Understanding what these proposals could mean for curbing global climate change first requires knowing where the world’s emissions are currently heading in the absence of new policies, as well as what levels they may reach with additional policy action.
The CAIT Projections module, released in a beta version today, provides access to emissions projections for major emitters through the year 2100.
The scenarios included in the beta version factor in existing mitigation measures, and the tool provides both quantitative figures and information about the assumptions that define each scenario. These assumptions are based on the Greenhouse Gas Protocol Mitigation Goals Standard and help users understand the key information that underpin each scenario. By looking at this information, policymakers, researchers and others can get a sense of countries’ possible emissions trajectories, which can ultimately help inform decision-making.
Future Emissions in China, India and the United States
The CAIT Projections module pulls in data for 17 major emitters, as published by governments and independent organizations, so multiple scenarios—as well as their underlying assumptions—are available for most countries.
For example, consider some scenarios of China’s carbon dioxide emissions from fossil fuel consumption:
The graph shows us three different pathways, published by the International Energy Agency (IEA), U.S. Energy Information Administration (EIA), and the Chinese government. All three scenarios show the trajectory of emissions if the country takes no additional emissions-reduction actions. They have a wide range: IEA estimates 12.9 GtCO₂ in 2040 — 57 percent higher than their number in 2012—while EIA estimates 14.9 GtCO₂ in 2040, 66 percent higher than their 2012 number.
So what are the reasons for these disparities? Table 1 shows some of the different assumptions for these scenarios. Obvious variations are present in population (slightly larger in the IEA’s scenario) and GDP growth rates (largest in the national government scenario). In addition, the timeframe and year in which the scenario starts are also different for each published scenario. These differences in underlying assumptions impact the way projected emissions are calculated, so it’s important that they’re communicated transparently. For more details, see EIA’s own comparative analysis of their Reference Case with IEA’s Current Policies scenario.
Table 1: Selected projection assumptions for China
The graph above shows U.S. emission projections supplied by the U.S. government, the Potsdam Institute for Climate Impact Research (PIK) and the Netherlands Environmental Assessment Agency (PBL)1. The U.S. government estimates2 that emissions are projected to rise again from 2015-2030 after a decrease from 2005-2015. However, the other two projections both see the United States reducing its emissions through 2030.
Table 2 shows a comparison of the assumptions published in the CAIT Projections module. A major difference is that the PBL and PIK scenarios assume a set of policies are implemented through 2020, while the government projection assumes no new mitigation policies after September 2012. We can also see that the numbers between 2005 and 2010 are actually different between the projections, even though this data is in the past. Information in CAIT shows us that the U.S. government’s projection timeframe starts at 2015, while PIK’s and PBL’s start a decade earlier, at 2005.
Table 2: Selected projection assumptions for the U.S.
With Measures scenario takes into account only those policies adopted before September 2012 (i.e., not the President's Climate Action
RefPol is the linient (weak) climate policy reference case which takes up existing commitments and pledges mostly specified until 2020 and
extrapolates the level of stringency reflected in the commitments until the end of the century.
For India, the scenarios presented show a wide range of emissions pathways. The Indian government’s emissions projection in 2030 is higher than IEA’s and nearly double that of EIA’s 2030 projection.
Table 3 shows us that the national projections use a higher economic growth rate than both the EIA and IEA projections. While all scenarios factor in existing policies or laws, the specific policy assumptions—like the specific implementation of existing climate policies —are not always readily available, often making differences hard to explain. This affirms that it is essential for researchers to transparently publish scenario assumptions, and for the audience to only use these numbers with a cautious understanding of the underlying assumptions.
Table 3: Selected projection assumptions for India
As shown in the examples above, the CAIT Projections module can help users better understand and analyze emissions projections for a variety of objectives. In particular:
National governments can compare projections more easily and use them to inform mitigation actions and policies;
Analysts can access all data and use it for INDC assessment; and
Researchers can increase transparency by providing missing information.
Countries have the potential to significantly contribute to the reduction of global emissions through their INDCs. Understanding where their emissions are heading, and how new policies can help to reduce them in the future, is a critical step in creating efficient national climate action plans.
PBL and PIK GHG Emissions projections are converted by WRI from per gas emissions reported in the LIMITS Scenario Database using AR4 100yr-GWP values ↩︎
United States reported Forestry and Land Use emissions under both high sequestration and low sequestration conditions in its First Biennial Report, only high sequestration is reported here. ↩︎