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Nanotechnology applications (nanoproducts) have entered the market or are expected to do so in the near future. Robust and science-based criteria are required to appraise and manage their sustainability. This paper describes the approach used to develop a comprehensive and reliable framework of criteria, which was missing until now, for evaluating the sustainability of nanoproducts. A literature review of the frameworks and tools employed to assess nanoproducts sustainability implications was firstly performed to select an initial set of criteria. A survey of experts in the sustainable nanotechnology domain was then conducted to elicit their knowledge in terms of completeness, reliability and validity of the criteria set. Ranking and correlation analyses completed the research by identifying the parameters of major interest as well as the links and dependencies between them. A total of 54 and 65 experts replied to the pilot and main survey, respectively. The reliability and validity of the criteria was assessed with the responses from both questionnaires, whereas the answers from the main survey were used to calculate the relative index of the criteria as well as their correlations. This research resulted in a framework composed of 68 criteria, which are structured into six main areas: (i) economic performance; (ii) environmental impacts, (iii) environmental risk assessment; (iv) human health risk assessment; (v) social implications and (vi) technical performance. This study helps to broaden the understanding on the identification of criteria for sustainability assessments. It also provides those interested in evaluating nanotechnology implications with the basis for real case studies, possibly by integrating available information with the stakeholders using tools that support decision-making. [ABSTRACT FROM AUTHOR]

The assessment of the implementation of green chemistry principles in the syntheses of nanomaterials is a complex decision-making problem that necessitates the integration of several evaluation criteria. Multiple Criteria Decision Aiding (MCDA) provides support for such a challenge. One of its methods – Dominance-based Rough Set Approach (DRSA) – was used in this research to develop a model for the green chemistry-based classification of silver nanoparticle synthesis protocols into preference-ordered performance classes. DRSA allowed integration of knowledge from both peer-reviewed literature and experts (decision makers, DMs) in the field, resulting in a model composed of decision rules that are logical statements in the form: “if conditions, then decision”. The approach provides the basis for the design of rules for the greener synthesis of silver nanoparticles. Decision rules are supported by synthesis protocols that enforce the principles of green chemistry to various extents, resulting in robust recommendations for the development and assessment of silver nanoparticle synthesis that perform at one of five pre-determined levels. The DRSA-based approach is transparent and structured and can be easily updated. New perspectives and criteria could be added into the model if relevant data were available and domain-specific experts could collaborate through the MCDA procedure. [ABSTRACT FROM AUTHOR]

Sustainability assessments require the management of a wide variety of information types, parameters and uncertainties. Multi criteria decision analysis (MCDA) has been regarded as a suitable set of methods to perform sustainability evaluations as a result of its flexibility and the possibility of facilitating the dialogue between stakeholders, analysts and scientists. However, it has been reported that researchers do not usually properly define the reasons for choosing a certain MCDA method instead of another. Familiarity and affinity with a certain approach seem to be the drivers for the choice of a certain procedure. This review paper presents the performance of five MCDA methods (i.e. MAUT, AHP, PROMETHEE, ELECTRE and DRSA) in respect to ten crucial criteria that sustainability assessments tools should satisfy, among which are a life cycle perspective, thresholds and uncertainty management, software support and ease of use. The review shows that MAUT and AHP are fairly simple to understand and have good software support, but they are cognitively demanding for the decision makers, and can only embrace a weak sustainability perspective as trade-offs are the norm. Mixed information and uncertainty can be managed by all the methods, while robust results can only be obtained with MAUT. ELECTRE, PROMETHEE and DRSA are non-compensatory approaches which consent to use a strong sustainability concept, accept a variety of thresholds, but suffer from rank reversal. DRSA is less demanding in terms of preference elicitation, is very easy to understand and provides a straightforward set of decision rules expressed in the form of elementary “if … then …” conditions. Dedicated software is available for all the approaches with a medium to wide range of results capability representation. DRSA emerges as the easiest method, followed by AHP, PROMETHEE and MAUT, while ELECTRE is regarded as fairly difficult. Overall, the analysis has shown that most of the requirements are satisfied by the MCDA methods (although to different extents) with the exclusion of management of mixed data types and adoption of life cycle perspective which are covered by all the considered approaches. [ABSTRACT FROM AUTHOR]