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The dataset contains the FTIR spectra collected during the electrical measurements DIR-SOFC with LSCNT layer. The SOFC was reduced at 800degC in H2 prior to mesurements. The spectra were collected every 10 min.

The Swiss FluxNet Site Davos is a managed subalpine evergreen forest, located on the Seehorn mountain near Davos in the Swiss Alps. The site is dominated by Norway spruce. The tower is owned by the Federal Office for the Environment (FOEN). Ecosystem flux measurements of CO2, H2O (since 1997) as well as CH4 and N2O (since 2016) are performed with the eddy covariance method. In addition to Swiss FluxNet, the site is part of the National Air Pollution Monitoring Network (NABEL), the Long term Forest Ecosystem Research (LWF), the biological drought and growth indicator network (TreeNet) and of ICOS Switzerland (Integrated Carbon Observation System). Since November 2019, the site is an ICOS Class 1 Ecosystem station.Measurements- Ecosystem flux measurements of CO2, H2O vapour (since 1997) as well a CH4 and N2O (since 2016) are performed with the eddy-covariance method. This method is based on measurements of trace gas mixing ratios, using infrared gas analyzers (for CO2, H2O vapor) and laser spectrometers (for CH4 and N2O), combined with wind speed and wind direction measurements, using 3D sonic anemometers. To resolve the short-term turbulent fluctuations in the atmosphere, very fast measurements are needed: we measure at 10-20 Hz, i.e., 10-20 times per second. To assess the energy budget of each ecosystem, also radiation sensors and soil climate profiles are installed at the site.- Sub-canopy eddy fluxes (CO2, H2O, since 2023 also CH4).- Continuous profile concentration and forest floor flux measurement of CO2, H2O, CH4, N2O.- Auxiliary micrometeorology and soil climate measurements.Data availabilityNear real-time flux and meteo data uploaded daily to the ICOS Carbon Portal. Processed flux and meteo data are also available from the European Fluxes Database Cluster and part of Fluxnet2015 dataset.Data policyICOS data license: [https://www.icos-cp.eu/data-services/about-data-portal/data-license](https://www.icos-cp.eu/data-services/about-data-portal/data-license)Detailed site info: [https://www.swissfluxnet.ethz.ch/index.php/sites/ch-dav-davos/site-info-ch-dav/](https://www.swissfluxnet.ethz.ch/index.php/sites/ch-dav-davos/site-info-ch-dav/)

PAPILA dataset is a collection of annual emission inventories of reactive gases (CO, NOx, NMVOCs, NH3 and SO2) from anthropogenic sources in South America, for the period 2014–2016. The dataset was developed on the basis of the existing data on the global dataset CAMS-GLOB-ANT v4.1 (developed by joining CEDS trends and EDGARv4.3.2 historical data), enriching it with derived data from locally available emission inventories for Argentina, Chile and Colombia. The inventories are presented as NetCDF4 files, one for each species and year, gridded with a spatial resolution of 0.1° x 0.1° covering the domain 32° W–120° W and 34° N–58° S. Each file contains 12 variables corresponding to the emissions in Tg/y from the following categories, which are organized and denominated using the nomenclature given by CAMS: thermal power plants (ENE); residential and commercial combustion (RES); road transportation (TRO); non-road transportation (TNR); fugitive emissions (FEF); industries (including fuel consumption in manufacturing industries and construction, refineries, industrial processes and solvent and other products use) (IND); agricultural soils (AGS); agriculture livestock (AGL); inland navigation (SHP); international navigation (SHP-INT); waste (including solid waste, wastewater and incineration) (SWD); and the sum of all sectors (SUM).

Article Abstract To better allocate funds in the new EU research framework programme Horizon Europe, an assessment of current and past efforts is crucial. In this paper we develop and apply a multi-method qualitative and computational approach to provide a catalogue of climate crisis mitigation technologies on the EU level between 2014 and 2020. Using the approach, we observed no public EU-level funding for multiple technologies prioritised by the EU, such as low-carbon production and use of cement and chemicals, electric battery, and a number of industrial decarbonisation processes. We observed a rising trend in the funding of solar power and onshore wind, the adjacent to them power-to-X technology, as well as recycling. At the same time, the shares of funding into fuel cell, biofuel, demand-side energy management, microgrids, and waste management show a decline trend. With note of the exploratory character of the present paper, we propose that the EU Horizon 2020 funding of clean technologies only partially reflected the expectations of key institutionalised EU actors due to the existence of many non-funded prioritised technologies.

Abstract: The Brazilian solar energy potential presents an annual average considerably high compared with Germany, which receives 40% less radiation than the least sunny place in Brazil and, even so, is at an advanced stage of research and facilities. The cooperation between Brazil and Germany promotes important results for the development of solar energy in the country.

Matlab program and data for the paper “An energy consumption rectification method based on Bayesian linear regression and heating degree-days". "simulation model.zip" is the heating house model in Trnsys simulation software. "Example1" and "Example2" is the Matlab program and data in this paper.

Ammonia is widely used for industrial cooling, but also capable to deliver heat for hot water production up to 90 °C. Butane has favourable thermodynamic properties for high temperature applications above 90 °C. Recent improvement in both ammonia and hydrocarbon compressor technology shows potential for higher condensation temperature thereby expanding their application for heating. Both working fluids can independently convert waste heat to higher temperatures. When integrated into one system, the possibilities are further improved with more flexibility for industrial applications. This paper explores the potential of different cycle configurations of ammonia and butane cascade heat pump for high temperature industrial heating. The systems are designed to take advantage of the favourable properties of each working fluid, while optimized for different operating conditions. Several theoretical models using simulation tools are developed to implement the component and system designs. The model uses both technology that is commercially available and improved components to demonstrate the opportunities.

This dataset includes input data to estimate learning-by-doing (LbD) and learning-by-researching (LbR) rates for onshore wind and solar PV in the United States. Using different learning curve approaches the simulated technology cost developments are also presented. Coefficient of determination (R square) and Root Mean Square Error (RMSE) were applied for quantification of the agreement between simulated and observed technology costs.