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

A review of pollution-based real-time modelling and control for sewage systems

Conventional solutions for wastewater collection focus on reducing overflow events in the sewage network, which can be achieved by adapting sewer infrastructure or, a more cost-effective alternative, by implementing a non-engineering management solution. The state-of-the-art solution is centered on Real-Time Control (RTC), which is already resulting in a positive impact on the environment by decreasing the volume of wastewater being discharged into receiving waters. Researchers have been continuing efforts towards upgrading RTC solutions for sewage systems and a new approach, although rudimentary, was introduced in 1997, known as Pollution-based RTC (P-RTC), which added water quality (concentration or load) information explicitly within the RTC algorithm. Formally, P-RTC is encompassed of several control methodologies using a measurement or estimation of the concentration (i.e. COD or ammonia) of the sewage throughout the network. The use of P-RTC can result in a better control performance with a reduction in concentration of overflowing wastewater observed associated with an increase of concentration of sewage arriving at the Wastewater Treatment Plant (WWTP). The literature revealed that P-RTC can be differentiated by: (1) implementation method; (2) how water quality is incorporated, and (3) overall control objectives. Additionally, this paper evaluates the hydrological models used for P-RTC. The objective of this paper is to compile relevant research in pollution-based modelling and real-time control of sewage systems, explaining the general concepts within each P-RTC category and their differences.

Modeling spatiotemporal domestic wastewater variability: Implications for measuring treatment efficiency

Continuously measuring the efficiency of wastewater treatment plants is crucial to progress in sanitation management. Regulations for decentralized wastewater treatment plants (WWTP) can include rudimentary specifications for sporadic sampling, unencouraging continuous monitoring, and missing crucial domestic wastewater (DW) variability, especially in low- and middle-income countries. However, few studies have focused on modeling and understanding spatiotemporal DW variability. We developed and calibrated an agent-based model (ABM) to understand spatial and temporal DW variability, its role in estimated WWTP efficiency, and provide recommendations to improve sampling regulations. We simulated DW variability at various spatial and temporal resolutions in Santa Ana Atzcapotzaltongo, Mexico, focusing on chemical oxygen demand (COD) and total suspended solids (TSS). The model results show that DW variability increases at higher spatiotemporal resolutions. Without a proper understanding of DW variability, treatment efficiency can be overestimated or underestimated by as much as 25% from sporadic sampling. Sensor measurements at 6-min intervals over 3 hours are recommended to overcome uncertainty resulting from temporal variability during heavy drinking water demand in the morning. Reporting of sewage catchment areas, population sizes, and sampling times and intervals is recommended to compare WWTP efficiencies to overcome uncertainty resulting from spatiotemporal variability. The proposed model is a useful tool for understanding DW variability. It can be used to estimate the impact of spatiotemporal variability when measuring WWTP efficiencies, support improvements to sampling regulations for decentralized sanitation, and alternatively for designing and operating WWTPs.

Galdieria sulphuraria ACUF427 Freeze-Dried Biomass as Novel Biosorbent for Rare Earth Elements

Rare earth elements (REEs) are essential components of modern technologies and are often challenging to acquire from natural resources. The demand for REEs is so high that there is a clear need to develop efficient and environmentally-friendly recycling methods. In the present study, freeze-dried cells of the extremophile Galdieria sulphuraria were employed to recover yttrium, cerium, europium, and terbium from quaternary-metal aqueous solutions. The biosorption capacity of G. sulphuraria freeze-dried algal biomass was tested at different pHs, contact times, and biosorbent dosages. All rare earths were biosorbed in a more efficient way by the lowest dose of biosorbent, at pH 4.5, within 30 min; the highest removal rate of cerium was recorded at acidic pH (2.5) and after a longer contact time, i.e., 360 min. This study confirms the potential of freeze-dried cells of G. sulphuraria as innovative ecological biosorbents in technological applications for sustainable recycling of metals from e-waste and wastewater.

Characterizing passenger-ship emissions: towards improved sustainability for MedMar fleet (gulf of Naples)

Promoting energetic and environmental sustainability in the naval sector requires a necessary understanding of the energy demand of vessels and of the factors affecting it. This article shows the results of a study conducted by the shipping company MedMar aimed at acquiring a detailed analysis of the energetic performances of its fleet. The study involved the analysis of fuel consumption and emissions of the fleet using a specific software and under different scenarios, assuming the navigation speed and the cargo level of the vessels as reference parameters. Simulations also provided a comparison, concerning emissions and externalities, between ships and two different means of transport. The purpose of this study was to identify potential areas of improvement, where ad hoc strategies could be used to further optimise the energetic and environmental performance of MedMar fleet and mitigate its impact on the delicate ecosystem of the gulf of Naples, where the fleet sails.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12053-022-10064-7.

Application of Neural Networks and Regression Modelling to Enable Environmental Regulatory Compliance and Energy Optimisation in a Sequencing Batch Reactor

Real-time control of wastewater treatment plants (WWTPs) can have significant environmental and cost advantages. However, its application to small and decentralised WWTPs, which typically have highly varying influent characteristics, remains limited to date due to cost, reliability and technical restrictions. In this study, a methodology was developed using numerical models that can improve sustainability, in real time, by enhancing wastewater treatment whilst also optimising operational and energy efficiency. The methodology leverages neural network and regression modelling to determine a suitable soft sensor for the prediction of ammonium-nitrogen trends. This study is based on a case-study decentralised WWTP employing sequencing batch reactor (SBR) treatment and uses pH and oxidation-reduction potential sensors as proxies for ammonium-nitrogen sensors. In the proposed method, data were pre-processed into 15 input variables and analysed using multi-layer neural network (MLNN) and regression models, creating 176 soft sensors. Each soft sensor was then analysed and ranked to determine the most suitable soft sensor for the WWTP. It was determined that the most suitable soft sensor for this WWTP would achieve a 67% cycle-time saving and 51% electricity saving for each treatment cycle while meeting the criteria set for ammonium discharges. This proposed soft sensor selection methodology can be applied, in full or in part, to existing or new WWTPs, potentially increasing the adoption of real-time control technologies, thus enhancing their overall effluent quality and energy performance.

A Review on the Reliability and the Readiness Level of Microalgae-Based Nutrient Recovery Technologies for Secondary Treated Effluent in Municipal Wastewater Treatment Plants

Algae-based wastewater treatment technologies are promising green technologies with huge economical potential and environmental co-benefits. However, despite the immense research, work, and achievement, no publications were found wherein these technologies have been successfully applied in an operational environment for nitrogen and phosphorus removal of secondary treated effluent in municipal wastewater treatment plants. Based on a literature review and targeted comprehensive analysis, the paper seeks to identify the main reasons for this. The reliability (considering inlet wastewater quality variations, operating conditions and process control, algae harvesting method, and produced biomass) as well as the technology readiness level for five types of reactors are discussed. The review shows that the reactors with a higher level of control over the technological parameters are more reliable but algal post-treatment harvesting and additional costs are barriers for their deployment. The least reliable systems continue to be attractive for research due to the non-complex operation and relieved expenditure costs. The rotating biofilm systems are currently undertaking serious development due to their promising features. Among the remaining research gaps and challenges for all the reactor types are the identification of the optimal algal strains, establishment of technological parameters, overcoming seasonal variations in the effluent’s quality, and biomass harvesting.

Extremophilic Microalgae Galdieria Gen. for Urban Wastewater Treatment: Current State, the Case of “POWER” System, and Future Prospects

Over the past decades, wastewater research has increasingly focused on the use of microalgae as a tool to remove contaminants, entrapping nutrients, and whose biomass could provide both material and energy resources. This review covers the advances in the emerging research on the use in wastewater sector of thermoacidophilic, low-lipid microalgae of the genus Galdieria, which exhibit high content of protein, reserve carbohydrates, and other potentially extractable high-value compounds. The natural tolerance of Galdieria for high toxic environments and hot climates recently made it a key player in a single-step process for municipal wastewater treatment, biomass cultivation and production of energetic compounds using hydrothermal liquefaction. In this system developed in New Mexico, Galdieria proved to be a highly performing organism, able to restore the composition of the effluent to the standards required by the current legislation for the discharge of treated wastewater. Future research efforts should focus on the implementation, in the context of wastewater treatment, of more energetically efficient cultivation systems, potentially capable of generating water with increasingly higher purity levels.