JRC scientists developed a new analytical method to support the European Commission’s fight against tobacco fraud.
The fight against fraud is high on the European Commission’s political agenda. The Protocol to the WHO Framework Convention on Tobacco Control (FCTC), supported by the EU, recognises illicit trade in tobacco products as a global multi-billion Euro business; it serves financing of transnational criminal activities.
Every year, illicit trade of cigarettes causes approximately 10 billion Euros of tax revenues losses to the budget of EU Member States.
This illicit trade of cigarettes has many facets. It includes contraband or counterfeit products.
Cigarettes that are legal in one country can be illegal in another country. Fraud includes smuggling cigarettes from low-tax Member States to Member State with higher tax rates or by trafficking cigarettes from outside the EU into the Common Market.
Second Action Plan to fight the illicit tobacco trade 2018-2022
In 2018 the Commission launched a specific Action Plan in the fight against illicit tobacco.
One of the actions of the plan is the provision of chemical and technical analysis on seized tobacco products by the EU Tobacco Laboratory, operated by the JRC.
Cigarettes have distinct flavours that consumers can recognise and distinguish. This is done by blending specific tobacco varieties and adding natural or synthetic flavour imparting substances.
JRC scientists developed a method to extract those substances by thermal desorption from unburnt tobacco. They are then measured by gas chromatography hyphenated to high resolution mass spectrometry.
This results in a profile of volatile substances. Artificial intelligence is then used to check whether suspect cigarettes are genuine or fake. The established discrimination model, which is selective and specific, will be applied for the analysis of cigarettes ceased by customs authorities in the EU Member States. It creates intelligence for prosecuting and dismantling criminal networks pushing illegal tobacco.
The analytical method was published in: Zelinkova, Z, and Wenzl, T. Identification of Cigarette Brands by Soft Independent Modeling of Class Analogy of Volatile Substances, Nicotine & Tobacco Research, 2020, 997–1003; doi:10.1093/ntr/ntz066
- Fecha de publicación
- 12 junio 2020