Electrical grid decarbonization refers to the process of reducing the amount of carbon emissions associated with the generation of electricity. Currently, many power plants use fossil fuels like coal or natural gas to produce electricity. Burning these fuels releases carbon dioxide (CO2) and other greenhouse gases into the atmosphere, contributing to climate change. Grid decarbonization aims to transition away from these fossil fuel-based power sources and replace them with cleaner and more sustainable alternatives like solar, wind, hydro, and geothermal power.
The decarbonization process involves increasing the share of renewable energy in the electricity mix. As more renewable energy sources are added to the grid, the carbon intensity of the electricity (kgCO2e/kWh) decreases. This shift towards cleaner energy sources helps reduce the overall carbon footprint of the electricity we use in our homes, businesses, and other buildings.
Electrical Grid Decarbonization Data
A number of different global, international, national, and state/province data sources exist for grid decarbonization data, projection, and historical data. cove.tool uses the following sources for historic, projected, and single-year data to cover the broadest range possible.
National Renewable Energy Laboratory (NREL) Cambium data
United States Environmental Protection Agency (EPA) eGRID data
European Environment Agency (EEA) Greenhouse Gas Emission Intensity Report
Carbon Footprint Country Specific Electricity Grid Greenhouse Gas Emission Factors
Institute for Global Environmental Strategies (IGES) List of Grid Emissions Factors
cove.tool uses these data sources to extrapolate the future decarbonization of the grid to account for lifecycle operational carbon in the Carbon Feature. Based on the Cambium projects from NREL, a logarithmic decay curve is fit to the projection data based on the decarbonization scenario selected. This curve is used to extrapolate future projections for locations without anticipated grid decarbonization data. In locations with historical data, the curve is fit to the historical data and a projected point in the future according to the selected decarbonization scenario. A similar approach is taken for locations which only have a single-year data point, fitting the curve between two points. In locations with no initial grid factor data, users may enter the initial year and the factor.