Study of using biological effect ratio (BER) method to predict the aquatic life criteria in China
WANG Xiao-nan1, YAN Zhen-guang1, LIU Zheng-tao1, WANG Wan-hua1, ZHANG Cong2
1. State Key Laboratory of Environmental Criteria and Risk Assessment, State Environmental Protection Key Laboratory of Ecological Effects and Risk Assessment of Chemicals, Chinese Research Academy of Environmental Sciences, Beijing 100012, China;
2. China Offshore Environmental Services Co., Ltd., Tianjin 300452, China
In this study, predicted aquatic life criteria using biological effect ratio (BER) method based on the difference of species sensitivity between China and the USA was investigated. First, pollutants with acute toxicity data from 3Phyla and 8Families that both in China and the USA were selected. Second, the different biological groups were developed for BER method based on the sensitivity and representation of species of the two countries. Third, effective BER method was selected based on the comparison of predicted criteria maximum concentration (CMC) and the measured CMC. Results showed that: 9pollutants of As(III), Cr(VI), Hg, Cu, Zn, Pb, parathion, chlorpyrifos and TBT both in China and the USA were selected, and the measured CMCs for protecting the Chinese native aquatic species were derived to be 201.72, 2.64, 0.74, 1.32, 55.83, 92.25, 0.12, 0.36 and 0.38μg/L, respectively. Moreover, comparison of predicted criteria and the measured criteria of 7different biological groups for BER method showed that BER method of biological groups based on the same genera or family could predict the CMCs of 9pollutants in China well. The result of this study could provide useful information for predicting CMC making full use of the existed toxicity data or just carrying out less toxicity test when toxicity data of native species is lacking.
王晓南, 闫振广, 刘征涛, 王婉华, 张聪. 生物效应比(BER)技术预测我国水生生物基准探讨[J]. 中国环境科学, 2016, 36(1): 276-285.
WANG Xiao-nan, YAN Zhen-guang, LIU Zheng-tao, WANG Wan-hua, ZHANG Cong. Study of using biological effect ratio (BER) method to predict the aquatic life criteria in China. CHINA ENVIRONMENTAL SCIENCECE, 2016, 36(1): 276-285.
Jin X, Zha J, Xu Y, et al. Derivation of aquatic predicted no-effect concentration (PNEC) for 2, 4-dichlorophenol:Comparing native species data with non-native species data[J]. Chemosphere, 2011,84(10):1506-1511.
[17]
Wang X, Liu Z, Yan Z, et al. Development of aquatic life criteria for triclosan and comparison of the sensitivity between native and non-native species[J]. Journal of hazardous materials, 2013,260:1017-1022.
[18]
Yan Z, Zhang Z, Wang H, et al. Development of aquatic life criteria for nitrobenzene in China[J]. Environmental Pollution, 2012,162:86-90.
[19]
Yang S, Yan Z, Xu F, et al. Development of freshwater aquatic life criteria for tetrabromobisphenol A in China[J]. Environmental Pollution, 2012,169:59-63.
[20]
US EPA. Guidelines for deriving numerical national water quality criteria for the protection of aquatic organisms and their uses (PB 85-227049)[R]. Duluth, Minnesota, Narragansett, Rhode Island; Corvallis, Oregon, USA:Office of Research and Development, Environmental Research Laboratories, U.S. Environmental Protection Agency, 1985.
[21]
ANZECC A. Australian and New Zealand guidelines for fresh and marine water quality[R]. Canberra,Australia:Australian and New Zealand Environment and Conservation Council, Agriculture and Resource Management Council of Australia and New Zealand, 2000.
[22]
Davies P, Cook L, Goenarso D. Sublethal responses to pesticides of several species of Australian freshwater fish and crustaceans and rainbow trout[J]. Environmental Toxicology and Chemistry, 1994,13(8):1341-1354.
[23]
中国科学院.中国动物志[M]. 北京:科学出版社, 1979.
[24]
Wang X, Yan Z, Liu Z, et al. Comparison of species sensitivity distributions for species from China and the USA[J]. Environmental Science and Pollution Research, 2014,21(1):168-176.
[25]
USEPA. Web-based interspecies correlation estimation (Web-ICE) for acute toxicity:User manual[M]. Gulf Breeze:USEPA, Office of Research and Development, 2013.
Dyer S, Versteeg D, Belanger S, et al. Comparison of species sensitivity distributions derived from interspecies correlation models to distributions used to derive water quality criteria[J]. Environmental Science and Technology, 2008,42(8):3076-3083.
[28]
Dyer S, Versteeg D, Belanger S, et al. Interspecies correlation estimates predict protective environmental concentrations[J]. Environmental Science and Technology, 2006,40(9):3102-3111.
[29]
Blum D, Speece R. Determining chemical toxicity to aquatic species[J]. Environmental Science and Technology, 1990,24(3):284-293.
[30]
Feng C, Wu F, Dyer S, et al. Derivation of freshwater quality criteria for zinc using interspecies correlation estimation models to protect aquatic life in China[J]. Chemosphere, 2013,90(3):1177-1183.
[31]
Wu F, Mu Y, Chang H, et al. Predicting water quality criteria for protecting aquatic life from physicochemical properties of metals or metalloids[J]. Environmental Science and Technology, 2012,47(1):446-453.
[32]
Awkerman J, Raimondo S, Barron M. Development of species sensitivity distributions for wildlife using interspecies toxicity correlation models[J]. Environmental Science and Technology, 2008,42(9):3447-3452.
US EPA. 1995Updates:water quality criteria documents for the protection of aquatic life in ambient water[R]. Office of Water, United States Environmental Protection Agency, 1996.
RIVM. Guidance document on deriving environmental risk limits in the Netherlands. Report No. 601501012[R]. Bilthoven,the Netherlands:National Institute of Public Health and the Environment, 2001.
[68]
USEPA. Water quality standards handbook[M]. Washington DC:Office of Water, 1994.
