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 inInternational journal of environmental research and public health Vol. 14; no. 10; p. 1251
Main Authors Scott‐Fordsmand, Janeck, Peijnenburg, Willie, Semenzin, Elena, Nowack, Bernd, Hunt, Neil, Hristozov, Danail, Marcomini, Antonio, Irfan, Muhammad‐Adeel, Jiménez, Araceli Sánchez, Landsiedel, Robert, Tran, Lang, Oomen, Agnes, Bos, Peter, Hund‐Rinke, Kerstin
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 19.10.2017
MDPI
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ISSN1660-4601
1661-7827
1660-4601
DOI10.3390/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.
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
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  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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Snippet An Environmental Risk Assessment (ERA) for nanomaterials (NMs) is outlined in this paper. Contrary to other recent papers on the subject, the main data...
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StartPage 1251
SubjectTerms Environmental science
Nanomaterials
Risk assessment
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Title Environmental Risk Assessment Strategy for Nanomaterials
URI https://www.ncbi.nlm.nih.gov/pubmed/29048395
https://www.proquest.com/docview/1965687987
https://www.proquest.com/docview/1953295696
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