An approach for environmental risk assessment of engineered nanomaterials using Analytical Hierarchy Process (AHP) and fuzzy inference rules

Topuz E., van Gestel C. A. M.

ENVIRONMENT INTERNATIONAL, pp.334-347, 2016 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2016
  • Doi Number: 10.1016/j.envint.2016.04.022
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.334-347
  • Istanbul Technical University Affiliated: Yes


The usage of Engineered Nanoparticles (ENPs) in consumer products is relatively new and there is a need to conduct environmental risk assessment (ERA) to evaluate their impacts on the environment. However, alternative approaches are required for ERA of ENPs because of the huge gap in data and knowledge compared to conventional pollutants and their unique properties that make it difficult to apply existing approaches. This study aims to propose an ERA approach for ENPs by integrating Analytical Hierarchy Process (AHP) and fuzzy inference models which provide a systematic evaluation of risk factors and reducing uncertainty about the data and information, respectively. Risk is assumed to be the combination of occurrence likelihood, exposure potential and toxic effects in the environment. A hierarchy was established to evaluate the sub factors of these components. Evaluation was made with fuzzy numbers to reduce uncertainty and incorporate the expert judgements. Overall score of each component was combined with fuzzy inference rules by using expert judgements. Proposed approach reports the risk class and its membership degree such as Minor (0.7). Therefore, results are precise and helpful to determine the risk management strategies. Moreover, priority weights calculated by comparing the risk factors based on their importance for the risk enable users to understand which factor is effective on the risk. Proposed approach was applied for Ag (two nanoparticles with different coating) and TiO2 nanoparticles for different case studies. Results verified.the proposed. benefits of the approach. (C) 2016 Elsevier Ltd. All rights reserved.