Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study
Real-time monitoring of energetic-environmental parameters in wastewater treatment plants enables big-data analysis for a true representation of the operating condition of a system, being still frequently mismanaged through policies based on the analysis of static data (energy billing, periodic chem...
Guardado en:
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
MDPI AG
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/a215cb112a104a6b9a01b3658da49333 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| id |
oai:doaj.org-article:a215cb112a104a6b9a01b3658da49333 |
|---|---|
| record_format |
dspace |
| spelling |
oai:doaj.org-article:a215cb112a104a6b9a01b3658da493332021-11-11T15:46:27ZReal-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study10.3390/en142169481996-1073https://doaj.org/article/a215cb112a104a6b9a01b3658da493332021-10-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/21/6948https://doaj.org/toc/1996-1073Real-time monitoring of energetic-environmental parameters in wastewater treatment plants enables big-data analysis for a true representation of the operating condition of a system, being still frequently mismanaged through policies based on the analysis of static data (energy billing, periodic chemical–physical analysis of wastewater). Here we discuss the results of monitoring activities based on both offline (“static”) data on the main process variables, and on-line (“dynamic”) data collected through a monitoring system for energetic-environmental parameters (dissolved oxygen, wastewater pH and temperature, TSS intake and output). Static-data analysis relied on a description model that employed statistical normalization techniques (KPIs, operational indicators). Dynamic data were statistically processed to explore possible correlations between energetic-environmental parameters, establishing comparisons with static data. Overall, the system efficiently fulfilled its functions, although it was undersized compared to the organic and hydraulic load it received. From the dynamic-data analysis, no correlation emerged between energy usage of the facility and dissolved oxygen content of the wastewater, whereas the TSS removal efficiency determined through static measurements was found to be underestimated. Finally, using probes allowed to characterize the pattern of pH and temperature values of the wastewater, which represent valuable physiological data for innovative and sustainable resource recovery technologies involving microorganisms.Maria Rosa di CiccoAntonio MasielloAntonio SpagnuoloCarmela VetromileLaura BoreaGiuseppe GiannellaManuela IovinellaCarmine LubrittoMDPI AGarticledynamic monitoringload factorsKPIpHsensorstemperatureTechnologyTENEnergies, Vol 14, Iss 6948, p 6948 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
dynamic monitoring load factors KPI pH sensors temperature Technology T |
| spellingShingle |
dynamic monitoring load factors KPI pH sensors temperature Technology T Maria Rosa di Cicco Antonio Masiello Antonio Spagnuolo Carmela Vetromile Laura Borea Giuseppe Giannella Manuela Iovinella Carmine Lubritto Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study |
| description |
Real-time monitoring of energetic-environmental parameters in wastewater treatment plants enables big-data analysis for a true representation of the operating condition of a system, being still frequently mismanaged through policies based on the analysis of static data (energy billing, periodic chemical–physical analysis of wastewater). Here we discuss the results of monitoring activities based on both offline (“static”) data on the main process variables, and on-line (“dynamic”) data collected through a monitoring system for energetic-environmental parameters (dissolved oxygen, wastewater pH and temperature, TSS intake and output). Static-data analysis relied on a description model that employed statistical normalization techniques (KPIs, operational indicators). Dynamic data were statistically processed to explore possible correlations between energetic-environmental parameters, establishing comparisons with static data. Overall, the system efficiently fulfilled its functions, although it was undersized compared to the organic and hydraulic load it received. From the dynamic-data analysis, no correlation emerged between energy usage of the facility and dissolved oxygen content of the wastewater, whereas the TSS removal efficiency determined through static measurements was found to be underestimated. Finally, using probes allowed to characterize the pattern of pH and temperature values of the wastewater, which represent valuable physiological data for innovative and sustainable resource recovery technologies involving microorganisms. |
| format |
article |
| author |
Maria Rosa di Cicco Antonio Masiello Antonio Spagnuolo Carmela Vetromile Laura Borea Giuseppe Giannella Manuela Iovinella Carmine Lubritto |
| author_facet |
Maria Rosa di Cicco Antonio Masiello Antonio Spagnuolo Carmela Vetromile Laura Borea Giuseppe Giannella Manuela Iovinella Carmine Lubritto |
| author_sort |
Maria Rosa di Cicco |
| title |
Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study |
| title_short |
Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study |
| title_full |
Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study |
| title_fullStr |
Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study |
| title_full_unstemmed |
Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study |
| title_sort |
real-time monitoring and static data analysis to assess energetic and environmental performances in the wastewater sector: a case study |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/a215cb112a104a6b9a01b3658da49333 |
| work_keys_str_mv |
AT mariarosadicicco realtimemonitoringandstaticdataanalysistoassessenergeticandenvironmentalperformancesinthewastewatersectoracasestudy AT antoniomasiello realtimemonitoringandstaticdataanalysistoassessenergeticandenvironmentalperformancesinthewastewatersectoracasestudy AT antoniospagnuolo realtimemonitoringandstaticdataanalysistoassessenergeticandenvironmentalperformancesinthewastewatersectoracasestudy AT carmelavetromile realtimemonitoringandstaticdataanalysistoassessenergeticandenvironmentalperformancesinthewastewatersectoracasestudy AT lauraborea realtimemonitoringandstaticdataanalysistoassessenergeticandenvironmentalperformancesinthewastewatersectoracasestudy AT giuseppegiannella realtimemonitoringandstaticdataanalysistoassessenergeticandenvironmentalperformancesinthewastewatersectoracasestudy AT manuelaiovinella realtimemonitoringandstaticdataanalysistoassessenergeticandenvironmentalperformancesinthewastewatersectoracasestudy AT carminelubritto realtimemonitoringandstaticdataanalysistoassessenergeticandenvironmentalperformancesinthewastewatersectoracasestudy |
| _version_ |
1718434042459717632 |