How to Measure GHG Emissions

Electric grids are enormously complex, but when it comes to how to measure GHG emissions, we can break things down into three key types of emissions calculations – grid average emissions, marginal emissions, and residual mix grid emissions – to help us understand the environmental impact of electricity use. In this article, we’ll explain those concepts, some pros and cons of each, and explore when an organization might want to use them to measure its emissions.

Grid Average Emissions

Grid average emissions is the most general option for how to measure GHG emissions that tells us the average amount of greenhouse gases released to produce a unit of electricity (MWh) across an entire electric grid.

For instance, let’s say there’s a (tiny) grid with 100 MWh of load consumption for an hour of operation. To keep it simple, we’ll say 50 MWh of the generation is from renewables (wind and solar) and 50 MWh of the generation is from natural gas generators.

To calculate the grid average emissions, our equation would look like this:

50 MWh renewables x 0 kg CO₂/MWh (carbon-free renewables have zero emissions intensity) = 0 kg CO₂

50 MWh natural gas x 450 kg CO₂/MWh (EPA’s average emissions intensity of natural gas) = 22,500 kg CO₂

Grid average emissions factor = total CO₂ emissions / total electricity generated

So

22,500 kg CO2 / 100 MWh = 225 kg CO₂/MWh

Based on this calculation, the grid average emissions intensity is 225 kg CO2/MWh.[1]

Grid average emissions consider all the different sources of electricity, from coal plants to wind turbines. The greater the amount of renewable energy generation on a grid, the lower the grid average emissions will be. (The EPA’s Emissions & Generation Resource Integrated Database (eGRID) provides comprehensive data on U.S. electric power generation attributes.)

There are benefits to using grid average emissions when planning a clean energy strategy, particularly for organizations beginning their clean energy journey:

• Grid average emissions data is easily calculated, readily available and regularly updated, so it’s easy to access.
• It also provides a standardized benchmark for comparison with other companies or industry averages.

However, there are also some significant drawbacks:

• Grid average emissions do not reflect the marginal impact of a company’s energy consumption. For instance, if a company uses more energy at peak times when the marginal unit has greater carbon intensity, its actual emissions impact will be higher than the grid average suggests.
• For this reason, average emissions understate the decarbonization impacts of flexible loads or storage resources (e.g., shifting electricity use to cleaner times of the day when consumption would have less impact).

Should I Use Grid Average Emissions Calculations?

Grid average emissions are the most convenient measurement, which is why they have been used as the basis for how to measure GHG emissions and voluntary standards like the Greenhouse Gas Protocol (GHGP) and Science-based Targets Initiative (SBTi) (although that may change when the GHGP finalizes updates to its scope 2 guidance in 2026). For companies just beginning their clean energy journey, using grid average emissions offers an accessible entry point for carbon accounting. It enables simple benchmarking of a company’s baseline emissions and can be helpful as companies plan their overall decarbonization roadmap.

Marginal Emissions

Marginal emissions measure the impact of adding one more unit of electricity consumption to the grid. Typically, this additional demand is met by the power plants that can ramp up production, which is often a fossil fuel-powered resource.

For companies looking to maximize their carbon reduction efforts, a marginal emissions approach offers meaningful benefits:

• Marginal emissions calculations provide a more accurate reflection of the environmental impact of each additional MWh of electricity consumed, especially for decisions on when to use energy-intensive processes. (This 2023 paper, from Tabors, Caramanis, Rudkevich, provides an in-depth explanation of why companies should use the marginal emissions metric for greater transparency in carbon accounting.)
• Marginal emissions also provide a more accurate signal for the impact of modifying operations in real-time.

The drawbacks mostly revolve around complexity and potential difficulty executing this approach:

• Determining marginal emissions is complex and requires detailed data on grid operations and the mix of generating resources that vary in real-time. Accessing real-time or near-real-time data on marginal emissions can be difficult, as it may not be readily available or transparent from all grid operators.
• Marginal emissions are more volatile than grid average emissions from day to day and hour to hour, especially with increasing levels of renewables, making it challenging to establish a clear and consistent carbon footprint over time for planning purposes.

Should I Use Marginal Emissions Calculations?

By digging deeper into more dynamic data, companies can maximize their environmental impact and align operations with precise grid cleanliness. Marginal emissions data can provide greater insight into a company’s real-time impact, particularly if it’s using advanced, dispatchable technology (e.g., flexible loads and/or energy storage). But marginal emissions measurement requires sophisticated data analysis and is more challenging to implement than using average emissions data. When it comes to how to measure GHG emissions, marginal emissions calculations are a tool that requires a solid foundation of data and strategic capability to be used effectively.

While valuable for measuring real-time impact, marginal emissions may not be the appropriate measure for planning purposes. For many grids, particularly those with lower levels of renewable penetration, the long-term marginal unit is a natural gas generator. A forecast of marginal emissions factors will show little differentiation between wind and solar, which may disincentivize building a balanced resource portfolio and potentially lead to over-indexing on one technology.

Residual Mix Grid Emissions

Residual mix grid emissions refer to the emissions of a grid if you remove any specifically claimed voluntary clean energy procurement. The point of this calculation is to avoid double counting someone else’s voluntary procurement of clean energy.

Let’s continue our example of a grid with 100 MWh of load consumption, with 50 MWh from renewables and 50 MWh from natural gas generators. However, now we’ll assume that 25 MWh of the 50 MWh of renewables came from voluntary corporate procurement.

The residual mix calculation omits the 25 MWh of corporate procurement from the grid’s total generation. That leaves us with only 25 MWh of renewables for our grid emissions calculation:

25 MWh renewables x 0 kg CO₂/MWh

50 MWh natural gas x 450 kg CO₂/MWh = 22,500 kg CO₂

Total CO₂ emissions / total electricity generated (without the 25 MWh of voluntary procurement)

So

22,500 kg CO₂ / 75 MWh = 300 kg CO₂/MWh

Based on this calculation, the residual mix grid emissions intensity is 300 kg CO2/MWh.

As we can see, removing other companies’ voluntary procurement from our calculation raises the number of residual emissions for other companies. (In late 2023, the Center for Resource Solutions published this methodology for calculating residual mix emissions rates.)

As with the other accounting methods, there are benefits and drawbacks to using residual grid emissions. Benefits include:

• Residual grid mix emissions more accurately reflect the carbon intensity of purchased electricity (particularly in markets where renewable energy is actively traded).
• Using this calculation prevents double counting of environmental claims.

Some drawbacks include:

• Residual grid mix emissions calculations require accurate data collection, including detailed knowledge of the grid’s overall energy mix and specific renewable energy procurements made by other organizations.
• They are difficult to forecast because they depend on assumptions of voluntary procurement of environmental attribute credits from existing and new clean resources.

Should I Use Residual Mix Emissions Calculations?

The residual grid emissions metric provides the most transparent accounting of a grid’s emissions intensity because it strips out other companies’ clean energy activities, thus avoiding the double counting of renewables that’s embedded in grid average emissions. In essence, it prevents companies from claiming the environmental benefits from other organizations’ voluntary investments in clean energy. However, this measurement also requires the most data, not only from the grid operator and your company, but from other companies on their clean energy investments. The EU currently has more robust data on this than the U.S.

It’s worth noting that if the U.S. moves toward a residual emissions accounting system (e.g., in the upcoming GHG Protocol scope 2 updates), we can expect to see companies’ carbon emissions calculations increase because they will no longer be double counting other companies’ carbon-free energy investments. However, residual grid mix is a difficult metric to use for planning purposes as the measure is dependent on voluntary procurement activities.

Understand the Differences When Deciding How to Measure GHG Emissions

In a nutshell, the grid average emissions metric is the most used metric today, is the easiest to calculate, and gives us a high-level picture of a company’s emissions. The marginal emissions metric requires more sophisticated methodologies but provides greater insight into the real-time impact of a company modifying its electricity use. And the residual emissions metric requires additional data on voluntary procurement but provides a more accurate measure of a company’s carbon footprint when consuming energy from the grid. Understanding these distinctions can help organizations plan more effectively to reduce their environmental impact and get ahead of potential future voluntary and regulatory changes.

[1] This and other calculations in this article are simplified examples meant to provide a basic understanding of how mixed energy sources impact average and residual grid emissions. They do not consider real-world variables such as varying load factors, operational hours, etc.