SSD), a weighted species sensitivity distribution (WSSD) approach was used to calculate the cumulative probability based on endemic species to Tai Lake. Acute and chronic WQC developed by use of the WSSD were 5.3 and 3.7 μg Cu/L, respectively. While the WQC values were comparable to those of other countries, there were slight differences due to variability in species composition of different regions. The site-specific criteria indicated that the current standard set for surface water by the Chinese government might not be protective of aquatic organisms in Tai Lake.

Keywords

Weighted species sensitivity distributions Probabilistic Asia Model Statistics 

Notes

Acknowledgments

This work was jointly funded by the National Natural Science Foundation of China (No. 21377053 and 20977047), Major National Science and Technology Projects (No. 2012ZX07506-001 and 2012ZX07501-003-02). Prof. Giesy was supported by the program of 2012 “High Level Foreign Experts” (No. GDW20123200120) funded by the State Administration of Foreign Experts Affairs, the People’s Republic of China to Nanjing University, and the Einstein Professor Program of the Chinese Academy of Sciences. He was also supported by the Canada Research Chair program, a Visiting Distinguished Professorship in the Department of Biology and Chemistry and State Key Laboratory in Marine Pollution, City University of Hong Kong. Great thanks to David Saunders, a vanier scholar in ecotoxicology studying in Toxicology Centre, University of Saskatchewan, for his time in polishing our manuscript.

Supplementary material

11356_2014_3156_MOESM1_ESM.docx (128 kb)
ESM 1 (DOCX 127 kb)

References

  1. ANZE, Australian and New Zealand Environment Conservation Council and Agriculture and Resource Management Council of Australia and New Zealand (2000) Australia and New Zealand guidelines for fresh and marine water quality [R]. ANZECC and ARMCANZ, AustraliaGoogle Scholar
  2. Baatrup E (1999) Structural and function effects of heavy metals on the nervous system, including sense organs of fish [J]. Comp Biochem Physiol 100C:253–257. doi: 10.1016/0742-8413(91)90163-N Google Scholar
  3. CCME, Canadian Council of Ministers of the Environment (1999) Protocol for the derivation of water quality guidelines for the protection of aquatic life [R]. Canadian Council of Ministers of the Environment, WinnipegGoogle Scholar
  4. Chapman PM, Wang F, Janssen C et al (1998) Ecotoxicology of metals in aquatic sediments: binding and release, bioavailability, risk assessment, and remediation [J]. Can J Fish Aquat Sci 55(10):2221–2243. doi: 10.1139/f98-145 CrossRefGoogle Scholar
  5. Chen JC, Lin CH (2001) Toxicity of copper sulfate for survival, growth, molting and feeding of juveniles of the tiger shrimp, Penaeusmonodon [J]. Aquaculture 192:55–65. doi: 10.1016/S0044-8486(00)00442-7 CrossRefGoogle Scholar
  6. Chen Y, Huang J, Xing LQ et al (2014) Effects of multi-generational exposures of D. magna to environmentally relevant concentrations of pentachlorophenol [J]. Environ Sci Pollut Res 21:234–243. doi: 10.1007/s11356-013-1692-z CrossRefGoogle Scholar
  7. China EPA, China State Environmental Protection Administration (2002) GB3838-2002. Environmental quality standard for surface water (in Chinese). China Standards Press, BeijingGoogle Scholar
  8. Di Toro DM, Allen HE, Bergman HL et al (2001) Biotic ligand model of the acute toxicity of metals. 1. Technical basis. Environ Toxicol Chem 20(10):2383–2396. doi: 10.1897/1551-5028 (2001) 0202.0.CO;2 CrossRefGoogle Scholar
  9. Duboudin C, Ciffroy P, Magaud H (2004) Effects of data manipulation and statistical methodson species sensitivity distributions [J]. Environ Toxicol Chem 23(2):489–499. doi: 10.1897/03-159 CrossRefGoogle Scholar
  10. EMEA (2004a) Committee for Medicinal Products for Veterinary Use (CVMP): Guideline on environmental impact assessment for veterinary medicinal products phase II. European Medicines Agency Veterinary Medicines and Inspections. EMEA, London, UKGoogle Scholar
  11. EMEA (2004b) Committee for Medicinal Products for Human Use (CHMP): Guideline on the environmental risk assessment of medicinal products for human use. European Medicines Agency Pre-Authorization Evaluation of Medicines for Human Use. EMEA, London, UKGoogle Scholar
  12. European Commission (2003) Technical guidance document in support of Commission Directive 93/67/EEC on risk assessment for new notified substances. Commission Regulation (EC) 1488/94 on risk assessment for existing substances and Directive 98/8/EC of the European Parliament and of the Council concerning the placing of biocidal products on the market. Ispra, Italy, p328Google Scholar
  13. Feng CL, Wu FC, Zhao XL et al (2012) Water quality criteria research and progress [J]. Sci China Earth Sci 55(6):882–891. doi: 10.1007/s11430-012-4384-5 CrossRefGoogle Scholar
  14. Forbes VE, Calow P (2002) Species sensitivity distributions revisited: a critical appraisal [J]. Hum Ecol Risk Assess 8(3):473–492. doi: 10.1080/10807030290879781 CrossRefGoogle Scholar
  15. Forbes TL, Forbes VE (1993) A critique of the use of distribution based extrapolation models in ecotoxicology [J]. Funct Ecol 7:249–254CrossRefGoogle Scholar
  16. Giesy JP, Solomon KR, Coats JR et al (1999) Ecological risk assessment of Chlorpyrifos in North American aquatic environments [J]. Rev Environ Contam Toxicol 160:121–129. doi: 10.1007/978-1-4612-1498-4_1 Google Scholar
  17. Hall LW, Scott MC, Killen WD (1998) Ecological risk assessment of copper and cadmium in surface waters of Chesapeake Bay watershed [J]. Environ Toxicol Chem 17:1172–1189CrossRefGoogle Scholar
  18. Jin X, Zha J, Xu Y et al (2012a) Toxicity of pentachlorophenol to native aquatic species in the Yangtze River [J]. Environ Sci Pollut Res 19:609–618. doi: 10.1007/s11356-011-0594-1 CrossRefGoogle Scholar
  19. Jin X, Zha J, Xu Y et al (2012b) Derivation of predicted no effect concentrations (PNEC) for 2,4,6-trichlorophenol based on Chinese resident species [J]. Chemosphere 86:17–23. doi: 10.1016/j.chemosphere.2011.08.040 CrossRefGoogle Scholar
  20. Jin X, Wang Z, Giesy JP et al (2014) Development of aquatic life criteria in China: viewpoint on the challenge [J]. Environ Sci Pollut Res 21:234–243. doi: 10.1007/s11356-013-1667-0 CrossRefGoogle Scholar
  21. Klimisch HJ, Andreae M, Tillmann U (1997) A systematic approach for evaluating the quality of experimental toxicological and ecotoxicological data [J]. Regul Toxicol Pharmacol 25(1):1–5. doi: 10.1006/rtph.1996.1076 CrossRefGoogle Scholar
  22. Kooijman SALM (1987) A safety factor for LC50 values allowing for differences in sensitivity among species [J]. Water Res 21:269–276. doi: 10.1016/0043-1354(87)90205-3 CrossRefGoogle Scholar
  23. Li US, Wu FC, Cui XY et al (2013) Derivation of an aquatic predicted no-effect concentration for endocrine disruptor effects of 17β-estradiol. Rev Environ Contam Toxicol 228:31–56Google Scholar
  24. Liu YD, Wu FC, Mu Y-S et al (2014) Setting water quality criteria in China: approaches for developing species sensitivity distributions for metals and metalloids [J]. Rev Environ Contam Toxicol 230:35–58. doi: 10.1007/978-3-319-04411-8_2 Google Scholar
  25. McCormick FH, Hill BH, Parrish LP et al (1994) Mining impacts on fish assemblages in the Eagle and Arkansas rivers, Colorado [J]. J Freshwater Ecol 9:175–179. doi: 10.1080/02705060.1994.9664884 CrossRefGoogle Scholar
  26. Meng W, Zhang Y, Zheng BH (2006) The quality criteria, standards of water environment and the water pollutant control strategy on watershed [J]. Res Environ Sci 19:1–3 (in Chinese)Google Scholar
  27. Mu YS, Wu FC, Chen C et al (2014) Predicting criteria continuous concentrations of 34 metals or metalloids by use of quantitative ion character-activity relationships species sensitivity distributions (QICAReSSD) model [J]. Environ Pollut 188:50–55. doi: 10.1016/j.envpol.2014.01.011 CrossRefGoogle Scholar
  28. Posthuma L, Suter GW II, Traas TP (eds) (2002) Species-sensitivity distributions in ecotoxicology. Lewis, Boca Raton, FL, USAGoogle Scholar
  29. Santore RC, Di Toro DM, Paquin PR et al (2001) Biotic ligand model of the acute toxicity of metals. 2. Application to acute copper toxicity in freshwater fish and Daphnia [J]. Environ Toxicol Chem 20(10):2397–2402. doi: 10.1002/etc.5620201035 CrossRefGoogle Scholar
  30. Schuler L, Hoang T, Rand G (2008) Aquatic risk assessment of copper in freshwater and saltwater ecosystems of South Florida. Ecotoxicology 17:642–659. doi: 10.1007/s10646-008-0236-7 CrossRefGoogle Scholar
  31. Stephan CE, Mount DI, Hansen DJ et al (1985) Guidelines for deriving numerical national water quality criteria for the protection of aquatic organisms and their uses. PB85-227049. National Technical Information Service, Springfield, VA, USAGoogle Scholar
  32. Su Hailei (2011) The aquatic biota characteristics of Tai Lake and its relationship with the derivation of lake water quality criteria in China. Chinese Research Academy of Environmental Sciences, Thesis of Master DegreeGoogle Scholar
  33. Su HL, Wu F-C, Zhang R-Q et al (2014) Toxicity reference values for protecting aquatic birds in China from effects of polychlorinated biphenyls. Rev Environ Contam Toxicol 230:59–82Google Scholar
  34. Suter GW, Cormier SM (2008) What is meant by risk-based environmental quality criteria [J]? Integr Environ Assess Manag 4:486–489. doi: 10.1897/IEAM_2008-017.1 CrossRefGoogle Scholar
  35. US EPA, United States Environment Protection Agency (2006) National recommended water quality criteria. Office of Water, Office of Science and Technology, WashingtonGoogle Scholar
  36. Van Sprang PA, Verdonck FAM, Vanrolleghem PA et al (2004) Probabilistic environmental risk assessment of zinc in Dutch surface waters [J]. Environ Toxicol Chem 23:2993–300. doi: 10.1897/03-444.1 CrossRefGoogle Scholar
  37. Wheeler JR, Grist EPM, Leung KMY et al (2002) Species sensitivity distributions: data and model choice [J]. Mar Pollut Bull 45:192–202. doi: 10.1016/S0025-326X(01)00327-7 CrossRefGoogle Scholar
  38. Wu FC, Meng W, Zhao XL et al (2010) China embarking on development of its own national water quality criteria system [J]. Environ Sci Technol 44:7992–7993. doi: 10.1021/es1029365 CrossRefGoogle Scholar
  39. Wu FC, Feng CL, Cao YJ et al (2011) Aquatic life ambient freshwater quality criteria for copper in China [J]. Asian J Ecotoxicol 6(6):617–628 (in Chinese)Google Scholar
  40. Wu FC, Mu YS, Hong C et al (2013) Predicting water quality criteria for protecting aquatic life from physico-chemical properties of metals [J]. Environ Sci Technol 47:446–453CrossRefGoogle Scholar
  41. Xing LQ, Liu HL, Giesy JP et al (2012) pH-dependent aquatic criteria for 2,4-dichlorophenol, 2,4,6-trichlorophenol and pentachlorophenol [J]. Sci Total Environ 441C:125–131. doi: 10.1016/j.scitotenv.2012.09.060 CrossRefGoogle Scholar
  42. Xing LQ, Liu HL, Zhang XW et al (2014) A comparison of statistical methods for deriving freshwater quality criteria for the protection of aquatic organisms [J]. Environ Sci Pollut Res 21:159–167. doi: 10.1007/s11356-013-1462-y CrossRefGoogle Scholar
  43. Yin DQ, Jin HJ, Yu LW et al (2003) Deriving freshwater quality criteria for 2,4-dichlorophenol for protection of aquatic life in China [J]. Environ Pollut 122:217–222. doi: 10.1016/S0269-7491(02)00292-0 CrossRefGoogle Scholar
  44. Zhang R, Wu FC, Li HX et al (2013) Toxicity reference values and tissue residue criteria for protection of avian wildlife exposed to methylmercury in China. Rev Environ Contam Toxicol 223:53–80Google Scholar
  45. Zhou QX, Luo Y, Zhu LY (2007) Scientific research on environmental benchmark values and revision of national environmental standards in China [J]. J Agron-Environ Sci 26(1):1–5 (in Chinese)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Rui Shi
    • 1
  • Chunhui Yang
    • 1
  • Runhua Su
    • 1
  • Jiarui Jin
    • 1
  • Yi Chen
    • 1
  • Hongling Liu
    • 1
    Email author
  • John P. Giesy
    • 1
    • 2
    • 3
  • Hongxia Yu
    • 1
  1. 1.State Key Laboratory of Pollution Control and Resource Reuse, School of the EnvironmentNanjing UniversityNanjingChina
  2. 2.Department of Veterinary Biomedical Sciences and Toxicology CentreUniversity of SaskatchewanSaskatoonCanada
  3. 3.State Key Laboratory in Marine Pollution, Department of Biology and ChemistryCity University of Hong KongKowloonHong Kong

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