The cross-sector effort to reduce waste is fuelling interest in circular economy solutions
Companies already investing in
this opportunity
growth opportunities in circular economy to 2030
The goal of a circular economy system is to reduce the negative impacts of consumption by cutting the amount of waste in a product’s lifecycle. Circular economy is often described as a closed loop system, which has a strong onus on reusing, recycling, reusing and repairing to minimise waste.
Circular economy considerations affect the design process and decisions across the supply chain. From the mining of materials and the manufacturing of products to the way they are used and disposed of, recycled, or reused. The circular economy system emphasises the reuse of materials. Innovators can adopt “recyclability by design”, physical and chemical recycling, and redesign systems to incentivise a circular model.
Estimated value of the global metal recycling market by 2030
Projected value of the global filtration and separation market by 2030
of growth opportunities to 2050
The circular economy could add $4.5 trillion to the global economy by 2030, rising to $25 trillion by 2050. It is also predicted to reduce greenhouse gas emissions by 39 percent, virgin material use by 28 percent and create up to 65 million new jobs. Yet many companies are a long way off adopting a circular economy system.
The greatest challenge in closing the loop is the fact that many components are not easy to separate out again. As such, recyclability by design is gaining popularity, enabling easier end-of-life recycling and reducing material costs. Digitalisation offers the promise of programming each material with a blockchain. At the end of use, information on optimal recycling processes could be easily extracted.
The circular economy offers opportunities across sectors.Manufacturing sectors are already heavily investing in circular economy andmore innovations are being driven by developments in neural networks,reinforcement learning, blockchain cryptography, reinforcement learning, andwireless sensors.
