What corporations aren't disclosing about their CO2 emissions
A new paper reveals how companies frequently under-report Scope 3 emissions by focusing on insignificant categories.
A new paper reveals how companies frequently under-report Scope 3 emissions by focusing on insignificant categories.
A new study estimates most corporations are not reporting the full scope of their carbon footprint, with many claiming to be ‘green’ despite a lack of reporting on Scope 3 key categories.
Scope 3 emissions are the emissions upstream and downstream of companies’ operations. They include 15 categories, from business travel to product use. For example, when someone uses products that emit carbon, like driving a car or burning gas at home, those emissions are attributed to car companies’ or gas companies’ Scope 3 emissions.
The latest research, published last week in PLOS Climate, is an industry-university collaboration between climate risk analysis firm (EMMI) and researchers at UNSW Sydney, Griffith University and the University of Otago.
“By analysing reported emissions from over 1200 companies, we found most companies are under-reporting their Scope 3 emissions by up to 44 per cent,” says Dr Ben McNeil, an Adjunct Fellow at the UNSW Climate Change Research Centre and co-founder of EMMI.
“This is because companies typically focus on emission categories that don’t generate huge amounts of emissions, like business travel, while avoiding the carbon emissions involved in carbon intensive categories like 'product use'.”
These results reveal that the majority of Scope 3 emissions disclosed from companies are not captured and are too low.
Finance and Economics Professor Ivan Diaz-Rainey, a leading international expert in climate and sustainable finance from Griffith University, says firms were being strategic in their Scope 3 reporting, and this could underpin greenwashing.
“Scope 3 emissions account for the highest proportion of total emissions, and it’s the least likely scope to be reported on,” says Professor Diaz-Rainey.
"Scope 3 emissions often dominate a company's total carbon footprint, particularly for financial institutions, energy, utilities, mining and materials companies,” Dr McNeil says.
“The problem is that Scope 3 is difficult to quantify but critical to understanding how companies are financially exposed to carbon pricing as markets shift away from carbon-intensive products. This research aims to better understand and predict emissions – including Scope 3 – to give greater coverage and accuracy for investors.”
Though CO2 reporting is currently voluntary for most firms, corporations are under pressure from investors, regulators, politicians, non-profit organisations and other stakeholders to disclose and reduce greenhouse gas emissions (GHG).
The standard for greenhouse gas accounting, the Greenhouse Gas Protocol, is used worldwide to measure a company’s total carbon footprint with three levels of reporting.
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“Companies have a great incentive to better their scope 1 and 2 emissions because direct energy efficiency leads to financial savings,” says Prof. Diaz-Rainey. “An oil and gas firm may pump oil out of the ground and in doing so, may use vehicles and electricity, but what really counts in terms of the impact of an oil and gas firm is how the end users are emitting GHG as a result of purchasing the firm’s product.
“For the oil and gas firm, the Scope 3 emissions are emitted by people who purchase the oil and use it in their cars to drive around or take a flight. If an oil and gas firm only report on Scope 1 and 2, we are missing most of the story.”
In this study, researchers used machine learning to improve the prediction of corporate carbon footprints, which provided an indication of where policymakers and regulators should concentrate their efforts for greater disclosure.
“In this research we wanted to understand if we could use machine learning algorithms to predict Scope 3 emissions for any company using just financial data,” says Dr McNeil.
The research team discovered that firms chose to report on particular categories within Scope 3 – and they often report on categories which are easier to calculate, instead of categories which really matter.
“For example, only 24 per cent of companies reported ‘Use of Sold Products’ emissions which we found make up 63 per cent of Scope 3 emissions – by far the most important category,” says Dr McNeil.
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“It is interesting to see the Scope 3 categories firms choose to report on are not always the most material, such as travel emissions,” says University of Otago Research Fellow Dr Quyen Nguyen.
“This may be because it is difficult to collect data for other relevant and material categories, such as the use of products and processing of sold products. But it could also mean that the true environmental impact of a firm is being disguised. Machine learning can help predict individual Scope 3 categories, but it is no magic bullet. What we need is for firms to report more Scope 3 categories.”
Although significant uncertainty remains, Dr McNeil explains how the machine learning approach to estimating Scope 3 emissions has proven valuable to EMMI in quantifying climate risk for investments.
“This is important in understanding how a company is at risk of financial repercussions in a net-zero world, where carbon is legislated and priced,” Dr McNeil says.
However, firms are reporting more categories over time, and some jurisdictions are moving towards mandatory disclosures, driven by the Task Force on Climate-Related Financial Disclosures (TCFD), and there is increasing pressure to make Scope 3 reporting mandatory.
“Future work in this area will focus on better methods to forecast company emissions to help check and verify decarbonisation plans, and evaluate whether they are achievable,” says Dr McNeil.