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Improving structure and transparency in reliability evaluations of data under REACH: suggestions for a systematic method
Human and Ecological Risk Assessment ( IF 3.0 ) Pub Date : 2019-01-15 , DOI: 10.1080/10807039.2018.1504275
Ellen Ingre-Khans 1 , Marlene Ågerstrand 1 , Christina Rudén 1 , Anna Beronius 2
Affiliation  

Abstract

The goal of identifying hazardous chemicals registered under the Registration, Evaluation, Authorization and restriction of CHemicals (REACH) Regulation and taking appropriate risk management measures relies on robust data registrations. However, the current procedures for European chemical manufacturers and importers to evaluate data under REACH neither support systematic evaluations of data nor transparently communicate these assessments. The aim of this study was to explore how using a data evaluation method with predefined criteria for reliability and establishing principles for assigning reliability categories could contribute to more structured and transparent evaluations under REACH. In total, 20 peer-reviewed studies for 15 substances registered under REACH were selected for an in-depth evaluation of reliability with the SciRAP tool. The results show that using a method for study evaluation, with clear criteria for assessing reliability and assigning studies to reliability categories, contributes to more structured and transparent reliability evaluations. Consequently, it is recommended to implement a method for evaluating data under REACH with predefined criteria and fields for documenting and justifying the assessments to increase consistency of data evaluations and transparency.



中文翻译:

改善REACH下数据可靠性评估的结构和透明度:系统方法的建议

摘要

识别根据《化学品注册,评估,授权和限制》(REACH)法规注册的危险化学品并采取适当风险管理措施的目标取决于可靠的数据注册。但是,欧洲化学品制造商和进口商根据REACH评估数据的现行程序既不支持数据的系统评估,也不能透明地传达这些评估。这项研究的目的是探索使用具有预定义的可靠性标准的数据评估方法以及建立用于分配可靠性类别的原则如何有助于在REACH下进行更加结构化和透明的评估。总共选择了针对REACH注册的15种物质的20项同行评审研究,以使用SciRAP工具对可靠性进行深入评估。结果表明,使用一种研究评估方法,具有明确的评估可靠性标准并将研究分配给可靠性类别的方法,有助于进行更加结构化和透明的可靠性评估。因此,建议实施一种具有预定义标准和字段的REACH数据评估方法,以记录和证明评估结果,以提高数据评估的一致性和透明度。

更新日期:2020-01-07
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