investment viewpoints

Climate bonds: assessing avoided emissions

Climate bonds: assessing avoided emissions
Christopher Kaminker, PhD - Group Head of Sustainable Investment Research, Strategy & Stewardship

Christopher Kaminker, PhD

Group Head of Sustainable Investment Research, Strategy & Stewardship
Thomas Höhne-Sparborth, PhD - Head of Sustainability Research

Thomas Höhne-Sparborth, PhD

Head of Sustainability Research
Erika Karolina Wranegard - Portfolio Manager, Fixed Income

Erika Karolina Wranegard

Portfolio Manager, Fixed Income

Assessing the carbon profile of projects funded by our Global Climate Bond strategy is crucial to determining the climate mitigation potential of our investments. As carbon is the ‘currency’ of climate change, our independent analysis is aimed at mitigating the lack of harmonisation and different degrees of sophistication characterising issuers’ reporting on avoided greenhouse gas (GHG) emissions.

The Carbon Yield® methodology1 quantifies one of the environmental impacts of the strategy in terms of greenhouse gas (GHG) emissions avoided through financed activities per USD invested. The methodology estimates the difference between:

  • The carbon footprint of the funded projects
  • The GHG emissions that would have occurred under a reasonable baseline scenario if those projects had not been implemented

 

Figure 1. The Carbon Yield® method to quantify avoided GHG emissions

GCB-report-2020-carbon-yield-method.png

Source: AIM, LOIM. For illustrative purposes only.

 

The difference represents the emissions that are potentially avoided by a given project2. Individual bond avoided emissions figures are aggregated to determine the portfolio–weighted GHG emissions avoided per unit of capital invested, ie the Carbon Yield®. The results of the funded projects’ GHG analysis in 2020 are summarised in figure 2. Through its 2020 holdings, the strategy avoided 126,622tCO2e due to the projects funded. This equates to a significant 70% GHG emissions savings.

 

Figure 2. Avoided emissions: 70% GHG emissions savings

                  CARBON YIELDCarbon-Yield-Methodology-1.png

                  GCB---CO2.jpg

268tCO2e / USDm per annum

 

Equivalent to 0.27tCO2e avoided per USD1,000 per annum.
Coverage ratio of 56% of 2020 average portfolio holding.

GCB---house.jpg

 

GCB---car.jpg

Equivalent to the emissions resulting from the average annual electricity consumption of 300 households in the United Kingdom.

 

Equivalent to the emissions resulting from over 1 million km driven by an average passenger vehicle in the United States.

 

This equates to 70% GHG emissions savings.

This represents the percentage difference between the footprint of the average baseline project and the footprint of the average funded project.

Calculations are based on project-level scope 1 & 2 emissions.

126,622tCO2 e avoided per year due to the projects funded by the bonds held.

Calculations are based on the International Energy Agency’s (IEA’s) Stated Policies Scenario (STEPs).

Calculations are based on project-level scope 1 & 2 emissions.

Scope 1 & 2

emissions 53,631 tCO2e

Estimated to arise from the operations of the funded projects.

Scope 1, 2 & 3

emissions 69,710 tCO2e

Estimated to arise when the construction and material use of the funded projects is also accounted for.

Source: AIM, LOIM. For illustrative purposes only.

 

Renewables: setting dynamic baselines

This year’s Impact Report differs from previous years in setting a dynamic baseline for avoided emissions in the renewables sector. While the change may result in lower estimated GHG emissions savings, it is the result of a more robust and conservative baseline-setting exercise that reflects our commitment to reporting impact using the best practice available.

In previous years, AIM conducted the analysis by assuming a static, business-as-usual scenario that implied the use of a ‘status quo’ baseline over the lifetime of a given funded project.  For renewable energy projects in 2020, the decision was made to replace business-as-usual baselines with dynamic baselines that take into consideration future changes in the composition of electricity grids across the globe, and consequent changes in their emission intensity, under rigorous scenarios.

For a renewable energy power-generating asset, avoided emissions are represented by the GHG emissions savings that are potentially enabled by the substitution of grid electricity (baseline scenario) with electricity from renewable sources generated through the funded project.

The generation mix of electricity grids across the globe has changed considerably in recent years. Figure 3 shows the recent development of grid emission factors in the United States and the European Union as well as future estimated emission factors derived from IEA projections under different scenarios as defined in the 2020 World Energy Outlook (WEO)3. Both grids, to different extents, have undergone substantial decarbonisation paths. This global trend is then projected to be reinforced by the increased ambition of climate policies, technology progress and market development that will lead to a larger uptake of renewables and lesser reliance on fossil fuels.

 

Figure 3. Carbon intensity of the electricity grid in the US and EU 

 

GCB-report-2020-carbon-intensity.png

Source: LOIM, AIM elaboration based on EIA and EEA (historical data) and IEA 2020 WEO (future projections). For illustrative purposes only.4

 

In light of the above, AIM deemed that static, business-as-usual baselines—i.e. point-in-time grid emission factors—should be replaced with emission factors reflecting the expected evolution of the energy mix during a given project’s lifetime. 

For 2020, the dynamic baselines were based on the IEA’s Stated Policies Scenario (STEPS)5. The STEPS scenario "reflects the impact of existing policy frameworks and today’s announced policy intentions". In addition, the same analysis was undertaken using the IEA’s Sustainable Development Scenario (SDS)6 as a baseline, reflecting the development of a Paris-aligned electricity mix. Both baselines were normalised figures of the expected grid composition during a project’s lifetime.

Overall, this methodological development for calculating the avoided emissions of renewable energy projects is in line with our commitment to best-practice impact reporting, even when upgraded methodologies may, at first glance, shed an unfavourable light on the impact achieved by our investments, such as their potential for climate-change mitigation.

In future, we will consider extending this scenario-based approach to other green project categories.

Please click here  to read the full impact report.

 

Sources

1 The Carbon Yield® methodology was jointly developed by Lion’s Head Global Partners, ISS ESG and Affirmative Investment Management (AIM), with funding by the Rockefeller Foundation.
2 Avoided emissions are calculated by deducting a project’s Scope 1 & 2 emissions from the Scope 1 & 2 emissions that would occur under a reasonable baseline scenario if that project had not been implemented. Scope 1 & 2 emissions are the project’s operational emissions. We also estimate emissions from construction and material use—ie among the most material emissions categories of a project value chain (Scope 3). However, because of disclosure gaps and related complex assumptions, avoided emissions are currently not adjusted for the funded projects’ construction phase GHG emissions.
3 IEA (2020), World Energy Outlook 2020, IEA, Paris https://www.iea.org/reports/world-energy-outlook-2020
4 Both historical and projected electricity grid carbon intensities presented in the graph were derived based on data on electricity generation and emissions from the electricity generation sector in the US and the EU. The use of multiple sources implied differences eg in the definition of the electricity sector perimeter. Moreover, projected carbon intensities have been linearly extrapolated based on IEA data for 2025, 2030 and 2040. The data presented in the graph may differ from the emission factors used in the funded projects’ GHG analysis.

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