Skip to main content
European Commission logo print header

European network on chain analysis for environmental decision support, specified for the domains of design & manufacturing, waste management & recycling and transport


The proposed Concerted Action CHAIN will collect and exchange experiences and insights present within the European scientific and industrial community, with the aim to identify relevant chain management tools for the analysis of environmental impact of "metabolised" use, take-back and recycling in different industrial sectors and secondly, to interactively formulate guidelines regarding the application of chain management tools, take-back and recycling, and, when appropriate, to make further generalisations on the application of those tools.

Experiences with and insights on chain management tools will be collected during meetings and will be documented in reports. Representatives of industry, the problem owners, and members of the research organisations will document the pros and cons of the use different chain management tools in the fields of consumer electronics, plastic packaging and phosphate processing. The overall conclusions will be formulated and documented in a guidebook.

The concerted action will bring together environmental problem owners and experts from different scientific fields from throughout the EU, which is highly desirable for obtaining more efficient solutions to complex environmental problems.

Collecting and documenting experiences and insight is essential to avoid development of policies and legislation on material and product re-use and recycling which impose an economic burden on European Industry disproportionate to any environmental benefit. There is a need for a wide dissemination of knowledge of reliable tools which recognise the complex structure of many environmental and economic problems, but which do not introduce unnecessary complications of detail.

Call for proposal

Data not available


2,einsteinweg 2
2300 RA Leiden

See on map

EU contribution
No data

Participants (6)