Das Projekt "H2020-EU.3.4. - Societal Challenges - Smart, Green And Integrated Transport - (H2020-EU.3.4. - Gesellschaftliche Herausforderungen - Intelligenter, umweltfreundlicher und integrierter Verkehr), Leveraging Big Data to Manage Transport Operations (LeMO)" wird/wurde gefördert durch: Kommission der Europäischen Gemeinschaften Brüssel. Es wird/wurde ausgeführt durch: Stiftinga Vestlandsforsking.Big data has opened a wide spectrum of opportunities in the field of transport research. Observing the recent emergent interest in the application of big data within transport, as well as the extended scope of its applications, it is evident that most of the challenges have yet to be addressed. Leveraging Big Data to Manage Transport Operations (LeMO) project will explore the implications of the utilisation of big data to enhance the economic sustainability and competitiveness of European transport sector. The project will study and analyse big data in the European transport domain in particular with respect to five transport dimensions: mode, sector, technology, policy and evaluation. LeMO will accomplish this by conducting a series of case studies, in order to provide recommendations on the prerequisites of effective big data implementation in the transport field. Through case studies, LeMO will investigate methodological, technological, governmental and institutional issues, which in turn contribute to evidence-based decision making. LeMO will supplement these case studies with a horizontal analysis that identifies the barriers and limitations of the transportation system to exploit big data opportunities. In collaboration with strong advisory and reference group, and expert stakeholders, LeMO will devise and develop research and policy roadmap that will provide incremental steps necessary towards data openness and sharing to make transport safer, more efficient and more sustainable. Notably, LeMO will bring crucial issues linked to privacy, data security and legal aspects to the forefront, paving the way for future legal framework for the collection and exploitation of big data in transport. Furthermore, LeMO will disseminate project findings to a large population of stakeholders, including transport authorities and industries leading to better understanding of travellers' and consumers' behaviour, targeted information and identify policy interventions.
Electricity generation gives rise to negative impacts on the environment and human health throughout all stages of its life-cycle. To date, power generation remains the largest GHG-emitting sector in Europe. Carbon dioxide (CO2) is by far the most commonly-emitted GHG across the sector, being a product of combustion processes. An almost complete decarbonisation of the EU’s electricity sector is needed in order to meet the EU’s objective of becoming the first carbon-neutral continent by 2050. Electricity can play an increasing role in decarbonising energy use across a number of sectors, such as transport, industry and households. Information about the carbon intensity of electricity generation is therefore relevant for many stakeholders. The EEA and its European Topic Centre for Climate Change Mitigation and Energy (ETC/CME) produce each year country- and EU-level data on the average annual CO2 emission intensity of electricity generation.
Das Projekt "Sustainable Value in the Airline Industry (EADS)" wird/wurde gefördert durch: EADS Deutschland GmbH / Sustainable Value Research Ltd.. Es wird/wurde ausgeführt durch: IZT - Institut für Zukunftsstudien und Technologiebewertung gemeinnütziger GmbH.
Das Projekt "Litebus-Modular Lightweight Sandwich Bus Concept" wird/wurde gefördert durch: Kommission der Europäischen Gemeinschaften Brüssel. Es wird/wurde ausgeführt durch: Technische Universität Clausthal, Institut für Polymerwerkstoffe und Kunststofftechnik.Objective: Increasing awareness by the public opinion about environmental issues, energy and material conservation at all stages of product life (from raw materials to disposal/recycling) is putting the industry in general and the transport industry in particular under increased pressure to reduce CO2 emissions and save energy. Environmental protection and safety will be increasingly influenced by legislation. The European transport industry is estimated to generate 22 percent of the carbon dioxide emission. As the car population is expected to grow 40 percent by the year 2010 new tough targets for reducing emissions by 30 percent in 2010 are being set by the EU, against the state of the art technologies of 1995. It is generally agreed by the industry that reductions of this size will require a change in current technologies. Multi-material technology (sandwich and/or hybrid materials) is becoming increasingly important in new vehicle design. Public service vehicles (buses and coaches) are regarded as primary targets for application of sandwich construction and multi-materials. Public service vehicles (PSV) play a major role in the transportation industry of both industrialized and developing countries. The proposed project will be focused on the development of a novel technology to manufacture bus/coach bodies using sandwich multi-material panels. The main overall objectives of the project are: - Solving the problem of reducing weight and production costs of land transport vehicles through the development of a technology of modular bus/coach construction, using 'all composite' multi-material sandwich panels instead of steel/aluminium space frame lined with sheets of different materials. - Devise design methodologies that reduce production lead time through reduction of number of components, functional integration, and allowance for dismantling, easy repair and recycling. Primce Contractor: INEGI - Instituto de Engenharia Mecanica e Gestao Industrial, Leca do Balio, Portugal.
Das Projekt "External health costs due to traffic related air pollution in Switzerland" wird/wurde ausgeführt durch: Universität Bern, Institut für Sozial- und Präventivmedizin, Abteilung Internationale Gesundheit & Umwelt, Ressort Umwelt und Gesundheit.This study establishes the external health costs caused by air pollution in Switzerland in the year 2000. The primary focus is on road and rail traffic related air pollution. First of all, the population's exposure to airborne pollutants is determined. Based on this, the additional cases of illness and death caused by air pollution are calculated. Using specific cost rates per incidence of illness and death, the impacts on health are then converted into monetary units. Where road traffic is concerned, health costs related to air pollution run to some 1,525 million CHF, of which 57 percent or 871 million CHF are caused by passenger transport, while the remaining 43 percent or 655 million CHF are caused by freight transport. The corresponding figure for rail traffic is 100 million CHF (46 percent passenger and 54 percent freight transport). Air pollution overall - caused by traffic, industry, commerce, households, agriculture and forestry - results in costs of 4,204 million CHF. This figure corresponds to 628 CHF per capita, or compared to GDP it is in the order of magnitude of 1.12 percent.
CH4-Emissionen in Baden-Württemberg 1990 bis 2020 in t/a Kleine und Mittlere Feuerungsanl. 1) 19903 521 VerkehrIndustrie und GewerbeBiogene Systeme 1)Sonstige Technische Einrichtungen 1)Summe 5 6001 186122 950178 988312 245 20003 6262 2052 204105 470128 027241 532 20023 6381 3352 344102 430121 953213 700 20043 7251 0611 92797 50695 921200 140 20064 6718122 20796 50070 530174 720 20083 7239431 34197 15043 470146 627 20104 0048081 293104 30040 030150 435 20123 3717001 863103 80032 230141 964 20142 7431 0591 781108 23830 730144 551 20163 5729912 470106 57529 837143 445 20183 1791 1532 276110 84125 916143 365 20202 9149072 409106 96324 085137 278 1) revidierte Werte
CO-Emissionen in Baden-Württemberg 1990 bis 2020 in t/a Kleine und Mittlere Feuerungsanl. VerkehrIndustrie und GewerbeBiogene SystemeSonstige Technische Einrichtungen1990106 616 Summe 736 87711 215–59 022913 730 20002004129 415365 91626 095–31 616553 042 91 691279 94128 781–24 319424 732 200698 730219 45626 785–23 523368 494 2008108 125163 01729 531–23 059323 732 2010116 253143 09325 637–23 182308 165 201297 893120 12028 723–23 200269 936 201479 797143 68026 078–22 960272 515 201657 060130 63124 826–22 362234 879 201850 734104 80728 339–17 348201 228 202047 21673 88323 936–17 524162 559
NMVOC-Emissionen in Baden-Württemberg 1990 bis 2020 in t/a Kleine und Mittlere Feuerungsanl. VerkehrIndustrie und GewerbeBiogene Systeme1)Sonstige Technische Einrichtungen19909 264 Summe 117 02659 23087 90757 377330 804 200020048 71338 82944 80388 56243 590224 497 8 98822 97839 16881 65041 123193 907 20069 68219 23239 09481 80542 715192 528 20084 85416 94137 91481 28641 440182 435 20105 19914 39234 86375 46730 946160 867 20124 34711 42030 34678 62030 240154 973 20143 52216 21930 14783 76729 088162 743 20164 59015 12930 45680 22230 083160 480 20184 07211 36234 79897 28129 592177 105 20203 7129 25734 53492 66530 581170 749 1) revidierte Werte bis 2014 nach [Thünen-Report 57]
NOx-Emissionen in Baden-Württemberg 1990 bis 2020 in t/a Kleine und Mittlere Feuerungsanl. VerkehrIndustrie und GewerbeBiogene Systeme 1, 2)Sonstige Technische EinrichtungenSumme 199015 205164 65458 95512 27838 266289 358 200014 540110 07632 00912 49128 369197 485 200414 25083 25130 22610 71621 905160 348 200614 47673 86930 67410 29320 151149 463 200813 82674 85728 40010 84118 601146 525 201015 09662 46626 87410 55516 554131 545 201212 89554 51925 96710 97415 560119 915 201410 96452 49423 97411 22115 430114 083 201611 24154 53724 86911 73913 925116 311 20189 90756 79824 32510 82610 721112 577 20209 87537 16420 6479 86910 33887 893 1) 2) berechnet aus NO revidierte Werte bis 2014 nach [Thünen-Report 57]
SO2-Emissionen in Baden-Württemberg 1990 bis 2020 in t/a Kleine und Mittlere Feuerungsanl. VerkehrIndustrie und GewerbeBiogene SystemeSonstige Technische EinrichtungenSumme 199015 4477 62363 843–2 68589 598 200012 9932 54523 742–38439 664 20049 07729023 472–932 848 20068 40421322 815–931 441 20087 63816620 883–928 696 20104 38616217 761–922 318 201274815716 222–917 136 201462817813 596–4214 444 201663118211 814–3812 665 201855413912 070–3812 801 2020538908 480–389 146
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