1995-2100 projections of 12 greenhouse gas and pollutant emissions at 5-year intervals on a 1-degree latitude-longitude grid. The dataset contains three internally consistent scenarios (low, reference, high) generated by the MIT Emissions Prediction and Policy Analysis (EPPA) model using a Monte Carlo analysis of 10,000 runs. Scenarios were selected based on the 2.5, 50, and 97.5 percentile values for CO2 emissions in 2100.
Use Cases
- Compare low, reference, and high scenario trajectories for CO2, CH4, and N2O emissions across the 1-degree grid to assess climate policy risks.
- Analyze spatial correlations between CO2 emissions and co-emitted substances like SOx, NOx, and NMVOC under conditioned probability scenarios.
- Use the 1995-2100 time-series of HFC, PFC, and SF6 emissions to project long-term impacts on atmospheric radiative forcing.
- Validate other downscaled emission datasets using the MIT EPPA model's population-weighted regional aggregation methodology.
- Study the impact of land use change and agriculture on carbonaceous particulate emissions, excluding natural sinks and forest regrowth.
Strengths
- Provides three probability-weighted scenarios (2.5, 50, 97.5 percentile) for 12 distinct substances, enabling uncertainty analysis.
- Spatially explicit data on a global 1-degree by 1-degree grid from 1995 to 2100 at consistent 5-year intervals.
- Scenarios are internally consistent, derived from 10,000 Monte Carlo runs of the MIT EPPA model.
Limitations
- Excludes emissions from natural sources and sinks, as well as carbon uptake from forest regrowth, limiting completeness for full carbon cycle analysis.
- Uncertainty in emissions is included for the base year 1995, which may propagate and affect long-term projection accuracy.
- The dataset's future projection end date (2100) implies it is not suitable for analyzing observed historical trends beyond its model base year.
Provenance
- Source
- Massachusetts Institute of Technology (MIT) Joint Program on the Science and Policy of Global Change, via NASA Earthdata.
- Collection Method
- Generated using the MIT Emissions Prediction and Policy Analysis (EPPA) model and the deterministic equivalent modeling method (DEMM), downscaled from aggregated regions using population weights.
- Time Range
- 1995 to 2100
- Freshness
- null
- Geography
- Global, on a 1-degree by 1-degree latitude-longitude grid.