Case study: Automotive Disclosure but not Transparency

Nov 28, 2022
cars in a line

The Automotive sector is currently failing at transparency. On the surface, the situation looks reasonable: 89% Scope 1-2 disclosure rate and 78% dominant Scope 3 (Category 11) disclosure. However, keystone metric disclosure rate is a meagre 11%. Beneath the surface there are three elemental problems that require attention.

Forgetting something?

The keystone metric of the Automotive sector is ‘well-to-wheel’ gCO2e per lifetime km. Well-to-wheel (WTW) incorporates the upstream supply chain emissions embodied by a vehicle, also known as ‘well-to-tank’ (WWT), in addition to the vehicles’ usephase emissions, referred to as ‘tank-to-wheel’ (TTW) or tailpipe emissions. It is important to include upstream emissions because this figure varies significantly between vehicle power-train.

It’s not asking for the World

The keystone metric should also represent all of a company’s sector activities. However, many manufacturers disclose data at the regional level only. Global companies are subject to different requirements on testing and calculating vehicle emissions for each regulatory jurisdiction. Manufacturers who feel their geographical distribution of vehicle sales puts them at a disadvantage compared with their peers, may be reluctant to consolidate their measurements. In addition to this, there is a lack of standardization over how the metric is calculated which can demotivate companies to report.

Our figures show a 72% disclosure rate for regional vehicle emissions intensity data yet only 11% for global vehicle emissions intensity. We recognise that regional data is still useful so companies receive a partial score for disclosing it.

No standard method

There is a failure in current methodology that prevents comparability between automakers. Outside of regulation, companies have full discretion over highly sensitive calculation variables, such as vehicle lifetime and annual mileage. This can prevent comparability and produce appreciably different results between similar companies.

Take BMW and Mercedes: two close competitors with very remote assumptions about their products. To calculate the keystone’s denominator they estimate how many years their cars live and how far they’re driven each year. Put in another way:

Lifetime mileage = Lifetime in years x Annual mileage

According to CDP data, BMW assumes a lifetime of 15 years at 10,000 km per year whereas Mercedes flip this around and assume 10 years at 20,000 km per year. This gives a lifetime mileage of 150,000 to BMW and 200,000 km to Mercedes. Average vehicle emissions intensity in the EU is remarkably similar between the two: 116 gCO2/km for BMW and 115 gCO2/km for Mercedes. This means that for every car sold in the EU, Mercedes Scope 3 emission is 34% higher than that of BMW, despite having the same intensity.

With the final release in 2015 of the Worldwide Harmonised Light Vehicle Test Procedure (WLTP), progress at least for measuring tailpipe emissions has been made, and companies such as BMW and Volkswagen refer to the WLTP in their reporting. But without a similar standard for Scope 3 product lifetime emissions intensity, and mechanism for its adoption, companies are free to manipulate key variables in their favour.

While this example cannot confirm manipulation has taken place, it does confirm that crucial variables are treated crudely, based on highly inconsistent and manipulatable assumptions, and any serious attempt to estimate them has not been made.