Contributions published at Informatics and Sustainability Research (Lorenz Hilty)

Electronic equipment (EE) contains important material resources, not only bulk materials but also precious metals and critical metals. While the recycling of bulk materials and precious metals is often well established, efforts to specifically recover critical metals from EE are only beginning. They are hampered by low contents per device, limitations of recovery technolo-gies, lack of economic incentives as well as limited knowledge of stocks, flows and disposal pathways of critical metals incorporated in EE. For an efficient management of these resources, it is thus important to know where they are located, how long they are used and when and how they are disposed of. This can be achieved by dynamic material flow analyses (MFAs), which are often used to investigate the development of material cycles over time. In this thesis, we explore the fate of critical metals in EE used by private end-users in Switzer-land with a focus on the examples of indium and neodymium. Additionally, we include the precious metal gold as a reference metal with already well-established recycling processes. The main objectives of this research are to better understand the metabolism of the anthroposphere regarding critical metals connected to the use of EE, provide a basis to develop appropriate tools and alternatives to manage efficient recycling systems and encourage the recycling and reintegration of critical metals into anthropogenic material cycles. We explore the fate of critical metals and their suitability for urban mining with a special focus on the service lifetime, storage time and disposal pathways of different device types. Within the use phase, we investigate the past and current quantities of electronic devices containing indium, neodymium, and gold in the in-use stock and quantify the flows between the use, storage and disposal phase. We further analyze the reasons for discre-pancies between low collection flows and high sales flows or long phase-out periods of technologies that are no longer sold. Within the collection, recycling and disposal phase, we assess sinks resulting from the dissipation of critical metals due to inappropriate recycling processes. As input data of dynamic MFAs are often acquired from many different sources with varying data reliability, we systematically consider the associated data uncertainties. Data for the service lifetime, storage time and disposal pathways are collected via a survey and additional interviews. Devices included are mobile phones, smartphones, desktop and laptop computers, monitors, cathode ray tube and flat panel display televisions, DVD players and headphones. Based on the empirical results, the system for the dynamic MFA is deve-loped as a cascade model, with each step consisting of an in-use-stock and a storage stock for new and secondhand devices, respectively. In order to track the three metals from their entry into Switzerland as components of new devices until their recovery, disposal in landfill or dissipation to the environment, the cascade model is extended with the collection, recy-cling, and disposal phase. With statistical entropy analysis (SEA), we further analyze the dilution or concentration of the metals during their route through the current system. Using a customized software tool, we apply Monte Carlo simulation to systematically consider data uncertainty in the calculation of the dynamic MFA. The cascade model provides new and important insights regarding product lifetimes and the transfer of devices from active use to storage and disposal. We show that not only the service lifetime but also the storage time and the flows between the in-use stock and the storage stock are important to consider in dynamic MFAs. The median service lifetime of new devices varies from 3 years for mobile phones to 9 years for CRT TVs, the median storage time from 0 years for most device types to 2 years for headphones. Due to reuse and storage, the total time a device stays in the use phase is significantly prolonged. Compared to the median service lifetime of new devices, the median total lifetime increases, for example, from 3 to 7 years for mobile phones and from 5 to 8 and 9 years for desktops and laptops, respectively. The results highlight the importance of the storage stock, which accounts for 25% (in terms of mass) or 40% (in terms of pieces) of the total stock of EE in 2014. Our study thus provides insights into the 'black box' that has been the usual way of modeling the use phase of end-user products so far. Furthermore, by differentiating among device types, the changing composition of outflows due to technology changes is accounted for. With the extended model, we are able to show the final destinations of indium and neodymium within the collection, recycling and disposal phase and quantify the related stocks and flows. The largest quantities of all three metals are still found in the EE currently in use and amount to 1.7 tonnes of indium, 39 tonnes of neodymium and 4.8 tonnes of gold. The second largest stocks are disposed slags in landfills for indium, slags used for construction for neodymium, and the output of metal recovery processes for gold. The average metal quantities reaching recycling in 2014 were 90 kg for indium, 2800 kg for neodymium and 330 kg for gold. With SEA, we illustrate how indium and neodymium are successfully concentrated during preprocessing, but subsequently lost in smelting and incineration processes. The variable data quality in MFAs is accounted for in a comprehensive and flexible way, by the inclusion of input data uncertainty in the form of probability distributions, by Monte-Carlo simulation and analysis of the resulting probabilistic stocks and flows. The presented approach is a step towards a deeper understanding of the stocks and flows of EE and its incorporated critical metals. The generic model can be customized and applied to any end-user product that is potentially reused and stored after its first service life.

In international trade and finance, financial institutes are traditionally established as an intermediary to facilitate the individual steps between the parties involved. While these intermediaries addressed some of the challenges including the risks to the exporter and importer, further improvements can be made with the advancement of technology like blockchain. As a distributed ledger technology, blockchain provides properties like immutability, transparency and verifiability of transactions that can bring improvements to the international trade and finance process. This study reviews the current state of the art of blockchain application in international trade and finance and develops an architecture and a prototype for the end-to-end processes in international trade and finance using blockchain technology.

null

Technological innovations usually have implications for society at large. Technology Assessment (TA) is a process that aims to contribute to the formation of public and political opinion on societal aspects of technology. In TA studies, potential technological impacts are predicted – very often in the form of what-if scenarios – and then evaluated for their desirability or undesirability by the participants of the study. Both steps, prediction and evaluation, usually lead to controversies. For example, when the cellular networks were built and the mobile phone became popular, there was a debate about potential health impacts of the non-ionizing radiation emitted by the phones and the base station antennas. Predicting the induced health risk is different from evaluating it; even if we assume a certain non-zero additional cancer risk, for example, we could still argue that this were acceptable compared to an assumed potential benefit of the technology. Both predicting and evaluating potential impacts needs some form of discourse to build consensus. This is imperative for the evaluation phase because evaluation involves values, in this case the value of health and the value of other opportunities which are traded against it. Every normative statement that somebody contributes to a discussion (i.e., a judgment about whether a situation is desirable or undesirable) is based on personal values. It is therefore important to find discursive forms of TA that support the elicitation and discussion of the subjective values that may be hidden behind diverging opinions on the technological innovations. The aim of our research is to find better ways to separate descriptive from normative statements in discussions about technological innovation, to elicit the values behind, and to support ethical reflection where dilemmas emerge. By this approach, we want to contribute to the methodology of discursive TA.

Companies in the fashion industry are increasingly looking for reliable data to make informed decisions and to prioritize their sustainability efforts. Life Cycle Assessment (LCA) provide a comprehensive and holistic way to assess environmental impacts over the full life cycle; yet, credible LCA data on the cultivation and processing of textiles is still limited. The World Apparel and Footwear Life Cycle Assessment Database (WALDB) was founded to solve this data challenge and to deliver robust data for environmental impact assessment and footprinting. One core limitation concerns cotton cultivation. There is a lack in the coverage and geographical representativeness of LCA data representing global cotton cultivation. To date, the entire cultivation of cotton is represented in the form of two country-generic LCA datasets which uniformly describe cotton cultivation in the context of the USA and in China. We believe that the integration of spatial data into LCA calculations can deliver more representative data for the assessment of cotton cultivation, when combined with a computerized method for regionalized LCI modeling. Regionalized LCI modeling is the procedure that generates and links process datasets to the location where they occur (C. L. Mutel, Pfister, and Hellweg 2012). Spatial explicit data on various context conditions (precipitation, soil properties, etc.) and production parameters (crop-specific fertilizer input, yield, etc.) is now available, in decent resolution and on a global scale (Hengl et al. 2014; Monfreda, Ramankutty, and Foley 2008; Mueller et al. 2012). However, the consideration of such data in the generation of LCA datasets is too labor-intensive with the classical means of data processing. Agricultural datasets are mainly generated manually, according to specific guidelines and emissions models and involving a wide array of raw data sources, ranging from public available databases (FAOSTAT, EUROSTAT, etc.), company data, surveys, case studies, publications, measurements, etc. (T. Nemecek et al. 2015). They typically are site-generic meaning that one datasets represent an entire country. Reinhard et al. (2017) have developed a regionalization framework that is capable of processing the spatial explicit data on various context conditions and production parameters into comprehensive LCA datasets. This work-in-progress article examines the extensions of the framework for the generation of robust and geographically representative cotton datasets. Reinhard et al. (2017) have developed a regionalization framework that is capable of processing the spatial explicit data on various context conditions and production parameters into comprehensive LCA datasets. This work-in-progress article examines the extensions of the framework for the generation of robust and geographically representative cotton datasets. We first review the core elements of the method for regionalized LCI modeling developed by (Reinhard et al. 2017) and show how it is used for the generation of regionalized cotton datasets. We next highlight geographically explicit results for cotton cultivation in China and in Turkey and show exemplarily how we compute country specific average datasets. We conclude with a discussion of the advancement provided by and improvement options of the framework.

This thesis takes a closer look at how the digitized signage influences our everyday life. The question is examined by the development of a concept for visual orientation of people in fitness clubs. The purpose of this project is to provide information to the costumer with the help of signage supported by external data sources. This promotes productí sales and reduces losses due to short-term cancellations of services like massages. The concept contains the elaboration of the positions, the visualization, the system architecture, the software components, the hardware components, and the communication. It shows how our everyday life in a fitness studio can be consciously influenced and that such a system does not have positive effects for the provider only.

Der Informatiker Lorenz M. Hilty über IT-Produkte, die langlebiger sind, als wir glauben, alternative Businessmodelle in der Telekommunikation und die Stärkung der Konsumenten durch die Digitalisierung.

Grundlagenforschung bedeutet, die grundlegenden Theorien und Konzepte eines Faches weiterzuentwickeln. Es sind also die Fundamente einer Wissenschaft, die durch Grundlagenforschung erweitert oder erneuert werden. Wo liegen die Fundamente der noch relativ jungen Wissenschaft Informatik? Diese Frage wird seit Jahrzehnten kontrovers diskutiert, gerade weil die Informatik eine so vielfältige Wissenschaft ist. Dabei gehen schon die Auffassungen über die Rolle des Computers in der Informatik auseinander. Ist der Computer der Erkenntnisgegenstand der Informatik oder geht es in der Informatik „genauso wenig um Computer wie in der Astronomie um Teleskope“, wie der holländische Informatiker Edsger W. Dijkstra es ausdrückte? Ich möchte Sie zu einem Rundgang einladen, auf dem wir die Informatik aus vier verschiedenen Perspektiven betrachten. Dabei werde ich auf die Erkenntnisziele eingehen, die sich aus der jeweiligen Perspektive stellen.

The aim of this study is to investigate consumers’ reflections and reactions to a food scare news story. Previous studies indicate that risk communication not always is able to influence people’s behavior and that pre-existing attitudes may influence people’s reactions and reflections. In this study, we investigate how consumers critically reflect and emotionally react to a food scare, here defined as risk communication that spirals public anxiety over food safety incidents, and leads to an unwanted escalation in media attention. In the Fall of 2014, a researcher from the Norwegian Institute of Public Health said in a newspaper interview that she never touched chicken with her bare hands. This interview was the beginning of a media storm, which resulted in a dramatic drop in sales of chicken. In this study, we explore a small group of consumers’ reflections and reactions to this news article. Data from five focus group interviews with Norwegian consumers of chicken were transcribed, content analyzed, and coded, before we conducted a multiple correspondence analysis and a hierarchical cluster analysis. The findings indicate that consumers do reflect when confronted with a food scare story. Some question the research behind the news, others compare the food scare’s danger to other risks. Even though consumers do reflect around the facts in the food scare article, their emotions seem to affect their behavior more systematic than their reflections.

Ideas are essential for innovation and for the continuous renewal of a firm’s product offerings. Previous research has argued that online communities contain such ideas. Therefore, online communities such as forums, Facebook groups, blogs etc. are potential gold mines for innovative ideas that can be used for boosting the innovation performance of the firm. However, the nature of online community data makes idea detection labor intensive. As an answer to this problem, research has shown that it might be possible to detect ideas from online communities, automatically. Research is however, yet to provide an answer to what is it that makes such automatic idea detection possible? Our study is based on two datasets from dialogue between members of two distinct online communities. The first community is related to beer. The second is related to Lego. We generate machine learning classifiers based on Support Vector Machines and Partial Least Squares that can detect ideas from each respective online community. We use partial least squares to investigate what are the words and expressions that allows for automatic classification of ideas. We conclude that ideas from the two online communities, contains suggestion/solution words and expressions and it is these that make automatic idea detection possible. In addition we conclude that the nature of the ideas in the beer community seems to be related to the brewing process. The nature of the ideas in the Lego community seems to be related to new products that consumers would want.

The fair distribution of project topics to students frequently poses a challenge. This is why in this thesis a web application was developed with the intent to simplify this procedure. Supervisors fill in their topics using a neat user interface and students state their preferences. An algorithm then calculates the optimal distribution. The emphasis was placed on the analysis of existing solutions and on the input such that students can state their interests as accurately as possible. An additional focus was the development of the algorithm to achieve a distribution, which is as fair as possible. The result of the thesis is a web application in which students rank the available topics. Using the Gale-Shapley algorithm adapted for this purpose a distribution as optimal as possible is calculated, providing it exists.

Electronic equipment (EE) contains important material resources, including bulk materials, precious metals, and critical raw materials such as indium (In) and neodymium (Nd). For an efficient management of these resources, it is important to know where the devices are located, how long they are used and when and how they are disposed of. In this article, we explore the fate of critical raw materials in EE and thus the suitability of their in-use stock for urban mining. With a special focus on the service lifetime, storage time and disposal pathways of different device types, we investigate the past and current quantities of EE containing In and Nd in the stock and quantify the flows between the use, storage and disposal phase. Results highlight the importance of the storage stock, which accounts for 25% of the mass of the total stock in 2014. Electronic devices in Switzerland represent an In stock of over 2 tons and a Nd stock of 38 tons.

Electronic devices contain important resources, including precious and critical raw materials. For an efficient management of these resources, it is important to know where the devices are located, how long they are used and when and how they are disposed of. In this article, we explore the past and current quantities of electronic devices in the in-use stock and storage stock in Switzerland and quantify the flows between the use, storage and disposal phase with dynamic material flow analysis (MFA). Devices included are mobile phones, desktop and laptop computers, monitors, cathode ray tube and flat panel display televisions, DVD players, and headphones. The system for the dynamic MFA was developed as a cascade model dividing the use phase in first, second and further use, with each of these steps consisting of an in-use stock and a storage stock for devices. Using a customized software tool, we apply Monte Carlo simulation to systematically consider data uncertainty. The results highlight the importance of the storage stock, which accounts for 25% (in terms of mass) or 40% (in terms of pieces) of the total stock of electronic devices in 2014. Reuse and storage significantly influence the total lifetime of devices and lead to wide and positively skewed lifetime distributions.

One approach to decrease greenhouse gas emissions over a long-term period is emission trading with the cap-and-trade system. This bachelor thesis has the goal to optimize a web application that allows emission trading within an organisation. With the web application members of the organisation can trade limited resources, e.g. CO2-certificates. They can also record their business trips including the resulting CO2 emissions. Within the scope of this bachelor thesis, the web application was analysed and its original functional range could be restored. To calculate the CO2 emissions from an air trip, a new computation was implemented. Additionally, the concept of Responsive Design was applied to the web application. With the Responsive Design, the optimization for the use on mobile devices could be realized.

The present bachelor thesis pursues the question with which sensors it is possible to measure people’s behaviour regarding ventilation. The ventilation behavior should be measured with a small number of cheap sensors. The bachelor thesis contains the identification of the necessary sensors as well as the construction of a sensor node which includes sensors and raspberrypi. Additionally various application scenarios for the sensor node should be developed.

Purpose: The world is shaped by an education system that reinforces unsustainable thinking and practice. Efforts to transform our societies must thus prioritise the education of educators – building their understanding of sustainability and their ability to transform curriculum and wider learning opportunities. The purpose of this paper is to focus on university educators and critically review the professional development and policy landscape challenges that influence their effective engagement with Education for Sustainable Development (ESD). The paper is informed by a pan-European collaboration involving 33 countries that identified emerging scholarship and practice in this area and assessed the lessons learned from ESD professional development initiatives. It sets the context for a special issue titled “Professional Development in Higher Education for Sustainable Development” that draws together a collection of articles focusing on professional development of university educators across the world. Design/methodology/approach: This paper provides a critical review of existing practice, international policy frameworks and literature relating to ESD, professional development and higher education. It examines innovative initiatives worldwide that seek to improve the capability of educators in higher education to integrate ESD into academic practice at individual, disciplinary and institutional levels. A rigorous process of selection was applied and overseen by an international expert group. This ensured that the initiatives sought educational change in ESD, and not simply the embedding of content about sustainability into learning opportunities. It also assured that the initiatives had a clear and intentional professional learning process to underpin the engagement of participants with ESD. Findings: ESD has grown in visibility and status worldwide, with a clear increase in activity in higher education. The sector is viewed as a significant force for change in societies, through the education provision it offers to future professionals and leaders in all sectors. However, universities currently lack capacity to integrate ESD effectively into mainstream teaching practices and the training they provide for academic staff or to integrate ESD into their institutional teaching and learning priorities. Many ESD activities remain focused on teaching issues arising in sustainable development research and delivering specialist modules or courses in sustainability. Very few countries and institutions have significant staff development programmes to enhance the ESD competences of university educators and build their academic leadership capabilities for ESD. The contributions to this special issue show the need for greater understanding of the multi-level task of integrating ESD into professional development activities, not just for individual impact in the classroom but to advance institutional change and decisively influence the teaching and learning discourse of higher education. Originality/value: There are few research studies and documented activities on ESD professional development in higher education available in the literature. This paper attempts to explore what ESD professional development involves and describes its complexity within the higher education sector. The special issue provides a collection of innovative research and practical initiatives that can help those involved in education and learning to develop ESD as a priority for future university innovative pathways.

Simulation modelling is an important tool for assessing the environmental level of a pollutant. By modelling the flow of anthropogenic substances from the technosphere into the ecosphere and through several environmental compartments, the concentrations of these in air, water and soil can be estimated. These values are a fundamental requirement for any estimation of environmental hazard and risk posed by a chemical or substance. In general, the input data needed for such models is uncertain and determining reliable values for environmental stocks and flows using a mass-flow model is a challenge. That is why Material flow Analysis (MFA) needs methods and tools to deal with this uncertainty. In static cases, this can be done via Probabilistic Material Flow Analysis (PMFA). But processes including time-dynamic behaviour cannot be handled with this. Therefore, the present thesis presents Dynamic Probabilistic Material Flow Analysis (DPMFA) as a new approach to close this gap. It includes: – a mass balanced stock and flow representation, – time-dynamic system behaviour and discrete period based time progress, and – explicit uncertainty representation and propagation In DPMFA, the existing Probabilistic Material Flow Analysis (PMFA) is linked to dynamic modelling means. In PMFA a system of dependent material flows is assumed to be in equilibrium for the investigated period (e.g. a year). Incomplete system knowledge is represented as Bayesian parameter distributions. On this basis, the dependent model variables (such as environmental stocks) are derived using Monte-Carlo simulation. To introduce dynamic behaviour of a system over a longer time span, in DPMFA, the flows of subsequent periods need to be calculated and the material accumulations in the sinks have to be added up. External inflows are considered for each period individually and intermediate delays are represented as stocks with specific release functions. As a result, environmental pollutant concentrations and exposures are determined based on the absolute material amounts in stocks. In addition to the theoretical modelling approach, a respective modelling-package in Python was implemented and provided1. The tool enables application experts from different fields to develop models for their domain. One important application field for this approach is the assessment of new substances such as engineered nano-materials (ENM), which are used in a growing number of products. At present, there are no analytic methods available to quantify environmental concentrations of ENM. Most of them are long-lasting, so they can accumulate in the ecosphere over a longer time period. This qualifies the modelling and simulation of ENM flows as suitable example of use to demonstrate the new approach. We describe the development and application of DPMFA in the form of four scientific articles, which constitute the core of this thesis. Article I (Chapter 2) presents the specific requirements for the new modelling approach and implements a small example model using several existing modelling approaches to identify their possibilities and limitations. In article II (Chapter 3), the new approach is theoretically developed in detail and then exemplarily applied in a case-study to assess the environmental concentrations of Carbon Nanotubes (CNT) in Switzerland. The new approach is further specified in Article III (Chapter 4). In particular, the representation of incomplete knowledge from several data sources, model-robustness regarding design decisions, as well as sensitivityand uncertainty analyses are discussed and resulting implications on the model and the investigated system are highlighted. A comprehensive application of the approach was performed in a modelling study in Article IV (Chapter 5). This way, the approach has been validated by applying it to realistic cases. These are modelling the concentrations of the materials nano-TiO2, nano-ZnO, nano-Ag and CNT in the European Union. For each of the materials the concentrations in surface water, sediment, natural and urban soil, sludge treated soil and air have been estimated for the year 2014. Thereby, the appropriateness of the approach could be proved for the investigated class of exposure models.

Life Cycle Assessment (LCA) is perhaps the leading technique for assessing the environmental impact of products over their entire life cycle, and currently plays a decisive role in the field of environmental management. The technique is highly data-intensive and would be practically impossible without using the background unit process datasets provided by Life Cycle Inventory (LCI) databases. A typical product life cycle covers thousands of unit processes, each of which needs to be described with exchange flow data. Although the increased availability of LCI databases has substantially decreased the amount of work involved in conducting an LCA, the high costs associated with data collection still impose substantial limitations on the quality of LCA. These limitations either take the form of uncertain or incomplete background data, which must be gathered and maintained at great effort, or an excessively generic representation of highly context-dependent activities, for example, agricultural work. The overall goal of this dissertation is to increase the efficiency and effectiveness of data collection in LCA by means of two novel and complementary solutions based on information systems (IS). The first solution is a statistical prioritization approach that directs LCI database improvement efforts toward datasets of key importance in terms of their potential influence on overall database quality. This approach aims to increase the effectiveness of data collection for LCI databases. The second solution is a computational framework that facilitates the automated generation of regionalized cultivation datasets on the basis of publicly available spatial (raster) data. This approach aims to increase the efficiency and quality of unit process dataset generation in the important domain of agricultural LCAs. We examine the first, statistical prioritization approach in detail in two research articles. Article I (Chapter 2) presents a computational framework for prioritizing LCI database improvements. We demonstrate, then evaluate, a method for database-wide contribution analysis (CA) and corresponding summary measures that facilitate the identification of key processes, that is to say, unit processes with consistently large relative contributions throughout all product systems in the database. We show that prioritizing the improvement efforts is very useful because a tiny, robust nucleus of unit processes proves to be consistently important across all product systems and many Life Cycle Impact Assessment (LCIA) indicators. Focusing research efforts on these processes makes it possible to improve the LCI database effectively. Article II (Chapter 3) applies the same statistical prioritization framework to the ecoinvent databases in a comprehensive case study. We identify the most important unit processes according to a set of 19 selected LCIA indicators using a newly developed ranking algorithm. Our study shows that a relatively large proportion of the overall database quality is dependent on a small set of key processes. Overall, 300 (out of 11,000) datasets cause 60% of the environmental impacts across all LCIA indicators, while just three datasets cause 11% of all climate change impacts. We present a ranking of key processes that adds a new perspective to database improvements, in that it makes it possible to allocate resources according to the structural dependencies in the data. We examine the second, regionalization approach in another research article. Article III (Chapter 4) presents a computational framework that allows the automated, site-specific (regionalized) generation and assessment of cradle-to-gate agricultural unit process datasets. The framework facilitates the transformation of publicly available spatial (raster) data into comprehensive unit process datasets using default data from Version 3.2 of the ecoinvent database and the emission models from the World Food Life Cycle Database (WFLDB) guidelines. To illustrate the application of our framework, we describe its key features and present a case study on rapeseed production in Germany. Our study shows that automatically generating regionalized cultivation datasets harbors great potential for improving the accuracy of agricultural unit process datasets in LCA applications. With 580,000 datasets, the case study presented is likely the most comprehensive cradle-to-gate LCA on the climate change and eutrophication impacts of rapeseed cultivation in Germany. Our research demonstrates that both prioritization and regionalization are valid, useful approaches to improving the data foundation of LCA-based decision-making. The prioritization framework makes it easier to align data collection efforts in LCI databases with those datasets that are the most important in terms of their overall influence on the quality of the database. Focusing research efforts on these processes makes it possible to effectively improve the datasets that play a dominant role in nearly every LCA application. Our research provides valuable new design knowledge in the form of operational principles that can be applied and adapted in other, as yet unstudied fields. Our framework for regionalized LCI modeling makes it easier to automatically generate high-resolution agricultural process datasets for all major crops and all regions around the world. The framework improves the geographical representativeness and reproducibility of agricultural datasets and offers new possibilities for their aggregation and analysis. Finally, the design knowledge that we develop provides a starting point for enhancing the utility of LCA, particularly in the context of other environmental system analysis tools.

The need for an environmental risk assessment for engineered nanomaterials (ENM) necessitates the knowledge about their environmental emissions. Material flow models (MFA) have been used to provide predicted environmental emissions but most current nano-MFA models consider neither the rapid development of ENM production nor the fact that a large proportion of ENM are entering an in-use stock and are released from products over time (i.e., have a lag phase). Here we use dynamic probabilistic material flow modeling to predict scenarios of the future flows of four ENM (nano-TiO2, nano-ZnO, nano-Ag and CNT) to environmental compartments and to quantify their amounts in (temporary) sinks such as the in-use stock and (“final”) environmental sinks such as soil and sediment. In these scenarios, we estimate likely future amounts if the use and distribution of ENM in products continues along current trends (i.e., a business-as-usual approach) and predict the effect of hypothetical trends in the market development of nanomaterials, such as the emergence of a new widely used product or the ban on certain substances, on the flows of nanomaterials to the environment in years to come. We show that depending on the scenario and the product type affected, significant changes of the flows occur over time, driven by the growth of stocks and delayed release dynamics.

Is higher education capable of promoting learning for change? Can transformative learning nurture spaces for innovation in education for sustainable development? A call to action from saguf.