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Energy Climate dataset consistent with ENTSO-E Pan-European Climatic Database (PECD 2021.3) in CSV and netCDF format TL;DR: this is a nationally aggregated hourly dataset for the capacity factors per unit installed capacity for storage hydropower plants and run-of-river hydropower plants in the European region. All the data is provided for 30 climatic years (1981-2010). Method Description The hydro inflow data is based on historical river runoff reanalysis data simulated by the E-HYPE model. E-HYPE is a pan-European model developed by The Swedish Meteorological and Hydrological Institute (SMHI), which describes hydrological processes including flow paths at the subbasin level. E-hype only provides the time series of daily river runoff entering the inlet of each European subbasin over 1981-2010. To match the operational resolution of the dispatch model, we linearly downscale these time series to hourly. By summing up runoff associated with the inlet subbasins of each country, we also obtain the country-level river runoff. The hydro inflow time series per country is defined as the normalized energy inflows (per unit installed capacity of hydropower) embodied in the country-level river runoff. A dispatch model can be used to decides whether the energy inflows are actually used for electricity generation, stored, or spilled (in case the storage reservoir is already full). Data coverage This dataset considers two types of hydropower plants, namely storage hydropower plant (STO) and run-of-river hydropower plant (ROR). Not all countries have both types of hydropower plants installed (see table). The countries and their acronyms for both technologies included in this dataset are: Country Run-of-River Storage Austria AT_ROR AT_STO Belgium BE_ROR BE_STO Bulgaria BG_ROR BG_STO Switzerland CH_ROR CH_STO Cyprus CZ_ROR CZ_STO Germany DE_ROR DE_STO Denmark DK_ROR Estonia EE_ROR Greece EL_ROR EL_STO Spain ES_ROR ES_STO Finland FI_ROR FI_STO France FR_ROR FR_STO Great Britain GB_ROR GB_STO Croatia HR_ROR HR_STO Hungary HU_ROR HU_STO Ireland IE_ROR IE_STO Italy IT_ROR IT_STO Luxembourg LU_ROR Latvia LV_ROR the Netherlands NL_ROR Norway NO_ROR NO_STO Poland PL_ROR PL_STO Portugal PT_ROR PT_STO Romania RO_ROR RO_STO Sweden SE_ROR SE_STO Slovenia SI_ROR SI_STO Slovakia SK_ROR SK_STO Data structure description The files is provided in CSV (.csv) format with a comma (,) as separator and double-quote mark (") as text indicator. The first row stores the column labels. The columns contain the following: first column (or A) contains the row number Label: unlabeled Contents: interger range [1,262968] second column (or B) contains the valid-time Label: T1h Contents represent time with text as [DD/MM/YYYY HH:MM]) column 3-52 (or C-AY) each contain the capacity factor for each valid combination of a country and hydropower plant type Label: XX_YYY the two letter country code (XX) and the hydropower plant type (YYY) acronym for storage hydropower plant (STO) and run-of-river hydropower plant (ROR) Contents represent the capacity factor as a floating value in the range [0,1], the decimal separator is a point (.). DISCLAIMER: the content of this dataset has been created with the greatest possible care. However, we invite to use the original data for critical applications and studies. The raw hydro data was generated as part of 'Evaluating sediment Delivery Impacts on Reservoirs in changing climaTe and society across scales and sectors (DIRT-X)', this project and therefor, Jing hu, received funding from the European Research Area Network (ERA-NET) under grant number 438.19.902. Laurens P. Stoop received funding from the Netherlands Organization for Scientific Research (NWO) under Grant No. 647.003.005.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

‘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.

LocaGIStics is a support tool for the design of regional biomass delivery chains. It enables to further design and evaluate regional biomass delivery chains that are e.g. the result of initial planning by an energy company or a biobased producer. These general plans are translated in several biomass delivery designs using the variation in logistical concepts covering transport, pre-treatment and conversion options. The performance of every chain design can then be analyzed by comparing the different biomass delivery chains on the following environmental and economic indicators. A regional case study was performed in Aragón (Spain) using the LocaGIStics tool. In this case study maps were used where the biomass availability is specified for 2.5 x 2.5 grid cells. Data about the logistical components were supplied partly by the energy supplying company that was involved. This paper shows the main outcomes of this case study. Proceedings of the 25th European Biomass Conference and Exhibition, 12-15 June 2017, Stockholm, Sweden, pp. 41-47

Compression-resorption heat pumps (CRHP) enhanced by wet compression are considered a very promising option to upgrade low grade waste heat from the industry. This is especially true for applications where the heat source and/or sink have a large temperature glide. But commercial solutions using wet compression are not yet available on the market. Compared to the classically used vapor compression heat pumps (VCHP), CRHP can provide much better performance but only if the efficiency of the compressor exceeds 0.7. In this respect, a twin screw compressor has been identified as a potential solution to reach this efficiency goal. This study makes use of the entropy production minimization to identify where the major irreversibilites are located in a CRHP system operated with an ammonia-water mixture. A detailed model of the wet compressor and the resorber are coupled with simplified models of other components of the HP cycle to analyze where potential improvements can be made. The results show that significant benefits can be obtained using CRHP.

Supplementary material for peer review Model Input Model Results (LEAP/NEMO)

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