• Energy Research
• 13. Climate action close
• 15. Life on land close
• 14. Life underwater close
• GR close
• ZENODO close

This dataset contains the underlying data for the following publication: Doukas, H., Spiliotis, E., Jafari, M. A., Giarola, S. & Nikas, A. (2021). Low-cost emissions cuts in container shipping: Thinking inside the box. Transportation Research Part D: Transport and Environment, 94, 102815, https://doi.org/10.1016/j.trd.2021.102815.

This data set contains the essential files used as input for the analysis, intermediate files produced during the analysis, and the key output fields. The code of the analysis is available here: https://github.com/VUB-HYDR/2021_Thiery_etal_Science Input fields: - isimip.zip: Postprocessed ISIMIP2b simulation output. This data set is very similar to the data presented in Lange et al. (2020 Earth's Future) but includes selected additional impact models and scenarios (notably RCP8.5). This data set also includes the gridded population data. - GMT_50pc_manualoutput_4pathways.xlsx: Global mean temperature anomaly trajectories from the IPCC SR15 - wcde_data.xlsx: postprocessed cohort size data originally obtained from the Wittgenstein Centre Human Capital Data Explorer. - WPP2019_MORT_F16_1_LIFE_EXPECTANCY_BY_AGE_BOTH_SEXES.xlsx: Postprocessed life expectancy data originally obtained from the UNited Nations World Population Programme Intermediate files *only use if you're interested in reproducing the results*: - workspaces.zip: Postprocessed ISIMIP2b simulation output. These matlab workspaces contain data on land area annually exposed to extreme events which is stored in a format designed to speed up the analysis. - mw_isimip.mat: ISIMIP2 simulations metadata (e.g. model, gcm and rcp name per simulation) - mw_countries.mat: information on the countries used in the analysis (e.g. border polygon coordinates) - mw_exposure.mat: age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic.mat: pre-industrial control age-dependent exposure computed from the ISIMIP and population data - mw_exposure_pic_coldwaves.mat: pre-industrial control age-dependent exposure to coldwaves computed from the ISIMIP and population data Output of the analysis: - mw_output.mat: Matlab workspace containing all variables produced during the analysis presented in thepaper. Use this file if you wish to look up certain numbers or want to use the study results for further analysis.

This dataset contains the underlying data for the following publication: Song, L., Lieu, J., Nikas, A., Arsenopoulos, A., Vasileiou, G., & Doukas, H. (2020). Contested energy futures, conflicted rewards? Examining low-carbon transition risks and governance dynamics in China's built environment. Energy Research & Social Science, 59, 101306., https://doi.org/10.1016/j.erss.2019.101306. Full details of methods used to create the dataset and provided within this publication.

The report “Effects of Air Temperature Modified by Vulnerability Factors” was prepared as a milestone by researchers in the EU Project EXHAUSTION*. This report summarises the evidence on the interactive effects of high air temperature and various vulnerability factors, including the environmental, socio-economic, and individual behavioral factors on heart- and lung-related deaths and diseases (cardiopulmonary mortality and morbidity) across Europe. The study was conducted at the city, small-area (e.g., municipalities), and individual level. The findings show a greater vulnerability to heat for people living in urban areas with dense population, high air pollution levels, low coverage of green spaces, as well as areas with low Gross Domestic Product. Moreover, people with chronic pre-existing diseases and the elderly were found to be at greater risk. The findings highlight the urgent need to improve the urban environment as well as the health status and living conditions in European cities to contrast the impacts of heat and future climate change. This report alerts stakeholders and policymakers that targeted climate change adaptation measures need to be considered to protect vulnerable population and thereby increase European resilience to climate change.

This paper explores Climate Protection at a local level. Initially it was essential to define and understand the “Greenhouse Effect” before evaluating local authorities’ potential to counteract it. We examined strategies dealing with the problem of climate change and particular emphasis was placed on the potential for local authorities to exert an influence. We examined the frameworks, policies, challenges, problems and best practices for climate protection at a local level. Our research examined ten municipalities on the island of Rhodes in Greece and assessed their current contribution to climate protection. Results showed that all ten municipalities implement a range of measures to protect the climate and reduce CO2 emissions

In the recent decade, Machine Learning techniques have been widely deployed in solar systems due their high accuracy in predicting the performances without going through the physical modelling. In this work, the Artificial Neural Network (ANN) method is adopted to forecast the electrical and thermal efficiencies of a photovoltaic/thermal (PVT) air collector system. Indeed, two accurate modelling techniques have been used to generate the output results for training and validation. Both deployed electrical and thermal models have been validated experimentally and demonstrated high accuracy. Then, real climatic samples of one year with a 10 minute step of the Jordan valley location have been adopted to generate the electrical and thermal efficiencies. These latter are used in the training and validation of the developed ANN model under various combinations of the weather variables. The solar irradiance and the module temperature are the most important variables to consider as input in a NN-based model respectively. The developed ANN model shows MAE of 0.0078% and 3.3607% in predicting the electrical and thermal efficiency respectively. The electrical efficiency can be predicted with higher accuracy than the thermal efficiency. Further, the results demonstrate that the ANN outperforms the LS-SVM in forecasting the PVT air collector performances.

Recent calls to do climate policy research with, rather than for, stakeholders have been answered in non-modelling science. Notwithstanding progress in modelling literature, however, very little of the scenario space traces back to what stakeholders are ultimately concerned about. With a suite of eleven integrated assessment, energy system and sectoral models, we carry out a model inter-comparison for the EU, the scenario logic and research questions of which have been formulated based on stakeholders' concerns. The output of this process is a scenario framework exploring where the region is headed rather than how to achieve its goals, extrapolating its current policy efforts into the future. We find that Europe is currently on track to overperforming its pre-2020 40% target yet far from its newest ambition of 55% emissions cuts by 2030, as well as looking at a 1.0-2.35 GtCO2 emissions range in 2050. Aside from the importance of transport electrification, deployment levels of carbon capture and storage are found intertwined with deeper emissions cuts and with hydrogen diffusion, with most hydrogen produced post-2040 being blue. Finally, the multi-model exercise has highlighted benefits from deeper decarbonisation in terms of energy security and jobs, and moderate to high renewables-dominated investment needs.