National (Iranian) and global use of control banding-based methods for assessing the risks of activities involved with nanomaterials: a comparative review

Shekaftik, Soqrat Omari; Moghadasi, Narges; Nasirzadeh, Nafiseh

doi:10.1007/s11051-023-05800-8

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…Nowadays, the use of nanomaterials in a various industrial processing, products, and healthcare applications has widely spread 11 , 12 . Due to the lack of a clear toxicological basis for setting nanomaterial-specific occupational exposure limits 13 – 15 , it is necessary to assess the risk of nanomaterial hazards 16 – 18 .…”

Section: Introductionmentioning

confidence: 99%

“…Occupational health risk assessments are crucial in identifying and mitigating these occupational risks 21 , 22 . Control Banding (CB) methods such as CB Nanotool, Stoffenmanager Nano created in The Netherlands, and CB Tool from the French Agency for Food and Act, are employed as categories criteria, or "bands," for occupational and health risk assessment, which combined with parameters to determine desired levels of control measures 18 , 23 .…”

Section: Introductionmentioning

confidence: 99%

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An integrated approach to occupational health risk assessment of manufacturing nanomaterials using Pythagorean Fuzzy AHP and Fuzzy Inference System

Salari,

Sadeghi-Yarandi,

Golbabaei

2024

Sci Rep

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Nanomaterials (NMs) have the potential to be hazardous owing to their unique physico-chemical properties. Therefore, the need for Health Risk Assessment (HRA) of NMs is expanding. In this study, a novel HRA was developed by the Pythagorean Fuzzy Health Risk Assessment (PFHRA) approach. Risk is considered to be the outcome of parameters including Occurrence Likelihood (OL), Potential Exposure (PE) and Toxic Effects (TE). In our proposed method, priority weights of sub-factors in Pythagorean Fuzzy-Analytical Hierarchical Process (PF-AHP) were determined by pairwise comparison based on expert judgment. After determining parameter scores, both RM and risk class (i.e., negligible, minor, major and critical) were reported as Fuzzy Inference System (FIS) output. Ultimately, a risk management strategy is presented for NMs manufacturing workplaces. This proposed method provides experts with more flexibility to express their opinions. The PFHRA approach was applied for two scenarios. The production scenario for SiNPs can create minor (5%) and major (95%) occupational health risks; the production scenario for ZnONPs can create minor (100%) concerns. However, the production SiNPs and ZnONPs utilizing the CB Nanotool technique had a major and minor risk class, respectively. The results of the present study confirmed the reliability and applicability of this approach.

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