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Improving the accuracy of the GHG protocol in time and space

A survey on the need for updating the Greenhouse Gas (GHG) Protocol standards recently closed. Having been in existence since 2004 (with scope 2 and scope 3 guidance published in 2015 and 2013), it is a good time to consider changes.

Over the last few years, there has been a surge in interest in reporting accurate GHG figures. Many companies now report annually, either voluntarily or because they are large enough to be required by laws. The GHG protocol is the standard for these reports, even if they often are published in annoying formats (glossy PDFs).

In IT, transparency has also been improving. A year ago, AWS released its carbon calculator to bring it up to a similar level as Google and Microsoft. There have been some recent comments about AWS defunding their sustainability initiatives, but you can now at least get emissions numbers based on your cloud carbon footprint.

Unfortunately, the calculations are not all equal. Google is the most transparent with its methodology. AWS is the least - they give you a number, but the documentation is limited. This makes it impossible to compare between providers, but even within a single provider there insufficient detail to properly link energy generation with usage.

An 18th century painting of an electricity grid with gases coming out of the
Generated by DALL-E 2 (“an 18th century painting of an electricity grid with gases coming out of the trees”)

Can this be addressed with updates to the GHG protocol? Google published their submission to the GHG Protocol survey, and it’s a point they highlighted as a priority for change:

Under current GHGP methodologies, the actions that are credited as emissions reductions within companies’ inventories do not align sufficiently with the real-world GHG impact of those actions. Company strategies and actions that differ widely in effectiveness, both in their impact on a company’s own GHG footprint and on broader energy and economic systems, are in many cases credited equally…The updated GHGP should remedy this by more closely aligning credit for GHG reductions with real and measurable impacts of company actions.

Reporting also still requires lengthy analysis, often involving expensive consulting projects. It is very difficult to get data, particularly if you are a small business. The near real-time reporting we’re used to in finance is not yet possible in carbon accounting, although the cloud providers do a good job of updating their calculations frequently. Google is the best at this (every month), AWS the worst (3 months lag). This is going to be important for proper scope 3 reporting so that direct (scope 1 and scope 2) emissions figures can be reported through the supply chain.

Improving the granularity of electricity emissions data will help here, not least for serving as an input for temporal and spatial load shifting. This is important to be able to link clean energy generation to demand, says Google:

Under today’s GHGP guidance, geographic boundaries for scope 2 do not correspond to the physical markets where a company consumes electricity. A company can purchase Energy Attribute Certificates (EACs) far from where it consumes electricity, because the electricity represented by EACs is not required to be deliverable to the grid(s) where the company operates. Thus, EACs that are physically disconnected from underlying electricity consumption function effectively as offsets: they are reductions claimed elsewhere to compensate for a company’s electricity based emissions. This approach has become widespread in practice under today’s scope 2 guidance, despite the scope 2 standard ostensibly prohibiting the use of offsets to reduce a company’s emissions.

This is a limitation with how instruments like RECs are accounted for. There’s a disconnect between the grid mix at the time of use and using products like RECs to mitigate emissions. It’s why unbundled RECs are so cheap and are ineffective at achieving anything:

The Residual Mix of electricity from the grid is defined as the leftover once the consumed GOs are taken out from the total production mix. The basic idea is that companies (and consumers) that do not purchase the GOs or RECs, get this Residual Mix from the grid. However, the calculation of the Residual Mix in a country is still highly inaccurate. The reason for this inaccuracy is that there is a time delay between the trading of electricity and the trading of the corresponding RECs and GOs. The RECs and GOs are created in the month after the month of the production, or later, and the trading has a maximum delay of 1 year for GOs, and 21 month for RECs. It is mathematically not correct to subtract data from those two different trading systems, because Solar and Wind power have heavy fluctuating production characteristics, and the unbundled hydropower GOs are issued irregularly. Concluding: the Residual Mix should not be used in LCA.1

Such distortions show up in things like Norway’s emissions factors which are 10 kg CO2/MWh on a grid-level, but 402 kg CO2/MWh on a residual basis because most of the clean energy credits produced in Norway are actually sold and claimed outside of the region2. If these are then used to produce claims of 100% renewable energy on an annual basis, the emissions reductions can be overstated by as much as 50%3. If you see anyone making such claims, the only safe assumption is that they are bogus.

One of my first peer-reviewed articles was on this topic back in 2020 where I analyzed the suitability of the GHG Protocol for calculating cloud carbon emissions. The cloud providers subsequently made this a lot easier through their cloud carbon calculator products. That was the first step - getting a number.

Now the GHG Protocol needs to evolve to better represent the complexity of how energy markets work, how companies respond to incentives to get to net zero, and how that flows through supply chains to ensure all organizations can produce accurate emissions inventories.