Marco Cinelli

A green chemistry-based classification model for the synthesis of silver nanoparticles

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.

Workshop on life cycle sustainability assessment: the state of the art and research needs—November 26, 2012, Copenhagen, Denmark

The interest in life cycle sustainability assessment (LCSA) is currently booming in the LCA community, culminating lately in the forthcoming special issue from the International Journal of Life Cycle Assessment fully devoted to the topic. In the available literature, LCSA has mainly been conceptualised as a combination of LCA, social life cycle assessment (SLCA) and environmental life cycle costing (LCC). With the publication of guidelines for performing SLCA (Andrews et al. 2009), the code of practice for LCC (Swarr et al. 2011) and the existing standards for LCA, this could indicate that the question of how to perform an LCSA has been solved. However, the scientific publications give evidence of the need of further discussing the topic, both at conceptual and methodological level. The topic of LCSAwas at the core of a workshop organised on 26th November 2012 in the framework of the SETAC Europe 18th LCA Case Study Symposium in Copenhagen, with a dual aim: (1) to discuss the different schools of thoughts on LCSA and (2) to outline a research agenda framework for enabling/improving LCSA. The workshop was structured as four sessions (presentations) followed by a discussion part among participants which resulted in the identification of several research areas considered important for the successful future development of LCSA methodology and applications. The presentations provided insights on different approaches to LCSA both at conceptual and methodological level. A short summary of the main conclusions of the presentations and the main research topics proposed during the discussions is explained in the following sections.

Co-constructive development of a green chemistry-based model for the assessment of nanoparticles synthesis

Nanomaterials (materials at the nanoscale, 10-9m) are extensively used in several industry sectors due to the improved properties they empower commercial products with. There is a pressing need to produce these materials more sustainably. This paper proposes a MCDA approach to assess the implementation of green chemistry principles as applied to the protocols for nanoparticles synthesis. In the presence of multiple green and environmentally oriented criteria, decision aiding is performed with a synergy of ordinal regression methods; preference information in the form of desired assignment for a subset of reference protocols is accepted. The classification models, indirectly derived from such information, are composed of an additive value function and a vector of thresholds separating the pre-defined and ordered classes. The method delivers a single representative model that is used to assess the relative importance of the criteria, identify the possible gains with improvement of the protocols evaluations and classify the non-reference protocols. Such precise recommendation is validated against the outcomes of robustness analysis exploiting the sets of all classification models compatible with all maximal subsets of consistent assignment examples. The introduced approach is used with real-world data concerning silver nanoparticles. It is proven to effectively resolve inconsistency in the assignment examples, tolerate ordinal and cardinal measurement scales, differentiate between inter- and intra-criteria attractiveness and deliver easily interpretable scores and class assignments. This work thoroughly discusses the learning insights that MCDA provided during the co-constructive development of the classification model, distinguishing between problem structuring, preference elicitation, learning, modeling and problem-solving stages.

Robustness analysis of a green chemistry-based model for the classification of silver nanoparticles synthesis processes

This paper proposes a robustness analysis based on Multiple Criteria Decision Aiding (MCDA). The ensuing model was used to assess the implementation of green chemistry principles in the synthesis of silver nanoparticles. Its recommendations were also compared to an earlier developed model for the same purpose to investigate concordance between the models and potential decision support synergies. A three-phase procedure was adopted to achieve the research objectives. Firstly, an ordinal ranking of the evaluation criteria used to characterize the implementation of green chemistry principles was identified through relative ranking analysis. Secondly, a structured selection process for an MCDA classification method was conducted, which ensued in the identification of Stochastic Multi-Criteria Acceptability Analysis (SMAA). Lastly, the agreement of the classifications by the two MCDA models and the resulting synergistic role of decision recommendations were studied. This comparison showed that the results of the two models agree between 76% and 93% of the simulation set-ups and it confirmed that different MCDA models provide a more inclusive and transparent set of recommendations. This integrative research confirmed the beneficial complementary use of MCDA methods to aid responsible development of nanosynthesis, by accounting for multiple objectives and helping communication of complex information in a comprehensive and traceable format, suitable for stakeholders and/or decision-makers with diverse backgrounds.

Towards a research agenda for the use of LCA in the impact assessment of policies

Life cycle thinking and life cycle assessment are vital elements of sustainability assessment and increasingly mentioned as being essential for informing decisions in a comprehensive and holistic manner in both business and policy contexts (Sala et al. 2013). The European Commission has recently released a Communication on Better regulation (CEC 2015a) in order to improve the policy making process. The Communication is complemented with a Better Regulation toolbox (CEC 2015b) which lists models and methods to be used for assessing impacts and benefits of policies, in the so called Bpolicy impact assessment^ step. Life cycle assessment is listed among the models, aiming at supporting the environmental assessment of impact and benefits associated to different policy options (Sala et al. 2016). Life cycle assessment (LCA) may play a relevant role all along the policy cycle, from policy anticipation and problem definition, to policy evaluation. Indeed, the life cycle perspective and the systemic approach to the evaluation of options is a crucial added value. However, when the scope of the assessment changes from the product (micro) scale to the system (meso-macro) scale, several improvements are required to benefit the most from the LCA methodology. Suitable frameworks, methods, and tools for system analysis are needed to properly develop sustainable policies on, e.g., bioeconomy, circular economy, resources efficiency, ecoinnovation and sustainable production, and consumption. This calls for reflecting upon current and future challenges of the application of LCA within the policy development cycle. The Joint Research Centre of the European Commission organized a workshop on the 13th and 14th of December 2016 aimed at discussing the role of LCA in the policy cycle with particular reference to the impact assessment (IA) step. The IA is the integrated process to assess and to compare the merits of a range of policy options designed to address a well-defined problem (CEC 2015a) and represents a well-established step in the European policy development. The workshop gathered relevant experts in the area of application of LCA to policy within and beyond the European Commission services. Overall, 37 experts participated in the workshop both from the EU institutions and from leading research centers and universities. The main objective was to identify relevant points for a research agenda for the use of LCA in IA, answering to crucial questions such as: Which methodological developments are needed to address the complexity of policy evaluation in LCA? How can scenario modeling and foresight studies further inform the LCA? How can LCA results be better presented in order to improve their interpretation and comprehensiveness to finally support policies? The IA of policy addresses the three pillars of sustainability, economic, social, and environmental. Some key features of LCA are particularly relevant for addressing sustainability problems, in particular: the life cycle perspective, the identification of the most important burdens and most relevant life cycle stages contributing to environmental and social impacts, the identification of environmental (and Responsible editor: Mary Ann Curran