The ecological state of receiving water bodies can be significantly influenced by organic micropollutants that are emitted via stormwater runoff. Reported efforts to quantify the emission of micropollutants mainly focus on sampling at combined sewer overflows and storm sewer outfalls, which can be challenging. An alternative method, called fingerprinting, was developed and tested in this study. The fingerprinting method utilizes wastewater treatment plant (WWTP) influent samples and derives the proportion of stormwater in a sample. This is achieved by comparing the wet weather vs dry weather concentrations of substances-tracers which are present only in wastewater. It is then possible to estimate the concentration of organic micropollutants in stormwater runoff from measurements in the influent of a WWTP based on a mass balance. In this research, the fingerprinting method was applied in influent samples obtained in five WWTPs in the Netherlands. In total, 28 DWF and 22 WWF samples were used. The chosen tracers were ibuprofen, 2-hydroxyibuprofen, naproxen and diclofenac. Subsequently, the concentration in stormwater runoff of 403 organic micropollutants was estimated via the WWF samples. The substances that were present and analyzed included glyphosate and AMPA, 24 out of 254 pesticides, 6 out of 28 organochlorine pesticides, 45 out of 63 pharmaceuticals, 15 out of 15 PAHs, 2 of the 7 PCBs, and 20 of 33 other substances (e.g. bisphenol-A). A comparison with findings from other studies suggested that the fingerprinting method yields trustworthy results. It was also noted that a representative and stable dry weather flow reference concentration is a strict requirement for the successful application of the proposed method.

Infiltration and inflow (I/I) into sewers cause negative effects on the sewer system, wastewater treatment plant and environment. Identifying the causes and locating the inflows is necessary in order to address the I/I problem. This paper focuses on using distributed temperature sensing (DTS) for identifying, locating and characterising I/I into a sewer system during the end of winter-beginning of summer transition period under dry and wet weather conditions. During snowmelt, several locations with I/I were identified, while these locations did not show I/I during storm events after the snowmelt. In addition, during a very heavy storm after the snowmelt period, I/I was found at other locations. Therefore, DTS was demonstrated to be effective in identifying the type of I/I and in locating I/I. Finally, I/I monitoring campaigns in cold climates should take into account the variety of pathways of I/I during snowmelt and during rainfall.