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TECHNICAL INFO No data quality control has been carried out. No gap-filling has been applied. Detailed information about the site and deployment can be found in the Technical documentation of the urbisphere-Paris campaign. This publication may include a number of files that contain the same measurements (duplicate files, "dupes") as multiple raw data backups were performed on the data. The duplicate data can be differentiated by the information found in the timestamp column and file header. ACKNOWLEDGEMENTS Authors thank SIRTA/LMD staff for providing support and facilities; ATMO-TNA-3—0000000125 funding COPYRIGHT NOTICE Copyright Jörn Birkmann, Andreas Christen, Nektarios Chrysoulakis, and Sue Grimmond. Some rights reserved. CREATOR NOTICE This work is owned by the Principal Investigators (PIs) of the Urbisphere project. ATTRIBUTION NOTICE The [creation and] curation of this work has been funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 855005). DISCLAIMER NOTICE The use of the work is at the user's own risk. The authors, the involved institutions, and/or the European Research Council accept no liability for material or non-material damage arising from the use or non-use or from the use of incorrect or incomplete information in this work. The authors, the involved institutions, and/or the European Research Council are not responsible for any use that may be made of the information in this work. The legal provisions remain unaffected. MATERIAL NOTICE The notices cover data in databases, text and images contained in the work. MATERIAL URI Urbisphere project Original logger data files from radiometer intercomparison measurements at SIRTA Atmospheric Observatory in Palaiseau in the Greater Paris region.

As the European Union embarks on the energy transition, several challenges need to be faced to ensure that this shift is conducted from a holistic perspective that avoids burden-shifting across sustainability dimensions. One of the main concerns refers to the future availability of materials that clean technologies require. Critical rawmaterial assessment serves to guide the management of such mineral resources in a new paradigm of increasing demand. This work delves into the methodological fundamentals of several product-level criticality indicators in order to discuss their implications within the context of the ecodesign of two hydrogen-related products. Overall, criticality is advised to be assessed making use of several indicators. In the case study of a proton exchange membrane fuel cell stack, the combined interpretation of criticality indicators leads to identifying platinum as the main hotspot, while yttrium and lanthanum account for the most relevant criticality contributions in the casestudy of a solid oxide electrolysis cell stack. The authors would like to thank Gonzalo Puig-Samper and Eleonora Bargiacchi for the insights provided. This work has been carried out within the framework of the projects eGHOST and SH2E. These projects have received funding from the Fuel Cells and Hydrogen 2 Joint Undertaking (now Clean Hydrogen Partnership) under Grant Agreements No. 101007166 and 101007163, respectively. This Joint Undertaking receives support from the European Union’s Horizon 2020 Research and Innovation programme, Hydrogen Europe and Hydrogen Europe Research. The contents of this document are provided “AS IS”. It reflects only the authors’ view and the Joint Undertaking is not responsible for any use that may be made of the information it contains.

Excel document that contains the data of the article: ‘Technology validation of photosynthetic biogas upgrading in a semi-industrial scale algal-bacterial photobioreactor’. This dataset shows the values obtained during the experimental period and it complements the corresponding article.

Files for the manuscript “Radiocarbon Isotopic Disequilibrium Shows Little Incorporation of New Carbon in Soils and Fast Cycling of a Boreal Forest Ecosystem” 1. “Raw_Data” folder contains the files in .xlsx: - Lab_Atmospheric_Samples: D14C results from ambient air at the sampled heights. - Lab_Soil_Respiration: D14C results with date and integration time for the FFSR sampling campaign. - Lab_Solid_Samples: D14C and TOC results for soil, vegetation, roots, fungi and incubation samples.

The PV-Live dataset comprises data from a network of 40 solar irradiance measurement stations across the German state of Baden-Württemberg. All stations measure global horizontal irradiance and temperature with a pyranometer, and global tilted irradiance in east, south, and west direction with tilt angles of 25° with three photovoltaic reference cells in minute resolution. A quality control scheme has been developed specifically for this dataset and is applied to the measurements before publication. The minute resolution irradiance and temperature measurements are published with the derived quality flags. A description of the dataset and the quality control scheme is given in Lorenz et al. (2022) and Lorenz et al. (2020). The dataset contains data from September 2020 onwards. It will be continuously extended by adding data of the previous month on a monthly basis. QUALITY FLAGS Two types of flags are provided with the data. Each sensor is assigned a general quality flag, which is based on a combination of different tests. In addition, a shading flag is given, which is not sensor specific, i.e. it applies to all irradiance sensors simultaneously. The flags can have the levels 'passed, all tests complete', 'passed, not all tests complete', 'failed tests, likely erroneous' or 'failed tests, most likely erroneous'. If the flag level of the general quality flags is 'failed tests, most likely erroneous' the corresponding measurement value is set to NaN. DATA FORMAT The data is published as monthly .zip archives. Each archive contains the following files: 1. Tab separated data files (tng000XX_YYYY-MM.tsv) for each station, containing measurements and quality flags of one month 2. Tab separated station location metadata (metadata_stations_YYYY-MM.tsv) 3. Metadata of the dataset describing variable names and quality flag levels (metadata_measurements.json) 4. General comments on data availability and quality for the month (comments_quality_control_YYYY-MM.txt) 5. Log file of changes (change_log_YYYY-MM.txt) Station location metadata is given on a monthly basis because stations can be relocated. Therefore, we recommend to use the metadata valid for its corresponding month. VERSION UPDATES Version 7: - Recalculation of height information for all stations - One station has been moved to a new, nearby location on 16th September 2021 ACKNOWLEDGEMENTS The data have been collected and processed by Fraunhofer ISE in the framework of PV-Live, a project in cooperation with TransnetBW. We thank our station partners for cooperation in installing and maintaining our measurement stations: EnBW Solar, Badenova, Pohlen Solar, Oekogeno Solar7, Ecovision, Hochschule Ulm, Hofgemeinschaft Heggelbach, Soltechnics-solution and the Stadtwerke Karlsruhe, Grünstadt, Buchen, Crailsheim, Schwäbisch Hall, Pforzheim, Konstanz, Waldshut-Tiengen, Schwäbisch Gmünd, Ravensburg, Eberbach, Baden-Baden.

Creating a century-long homogenized near-surface wind speed (WS) observation dataset is essential to improve our knowledge about the uncertainty and causes of WS stilling and recovery. We rescued paper-based WS records dating back to the 1920s at 13 stations in Sweden and established a four-step homogenization procedure to generate the first 10-member centennial homogenized WS dataset (HomogWS-se) for community uses among climatology, ecology, hydrology and energy industry. HomogWS-se can be used to study the WS variability and change, assess climate reanalysis, and constrain climate simulations for better future projection of changes in the WS and wind energy potential. HomogWS-se contains 13 individual text files with 10-member century-long homogenized monthly WS series, as well as the member-mean series. {"references": ["Zhou, C., C. Azorin-Molina, E. Engstr\u00f6m, L. Wern, S. Hellstr\u00f6m, and D. Chen, 2022: A century-long homogenized dataset of near-surface wind speed observations since 1925 rescued in Sweden. Earth Syst. Sci. Data, 1-24, 10.5194/essd-2022-29."]}

Dataset from the outdoor characterization of a B Series module from Insolight at the rooftop of the Instituto de Energía Solar - Universidad Politécnica de Madrid. These are measurements of a module of the same type as “Outdoor monitoring data of an Insolight B-series module - CPV sub-module” however, in the previous measurements the module was mounted on a two-axis tracker to benchmark its performance, while in these measurements, the module’s integrated planar micro tracking system was used. This data was presented at IEEE PVSC 46 in June 2019 in Chicago. See preprint of conference article. Monitoring campaign: Location: 40.453°N, -3.727°E. Instituto de Energía Solar, Universidad Politécnica de Madrid. 28040 Madrid, Spain. Fixed Mounting Angle: Due South, Slope Angle = 30° Starting date: 30 May 2019 End date: 14 June 2018 Description of data file: Data files format: single comma-separated text file; headers in first row; all of the following parameters; order below is the same as order in file Measurement time: the vector of times represents the times at which the Insolight module firmware sampled the current values of the III-V and Si outputs (measured simultaneously). Date Time (dd/mmm/yyyy HH:MM:SS): time in CEST / UTC+2 Measured meteorological data: these values are measured directly by the IES meteorological station with 1-minute resolution. They have been re-interpolated to match the measurement times. DNI (W/m2): direct normal irradiance as measured by a Normal Incidence Pyrheliometer from Eppley on a solar tracker. Spectral Range: 250-3000 nm. Field of view: 5° DNI_Top (W/m2): equivalent direct normal irradiance as measured by a top component cell of a lattice-matched III-V triple-junction cell in the ICU-3J35 Triband Spectro-heliometer from Solar Added Value on a solar tracker. Spectral range: 300 - 680 nm. Field of view: 5.7º DNI_Mid (W/m2): equivalent direct normal irradiance as measured by a middle component cell of a lattice-matched III-V triple-junction cell in the ICU-3J35 Triband Spectro-heliometer from Solar Added Value on a solar tracker. Spectral range: 680 - 900 nm. Field of view: 5.7º GNI (W/m2): global normal irradiance at the aperture plane as measured with a pyranometer on a solar tracker. Spectral range: 305 – 2800 nm. G(41°) (W/m2): Global Inclined Irradiance as measured with a pyranometer mounted facing due south and at a slope angle of 41° (near to local latitude). Spectral range: 305 – 2800 nm. T_Amb (°C): ambient temperature Wind Speed (m/s): wind speed Wind Dir. (m/s): wind direction Processed meteorological data: these values are calculated from the above meteorological data and provided for convenience DII (W/m2): Direct Inclined (plane of array) Irradiance corresponding to the module slope angle has been calculated using the sun’s known declination and hour angle from the time. GII (W/m2): The Global Inclined (plane of array) Irradiance is calculated by first calculating the DII(41°), that is the DII corresponding to the G(41°) measurement, and finding the Diffuse Inclined Irradiance Diff(41°) = G(41°) – DII(41°). It is assumed that the Diffuse Inclined Irradiance at 41° and 30° is equal, so GII = DII + Diff(41°). SMR_Top_Mid (n.d.): “Spectral Matching Ratio”. This is the ratio between DNI_Top and DNI_Mid. A value of unity indicates a spectrum that is equivalent to AM1.5D with regards to the energy balance between top and middle subcells. Measured module data: The module was placed in a short-ciruit condition and allowed to track using its integrated tracking system. The short circuit current was measured using shut resistors and integrated A/D channels. This hybrid module features both III-V micro cells (under concentration, with planar microtracking) and large area silicon solar cells (for diffuse capture). ISC_measured_IIIV (A): ISC_measured_Si (A) Estimated module data: As is explained in the IEEE PVSC 46 manuscript (see Preprint) the following values are estimated using the previously listed measured data. T_Backplane (°C) PMP_estimated_IIIV (W) PMP_estimated_Si (W)

Sheets with information on the FOODRUS KPIs, including: general description, calculation methodology, and observations.