Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspective
In this work, operational data collected from four Danish wastewater treatment plants (WWTP) are assessed for quality issues and analyzed to investigate the feasibility of data-driven modeling for control purposes. All plants have permanent N2O sensors installed in the biological reactors, and N2O d...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2024-03-01
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| Series: | Water Practice and Technology |
| Subjects: | |
| Online Access: | http://wpt.iwaponline.com/content/19/3/1016 |
| _version_ | 1797200663567925248 |
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| author | Laura Debel Hansen Peter Alexander Stentoft Daniel Ortiz-Arroyo Petar Durdevic |
| author_facet | Laura Debel Hansen Peter Alexander Stentoft Daniel Ortiz-Arroyo Petar Durdevic |
| author_sort | Laura Debel Hansen |
| collection | DOAJ |
| description | In this work, operational data collected from four Danish wastewater treatment plants (WWTP) are assessed for quality issues and analyzed to investigate the feasibility of data-driven modeling for control purposes. All plants have permanent N2O sensors installed in the biological reactors, and N2O data are collected on the same terms as other operational data. We present and deploy a six-dimensional data quality assessment to the operational data evaluating (1) relevance, (2) accuracy, (3) completeness, (4) consistency, (5) comparability, and (6) accessibility. To increase the accuracy and completeness of the stored data, it is suggested that future initiatives are taken toward the collection and storing of metadata in WWTPs. Furthermore, seasonal variations and time-varying relationships between N2O, nitrogenous variables, and oxygen are investigated and compared across various case plants and process designs. Results show that the quality of the operational data varies substantially between plants. The investigation of time-varying interrelation between N2O and nitrogenous variables showed no clear pattern within or across different case plants. Furthermore, it is recommended that future research should consider adapting models so that more influence is linked to reliable measurements, contrary to assuming that all variables are of equal quality.
HIGHLIGHTS
The quality of operational data from full-scale WWTPs varies substantially.;
Metadata is required to ensure accurate data-driven modeling of N2O dynamics.;
Nitrous oxide measurements show heteroscedasticity across different case plants.;
The relationship between N2O and nitrogenous measurements is time varying.; |
| first_indexed | 2024-04-24T07:35:14Z |
| format | Article |
| id | doaj.art-7c3f518c922641a786a4ad02b66d59f8 |
| institution | Directory Open Access Journal |
| issn | 1751-231X |
| language | English |
| last_indexed | 2024-04-24T07:35:14Z |
| publishDate | 2024-03-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Practice and Technology |
| spelling | doaj.art-7c3f518c922641a786a4ad02b66d59f82024-04-20T07:04:27ZengIWA PublishingWater Practice and Technology1751-231X2024-03-011931016103110.2166/wpt.2024.045045Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspectiveLaura Debel Hansen0Peter Alexander Stentoft1Daniel Ortiz-Arroyo2Petar Durdevic3 Department of Energy, Aalborg University, Esbjerg, Denmark Krüger A/S, Veolia Water Technologies, Aalborg, Denmark Department of Energy, Aalborg University, Esbjerg, Denmark Department of Energy, Aalborg University, Esbjerg, Denmark In this work, operational data collected from four Danish wastewater treatment plants (WWTP) are assessed for quality issues and analyzed to investigate the feasibility of data-driven modeling for control purposes. All plants have permanent N2O sensors installed in the biological reactors, and N2O data are collected on the same terms as other operational data. We present and deploy a six-dimensional data quality assessment to the operational data evaluating (1) relevance, (2) accuracy, (3) completeness, (4) consistency, (5) comparability, and (6) accessibility. To increase the accuracy and completeness of the stored data, it is suggested that future initiatives are taken toward the collection and storing of metadata in WWTPs. Furthermore, seasonal variations and time-varying relationships between N2O, nitrogenous variables, and oxygen are investigated and compared across various case plants and process designs. Results show that the quality of the operational data varies substantially between plants. The investigation of time-varying interrelation between N2O and nitrogenous variables showed no clear pattern within or across different case plants. Furthermore, it is recommended that future research should consider adapting models so that more influence is linked to reliable measurements, contrary to assuming that all variables are of equal quality. HIGHLIGHTS The quality of operational data from full-scale WWTPs varies substantially.; Metadata is required to ensure accurate data-driven modeling of N2O dynamics.; Nitrous oxide measurements show heteroscedasticity across different case plants.; The relationship between N2O and nitrogenous measurements is time varying.;http://wpt.iwaponline.com/content/19/3/1016alternating activated sludge processdata quality assessmentexploratory data analysisgreenhouse gas emissionsheteroscedastic datatime series |
| spellingShingle | Laura Debel Hansen Peter Alexander Stentoft Daniel Ortiz-Arroyo Petar Durdevic Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspective Water Practice and Technology alternating activated sludge process data quality assessment exploratory data analysis greenhouse gas emissions heteroscedastic data time series |
| title | Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspective |
| title_full | Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspective |
| title_fullStr | Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspective |
| title_full_unstemmed | Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspective |
| title_short | Exploring data quality and seasonal variations of N2O in wastewater treatment: a modeling perspective |
| title_sort | exploring data quality and seasonal variations of n2o in wastewater treatment a modeling perspective |
| topic | alternating activated sludge process data quality assessment exploratory data analysis greenhouse gas emissions heteroscedastic data time series |
| url | http://wpt.iwaponline.com/content/19/3/1016 |
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