Located in the Zona Franca de Barcelona, the new plant represents an investment of more than €42 million and is expected to create over 85 direct jobs.
The project has been developed by PreZero, with plant integration delivered by Bianna and sorting technology supplied by Pellenc ST.
The facility is designed to process non-recyclable industrial waste into SRF, a high-efficiency fuel used primarily in energy-intensive sectors such as cement manufacturing and thermal energy production.
With a throughput of around 30 tonnes per hour – equating to nearly 200,000 tonnes annually – the plant will produce up to 70,000 tonnes of SRF each year while recovering more than 40,000 tonnes of recyclable materials.
Growth of European waste sector
The development comes amid continued expansion in Europe’s industrial waste management sector, which is forecast to grow significantly in the coming years.
Increasing regulatory pressure, combined with demand for sustainable waste treatment, is driving operators to invest in advanced recovery technologies.
Juan A. Gázquez Serrano, Director of Industrial Business North, PreZero Iberica, commented: “The plant thus becomes an example of tripartite cooperation capable of addressing today’s environmental challenges.”
The addition of a planned biomethane unit – named Bioenergy – will further enhance the site’s capabilities by enabling renewable gas injection into the natural gas grid.
Advanced sorting technology
Central to the plant’s performance is a suite of six optical sorters from Pellenc ST’s COMPACT+ range.
Designed for demanding industrial environments, the systems enable high levels of material recovery while maintaining efficiency in terms of energy use and maintenance.
Each unit is equipped with the company’s FLOW detection system, combining extended near-infrared (NIR/VIS) spectrometry with focused lighting to improve sorting accuracy and output purity.
The sorting infrastructure is also integrated with Pellenc ST’s SMART&SHARE platform, allowing operators to monitor key SRF quality metrics such as calorific value, chlorine content, PVC levels, moisture and biogenic carbon.
This data-driven approach enables real-time optimisation of fuel quality to meet the specific requirements of end users.
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