Waste treatment as a pillar of the circular economy and resilient growth. Waste treatment is a key pillar of the circular economy and environmental transition, according to LFDE analysts. Investing in plastic recycling and biogas recovery can turn climate risks into stable revenues while supporting industrial growth. Rising waste volumes and stricter regulations drive demand for better sorting, reuse, and energy recovery, creating resilient, locally dominant utility-like businesses with long-term value potential. 4 hours ago May 22, 2026 Waste treatment is a cornerstone of the environmental transition and the circular economy. According to Pierre Schang, manager, and Jisia Ranaivosoa, manager/analyst at LFDE, investing in plastic recycling and biogas energy recovery transforms climate risks into recurring revenues, offering resilience and industrial growth. Collecting, sorting, recovering, and treating increasingly large and complex waste streams: these are the long-term needs determined by population growth, climate change, the cost of raw materials, and tightening health regulations. Without significant intervention, global household waste production could reach 3.4 billion tons by 2050, equivalent to the city of Brussels buried under 25 meters of garbage. Waste treatment is now a central link in the environmental transition. Some pioneering investors have addressed these challenges, supporting the companies involved so they can consider them as true strategic and competitive levers. Circularity at the heart of the ecosystem. The environmental damage caused by plastic is a concrete illustration of these challenges. Emissions from the lifecycle of plastic are expected to triple by 2026. The challenge, therefore, lies not only in collecting more, but also in producing recycled material of sufficient quality to be reintroduced into packaging chains. Beyond the environmental aspect, this same requirement responds to a growing demand from industries and communities: better tracked flows, less susceptible to contamination, and capable of being exploited in circular supply chains. For example, Republic Services, a leading American waste management company, has created a Polymer Center in Las Vegas dedicated to the secondary sorting of post-consumer plastic to produce recycled materials ready for reuse in new packaging. The site's announced capacity exceeds 45,000 tons of recycled plastic per year, and the company is developing a second plant in Indianapolis. The role of equipment suppliers is also crucial in this value chain. The Norwegian company Tomra is developing automated return systems and optical sorting technologies that can identify and separate materials with great precision: packaging, plastic, metal, and food waste. Improving the quality of the flows is essential to ensure effective circularity: the more a material is properly isolated upstream, the greater its reintegration into value-added applications rather than being disposed of. Towards energy recovery. Energy recovery represents a second pillar of circularity and growth. A simple observation is enough: landfills emit methane, a powerful greenhouse gas that - if captured and treated - can be transformed into renewable natural gas, used in networks or as fuel. The North American group Waste Management therefore plans to invest $3 billion in its recycling and renewable natural gas infrastructure within around forty modern recycling centers. By 2024, the company had converted 58 million MMBtu of landfill gas into energy, enough to meet the electricity needs of a metropolis like Paris for a year. The group aims to significantly increase its production through new plants. Republic Services, meanwhile, has set itself the goal of increasing the reuse of its biogas by 50% by 2030, a prime example of transforming an environmental externality into a source of recurring revenue while simultaneously reducing emissions related to landfill disposal. For investors, waste treatment operators have similar characteristics to utilities, yet retain their own dynamics. As these are local markets, collection and landfill disposal are often subject to long-term contracts. Barriers to entry are significant: limited permits, limited social acceptability of new landfills or waste-to-energy plants, logistics density, as well as economies of scale in waste sorting and treatment. This structure creates local monopolies or oligopolies, with good visibility of volumes and the ability to pass on costs to prices. Unlike regulated utilities, these companies have greater tariff and operational flexibility. Within a portfolio, these companies, in its view, complement stocks more directly exposed to renewable energy or energy efficiency. The environmental transition isn't just about producing cleaner energy; it also requires better management of the materials its economies extract, consume, and discard. The waste management sector, whose growth is tied to long-term physical and regulatory needs, lies precisely at the intersection of resilience, circularity, and industrial growth. DISCLAIMER: This article was written by a third party contributor and does not reflect the opinion of Born2Invest, its management, staff or its associates. Please review its disclaimer for more information. This article may include forward-looking statements. These forward-looking statements generally are identified by the words "believe," "project," "estimate," "become," "plan," "will," and similar expressions. These forward-looking statements involve known and unknown risks as well as uncertainties, including those discussed in the following cautionary statements and elsewhere in this article and on this site. Although the Company may believe that its expectations are based on reasonable assumptions, the actual results that the Company may achieve may differ materially from any forward-looking statements, which reflect the opinions of the management of the Company only as of the date hereof. Additionally, please make sure to read these important disclosures. First published in ESG NEWS. A third-party contributor translated and adapted the article from the original. In case of discrepancy, the original will prevail. Although Born2Invest made reasonable efforts to provide accurate translations, some parts may be incorrect. Born2Invest assumes no responsibility for errors, omissions or ambiguities in the translations provided on this website. Any person or entity relying on translated content does so at their own risk. Born2Invest is not responsible for losses caused by such reliance on the accuracy or reliability of translated information. If you wish to report an error or inaccuracy in the translation, Born2Invest encourage you to contact Born2Invest Jeremy Whannell loves writing about the great outdoors, business ventures and tech giants, cryptocurrencies, marijuana stocks, and other investment topics. His proficiency in internet culture rivals his obsession with artificial intelligence and gaming developments. A biker and nature enthusiast, he prefers working and writing out in the wild over an afternoon in a coffee shop.

AI and deep learning are reshaping the future of recycling. Advanced waste sorting AI and deep learning are reshaping the future of recycling. May 12, 2026 Reading time: about 4 minutes TOMRA Recycling has unveiled a suite of innovations at IFAT 2026 in Munich that signal a fundamental shift in how the industry approaches sorting and material recovery - powered by AI and deep learning at every level of plant operations. At the heart of TOMRA's announcements is a breakthrough platform developed by PolyPerception, in which TOMRA has now acquired a 51% majority stake. The platform represents a significant evolution of PolyPerception's existing Waste Analyzer - an AI-powered analytics solution designed to improve sorting performance through end-to-end material tracking. What sets the new platform apart from conventional digital tools is its natural language interface. Plant operators can interrogate live data in plain English, posing questions such as 'How did changing the settings on the recovery line affect our purity?' and receiving immediate answers accompanied by detailed data breakdowns. The technical barrier between complex spreadsheets and day-to-day operational decision-making is, in effect, dissolved. Crucially, the platform goes beyond passive observation. Unlike traditional tools that are limited to reading and reporting data, this system also possesses what its developers describe as 'writing' capabilities - enabling it to act as an agent within the plant. It can create custom quality reports and set operational alerts in seconds, drawing on deep domain knowledge of the recycling process. "With the introduction of our new agent-based platform, recycling plants now gain a new cognitive layer," says Nicolas Braem, CEO and Co-Founder of PolyPerception. "Data is no longer just reported - it is interpreted, explained and transformed into relevant insights in a few seconds. Operators can interact naturally with their plant, ask questions, explore material behaviour and receive clear, actionable answers in real time." Open systems and advanced search capabilities. The platform is built around full data transparency, allowing recyclers to integrate plant data directly into their existing management systems. Managers can query waste statistics or purity levels through their own dashboards without needing to log into a separate system - a long-overdue step towards interoperability in an industry that has historically operated in siloed environments. Two new search methods further strengthen the platform's ability to respond to changing material streams. The first, a similarity search function, allows operators to right-click on a problematic object - an electronic vape, for instance - and instantly identify every visually similar item in the stream. This has immediate practical value for spotting fire hazards such as batteries, without the need to train an entirely new AI model. The second is a text and brand search function, enabling users to search for specific brands or object types - filled refuse bags or nappies, for example - to monitor in real time exactly what is passing through the facility. Both features address a genuine operational need: the ability to respond rapidly and precisely as the composition of incoming streams continues to evolve. "AI has always been part of TOMRA's DNA, but we are now entering an entirely new phase," says Lars Enge, EVP and Head of TOMRA Recycling. "With our acquisition of a majority stake in PolyPerception, we are moving beyond AI as a sorting tool to AI as a central intelligence for the recycling plant. By combining our advanced sorting systems and digital solutions with PolyPerception's AI platform we are creating an end-to-end solution that doesn't just optimise machines but fundamentally redefines how plants operate." Neural networks break through the sorting bottleneck. Alongside the PolyPerception platform, TOMRA is introducing three new deep learning applications for its GAINnext(TM) ecosystem - each targeting a persistent industry challenge where conventional sensor-based sorting has reached its limits. The first addresses food-grade PET tray sorting, a growing priority as tray material emerges as a critical feedstock alongside bottles. By training GAINnext(TM) on thousands of images, the system can now distinguish between takeaway or supermarket trays and consumer or medical packaging, based on shape and intended use. The result is a purity level exceeding 95% - a figure that transforms PET tray sorting from a technical obstacle into a commercially viable proposition. In the metals sector, TOMRA is launching a high-precision application targeting what the industry terms 'copper meatballs' - complex copper-steel composites such as motor armatures that present significant challenges in sorting. The GAINnext(TM) system identifies these materials automatically, even in oxidised or dirty streams, helping recyclers upgrade rebar-grade scrap to premium furnace feedstock. This development is particularly timely as the steel sector takes its first steps towards decarbonisation. The third application brings a high-throughput solution for used beverage can (UBC) aluminium recovery from packaging streams to the European market, following a successful rollout in North America. The system offers up to 33 times more throughput than manual sorting, delivering purity levels of 98% or higher. By instantly detecting and ejecting non-UBC materials, it provides a more efficient, automated route for aluminium can-to-can recycling. A turning point for intelligent resource recovery. Taken together, these announcements represent more than an incremental product update. They point towards a new operational model for the sector - one in which data, intelligence and physical sorting action are continuously and seamlessly connected. "These launches signal a true technology turning point for the industry," Enge concludes. "Deep learning is no longer just enhancing individual processes or tackling increasingly complex sorting challenges - it is linking insights directly to action across the plant. We are moving beyond high-speed detection toward a new era of intelligent, connected sorting, where complex challenges are solved and data is understood, contextualised and communicated directly to the operator. Once again, TOMRA is at the forefront of innovation, translating today's most advanced AI into real, measurable value for customers." TOMRA Recycling, which has installed more than 11,900 sorting systems across over 100 countries, was the first company to introduce deep learning-based AI technologies to the recycling industry. With its majority stake in PolyPerception now secured, the company appears well positioned to define what the next generation of intelligent, connected sorting looks like in practice. May 12, 2026 Last Update May 12, 2026

Tomra Recycling has launched an AI-native platform from PolyPerception alongside three new deep learning applications for its GainNext technology. The move follows Tomra's expanded investment in PolyPerception, acquiring a 51% majority stake. PolyPerception's platform upgrades its Waste Analyzer with a natural language interface, allowing operators to query plant data conversationally. The technology can draft quality reports, set operational alerts and integrate with existing management systems. Tomra also unveiled three GainNext applications: one for food-grade PET tray sorting achieving over 95% purity, a copper recovery solution for decarbonising steel production, and a high-throughput aluminium can recovery system providing 98% purity with 33 times more throughput than manual sorting. The company aims to transform AI from a sorting tool into central intelligence for recycling plants.