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Author: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk) ------------------------------------------------------------------------------- This dataset corresponds to the results of the paper titled: "Multi-Horizon Data-Driven Wind Power Forecast: From Nowcast to 2 Days-Ahead" 4th International Conference on Smart Energy Systems and Technologies (SEST) - 2021 -> https://sites.univaasa.fi/sest2021/ Submmited: Dec 2020 Accepted: Feb 2021 Published: Sep 2021 ------------------------------------------------------------------------------- The folder contains all the results presented in the paper, for clarity. Additional resources might be supplied under request. -------------------------------------------------------------------------------

Understanding N budgets of tundra ecosystems is crucial for projecting future changes in plant community composition, greenhouse gas balances and soil N stocks. Winter warming can lead to higher tundra winter nitrogen (N) mineralization rates, while summer warming may increase both growing season N mineralization and plant N demand. The undulating tundra landscape is inter-connected through water and solute movement on top of and within near-surface soil, but the importance of lateral N fluxes for tundra N budgets is not well known. We studied the size of lateral N fluxes and the fate of lateral N input in the snowmelt period with a shallow thaw layer, and in the late growing season with a deeper thaw layer. We used 15N to trace inorganic lateral N movement in a Low-arctic mesic tundra heath slope in West Greenland and to quantify the fate of N in the receiving area. We found that half of the early-season lateral N input was retained by the receiving ecosystem, whereas half was transported downslope. Plants appear as poor utilizers of early-season N, indicating that higher winter N mineralization may influence plant growth and carbon (C) sequestration less than expected. Still, evergreen plants were better at utilizing early-season N, highlighting how changes in N availability may impact plant community composition. In contrast, later growing season lateral N input was deeper and offered an advantage to deeper-rooted deciduous plants. The measurements suggest that N input driven by future warming at the study site will have no significant impact on the overall N2O emissions. Our work underlines how tundra ecosystem N allocation, C budgets and plant community composition vary in their response to lateral N inputs, which may help us understand future responses in a warmer Arctic. (Less)

Abstract District heating (DH) enables the utilisation and distribution of heating from sources unfeasible for stand-alone applications and combined with cogeneration of heat and power (CHP), has been the cornerstone of Denmark’s realisation of a steady national primary energy supply over the last four decades. However, progressively more energy-efficient houses and a steadily improving heat pump (HP) performance for individual dwellings is straining the competitive advantage of the CHP–DH combination as DH grid losses are growing in relative terms due to decreasing heating demands of buildings and relatively high DH supply temperatures. A main driver for the DH water temperature is the requirements for domestic hot water (DHW) production. This article investigates two alternatives for DHW supply: (a) DH based on central HPs combined with a heat exchanger, and (b) a combination of DH based on central HPs and a small booster HP using DH water as low-temperature source for DHW production. The analyses are conducted using the energyPRO simulation model and are conducted with hourly varying factors; heating demands, DH grid losses, HP coefficient of performance (COP) and spot market prices in order to be able to analyse the relative performance of the two options and their performance over the year. Results are also compared to individual boilers and individual HPs. The results indicate that applying booster HPs enables the DH system to operate at substantially lower temperature levels, improving the COP of central DH HPs while simultaneously lowering DH grid losses significantly. Thus, DH performance is increased significantly. Additionally, performance for the DH HP with booster combination is considerably better than individual boiler or HP solutions.

The supporting information of the journal article "Evaluation of sugar feedstocks for bio-based chemicals: A consequential, regionalized life cycle assessment" from Fabbri et al. (2022) includes one file with the following content: S1 Details of consequential modelling: feedstock S1.1 Identification type of changes (demand or supply) S1.2 Identification of constrains in the market S1.3 Identification of product substitutions S1.4 Identification of affected production technology S1.5 Identification of marginal crop and marginal supplier S2 Details of consequential modelling: by-products S3 Model parameters and unit processes S3.1 Sugar beet S3.2 Sugar cane S3.3 Wheat S3.4 Maize S3.5 Wood S3.6 Residual woodchips and sawdust S4 Review of land use change accounting methods S4.1 Direct land use change (dLUC) S4.2. Indirect land use change (iLUC) S5 Additional results S5.1 Influence of spatial differentiation in LCIA S5.2 Influence of indirect land use change (iLUC) S6 References This work was funded by the Innovation Fund Denmark under the Grand Solutions instrument; project ReMEG "Renewable Mono Ethylene Glycol for PET Plastic".

Microbial electrochemical technologies (METs) constitute the core of a number of emerging technologies with a high potential for treating urban wastewater due to a fascinating reaction mechanism—the electron transfer between bacteria and electrodes to transform metabolism into electrical current. In the current work, we focus on the model electroactive microorganism Geobacter sulfurreducens to explore both the design of new start-up procedures and electrochemical operations. Our chemostat-grown plug and play cells, were able to reduce the start-up period by 20-fold while enhancing chemical oxygen demand (COD) removal by more than 6-fold during this period. Moreover, a filter-press based bioreactor was successfully tested for both acetate-supplemented synthetic wastewater and real urban wastewater. This proof-of-concept pre-pilot treatment included a microbial electrolysis cell (MEC) followed in time by a microbial fuel cell (MFC) to finally generate electrical current of ca. 20 A·m−2 with a power of 10 W·m−2 while removing 42 g COD day−1·m−2. The effective removal of acetate suggests a potential use of this modular technology for treating acetogenic wastewater where Geobacter sulfurreducens outcompetes other organisms.

Supporting data for publication 'Impact of hysteresis on caloric cooling performance" submitted in the International Journal of Refrigeration (DOI 10.1016/j.ijrefrig.2020.10.012) The data comprise:1) An Excel file presenting the modeling results from the 1D regenerator model with hysteresis term (Qhys) to predict how modeled materials with a range of hysteresis values affect the cooling performance, including COP and cooling performance (Pcool). The Excel file presents the results for the six model materials, which have different physical (and thermodynamic) properties, i.e., specific heat capacity at zero field (c) and isothermal entropy change (s). For example, the material 'LoCLoS' has both a low specific heat capacitiy and a low isothermal entropy change. 2) An MS Word document with the additional Figs. S1 and S2 showing the modeled COPs for five model materials for a design cooling power of 50 W as a function of cycle frequency for different hysteresis values. The document also comprises a Table S1 presenting the modeled COPs for a design cooling power of 300 W as a function of cycle frequency for different hysteresis values.

Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. This dataset features a detailed map of material stocks for the whole of Germany on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Temporal extent The map is representative for ca. 2018. Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. The dataset features area and mass for different street types area and mass for different rail types area and mass for other infrastructure area, volume and mass for different building types Masses are reported as total values, and per material category. Units area in m² height in m volume in m³ mass in t for infrastructure and buildings Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.

Abstract The use of photovoltaic solar power generation is rising as worldwide energy demand increases. Therefore, reliability, safety, life cycle, and improved efficiency of photovoltaic plants have all become a major concern in research nowadays. In this context, monitoring systems are necessary to guarantee the required operating productivity and to avoid overpriced maintenance costs. This paper studies the non-ideal operating conditions for grid-connected photovoltaic plants and proposes an anomaly detection methodology that combines the advantages of the 2-sigma, short-window simple-moving average control charts with shading strength and irradiance transition parameters to detect early deviation in photovoltaic plant operational data. The key aspect of proposed methodology is that it requires neither historical data for model training procedure nor parameters from previous simulation. Only instantaneous meteorological and electrical parameters are required. The efficiency of the condition monitoring methodology has been validated through experimental results conducted in actual operating conditions. Results demonstrated that the proposed methodology is effective to identify non-ideal operating conditions for grid-connected photovoltaic plants, i.e., (i) normal operating condition, (ii) natural dynamic shading, (iii) artificial dynamic shading, and (iv) artificial static shading. Moreover, a low-cost and non-invasive internet-of-things-based embedded architecture is proposed to monitor photovoltaic plant operation in real-time.