Jointly meeting global challenges Annual report 2012

 

Unique collaboration reveals hard facts about European illicit drug use

26 July 2012Research

For the first time in history, scientists have made direct comparisons of illicit drug use in 19 European cities through a cooperative analysis of raw sewage samples. The research results receive a lot of attention in the national and international media. In Amsterdam, together with Antwerp, the highest per capita use of cocaine is observed, whereas the highest per capita use of MDMA (ecstasy) is found in Dutch and Belgian cities (Amsterdam, Eindhoven, Utrecht and Antwerp).

The Norwegian Institute for Water Research (NIVA) and the Mario Negri Institute in Milan initiate a study with partner institutes in 11 European countries. KWR Watercycle Research Institute is the Dutch participant. The participating institutes collect raw sewage samples from in total 19 European cities during a single week in March 2011. The samples are then analysed for the urinary biomarkers of cocaine, amphetamine, ecstasy, methamphetamine and cannabis. The results are published in the peer-reviewed journal Science of the Total Environment.

Compare for yourself the drug use per city by  selecting a drug and ticking on or off the towns.

Results

The total daily loads of the drugs used by the inhabitants that enter the sewage treatment plant of each of the 19 cities is calculated and then the results are adjusted for population size. This allows for a direct comparison between a megacity like London and a smaller one, such as Oslo (see infographic). When extrapolated to the total population of Europe, the results show that total daily use of cocaine is estimated to be equivalent to 355 kilograms per day. This estimate confirms the data that the United Nations Office on Drugs and Crime estimate to be Europe’s share of global cocaine consumption.

The method is now considered a complement to the use of traditional questionnaires to monitor drug use (see article “Sewage research produces reliable data”).

© 2017 KWR Watercycle Research Institute

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