Rapid Assessment of Samples from Large-Scale Clandestine Synthetic Drug Laboratories by Soft Ionization by Chemical Reaction in Transfer-High-Resolution Mass Spectrometry

The worldwide ongoing trend of synthetic drug production is also of increasing concern due to enormous amounts of chemical waste produced in clandestine laboratories. Typically, several tons of different types of production waste are stored in numerous containers and need to be characterized after dismantling a laboratory to assess production features, e.g., synthesis route and production scale, and to draw conclusions on the minimum number of batches produced. This forensic assessment is commonly done by a rather laborious gas chromatography - mass spectrometry approach. The aim of this work is to evaluate the suitability of the SICRIT (soft ionization by chemical reaction in transfer) ion source, which is based on the dielectric barrier discharge ionization principle, combined with high-resolution mass spectrometry (HRMS), for the rapid classification of liquid samples from amphetamine production in a seized large-scale clandestine drug laboratory. Among the different sample introduction methods tested, headspace analysis directly into the SICRIT ion source in conjunction with a heated inlet proved to be optimal. Identification of expected target substances (reaction educts, intermediates, byproducts, products) was possible as well as grouping related samples and assigning them to specific synthesis steps by multivariate data analysis in an unsupervised approach. In addition, supervised machine learning algorithms were evaluated to obtain a classification model for the assessment of production waste samples from one dismantled synthetic drug laboratory, and a random forest classifier showed the best performance with an accuracy of 97%. The potential of the novel SICRIT-HRMS approach for the assessment of synthetic drug laboratories was demonstrated.

Estimating illicit production of MDMA from its production waste, a Dutch case study

The Netherlands plays a key role in the global production of the synthetic illicit drug MDMA. However, the actual Dutch production of MDMA is difficult to quantify. The illicit production of MDMA results in large amounts of waste. This study uses amounts of waste found in the environment and production-related MDMA residues in wastewater to estimate the amount of MDMA that is produced. The MDMA produced, associated to the amount of waste found in the environment is 4.2 and 5.8 tons per year for two common synthesis routes. The MDMA produced, associated to production-related residues in wastewater is significantly larger, with 39.2 tons per year. The estimated MDMA production associated to waste in the environment and wastewater analysis is 43.4 and 45.0 tons per year for two common synthesis routes. Even though these estimates are difficult to validate, they are feasible when compared to prevalence-based consumption estimates or production estimates based on interceptions of precursors. The current study illustrates that waste of an illicit industry can shed light on its production volumes, thereby, complementing other efforts to estimate production, trade and use of synthetically produced illicit substances.

Cost-Efficient Coverage of Wastewater Networks by IoT Monitoring Devices

Wireless sensor networks are fundamental for technologies related to the Internet of Things. This technology has been constantly evolving in recent times. In this paper, we consider the problem of minimising the cost function of covering a sewer network. The cost function includes the acquisition and installation of electronic components such as sensors, batteries, and the devices on which these components are installed. The problem of sensor coverage in the sewer network or a part of it is presented in the form of a mixed-integer programming model. This method guarantees that we obtain an optimal solution to this problem. A model was proposed that can take into account either only partial or complete coverage of the considered sewer network. The CPLEX solver was used to solve this problem. The study was carried out for a practically relevant network under selected scenarios determined by artificial and realistic datasets.

Rapid and sensitive detection of amphetamine by SERS-based competitive immunoassay coupled with magnetic separation

Amphetamine (AMP), as a psychiatric drug acting on the central nervous system, and has become one of the most common drugs of abuse in the illegal market at present, which adversely affects social public safety. We developed a SERS magnetic immunoassay with high sensitivity, specificity, and rapid and quantitative detection of AMP. We synthesized a high SERS intensity substrate (Au-XP013@Ag) using the "hot spot" effect and combined it with antibodies to form SERS immunotags (Au-XP013@Ag-AMP-mAb). Subsequently, the carboxyl magnetic beads were linked to label antigens as functional magnetic beads (carboxyl magnetic beads-AMP-BSA). Using the principle of competitive immunoassay, the Raman response value of the immune complex formed with SERS tags and functional magnetic beads was detected to realize the quantitative detection of AMP. The detection limit of this method for AMP was 2.28 ng mL^-1. More importantly, a portable Raman instrument was used in this study, which can meet the requirements of point-of-care testing (POCT). Therefore, this SERS-based magnetic immunoassay can provide a favorable scientific basis for the control of drug abuse, monitoring by law enforcement agencies, and determination of drug users.

Non-target screening of production waste samples from Leuckart amphetamine synthesis using liquid chromatography - high-resolution mass spectrometry as a complementary method to GC-MS impurity-profiling

The established approaches of suspect and non-target screening (NTS) using liquid chromatography - high-resolution mass spectrometry (LC-HRMS) are usually applied in the field of environmental and bioanalytical analysis. Herein, these approaches were employed on a forensic-toxicological application by analyzing different production waste samples from controlled amphetamine synthesis via Leuckart route to evaluate the suitability of this methodology for identification of route-specific organic substances in such waste samples. For analysis, two complementary LC techniques were used to cover a broad polarity spectrum. After data processing and peak picking using the enviMass software and further manual data restriction, 17 features were tentatively identified as suspects, three of which were subsequently identified with reference substances. All suspects had been previously identified in studies, in which gas chromatography - mass spectrometry (GC-MS) was successfully applied for synthesis marker assessment in waste and amphetamine samples. Remaining features with high signal intensity and assigned sum formula were selected for the attempt of structure elucidation. Seven potential synthesis markers were tentatively identified, which were not yet reported, except the sum formula of one compound, and which were partly also detected in real case waste samples afterwards. The innovative application of the NTS approach using LC-HRMS for the analysis of aqueous amphetamine synthesis waste samples showed its suitability as extension to GC-MS analysis as it was possible to successfully identify seven new potential marker compounds, which are specific either for the conversion of the pre-precursors α-phenylacetoacetonitrile and α-phenylacetoacetamide to phenyl-2-propanone or for the subsequent Leuckart synthesis route after their conversion.

Capillary Sensor for Detection of Amphetamine Precursors in Sewage Water

This paper deals with the problem of detecting benzyl methyl ketone (BMK), which is a precursor of amphetamine that can be synthesized in home labs. The focus of our work was to identify an improvement for the analysis of sewage introduced into the municipal sewage system. The sensors used to detect BKM in these systems are often clogged and therefore cannot function properly. In this article, a new method of detecting BMK and other chemicals in wastewater is presented. A system containing capillary polypropylene, hydrophobized with polysiloxane coating fibers was prepared. These solutions were used for continuous online measurements by ion mobility spectrometry. The use of pipes with a polysiloxane coating reduces the permeation of water and significantly increases the BMK permeation due to its high solubility in the polymer.

Identifying and Estimating the Location of Sources of Industrial Pollution in the Sewage Network

Harsh pollutants that are illegally disposed in the sewer network may spread beyond the sewer network—e.g., through leakages leading to groundwater reservoirs—and may also impair the correct operation of wastewater treatment plants. Consequently, such pollutants pose serious threats to water bodies, to the natural environment and, therefore, to all life. In this article, we focus on the problem of identifying a wastewater pollutant and localizing its source point in the wastewater network, given a time-series of wastewater measurements collected by sensors positioned across the sewer network. We provide a solution to the problem by solving two linked sub-problems. The first sub-problem concerns the detection and identification of the flowing pollutants in wastewater, i.e., assessing whether a given time-series corresponds to a contamination event and determining what the polluting substance caused it. This problem is solved using random forest classifiers. The second sub-problem relates to the estimation of the distance between the point of measurement and the pollutant source, when considering the outcome of substance identification sub-problem. The XGBoost algorithm is used to predict the distance from the source to the sensor. Both of the models are trained using simulated electrical conductivity and pH measurements of wastewater in sewers of a european city sub-catchment area. Our experiments show that: (a) resulting precision and recall values of the solution to the identification sub-problem can be both as high as 96%, and that (b) the median of the error that is obtained for the estimation of the source location sub-problem can be as low as 6.30 m.

Novel multiplex capacitive sensor based on molecularly imprinted polymers: A promising tool for tracing specific amphetamine synthesis markers in sewage water

The development of a sensing system for amphetamine (AMP), N-formyl amphetamine (NFA), and benzyl methyl ketone (BMK) in sewage is a strict requirement for enabling the on-site detection and tracing of the consumption of AMP, and the production and/or transportation of these target analytes. The present research is therefore devoted to the development of an on-site capacitive sensing system, based on molecularly imprinted polymers (MIPs) as recognition elements. To this end, the commercially available CapSenze capacitive sensor system was miniaturized by implementing an application-specific integrated circuit (ASIC), dedicated to the bias and read-out of the chemical sensor. MIPs towards AMP were purchased, whereas the ones towards NFA and BMK were synthesized in house. Gold transducers, consisting of six working electrodes with their corresponding reference electrodes and one common auxiliary electrode, were designed together with a flow cell to enable analyses. The applied water samples were filtered through a 20 micron filter before application in the sensors' flow cell. The limits of detection in filtered sewage water were determined to be 25 μM for NFA and BMK and 50 μM for AMP. The overall performance of the sensing system was tested by analysis of blind-coded sewage samples, provided by legal authorities. To the best of our knowledge, this is the first research presenting multiplex MIP-based detection of amphetamine synthesis markers using a capacitive sensor, miniaturized via ASIC technology. The presented technique is undoubtedly a potential solution for any analysis requiring constant reliable on-site monitoring of a substance of interest.

Pollution Source Localization in Wastewater Networks

In December 2016, the wastewater treatment plant of Baarle-Nassau, Netherlands, failed. The failure was caused by the illegal disposal of high volumes of acidic waste into the sewer network. Repairs cost between 80,000 and 100,000 EUR. A continuous monitoring system of a utility network such as this one would help to determine the causes of such pollution and could mitigate or reduce the impact of these kinds of events in the future. We have designed and tested a data fusion system that transforms the time-series of sensor measurements into an array of source-localized discharge events. The data fusion system performs this transformation as follows. First, the time-series of sensor measurements are resampled and converted to sensor observations in a unified discrete time domain. Second, sensor observations are mapped to pollutant detections that indicate the amount of specific pollutants according to a priori knowledge. Third, pollutant detections are used for inferring the propagation of the discharged pollutant downstream of the sewage network to account for missing sensor observations. Fourth, pollutant detections and inferred sensor observations are clustered to form tracks. Finally, tracks are processed and propagated upstream to form the final list of probable events. A set of experiments was performed using a modified variant of the EPANET Example Network 2. Results of our experiments show that the proposed system can narrow down the source of pollution to seven or fewer nodes, depending on the number of sensors, while processing approximately 100 sensor observations per second. Having considered the results, such a system could provide meaningful information about pollution events in utility networks.

Capacitively coupled contactless conductivity detection for analytical techniques - Developments from 2018 to 2020

The developments of analytical contactless conductivity measurements based on capacitive coupling over the two years from mid-2018 to mid-2020 are covered. This mostly concerns applications of the technique in zone electrophoresis employing conventional capillaries and to a lesser extent lab-on-chip devices. However, its use for the detection in several other flow-based analytical methods has also been reported. Detection of bubbles and measurements of flow rates in two-phase flows are also recurring themes. A few new applications in stagnant aqueous samples, e.g. endpoint detection in titrations and measurement on paper-based devices, have been reported. Some variations of the design of the measuring cells and their read-out electronics have also been described.

Interpol review of controlled substances 2016-2019

This review paper covers the forensic-relevant literature in controlled substances from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20Papers%202019.pdf.