Contributions published at Informatics and Sustainability Research (Lorenz Hilty)

The use of drones (or Unmanned Aerial Vehicles) in urban areas has emerged rapidly in the last decade, and continues to expand at an accelerating pace. Alongside the emergent uses of high-impact technology in both public and private sectors, political debates about the potential risks and challenges have arisen, encompassing diverse perspectives and attitudes about the ethical, legal, social, and regulatory implications of introducing and integrating new technology in society. This scoping review offers an assessment of the societal acceptance factors of urban drones discussed in the current academic literature. We used a hybrid approach including quantitative landscape mapping and qualitative content analysis of the selected articles to inductively develop a typology of acceptance factors associated with urban use of drones. This review illuminates areas that have been the focus of attention within the current body of knowledge (e.g., visual and noise pollution of drones), sketches the evolution of the relevant discussions over time (e.g., a focus on the safety of the drone technology toward safety of the cargo it carries and security of the data it collects), and points to areas that have received less considerations (e.g., media appropriation and social group influence). It can, thus, help situate the topic of societal acceptance of urban drones in specific contexts, and orient future research on promoting value sensitive innovation in society more broadly.

In this study the energy consumption and greenhouse gas emissions of a video livestream with a length of four hours on the livestreaming platform twitch.tv were calculated. The video transmission requires the end devices of the streamer and the viewer, the data centres and the communication network. The communication network is separated into wide area network, radio access network and fixed network. In the reference scenario, the livestreamer uses a desktop PC and two screens to broadcast a video with a resolution of 1080p and 60hz through a fixed network connection. Viewers can play the livestream on different end devices. As a result of the calculations, the range of greenhouse gas emissions generated during the livestream is between 207 and 804g CO2. The difference is due to the choice of the used end device and the difference between wireless and landline connections. For the end devices, the screen size is an important factor for the contribution to the total energy consumption of a livestream. The radio access network connection has the highest energy intensity because of the consumption of the older radio generations compared to 4G. The enhancement of the internet infrastructure to 5G will lead to more efficient transmission and the main consumption will shift to the end devices. The choice of the end device and its usage can offset the savings of the energy and the greenhouse emissions by switching to a better internet infrastructure. Strategies are needed against more intensive production and consumption to oppose the climate change.

ICT hold significant potential to increase resource and energy efficiencies and contribute to a circular economy. Yet unresolved is whether the aggregated net effect of ICT overall mitigates or aggravates environmental burdens. While the savings potentials have been explored, drivers that prevent these and possible counter measures have not been researched thoroughly. The concept digital sufficiency constitutes a basis to understand how ICT can become part of the essential environmental transformation. Digital sufficiency consists of four dimensions, each suggesting a set of strategies and policy proposals: (a) hardware sufficiency, which aims for fewer devices needing to be produced and their absolute energy demand being kept to the lowest level possible to perform the desired tasks; (b) software sufficiency, which covers ensuring that data traffic and hardware utilization during application are kept as low as possible; (c) user sufficiency, which strives for users applying digital devices frugally and using ICT in a way that promotes sustainable lifestyles; and (d) economic sufficiency, which aspires to digitalization supporting a transition to an economy characterized not by economic growth as the primary goal but by sufficient production and consumption within planetary boundaries. The policies for hardware and software sufficiency are relatively easily conceivable and executable. Policies for user and economic sufficiency are politically more difficult to implement and relate strongly to policies for environmental transformation in general. This article argues for comprehensive policies for digital sufficiency, which are indispensible if ICT are to play a beneficial role in overall environmental transformation.

Various studies have assessed the GHG footprint of the ICT sector (ICT end-user devices, data centers, telecommunication networks) and the potential of ICT use cases (e.g. smart homes, ride sharing) to avoid GHG emissions in other sectors (e.g buildings, transport). We systematically compare relevant studies from the last ten years and discuss the robustness of results in view of the methods used. The results show that the ICT sector causes between 1.5% and 4% of global GHG emissions, a major share of which is due to the production of ICT end-user devices. Estimating GHG impacts of device production is the main source of uncertainty. Results of studies on ICT's GHG abatement potential are less robust, in particular due to uncertainty with regard to use case impacts in a real-life setting, types and sizes of economy-wide rebound effects. Thus the existing studies do not provide a reliable basis for estimating the actually realized GHG abatements. To improve the assessment results and provide a more reliable basis for deriving GHG reduction measures future research should empirically investigate which solution design and accompanying policies are suitable to exploit GHG reduction potentials in real-life. Results of these studies would also increase the robustness of assessments of GHG abatement potentials.

Information communication technology (ICT)’s environmental impact must be considered in digital innovation and associated policy to mitigate ICT’s climate change contribution. A pro- posed solution to reduce ICT emissions is by improving efficiency, yet this fails to consider rebound effects where efficiency improvements offset emissions savings or increase emissions. In this perspective, we reveal insights from a transdisciplinary workshop that identified challenges for why rebound effects are difficult to include in innovation and policy. From this, we call researchers to (1) find new ways of presenting rebound effects to digital innovators and policymakers; (2) gather cross-disciplinary evidence of ICT rebound effects; and (3) transparently analyze ICT’s environmental, societal, and economic impacts together. We also call for a systems thinking approach to addressing ICT’s environmental impacts, whereby a solution to rebound ef- fects becomes visible: efficiencies under emission constraints.

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Governments worldwide hope that digital technologies can provide key solutions. Yet this report shows that digitalisation, in its current and mainstream form, is rather aggravating than solving many of the pressing social and environmental crises at hand. What is needed instead is a deep sustainability transformation that fundamentally reorganises the economy and all its sectors - agriculture, mobility, energy, buildings, industry, and consumption. The Report »Digital Reset« shows how digital technologies can support the quest for such a deep sustainability transformation. The report provides a blueprint for the European Union on how to reconceptualise digitalisation so that it first and foremost contributes to achieving carbon neutrality, resource autonomy and economic resilience while supporting equity and fully respecting citizen's rights and privacy. The report is the outcome of a two-year international science-policy dialogue, »Digitalization for Sustainability« (D4S), and presents an up-to-date comprehensive analysis of opportunities, risks and governance options regarding digitalization and sustainability.

5G mobile networks are intended to meet the increasing requirements placed on mobile communications. Producing and operating 5G infrastructure causes direct effects on greenhouse gas (GHG) emissions. Meanwhile, 5G is expected to support applications that contribute to GHG abatement. We investigated (i) the GHG footprint of 5G infrastructure, and (ii) the GHG abatement potential of four 5G-supported use cases (i.e., flexible work, smart grids, automated driving and precision farming) for Switzerland in 2030. Our results show that 5G infrastructure is expected to cause 0.018 Mt CO2 e/year. Per unit of data transmitted, 5G is expected to cause 85% less GHG emissions in 2030 than today’s 2G/3G/4G network mix. The four 5G-supported use cases have the potential to avoid up to 2.1 Mt CO2 e/year; clearly more than the predicted GHG footprint of 5G infrastructure. The use cases benefit especially from ultra-low latency, the possibility to connect many devices, high reliability, mobility, availability and security provided by 5G. To put 5G at the service of climate protection, measures should be taken in two fields. First, the GHG footprint of 5G should be kept small, by installing only as much 5G infrastructure as required, running 5G with electricity from renewable energy sources, and decommissioning older network technologies once 5G is widely available. Second, the GHG abatements enabled by 5G-supported use cases should be unleashed by creating conditions that target GHG reductions and mitigate rebound effects. The final outcome depends largely on the political will to steer the development into the direction of a net GHG reduction.

A promising strategy to reduce smartphones' environmental footprint is to increase their service lifetime, thereby reducing the demand for resource-intensive production of new devices. Most of the existing literature focuses on production-oriented measures, such as improving repairability, but what remains missing is a systematic overview of consumer-oriented interventions to extend smartphones' service lifetime. In this study, we applied the consumer intervention mapping approach by systematically identifying consumer decision situations along the smartphone life cycle and interventions that encourage consumers to make smartphone lifetime-extending decisions. We identify two main mechanisms to achieve lifetime extension: retention by increasing the time during which a user keeps a device, and recirculation by passing on a device to an additional user. Altogether, we identified 26 different types of interventions to induce consumers to make smartphone lifetime-extending decisions and structure these according to consumer-influence techniques, e.g., informing consumers about retention/recirculation options and environmental impacts caused throughout device life cycles, persuading consumers by creating emotional attachment, nudging consumers through product labels for secondhand devices, simplifying execution of lifetime-extending decision options through take-back programs, and incentivizing lifetime-extension through buy-back programs. These interventions' success in achieving lifetime extensions and reducing environmental impacts in practice depends on the degree to which they actually extend smartphones' service lifetime and reduce production of new devices (displacement rate), induction and re-spending effects associated with the interventions, and the interventions’ implementation feasibility, which conflicts of interest in the smartphone ecosystem often challenge.

Green ZORA is a project at the University of Zurich that classifies scientific papers published at the University of Zurich into whether they are “about sustainability” or are “not about sustainability”. In this thesis we will go one step further into the project and prototype the additional feature to not only classify the papers into “about sustainability” or “not about sustainability” but into directly one of the 17 SDGs that were set up by the United Nations General Assembly. The goal of this thesis can be summarized as to identify and prototype a machine learning based SDG-classification for scientific papers published on ZORA. In this thesis I will not only present the implementation of the prototype but also its results and the future work that can be done to keep improving it.

In most Western democracies, non-institutionalized political activities such as political consumerism often represent the only accessible means of political expression for foreign residents. However, the few studies available to date show that foreign residents consume significantly less politically than national citizens. This study examines how the key political resources education, political interest, and organization membership may account for this gap. By means of original survey data from Switzerland, I find that (i) organization membership is the strongest predictor for political consumerism but does not explain the participation gap; (ii) political interest is the most important resource to explain why foreign residents consume less politically than Swiss citizens; and (iii) the three resources work similarly for both groups, whereas political interest and education act as partial mediators. The results of this study suggest that political resources mediate rather than moderate political consumer differences based on citizenship status.

The results for the calculation of the energy consumption of streaming are currently very far apart. The difficulty here is that many assumptions have to be made and the streaming process is very complex. The aim of this work is to determine the relevant parameters for the energy consumption of streaming and also to show ways to effectively reduce energy consumption using these parameters. To achieve this goal, available literature was used to analyze the streaming process to find out where energy is consumed during video streaming. In the second part, it was worked out which parameters have a decisive influence on the level of energy consumption. It turned out that the relevant parameters for the energy consumption of streaming are the utilization and energy efficiency of the servers in the data centers, the file size of the videos, the efficiency of file transfer and the screen size of the end device. Effective ways to reduce energy consumption with these parameters are the purchase of energy-efficient servers, server virtualization, the use of so-called content delivery networks (CDN), the expansion of fiber optic networks and the 5G infrastructure, the compression of video files and the choice of smaller dispaying devices.

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This study sought to calculate the environmental impacts of streaming video in terms of energy use and carbon dioxide emissions, based on technical and geographical parameters. The resulting data was used to create an online carbon dioxide calculator, which allows users to estimate the environmental impact of their own video consumption. The calculator can be accessed online at https://streaming-co2-rechner.ch/. To calculate the environmental impacts, the energy consumption of the various components involved in the distribution and playback of the video content was taken into account: the data centers, the communication networks and the end devices. In an engagement with current studies, it was found that, on average, streaming video emits 62 g CO2e per hour. This is equivalent to driving a car for 430 meters. However, this value can not be applied indiscriminately to any streaming scenario, as there is inherent variability in the estimates depending on various factors. The calculator allows users to identify the factors that most significantly affect the results. These include the country-specific emissions factor for the electricity grid, the video resolution, the choice of end device and the choice of network connection. The study also identified a need for further research into the use of appropriate allocation rules in order to calculate the impacts of streaming video in a more precise and consistent way. It was found that the use of energy consumption values per unit of data is not suitable for streaming and other data-intensive services. This leads to significant uncertainty in calculating the energy consumption of network components, as there is currently a lack of quantitative data and appropriate calculation methods need to be further validated and refined.

he digital world and our economy rely on data, and blockchain is ideally suited for supplying this information. It delivers real-time, transparent, and fully sharable data stored on an immutable ledger that only authorized network users can access. At the same time, solutions are necessary due to the growing environmental threat caused by specific blockchain platforms, such as Bitcoin and Ethereum. The energy-intensive Proof-of-Work consensus algorithm is responsible for their high energy consumption and carbon footprint. This bachelor thesis examines the consensus mechanisms Proof-of-Work and Proof-of-Stake. This paper aims to investigate the transition from Proof-of-Work to Proof-of-Stake, emphasizing environmental sustainability. In addition, this thesis seeks to determine if there are any implications for developing and implementing blockchain platforms and oracles. The paper is written under the framework of the Blockchain Presence Project and Informatics Sustainability Research Group. A systematic literature review has been conducted to answer the research questions and understand why blockchain platforms intend to move to energy-efficient consensus protocols.

Nicht-institutionalisierte politische Aktivitäten wie politischer Konsum sind in den meisten Demokratien für Ausländer*innen oft die einzige Möglichkeit, sich politisch zu beteiligen. Umfragedaten zum politischen Konsum in der Schweiz zeigen aber, dass Ausländer*innen deutlich weniger politisch konsumieren als Schweizer Bürger*innen. Meine Analysen zeigen, dass das politische Interesse den dafür grössten Erklärungsfaktor darstellt.

Genetic Algorithms employ the underlying mechanisms that give rise to evolution in order to approach computational challenges. In this context, a Genetic Algorithm is implemented and used to perform a global Sensitivity Analysis on a simulated Swiss city as part of the ongoing Post Fossil Cities project. Spanning three scenarios, the Genetic Algorithm is able to identify the ensemble of Population, Energy Intensity, and the collective of Typesplit and Splitshare resources as the main factors that can reduce the Carbon Dioxide (CO2) emissions and energy consumption within this city. Further investigation into the Genetic Algorithm’s behaviour using a multiple linear regression shows that both the population size and the number of generations have a significant impact on the fitness that can be reached. Additionally, as a side-product of the genetic mechanisms, an instability of the diversity emerges at small population sizes that closely resembles genetic drift. When comparing the performance of the Genetic Algorithm to a Monte-Carlo approach, there is a highly significant advantage in favour of the Genetic Algorithm.

As engineering is being more and more virtualized, simulations replace real testing and are becoming increasingly sophisticated. Co-simulation environments allow for several such simulations to be connected and executed together, automating the exchange of data between them. These environments have been gaining popularity as they can be used to model a set of connected systems more properly. But most co-simulation tools that have been created until now were either commercial or designed for a specific area of research. Further, data validation is getting little attention in research about co-simulation, although it is integral to ensure plausibility of a simulation's results. This thesis gives an overview over the commonly used standards and technologies, focusing on the FMI standard for co-simulation. It proposes ways on how to realise them with integrated validation processes. Using this information, an implementation is provided in Python and Android. Any person can use the newly created software without needing to understand the underlying systems, only requiring basic programming knowledge to deploy data validation processes. It allows users of any research area to quickly set up and test their models in a co-simulation environment, minimizing the resources required for an initial deployment.

Research projects often generate large amounts of data that are of interest not only to the scientists who were originally involved in the project, but also to other scientists and various groups of stakeholders. However, most open-data initiatives only enable access to raw data, requiring considerable data analysis expertise and implicitly limiting the prospective users of the data to scientists with such expertise. In order to make open-data accessible also to stakeholder groups outside the scientific community, other forms of data representation may be required. The master project documented in this thesis uses dashboard techniques for this purpose and a research project funded by the EU under the Horizon 2020 program as a case. In Study 1, the development of four interactive dashboard prototypes is documented from requirements gathering to launch. In Study 2, the usability of the dashboards is assessed in terms of task completeness, task completion time, the System Usability Scale (SUS) plus a qualitative analysis of think-aloud protocols collected from test users. Taken together, the results show that the created dashboards are easy to use and that the visualized research data is understandable for users with and without prior knowledge about the research project that served as a case. Possible extensions to dynamic data and semi-structured verbal data are discussed.