CARBON FOOTPRINT OF MUNICIPAL SOLID WASTE COLLECTION IN THE TREVISO AREA (ITALY)

Carbon Footprint (CF) is an environmental indicator used in Life Cycle Assessment (LCA) that allows measuring the total amount of CO2 emissions caused directly or indirectly by an activity or accumulated through the life cycle stages of a product (ISO 14064-14067). In this article CF was used to analyse and assess the environmental impacts of the resources used for the collection of municipal solid waste by the company Contarina S.p.A. Contarina oversees waste management for part of the Treviso province (Italy), serving about 260,000 appliances in 50 municipalities distributed in the territory. The presented case study assessed CF of year 2015 related the whole fleet involved in door-to-door collection of municipal solid waste without taking into account treatment processes. In addition, a future scenario, in which part of the current fleet is replaced by compressed natural gas engine (CNG) based vehicles, was assessed and compared to the current status. The CF was performed by adapting the SimaPro software from PRè, one of the most widely used LCA software since the nineties, by introducing fuel based analysis and creating CNG lorries. The analysis aimed at improving sustainability of Contarina’s services while fostering an informed development and testing of new technologies aimed at reducing its overall greenhouse gas emissions

Assessment of Climate Change Impacts in the North Adriatic Coastal Area. Part II: Consequences for Coastal Erosion Impacts at the Regional Scale

Coastal erosion is an issue of major concern for coastal managers and is expected to increase in magnitude and severity due to global climate change. This paper analyzes the potential consequences of climate change on coastal erosion (e.g., impacts on beaches, wetlands and protected areas) by applying a Regional Risk Assessment (RRA) methodology to the North Adriatic (NA) coast of Italy. The approach employs hazard scenarios from a multi-model chain in order to project the spatial and temporal patterns of relevant coastal erosion stressors (i.e., increases in mean sea-level, changes in wave height and variations in the sediment mobility at the sea bottom) under the A1B climate change scenario. Site-specific environmental and socio-economic indicators (e.g., vegetation cover, geomorphology, population) and hazard metrics are then aggregated by means of Multi-Criteria Decision Analysis (MCDA) with the aim to provide an example of exposure, susceptibility, risk and damage maps for the NA region. Among seasonal exposure maps winter and autumn depict the worse situation in 2070–2100, and locally around the Po river delta. Risk maps highlight that the receptors at higher risk are beaches, wetlands and river mouths. The work presents the results of the RRA tested in the NA region, discussing how spatial risk mapping can be used to establish relative priorities for intervention, to identify hot-spot areas and to provide a basis for the definition of coastal adaptation and management strategies.publishedVersio

Decision Support for International Agreements Regulating Nanomaterials

Nanomaterials are handled in global value chains for many different products, albeit not always recognisable as nanoproducts. The global market for nanomaterials faces an uncertain future, as the international dialogue on regulating nanomaterials is still ongoing and risk assessment data are being collected. At the same time, regulators and civil society organisations complain about a lack of transparency about the presence of nanomaterials on the market. In the project on Sustainable nanotechnologies (SUN, www.sun-fp7.eu), a Decision Support System (SUNDS) has been developed, primarily for confidential use by risk and sustainability managers inside a company or consortium. In this article, we formulate a scenario concerning a potential role for an open access decision support system in negotiations on international agreements regulating trade in nanomaterials. The scenario includes design rules for decision support systems as well as procedures for use of such a system in stakeholder dialogue and policy-making on governance of these and other emerging technologies. This article incorporates analysis of results of stakeholder engagement on nanomaterials as well as literature and internet sources suggested by these stakeholders

Comparing mental models of prospective users of the sustainable nanotechnology decision support system

Mental modelling analysis can be a valuable tool in understanding and bridging cognitive values in multi-stakeholders' communities. It is especially true in situation of emerging risks where significant uncertainty and competing objectives could result in significant difference in stakeholder perspective on the use of new materials and technologies. This paper presents a mental modelling study performed among prospective users of an innovative decision support system for safe and sustainable development of nano-enabled products. These users included representatives of industry and regulators, as well as several insurance specialists and researchers. We present methodology and tools for comparing stakeholder views and objectives in the context of developing a decision support system

A battery-less NFC sensor transponder for museum artefact monitoring - a review of NFC sensor technology and a proposed solution

This paper presents a novel, low-cost, battery-less Near-Field Communication (NFC) sensor transponder for museum artefact monitoring of Cultural Heritage objects. The proposed solution combines a unique combination of packaging materials and NFC technology to enable a low-cost preventive conservation solution that is practical to implement, something that is not possible at present. Cultural Heritage objects and artefacts are valuable objects housed by museums and are often stored in uncontrolled climatic conditions, which may lead to degradation of these objects. Preventive conservation is a new strategy that aims to avoid future degradation of these types of valuable objects. Recently, NFC sensor transponders have shown an increased use in food and pharmaceutical cold supply chains for monitoring, but these commercial solutions are expensive to implement and cannot be easily adapted for museum artefact monitoring. In this work, we present a battery-less, long shelf life, low-cost sensor transponder for monitoring the temperature and humidity conditions inside cardboard artefact storage boxes. In developing the proposed solution, the state of the art NFC sensor technology is first reviewed in detail, and a battery-less NFC sensor transponder is proposed with a cost of less than â ¬5 in quantities of 10k. In addition to this, early-stage prototype results are also presented

How can we justify grouping of nanoforms for hazard assessment? Concepts and tools to quantify similarity

The risk of each nanoform (NF) of the same substance cannot be assumed to be the same, as they may vary in their physicochemical characteristics, exposure and hazard. However, neither can we justify a need for more animal testing and resources to test every NF individually. To reduce the need to test all NFs, (regulatory) information requirements may be fulfilled by grouping approaches. For such grouping to be acceptable, it is important to demonstrate similarities in physicochemical properties, toxicokinetic behaviour, and (eco)toxicological behaviour. The GRACIOUS Framework supports the grouping of NFs, by identifying suitable grouping hypotheses that describe the key similarities between different NFs. The Framework then supports the user to gather the evidence required to test these hypotheses and to subsequently assess the similarity of the NFs within the proposed group. The evidence needed to support a hypothesis is gathered by an Integrated Approach to Testing and Assessment (IATA), designed as decision trees constructed of decision nodes. Each decision node asks the questions and provides the methods needed to obtain the most relevant information. This White paper outlines existing and novel methods to assess similarity of the data generated for each decision node, either via a pairwise analysis conducted property-by-property, or by assessing multiple decision nodes simultaneously via a multidimensional analysis. For the pairwise comparison conducted property-by-property we included in this White paper: • A Bayesian model assessment which compares two sets of values using nested sampling. This approach is new in NF grouping. • A Arsinh-Ordered Weighted Average model (Arsinh-OWA) which applies the arsinh transformation to the distance between two NFs, and then rescales the result to the arsinh of a biologically relevant threshold before grouping using OWA based distance. This approach is new in NF grouping. • An x-fold comparison as used in the ECETOC NanoApp. • Euclidean distance, which is a highly established distance metric. The x-fold, Bayesian and Arsinh-OWA distance algorithms performed comparably in the scoring of similarity between NF pairs. The Euclidean distance was also useful, but only with proper data transformation. The x-fold method does not standardize data, and thus produces skewed histograms, but has the advantage that it can be implemented without programming knowhow. A range of multidimensional evaluations, using for example dendrogram clustering approaches, were also investigated. Multidimensional distance metrics were demonstrated to be difficult to use in a regulatory context, but from a scientific perspective were found to offer unexpected insights into the overall similarity of very different materials. In conclusion, for regulatory purposes, a property-by-property evaluation of the data matrix is recommended to substantiate grouping, while the multidimensional approaches are considered to be tools of discovery rather than regulatory methods

Similarity of multicomponent nanomaterials in a safer-by-design context : the case of core–shell quantum dots

Concepts of similarity, such as grouping, categorization, and read-across, enable a fast comparative screening of hazard, reducing animal testing. These concepts are established primarily for molecular substances. We demonstrate the development of multi-dimensional similarity assessment methods that can be applied to multicomponent nanomaterials (MCNMs) for the case of core–shell quantum dots (QDs). The term ‘multicomponent’ refers to their structural composition, which consists of up to four different heavy metals (cadmium, zinc, copper, indium) in different mass percentages, with different morphologies and surface chemistries. The development of concepts of similarity is also motivated by the increased need for comparison of innovative against conventional materials in the safe and sustainable by design (SSbD) context. This case study thus considers the industrial need for an informed balance of functionality and safety: we propose two different approaches to compare and rank the case study materials amongst themselves and against well-known benchmark materials, here ZnO NM110, BaSO4 NM220, TiO2 NM105, and CuO. Relative differences in the sample set are calibrated against the biologically relevant range. The choice of properties that are subjected to similarity assessment is guided by the integrated approaches to testing and assessment (IATA) for the inhalation hazard of simple nanomaterials, which recommends characterizing QDs by (i) dynamic dissolution in lung simulant fluids and (ii) the surface reactivity in the abiotic ferric reducing ability of serum (FRAS) assay. In addition, the similarity of fluorescence spectra was assessed as a measure of the QD performance for the intended functionality as a color converter. We applied two approaches to evaluate the data matrix: in the first approach, specific descriptors for each assay (i.e., leachable mass (%) and mass based biological oxidative damage (mBOD)) were selected based on expert knowledge and used as input data for generation of similarity matrices. The second approach introduces the possibility of evaluating multidimensional raw data by a meaningful similarity analysis, without the need for predefined descriptors. We discuss the strengths and weaknesses of each of the two approaches. We anticipate that the similarity assessment approach is transferable to the assessment of further advanced materials (AdMa) that are composed of multiple components

Socio-Economic Life Cycle-Based Framework for Safe and Sustainable Design of Engineered Nanomaterials and Nano-Enabled Products

This manuscript describes an innovative approach to socio-economic assessment of (advanced) engineered nanomaterials and nano-enabled products (NEPs) to support safe-and-sustainable-by-design (SSbD) decision making by industries in the early stages of product development. This semi-quantitative methodology is based on a sound conceptual framework grounded in the combination of social life cycle analysis and multi-criteria decision analysis methods and supports decision making based upon socio-economic impacts assessed over the full life cycle of a product. To facilitate its application by industries, the methodology was implemented as an Excel-based self-assessment tool. This easy-to-use, cost- and time-efficient tool can guide users through their SSbD decision making regarding newly developed nanomaterials and NEPs and can also be applied to re-evaluate existing materials and NEPs in order to improve their sustainability from a socio-economic perspective. The relatively low requirements of this tool regarding the level of efforts and expert knowledge needed for its application make it a good starting point for initial assessment to highlight socio-economic issues in the value chain. The results of this initial screening can be further used for more detailed analysis in the later stages of product development by performing a full social life cycle assessment (S-LCA)

Socio-Economic Life Cycle-Based Framework for Safe and Sustainable Design of Engineered Nanomaterials and Nano-Enabled Products

This manuscript describes an innovative approach to socio-economic assessment of (advanced) engineered nanomaterials and nano-enabled products (NEPs) to support safe-and-sustainable-by-design (SSbD) decision making by industries in the early stages of product development. This semi-quantitative methodology is based on a sound conceptual framework grounded in the combination of social life cycle analysis and multi-criteria decision analysis methods and supports decision making based upon socio-economic impacts assessed over the full life cycle of a product. To facilitate its application by industries, the methodology was implemented as an Excel-based self-assessment tool. This easy-to-use, cost- and time-efficient tool can guide users through their SSbD decision making regarding newly developed nanomaterials and NEPs and can also be applied to re-evaluate existing materials and NEPs in order to improve their sustainability from a socio-economic perspective. The relatively low requirements of this tool regarding the level of efforts and expert knowledge needed for its application make it a good starting point for initial assessment to highlight socio-economic issues in the value chain. The results of this initial screening can be further used for more detailed analysis in the later stages of product development by performing a full social life cycle assessment (S-LCA)