Derivation of Soil Ecological Criteria for Copper in Chinese Soils.

Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Xiaoqing Wang [verfasserIn] Dongpu Wei [verfasserIn] Yibing Ma [verfasserIn] Mike J McLaughlin [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2015

Übergeordnetes Werk:	In: PLoS ONE - Public Library of Science (PLoS), 2007, 10(2015), 7, p e0133941
Übergeordnetes Werk:	volume:10 ; year:2015 ; number:7, p e0133941

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1371/journal.pone.0133941

Katalog-ID:	DOAJ054501733

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allfields	10.1371/journal.pone.0133941 doi (DE-627)DOAJ054501733 (DE-599)DOAJac7b3976614c49a89dea7ce6888e3210 DE-627 ger DE-627 rakwb eng Xiaoqing Wang verfasserin aut Derivation of Soil Ecological Criteria for Copper in Chinese Soils. 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils. Medicine R Science Q Dongpu Wei verfasserin aut Yibing Ma verfasserin aut Mike J McLaughlin verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 10(2015), 7, p e0133941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:10 year:2015 number:7, p e0133941 https://doi.org/10.1371/journal.pone.0133941 kostenfrei https://doaj.org/article/ac7b3976614c49a89dea7ce6888e3210 kostenfrei http://europepmc.org/articles/PMC4514794?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2015 7, p e0133941
spelling	10.1371/journal.pone.0133941 doi (DE-627)DOAJ054501733 (DE-599)DOAJac7b3976614c49a89dea7ce6888e3210 DE-627 ger DE-627 rakwb eng Xiaoqing Wang verfasserin aut Derivation of Soil Ecological Criteria for Copper in Chinese Soils. 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils. Medicine R Science Q Dongpu Wei verfasserin aut Yibing Ma verfasserin aut Mike J McLaughlin verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 10(2015), 7, p e0133941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:10 year:2015 number:7, p e0133941 https://doi.org/10.1371/journal.pone.0133941 kostenfrei https://doaj.org/article/ac7b3976614c49a89dea7ce6888e3210 kostenfrei http://europepmc.org/articles/PMC4514794?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2015 7, p e0133941
allfields_unstemmed	10.1371/journal.pone.0133941 doi (DE-627)DOAJ054501733 (DE-599)DOAJac7b3976614c49a89dea7ce6888e3210 DE-627 ger DE-627 rakwb eng Xiaoqing Wang verfasserin aut Derivation of Soil Ecological Criteria for Copper in Chinese Soils. 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils. Medicine R Science Q Dongpu Wei verfasserin aut Yibing Ma verfasserin aut Mike J McLaughlin verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 10(2015), 7, p e0133941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:10 year:2015 number:7, p e0133941 https://doi.org/10.1371/journal.pone.0133941 kostenfrei https://doaj.org/article/ac7b3976614c49a89dea7ce6888e3210 kostenfrei http://europepmc.org/articles/PMC4514794?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2015 7, p e0133941
allfieldsGer	10.1371/journal.pone.0133941 doi (DE-627)DOAJ054501733 (DE-599)DOAJac7b3976614c49a89dea7ce6888e3210 DE-627 ger DE-627 rakwb eng Xiaoqing Wang verfasserin aut Derivation of Soil Ecological Criteria for Copper in Chinese Soils. 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils. Medicine R Science Q Dongpu Wei verfasserin aut Yibing Ma verfasserin aut Mike J McLaughlin verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 10(2015), 7, p e0133941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:10 year:2015 number:7, p e0133941 https://doi.org/10.1371/journal.pone.0133941 kostenfrei https://doaj.org/article/ac7b3976614c49a89dea7ce6888e3210 kostenfrei http://europepmc.org/articles/PMC4514794?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2015 7, p e0133941
allfieldsSound	10.1371/journal.pone.0133941 doi (DE-627)DOAJ054501733 (DE-599)DOAJac7b3976614c49a89dea7ce6888e3210 DE-627 ger DE-627 rakwb eng Xiaoqing Wang verfasserin aut Derivation of Soil Ecological Criteria for Copper in Chinese Soils. 2015 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils. Medicine R Science Q Dongpu Wei verfasserin aut Yibing Ma verfasserin aut Mike J McLaughlin verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 10(2015), 7, p e0133941 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:10 year:2015 number:7, p e0133941 https://doi.org/10.1371/journal.pone.0133941 kostenfrei https://doaj.org/article/ac7b3976614c49a89dea7ce6888e3210 kostenfrei http://europepmc.org/articles/PMC4514794?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2015 7, p e0133941
language	English
source	In PLoS ONE 10(2015), 7, p e0133941 volume:10 year:2015 number:7, p e0133941
sourceStr	In PLoS ONE 10(2015), 7, p e0133941 volume:10 year:2015 number:7, p e0133941
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authorswithroles_txt_mv	Xiaoqing Wang @@aut@@ Dongpu Wei @@aut@@ Yibing Ma @@aut@@ Mike J McLaughlin @@aut@@
publishDateDaySort_date	2015-01-01T00:00:00Z
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author	Xiaoqing Wang
spellingShingle	Xiaoqing Wang misc Medicine misc R misc Science misc Q Derivation of Soil Ecological Criteria for Copper in Chinese Soils.
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topic_title	Derivation of Soil Ecological Criteria for Copper in Chinese Soils
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title	Derivation of Soil Ecological Criteria for Copper in Chinese Soils.
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title_full	Derivation of Soil Ecological Criteria for Copper in Chinese Soils
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title_sort	derivation of soil ecological criteria for copper in chinese soils
title_auth	Derivation of Soil Ecological Criteria for Copper in Chinese Soils.
abstract	Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils.
abstractGer	Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils.
abstract_unstemmed	Considerable information on copper (Cu) ecotoxicity as affected by biological species and abiotic properties of soils has been collected from the last decade in the present study. The information on bioavailability/ecotoxicity, species sensitivity and differences in laboratory and field ecotoxicity of Cu in different soils was collated and integrated to derive soil ecological criteria for Cu in Chinese soils, which were expressed as predicted no effect concentrations (PNEC). First, all ecotoxicity data of Cu from bioassays based on Chinese soils were collected and screened with given criteria to compile a database. Second, the compiled data were corrected with leaching and aging factors to minimize the differences between laboratory and field conditions. Before Cu ecotoxicity data were entered into a species sensitivity distribution (SSD), they were normalized with Cu ecotoxicity predictive models to modify the effects of soil properties on Cu ecotoxicity. The PNEC value was set equal to the hazardous concentration for x% of the species (HCx), which could be calculated from the SSD curves, without an additional assessment factor. Finally, predictive models for HCx based on soil properties were developed. The soil properties had a significant effect on the magnitude of HCx, with HC5 varying from 13.1 mg/kg in acidic soils to 51.9 mg/kg in alkaline non-calcareous soils. The two-factor predictive models based on soil pH and cation exchange capacity could predict HCx with determination coefficients (R2) of 0.82-0.91. The three-factor predictive models--that took into account the effect of soil organic carbon--were more accurate than two-factor models, with R2 of 0.85-0.99. The predictive models obtained here could be used to calculate soil-specific criteria. All results obtained here could provide a scientific basis for revision of current Chinese soil environmental quality standards, and the approach adopted in this study could be used as a pragmatic framework for developing soil ecological criteria for other trace elements in soils.
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title_short	Derivation of Soil Ecological Criteria for Copper in Chinese Soils.
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Derivation of Soil Ecological Criteria for Copper in Chinese Soils.

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