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Methodology Scenario Design Cross-Cutting Data Other Relevant Research

Methodology

Global Change Analysis Model (GCAM-CGS)

Our analysis uses the Global Change Analysis Model (GCAM), a global market equilibrium model that combines economic, energy, land use, and climate systems to analyze the interactions between human activities and global environmental changes. It is an open-source community model developed over 40 years and maintained at PNNL/JGCRI (College Park, MD). The download link and documentation is available at: http://jgcri.github.io/gcam-doc/toc.html.

 

 

Other open source tools used in this analysis
 
  • gcamreport: tool for processing scenario output from the GCAM model into a dataset aligned with Integrated Assessment Modeling Consortium (IAMC) standards. Additional information is available at: https://github.com/bc3LC/gcamreport
  • rhistiamc: tool for aggregating and processing historical reference data into the IAMC format for comparison with GCAM (or other IAM) scenario output. Additional information is available at: https://github.com/umd-cgs/rhistiamc 
     

Data Use

Our analysis uses 100 year global warming potentials (GWP) from IPCC’s fourth assessment report (AR4), and for historical data uses the country-reported dataset from PRIMAP-hist (Gütschow et al. 2025). For electricity emissions, the historical data from EMBER is an estimate for total greenhouse gas (GHG) emissions, whereas scenario data includes only CO2 emissions, which explains part of the discrepancies in Figure 1 of many country pages.

 

For sectoral disaggregation of emissions, we use the differentiation into the four major gases, as well as separating the Land Use, Land Use Change and Forestry (LULUCF) and electricity CO2 emissions in figures 1, and in the text furthermore discuss the largest ‘sectors’ of greenhouse gases between the following: Energy supply / Electricity CO2, Industry CO2, Buildings CO2 (Residential and Commercial), Transport CO2, LULUCF CO2, total CH4, total N2O and F-Gases. This harmonized set of ‘sectoral’ contributors is chosen to provide meaningful disaggregation of total greenhouse gas emissions for all countries that is common across countries (while for specific countries a different disaggregation could have advantages, e.g. further disaggregating methane emissions into sectors for countries with large methane contributions.)
 

Scenarios Design

The high-ambition scenarios for most countries are developed based on the Net Zero 2050 (or 1.5°C) scenario using GCAM from NGFS 2024, with additional country-specific adjustments made in cases where particular model dynamics like electricity demand projections appear implausible based on latest data.

 

The Net Zero 2050 scenario has a 50% chance of limiting average global warming to below 1.5°C by 2100, with an overshoot likely occurring around mid-century. Global CO2 emissions reach or approach zero in 2050, and countries with a political commitment to a net zero target meet the target in their respective target year (2050, 2060, or 2070). Some jurisdictions, such as the US, EU, UK, Canada, Australia, and Japan, reach net zero for all GHGs. Australia and the EU are not standalone regions in GCAM; therefore we use downscaled scenario results for modeling from the Australia_NZ and EU_12, EU_15 and Europe_Non_EU regions, respectively.

 

A different set of scenarios with detailed sectoral policy modeling are used for some countries. Additional bespoke scenarios are developed using GCAM-CGS for China, Indonesia, US and Canada. Both high ambition and current policies scenarios are developed for China, US and Canada using the latest available policy information. 
 

Cross-Cutting Data

Relevant Research

 

Global

 

Australia

 

Brazil

 

Canada

 

China

 

EU

 

India


Indonesia

 

Japan

 

ROK

 

Mexico

 

South Africa

 

USA