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Oxy-fuel carbon capture in power plants is a relatively new concept aiming at reducing carbon dioxide emissions from the plants. This is achieved by burning the fossil fuel using oxygen as oxidizer with no nitrogen, thereby rendering the exhaust gases very rich in carbon dioxide (after condensing water vapor by cooling), which facilitates its capture for environmental or commercial purposes. Despite the worldwide interest in oxy-fuel carbon capture, its progress is at risk given the large energy needed to separate oxygen from air in order to provide the oxidizer, thereby hindering further progress of this concept toward large-scale applications. This paper focuses on alleviating this drawback of oxy-fuel combustion by making it more attractive through combining it with another concept, namely magnetohydrodynamic (MHD) power generators. The end product is a power plant operating on a combined cycle composed of a topping MHD ultra-high-temperature cycle with direct electricity extraction from plasma, followed by a bottoming steam cycle with conventional turbo-generators. Different design aspects and simplified technical analysis for the MHD generator are presented.

Oxy-fuel carbon capture in power plants is a relatively new concept aiming at reducing carbon dioxide emissions from the plants. This is achieved by burning the fossil fuel using oxygen as oxidizer with no nitrogen, thereby rendering the exhaust gases very rich in carbon dioxide (after condensing water vapor by cooling), which facilitates its capture for environmental or commercial purposes. Despite the worldwide interest in oxy-fuel carbon capture, its progress is at risk given the large energy needed to separate oxygen from air in order to provide the oxidizer, thereby hindering further progress of this concept toward large-scale applications. This paper focuses on alleviating this drawback of oxy-fuel combustion by making it more attractive through combining it with another concept, namely magnetohydrodynamic (MHD) power generators. The end product is a power plant operating on a combined cycle composed of a topping MHD ultra-high-temperature cycle with direct electricity extraction from plasma, followed by a bottoming steam cycle with conventional turbo-generators. Different design aspects and simplified technical analysis for the MHD generator are presented.

PyPSA-Eur is an open model dataset of the European power system at the transmission network level that covers the full ENTSO-E area. It can be built using the code provided at https://github.com/PyPSA/PyPSA-eur. It contains alternating current lines at and above 220 kV voltage level and all high voltage direct current lines, substations, an open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power. Not all data dependencies are shipped with the code repository, since git is not suited for handling large changing files. Instead we provide separate data bundles to be downloaded and extracted as noted in the documentation. This is the full data bundle to be used for rigorous research. It includes large bathymetry and natural protection area datasets. While the code in PyPSA-Eur is released as free software under the MIT, different licenses and terms of use apply to the various input data, which are summarised below: corine/* CORINE Land Cover (CLC) database Source: https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012/ Terms of Use: https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012?tab=metadata natura/* Natura 2000 natural protection areas Source: https://www.eea.europa.eu/data-and-maps/data/natura-10 Terms of Use: https://www.eea.europa.eu/data-and-maps/data/natura-10#tab-metadata gebco/GEBCO_2014_2D.nc GEBCO bathymetric dataset Source: https://www.gebco.net/data_and_products/gridded_bathymetry_data/version_20141103/ Terms of Use: https://www.gebco.net/data_and_products/gridded_bathymetry_data/documents/gebco_2014_historic.pdf je-e-21.03.02.xls Population and GDP data for Swiss Cantons Source: https://www.bfs.admin.ch/bfs/en/home/news/whats-new.assetdetail.7786557.html Terms of Use: https://www.bfs.admin.ch/bfs/en/home/fso/swiss-federal-statistical-office/terms-of-use.html https://www.bfs.admin.ch/bfs/de/home/bfs/oeffentliche-statistik/copyright.html nama_10r_3popgdp.tsv.gz Population by NUTS3 region Source: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3popgdp&lang=en Terms of Use: https://ec.europa.eu/eurostat/about/policies/copyright GDP_per_capita_PPP_1990_2015_v2.nc Gross Domestic Product per capita (PPP) from years 1999 to 2015 Rectangular cutout for European countries in PyPSA-Eur, including a 10 km buffer Kummu et al. "Data from: Gridded global datasets for Gross Domestic Product and Human Development Index over 1990-2015" Source: https://doi.org/10.1038/sdata.2018.4 and associated dataset https://doi.org/10.1038/sdata.2018.4 ppp_2019_1km_Aggregated.tif The spatial distribution of population in 2020: Estimated total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 30 arc (approximately 1km at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. The mapping approach is Random Forest-based dasymetric redistribution. Rectangular cutout for non-NUTS3 countries in PyPSA-Eur, i.e. MD and UA, including a 10 km buffer WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00647 Source: https://data.humdata.org/dataset/worldpop-population-counts-for-world and https://hub.worldpop.org/geodata/summary?id=24777 License: Creative Commons Attribution 4.0 International Licens data/bundle/era5-HDD-per-country.csv - Link: https://gist.github.com/fneum/d99e24e19da423038fd55fe3a4ddf875- License: CC-BY 4.0- Contains country-level heating degree days in Europe for 1941-2023. Used for rescaling heat demand in weather years not covered by energy balance statistics. data/bundle/era5-runoff-per-country.csv - Link: https://gist.github.com/fneum/d99e24e19da423038fd55fe3a4ddf875- License: CC-BY 4.0- Contains country-level daily sum of runoff in Europe for 1941-2023. Used for rescaling hydro-electricity availability in weather years not covered by EIA hydro-generation statistics. shipdensity_global.zip Global Shipping Traffic Density Creative Commons Attribution 4.0 https://datacatalog.worldbank.org/search/dataset/0037580/Global-Shipping-Traffic-Density seawater_temperature.nc Global Ocean Physics Reanalysis Link: https://data.marine.copernicus.eu/product/GLOBAL_MULTIYEAR_PHY_001_030/services License: https://marine.copernicus.eu/user-corner/service-commitments-and-licence

PyPSA-Eur is an open model dataset of the European power system at the transmission network level that covers the full ENTSO-E area. It can be built using the code provided at https://github.com/PyPSA/PyPSA-eur. It contains alternating current lines at and above 220 kV voltage level and all high voltage direct current lines, substations, an open database of conventional power plants, time series for electrical demand and variable renewable generator availability, and geographic potentials for the expansion of wind and solar power. Not all data dependencies are shipped with the code repository, since git is not suited for handling large changing files. Instead we provide separate data bundles to be downloaded and extracted as noted in the documentation. This is the full data bundle to be used for rigorous research. It includes large bathymetry and natural protection area datasets. While the code in PyPSA-Eur is released as free software under the MIT, different licenses and terms of use apply to the various input data, which are summarised below: corine/* CORINE Land Cover (CLC) database Source: https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012/ Terms of Use: https://land.copernicus.eu/pan-european/corine-land-cover/clc-2012?tab=metadata natura/* Natura 2000 natural protection areas Source: https://www.eea.europa.eu/data-and-maps/data/natura-10 Terms of Use: https://www.eea.europa.eu/data-and-maps/data/natura-10#tab-metadata gebco/GEBCO_2014_2D.nc GEBCO bathymetric dataset Source: https://www.gebco.net/data_and_products/gridded_bathymetry_data/version_20141103/ Terms of Use: https://www.gebco.net/data_and_products/gridded_bathymetry_data/documents/gebco_2014_historic.pdf je-e-21.03.02.xls Population and GDP data for Swiss Cantons Source: https://www.bfs.admin.ch/bfs/en/home/news/whats-new.assetdetail.7786557.html Terms of Use: https://www.bfs.admin.ch/bfs/en/home/fso/swiss-federal-statistical-office/terms-of-use.html https://www.bfs.admin.ch/bfs/de/home/bfs/oeffentliche-statistik/copyright.html nama_10r_3popgdp.tsv.gz Population by NUTS3 region Source: http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=nama_10r_3popgdp&lang=en Terms of Use: https://ec.europa.eu/eurostat/about/policies/copyright GDP_per_capita_PPP_1990_2015_v2.nc Gross Domestic Product per capita (PPP) from years 1999 to 2015 Rectangular cutout for European countries in PyPSA-Eur, including a 10 km buffer Kummu et al. "Data from: Gridded global datasets for Gross Domestic Product and Human Development Index over 1990-2015" Source: https://doi.org/10.1038/sdata.2018.4 and associated dataset https://doi.org/10.1038/sdata.2018.4 ppp_2019_1km_Aggregated.tif The spatial distribution of population in 2020: Estimated total number of people per grid-cell. The dataset is available to download in Geotiff format at a resolution of 30 arc (approximately 1km at the equator). The projection is Geographic Coordinate System, WGS84. The units are number of people per pixel. The mapping approach is Random Forest-based dasymetric redistribution. Rectangular cutout for non-NUTS3 countries in PyPSA-Eur, i.e. MD and UA, including a 10 km buffer WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00647 Source: https://data.humdata.org/dataset/worldpop-population-counts-for-world and https://hub.worldpop.org/geodata/summary?id=24777 License: Creative Commons Attribution 4.0 International Licens data/bundle/era5-HDD-per-country.csv - Link: https://gist.github.com/fneum/d99e24e19da423038fd55fe3a4ddf875- License: CC-BY 4.0- Contains country-level heating degree days in Europe for 1941-2023. Used for rescaling heat demand in weather years not covered by energy balance statistics. data/bundle/era5-runoff-per-country.csv - Link: https://gist.github.com/fneum/d99e24e19da423038fd55fe3a4ddf875- License: CC-BY 4.0- Contains country-level daily sum of runoff in Europe for 1941-2023. Used for rescaling hydro-electricity availability in weather years not covered by EIA hydro-generation statistics. shipdensity_global.zip Global Shipping Traffic Density Creative Commons Attribution 4.0 https://datacatalog.worldbank.org/search/dataset/0037580/Global-Shipping-Traffic-Density seawater_temperature.nc Global Ocean Physics Reanalysis Link: https://data.marine.copernicus.eu/product/GLOBAL_MULTIYEAR_PHY_001_030/services License: https://marine.copernicus.eu/user-corner/service-commitments-and-licence

The concept of energy analysis is defined and applied to industrial processes. The study discusses the significance of choosing the definition of efficiency, system limitations and problem definition. The purpose of this report is to show the simplicity and value of using the concept of energy analysis in the analysis of industrial processes and to develop conventions and standards in the field of process efficiency. In the situation of the Republic of Moldova, the implementation of projects to improve energy efficiency and the use of renewable energy sources contributes to reducing the degree of the energy dependence of the country and also represents a national contribution in the fight against climate change.

The concept of energy analysis is defined and applied to industrial processes. The study discusses the significance of choosing the definition of efficiency, system limitations and problem definition. The purpose of this report is to show the simplicity and value of using the concept of energy analysis in the analysis of industrial processes and to develop conventions and standards in the field of process efficiency. In the situation of the Republic of Moldova, the implementation of projects to improve energy efficiency and the use of renewable energy sources contributes to reducing the degree of the energy dependence of the country and also represents a national contribution in the fight against climate change.

AbstractAs the bones and muscles of our built environment, engineering structures support all kind of societal activities. However, they consume huge amounts of resources and significantly contribute to impact on our environment. Structural design codes play an important matter in this regard since they regulate the use of materials by use of prescribed decision rules. These relatively simple and generalized rules offer significant potential for improvement. Grounded on risk-based optimization approaches, this paper explores this potential in connection with the design of reinforced concrete floor systems. Assuming a large variety of realistic design situations, representative sets of such members are defined and designed according to the semi-probabilistic safety concept in the Eurocodes. The benefits of a risk-informed structural design compared to the use of these standardized decision rules are demonstrated in terms of material consumption and CO2 emissions.