This dataset contains yearly electricity generation, capacity, emissions, import and demand data for over 200 geographies. Data is collected from multi-country datasets (EIA, Eurostat, BP, UN) as well as national sources (e.g China data from the National Bureau of Statistics).

Credit: Nicolas Fulghum https://ember-climate.org/data-catalogue/yearly-electricity-data/

This dataset includes photochemical air quality modeling files for simulations of fire impacts on ground-level ozone cocnentrations in the U.S. during the summer of 2023. A data dictionary describes what is included in the each of the files. Detailed information on the model simulations and the file contents is included in a journal article documenting the dataset: Simon, H., Beidler, J., Baker, K.R., Henderson, B.H., Fox, L., Misenis, C., Campbell, P., Vukovich, J. Possiel, N., Eyth, E. Expediated Modeling of Burn Events Results (EMBER): A Screening-Level Dataset of 2023 Ozone Fire Impacts in the US, Data in Brief, https://doi.org/10.1016/j.dib.2024.111208 A web-based tool for browsing this dataset is also available at: https://www.epa.gov/air-quality-analysis/expedited-modeling-burn-events-results-ember. This dataset is associated with the following publication: Simon, H., J. Beidler, K. Baker, B. Henderson, L. Fox, C. Misenis, P. Campbell, J. Vukovich, N. Possiel, and A. Eyth. Expediated Modeling of Burn Events Results (EMBER): A Screening-Level Dataset of 2023 Ozone Fire Impacts in the US. Data in Brief. Elsevier B.V., Amsterdam, NETHERLANDS, 58: 111208, (2025).

This dataset contains monthly generation, emissions and demand data for 85 geographies representing more than 90% of global power demand. Data is collected from multi-country datasets (EIA, Eurostat, BP, UN) as well as national sources (e.g China data from the National Bureau of Statistics).

credit: Nicolas Fulghum https://ember-climate.org/data-catalogue/monthly-electricity-data/

Traffic analytics, rankings, and competitive metrics for ember-energy.org as of September 2025

Ember Energy Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

"**Electricity Generation (OurWorldInData, 1985-2023)**" dataset contains the total electricity generation worldwide by country from 1985 to 2023. The amounts have been measured in terawatt-hours unit for each country.

At A Glance:

Area Covered: Worldwide; Country-wise

Period: 1985-2023

File Format: csv

License: Creative Commons BY license

Online Source: https://ourworldindata.org/grapher/electricity-generation?facet=none&uniformYAxis=0

Citation: Ember (2024); Energy Institute - Statistical Review of World Energy (2023) – with major processing by Our World in Data. “Total electricity generation – Ember and Energy Institute” [dataset]. Ember, “Yearly Electricity Data”; Energy Institute, “Statistical Review of World Energy” [original data]. Retrieved June 4, 2024 from https://ourworldindata.org/grapher/electricity-generation

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F20650127%2Fcdd8afbf4fae4a994d970b2ccc2bcca6%2Felectricity-generation.png?generation=1717493035288969&alt=media" alt="">

This ember load dataset represents the ember load index (ELI) per pixel, for a given pixel, based on surface and canopy fuel characteristics, climate, and topography within the pixel. The Ember Load Index (ELI) incorporates burn probability (BP). BP is incorporated into calculations of the ember production before the distribution of embers across the landscape to determine ember load. Given that ELI incorporates burn probability, this index can be used to identify where on the landscape hardening buildings may be needed to resist ignition and the priority for doing so according to the likelihood of the area being visited by fire.

Data taken from "Our World in Data".

Data is compiled by Our World in Data based on two sources:

– BP Statistical Review of World Energy: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html – Ember: https://ember-climate.org/data/

We rely on electricity mix data from BP as our primary source for two key reasons: BP also provides total energy (not just electricity) consumption data, meaning energy and electricity data is consistent from the same source; and it provides a longer time-series (dating back to 1965) versus only 2000 from Ember.

However, BP does not provide data for all countries. So, where data from BP is available for a given country or year, we rely on it as the primary source. But we supplement this with data from Ember where it's not available.

2020 electricity data is currently only available for EU countries and the UK based on the latest release of European data from Ember: https://ember-climate.org/data/european-electricity/

Our World in Data has converted absolute electricity production by source to the share in the mix by dividing each by the total electricity production.

ember-lab-berkeley/LeVERB-Bench-Data dataset hosted on Hugging Face and contributed by the HF Datasets community

This dataset contains the predicted prices of the asset Ember over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset contains the predicted prices of the asset Ember Bodol over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Description

This repository contains all data and code to extend the hybrid-units version of EXIOBASE to account for new innovative steelmaking routes envisaged to be deployed in the EU to meet decarbonization targets for the steel industry. The new model was built by adopting the MARIO open-source framework.

The database is an improved version of the one described in the following open-access paper (DOI: https://doi.org/10.1088/1748-9326/ad5bf1)

What's new

• The new technologies have been characterized for all regions, assuming each inventory to be the same in all regions but differentiated by regional import patterns of each commodity.
• A slight aggregation on electricity production activities and commodities have been also performed, to nowcast electricity production mixes to 2024 based on Ember data. Data from Ember have been rearranged to calculate electricity mixes by year and Exiobase regions
• The list of steel production technologies have been extended. Full list in the table below

The database implements in the EU the following new activities and commodities:

Instructions

To use the database, please install MARIO following the instructions. The database can be parsed by using the following command

The ember transport model used in WildEST tracks the travel of embers from each source pixel to downwind receiving pixels. The relative number of embers landing on a given receiving pixel is summed across all potential source pixels. If the receiving pixel has a nonzero WRC Building Cover value (meaning the pixel is within 75 m of a qualifying building), then we separately sum the relative number of embers from the source pixel. The final SELB raster represents the expected annual relative ember production that lands on building cover across all weather types.

This dataset provides information about the number of properties, residents, and average property values for Ember Path cross streets in Hernando, FL.

This dataset provides information about the number of properties, residents, and average property values for Ember Drive cross streets in Westfield, WI.

Data on Energy by Our World in Data

Our complete Energy dataset is a collection of key metrics maintained by Our World in Data. It is updated regularly and includes data on energy consumption (primary energy, per capita, and growth rates), energy mix, electricity mix and other relevant metrics.

The complete Our World in Data Energy dataset

🗂️ Download our complete Energy dataset : CSV | XLSX | JSON

The CSV and XLSX files follow a format of 1 row per location and year. The JSON version is split by country, with an array of yearly records.

The variables represent all of our main data related to energy consumption, energy mix, electricity mix as well as other variables of potential interest.

We will continue to publish updated data on energy as it becomes available. Most metrics are published on an annual basis.

A full codebook is made available, with a description and source for each variable in the dataset.

Our source data and code

The dataset is built upon a number of datasets and processing steps: - Statistical review of world energy (Energy Institute, EI): - Source data - Ingestion code - Basic processing code - Further processing code - International energy data (U.S. Energy Information Administration, EIA): - Source data - Ingestion code - Basic processing code - Further processing code - Energy from fossil fuels (The Shift Dataportal): - Source data - Ingestion code - Basic processing code - Further processing code - Yearly Electricity Data (Ember): - Source data - Ingestion code - Basic processing code - Further processing code - European Electricity Review (Ember): - Source data - Ingestion code - Basic processing code - Further processing code - Combined Electricity (Our World in Data based on Ember's Yearly Electricity Data and European Electricity Review): - Processing code - Energy mix (Our World in Data based on EI's Statistical review of world energy): - Processing code - Fossil fuel production (Our World in Data based on EI's Statistical review of world energy & The Shift Dataportal's Energy from fossil fuels): - Processing code - Primary energy consumption (Our World in Data based on EI's Statistical review of world energy &...

This dataset provides information about the number of properties, residents, and average property values for Ember Lane cross streets in Heath Springs, SC.

Non-traditional data signals from social media and employment platforms for EMBT stock analysis

This dataset contains numerical data and descriptive information on all 'burning ember' diagrams presented in the reports of the Intergovernmental Panel on Climate Change (IPCC), from the first appearance of these diagrams in 2001 to the 6th Assessment Report, published in 2022. The aim of this dataset is to bring together the data and metadata needed to reconstruct the burning embers diagrams and acquire essential information on the risks assessed and their evolution, within a single, homogeneous framework. The file presented here has been extracted from the database at the indicated date: it is a versioned archive of the database (excluding internal development fields, which are not publicly available). Analyses and figures based on this dataset are presented in Marbaix et al., 2024 [1], which provides information about the data. The data are provided in a text file in JSON format, the structure of which is described in the file itself and in the Supplement to Marbaix et al. 2024 [1].

The IPCC secretariat has confirmed that these data can be distributed under the CC-BY licence as indicated here. When using this dataset, we ask you to provide the reference to each IPCC report which is the source of the data (and additional sources listed in the references to this dataset when relevant), as well as to the dataset, adding the related paper [1] as soon as it is available.

Ember Technologies Inc Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.