Measurements in European sewage
Growing interest in drug research
In a large-scale European research project about drugs in sewage water, KWR produces the data on Dutch cities. A new scientific publication attracts a great deal of media attention, and leads to follow-up research in various Dutch municipalities, which, with this and other research methods, want to acquire a complete picture of drug use in their cities.
After the wastewater of 19 European cities is studied over a period of one week in 2011 for the presence of drugs (residues) excreted by humans, the research is repeated in 2012 in 23 cities in 11 countries and, in 2013, in 42 cities in 21 countries. The results of all 3 measurement programmes are then compared, and, in mid 2014, the scientific journal “Addiction” publishes an article on the results of the research, which is the most extensive sewage drugs study ever conducted. The conclusions also appear in the European Drug Report 2014 of the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). On the basis of the data, the report concludes that “wastewater analysis provides the possibility to collect and report measurements more quickly and regularly than is the current norm for national surveys.” Pim de Voogt, principal scientist at KWR and, since 1 September 2014, Professor of Chemico-Biological Interactions in Aquatic Ecosystems at the University of Amsterdam, has been involved in the European wastewater research since the start. He observes that “if this method is used more routinely as a complement to other drug surveillance methods, it can generate valuable additional information about trends in the spread and use of drugs, and signal the arrival of new psychoactive substances on the market.”
Geography- and time-dependant drug use
The research shows that traces of cocaine are higher in the west and south than in the north and east of Europe. The use of amphetamine is relatively evenly distributed over the continent, with the north and north-west showing the highest levels. Methamphetamine use is generally quite low, but while it was previously limited to the Czech Republic and Slovakia, we see it is also now used in eastern Germany and Scandinavia. Dutch cities show relatively high use of cocaine, amphetamine and ecstasy, and the Netherlands ranks among the top 5 in cannabis use. In most European cities the use of cocaine and ecstasy rises sharply over the week-ends, while methamphetamine and cannabis use is more evenly spread throughout the week.
Media attention and parliamentary questions
Various newspapers, radio and television programmes cover the research’s conclusions. Members of the Dutch Lower House ask the Minister of Security and Justice and the State Secretary for Health, Welfare and Sport a number of critical questions. In his response, the State Secretary emphasises that the sewage drugs research is a complement to other methods of monitoring drug use, as noted in the EMCDDA report. He sees no need for the national government itself to have follow-up research conducted into drugs in sewage, leaving it to the discretion of the local authorities.
In most European cities the use of cocaine and ecstasy rises sharply over the week-ends
Research in more Dutch cities
Several Dutch cities are curious about drug use among their residents and visitors. The municipality of the island of Texel is one of them: “Both Texel’s Municipal Executive and City Council believe the further reduction of drug use on Texel to be desirable. Through sewage measurements, we can acquire more insight into drug use on the island. Precise measurements by KWR can establish how many grams of drugs are discharged in the wastewater over a period of 24 hours per 1,000 residents. These numbers, together with the results of other research, provide an objective and complete picture of drug use on Texel. The results can be compared with those of other municipalities.”
© 2017 KWR Watercycle Research Institute
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Pim de Voogt
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Spatial differences and temporal changes in illicit drug use in Europe quantified by wastewater analysis