Submitted by Sergey Kolesnikov on Sun, 27/08/2023 - 22:35
The majority of carbon offset schemes are significantly overestimating the levels of deforestation they are preventing, according to a new study published in Science by an international team of scientists and economists led by CEENRG fellows Dr Thales West, representing VU Amsterdam, and Professor Andreas Kontoleon in the Department of Land Economy, University of Cambridge. These findings mean that many of the “carbon credits” bought by companies to balance out emissions are not tied to real-world forest preservation as claimed.
The study analysed 18 major carbon offset projects across five countries: Peru, Columbia, Tanzania, Cambodia, and the Democratic Republic of Congo. The researchers compared the claimed levels of conservation by these projects to real-world deforestation levels. They found that millions of carbon credits, traded on the worldwide carbon credit market which was worth 1.3 billion USD in 2021, are based on crude calculations that inflate the conservation successes of voluntary REDD+ projects, which aim to reduce emissions from deforestation and forest degradation in developing countries. Of the 89 million carbon credits expected to be generated in 2020 from the sites analysed, some 68% would have originated from projects that barely reduced deforestation, if at all.
Professor Andreas Kontoleon, a co-author of the study, said,
"Carbon credits provide major polluters with some semblance of climate credentials. Yet we can see that claims of saving vast swathes of forest from the chainsaw to balance emissions are overblown."
The study calls for greater regulation of the industry, with the closing of loopholes and more sophisticated and transparent methods for the quantification of preserved forest.
The study already received extensive media coverage, including, among others, by the following publications:
Bloomberg (+ Yahoo! coverage)
Der Spiegel
The Hill
The Daily Telegraph
The Guardian
The Times
Banner image © John W Banagan/Stone via Getty Images.
