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. 2024 Aug;31(40):53410-53423.
doi: 10.1007/s11356-024-34783-9. Epub 2024 Aug 27.

Assessment of dynamics and variability of organic substances in river bank filtration for prioritisation in analytical workflows

Affiliations

Assessment of dynamics and variability of organic substances in river bank filtration for prioritisation in analytical workflows

Sebastian Handl et al. Environ Sci Pollut Res Int. 2024 Aug.

Abstract

Bank filtration supports the growing global demand for drinking water amidst concerns over organic micropollutants (OMPs). Efforts to investigate, regulate and manage OMPs have intensified due to their documented impacts on ecosystems and human health. Non-targeted analysis (NTA) is critical for addressing the challenge of numerous OMPs. While identification in NTA typically prioritises compounds based on properties like toxicity, considering substance quantity, occurrence frequency and exposure duration is essential for comprehensive risk management. A prioritisation scheme, drawing from intensive sampling and NTA of bank filtrate, is presented and reveals significant variability in OMP occurrence. Quasi-omnipresent substances, though only 7% of compounds, accounted for 44% of cumulative detections. Moderately common substances, constituting 31% of compounds, accounted for 50% of cumulative detections. Rare compounds, comprising 61%, contributed only 6% to cumulative detections. The application of suspect screening for 31 substances to the dataset yielded results akin to NTA, underscoring NTA's value. Correlation between both methods demonstrates the efficacy of high-resolution mass spectrometry-based NTA in assessing temporal and quantitative OMP dynamics.

Keywords: Exposure; LC-HRMS; Non-targeted analysis; Organic micropollutants; River bank filtration.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Time series of the number of detected compounds according to their recurrence dynamics (colours) for positive (top) and negative (bottom) ionisation modes
Fig. 2
Fig. 2
Histogram of absolute frequency of occurrence for positive (top) and negative (bottom) ionisation mode. The relative frequency is indicated by colour
Fig. 3
Fig. 3
Time series of the number of compounds according to their frequency of occurrence class for positive (top) and negative (bottom) ionisation mode. Relative frequency is indicated by colour
Fig. 4
Fig. 4
Number of compounds by average duration between detections for different abundance groups (moderately common: top; rare: bottom). Omnipresent compounds are not displayed. The average duration between detections is 2 days for all compounds in this group
Fig. 5
Fig. 5
Number of compounds by semi-quantitative variability of compound intensities (maximum deviation from the mean expressed in standard deviations). Compounds only detected once cannot be evaluated and are categorised “NA”
Fig. 6
Fig. 6
Time series of intensities of substances detected above the detection limit. The measurement values in the environmental samples are shown as green dots connected by a line. Measurements that were below the detection limit are represented as pink dots at the intensity of zero
Fig. 7
Fig. 7
Scatter plot of intensities obtained from SSC and intensities from NTA for field samples and repetitions

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