Data Methodology

The document outlines the technical processes Ember uses to assemble electricity data for 215 countries from 2000 to 2021. It describes the use of multiple sources—including the EIA, Eurostat, and IRENA—to reconcile annual and monthly data, disaggregate thermal generation, and estimate emissions using IPCC factors. The guide also provides a detailed country-by-country breakdown of the specific sources and adjustments applied to each territory's data.

• Ember's core datasets cover five primary metrics: electricity generation, net imports, electricity demand (calculated as the sum of production and net imports), installed power generation capacity, and emissions from electricity generation.
• Global fuel data is categorized into nine types: Bioenergy, Coal, Gas, Hydro, Nuclear, Other Fossil, Other Renewables, Solar, and Wind. In European datasets, Coal is further subdivided into Hard Coal and Lignite.
• To estimate the latest annual generation when data is unavailable, Ember applies absolute changes from available annualised monthly data to historical annual values, using 2019 as a reference point due to COVID-19 pandemic anomalies.
• Thermal generation is disaggregated using a hierarchy of sources: first using IEA monthly electricity generation statistics ratios, then BP’s statistical review of world energy, and finally capacity ratios for remaining countries.
• Installed capacity data is primarily sourced from Global Energy Monitor (GEM) for coal and gas, the International Renewable Energy Agency (IRENA) for non-fossil generation, and the World Resources Institute (WRI) for certain Other Fossil capacity data.
• Global emissions figures are calculated using IPCC 5th Assessment Report Annex 3 (2014) factors, which include full lifecycle emissions and upstream methane, converted to CO2 equivalent over a 100-year timescale.
• Ember identifies several caveats in emissions intensity factors, noting that IPCC figures may not capture regional fuel quality differences (e.g., lignite vs anthracite), recent efficiency improvements in Chinese coal plants, or the high-carbon risk of certain woody biomass feedstocks in bioenergy.

APA

Ember (n.d.). Data Methodology. https://ember-energy.org/app/uploads/2022/03/Methodology-GER22-PDF-844-KB.pdf

Chicago

Ember. Data Methodology. n.d. https://ember-energy.org/app/uploads/2022/03/Methodology-GER22-PDF-844-KB.pdf.

Wikipedia

{{cite report |author=Ember |title=Data Methodology |url=https://ember-energy.org/app/uploads/2022/03/Methodology-GER22-PDF-844-KB.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{embernddata, author = {{Ember}}, title = {{Data Methodology}}, institution = {Ember}, url = {https://ember-energy.org/app/uploads/2022/03/Methodology-GER22-PDF-844-KB.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }