AndreaBozzo/ceres-open-data-index huggingface dataset:
Solar-to-Grid Public Data File for Utility-scale (UPV) and Distributed Photovoltaics (DPV) Generation, Capacity Credit, and Value for 2012-2020

Lawrence Berkeley National Laboratory (Berkeley Lab) estimates hourly project-level generation data for utility-scale solar projects and hourly county-level generation data for residential and non-residential distributed photovoltaic (PV) systems in the seven organized wholesale markets and 10 additional Balancing Areas. To encourage its broader use, Berkeley Lab has made this data file public here at OEDI, covering the years 2012-2020. The public project-level dataset is updated annually with data from the previous calendar year. For more information about the research project, including a technical report, briefing material, visualizations, and additional data, please visit the project homepage linked in this submission.

Tags: annual-solar-value, caiso, capacity-credit, distributed-pv, duck-curve, eia-860, eia-923, energy, ercot, hourly-generation, iso-ne, lbnl, market-value, nsrdb, photovoltaics, pv, sam, solar, solar-to-grid, utility-scale-pv
Organization: Department of Energy
NOAA/WDS Paleoclimatology - Dietrich - Watcomb - PIBN - ITRDB CANA555

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Ontario, Canada. The time period coverage is from 29 to -61 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Tags: biological records, canada, climate indicators, continent, doc/noaa/nesdis/ncei, earth science, jack pine, land records, latitude 49.85, longitude -91.3167, material: null, national centers for environmental information, nesdis, noaa, north america, ontario, paleoclimate, paleoclimate indicators, pibn, pinus banksiana lamb., tree ring, tree rings, tree-ring, u.s. department of commerce, watcomb, what: age, what: total ring width, width
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Estimates of lake nitrogen, phosphorus, and chlorophyll-a concentrations to characterize harmful algal bloom risk across the United States

The objective of this research was to predict nutrient, chlorophyll-a, and associated harmful algal bloom, hypoxia, and eutrophication effects in US lakes. This research used nutrient and chlorophyll-a concentration data from the National Lakes Assessment (NLA), soil, landcover, and landscape characteristic data from LakeCat, landscape nutrient data from the National Nutrient Inventory (NNI), nutrient deposition data from the National Atmospheric Deposition Program (NADP), climate data from PRISM, landscape ecosystem data from the Earth Observatory Network (EON), and lake depth data from LAGOS and the National Hydrography Dataset (NHD). Prediction data of total nitrogen, total phosphorus, and chlorophyll-a concentrations were summarized at the catchment and lake watershed scales.

Tags: agriculture, chlorophyll, drinking-water, harmful-algal-bloom, lakes, nitrogen, nitrogen-and-co-pollutants, phosphorus, phosphorus-and-nitrogen, water-quality
Organization: U.S. Environmental Protection Agency
EnviroAtlas Potential Wetland Areas CONUS 2024

Wetland habitats provide critical ecosystem services to the surrounding landscape, including nutrient and pollutant retention, flood mitigation, and carbon storage. This EnviroAtlas dataset uses data about existing wetlands to predict areas across the conterminous United States with landscape characteristics that are likely to support wetland habitats, or potential wetland area (PWA). These data along with data on existing wetland locations can be useful for identifying sites for restoration or construction of wetlands. 

This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data or as an EnviroAtlas map service. Additional descriptive information about this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

Tags: ecosystem-services, nitrogen-and-co-pollutants, restoration, wetlands
Organization: U.S. Environmental Protection Agency
Demographics for US Census Tracts - 2012 (American Community Survey 2008-2012 Derived Summary Tables)

This map service displays data derived from the 2008-2012 American Community Survey (ACS). Values derived from the ACS and used for this map service include: Total Population, Population Density (per square mile), Percent Minority, Percent Below Poverty Level, Percent Age (less than 5, less than 18, and greater than 64), Percent Housing Units Built Before 1950, Percent (population) 25 years and over (with less than a High School Degree and with a High School Degree), Percent Linguistically Isolated Households, Population of American Indians and Alaskan Natives, Population of American Indians and Alaskan Natives Below Poverty Level, and Percent Low Income Population (Less Than 2X Poverty Level). This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States.

Tags: alabama, alaska, american samoa, arizona, arkansas, california, canada, colorado, connecticut, delaware, florida, georgia, hawaii, human, idaho, illinois, indiana, iowa, kansas, kentucky, louisiana, maine, maryland, massachusetts, mexico, michigan, minnesota, mississippi, missouri, montana, nebraska, nevada, new hampshire, new jersey, new mexico, new york, north carolina, north dakota, ohio, oklahoma, oregon, pennsylvania, rhode island, south carolina, south dakota, tennessee, texas, united states, utah, vermont, virginia, washington, washington dc, west virginia, wisconsin, wyoming
Organization: U.S. Environmental Protection Agency
Data dictionary for CATHGEN study

These data contain health and demographic information from cardiac catheterization patients at Duke University, as well as estimated PM2.5 exposure from Harvard University and data from the US Census Bureau. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: These data can be requested from the CATHGEN steering committee at Duke University. Format: Data are stored as SAS files on secured EPA drives. 

This dataset is associated with the following publications:
Weaver, A., L. McGuinn, L. Neas, R. Devlin, R. Dhingra, C. Ward-Caviness, W. Cascio, W. Kraus, E. Hauser, and D. Diaz-Sanchez. Associations between neighborhood socioeconomic cluster and hypertension, diabetes, myocardial infarction, and coronary artery disease within a cohort of cardiac catheterization patients.   American Heart Journal. Mosby Year Book Incorporated, Orlando, FL, USA, 243: 201-209, (2022).
Slawsky, E., A. Weaver, C. Ward-Caviness, L. Neas, R. Devlin, W. Cascio, A. Russell, R. Huang, W. Kraus, E. Hauser, and D. Diaz-Sanchez. Evaluation of PM2.5 Air Pollution Sources and Cardiovascular Health.   ENVIRONMENTAL HEALTH PERSPECTIVES. National Institute of Environmental Health Sciences (NIEHS), Research Triangle Park, NC, USA, 2020: 1, (2020).

Tags: american-indian, cardiovascular-disease, environmental-justice, socioeconomic-status
Organization: U.S. Environmental Protection Agency
Lidar-derived elevation data for Portage, southcentral Alaska, collected October 15, 2020

Lidar-derived elevation data for Portage, southcentral Alaska, collected October 15, 2020, Raw Data File 2024-7, provides aerial lidar-derived classified point cloud data, a digital surface model (DSM), a digital terrain model (DTM), and an intensity model of slopes above Portage Glacier, Southcentral Alaska, during leaf-off conditions. The survey provides snow-free surface elevations for use in landslide and avalanche hazard assessments. Aerial lidar data were collected on October 15, 2020, and ground control data were collected on November 13, 2020, and subsequently merged and processed using a suite of geospatial processing software. This data collection is released as a Raw Data File with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/31160).

Tags: avalanche, byron peak, dggs, digital elevation model, digital surface model (dsm), digital terrain model, elevation, emergency preparedness, engineering, engineering geology, geologic, geologic hazards, geological process, geology, geomorphology, geotechnical, hazards, landslide, landslide susceptibility, lidar, lidar intensity image, lidar las file format, point cloud data, portage lake, raster image, remote sensing, slope, slope instability, southcentral alaska, surface, surficial, surficial geology, topography
Organization: State of Alaska
NOAA/WDS Paleoclimatology - Schneider - Berlin GrÃ¼nanlage Britz-SÃ¼d den10 - FREX - ITRDB DEU313

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Germany, Western Europe. The time period coverage is from -4 to -67 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Tags: berlin grã¼nanlage britz-sã¼d den10, biological records, climate indicators, common ash, continent, doc/noaa/nesdis/ncei, earth science, europe, european ash, fraxinus excelsior l., frex, germany, land records, latitude 52.443889, longitude 13.440278, material: null, national centers for environmental information, nesdis, noaa, paleoclimate, paleoclimate indicators, tree ring, tree rings, tree-ring, u.s. department of commerce, western europe, what: age, what: total ring width, width
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
NOAA/PIBHMC 10-m Bathymetry: CNMI: Asuncion

A 10-m resolution gridded digital elevation model (DEM) for the bathymetry (ocean depth) surrounding Asuncion Island in the Commonwealth of the Northern Mariana Islands (CNMI) compiled from ship-borne multibeam sonar surveys merged with coastal bathymetry derived from multipectral IKONOS satellite data. Almost complete bottom coverage was achieved in depths between 0 and 800 m. Data collected by the Pacific Islands Benthic Habitat Mapping Center (PIBHMC) in support of NOAA's Coral Reef Conservation Program. Not to be used for navigational purposes. For a grayscale hillshade image layer of this dataset, see "mp_pibhmc_asu_bathy10m_hillshade" in the distribution links listed in the metadata. For further details about this dataset, please see: https://www.soest.hawaii.edu/pibhmc/cms/data-by-location/cnmi-guam/asunction-island/.

Tags: acoustic sounders, asuncion, bathymetry, bathymetry/seafloor topography, cameras, commonwealth of the northern mariana islands (cnmi), dem, digital elevation model, earth observation satellites, earth remote sensing instruments, earth science, height, ikonos, in situ ocean-based platforms, in situ/laboratory instruments, latitude, longitude, micronesia, models/analyses, multi-spectral, multispectral camera, northern mariana islands, ocean, oceans, pacific islands ocean observing system, pacific ocean, pacioos, passive remote sensing, photon/optical detectors, profilers/sounders, ships, sonar, western pacific ocean
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
2012-2022 National-Level Greenhouse Gas Emission Totals by Industry

These data are an update to 2012-2020 Greenhouse Gas National- and State-Level Emission Totals by Industry (https://doi.org/10.23719/1529805). Data for 2021 and 2022 are added. The primary emissions source was updated to use the U.S. GHG Inventory 2024 report.  The industry classifications were updated to use 2017 North American Industry Classification Codes. Totals by industry and state are not included. The code used to generate the datasets is available in the FLOWSA v2.0.3 tool (https://github.com/USEPA/flowsa/tree/v2.0.3). Values are given in total kilograms emitted for the given year, sector and location. Please see the related publication for more background information. 

This dataset is associated with the following publication:
Young, B., C. Birney, and W.W. Ingwersen. Dataset of 2012-2020 U.S. National- and State-Level Greenhouse Gas Emissions by Sector.   Data in Brief. Elsevier B.V., Amsterdam,  NETHERLANDS, 53: 110173, (2024).

Tags: climate-change, environmental-economic-accounts, flowsa, ghgs, greenhouse-gas-emissions, national-totals-by-industry, sector-attribution-model
Organization: U.S. Environmental Protection Agency
Supply Chain Greenhouse Gas Emission Factors v1.3 by NAICS-6

The datasets comprise greenhouse gas (GHG) emission factors (Factors) for 1,016 U.S. commodities as defined by the 2017 version of the North American Industry Classification System (NAICS). The Factors are based on GHG data for 2022. Factors are given for all NAICS-defined commodities at the 6-digit level except for electricity, government, and households. Each record consists of three factor types as in the previous releases: Supply Chain Emissions without Margins (SEF), Margins of Supply Chain Emissions (MEF), and Supply Chain Emissions with Margins (SEF+MEF). One set of Factors provides kg carbon dioxide equivalents (CO2e) per 2022 U.S. dollar (USD) for all GHGs combined using 100-yr global warming potentials from IPCC 5th report (AR5) to calculate the equivalents. In this dataset there is one SEF, MEF and SEF+MEF per commodity. The other dataset of Factors provides kg of each unique GHG emitted per 2022 dollar per commodity without the CO2e calculation. The dollar in the denominator of all factors uses purchaser prices. See the supporting file 'Aboutv1.3SupplyChainGHGEmissionFactors.docx' for complete documentation of this dataset. 

Tags: climate-change, ghg-reporting, industry-ghgs, scope-3, useeio
Organization: U.S. Environmental Protection Agency
Cross-species molecular docking method to support predictions of species susceptibility to chemical effects

The advancement of protein structural prediction tools, exemplified by AlphaFold and Iterative Threading ASSEmbly Refinement, has enabled the prediction of protein structures across species based on available protein sequence and structural data. In this study, we introduce an innovative molecular docking method that capitalizes on this wealth of structural data to enhance predictions of chemical susceptibility across species. We demonstrated this method using the androgen receptor as a pertinent modulator of endocrine function. By using protein structures, this method contextualizes species susceptibility within a functional framework and helps to integrate molecular docking into the repertoire of New Approach Methodologies (NAMs) that support the Next-Generation Risk Assessment (NGRA) paradigm through the novel integration of various open-source tools. 

This dataset is associated with the following publication:
Schumann, P., D. Chang, S. Mayasich, S. Vliet, T. Brown, and C. LaLone. Cross-species molecular docking method to support predictions of species susceptibility to chemical effects.   Computational Toxicology. Elsevier B.V., Amsterdam,  NETHERLANDS, 30(4): 100319, (2024).

Tags: androgen-receptor, bioinformatics, case-studies, endocrine, molecular-docking, molecular-modelling, new-approach-methods, next-generation-risk-assessment, regulation, seqapass, species-extrapolation
Organization: U.S. Environmental Protection Agency
Connecticut Neighboring Towns

This dataset provides the neighboring relationships between towns, with each row representing a unique town-to-neighbor connection. It includes columns for the town's name and the corresponding neighboring town name. Most towns have more than one neighbor, so there will be multiple rows for each town.

See the "Attachments" section below to download a pivoted version of this dataset named "CT Neighboring Towns in Wide Format". This includes one row for each town, a column for each neighboring town, and a total sum of neighboring towns.

Tags: boundaries, boundary, ct, towns
Organization: State of Connecticut
Incorporating weather in counts and trends of migrating Common Nighthawks

Guide to how to access NRRI data with an email request to the author. This dataset is not publicly accessible because: The data are private, but available on request. It can be accessed through the following means: Email request to Stephen Kolbe - kolbe023@d.umn.edu. Format: Novel data collected by the lead author, which are kept and curated by National Resources Research Institute (NRRI). 

This dataset is associated with the following publication:
Kolbe, S., G. Niemi, A. Bracey, M. Etterson, and A. Grinde. Incorporating weather in counts and trends of migrating Common Nighthawks.   Avian Conservation and Ecology. Society of Canadian Ornithologists and Bird Studies Canada,   CANADA, 19(1): 9, (2024).

Tags: aerial-insectivore, migration, monitoring, population-trends, weather
Organization: U.S. Environmental Protection Agency
NOAA/WDS Paleoclimatology - Warner - Huron Mountain Club - BEAL - ITRDB MI036

This archived Paleoclimatology Study is available from the NOAA National Centers for Environmental Information (NCEI), under the World Data Service (WDS) for Paleoclimatology. The associated NCEI study type is Tree Ring. The data include parameters of tree ring with a geographic location of Michigan, United States Of America. The time period coverage is from 161 to -67 in calendar years before present (BP). See metadata information for parameter and study location details. Please cite this study when using the data.

Tags: beal, betula alleghaniensis britton, biological records, climate indicators, continent, doc/noaa/nesdis/ncei, earth science, huron mountain club 3, land records, latitude, longitude, material: null, michigan, national centers for environmental information, nesdis, noaa, north america, paleoclimate, paleoclimate indicators, tree ring, tree rings, tree-ring, u.s. department of commerce, united states of america, what: age, what: total ring width, width, yellow birch
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
PRASA 301(h) WWTP databases

These data were used to investigate  long-term effects of advanced primary treated effluent discharge on coral reefs adjacent to Puerto Rico Aqueducts and Sewer Authority (PRASA) WWTPs outfalls on the north and northwest coasts of Puerto Rico. Our data were derived from secondary data sources of datasets for biological and water quality metrics collected from the PRASA monitoring program and to identify potential changes in coral reef condition from 1999 – 2018.  our database includes 1) biological endpoints consisting of percent coverage of biological and abiotic endpoints along transects near each WWTP, 2) water quality and physical data for metrics typically associated with point source WWTP effluent (e.g., coliform bacteria, ammonia, temperature, salinity, dissolved oxygen, etc.), and 3) contaminants data representing a suite of standard chemical analytes that may arise from potential point and non-point sources (e.g., pesticides, heavy metals, herbicides, etc.). 

This dataset is associated with the following publication:
Santavy, D., C. Horstmann, E. Huertas, I. Wojtenko, and S. Raimondo. Derivation of biocriteria to protect coral reefs in Puerto Rico using a biological condition gradient framework and 301(h) water quality and coral monitoring data (PR-CRBGC), Phase 2. U.S. Environmental Protection Agency, Washington, DC, USA.

Tags: coral-reef-communities, prasa, puerto-rico, wastewater-treatment-effects
Organization: U.S. Environmental Protection Agency
Lidar-derived snow surface elevation data for Deadhorse, northern Alaska, collected May 10, 2022

Lidar-derived snow surface elevation data for Deadhorse, northern Alaska, collected May 10, 2022, Raw Data File 2024-13, provides aerial lidar-derived classified classified point cloud, digital surface model (DSM), digital terrain model (DTM), and an intensity model of Deadhorse, Northern Alaska, during during peak snowpack conditions. The survey provides snow surface elevations for use in snowpack assessment. Aerial lidar data and ground control data were collected on May 10, 2022, and subsequently merged and processed using a suite of geospatial processing software. This data collection is released as a Raw Data File with an open end-user license. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/31259).

Tags: big lake, coastal, d-pad lake, deadhorse, dggs, digital elevation model, digital surface model (dsm), digital terrain model, elevation, emergency preparedness, engineering, engineering geology, environment, geologic, geologic hazards, geological process, geology, geomorphology, geophysics, geotechnical, hazards, lidar, lidar intensity image, lidar las file format, north slope, north slope borough, north slope borough coastal district, point cloud data, prudhoe bay, putuligayuk river, raster image, remote sensing, sagavanirktok river, surface, surficial, surficial geology, topography
Organization: State of Alaska
Lidar-derived elevation data for Deadhorse, Northern Alaska, collected July 16-18, 2021

Lidar-derived elevation data for Deadhorse, Northern Alaska, collected July 16-18, 2021, Raw Data File 2024-15, provides aerial lidar-derived classified classified point cloud, digital surface model (DSM), digital terrain model (DTM), and an intensity model of Deadhorse, Northern Alaska, during leaf-on conditions (cover figure). The survey provides snow-free surface elevations for use in snowpack assessment. Aerial lidar data were collected July 16-18, 2021, and ground control data were collected July 17 and 19, 2021, and subsequently merged and processed using a suite of geospatial processing software. All files can be downloaded from the Alaska Division of Geological & Geophysical Surveys website (http://doi.org/10.14509/31273).

Tags: big lake, d-pad lake, deadhorse, dggs, digital elevation model, digital surface model (dsm), digital terrain model, elevation, emergency preparedness, engineering, engineering geology, environment, geologic, geologic hazards, geology, geomorphology, geotechnical, landslide, landslide susceptibility, lidar, lidar intensity image, lidar las file format, north slope, north slope borough, north slope borough coastal district, prudhoe bay, putuligayuk river, raster image, remote sensing, sagavanirktok river, surface, surficial, surficial geology, topography
Organization: State of Alaska