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Occurrence and concentrations of organic micropollutants (OMPs) in highway stormwater: A comparative field study in Sweden
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This Swedish study characterized organic micropollutants in highway stormwater, detecting bisphenol-A, alkylphenols, and polycyclic aromatic hydrocarbons above environmental quality standards. Highway runoff is also a significant source of tire wear microplastics, meaning these chemical and physical pollutants often reach waterways together.
Abstract This study details the occurrence and concentrations of organic micropollutants (OMPs) in stormwater collected from a highway bridge catchment in Sweden. The prioritized OMPs were bisphenol-A (BPA), eight alkylphenols, sixteen polycyclic aromatic hydrocarbons (PAHs), and four fractions of petroleum hydrocarbons (PHCs), along with other global parameters, namely, total organic carbon (TOC), total suspended solids (TSS), turbidity, and conductivity (EC). A Monte Carlo (MC) simulation was applied to estimate the event mean concentrations (EMC) of OMPs based on intra-event subsamples during eight rain events, and analyze the associated uncertainties. Assessing the occurrence of all OMPs in the catchment and comparing the EMC values with corresponding environmental quality standards (EQSs) revealed that BPA, octylphenol (OP), nonylphenol (NP), five carcinogenic and four non-carcinogenic PAHs, and C 16 -C 40 fractions of PHCs can be problematic for freshwater. On the other hand, alkylphenol ethoxylates (OPnEO and NPnEO), six low molecule weight PAHs, and lighter fractions of PHCs (C 10 -C 16 ) do not occur at levels that are expected to pose an environmental risk. Our data analysis suggests that three water quality parameters (turbidity, TOC, and EC) hold strong potential as surrogate parameters for PAHs, PHCs, BPA, OP, and TSS. Therefore, continuously measuring these parameters could complement data from monitoring programs in which long-term, high-resolution time series are of interest. Furthermore, the EMC error analysis showed that high uncertainty in OMP data can influence the final interpretation of EMC values. As such, some of the challenges that were experienced in the presented research yielded suggestions for future monitoring programs to obtain more reliable data acquisition and analysis.
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