|Abstract Title:||The IMPART project, a citizen science approach to using passive samplers to monitor for emerging contaminants|
|Presenter Name:||Mr Richardson AK|
|Co-authors:|| Friedman S|
|Company/Organisation:||Imperial College London|
Abstract Information :
The Imperial Monitoring using Passive Samplers to Assess River Tributaries (IMPART) project takes a citizen science approach to the monitoring of local rivers for contaminants of emerging concern using a miniaturised 3D printed passive sampling device (3D-PSD). The 3D-PSDs were manufactured from a methacrylate-based resin and hold up to five individual 9 mm sorbent disks. Seventeen citizen scientists were engaged from four community groups across three UK sites (Norwich, Sheffield, and Brent) to deploy and retrieve the passive sampler devices. Using their local river knowledge and experience, the citizen scientists were trained to deployed seven 3D-PSDs (unaided) per community group (in locations of their choosing) for one week. Water samples were collected, and field blanks were exposed by the citizen scientists during deployment and retrieval.
In total, 35 devices were successfully deployed and retrieved by the citizen scientists and returned to Imperial College London for analysis with no losses. Across all sites, 57 unique emerging contaminants were quantified on the passive sampler and 35 were common to all sites, including carbamazepine, imidacloprid, and venlafaxine. In the water samples, only 20 unique compounds were qualifiable above method LLOQ across all sites, demonstrating the increased sensitivity of the 3D-PSD for contaminants at environmentally relevant concentrations. Within each site, sources of pollution were clearly identifiable from the 2.5 to 4-fold increase in the total mass of contaminants accumulated onto the 3D-PSD. There were between four and three unique compounds per site and multivariate statistics are being explored to determine if it is possible to classify rivers based on their chemical profile which has been demonstrated in the London tributaries. This work demonstrates the applicability of the 3D-PSD to citizen science and community engagement projects.