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28 results for “Planetary Boundaries”
Planetary Boundaries Assessment of Flue Gas Valorization into Ammonia and Methane
<p>Dataset associated with the publication "Planetary Boundaries Assessment of Flue Gas Valorization into Ammonia and Methane" by Sebastiano C. D'Angelo, Julian Mache, and Gonzalo Guillén-Gosálbez, available at <a href="https://doi.org/10.1021/acssuschemeng.1c01915">https://doi.org/10.1016/B978-0-323-95879-0.50134-X</a>. The dataset includes the numeric data associated with Table 1 and Figure 2, converted into a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>StreamTable</strong>: numerical values associated with full set of streams depicted in Figure 1, among which a selection is reported in Table 1.</li> <li><strong>LCA-Results</strong>: numerical values associated with the breakdown of the environmental impacts for the selection of scenarios reported in Figure 2, for all the assessed control variables.</li> </ul>
Planetary Boundaries Analysis of Low-Carbon Ammonia Production Routes
<p>Dataset associated with the publication "Planetary Boundaries Analysis of Low-Carbon Ammonia Production Routes" by Sebastiano C. D'Angelo, Selene Cobo, Abhinandan Nabera, Antonio J. Martín, Javier Pérez-Ramírez, and Gonzalo Guillén-Gosálbez, available at <a href="https://doi.org/10.1021/acssuschemeng.1c01915">https://doi.org/10.1021/acssuschemeng.1c01915</a>. The dataset includes the numeric data required to plot all the figures embedded in the main manuscript and in the Supporting Information (SI), as well as the tables presented in the SI converted in a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>LCA-Total</strong>: numerical values associated with the total share of safe operating space for all the assessed control variables of the seven planetary boundaries quantified in the study, for all the considered scenarios. The results are presented for the three different downscaling approaches considered in the study. The global warming impacts for all the scenarios, calculated with the ReCiPe 2016 methodology (hierarchist approach), are here reported, as well.</li> <li><strong>LCA-Breakdown</strong>: numerical values associated with the breakdown of the environmental impacts for the selection of scenarios reported in the main manuscript, for all the assessed control variables.</li> <li><strong>Economics</strong>: numerical values associated with the breakdown of the economic impacts reported in the main manuscript, for all the assessed scenarios.</li> <li><strong>SI-Tables-LCI</strong>: tables reported in the SI associated with the environmental assessment of all the scenarios.</li> <li><strong>SI-Tables-Economics</strong>: tables reported in the SI associated with the economic assessment of all the scenarios.</li> </ul>
Planetary boundaries analysis of Fischer-Tropsch Diesel for decarbonizing heavy-duty transport
<p>Dataset associated with the publication "Planetary boundaries analysis of Fischer-Tropsch Diesel for decarbonizing heavy-duty transport" by Margarita A. Charalambous, Juan D. Medrano-Garcia, and Gonzalo Guillén-Gosálbez, available at <a href="https://doi.org/10.1016/B978-0-323-85159-6.50328-6">https://doi.org/10.1016/B978-0-323-85159-6.50328-6</a>. The dataset includes the numeric data required to plot all the figures embedded in the manuscript.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>LCA-Inventories:</strong> Inventory datasets used for life cycle assessment. Includes the inventory for the production of FT-diesel from CO<sub>2</sub> and H<sub>2</sub> sources investigated in this work, carbon dioxide from direct air capture (DAC), and point source coal power plant, as well as, the production of hydrogen from biomass and polymer electrolyte water electrolysis. Moreover, required adjustments to accommodation FT-diesel fuel in the truck transport activity are summarized.</li> <li><strong>LCA-Total</strong>: numerical values associated with the total share of safe operating space for all the assessed control variables of the seven planetary boundaries quantified in the study, for all the considered scenarios. These values represent the data used to create Figure 2.</li> <li><strong>LCA-Breakdown</strong>: numerical values associated with the breakdown of the environmental impacts for the studied scenarios, for three control variables (CO<sub>2</sub> concentration, and biosphere integrity). These values represent the data used to create Figure 3. </li> </ul>
The role of hydrogen in heavy transport to operate within planetary boundaries
<p>Dataset associated with the publication "The role of hydrogen in heavy transport to operate within planetary boundaries" by Antonio Valente, Victor Tulus, Galán-Martín, Mark A. J. Huijbregts, and Gonzalo Guillén-Gosálbez, available at <a href="https://doi.org/10.1039/D1SE00790D">https://doi.org/10.1039/D1SE00790D</a>. The dataset includes the numeric data associated with the plots described in the main manuscript, as well as the tables presented in the main manuscript converted in a machine-readable format.</p> <p>The structure of the dataset is here elucidated sheet by sheet:</p> <ul> <li><strong>Tables</strong>: tables 3 and 4, as reported in the main manuscript, with evolution considered for the main technical parameters and the values of the parameters used in the baseline, best and worst scenario.</li> <li><strong>Plots</strong>: numerical values associated with figures 2, 3, and 4, as reported in the main manuscript.</li> </ul>
Dataset for Process design within planetary boundaries: Application to CO2 based methanol production
<p>Dataset for the journal article: Process design within planetary boundaries: Application to CO2 based methanol production</p>
Data accompanying article: A planetary boundary for green water
<p>This deposit contains the LPJmL model simulation outputs of mean monthly root-zone soil moisture ("LPJmL_rzsm_hist.zip") and the data underlying the plot in Fig. 3 ("Fig_3_plotdata.xlsx") in the article: Wang-Erlandsson, L., Tobian, A., van der Ent, R. J., Fetzer, I., te Wierik, S., Porkka, M., Staal, A., Jaramillo, F., Dahlmann, H., Singh, C., Greve, P., Gerten, D., Keys, P.W., Gleeson, T, Cornell, S. E., Steffen, W., Bai, X., Rockström, J., (2022): A<em> planetary boundary for green water</em>. Nature Reviews Earth & Environment. For method description, please refer to the article.</p> <p>Files in the folder "LPJmL_rzsm_hist.zip" are named as NN_rzsm_hist_M.tif, in which:</p> <ul> <li>NN refers to the name of an Earth system model, of which the outputs were used as forcing in the LPJmL runs</li> <li>rzsm refers to "root zone soil moisture"</li> <li>hist refers to historical period 1850-2014</li> <li>M refers to name of month (jan for January etc.)</li> </ul> <p> </p> <p> </p>
Planetary Boundary Layer Height Retrievals from the Cloud-Aerosol Transport System (CATS) around the US Southern Great Plains and the Eastern North Atlantic
<p>Planetary Boundary Layer Height (PBLH) retrievals in kilometers from the Cloud-Aerosol Transport System (CATS) around the DOE ARM US Southern Great Plains (SGP) and the Eastern North Atlantic (ENA), using a modified version of the Different Thermo-Dynamics Stability (DTDS) algorithm. Quality control Flags are included as follows:</p> <ul> <li>0 = 'Good Quality'</li> <li>1 = 'Mediate Quality'</li> <li>2 = 'Bad Quality'</li> </ul> <p>In addition, -999 values in the dataset represent no data. <br>The PBLH for daytime denoised CATS photon counts at SGP is named: "daytime-denoised-dtds-pblh-sgp.csv"<br>The PBLH for the original daytime and nighttime data at SGP and ENA, without denoising the data, are named: "original-cats-dtds-pblh-daytime-nighttime-sgp.csv" and "original-cats-dtds-pblh-daytime-nighttime-ena.csv"</p> <p>References: </p> <p>Roldán-Henao, N., Yorks, J., Su, T., Selmer, P., & Li, Z. (2024). Statistically Resolved Planetary Boundary Layer Height Diurnal Variability Using Spaceborne Lidar Data. <em>Remote Sensing. </em></p> <p>Su, T., Li, Z., & Kahn, R. (2020). A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions. <em>Remote Sensing of Environment</em>, <em>237</em>, 111519.</p>
Dataset: The implications of microalgae biofuel production for the heavy-duty transport sector under planetary boundary perspective
<p><strong>Dataset of the article: </strong><em>"The implications of microalgae biofuel production for the heavy-duty transport sector under planetary boundary perspective"</em></p> <ul> <li>Selected results of the analysis are included in <strong>Microalgae biofuel results.zip</strong></li> </ul> <p><strong>Summary:</strong></p> <p>In this contribution, we study the extent to which 68 scenarios for microalgae biofuels could help the heavy-duty transport sector operate within planetary boundaries. The proposed scenarios are built considering a range of alternative configurations based on three types of fuel production processes (i.e., transesterification, hydrodeoxygenation and hydrothermal liquefaction), different carbon sources (such us a natural gas power plants and direct air capture), byproduct treatments, and two electricity mixes. Our results reveal that microalgae biofuels could significantly reduce the environmental and human health impacts of the business-as-usual (fossil-based) heavy-duty transport sector. Moreover, relative to standard biofuels that show large land-use requirements, we find that microalgae biofuels also decrease the damage on biosphere integrity substantially. Notably, pathways resorting to hydrodeoxygenation of microalgae oil and direct air capture and carbon storage could reduce the current impact induced globally on climate change by the heavy transport by 77%, while attaining six-fold reductions in biosphere integrity impacts, both relative to conventional biofuels. Simultaneously, microalgae-based biofuels can achieve impacts six times lower than conventional biofuels in biosphere integrity and 45% lower in human health.</p>
Data for One Earth publication "Breaching planetary boundaries: Over half of global land area suffers critical losses in functional biosphere integrity"
<p>This repository contains data and processing scripts for the study: Stenzel et al. 2025, One Earth, "Breaching planetary boundaries: Over half of global land area suffers critical losses in functional biosphere integrity".</p>
Planetary Boundary Layer Height Retrievals from Micropulse-lidar at four Multiple ARM Sites Around the World
<p><span>Planetary Boundary Layer Height Retrievals from Micropulse-lidar at the following ARM campaigns: GOAMAZON (MAO), COPS (FKB), CACTI (COR), and BAECC (TMP).</span><span> These retrievals </span><span>were computed</span><span> using the Different Thermo-Dynamic Stabilities (DTDS) algorithm </span><span>(Su et al., 2020; Su et al., 2022)</span><span>. The quality-control flag is provided in the dataset file, where zero (0) indicates a high-quality flag. </span></p> <p>Su, T., Zheng, Y. and Li, Z., 2022. Methodology to determine the coupling of continental clouds with surface and boundary layer height under cloudy conditions from lidar and meteorological data. Atmospheric Chemistry and Physics, 22(2), pp.1453-1466.</p> <p>Su, T., Li, Z. and Kahn, R., 2020. A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions. Remote Sensing of Environment, 237, p.111519.</p> <p><span>Roldán-Henao, N., Su, T., and Li, Z. (2024, under review). Refining Planetary Boundary Layer Height Retrievals from Micropulse-lidar at Multiple ARM Sites Around the World. Submitted to <em><span>Journal of Geophysical Research: Atmospheres. </span></em></span></p>
Outside the Safe Operating Space of a New Planetary Boundary for Per- and Polyfluoroalkyl Substances (PFAS)
<p>Supporting information (Open Data)m for the article Outside the Safe Operating Space of a New Planetary Boundary for Per- and Polyfluoroalkyl Substances (PFAS)</p>
Planetary boundary layer height (PBLH) over the SGP
<p>PBLH is a critical parameter influencing weather phenomena, air quality, and various meteorological processes. However, accurately retrieving PBLH has been a challenging task due to limitations such as coarse temporal resolution and measurement drift in traditional radiosonde observations. To address these limitations, we have devised a lidar-based methodology that capitalizes on a newly developed algorithm for PBLH retrieval. This algorithm demonstrates enhanced capabilities in capturing diurnal fluctuations in PBLH compared to existing lidar-based methods (Su et al., 2020). In addition, we have refined this algorithm specifically for PBLH retrieval under cloudy conditions through a novel scheme (Su et al., 2022). To ensure data reliability, a quality-control process has been implemented to filter out questionable data points. Accompanying the dataset is a quality-control flag for ease of reference. It should be noted that we have assimilated all available radiosonde observations to provide a more robust estimate of PBLH, making the dataset valuable for a variety of related studies.</p> <p>Data for PBLH are collected between 07:00 and 19:00 Local Time and are expressed in meters. In the dataset, a Quality Control (QC) value of 0 signifies valid data. A QC value of -2 denotes data that are "Not a Number" (NaN), indicating missing or non-applicable information. A QC value of 2 flags problematic data that may require further scrutiny.</p>
Simulation performance of different planetary boundary layer schemes in WRF V4.3.1 on wind field over Sichuan Basin within "Gray zone" resolution
<p>Weather Research and Forecasting (WRF) model was <span>used</span> to <span>investigate the performance of different planetary </span>boundary layer <span>(PBL) </span>parameteri<span>z</span>ation schemes <span>on </span>simulat<span>ing</span> surface wind <span>fields over Sichuan Basin</span> at a spatial resolution of <span>0.33</span>km<span>.</span> <span>T</span>he <span>experiment</span> is based on <span>multi-</span>case stud<span>ies, so</span> 2<span>8 near-surface </span>wind events from 2021 to 2022 <span>were selected, and</span> <span>a</span> total of 112 <span>sensitivity </span>simulations were <span>carried out by</span> employing four common<span>ly used</span> <span>PBL </span>schemes: YSU, MYJ, MYNN2, and QNSE<span>, and</span> compared to observations.</p> <p>The mean 10 minutes observations of wind speed and direction during the study period from the Guanghan Airport are stored in one seperate txt file named OBS-28cases-every10min-10m-wind-Guanghan-Airoprt.txt.</p> <p>Wind field (U10, V10) at the central point from the WRF simulations of inner domain from all the PBL simulations are investigated, which are stored in txt format (.txt), and all the results are available from the first author(yuet@mail.iap.ac.cn).</p>
Code and data for "Multiple planetary boundaries preclude BECCS outside of agricultural areas"
<p>This repository contains the model code, scripts, configuration files, key results and documentation for the main analysis in:</p> <p>Braun, et al. “Multiple planetary boundaries preclude BECCS outside of agricultural areas”</p> <p>It contains:</p> <p># LPJmL</p> <p>## 1_LPJmL_model_code</p> <p>## 2_configure_runs</p> <p>## 3_configurations</p> <p># R</p> <p>## 1_generate_inputs</p> <p>## 2_process_input_data</p> <p>## 3_beccs_optimization</p> <p># Results</p> <p>## 1_source_data_figures</p> <p>## 2_further_results</p> <p># README</p>
Data from the article "Modulation of wintertime canopy Urban Heat Island (CUHI) intensity in Beijing by synoptic weather pattern in planetary boundary layer"
<p>The link includes four datasets, "pcttype" is weather typing data, "pblh" is PBLH data, "uhii-UV" is the mean value of CUHII and wind direction UV of all urban stations, and "uhii-sws" is the value of CUHII, wind speed and wind direction of all urban stations.</p>
Planetary boundaries framework scenarios
<p>The planetary boundaries framework serves as a comprehensive method to define a safe operating space for humanity on Earth. This set of scenarios projects eight out of nine planetary boundaries processes under different scenarios to 2050, both with and without strong environmental policy response strategies.</p>
Supplementary, raw data, and model for manuscript titled Coupling the TKE-ACM2 Planetary Boundary Layer Scheme with the Building Effect Parameterization Model
<p>This file contains 1. raw data simulated by WRF and PALM, and LiDAR and surface station measurements (<a href="https://zenodo.org/api/records/13959541/draft/files/Raw%20data%20PALM_WRF_Obs.zip/content" target="_blank" rel="noopener noreferrer">Raw data PALM_WRF_Obs.zip</a>); 2. supplementary drawing modeled and simulated U10, T2, and RH2 time series at surface stations (<a href="https://zenodo.org/api/records/13959541/draft/files/Supplementary.docx/content" target="_blank" rel="noopener noreferrer">Supplementary.docx</a>); 3. WRF version containing the TKE-ACM2+BEP (<a href="https://zenodo.org/api/records/13959541/draft/files/WRF433_TKE-ACM2+BEP.tar.gz/content" target="_blank" rel="noopener noreferrer">WRF433_TKE-ACM2+BEP.tar.gz</a>).</p>
Selected data analyzed in the JGR Atmosphere manuscript "Atmospheric meridional circulation between South Asia and Tibetan Plateau caused by the change of planetary boundary layer depth."
<p>1. The PBL depth dataset including the PBL type (the convective boundary layer, the neutral boundary layer, and the stable boundary layer) and the calculated the PBL depths at the 19 stations for the 2013-2015 summers.</p> <p>2. The control experiment (WRF-CTL) and the MEP experiment (WRF-MEP) simulations results including PBL depth and geopotential height at 500 hPa at 00:00 UTC, 06:00 UTC, 12:00 UTC, and 18:00 and hourly sensible and latent heat. The simulation period was 1 June to 31 August 2015 with 30 hours from 12:00 UTC (20:00 Beijing time (BJT)) each day.</p>
Selected data analyzed in the JGR Atmosphere manuscript "Atmospheric meridional circulation between South Asia and Tibetan Plateau caused by the change of planetary boundary layer depth."
<p>1. The PBL depth dataset including the PBL type (the convective boundary layer, the neutral boundary layer, and the stable boundary layer) and the calculated the PBL depths at the 19 stations for the 2013-2015 summers.</p> <p>2. The control experiment (WRF-CTL) and the MEP experiment (WRF-MEP) simulations results including PBL depth and geopotential height at 500 hPa at 00:00 UTC, 06:00 UTC, 12:00 UTC, and 18:00 and hourly sensible, latent heat and thermal radiation (net longwave radiation). The simulation period was 1 June to 31 August 2015 with 30 hours from 12:00 UTC (20:00 Beijing time (BJT)) each day.</p>
Data and accompanying software for One Earth submission "A software package for assessing terrestrial planetary boundaries"
<div>This repository contains the data as well as the accompanying model software and analysis scripts being used in the One Earth submission <em>A software package for assessing terrestrial planetary boundaries</em> that describes the software package boundaries:</div> <div> </div> <div><em>Braun, J., Breier, J., Stenzel, F., & Vanelli, C. (2025). boundaries: Planetary Boundary Status based on LPJmL simulations (Version 1.3.1) [Computer software]. https://doi.org/10.5281/zenodo.</em>14906079</div> <div> </div> <div>Usage information: We split zip files to bypass Zenodo's upload restrictions. Please download all and open one of the zip files to unpack all automatically.</div>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.