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Abstract Island communities are among the first and most adversely affected by the impacts of global climate change. Islands are vulnerable to climate change because of their isolated geography, large coastal areas, and low economic diversification. This paper presents a model-based evaluation of the macroeconomic impacts of climate change on the Blue Economy of southern European islands. We consider climate change impact chains on tourism, maritime transport, and electricity demand in a downscaled modeling framework for different climatic scenarios to the end of the century. Our findings show important economic losses in all climatic scenarios, yet economic damages under an RCP8.5 scenario more than doubled compared to a RCP2.6 pathway. Magnitudes of impacts vary across islands, depending on the level of economic diversification and geographic remoteness. The effects of climate change on the tourism sector are detrimental to the islandic economies, given the sector’s complex value chain and dominant position in value added. Similarly, increasing electricity demand for cooling and water desalination puts additional stress on the economy of the islands.

The EU decarbonization strategy foresees deep cuts in CO2 in the transport sector. Investment in infrastructure, manufacturing of new technology vehicles and production of alternative fuels induce macroeconomic changes in activity and employment for both national and regional economies. The objective of the paper is to present a newly built macroeconomic-regional model (GEM-E3-R general equilibrium model for economy, energy and environment for regions) for assessing impacts of transport sector restructuring on regional economies of the entire EU, segmented following NUTS-3 (nomenclature of territorial units of statistics). The model combines general economic equilibrium theory with location choice and New Economic Geography and implements a dynamic, fully endogenous agglomeration-dispersion mechanism for people and industries coupled with a gravity model for bilateral interregional flows. A novelty of the model is a two-layers structure: (i) the country-wide layer formulated as a global multi-sector, multi-country and multi-period computable general equilibrium (CGE) model; and (ii) the regional economy layer, which simulates impacts on regional economies, while considering country-wide economic trends as boundary conditions. The paper presents a use of the model in the assessment of regional economic effects of electrification of car mobility in Europe and wide use of domestically produced advanced biofuels.

The public is increasingly becoming aware of environmental challenges and adjusting its purchasing behavior in pursuit of sustainable products and services. To compete in the global scene, firms need to transform their supply chains to adhere to eco-friendly practices. This study focuses on the electronics market, which is distinctively interesting due to its small product life cycles, high-end capabilities, and fierce competition. A novel research model comprising nine hypotheses that attempt to investigate and assess the factors influencing customers’ perceptions and purchasing preferences in relation to green supply chains in the electronics industry was developed. We conducted field research to test the model empirically using survey data from 147 individuals with different backgrounds. The dataset was verified and validated by means of explanatory factor analysis. Structural equation modeling analysis was performed that revealed the linkage between demographics (age), willingness to pay, purchasing intention, and green consumerism. Other research findings included the intricate interconnections between environmental concern, knowledge, attitude, customers’ perceptions/effectiveness, and behavior. This research gives insights into green consumerism in the electronics sector, and its managerial implications can guide sustainable supply chain practices and customer-centric marketing approaches.

Climate change and inequality are critical and interrelated issues. Despite growing empirical evidence on the distributional implications of climate policies and climate risks, mainstream model-based assessments are often silent on the interplay between climate change and economic inequality. Here we fill this gap through an ensemble of eight large-scale integrated assessment models that belong to different economic paradigms and feature income heterogeneity. We quantify the distributional implications of climate impacts and of the varying compensation schemes of climate policies compatible with the goals of the Paris Agreement. By 2100, climate impacts will increase inequality by 1.4 points of the Gini index on average. Maintaining global mean temperature below 1.5 °C reduces long-term inequality increase by two-thirds but increases it slightly in the short term. However, equal per-capita redistribution can offset the short-term effect, lowering the Gini index by almost two points. We quantify model uncertainty and find robust evidence that well-designed policies can help stabilize climate and promote economic inclusion.

PROOF, the Parallel ROOT Facility, is a ROOT-based framework which enables interactive parallelism for event-based tasks on a cluster of computing nodes. Although PROOF can be used simply from within a ROOT session with no additional requirements, deploying and configuring a PROOF cluster used to be not as straightforward. Recently great efforts have been spent to make the provisioning of generic PROOF analysis facilities with zero configuration, with the added advantages of positively affecting both stability and scalability, making the deployment operations feasible even for the end user. Since a growing amount of large-scale computing resources are nowadays made available by Cloud providers in a virtualized form, we have developed the Virtual PROOF-based Analysis Facility: a cluster appliance combining the solid CernVM ecosystem and PoD (PROOF on Demand), ready to be deployed on the Cloud and leveraging some peculiar Cloud features such as elasticity. We will show how this approach is effective both for sysadmins, who will have little or no configuration to do to run it on their Clouds, and for the end users, who are ultimately in full control of their PROOF cluster and can even easily restart it by themselves in the unfortunate event of a major failure. We will also show how elasticity leads to a more optimal and uniform usage of Cloud resources.

Long-term preservation of scientific data represents a challenge to experiments, especially regarding the analysis software. Preserving data is not enough; the full software and hardware environment is needed. Virtual machines (VMs) make it possible to preserve hardware “in software”. A complete infrastructure package has been developed for easy deployment and management of VMs, based on CERN virtual machine (CernVM). Further, a HTTP-based file system, CernVM file system (CVMFS), is used for the distribution of the software. It is possible to process data with any given software version, and a matching, regenerated VM version. A point-and-click web user interface is being developed for setting up the complete processing chain, including VM and software versions, number and type of processing nodes, and the particular type of analysis and data. This paradigm also allows for distributed cloud-computing on private and public clouds, for both legacy and contemporary experiments.

The stability of magnetic skyrmions has been investigated in the past, but mostly in the absence of thermal fluctuations. However, thermal spin fluctuations modify the magnetic properties (exchange stiffness, Dzyaloshinskii-Moriya interaction (DMI) and anisotropy) that define skyrmion stability. Thermal magnons also excite internal skrymion dynamics, deforming the skyrmion shape. Entropy has also been shown to modify skyrmion lifetimes in experiments, but is absent or approximated in previous studies. Here we use metadynamics to calculate the free energy surface of a magnetic thin film in terms of the topological charge and magnetization. We identify the free energy minima corresponding to different spin textures and the lowest energy paths between the ferromagnetic and single skyrmion states. We show that at low temperatures the lowest free energy barrier is a skyrmion collapse process. However, this energy barrier increases with temperature. An alternative path, where a singularity forms on the skrymion edge, has a larger free energy barrier at low temperatures but decreases with increasing temperature and eventually becomes the lowest energy barrier.

Volunteer computing (VC) or distributed computing projects are common in the citizen cyberscience (CCS) community and present extensive opportunities for scientists to make use of computing power donated by volunteers to undertake large-scale scientific computing tasks. Volunteer computing is generally a non-interactive process for those contributing computing resources to a project whereas volunteer thinking (VT) or distributed thinking, which allows volunteers to participate interactively in citizen cyberscience projects to solve human computation tasks. In this paper we describe the integration of three tools, the Virtual Atom Smasher (VAS) game developed by CERN, LiveQ, a job distribution middleware, and CitizenGrid, an online platform for hosting and providing computation to CCS projects. This integration demonstrates the combining of volunteer computing and volunteer thinking to help address the scientific and educational goals of games like VAS. The paper introduces the three tools and provides details of the integration process along with further potential usage scenarios for the resulting platform.

PROOF, the Parallel ROOT Facility, is a ROOT-based framework which enables interactive parallelism for event-based tasks on a cluster of computing nodes. Although PROOF can be used simply from within a ROOT session with no additional requirements, deploying and configuring a PROOF cluster used to be not as straightforward. Recently great efforts have been spent to make the provisioning of generic PROOF analysis facilities with zero configuration, with the added advantages of positively affecting both stability and scalability, making the deployment operations feasible even for the end user. Since a growing amount of large-scale computing resources are nowadays made available by Cloud providers in a virtualized form, we have developed the Virtual PROOF-based Analysis Facility: a cluster appliance combining the solid CernVM ecosystem and PoD (PROOF on Demand), ready to be deployed on the Cloud and leveraging some peculiar Cloud features such as elasticity. We will show how this approach is effective both for sysadmins, who will have little or no configuration to do to run it on their Clouds, and for the end users, who are ultimately in full control of their PROOF cluster and can even easily restart it by themselves in the unfortunate event of a major failure. We will also show how elasticity leads to a more optimal and uniform usage of Cloud resources.