Abstract
Food waste remains a major environmental, economic, and social challenge in Europe, with over 58 million
tonnes generated annually and households accounting for the largest share. Beyond direct economic losses,
food waste significantly contributes to greenhouse gas emissions and represents inefficient use of natural
resources. In response, the European Union has strengthened its policy framework, most notably through the
amended Waste Framework Directive, which sets binding food waste reduction targets and highlights the need
for innovative and circular approaches to the management of biological resources.
Against this background, Sweden provides an advanced policy and implementation context. Mandatory
separate collection of food waste, combined with a widespread biogas infrastructure, has enabled high rates
of biological treatment. However, the effectiveness of these systems increasingly depends not only on the
quantity of food waste collected, but also on its quality. Contamination with plastics and other materials leads
to rejected feedstock, higher treatment costs, and loss of bioenergy potential, creating both economic and
environmental burdens for municipalities.
This report presents initiatives in Sweden where advanced and smart technologies are key enablers for
improving the handling, quality and usability of food waste, in line with the objectives of IEA Bioenergy Task
36. Automated, data-driven solutions—including sensor-based systems, AI-supported monitoring, and smart
measurement technologies—offer new opportunities to detect contamination, generate high-resolution data,
and support targeted interventions across the waste management chain.
The report presents a Swedish case study and ongoing initiatives that illustrate how these technologies can be
applied in practice. The Sopsmart AI project in Östersund demonstrates how AI-supported image analysis
integrated into collection vehicles can identify incorrect sorting at source, provide actionable feedback to
households, and significantly reduce contamination risks for biogas production. Complementary initiatives,
such as Tekniska verken’s advanced post-sorting facility at Gärstad and a smart bin–based monitoring
developed by the University of Borås, highlight how automation and digitalisation can enhance food waste
recovery both at system and operational levels.
Taken together, these examples show that advanced and smart technologies can play a crucial role in
improving feedstock quality for further processing, reducing unnecessary energy recovery of organic material,
and enabling data-driven waste prevention and valorisation strategies. While several initiatives are still under
development, the findings underline the potential of these approaches to support EU and national food waste
targets and to strengthen integrated material and energy recovery systems within a circular bioeconomy.