Alex Zabeo

A weight of evidence approach for hazard screening of engineered nanomaterials

Abstract Hazard identification is an important step in assessing nanomaterial risk and is required under multiple regulatory frameworks in the US, Europe and worldwide. Given the emerging nature of the field and complexity of nanomaterials, multiple studies on even basic material properties often result in varying data pointing in different directions when data interpretation is attempted. Weight of evidence (WOE) evaluation has been recommended for nanomaterial risk assessment, but the majority of WOE frameworks are qualitative in nature and do not satisfy the growing needs for objectivity and transparency that are necessary for regulatory decision making. This paper implements a quantitative WOE framework that utilizes multi-criteria decision analysis methodology for integrating individual studies on nanomaterial hazard resulting from physico-chemical and toxicological properties of nanomaterials. For the first time, a WOE approach explicitly integrates expert evaluation of data quality of available information. Application of the framework is illustrated for titanium dioxide nanoparticles (nano-TiO2), but the approach is designed to compare the relative hazard of several nanomaterials as well as emerging stressors in general.

Climate change impact assessment in Veneto and Friuli Plain groundwater. Part II: A spatially resolved regional risk assessment

Climate change impact assessment on water resources has received high international attention over the last two decades, due to the observed global warming and its consequences at the global to local scale. In particular, climate-related risks for groundwater and related ecosystems pose a great concern to scientists and water authorities involved in the protection of these valuable resources. The close link of global warming with water cycle alterations encourages research to deepen current knowledge on relationships between climate trends and status of water systems, and to develop predictive tools for their sustainable management, copying with key principles of EU water policy. Within the European project Life+ TRUST (Tool for Regional-scale assessment of groundwater Storage improvement in adaptation to climaTe change), a Regional Risk Assessment (RRA) methodology was developed in order to identify impacts from climate change on groundwater and associated ecosystems (e.g. surface waters, agricultural areas, natural environments) and to rank areas and receptors at risk in the high and middle Veneto and Friuli Plain (Italy). Based on an integrated analysis of impacts, vulnerability and risks linked to climate change at the regional scale, a RRA framework complying with the Sources-Pathway-Receptor-Consequence (SPRC) approach was defined. Relevant impacts on groundwater and surface waters (i.e. groundwater level variations, changes in nitrate infiltration processes, changes in water availability for irrigation) were selected and analyzed through hazard scenario, exposure, susceptibility and risk assessment. The RRA methodology used hazard scenarios constructed through global and high resolution model simulations for the 2071-2100 period, according to IPCC A1B emission scenario in order to produce useful indications for future risk prioritization and to support the addressing of adaptation measures, primarily Managed Artificial Recharge (MAR) techniques. Relevant outcomes from the described RRA application highlighted that potential climate change impacts will occur with different extension and magnitude in the case study area. Particularly, qualitative and quantitative impacts on groundwater will occur with more severe consequences in the wettest and in the driest scenario (respectively). Moreover, such impacts will likely have little direct effects on related ecosystems - croplands, forests and natural environments - lying along the spring area (about 12% of croplands and 2% of natural environments at risk) while more severe consequences will indirectly occur on natural and anthropic systems through the reduction in quality and quantity of water availability for agricultural and other uses (about 80% of agricultural areas and 27% of groundwater bodies at risk).

Sustainable nanotechnology decision support system: bridging risk management, sustainable innovation and risk governance

The significant uncertainties associated with the (eco)toxicological risks of engineered nanomaterials pose challenges to the development of nano-enabled products toward greatest possible societal benefit. This paper argues for the use of risk governance approaches to manage nanotechnology risks and sustainability, and considers the links between these concepts. Further, seven risk assessment and management criteria relevant to risk governance are defined: (a) life cycle thinking, (b) triple bottom line, (c) inclusion of stakeholders, (d) risk management, (e) benefit–risk assessment, (f) consideration of uncertainty, and (g) adaptive response. These criteria are used to compare five well-developed nanotechnology frameworks: International Risk Governance Council framework, Comprehensive Environmental Assessment, Streaming Life Cycle Risk Assessment, Certifiable Nanospecific Risk Management and Monitoring System and LICARA NanoSCAN. A Sustainable Nanotechnology Decision Support System (SUNDS) is proposed to better address current nanotechnology risk assessment and management needs, and makes. Stakeholder needs were solicited for further SUNDS enhancement through a stakeholder workshop that included representatives from regulatory, industry and insurance sectors. Workshop participants expressed the need for the wider adoption of sustainability assessment methods and tools for designing greener nanomaterials.

Application of a quantitative weight of evidence approach for ranking and prioritising occupational exposure scenarios for titanium dioxide and carbon nanomaterials

Abstract Substantial limitations and uncertainties hinder the exposure assessment of engineered nanomaterials (ENMs). The present deficit of reliable measurements and models will inevitably lead in the near term to qualitative and uncertain exposure estimations, which may fail to support adequate risk assessment and management. Therefore it is necessary to complement the current toolset with user-friendly methods for near-term nanosafety evaluation. This paper proposes an approach for relative exposure screening of ENMs. For the first time, an exposure model explicitly implements quantitative weight of evidence (WoE) methods and utilises expert judgement for filling data gaps in the available evidence-base. Application of the framework is illustrated for screening of exposure scenarios for nanoscale titanium dioxide, carbon nanotubes and fullerenes, but it is applicable to other nanomaterials as well. The results show that the WoE-based model overestimates exposure for scenarios where expert judgement was substantially used to fill data gaps, which suggests its conservative nature. In order to test how variations in input data influence the obtained results, probabilistic Monte Carlo sensitivity analysis was applied to demonstrate that the model performs in stable manner.

Species sensitivity weighted distribution for ecological risk assessment of engineered nanomaterials: The n-TiO2 case study

Societal concerns about the environmental risks of engineered nanomaterials (ENMs) have recently increased, but nano-ecological risk assessments are constrained by significant gaps in basic information on long-term effects and exposures, for example. An approach to the ecological risk assessment of ENMs is proposed that can operate in the context of high uncertainty. This approach further develops species sensitivity weighted distribution (SSWD) by including 3 weighting criteria (species relevance, trophic level abundance, and nanotoxicity data quality) to address nano-specific needs (n-SSWD). The application of n-SSWD is illustrated for nanoscale titanium dioxide (n-TiO2 ), which is available in different crystal forms; it was selected because of its widespread use in consumer products (e.g., cosmetics) and the ample availability of data from ecotoxicological studies in the literature (including endpoints for algae, invertebrates, bacteria, and vertebrates in freshwater, saltwater, and terrestrial compartments). The n-SSWD application resulted in estimation of environmental quality criteria (hazard concentration affecting 5% and 50% of the species) and ecological risk (potentially affected fraction of species), which were then compared with similar results obtained by applying the traditional species sensitivity distribution (SSD) approach to the same dataset. The n-SSWDs were also built for specific trophic levels (e.g., primary producers) and taxonomic groups (e.g., algae), which helped to identify the most sensitive organisms. These results showd that n-SSWD is a valuable risk tool, although further testing is suggested.

Integrated Risk Assessment for WFD Ecological Status classification applied to Llobregat river basin (Spain). Part II - Evaluation process applied to five environmental Lines of Evidence.

Many indicators and indices related to a variety of biological, physico-chemical, chemical, and hydromorphological water conditions have been recently developed or adapted by scientists in order to support water managers in the Water Framework Directive (WFD) implementation. In this context, the achievement of a comprehensive and reliable Ecological Status classification of water bodies across Europe is hampered by the lack of harmonised procedures for selecting an appropriate set of indicators and integrating heterogeneous information in a flexible way. To this purpose, an Integrated Risk Assessment (IRA)(2) methodology was developed based on the Weight of Evidence approach. This method analyses and combines a set of environmental indicators grouped into five Lines of Evidence (LoE), i.e. Biology, Chemistry, Ecotoxicology, Physico-chemistry and Hydromorphology. The whole IRA methodology has been implemented as a specific module into a freeware GIS (Geographic Information System)-based Decision Support System, named MODELKEY DSS. This paper focuses on the evaluation of the four supporting LoE (i.e. Chemistry, Ecotoxicology, Physico-chemistry and Hydromorphology), and includes a procedure for a comparison of each indicator with proper thresholds and a subsequent integration process to combine the obtained output with the LoE Biology results in order to provide a single score expressing the Ecological Status classification. The approach supports the identification of the most prominent stressors, which are responsible for the observed alterations in the river basin under investigation. The results provided by the preliminary testing of the IRA methodology through application of the MODELKEY DSS to the Llobregat case study are finally reported and discussed.

Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials

Abstract Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

Actor networks and the construction of applicable knowledge: the case of the Timbre Brownfield Prioritization Tool

This article deals with experiences acquired during the process of developing the Timbre Brownfield Prioritization Tool (TBPT). Developing a decision support tool that takes into account the expectations and experiences of its potential users is similar to creating applicable knowledge by the joint action of scientists and heterogeneous actors. Actor network theory is used to explore the construction of this form of applicable knowledge as a process of actor network creation. Following the French sociologist Callon, networks are seen to be initiated and carried out by a group of scientists (tool developers) via four moments of translation, called problematization, interessement, enrolment and mobilization. Each step in the construction of the TBPT—from the initial research question to the final model—can be linked in retrospect to changing configurations of actor networks. Based on the experiences of the tool developers in the Czech Republic, Poland, Germany and Romania, we illustrate how these configurations varied across space and time. This contribution emphasizes the ability to correlate gains in knowledge with the more visible changes in the scope of actor networks in order to highlight achievements but also limitations in acquiring applicable knowledge.

Probabilistic risk assessment of emerging materials: case study of titanium dioxide nanoparticles

Abstract The development and use of emerging technologies such as nanomaterials can provide both benefits and risks to society. Emerging materials may promise to bring many technological advantages but may not be well characterized in terms of their production volumes, magnitude of emissions, behaviour in the environment and effects on living organisms. This uncertainty can present challenges to scientists developing these materials and persons responsible for defining and measuring their adverse impacts. Human health risk assessment is a method of identifying the intrinsic hazard of and quantifying the dose–response relationship and exposure to a chemical, to finally determine the estimation of risk. Commonly applied deterministic approaches may not sufficiently estimate and communicate the likelihood of risks from emerging technologies whose uncertainty is large. Probabilistic approaches allow for parameters in the risk assessment process to be defined by distributions instead of single deterministic values whose uncertainty could undermine the value of the assessment. A probabilistic approach was applied to the dose–response and exposure assessment of a case study involving the production of nanoparticles of titanium dioxide in seven different exposure scenarios. Only one exposure scenario showed a statistically significant level of risk. In the latter case, this involved dumping high volumes of nano-TiO2 powders into an open vessel with no personal protection equipment. The probabilistic approach not only provided the likelihood of but also the major contributing factors to the estimated risk (e.g. emission potential).

Assessing storm surge risk under future sea-level rise scenarios: a case study in the North Adriatic coast

Low-lying coastal areas are often prone to storm surge flooding that can render severe damages to properties, destruction of habitats, threat to human safety and the environment. The impacts of coastal flooding are also expected to increase in the future as a consequence of global climate change and sea-level rise. This paper presents a comprehensive assessment of the potential risks raised by storm surge and sea-level rise on multiple coastal targets (i.e., population, buildings, infrastructures, agriculture, natural and semi-natural environments and cultural heritage) in the Northern Adriatic coast in Italy. Through the assessment of hazard, exposure, vulnerability and risk, a Regional Risk Assessment (RRA) methodology allowed identifying and prioritizing hot-spot risk areas and targets requiring particular attention for the definition of adaptation strategies. Hazard scenarios were based on the analysis of tide gauge data (elaborated with the Joint Probability Method) and of different sea-level rise projections for the year 2100. Geographical-information analysis was then used to characterize vulnerability patterns of exposed natural and human systems and to make a spatial ranking of risks. Maps produced for the worst scenario showed that beaches are the target at higher risk (with more than 90% of the surface in the higher relative risk class) due to the low elevation and high proximity to the coastline. Also cultural heritage (i.e., villas, historical buildings and roads) and wetlands are highly threatened by storm surge flooding. The relative risks will be lower (i.e., between 25% and 40% of their surface/length in the higher relative risk class) for most of the other receptors (i.e., local roads, railways, natural and semi-natural environments and agricultural areas), including population and buildings that are mostly classified in lower risk classes. The overall results of the assessment, including maps and risk metrics, can be useful to rise the attention of coastal managers about the need to adapt to climate change, developing climate-proof policies and programs for the sustainable management of coastal zones.