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Data and scripts used for the paper 'A global census of the significance of giant mesopelagic protists to the biogeochemical cycles of carbon and silicon' authored by: Manon Laget, Laetitia Drago, Thelma Panaïotis, Rainer Kiko, Lars Stemmann, Andreas Rogge, Natalia Llopis-Monferrer, Aude Leynaert, Jean-Olivier Irisson, Tristan Biard

Having barely registered an increase at the beginning of the new millennium, during the economic upturn after 2009, there was significant growth in the mileage by registered motor vehicles in Germany, both in the case of utility vehicles and automobiles. Overall, in 2011, automobiles covered a higher mileage than ever before. Despite more efficient engines, this resulted in fuel consumption stagnating in recent years, although the long-term trend is one of decline. With an 85-percent share of total mileage, automobiles dominate our roads. This transport demand pattern is predominantly created by the needs of private households and it is currently in a state of flux when it comes to gender and age balance. Women's growing presence in education and on the labor market has, in turn, resulted in an increase in their car ownership and mileage. At the same time, men and women are maintaining a more mobile lifestyle by retaining their cars into older age. However, more limited car use has been observed, particularly among young people who, more frequently than previously, seem to be opting for the most suitable form of transport rather than traveling exclusively in their own vehicles.

Data and scripts used for the paper 'A global census of the significance of giant mesopelagic protists to the biogeochemical cycles of carbon and silicon' authored by: Manon Laget, Laetitia Drago, Thelma Panaïotis, Rainer Kiko, Lars Stemmann, Andreas Rogge, Natalia Llopis-Monferrer, Aude Leynaert, Jean-Olivier Irisson, Tristan Biard

This following special issue of the European Journal of Transport Infrastructure Research (EJTIR) containing 4 scientific papers is the result of the work conducted under the research project ‘National Transport Planning – Sustainability, Institutions and Tools’ (SUSTAIN) (2012- 2017) financed by the Danish Innovation Fund. SUSTAIN was coordinated by first the Department of Transport of the Technical University of Denmark (DTU Transport) and later as the result of a reorganisation of the transport research at DTU by the Department of Management Engineering (DTU Management Engineering). The project was carried out in cooperation with several Danish and international partners. In SUSTAIN the following definition of national sustainable transport planning (NSTP) was adopted: deliberate, knowledge-based, and strategic endeavours to integrate sustainability principles, criteria and goals in the development, management, regulation and assessment of nationally significant transport systems and services. This paper presents the research outcome by reviewing some of the major findings and seeing these collectively as a basis for promoting sustainability through the formulated research topic of NSTP. This basis includes defining criteria and indicators for use in NSTP combining evidence-based and performance oriented planning approaches. Furthermore, it contains a flexible evaluation framework that includes a decision support model that when informed by criteria and indicators can structure and assist an NSTP practice. This practice can support a planning process aiming at realising a sustainable transport development. Finally, the basis comprises a review of the complex political and administrative fabric in which NSTP is embedded, and thereby it can condition the ability to promote sustainability in practice.

EMB Future Science Brief No. 11 ‘Marine habitat mapping’ presents science and policy needs and recommendations to advance next-generation marine habitat mapping. It highlights current methods and future trends in the acquisition of data from the seabed and water column via remote sensing and direct, in situ techniques. It discusses combining data to produce maps using modelling approaches and presents recommendations for adopting fit-for-purpose habitat classification schemes. It also provides an overview of what has been mapped and where within the European sea-basins, highlights the need to increase the quality and resolution of marine habitat maps. It identifies critical gaps in habitat types and geographic extent, including the coastal areas, the deep sea, Natura 2000 sites and other Marine Protected Areas across all regional seas. Finally, it describes the need to improve the assessment and communication of uncertainty and confidence in maps, and to make maps more easily accessible to a variety of stakeholders to increase their value for end-users and to the public for Ocean literacy.

An increasing number of municipalities are striving for energy autonomy. This study determines in which municipalities and at what additional cost energy autonomy is feasible for a case study of Germany. An existing municipal energy system optimization model is extended to include the personal transport, industrial and commercial sectors. A machine learning approach identifies a regression model among 19 methods, which is best suited for the transfer of individual optimization results to all municipalities. The resulting levelized cost of energy (LCOE) from the optimization of 15 case studies are transferred using a stepwise linear regression model. The regression model shows a mean absolute percentage error of 12.5%. The study demonstrates that energy autonomy is technically feasible in 6,314 (56%) municipalities. Thereby, the LCOEs increase in the autonomous case on average by 0.41 €/kWh compared to the minimum cost scenario. Apart from energy demand, base-load-capable bioenergy and deep geothermal energy appear to have the greatest influence on the LCOEs. This study represents a starting point for defining possible scenarios in studies of future national energy system or transmission grid expansion planning, which for the first time consider completely energy autonomous municipalities.

In the context of high energy use and greenhouse gas emissions from road passenger transport, the prospects of market diffusion of new car technologies is at present time uncertain. For instance, the impact of current oil prices on the market uptake of electric vehicles is yet to be seen. Systems thinking and scenario analysis are useful to explore possible future outcomes. This paper focuses on car technologies scenarios for the Chinese, German and US markets until 2030. The technologies investigated are: gasoline, diesel, flexi-fuel, liquefied petroleum gas, natural gas, hybrid, plug-in hybrid, battery electric and fuel cell vehicles. Based on the System Dynamics approach, a model integrating discrete choice and accounting frameworks is developed. The developed System Dynamics model is applied to examine alternative policies and to estimate energy use and emissions in each of the markets under various scenarios. The model results illustrate the importance of taking indirect emissions into account. In conclusion, simulated policies sensibly alter car technology uptake and have an impact on the environment. Finally, the ideas of feedback process and expansion of model boundaries are considered to be crucial in modeling such a complex and uncertain system.

Global electricity demand is increasing every year. New services appear on the market in order to make our daily life easier. Decarbonization in transport sector makes electric vehicles more popular. Those electric vehicles are considered new demand in electricity sector. New power plants are to be built in order to serve those increasing demand. Due to climate change and global warming, many countries tend to increase the share of renewable energy. Those renewable power plants such as wind and photovoltaic tend to be, not only unpredictable, but also, distributed generation. They tend to be a number of small-scale power plants which are installed close to the loads in order to reduce the transmission losses. This high number of small-scale power plants makes it more challenging to manage. With all these challenges, the electrical grid must be smarter in order to cope with the increasing demand and also be able to balance between power demand side and power supply side. It should be monitored and be able make real-time adjustment in order to deliver electricity efficiently with standard power security and power quality to consumers.There are various types of smart grid technologies that can contribute directly to the reduction of electricity production cost. The reduction of peak demand is the key. Smart grid technologies such as Home energy management system, utility-scale battery storage system, and vehicle-to-grid are investigated in this master thesis in order to reduce the peak demand.