Publication Details |
| Category | Text Publication |
| Reference Category | Journals |
| DOI | 10.1021/acs.est.5c02486 |
Licence  |
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| Title (Primary) | Exploring domestic discharge patterns in wastewater through LC-HRMS screening and temporal clustering |
| Author | Haalck, I.; Krauss, M.
; Brack, W.; Huber, C. |
| Source Titel | Environmental Science & Technology |
| Year | 2025 |
| Department | EXPO |
| Volume | 59 |
| Issue | 29 |
| Page From | 15375 |
| Page To | 15384 |
| Language | englisch |
| Topic | T9 Healthy Planet |
| Supplements | https://pubs.acs.org/doi/suppl/10.1021/acs.est.5c02486/suppl_file/es5c02486_si_001.pdf https://pubs.acs.org/doi/suppl/10.1021/acs.est.5c02486/suppl_file/es5c02486_si_002.xlsx |
| Keywords | LC-HRMS; non-target screening; wastewater-based epidemiology; k-means temporal clustering; domestic wastewater |
| Abstract | Wastewater influent contains valuable epidemiological information, but the complexity of the wastewater matrix poses challenges for data interpretation and linking signals to human exposure. This study aims to analyze daily discharge patterns in influent wastewater to identify recurring patterns for trace organic compounds, particularly those from domestic sources, providing insights into discharge dynamics originating from population chemical consumption and exposure. Over three 24-h periods, hourly composite influent samples from a wastewater treatment plant were analyzed using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Target and non-target screening revealed over 72,000 features, with 402 target compounds annotated. Temporal k-means clustering of target compounds identified five distinct daily patterns, with two clusters linked to domestic use: one correlated with wastewater flow, representing general daily population activities, and another showing a morning peak, likely associated with morning urine. Based on these patterns, cluster predictions were applied to the non-targeted feature list, prioritizing features with similar temporal trends. This led to 70 additional features associated with the morning peak pattern, with four compounds exemplarily identified. The findings highlight the value of combining targeted and non-targeted analyzes with clustering methods to improve the interpretation of complex wastewater data and unravel chemical discharge patterns linked to population exposure. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=31043 |
| Haalck, I., Krauss, M., Brack, W., Huber, C. (2025): Exploring domestic discharge patterns in wastewater through LC-HRMS screening and temporal clustering Environ. Sci. Technol. 59 (29), 15375 - 15384 10.1021/acs.est.5c02486 |
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