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Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.AerChemMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.

The aim of this study was to identify the attitudes of the public in the United States and in 12 European countries towards foreign policy issues and transatlantic issues. The survey concentrated on issues such as: United States and European Union (EU) leadership and relations, favorability towards certain countries, institutions and people, security, cooperation and the perception of threat including issues of concern with Afghanistan, Iran, and Russia, energy dependence, economic downturn, and global warming, Turkey and Turkish accession to the EU, promotion of democracy in other countries, and the importance of economic versus military power. Several questions asked of respondents pertained to voting and politics including whether they discussed political matters with friends and whether they attempted to persuade others close to them to share their views on politics which they held strong opinions about, vote intention, their assessment of the current United States President and upcoming presidential election, political party attachment, and left-right political self-placement. Demographic and other background information includes age, gender, race, ethnicity, religious affiliation and participation, age when stopped full-time education and stage at which full-time education completed, occupation, number of people aged 18 years and older living in the household, type of locality, region of residence, prior travel to the United States or Europe, and language of interview. computer-assisted personal interview (CAPI); computer-assisted telephone interview (CATI); paper and pencil interview (PAPI)The original data collection was carried out by TNS, Fait et Opinion -- Brussels on request of the German Marshall Fund of the United States.The codebook and setup files for this collection contain characters with diacritical marks used in many European languages.A split ballot was used for one or more questions in this survey. The variable SPLIT defines the separate groups.For data collection, the computer-assisted face-to-face interview was used in Poland, the paper and pencil interview was used in Bulgaria, Romania, Slovakia and Turkey, and the computer-assisted telephone interview was used in all other countries.Additional information on the Transatlantic Trends Survey is provided on the Transatlantic Trends Web site. (1) Multistage random sampling was implemented in the countries using face-to-face interviewing. Sampling points were selected according to region, and then random routes were conducted within these sampling points. Four callbacks were used for each address. The birthday rule was used to randomly select respondents within a household. (2) Random Digit Dialing was implemented in the countries using telephone interviewing. Eight callbacks were used for each telephone number. The birthday rule was used to randomly select respondents within a household. The adult population aged 18 years and over in 13 countries: Bulgaria, France, Germany, Italy, the Netherlands, Poland, Portugal, Romania, Slovakia, Spain, Turkey, the United Kingdom, and the United States. Smallest Geographic Unit: country Response Rates: The total response rate for all countries surveyed is 23 percent. Please refer to the "Technical Note" in the ICPSR codebook for additional information about response rate. Please refer to the "Technical Note" in the ICPSR codebook for further information about weighting. Datasets: DS1: Transatlantic Trends Survey, 2008

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.HAMMOZ-Consortium.MPI-ESM-1-2-HAM.historical' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The MPI-ESM1.2-HAM climate model, released in 2017, includes the following components: aerosol: HAM2.3, atmos: ECHAM6.3 (spectral T63; 192 x 96 longitude/latitude; 47 levels; top level 0.01 hPa), atmosChem: sulfur chemistry (unnamed), land: JSBACH 3.20, ocean: MPIOM1.63 (bipolar GR1.5, approximately 1.5deg; 256 x 220 longitude/latitude; 40 levels; top grid cell 0-12 m), ocnBgchem: HAMOCC6, seaIce: unnamed (thermodynamic (Semtner zero-layer) dynamic (Hibler 79) sea ice model). The model was run by the ETH Zurich, Switzerland; Max Planck Institut fur Meteorologie, Germany; Forschungszentrum Julich, Germany; University of Oxford, UK; Finnish Meteorological Institute, Finland; Leibniz Institute for Tropospheric Research, Germany; Center for Climate Systems Modeling (C2SM) at ETH Zurich, Switzerland (HAMMOZ-Consortium) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 250 km, ocnBgchem: 250 km, seaIce: 250 km.

‘Productive Uses of Energy and gender in the Street Food Sector’, is a title of our four year project which is part of the DFID funded ENERGIA Gender and Energy Research programme. This research focuses on male and female owned micro enterprises preparing and selling food in Rwanda, Senegal and South Africa. This sector provides livelihoods for many women and men in these countries and this project provides the gender and energy nexus analysis. One of the primary goals of this project is to influence energy policy making and implementation in the focus countries.

Projections of Sea Level Rise (SLR) under RCP 4.5 and RCP 8.5 (AR5) along the Mekong Coast, Published1 by the Ministry of Natural Resources and Environment (MONRE), Hanoi, Vietnam. Projections of Mekong River discharge during the dry season under RCP 4.5 and RCP 8.5 at Kratie, Cambodia. The data contains the cumulative, minimum and maximum dry season (January-1st to April-30th) discharge from 5 different climate models. PCR-GLOBWB2 was run at 5 arc-min spatial resolution and forced with the data based on output from five ISIMIP CMIP5 global climate models (HadGEM2-ES, GFDL-ESM2, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M). 1. Ministry of Natural Resources and Environment (MONRE), V. Climate change and sea level rise scenarios for Vietnam, Ministry of Natural Resources and Environment. (2016). 2. Sutanudjaja, E. H. et al. PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model. Geosci. Model Dev. 11, 2429–2453 (2018). {"references": ["Sutanudjaja et al. (2018)", "Ministry of Natural Resources and Environment (2016)"]}

As a renewable energy source, wind power is gaining popularity as a favoured alternative to fossil fuel, nuclear and hydro power generation. In Europe, countries are required to achieve 15% of their energy consumption from wind by 2010 as the EU strives to meet its Kyoto obligations. Wind power is considered to be environmentally friendly and low cost. While environmental friendliness has come under scrutiny because wind turbines continue to pose a hazard to birds, are visually unappealing, affect the uses of land and change air flows, the purpose of this paper is to examine the question of its presumed low cost and effectiveness at reducing CO2 emissions by replacing power generated from fossil fuels. To do so, we develop a mathematical programming model of an electrical energy grid that employs power generated by a base-load nuclear power plant, a coal-fired power plant and a gas facility, with the latter used primarily to meet peak-load demand. We then introduce varying levels of wind power generating capacity into the grid. The results indicate that, at low levels of penetration, wind power can provide CO2 mitigation benefits at low cost. However, as the degree of penetrability increases, the costs of reducing CO2 emissions rise rapidly because of the spinning reserves required in the coal- and gas-fired power plants. Fossil fuels are consumed even though no power is generated in the eventuality that wind power is suddenly unavailable. The whimsical nature of wind energy makes it a less than desirable long-term source of energy.

Biomass production has both direct effects and indirect effects. Direct effects such as the energy balance and GHG balance can be directly measured, to make sure that impacts are (significantly) below the fossil fuel comparator. In recent years it has also been recognized that the production and use of biomass for energy has indirect effects which are caused by competition for inputs and land. The most important indirect effect is ILUC (indirect land use change) and the associated GHG emissions, which have been quantified in different studies. Avoiding ILUC is now becoming important. An important option is the use of land that would otherwise not be used for food or feed production. This generally means that lower quality or marginal land will be used. Switchgrass is one of the main perennial biomass crops that can produce high biomass yields under low input conditions and which can be established at low cost by seeds. In Ukraine this crop has in recent years been tested, yielding information that can be used to assess the cost and GHG balance of growing the crop, pelletizing, transport to the Netherlands and conversion into electricity. Results show that GHG emissions on low quality soil without ILUC (12.5 g CO2 MJ-1 pellet) are higher than for good quality soil grown switchgrass with ILUC (0.1 g CO2 MJ-1 pellet). Analysis of the costs of growing switchgrass on low productive soils are 22% higher compared to high quality soils. We conclude that ILUC avoidance needs to be quantified and rewarded. Proceedings of the 20th European Biomass Conference and Exhibition, 18-22 June 2012, Milan, Italy, pp. 1988-1991

Large quantities of biomass will be needed to feed the biobased economy. Use of crops and wood may cause (indirect) land use change related greenhouse gas emissions. Agro-residues could be an interesting alternative. However, several issues are hindering efficient application: high potassium and chlorine content and low bulk density are the most important issues. In this research, a series of processes is proposed to overcome these issues. Through a combination of extraction (to remove potassium and chlorine), steam treatment and pelleting, Clean Agro-Pellet Commodities(CAPCOMs) were produced. The pellets showed improved handling properties. Combustion tests showed improved ash melting behavior, reduced fouling of heat exchangers and low emissions of NOx and fines. Fermentation tests showed that pellets produced at low severity factors were easily hydrolized and fermented to produce ethanol at normal yields. Some inhibition was seen with undiluted hydrolysates. Based on the results a techno-economical evaluation showed that pellets from agro-residues could be produced and transported at a cost of around 6 EURO/GJHHV. Sustainability analysis revealed that pellets could be produced with GHG emissions of 3 to 6.4 kgCO2eq/GJLHV. Via the combination of processes described in this paper, a huge potential of nowadays unused biomass can be made applicable for the bioeconomy. Proceedings of the 29th European Biomass Conference and Exhibition, 26-29 April 2021, Online, pp. 791-794

The aim of this work was to gain insight and knowledge with the basic concepts of the Bitcoinnetwork and its relation to energy consumption. Precisely, the ambition of this literature-based research was to identify key determinants of the network ́s energy intensiveness. After an extensive review of the relevant literature on the topic, key principles of Bitcoin ́s electricity consumption were derived.With regards to environmental sustainability concerns, it was found that the network ́sproperties, in theory, allow for improvements of the unit economics of renewable energy production facilities and renewable intensive energy grids. Such applications, however, are dependent on the unforecastable market dynamics of the Bitcoin price.In a contextualization approach it was attempted to categorize the electricity consumption levels of the Bitcoin network based on the services offered with similar but not comparable entities.This approach finds that energy consumption does not provide a conclusive and instructive comparative parameter to determine whether energy consumption levels of the Bitcoin network.The paper concludes with advocating for location dependent policy approaches that encourage the strategic deployment of Bitcoin mining hardware to minimize environmental and economic opportunity cost.