Accuracy first: a new approach to avoided emissions  

As the world races to combat climate change, renewables must be a vital part of global decarbonisation strategies. Inflated estimates for avoided emissions can mislead policymakers and corporate leaders into dialling back their decarbonisation ambitions when more action is needed. 

Wind turbines, solar panels, and other renewable energy sources are replacing fossil fuels. This leads to significant reductions in greenhouse gas emissions. But are all renewables really replacing fossil fuel-based electricity generation? What about renewables replacing other renewables? And what about increasing electricity demand? 

Our latest white paper introduces a new methodology that challenges conventional assumptions, leading to a more accurate quantification of the emissions avoided by renewables. 

Why avoided emissions matter 

Avoided emissions quantify the environmental benefits of a solution, such as renewable energy, by comparing its impact to a hypothetical reference scenario. That’s normally something like “business as usual”.  

Unlike a company’s carbon footprint, which measures its environmental burden, avoided emissions highlight a solution’s positive contribution to decarbonisation. 

Being able to accurately quantify avoided emissions is critical for several reasons:

Trusted carbon credits: If avoided emissions are sold as carbon credits, trustworthy calculations ensure that buyers and sellers make fair and impactful exchanges.

Informed decision-making: It allows for a fair comparison and ensures scaling of the most impactful solutions.

Policy decisions: Governments can leverage avoided emissions data to shape energy policies. They can also allocate resources where they will have the greatest impact.

However, existing methodologies for calculating avoided emissions often fall short, leaving decision-makers with an incomplete or overly optimistic picture.

The problem with conventional approaches 

Traditional methods for estimating avoided emissions from renewables rely on simplistic assumptions: 

Ignoring repowering: When renewables replace older renewable energy sources rather than fossil fuels, no emissions are avoided compared to the status quo. On the contrary, the required installation and recycling processes cause additional emissions. 

Neglecting growing energy demand: As electricity demand increases, some of the energy generated by renewables serves growing demand rather than replacing fossil fuels. This rebound effect reduces the absolute emissions avoided.

Zero-emission renewables: Renewables such as wind, solar, geothermal, hydro, bioenergy, etc., are usually assumed to have zero emissions per kilowatt-hour. In fact, they have a small but non-zero carbon footprint. Taking it into account allows for differentiating between various renewable energy sources. 

How to introduce more integrity in your avoided emissions reporting? 

Hexagon’s white paper introduces a four-step methodology that addresses the described limitations of conventional approaches. By incorporating repowering, growing energy demand, and the carbon intensity of renewables, this method provides a more realistic framework for quantifying avoided emissions. 

Step 1: The first step calculates the annual energy generated by newly installed renewable capacity. If precise data is unavailable, we can use country averages as a proxy. 

Step 2: Split the generated electricity into two parts based on a country’s energy mix, its year-over-year changes, and average power plant lifetimes by energy source: 

• Replacing Existing Demand (RED): The energy that replaces existing power plants reaching their end-of-life. 
• Serving New Demand (SND): The energy that exceeds past electricity generation. 

Step 3: In a third step, the carbon intensity of both RED and SND is determined – what are the emissions associated with generating one kilowatt-hour of RED and SND, respectively? 

Step 4: Finally, avoided emissions are estimated, taking into account renewables’ small but non-zero carbon intensity.  

Differentiating between RED and SND allows us to distinguish between a real reduction in emissions (avoided emissions from RED) and a lesser increase in emissions (avoided emissions from SND). 

Why greater accuracy matters 

Hexagon’s methodology for measuring avoided emissions offers a more realistic and reliable approach. It reflects the fact that, in most countries, newly added energy sources are cleaner than the existing grid. It also accounts for the longer lifespan of fossil power plants compared to renewables. This means new wind and solar installations often replace other renewables rather than fossil fuels.  

By assigning non-zero emissions to renewables, the method allows for meaningful comparisons between different technologies. It also considers rebound effects, helping to distinguish between genuine reductions in emissions and slower rates of increase. This results in a more accurate estimate. Corporate leaders, policymakers and carbon credit buyers can rely on the data to make confident decisions. 

The result? An accurate estimation of avoided emissions that empowers decision-makers with trustworthy data. Whether you’re a corporate leader, a politician, or a carbon credit buyer, your decisions are only as good as the data quality they’re based on.