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Calculating the carbon footprint of circular strategies

Why is there disconnect between circular economy strategies and most corporate climate roadmaps? 

Person looking at a very large chalk board with math equations written on it.

The intuitive link between climate change, carbon emissions and the circular economy is relatively straightforward: If we more efficiently make higher-quality things, use them for longer and preserve valuable resources within our industrial systems, we will lighten the environmental load and limit the need for unchecked, emissions-intensive primary production and the associated impact of shorter material lifecycles. 

At the systems-level, the relationship between climate and the circular economy is gaining traction. According to the 2021 Circularity Gap Report, circular economy strategies can cut global greenhouse gas emissions by 39 percent, keep the planet well below a 2 degrees Celsius trajectory and increase the proportion of materials that are reused from 8.6 to 17 percent. Notably, the European Union’s Circular Economy Action Plan is an important part of the European Green Deal’s roadmap for becoming the first zero emissions continent by 2050.  

Yet as more companies step up on climate change, set science-based targets and jump on the net-zero bandwagon, circular economy strategies have been notably absent from most corporate climate roadmaps despite the intuitive link. 

So, why the disconnect? 

Many would argue that the notion of achieving a climate goal through a circular economy strategy has rested for too long on its laurels of intuitive improvement. And when it comes to climate change, intuition won’t cut it.

As more companies step up on climate change, set science-based targets and jump on the net-zero bandwagon, circular economy strategies have been notably absent from most corporate climate roadmaps.

The challenge of reliably and efficiently calculating the carbon footprint of circular strategies at the product, company and country scale has been the most common concern I’ve heard over the last year within the context of the circular economy. Accordingly, a growing number of tools and frameworks have been developed (or are currently in the works) to measure and report on the emissions reductions associated with shifting to recyclable, bio-based or reusable packaging, business models such as repair and resale and end of life materials management, among other circular economy initiatives.

As climate change takes center stage on global agendas, the expectation of justifying circular strategies with carbon reduction metrics is logical, and a handful of organizations are working hard to get the math right and reduce emissions through meaningful new approaches to supply chain engagement. 

But in the equation of balancing carbon emissions with circular economy strategies, the math doesn’t always pencil out. 

Consider recycling: The process of collecting, sorting, reprocessing and manufacturing post-consumer plastics will often outweigh sourcing cheap and lightweight virgin films (that eventually would be landfilled) from a pure carbon emissions perspective. This calculus has no concern for the unchecked extraction of nonrenewable petrochemicals and associated social and environmental implications, nor a mindfulness of the mounting landfill at the end of its useful life. (It’s a carbon sink, right?). 

If all circular economy initiatives were adopted only if they offered near-term carbon reductions, many might not get off the ground. 

I’m certainly not arguing against the rigor of science-based targets and carbon accounting; these are vitally important tools to set strategy and track progress on climate change mitigation. But these quantitative metrics can’t overlook the value of preserving ecosystems and biodiversity; supporting communities and generating economic prosperity; designing out nonrenewable resources, litter and landfills, not to mention mitigating risk and increasing supply chain resilience. After all, that’s why the circular economy concept was developed in the first place. 

A data-driven decision on climate can’t be based solely on one data set.

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