Efficient management of a sewer system includes the control of the conveyed wastewater quality to adequately operate treatment plants and protect the receiving water bodies. Moreover, these systems are vulnerable to either accidental spills or intentional unauthorized discharges. To properly manage them, a limited number of sensors could be placed at different locations to monitor the water quality. In this paper, multiobjective and single-objective optimization procedures to optimally locate sensors in sewer systems are proposed, tested, and compared. The multiobjective procedures include objective functions related to information theory (IT procedure), detection time and reliability (DR procedure), and a combination of them (IT_DR procedure). The single-objective procedures include a greedy-based objective function (GR procedure) and a merged objective function (DR_IT_GR procedure). The procedures show a similar performance when applied on a small network, whereas in a real system, the results show that (1) the IT-based method can be effectively used as a filtering technique; (2) the DR_IT_GR procedure outperforms the other multiobjective ones; and (3) the GR procedure is very efficient in finding the Pareto extreme solutions.

Wastewater quality monitoring is receiving growing interest with the necessity of developing new strategies for controlling accidental and intentional illicit intrusions. In designing a monitoring network, a crucial aspect is represented by the sensors’ location. In this study, a methodology for the optimal placement of wastewater monitoring sensors in sewer systems is presented. The sensor location is formulated as an optimization problem solved using greedy algorithms (GRs). The Storm Water Management Model (SWMM) was used to perform hydraulic and water-quality simulations. Six different procedures characterized by different fitness functions are presented and compared. The performances of the procedures are tested on a real sewer system, demonstrating the suitability of GRs for the sensor-placement problem. The results show a robustness of the methodology with respect to the detection concentration parameter, and they suggest that procedures with multiple objectives into a single fitness function give better results. A further comparison is performed using previously developed multi-objective procedures with multiple fitness functions solved using a genetic algorithm (GA), indicating better performances of the GR. The existing monitoring network, realized without the application of any sensor design, is always suboptimal.

Chromium(VI) contamination is carcinogenic and largely anthropogenic, stemming from specific industries. With Bangladesh experiencing rapid industrialization, the increasing number of industries necessitates an economic and sustainable secondary treatment process to maintain acceptable chromium levels. Phytoremediation, an environmentally friendly biochemical technique, has been extensively researched, particularly in the context of constructed wetlands. However, due to land scarcity and legal issues a constructed wetland is not the most viable option. In this study, three native aquatic plants—Eichhornia crassipes (Water Hyacinth), Pistia stratiotes (Water Lettuce), and Lemna minor (Duckweed)—were chosen to evaluate their effectiveness in removing chromium from wastewater. These plants underwent testing with five different chromium concentrations (1 mg/L, 2 mg/L, 3 mg/L, 4 mg/L, 5 mg/L) and two pH values (6 and 8) using natural ditch water as the feed solution. All the experiments were performed for 7 days in duplicate, along with a control experiment of chromium without plants. The study was conducted at Shahjalal University of Science and Technology campus, Bangladesh, from May 25 to June 1, 2023. Atomic Absorption Spectrometer was employed to measure Cr(VI) concentration, revealing average chromium removal rates of 29.4%, 81.1%, and 81.5% for Eichhornia crassipes, Pistia stratiotes, and Lemna minor, respectively, after seven days. Notably, on day three, Lemna minor exhibited the highest average removal efficiency at 84.7%.

Microcoleus sp. is a versatile microorganism widely available in the environment and easily culturable. Hence, there is a progressing demand for wastewater treatment using this novel biosorption medium. The design of such a treatment method may be defined as an optimisation problem of algal dose and hydraulic retention time for attaining an adequate removal efficiency of heavy metals (Cr6+, Ni2+, and Zn2+) and nutrients (PO43- and NO3-). Batch experiments on synthetic wastewater were conducted for algal doses varying from 0.5 to 25 g/L and hydraulic retention times from 1 to 7 days. Significant removal efficiencies of greater than 90% were observed for the heavy metals, 75% of PO43- removal, and no removal of NO3- was found under continuous daylight. The single-factor ANOVA test confirms the statistical significance of the varying parameters on the pollutant removal efficiency. Langmuir and Freundlich's adsorption isotherms indicate satisfactory adsorption of the contaminants about the separation factor and the adsorption intensity constant. The R2 > 0.67 and RMSE < 0.21 suggest a good fit of the modelled data. Following this, the study suggests that the use of Microcoleus sp. is a prospective bioremediation technique for industrial and municipal wastewater.