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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.

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.

One of the aims of serious role-playing games (SRPG) is to educate people by simulating the impact of their actions in various domains. Climate change is one of these domains. Such SRPGs are usually based on complex simulations of heterogeneous models. However, interfacing a SRPG with heterogeneous simulations is currently a manual and fault-prone process that requires both domain-specific and technical knowledge. This research proposes a conceptual framework that supports game designers in interfacing their SRPGs with pre-existing or custom-tailored simulation models. In addition, a first implementation of such an interface is presented that further facilitates the creation, configuration and execution of such games.

"Blackout" is a novel by Marc Elsberg. It is about a Europe-wide blackout caused by a hacker attack on the power grid. The book impressively illustrates the consequences of a prolonged blackout, some of which are unimaginable for people who are not familiar with the topic. With the success of the fictional book Blackout, the topic of the vulnerability of the power grid and its consequences for society and the environment were brought to a wider audience. This paper validates the attack on the power grid from a technical perspective and discusses whether a similar attack could in fact lead to a Europe-wide blackout of the magnitude described. We distinguish between two types of effects that occur when the grid is attacked, immediate effects and consequences. If an attacker remotely cuts off the power of several households by hacking their smart meters, the immediate effect is that the hacked households no longer have power. A consequence is the instability of the power grid that may follow the immediate effect due to the fact that the generation and consumption of power are not in line anymore. Consequences form chains of effects which can be described by the metaphor of "domino effect". A blackout can reach out to places where nothing was attacked because the power grid as a whole collapses, which causes other infrastructures such as the telecommunications system, the traffic system and food supply chains to collapse. This paper mainly focuses on the validation of the immediate effects described in "Blackout".

Bees collect pollen from a variety of plant species. This pollen diversity is both an indicator of biodiversity and a balanced diet for bees which has a positive effect on their health. Traditionally, pollen diversity is determined by invasively and manually collecting and analysing the pollen. In this paper, we present a heuristic for assessing the pollen diversity around a hive using data on flora. This data-driven approach is both efficient and non-invasive. We evaluated our approach against the results of a microscope analysis, showing that it delivers useable results, despite the lack of flora data in some places. As a next step, we will incorporate data from our AI-based video monitoring system of hives to match plants based on pollen colours that were detected in the images.