Dataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the UV-vis range
Abstract A major challenge in wastewater and sewer system monitoring is the development of advanced sensing technologies to improve standard pollutant measurement and allow real-time online detection of emerging contaminants. This study presents a dataset from a 25-week measurement campaign comparin...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05459-x |
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| author | Pierre Lechevallier Günter Gruber Vojtěch Bareš Nicolas Neuenhofer Laura Waldner Abhinit Mahajan Lena Mutzner Jörg Rieckermann |
| author_facet | Pierre Lechevallier Günter Gruber Vojtěch Bareš Nicolas Neuenhofer Laura Waldner Abhinit Mahajan Lena Mutzner Jörg Rieckermann |
| author_sort | Pierre Lechevallier |
| collection | DOAJ |
| description | Abstract A major challenge in wastewater and sewer system monitoring is the development of advanced sensing technologies to improve standard pollutant measurement and allow real-time online detection of emerging contaminants. This study presents a dataset from a 25-week measurement campaign comparing a novel hyperspectral imaging system to state-of-the-art ultraviolet-visible (UV-vis) sensors. The dataset includes 5801 hyperspectral images of raw wastewater, measurements of temperature, ammonium, flow, turbidity, pH, and UV-vis absorbance spectra, as well as 533 grab samples analyzed for conventional pollutants. We also gathered 86 samples after four rain events and analyzed them for twenty organic chemicals, providing insights into the impact of wet weather on pollutant levels. The data collection and processing methodologies are detailed, along with visualizations and analysis. Despite difficulties in the maintenance of some sensors, in particular the ion-selective electrode for ammonium measurement, the dataset’s high temporal resolution, the time span of 25 weeks, and the extensive range of analyzed pollutants make it a valuable resource for advancing the field of urban water management. |
| format | Article |
| id | doaj-art-2c163db8d44e470bab798f1bb2ebf1de |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-2c163db8d44e470bab798f1bb2ebf1de2025-08-20T03:45:44ZengNature PortfolioScientific Data2052-44632025-07-0112111510.1038/s41597-025-05459-xDataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the UV-vis rangePierre Lechevallier0Günter Gruber1Vojtěch Bareš2Nicolas Neuenhofer3Laura Waldner4Abhinit Mahajan5Lena Mutzner6Jörg Rieckermann7Department of Urban Water Management, Swiss Federal Institute of Aquatic Science & Technology (Eawag)Institute of Urban Water Management and Landscape Water Engineering, Graz University of TechnologyDepartment of Hydraulics and Hydrology, Czech Technical University in PragueDepartment of Urban Water Management, Swiss Federal Institute of Aquatic Science & Technology (Eawag)Department of Urban Water Management, Swiss Federal Institute of Aquatic Science & Technology (Eawag)Department of Urban Water Management, Swiss Federal Institute of Aquatic Science & Technology (Eawag)Department of Urban Water Management, Swiss Federal Institute of Aquatic Science & Technology (Eawag)Department of Urban Water Management, Swiss Federal Institute of Aquatic Science & Technology (Eawag)Abstract A major challenge in wastewater and sewer system monitoring is the development of advanced sensing technologies to improve standard pollutant measurement and allow real-time online detection of emerging contaminants. This study presents a dataset from a 25-week measurement campaign comparing a novel hyperspectral imaging system to state-of-the-art ultraviolet-visible (UV-vis) sensors. The dataset includes 5801 hyperspectral images of raw wastewater, measurements of temperature, ammonium, flow, turbidity, pH, and UV-vis absorbance spectra, as well as 533 grab samples analyzed for conventional pollutants. We also gathered 86 samples after four rain events and analyzed them for twenty organic chemicals, providing insights into the impact of wet weather on pollutant levels. The data collection and processing methodologies are detailed, along with visualizations and analysis. Despite difficulties in the maintenance of some sensors, in particular the ion-selective electrode for ammonium measurement, the dataset’s high temporal resolution, the time span of 25 weeks, and the extensive range of analyzed pollutants make it a valuable resource for advancing the field of urban water management.https://doi.org/10.1038/s41597-025-05459-x |
| spellingShingle | Pierre Lechevallier Günter Gruber Vojtěch Bareš Nicolas Neuenhofer Laura Waldner Abhinit Mahajan Lena Mutzner Jörg Rieckermann Dataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the UV-vis range Scientific Data |
| title | Dataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the UV-vis range |
| title_full | Dataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the UV-vis range |
| title_fullStr | Dataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the UV-vis range |
| title_full_unstemmed | Dataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the UV-vis range |
| title_short | Dataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the UV-vis range |
| title_sort | dataset on wastewater quality monitoring with adsorption and reflectance spectrometry in the uv vis range |
| url | https://doi.org/10.1038/s41597-025-05459-x |
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