Researchers from the US military have teamed up with academics from Europe to propose a new method of classification for nanomaterial risk.

How do you bring a geochemist, an ecotoxicologist, two decision-scientists and two risk-assessors together to develop a system for classifying nanomaterial risk? Igor Linkov of the United States Army Research and Development Center started by organizing a NATO workshop “Risk, Uncertainty and Decision Analysis for Non-Chemical Stressors” in Lisbon, Portugal in April 2007.

During the workshop, Linkov and some of the speakers — Tommi Tervonen, José Figueira, Jeffery Steevens, Mark Chappell and Myriam Merad — held a brainstorming session that came to fruition a year later in the form of a paper classifying a given nanomaterial into one of five risk categories (J. Nanopart. Res. doi:10.1007/s11051-008-9546-1; 2008).

The model uses both quantitative and qualitative factors as inputs, as well as uncertainty parameters. Linkov and co-authors, who are now based in France, the Netherlands, Portugal and the United States, looked at five nanomaterials: CdSe quantum dots were deemed to be most hazardous, falling into the 'high-risk' category with high confidence; aluminum nanoparticles were the safest.

“This was one of the most challenging papers for me”, says Linkov. “The concept was novel to all of the co-authors. Decision analysts and risk assessors are accustomed to the development of elaborate models from purely theoretical grounds, whereas the 'hard' scientists on the team argued for more extensive data collection before modelling began.”

A major breakthrough, he said, was getting everyone to accept that even classical statistical analysis requires expert judgement, and that the present work simply called for a different set of expertise. Patience, mutual respect and an iterative process were the key to success, Linkov adds.