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The circular economy model aims to reduce the consumption of virgin materials by increasing the time materials remain in use while transitioning economic activities to sectors with lower material intensities. Circular economy concepts have largely been focussed on the role of businesses and institutions, yet consumer changes can have a large impact. In a more circular economy consumers often become users-they purchase access to goods and services rather than physical products. Other consumer engagement includes purchasing renewable energy, recycling and using repair and maintenance services etc. However, there are few studies on whether consumers actually make these sorts of consumption choices at large scale, and what impacts arise from these choices on life-cycle material consumption. Here we examine what types of households exhibit circular consumption habits, and whether such habits are reflected in their material footprints. We link the Eurostat Household Budget Survey 2010 with a global input-output model and assess the material footprints of 189 800 households across 24 European countries, making the results highly generalizable in the European context. Our results reveal that different types of households (young, seniors, families etc) adopt different circular features in their consumption behaviour. Furthermore, we show that due to rebound effects, the circular consumption habits investigated have a weak connection to total material footprint. Our findings highlight the limitations of circular consumption in today's economic systems, and the need for stronger policy incentives, such as shifting taxation from renewable resources and labour to non-renewable resources.

Due to the open data policies, nowadays, some countries have their power grid data available online. This may bring a new concern to the power grid operators in terms of malicious threats. In this paper, we assess the vulnerability of power grids to targeted attacks based on network science. By employing two graph models for power grids as simple and weighted graphs, we first calculate the centrality metrics of each node in a power grid. Subsequently, we formulate different node-attack strategies based on those centrality metrics, and empirically analyse the impact of targeted attacks on the structural and the operational performance of power grids. We demonstrate our methodology in the high-voltage transmission networks of 5 European countries and in commonly used IEEE test power grids.

For this study, we investigated efficient strategies for the recovery of individual links in power grids governed by the direct current (DC) power flow model, under random link failures. Our primary objective was to explore the efficacy of recovering failed links based solely on topological network metrics. In total, we considered 13 recovery strategies, which encompassed 2 strategies based on link centrality values (link betweenness and link flow betweenness), 8 strategies based on the products of node centrality values at link endpoints (degree, eigenvector, weighted eigenvector, closeness, electrical closeness, weighted electrical closeness, zeta vector, and weighted zeta vector), and 2 heuristic strategies (greedy recovery and two-step greedy recovery), in addition to the random recovery strategy. To evaluate the performance of these proposed strategies, we conducted simulations on three distinct power systems: the IEEE 30, IEEE 39, and IEEE 118 systems. Our findings revealed several key insights: Firstly, there were notable variations in the performance of the recovery strategies based on topological network metrics across different power systems. Secondly, all such strategies exhibited inferior performance when compared to the heuristic recovery strategies. Thirdly, the two-step greedy recovery strategy consistently outperformed the others, with the greedy recovery strategy ranking second. Based on our results, we conclude that relying solely on a single metric for the development of a recovery strategy is insufficient when restoring power grids following link failures. By comparison, recovery strategies employing greedy algorithms prove to be more effective choices.

We study the electrodynamic impedance of percolating conductors with a pre-defined network topology using a scanning microwave impedance microscope (sMIM) at GHz frequencies. For a given percolation number we observe strong spatial variations across a sample which correlate with the connected regions (clusters) in the network when the resistivity is low such as in Aluminum. For the more resistive material NbTiN the impedance becomes dominated by the local structure of the percolating network (connectivity). The results can qualitatively be understood and reproduced with a network current spreading model based on the pseudo-inverse Laplacian of the underlying network graph.

Due to increased environmental concerns, utilization of the renewable energy, especially the wind power, gains importance. Like developed countries which have set their renewable energy targets for the long term integration, Turkish government has also set the goal as 20 GW of total wind power installed capacity in 2023. In this thesis, the wind power potential in Turkey is analyzed and different cases are studied to determine optimal locations for wind power plant establishment.In order to determine the wind power potential, annual and seasonal average wind speeds and Weibull distribution parameters of the speed are calculated for every 6 km x 6 km area in Turkey. Moreover, using calculated parameters of the speed, wind power densities and capacity factors of the potential power plant are determined. To visualize results via maps, Plate Carrée map transformation is utilized.The calculated wind speed parameters, the altitude and urban data of Turkey are used to find the set of feasible locations for wind power plant establishment and possible transformer substation connections for wind power plants. Then, among the set of feasible locations, linear programming optimization method is performed in the expected 2017 summer peak scenario of Turkey to determine optimal locations of wind power plants which lead maximum annual wind power production. While solving the optimization problem, DC load flow equations are utilized by taking the transmission constraints into account and the impact of wind power penetration on Turkish grid is analyzed.