Real-Time Monitoring and Static Data Analysis to Assess Energetic and Environmental Performances in the Wastewater Sector: A Case Study

Maria Di Cicco,Giuseppe Giannella,Manuela Iovinella,Carmela Vetromile,Carmine Lubritto,Laura Borea,Antonio Spagnuolo,Antonio Masiello

doi:10.3390/en14216948

Abstract

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.

Highlights

Ensuring satisfactory energetic-environmental performance in wastewater treatment plants is a challenge of great interest and relevance for the world of research, because of the many implications for sanitary purposes, and related to the concept of sustainability [1].The academic and experimental experience gained in recent years through direct contact with companies involved in the integrated water service has revealed many weaknesses in the management of these industrial realities [2], which are so valuable for the protection of our habitats and our health
Concerning the stress faced by the plant, observing the results obtained for the organic and hydraulic load factors, it was possible to notice that the plant received a highly fluctuating organic contaminants load during the year, while more regular were the volumetric flowrates received by the system, for which the WWTP almost always works in conditions close to or equal to the maximum sustainable capacity
Using the operational indicators conceived for the evaluation of organic and hydraulic load entering the system, the plant has shown a tendency to be undersized compared to the amount of pollutants and—especially—volumetric flowrates it receives, very often exceeding the maximum design capacity (45.000 PE)

Summary

Introduction

Ensuring satisfactory energetic-environmental performance in wastewater treatment plants ( referred to as WWTP) is a challenge of great interest and relevance for the world of research, because of the many implications for sanitary purposes, and related to the concept of sustainability [1].The academic and experimental experience gained in recent years through direct contact with companies involved in the integrated water service has revealed many weaknesses in the management of these industrial realities [2], which are so valuable for the protection of our habitats and our health. For the recovery of resources from the wastewater sector, several strategies and technologies are being studied in recent years, an example of which is the use of microalgae to trap these elements in a biomass matrix, commercially expendable for the extraction of many valuable by-products or energy [12]. The use of these practices, is still at a testing stage in most of the realities that have chosen to adopt these solutions for the increase of their performance indices [13]. The second tool, on the other hand, is necessary to learn in a satisfactory way the operating status of a system; it is well-known that only the use of real-time monitoring and management systems mediated by proper sensing devices can enable a big data analysis statistically representative of the system, as well as the development of predictive models that can support the managing bodies in the decision-making processes related to the proper management of the plants [16]

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Results

Conclusion