Environmental Risk Assessment Strategy for Nanomaterials
An Environmental Risk Assessment (ERA) for nanomaterials (NMs) is outlined in this paper. Contrary to other recent papers on the subject, the main data requirements, models and advancement within each of the four risk assessment domains are described, i.e., in the: (i) materials, (ii) release, fate...
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Published in | International journal of environmental research and public health Vol. 14; no. 10; p. 1251 |
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Main Authors | , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
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19.10.2017
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ISSN | 1660-4601 1661-7827 1660-4601 |
DOI | 10.3390/ijerph14101251 |
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Abstract | An Environmental Risk Assessment (ERA) for nanomaterials (NMs) is outlined in this paper. Contrary to other recent papers on the subject, the main data requirements, models and advancement within each of the four risk assessment domains are described, i.e., in the: (i) materials, (ii) release, fate and exposure, (iii) hazard and (iv) risk characterisation domains. The material, which is obviously the foundation for any risk assessment, should be described according to the legislatively required characterisation data. Characterisation data will also be used at various levels within the ERA, e.g., exposure modelling. The release, fate and exposure data and models cover the input for environmental distribution models in order to identify the potential (PES) and relevant exposure scenarios (RES) and, subsequently, the possible release routes, both with regard to which compartment(s) NMs are distributed in line with the factors determining the fate within environmental compartment. The initial outcome in the risk characterisation will be a generic Predicted Environmental Concentration (PEC), but a refined PEC can be obtained by applying specific exposure models for relevant media. The hazard information covers a variety of representative, relevant and reliable organisms and/or functions, relevant for the RES and enabling a hazard characterisation. The initial outcome will be hazard characterisation in test systems allowing estimating a Predicted No-Effect concentration (PNEC), either based on uncertainty factors or on a NM adapted version of the Species Sensitivity Distributions approach. The risk characterisation will either be based on a deterministic risk ratio approach (i.e., PEC/PNEC) or an overlay of probability distributions, i.e., exposure and hazard distributions, using the nano relevant models. |
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AbstractList | An Environmental Risk Assessment (ERA) for nanomaterials (NMs) is outlined in this paper. Contrary to other recent papers on the subject, the main data requirements, models and advancement within each of the four risk assessment domains are described, i.e., in the: (i) materials, (ii) release, fate and exposure, (iii) hazard and (iv) risk characterisation domains. The material, which is obviously the foundation for any risk assessment, should be described according to the legislatively required characterisation data. Characterisation data will also be used at various levels within the ERA, e.g., exposure modelling. The release, fate and exposure data and models cover the input for environmental distribution models in order to identify the potential (PES) and relevant exposure scenarios (RES) and, subsequently, the possible release routes, both with regard to which compartment(s) NMs are distributed in line with the factors determining the fate within environmental compartment. The initial outcome in the risk characterisation will be a generic Predicted Environmental Concentration (PEC), but a refined PEC can be obtained by applying specific exposure models for relevant media. The hazard information covers a variety of representative, relevant and reliable organisms and/or functions, relevant for the RES and enabling a hazard characterisation. The initial outcome will be hazard characterisation in test systems allowing estimating a Predicted No-Effect concentration (PNEC), either based on uncertainty factors or on a NM adapted version of the Species Sensitivity Distributions approach. The risk characterisation will either be based on a deterministic risk ratio approach (i.e., PEC/PNEC) or an overlay of probability distributions, i.e., exposure and hazard distributions, using the nano relevant models. An Environmental Risk Assessment (ERA) for nanomaterials (NMs) is outlined in this paper. Contrary to other recent papers on the subject, the main data requirements, models and advancement within each of the four risk assessment domains are described, i.e., in the: (i) materials, (ii) release, fate and exposure, (iii) hazard and (iv) risk characterisation domains. The material, which is obviously the foundation for any risk assessment, should be described according to the legislatively required characterisation data. Characterisation data will also be used at various levels within the ERA, e.g., exposure modelling. The release, fate and exposure data and models cover the input for environmental distribution models in order to identify the potential (PES) and relevant exposure scenarios (RES) and, subsequently, the possible release routes, both with regard to which compartment(s) NMs are distributed in line with the factors determining the fate within environmental compartment. The initial outcome in the risk characterisation will be a generic Predicted Environmental Concentration (PEC), but a refined PEC can be obtained by applying specific exposure models for relevant media. The hazard information covers a variety of representative, relevant and reliable organisms and/or functions, relevant for the RES and enabling a hazard characterisation. The initial outcome will be hazard characterisation in test systems allowing estimating a Predicted No-Effect concentration (PNEC), either based on uncertainty factors or on a NM adapted version of the Species Sensitivity Distributions approach. The risk characterisation will either be based on a deterministic risk ratio approach (i.e., PEC/PNEC) or an overlay of probability distributions, i.e., exposure and hazard distributions, using the nano relevant models.An Environmental Risk Assessment (ERA) for nanomaterials (NMs) is outlined in this paper. Contrary to other recent papers on the subject, the main data requirements, models and advancement within each of the four risk assessment domains are described, i.e., in the: (i) materials, (ii) release, fate and exposure, (iii) hazard and (iv) risk characterisation domains. The material, which is obviously the foundation for any risk assessment, should be described according to the legislatively required characterisation data. Characterisation data will also be used at various levels within the ERA, e.g., exposure modelling. The release, fate and exposure data and models cover the input for environmental distribution models in order to identify the potential (PES) and relevant exposure scenarios (RES) and, subsequently, the possible release routes, both with regard to which compartment(s) NMs are distributed in line with the factors determining the fate within environmental compartment. The initial outcome in the risk characterisation will be a generic Predicted Environmental Concentration (PEC), but a refined PEC can be obtained by applying specific exposure models for relevant media. The hazard information covers a variety of representative, relevant and reliable organisms and/or functions, relevant for the RES and enabling a hazard characterisation. The initial outcome will be hazard characterisation in test systems allowing estimating a Predicted No-Effect concentration (PNEC), either based on uncertainty factors or on a NM adapted version of the Species Sensitivity Distributions approach. The risk characterisation will either be based on a deterministic risk ratio approach (i.e., PEC/PNEC) or an overlay of probability distributions, i.e., exposure and hazard distributions, using the nano relevant models. |
Author | Tran, Lang Semenzin, Elena Hund‐Rinke, Kerstin Peijnenburg, Willie Hristozov, Danail Scott‐Fordsmand, Janeck Jiménez, Araceli Sánchez Bos, Peter Irfan, Muhammad‐Adeel Nowack, Bernd Landsiedel, Robert Marcomini, Antonio Hunt, Neil Oomen, Agnes |
AuthorAffiliation | 6 The REACH Centre, Gordon Manley Building, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK; N.Hunt@thereachcentre.com 4 Department of Environmental Sciences, Informatics and Statistics, University Ca’ Foscari of Venice, VEGApark, Via delle Industrie 21/8, 30175 Marghera (VE), Italy; Semenzin@unive.it (E.S.); Danail.Hristozov@unive.it (D.H.); marcom@unive.it (A.M.) 3 Centre for Environmental Sciences, University Leiden, P.O. Box 9518, 2300 RA Leiden, The Netherlands 9 Institute of Occupational Medicine, Centre for Human Exposure Science (CHES), Research Avenue North, Riccarton, Edinburgh EH14 4AP, UK; Araceli.Sanchez@iom-world.org (A.S.J.); lang.tran@iom-world.org (L.T.) 7 Greendecision Srl., Via delle Industrie 21/8, 30175 Marghera (VE), Italy 1 Department of Bioscience, Aarhus University, Vejlsøvej 25, P.O. Box 314, 8600 Silkeborg, Denmark 2 National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; Willie.Peij |
AuthorAffiliation_xml | – name: 8 Experimental Toxicology and Ecology, BASF SE, RB/TB-Z470, 67056 Ludwigshafen, Germany; muhammad-adeel.irfan@basf.com (M.-A.I.) robert.landsiedel@basf.com (R.L.) – name: 1 Department of Bioscience, Aarhus University, Vejlsøvej 25, P.O. Box 314, 8600 Silkeborg, Denmark – name: 6 The REACH Centre, Gordon Manley Building, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK; N.Hunt@thereachcentre.com – name: 9 Institute of Occupational Medicine, Centre for Human Exposure Science (CHES), Research Avenue North, Riccarton, Edinburgh EH14 4AP, UK; Araceli.Sanchez@iom-world.org (A.S.J.); lang.tran@iom-world.org (L.T.) – name: 5 Swiss Federal Laboratories for Material Science and Technology, EMPA, 8600 Dübendorf, Switzerland; Bernd.Nowack@empa.ch – name: 2 National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720 BA Bilthoven, The Netherlands; Willie.Peijnenburg@rivm.nl (W.J.G.M.P.); Agnes.Oomen@rivm.nl (A.G.O.); Peter.Bos@rivm.nl (P.M.J.B.) – name: 7 Greendecision Srl., Via delle Industrie 21/8, 30175 Marghera (VE), Italy – name: 3 Centre for Environmental Sciences, University Leiden, P.O. Box 9518, 2300 RA Leiden, The Netherlands – name: 4 Department of Environmental Sciences, Informatics and Statistics, University Ca’ Foscari of Venice, VEGApark, Via delle Industrie 21/8, 30175 Marghera (VE), Italy; Semenzin@unive.it (E.S.); Danail.Hristozov@unive.it (D.H.); marcom@unive.it (A.M.) – name: 10 Fraunhofer Institute for Molecular Biology and Applied Ecology, Auf dem Aberg 1, 57392 Schmallenberg, Germany; Kerstin.Hund-Rinke@ime.fraunhofer.de |
Author_xml | – sequence: 1 givenname: Janeck surname: Scott‐Fordsmand fullname: Scott‐Fordsmand, Janeck – sequence: 2 givenname: Willie orcidid: 0000-0003-2958-9149 surname: Peijnenburg fullname: Peijnenburg, Willie – sequence: 3 givenname: Elena surname: Semenzin fullname: Semenzin, Elena – sequence: 4 givenname: Bernd surname: Nowack fullname: Nowack, Bernd – sequence: 5 givenname: Neil surname: Hunt fullname: Hunt, Neil – sequence: 6 givenname: Danail surname: Hristozov fullname: Hristozov, Danail – sequence: 7 givenname: Antonio surname: Marcomini fullname: Marcomini, Antonio – sequence: 8 givenname: Muhammad‐Adeel surname: Irfan fullname: Irfan, Muhammad‐Adeel – sequence: 9 givenname: Araceli Sánchez surname: Jiménez fullname: Jiménez, Araceli Sánchez – sequence: 10 givenname: Robert surname: Landsiedel fullname: Landsiedel, Robert – sequence: 11 givenname: Lang surname: Tran fullname: Tran, Lang – sequence: 12 givenname: Agnes surname: Oomen fullname: Oomen, Agnes – sequence: 13 givenname: Peter surname: Bos fullname: Bos, Peter – sequence: 14 givenname: Kerstin surname: Hund‐Rinke fullname: Hund‐Rinke, Kerstin |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29048395$$D View this record in MEDLINE/PubMed |
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Title | Environmental Risk Assessment Strategy for Nanomaterials |
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