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Article

Saving Energy in Biological Wastewater Treatment by Using Extremely Low-Frequency Electric Field—Pilot-Scale Study

1
Research-Development Institute for Environmental Protection Technologies and Equipment, S.C. ICPE Bistriţa S.A., Parcului Str., No. 7, 420035 Bistrita, Romania
2
National Institute for Research and Development in Electrical Engineering ICPE-CA Bucharest, 313 Splaiul Unirii, 030138 Bucharest, Romania
3
Faculty of Electrical Engineering, Technical University of Cluj Napoca, G. Bariţiu Str., No. 26-28, 400027 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(15), 11670; https://doi.org/10.3390/su151511670
Submission received: 20 June 2023 / Revised: 25 July 2023 / Accepted: 25 July 2023 / Published: 28 July 2023
(This article belongs to the Special Issue Sustainable Development of Material and Engineering)

Abstract

:
The results of a pilot-scale study on the influence of electric field use for stimulating the active sludge in the biological purification tank of a small capacity wastewater treatment plant (up to 600 m3/day) are presented. Through specific comparative chemical tests (DO, COD, N-NH4, and Pt) it was found that, by applying a sinusoidal electric field of 5 Vrms/m at 49.9 Hz on the active sludge suspension, the overall pollutant denitrification process speed is doubled compared with the reference case when no stimulation is used. Also, under identical operating conditions, the residual pollutant content of the biological treatment tank outlet water is reduced approximately three times for COD and approximately two times for N-NH4 and Pt compared to the reference tank. These findings lead to the conclusion that, by stimulating the active sludge microbial activity of the wastewater treatment plants by a sinusoidal electric field of 5 Vrms/m at 49.9 Hz, the time of the biological purification treatment can be reduced by approx. 50%. This leads to a corresponding decrease in energy consumption, which usually represents more than 30% of a wastewater treatment plant’s specific electricity consumption.

1. Introduction

In the current context of climate change and the energy crisis, the efforts made for reaching the environmental targets are of great importance. From this perspective, there is a constant need to apply a rational management of both natural freshwater and energy resources. Since life is supported by the existence and availability of water resources, respectively, by the quality of surface and underground waters, several studies investigate this issue. The research performed in [1] shows the importance of land classification regarding its vulnerability to pollutant leakages. The study reported in [2] approaches the effect of the global changes on the groundwater resources, while refs. [3,4] investigate the surface water quality from rivers and shallow wells and asses its potential to be used as drinking water. Some studies, like the one reported in [5], aims to determine the presence of some specific pollutants (e.g., arsenic) in drinking water. The importance of water quality in significant water bodies like Danube River is tackled in [6], both concerning the oxygen content necessary for fish welfare and the heavy metals content due to tributaries and wastewater discharge. On the other hand, human activities result in significant wastewater amounts—both domestic and industrial. Domestic wastewaters contain organic pollutants, nitrogen compounds—ammonium [7], phosphorus compounds from detergents and products for water softening [8,9], as well as microplastics [10,11], which are hardly biodegradable [12,13]. The majority of industrial wastewater comes from diverse areas, such as tannery [14,15], mining [16], pharmaceuticals [17,18], the food industry [19,20], the textile industry [21,22,23], etc.
The quality of surface water and groundwater [24,25,26,27,28] is largely determined by the organic pollutants content (such as petroleum products [29], xenobiotics [30,31], hardly biodegradable plastics [32,33], etc.), inorganic pollutants (such as phosphates and polyphosphates [8,9], heavy metals [16,34,35], etc.), biohazardous residues [36,37], etc., in discharged wastewater.
Wastewater treatment is of particular importance since it reduces the pollutant content below the concentration limits set by specific regulations for discharge into surface waters [38,39,40]. In order to not exceed the imposed pollution levels, different processes are applied in wastewater treatment plants, such as physical processes (filtration, sedimentation), chemical processes (pH correction, precipitation, etc.), and microbiological processes [40] (metabolism of organic pollutants, etc.). All these treatment stages involve significant energy consumption, primarily determined by the pollutant content of the water, the processing temperature, and the purification technology [20,41,42,43,44] that is implemented. The values reported in the literature range from 2.8 kWh/m3 [45] for wastewater treatment plants up to 1000 m3/day, to 0.240 kWh/m3 in large wastewater treatment plants, that are usually equipped with digesters for biogas production [46,47].
Advanced purification is achieved by aerobic and/or anaerobic biological treatment. This implies the use of active sludge microorganisms [38,40,48,49] such as aerobic and anaerobic bacteria, microalgae, and molds [50,51]. These microorganisms metabolize the organic pollutants from the wastewater processed in the mechanical and chemical stages, including those containing nitrogen and phosphorus [52]. Since these processes are relatively slow, biochemical treatment takes a long time. Therefore, the consumption of energy during the biochemical purification stages is relatively high and is due to the operation of the recirculation pumps, of the air compressors for oxygenation, of the mechanical agitators, etc. As reported in the literature, the energy consumption associated with the biochemical treatment stages usually represents more than 60% of a wastewater treatment plant’s total energy consumption [45,47,48,52]. As reported in [48,50,53], bioactivators can be used to increase the metabolism rate and thus to diminish the biochemical treatment time. By doing so, the related energy consumption can be reduced.
Some experimental studies have shown that extremely low-frequency (ELF) electromagnetic fields produce changes in the microorganisms metabolism [54,55,56,57]. It has been found that changes take place at certain “representative” frequencies [56,57,58] that can be determined by dielectric spectroscopy [56,58,59]. This method allows for the determination of the frequencies at which processes that change the charge carriers number (such as amino acid condensation and/or protein hydrolysis reactions or enzyme formation processes) take place in the biomass.
The importance of establishing the proper electrical stimulation frequency is approached in many studies and research works. Thus, recent experimental studies [60] revealed that the proper frequency used in the electrical field stimulation of the hydrogenotrophic Hydrogenophaga, Thauera, and Rhodospirillales significantly improved the electron transfer efficiency for aniline degradation and nitrogen metabolism. It showed good results also in the treatment of wastewater containing antibiotics [61] as well as in increasing the nitrogen and phosphorus removal efficiency in the case of filamentous algae Tribonema sp. [62].
The active sludge from wastewater treatment plants’ bioreactors contains numerous species of bacteria, microalgae, and molds. The behavior of these species in an extremely low-frequency electric field (1–500 Hz) was studied using the dielectric spectroscopy technique [58,59], determining the proper electrical stimulation frequencies. In [63], the comparative laboratory experimental results (with and without stimulation in the electric field) regarding the removal efficiency of pollutants from synthetic wastewater are presented.
This selective behavior at representative frequencies can be explained by synchronisms in the steps of ion-pumping in individual enzymes via a hold-and-release mechanism [55]. A review on microbial cultures biostimulation with applications in biotechnological processes is presented in [64]. Experimental laboratory studies and field determinations (case studies) have shown that, at industrial frequencies of 50 Hz, the microorganisms’ activity (including Aspergillus niger) is stimulated, resulting in the biodeterioration of both the insulation of underground power cables and underground metallic pipelines [13,65,66,67] as well as of some painting materials [12]. It is to be noted that intense electric fields applied to microorganism cultures result in membrane permeabilization and subsequently the leakage of intracellular compounds [68]. Recently, it was reported that, under the influence of the periodic direct current, the algal biomass growth of Scenedesmus obliquus and its lipid yield are significantly improved [69].
Aiming to reduce energy consumption and taking into account the results of the studies above (in particular the information reported in [58,59,69,70]), a pilot for the ELF electric field activation of microbial flora in an operating wastewater treatment plant was designed and implemented [71]. The aim of this paper is to make a comparative analysis of the biological treatment processes’ operating parameters for the pilot-scale wastewater treatment plant with and without active sludge ELF stimulation.

2. Materials and Methods

To determine the ELF electric field influence on the microbial flora from active sludge in real operating conditions, a small capacity wastewater treatment plant of 600 m3/day was chosen. The plant is operating in the northern part of Romania, in Romuli village, BN County (Figure 1).
Figure 1 shows that the experimental wastewater treatment plant has two identical biological purification lines (BgT-1 and BgT-2), with parallelepipedal tanks (bioreactors) open on top.
The diagram of the wastewater purification technological flow in the experimental wastewater treatment plant is shown in Figure 2.
Figure 2 shows that the wastewater is treated by mechanical purification (MPT), whereby solid particles are removed by sedimentation and coarse filtration. From the MPT, the water passes into the homogenization tank (HT), where the pH is corrected under continuous agitation (lime dosing) and flocculants are added (double iron and aluminum sulphate) for suspended particles sedimentation. From HT, the water is taken by IP-1 and IP-2 pumps into the two parallel biological treatment lines BgT-1 and BgT-2. Aerobic and anaerobic conditions (bubbling by AP1 and AP2 air pumps, and mechanical agitation with AP1 and AP2 switched off, respectively) are provided sequentially in these bioreactors. The active sludge in the treated water from BgT-1 and BgT-2 is recirculated with the help of RP-1 and RP-2 pumps until the pollutant content of the water comes below the accepted levels in the environmental regulations for discharge into surface waters. The depleted biomass from BgT-1 and BgT-2 biological treatment lines is separated by sedimentation, filtration, and dewatering (SDS); the extracted sludge is used as a fertilizer in agriculture. After sludge separation, the treated water is disinfected (DI) and discharged into the Sălăuța mountain River near the wastewater treatment plant.
In order to enable the process control in Figure 2, the wastewater treatment plant in Figure 1 is equipped with appropriate sensors and transducers (pH, temperature, dissolved oxygen concentration, turbidity, flow meters, level transducers, etc.). The purification control at the set parameters is automatically carried out by a process computer. On the basis of the acquired data from the technological flow (Figure 2), it controls the electrical consumers (pumps, agitators, solenoid valves, etc.) [72] according to the set program.
To comparatively assess the ELF electric field effect on the microbial flora in the active sludge, polarization electrodes were fitted at the biological purification tank ends of the BgT-2-line (Figure 3).
The selection of the polarization electrode material was conducted by taking into account the dissolution rate under the given operating conditions (alternative current polarization in treated water). Electrochemical and gravimetric tests showed that austenitic steel AISI 304 has a dissolution rate of approximately 4 × 10−5 g/Ah—more than 10,000 times less than in usual carbon steels; this is approximately equal to the dissolution rate, under similar conditions, of high-silicon cast irons with 12% Si content [73]. Therefore, the electrodes from Figure 3, fitted with “barrel”-type insulating elements and insulated conductor wires [71], were made of a 2 mm thick perforated sheet of AISI 304. Based on the data reported in [58] and [59], by the polarization electrodes connection to a power supply having sinusoidal output voltage with programmable frequency in the ELF range (between 5 and 500 Hz), an electric field of 5 Vrms/m at 49.9 Hz was applied to the active sludge suspension in the treated water.
To ensure the stimulation of the ELF electric field of the active sludge microbial flora, the BgT-2 bioreactor was equipped with several components and devices, like ELF power supply, cables, polarizing electrodes, etc. Their total cost, including labor, represented 0.05% of the initial investment. The energy consumption of the ELF power supply is up to 14 kWh/month. This is negligible (0.3%) compared to the average total energy consumption of BgT-2, which is 4500 kWh/month. The maintenance costs related to the ELF electric field stimulation system are also negligible compared to the maintenance costs of BgT-2. These primarily include revisions and repair works to the mechanical agitators, recirculation pumps, sensors, transducers, etc. This economic benefit related to the operation and maintenance of the proposed stimulation system represents a significant advantage over other similar solutions. It should be mentioned that the studies reported in the literature are performed on laboratory-scale systems, like the lab-scale sequential batch reactors in [60]. When referring to the real scale, a series of advantages and disadvantages have been reported, ref. [61] like how the initial investment represents one third to one half of a conventional wastewater treatment plant, the greenhouse gases emissions are lower, but the necessary land to be occupied by the plant is 9 times higher. Over these solutions, the proposed equipment can be easily integrated into an already operational plant, leading to supplementary economic benefits.
Under identical operating conditions (treated wastewater pollutant content, inlet flow rates, processing temperature, air flow rates and bubbling times, recirculation rates), comparative chemical tests of water from BgT-1 and BgT-2 were performed. Comparative chemical tests were made on wastewater samples collected simultaneously from the BgT-1 (reference—without applied electric field) and BgT-2 (with ELF electric field bioactivity stimulation) inlet, as well as on samples of biologically treated water from the BgT-1 and BgT-2 outlet:
-
Dissolved oxygen—DO [mg/L] with a portable meter HQ40d, Intellical™ LDO101 Probe (Hach-Langhe);
-
Chemical oxygen demand—COD [mg/L], in accordance with [74] ISO 6060-1989 (Dichromate method), with an LCK 114/Cuvette Test (Hach-Langhe);
-
Ammonium-N-NH4 [mg/L]—in accordance with ISO 7150-1, DIN 38406 E5-1, and UNI 11669:2017 (Indophenol Blue method) [75,76,77], with an LCK 303, 304/Cuvette Test (Hach-Langhe);
-
Phosphate (ortho/total)—Pt [mg/L]—in accordance with ISO 6878-1-1986 [78], (Phosphormolybdenum Blue method), with an LCK 348, 350/Cuvette Test (Hach-Langhe).
Tests were made for different processing temperatures, measured in BgT-1 and BgT-2 tanks, corresponding to different climatic conditions (including winter, Figure 4).
Also, during operation, the dissolved oxygen concentration variations were comparatively monitored by D02-903-type oxygen transducers supplied by TriOS Mess -und Datentechnik GmbH installed in BgT-1 and BgT-2.

3. Results and Discussion

Comparative results of the chemical analyses performed on wastewater samples from the biological processing inlet and from the reference BgT-1 and BgT-2 outlet (with active sludge stimulated by exposure to electric field of 5 Vrms/m at 49.9 Hz) are summarized in Table 1. The data are monitored at different times of the year (respectively, ambient temperature, Figure 1 vs. Figure 4), determining the processing temperatures (identical in BgT-1 and BgT-2) and the processing conditions (identical inlet flows and recirculation rates).
The analysis of the data in Table 1 shows that the pollutants content (COD, N-NH4, and Pt) in the wastewater from the biological treatment stages is not constant. This is due to the behavior and seasonal habits of the population connected to the sewage network. Therefore, for COD and N-NH4, values between 1340 and 1550 mg/L and 43.9 and 40.5 mg/L were recorded. It can be seen that as the temperature rises, COD increases, while N-NH4 decreases. Large seasonal differences were recorded for Pt—relatively high values (6.1 g/L) were recorded in the summer months, while lower values were recorded in winter (4.4 g/L). This fact suggests that the population uses more detergents in warmer periods. In all investigated periods, the residual pollutant content at the BgT-1 outlet (reference) is within the accepted limits. According to Romanian environmental regulations NTPA-001/2002, there is a set maximum of 125 mg/L for COD, 15 mg/L for N-NH4, and 2 mg/L for Pt. The average recorded values were of 123 mg/L, 14.96 mg/L, and 1.93 mg/L, respectively. Comparing the residual pollutant content at the BgT-1 (row 3, Table 1) and BgT-2 (row 4, Table 1) outlet, it is noticed that the recorded values of N-NH4 and Pt at BgT-2 are lower than the reference. An average of 7.4 mg/L was recorded for N-NH4, and 0.97 mg/L for Pt, which is approximately half compared to the reference. It is also noted that the COD is approximately three times lower at BgT-2 (average 41 mg/L) than at BgT-1 (123 mg/L). The values are in good agreement with the DO values recorded at the outflow of BgT-1 (average 2.4 mg/L) and BgT-2 (average 6.5 mg/L).
The data in Table 1 recorded at the pilot are in good agreement with the values reported in [59], measured under laboratory conditions, in synthetic wastewater with 3220 mg/L COD, 67.5 mg/L N-NH4, and 10.6 mg/L Pt, respectively. The residual pollutant content evolution reported in [59] and the comparative values of rows 3 and 4 in Table 1 demonstrate the same benefits: the pollutant metabolism speed, especially the one of the organic pollutants, increases more than two times by microbial flora stimulation in 5 Vrms/m electric field at 49.9 Hz. This finding reveals that, for active sludge stimulation in 49.9 Hz ELF field, the biological treatment time is reduced by more than 50% for the same water purification degree. This leads to a reduction in the mechanical mixer, recirculation, and aeration pumps’ operation time. Therefore, the specific energy consumption of the equipment involved in the biological treatment stage decreases by about 50%.
The comparative evolution of dissolved oxygen recorded every 4 min, on 3 February 2022 in BgT-1 and BgT-2 biological purification tanks, is shown in Figure 5.
The analysis of Figure 5 showed that the DO level in the biological purification tanks presents cyclic variations—it increases during air bubbling periods and decreases during anaerobic periods (mechanical agitation, without air bubbling). The average values recorded were 3.184 mg/L in BgT-1 and 8.407 in BgT-2, respectively. At identical inflow and recirculation rates in BgT-1 and BgT-2, these values indicate that the average organic pollutant content in BgT-1 is approximately three times higher than in BgT-2, which is in good agreement with the data in Table 1.
During air bubbling and after compressor shutdown, the DO is consumed by the oxidation processes of ammonia nitrogen pollutants, a process that is carried out by aerobic autotrophic bacteria [79,80] in two stages, (1) and (2), respectively:
2NH4+ + 3O2 → 2NO2 + 2H2O + 4H+,
2NO2 + O2 → 2NO3,
The overall oxidation reaction of ammonia nitrogen pollutants is (3):
NH4+ + 2O2 → NO3 + H2O + 2H+,
Under these conditions, it is considered that the decreasing slopes of dissolved oxygen (ΔDO), in the time periods (Δt) when the air compressors are shutdown, represent the speed of the overall oxidation process (3) Vox, according to Figure 6, and therefore it results in (4):
Vox = ΔDO/Δt,
The results obtained by processing the DO values acquired over time (Figure 5) are summarized in Table 2.
The analysis of the data in Table 2 revealed that the aerobic autotrophic activity of the bacteria involved in process (3) is dependent on the water temperature in the biological purification tanks by the k process speed constant, which according to Arhenius’ relation is (5):
k = A e E a / R T
where A —the pre-exponential factor, Ea—the process activation energy, R—the gas constant, and T—the absolute temperature.
Table 2 also shows that the speed of dissolved oxygen consumption ΔDO/Δt in BgT-2 is systematically approximately two times higher than in BgT-1. This suggests that, under identical temperature and N-NH4 conditions, the process activation energy (3) controlled by aerobic autotrophic bacteria decreases significantly in BgT-2 under the influence of the applied ELF electric field.
Under mechanical agitation and without air bubbling, the denitrification process takes place due to heterotrophic bacteria by re-mineralizing the organic pollutants (by oxidation to CO2) and nitrates (by reduction to N2) [79,80], according to the overall reaction (6):
5Corganic + 4H+ + 4NO3 → 5CO2↑ + 2N2↑ + 2H2O,
From (1), (2), (3), and (6), it can be seen that, after complex biological purification processes, the organic and nitrogenous pollutants in the wastewater are converted into gaseous products (CO2 and N2 which are released in atmosphere) and biomass (spent sludge, which is extracted by sedimentation and filters).
Figure 7 shows a polarization electrode extracted from BgT-2 after 5 days of operation.
Figure 7 shows massive deposits of biomass, especially in the upper part of the electrode. This suggests that, probably stimulated by the applied ELF electric field [13], the microalgae have also developed in the complex microbial flora of the activated sludge [49] in the upper part of the basin, where there are favorable conditions—light and CO2. Taking into account these findings, it is considered appropriate to continue the research in order to develop a bioreactor with intensive growth using the ELF electric field stimulation and under controlled microalgae conditions (for nutrient use and/or raw material for the pharmaceutical industry). We consider that the major challenge of this research and development will be to determine the optimal applied electric field intensities and the “representative” frequencies [56,58,59] in the ELF domain at which biochemical processes (specific to the algal species and culture medium) occurring during periods of light and dark are stimulated.

4. Conclusions

The influence of the ELF sinusoidal electric field on the processes controlled by microorganisms in the biological purification stages was studied in a pilot-scale study by performing specific chemical tests within a small-capacity wastewater treatment plant (up to 600 m3/day). Thus, in order to identify this influence, several tests were performed at different temperatures as follows: two similar treatments tanks were chosen to be simultaneously monitored; to one tank the ELF electric field was applied, while to the other tank there was not used any stimulation. This procedure enabled the comparative study of the effect which the electric field has on the microorganisms activity from the wastewater.
Experimental data were acquired from both treatment tanks—the reference one (no ELF electric field exposure) and the one to which a sinusoidal electric field of 5 Vrms/m at 49.9 Hz was applied. The comparative analysis of these data revealed that, under identical operating conditions (inlet pollutants, inlet flow and recirculation rates, aeration times and flow rates, as well as identical temperatures), the biological purification processes are significantly accelerated by the stimulation of the electric field.
The research showed that by exposing the active sludge suspension to the electric field, the residual pollutant content (measured at the biological purification tank outlet) is significantly lower, i.e., approximately three times for COD and approximately two times for N-NH4 and Pt. By processing the DO content evolution data of the treated water in aerobic (air bubbling) and anaerobic (without air bubbling, only mechanical agitation) periods, it was identified that under the influence of the applied electric field, the speed of the overall denitrification process is approximately two times higher than the reference (without the electric field being applied).
These experimental findings (pilot-scale study) lead to the conclusion that by the active sludge microbial activity stimulation in wastewater treatment plants with a sinusoidal electric field of 5 Vrms/m at 49.9 Hz, the biological purification treatment time (including the related electricity consumption—air pumps, recirculation pumps, etc.) can be reduced by approximately 50% without influencing the purification degree (residual pollutant content).

Author Contributions

C.B., A.T. and I.L.—conceptualization and methodology, I.L., A.V. and G.C.—writing—review and editing, M.J., A.C., A.V. and D.-D.M.—literature review and investigation, A.T. and A.C.—formal analysis, G.C. and D.-D.M.—investigation and data analysis C.B., M.J., and I.L.—results interpretation. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by three grants of the Ministry of Research, Innovation and Digitization, CCCDI—UEFISCDI, project number PN-III-P2-2.1-PTE-2019-0139, project number PN-III-P2-2.1-PTE-2021-0075, and 25PFE/2021 within PNCDI III.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The research data can be provided upon request to the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Paltineanu, C.; Dumitru, S.I.; Lăcătușu, A.R. Assessing Land Susceptibility for Possible Groundwater Pollution due to Leaching—A Case Study on Romania. Carpathian J. Earth Environ. Sci. 2022, 17, 49–57. [Google Scholar] [CrossRef]
  2. Olichwer, T. Long-term variability of water resources in mountainous areas: Case study-Kłodzko region (SW Poland). Carpathian J. Earth Environ. Sci. 2019, 14, 29–38. [Google Scholar] [CrossRef]
  3. Burcă, S.; Indolean, C. The water quality of some shallow wells from Harghita county (Sâdominic commune), Romania. Stud. UBB Chem. 2021, LXVI, 115–125. [Google Scholar] [CrossRef]
  4. Mbaka, P.K.; Mwangi, J.K.; Kiptum, C.K. Assessment of water quality in selected shallow wells of Keiyo Highlands, Kenya. Afr. J. Sci. Technol. Innov. Dev. 2017, 9, 329–338. [Google Scholar] [CrossRef]
  5. Zubair, S.; Faridi, T.A.; Rana, M.S.; Raza, S.A.; Arshad, M. Physicochemical Analysis of Drinking Water for the Detection of Arsenic from Manga Mandi Punjab, Pakistan. Carpathian J. Earth Environ. Sci. 2022, 17, 267–274. [Google Scholar] [CrossRef]
  6. Popescu, F.; Trumic, M.; Cioabla, A.E.; Vujic, B.; Stoica, V.; Trumic, M.; Opris, C.; Bogdanovic, G.; Trif-Tordai, G. Analysis of Surface Water Quality and Sediments Content on Danube Basin in Djerdap-Iron Gate Protected Areas. Water 2022, 14, 2991. [Google Scholar] [CrossRef]
  7. Angelidaki, I.; Ahring, B.K. Thermophilic anaerobic digestion of livestock waste: The effect of ammonia. Appl. Microbiol. Biotechnol. 1993, 38, 560–564. [Google Scholar] [CrossRef]
  8. Muntenita, C.; Dragomir Balanica, C.M.; Simionescu, A.G.; Stanciu, S.; Popa, C.L. The efficiency of biological total phosphorus removal process. Rev. Chim. 2019, 70, 1920–1923. [Google Scholar] [CrossRef]
  9. Rangabhashiyam, S.; dos Santos Lins, P.V.; de Magalhães Oliveira, L.M.T.; Sepulveda, P.; Ighalo, J.O.; Rajapaksha, A.U.; Meili, L. Sewage sludge-derived biochar for the adsorptive removal of wastewater pollutants: A critical review. Environ. Pollut. 2022, 293, 118581. [Google Scholar] [CrossRef]
  10. Sun, J.; Dai, X.; Wang, Q.; Mark, C.M.; van Loosdrecht, M.C.; Ni, B.J. Microplastics in wastewater treatment plants: Detection, occurrence and removal. Water Res. 2019, 152, 21–37. [Google Scholar] [CrossRef]
  11. Sierra, I.; Chialanza, M.R.; Faccio, R.; Carrizo, D.; Fornaro, L.; Pérez-Parada, A. Identification of microplastics in wastewater samples by means of polarized light optical microscopy. Environ Sci Pollut Res. 2020, 27, 7409–7419. [Google Scholar] [CrossRef] [PubMed]
  12. Caramitu, A.R.; Butoi, N.; Rus, T.; Luchian, A.M.; Mitrea, S. The resistance to the action of molds of some painting materials aged by thermal cycling and exposed to an electrical field of 50 Hz. Mater. Plast. 2017, 54, 331–337. [Google Scholar] [CrossRef]
  13. Bors, A.M.; Butoi, N.; Caramitu, A.R.; Marinescu, V.; Lingvay, I. The thermooxidation and resistance to moulds action of some polyethylene sorts used at anticorrosive insulation of the underground pipelines. Mater. Plast. 2017, 54, 447–452. [Google Scholar] [CrossRef]
  14. Cooman, K.; Gajardo, M.; Nieto, J.; Bornhardt, C.; Vidal, G. Tannery wastewater characterization and toxicity effects on Daphnia spp. Environ. Toxicol. 2003, 18, 45–51. [Google Scholar] [CrossRef]
  15. Haydar, S.; Aziz, J.A. Characterization and treatability studies of tannery wastewater using chemically enhanced primary treatment (CEPT)—A case study of Saddiq leather works. J. Hazard. Mater. 2009, 163, 1076–1083. [Google Scholar] [CrossRef]
  16. Moldovan, A.; Török, A.I.; Cadar, O.; Roman, M.; Roman, C.; Micle, V. Assessment of toxic elements contamination in surface water and sediments in a mining affected area. Studia UBB Chem. 2021, LXVI, 189–196. [Google Scholar] [CrossRef]
  17. Watkinson, A.J.; Murby, E.J.; Costanzo, S.D. Removal of antibiotics in conventional and advanced wastewater treatment: Implications for environmental discharge and wastewater recycling. Water Res. 2007, 41, 4164–4176. [Google Scholar] [CrossRef]
  18. Zheng, W.; Wen, X.; Zhang, B.; Qiu, Y. Selective effect and elimination of antibiotics in membrane bioreactor of urban wastewater treatment plant. Sci. Total Environ. 2019, 646, 1293–1303. [Google Scholar] [CrossRef]
  19. Victoria-Salinas, R.E.; Martínez-Miranda, V.; Linares-Hernández, I.; Vázquez-Mejía, G.; Castañeda-Juárez, M.; Almazán-Sánchez, P.T. Pre-treatment of soft drink wastewater with a calcium-modified zeolite to improve electrooxidation of organic matter. J. Environ. Sci. Health Part A 2019, 54, 617–627. [Google Scholar] [CrossRef]
  20. Yapicioğlu, P.S. Energy cost estimation for a dairy wastewater treatment plant in terms of organic load. Acad. Perspect. Procedia 2019, 2, 859–864. [Google Scholar] [CrossRef] [Green Version]
  21. Akshaya, K.V.; Rajesh, R.D.; Puspendu, B. A review on chemical coagulation/flocculation technologies for removal of colour from textile wastewaters. J. Environ. Manag. 2012, 93, 154–168. [Google Scholar] [CrossRef]
  22. Bulc, T.G.; Ojstrsek, A. The use of constructed wetland for dye-rich textile wastewater treatment. J. Hazard. Mater. 2008, 155, 76–82. [Google Scholar] [CrossRef]
  23. Haroun, M.; Idris, A. Treatment of textile wastewater with an anaerobic fluidized bed reactor. Desalination 2009, 237, 357–366. [Google Scholar] [CrossRef]
  24. Frîncu, R.M.; Iulian, O. Impact of Bucharest wastewater on Dâmbovita River water quality (2010–2015). Carpathian J. Earth Environ. Sci. 2021, 16, 47–58. [Google Scholar] [CrossRef]
  25. Stevanović, Z.; Kovačevi, R.; Marković, R.; Gardić, V.; Vulpe, B.C.; Boros, B.; Menghiu, G. State of the surface waters in cross borderregion of eastern Serbia and Caras Severin county—Moldova Noua in Romania. Studia UBB Chem. 2021, LXVI, 309–328. [Google Scholar] [CrossRef]
  26. Nováková, J.; Švehláková, H.; Kučerová, R.; Matějová, T.; Andráš, P. The Behaviour of Phosphorus in an Old Parallel Channel Slaňáky in the Poodří (Czech Republic). Carpathian J. Earth Environ. Sci. 2022, 17, 199–205. [Google Scholar] [CrossRef]
  27. Frîncu, R.M. Long-Term Trends in Water Quality Indices in the Lower Danube and Tributaries in Romania (1996–2017). Int. J. Environ. Res. Public Health 2021, 18, 1665. [Google Scholar] [CrossRef]
  28. Ionescu, P.; Ivanov, A.A.; Radu, V.M.; Deak, G.; Diacu, E.; Marcu, E.; Anghel, A.M. Quality assessment of some freshwater resources located in Bucharest and surrounding areas II. Water quality assessment of Arges and Dambovita rivers. Rev. Chim. 2019, 70, 3638–3643. [Google Scholar] [CrossRef]
  29. Bacosa, H.P.; Ancla, S.M.B.; Arcadio, C.G.L.A.; Dalogdog, J.R.A.; Ellos, D.M.C.; Hayag, H.D.A.; Jarabe, J.G.P.; Karim, A.J.T.; Navarro, C.K.P.; Palma, M.P.I.; et al. From Surface Water to the Deep Sea: A Review on Factors Affecting the Biodegradation of Spilled Oil in Marine Environment. J. Mar. Sci. Eng. 2022, 10, 426. [Google Scholar] [CrossRef]
  30. Byrns, G. The fate of xenobiotic organic compounds in wastewater treatment plants. Water Res. 2001, 35, 2523–2533. [Google Scholar] [CrossRef]
  31. D’Andrea, M.F.; Letourneau, G.; Rousseau, A.N.; Brodeur, J.C. Sensitivity analysis of the pesticide in water calculator model for applications in the Pampa Region of Argentina. Sci. Total Environ. 2020, 698, 134232. [Google Scholar] [CrossRef] [PubMed]
  32. Kay, P.; Hiscoe, R.; Moberley, I.; Bajic, L.; McKenna, N. Wastewater treatment plants as a source of microplastics in river catchments. Environ. Sci. Pollut. Res. 2018, 25, 20264–20267. [Google Scholar] [CrossRef] [Green Version]
  33. Conley, K.; Clum, A.; Deepe, J.; Lane, H.; Beckingham, B. Wastewater treatment plants as a source of microplastics to an urban estuary: Removal efficiencies and loading per capita over one year. Water Research X 2019, 3, 100030. [Google Scholar] [CrossRef] [PubMed]
  34. Covaliu, C.I.; Stoian, O.; Matei, E.; Paraschiv, G.; Tanasa, E.; Catrina (Traistaru), G.A. Research on Copper Ions Removal from Wastewater Using Fe3O4 and Fe3O4- PVP Hybrid Nanomaterials. Mater. Plast. 2021, 58, 154–166. [Google Scholar] [CrossRef]
  35. Vaiopoulou, E.; Gikas, P. Effects of chromium on activated sludge and on the performance of wastewater treatment plants: A review. Water Res. 2012, 46, 549–570. [Google Scholar] [CrossRef]
  36. Banciu, A.R.; Ionescu, L.; Ionica, D.L.; Vaideanu, M.A.; Calinescu, S.M.; Nita Lazar, M.; Marutescu, L.; Popa, M.; Chifiriuc, M.C. The evolution of the bacterial community between hospitals, wastewater treatment plants and the aquatic environment. Rev. Chim. 2020, 71, 313–316. [Google Scholar] [CrossRef]
  37. Earar, K.; Ciuca, I.; Antohe, M.E.; Harabor, V.R.; Constantin, I.; Calin, A.M.; Tiutiuca, C.; Bratu, A.M.; Beznea, A.; Olteanu, C. Medical Waste Water Treatment by Membrane Filtration. Mater. Plast. 2022, 59, 188–193. [Google Scholar] [CrossRef]
  38. Dragomir Balanica, C.M.; Muntenita, C.; Zeca, D.E.; Stoica, M. Statistical analysis of the physicochemical characteristics of urban wastewater treatment plants from Romania. Rev. Chim. 2020, 71, 100–107. [Google Scholar] [CrossRef]
  39. Beenen, A.; Langeveld, J.; Liefting, H.; Aalderink, R.; Velthorst, H. An integrated approach for urban water quality assessment. Water Sci. Technol. 2011, 64, 1519–1526. [Google Scholar] [CrossRef] [Green Version]
  40. Mincu, M.; Marcus, M.; Mitiu, M.A.; Raischi, N.S. Increasing the efficiency of pollutants removal from municipal wastewater using biological filters. Rev. Chim. 2018, 69, 3553–3556. [Google Scholar] [CrossRef]
  41. Castellet Viciano, L.; Torregrossa, D.; Hernandez Sancho, F. The relevance of the design characteristics to the optimal operation of wastewater treatment plants: Energy cost assessment. J. Environ. Manag. 2018, 222, 275–283. [Google Scholar] [CrossRef] [PubMed]
  42. Torregrossa, D.; Leopold, U.; Hernández Sancho, F.; Hansen, J. Machine learning for energy cost modelling in wastewater treatment plants. J. Environ. Manag. 2018, 223, 1061–1067. [Google Scholar] [CrossRef]
  43. Cardoso, B.J.; Rodrigues, E.; Gaspar, A.R.; Gomes, Á. Energy performance factors in wastewater treatment plants: A review. J. Clean. Prod. 2021, 322, 129107. [Google Scholar] [CrossRef]
  44. Żyłka, R.; Karolinczak, B.; Dąbrowski, W. Structure and indicators of electric energy consumption in dairy wastewater treatment plant. Sci. Total Environ. 2021, 782, 146599. [Google Scholar] [CrossRef] [PubMed]
  45. Soares, R.B.; Memelli, M.S.; Roque, R.P.; Gonçalves, R.F. Comparative Analysis of the Energy Consumption of Different Wastewater Treatment Plants. Int. J. Archit. Arts Appl. 2017, 3, 79–86. [Google Scholar] [CrossRef] [Green Version]
  46. Shen, Y.; Linville, J.L.; Urgun Demirtas, M.; Mintz, M.M.; Snyder, S.W. An overview of biogas production and utilization at full-scale wastewater treatment plants (WWTPs) in the United States: Challenges and opportunities towards energy-neutral WWTPs. Renew. Sust. Energ. Rev. 2015, 50, 346–362. [Google Scholar] [CrossRef] [Green Version]
  47. Gupta, A.S. Feasibility Study for Production of Biogas from Wastewater and Sewage Sludge—Development of a Sustainability Assessment Framework and Its Application. Master Thesis, KTH School of Industrial Engineering and Management, Energy Technology, Stockholm, Sweden, 2020. [Google Scholar]
  48. Bumbac, C.; Manea, E.; Banciu, A.; Stoica, C.; Ionescu, I.; Badescu, V.; Nita-Lazar, M. Identification of physical, morphological and chemical particularities of mixed microalgae-bacteria granules. Rev. Chim. 2019, 70, 275–277. [Google Scholar] [CrossRef]
  49. Manea, E.; Bumbac, C.; Banciu, A.; Stoica, C.; Nita-Lazar, M. Kinetical Parameters Evaluation for Microalgae-Bacteria Granules used for Waste Water Treatment. Rev. Chim. 2020, 71, 88–92. [Google Scholar] [CrossRef]
  50. Gherman, V.D.; Molnar, P.; Motoc, M.; Negrea, A. Pretreatments testing of high biodiversity inocula with simultaneous biohydrogen production and wastewater treatment. Rev. Chim. 2018, 69, 806–808. [Google Scholar] [CrossRef]
  51. Biris-Dorhoi, E.S.; Tofana, M.; Chis, S.M.; Lupu, C.E.; Negreanu-Pirjol, T. Wastewater Treatment Using Marine Algae Biomass as Pollutants Removal. Rev. Chim. 2018, 69, 1089–1098. [Google Scholar] [CrossRef]
  52. Mirel, O.S.; Florescu, C. Simulation of wastewater depolution processes by advanced biological methods. Rev. Chim. 2020, 71, 150–160. [Google Scholar] [CrossRef]
  53. Nwankwegu, A.S.; Zhang, L.; Xie, D.T.; Onwosi, C.O.; Muhammad, W.I.; Odoh, C.K.; Sam, K.; Idenyi, J.N. Bioaugmentation as a green technology for hydrocarbon pollution remediation. Problems and prospects J. Environ. Manag. 2022, 304, 114313. [Google Scholar] [CrossRef]
  54. Riffo, B.; Henríquez, C.; Chávez, R.; Peña, R.; Sangorrín, M.; Gil-Duran, C.; Rodríguez, A.; Ganga, M.A. Nonionizing Electromagnetic Field: A Promising Alternative for Growing Control Yeast. J. Fungi. 2021, 7, 281. [Google Scholar] [CrossRef] [PubMed]
  55. Ferencz, C.M.; Petrovszki, P.; Dér, A.; Sebők-Nagy, K.; Kóta, Z.; Páli, T. Oscillating electric field measures the rotation rate in a native Rotary enzyme. Sci. Rep. 2017, 7, 45309. [Google Scholar] [CrossRef] [Green Version]
  56. Lingvay, M.; Caramitu, A.R.; Borș, A.M.; Lingvay, I. Dielectric spectroscopic evaluation in the extremely low frequency range of an Aspergillus niger culture. Stud. UBB Chem. 2019, 64, 279–288. [Google Scholar] [CrossRef]
  57. Gao, M.; Zhang, J.; Feng, H. Extremely Low Frequency Magnetic Field Effects on Metabolite of Aspergillus niger. Bioelectromagnetics 2011, 32, 73–78. [Google Scholar] [CrossRef] [PubMed]
  58. Mokhtar, N.M.; Omar, R.; Mohammad Salleh, M.A.; Idris, A. Characterization of sludge from the wastewater-treatment plant of a refinery. Int. J. Eng. Tech. 2011, 8, 48–56. [Google Scholar]
  59. Tókos, A.; Bartha, C.; Jipa, M.; Micu, D.D.; Caramitu, A.R.; Lingvay, I. Interactions of Extremely Low-Frequency Electric Field with the Active Sludge Live Materia from Wastewater Treatments. In Proceedings of the 12th International Symposium on Advanced Topics in Electrical Engineering (ATEE), Bucharest, Romania, 25–27 May 2021. [Google Scholar] [CrossRef]
  60. Nanping, W.; Qian, Z.; Bin, T.; Junhao, S.; Jiapeng, F.; Yunjie, Z.; Jing, H.; Meng, L.; Qi, H. Understanding the impacts of intermittent electro field on the bioelectrochemical aniline degradation system: Performance, microbial community and functional enzyme. Environ. Res. 2023, 231, 116039. [Google Scholar] [CrossRef]
  61. Shuang, L.; Zhi-Yuan, Z.; Ying, L.; Ran, L.; Wen-Zong, L.; Xiao-Chi, F.; Ai-Jie, W.; Hong-Cheng, W. Recent advancements in antibiotics containing wastewater treatment by integrated bio-electrochemical-constructed wetland systems (BES-CWs). Chem. Eng. J. 2023, 457, 141133. [Google Scholar] [CrossRef]
  62. Ameer, A.K.; Nana, J.; Yi, C.; Xinjuan, H.; Jingya, Q.; Xinyi, Z.; Cunsheng, Z.; Feifei, Z.; Santosh, K.; Shuhao, H. Magnetic/electric field intervention on oil-rich filamentous algae production in the application of acrylonitrile butadiene styrene based wastewater treatment. Bioresour. Technol. 2022, 356, 127272. [Google Scholar] [CrossRef]
  63. Bartha, C.; Jipa, M.; Caramitu, A.R.; Voina, A.; Tókos, A.; Circiumaru, G.; Micu, D.D.; Lingvay, I. Behavior of Microorganisms from Waste water Treatments in Extremely Low-Frequency Electric Field. Biointerface Res. Appl. Chem. 2022, 12, 5071–5080. [Google Scholar] [CrossRef]
  64. Hunt, R.W.; Zavalin, A.; Bhatnagar, A.; Chinnasamy, S.; Das, K.C. Electromagnetic Biostimulation of Living Cultures for Biotechnology, Biofuel and Bioenergy Applications. Int. J. Mol. Sci. 2009, 10, 4515–4558. [Google Scholar] [CrossRef] [Green Version]
  65. Lingvay, I.; Bors, A.M.; Lingvay, D.; Radermacher, L.; Neagu, V. Electromagnetic Pollution of the Environment and its Effects on the Materials from the Built up Media. Rev. Chim. 2018, 69, 3593–3599. [Google Scholar] [CrossRef]
  66. Oprina, G.; Radermacher, L.; Lingvay, D.; Marin, D.; Voina, A.; Mitrea, S. Bituminous Insulations Durability of Underground Metallic Pipelines I Field investigations. Rev. Chim. 2017, 68, 581–585. [Google Scholar] [CrossRef]
  67. Lingvay, I.; Radu, E.; Caramitu, A.R.; Pătroi, D.; Oprina, G.; Radermacher, L.; Mitrea, S. Bituminous insulations durability of underground metallic pipelines 2—Laboratory study on the aging of bituminous material. Rev. Chim. 2017, 68, 646–651. [Google Scholar] [CrossRef]
  68. Aronsson, K.; Rfnner, U.; Borch, E. Inactivation of Escherichia coli, Listeria innocua and Saccharomyces cerevisiae in relation to membrane permeabilization and subsequent leakage of intracellular compounds due to pulsed electric field processing. Int. J. Food Microbiol. 2005, 99, 19–32. [Google Scholar] [CrossRef] [PubMed]
  69. He, Z.; Jin, W.; Zhou, X.; Han, W.; Gao, S.; Chen, C.; Chen, Y.; Yin, S.; Che, L.; Jiang, G. Enhancing biomass and lipid yield of microalga Scenedesmus obliquus by the periodic direct current. J. Water Process Eng. 2022, 48, 102872. [Google Scholar] [CrossRef]
  70. Beretta, G.; Mastorgio, A.F.; Pedrali, L.; Saponaro, S.; Sezenna, E. The effects of electric, magnetic and electromagnetic fields on microorganisms in the perspective of bioremediation. Rev. Env. Sci. Biotechnol. 2019, 18, 29–75. [Google Scholar] [CrossRef] [Green Version]
  71. Tókos, A.; Jipa, M.; Círciumaru, G.; Bartha, C.; Voina, A.; Caramitu, R.A.; Micu, D.D.; Lingvay, I. Contributions to Energy Saving in Wastewater Treatment Plants. In Proceedings of the International Conference on Electrical, Computer and Energy Technologies (ICECET), Prague, Czech Republic, 20–22 July 2022. [Google Scholar] [CrossRef]
  72. Singh, P.; Carliell-Marquet, C.; Kansal, A. Energy pattern analysis of a wastewater treatment plant. Appl. Water Sci. 2012, 2, 221–226. [Google Scholar] [CrossRef] [Green Version]
  73. Bartha, C.; Marinescu, V.; Jipa, M.; Sbarcea, B.G.; Tókos, A.; Caramitu, A.R.; Lingvay, I. Behavior in AC polarization of high-silicon cast irons. Studia UBB Chem. 2021, LXVI, 49–61. [Google Scholar] [CrossRef]
  74. ISO 6060:1989; Water Quality—Determination of the Chemical Oxygen Demand. ISO/TC 147/SC 2: Geneva, Switzerland, 1989.
  75. ISO 7150-1:1984; Water Quality—Determination of Ammonium—Part 1: Manual Spectrometric Method. ISO/TC 147/SC 2: Geneva, Switzerland, 1984.
  76. DIN 38406 E5-1; Deutsche Einheitsverfahren zur Wasser-, Abwasser- und Schlammuntersuchung; Kationen (Gruppe E); Bestimmung des Ammonium-Stickstoffs (E 5). Deutsches Institut fur Normung E.V. (DIN): Berlin, Germany, 1983.
  77. UNI 11669:2017; Qualità Dell’acqua—Determinazione Dell’azoto Ammoniacale (N-NH4) in Acque di Diversa Natura Mediante prova (Test) in Cuvette. Ente Italiano del Normazioni: Milano, Italy, 2017.
  78. ISO 6878-1-1986; Water Quality—Determination of Phosphorus—Part 1: Ammonium Molybdate Spectrometric Method. ISO/TC 147/SC 2: Geneva, Switzerland, 1986.
  79. Rui, D.; Yongzhen, P.; Shenbin, C.; Chengcheng, W.; Dongchen, W.; Shuying, W.; Jianzhong, H. Advanced nitrogen removal with simultaneaus Anammox and denitrification in sequencing batch reactor. Bioresurce Tehnol. 2014, 162, 316–322. [Google Scholar] [CrossRef]
  80. Rossi, F.; Motta, O.; Matrella, S.; Proto, A.; Vigliotta, G. Nitrate Removal from Wastewater through Biological Denitrification with OGA 24 in a Batch Reactor. Water 2015, 7, 51–62. [Google Scholar] [CrossRef]
Figure 1. Wastewater treatment plant in Romuli village—Bistrita-Nasaud County, Romania.
Figure 1. Wastewater treatment plant in Romuli village—Bistrita-Nasaud County, Romania.
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Figure 2. Diagram of the technological flow at the Romuli wastewater treatment plant, Bistrita-Nasaud County, Romania.
Figure 2. Diagram of the technological flow at the Romuli wastewater treatment plant, Bistrita-Nasaud County, Romania.
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Figure 3. Polarization electrodes and their fitting on the biological purification tank [71].
Figure 3. Polarization electrodes and their fitting on the biological purification tank [71].
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Figure 4. BgT-1 and BgT-2 biological treatment basins in January 2022.
Figure 4. BgT-1 and BgT-2 biological treatment basins in January 2022.
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Figure 5. Evolution of LDO in BgT-1 compared to BgT-2 (3 February 2022—30 min cycles, with and without air bubbling).
Figure 5. Evolution of LDO in BgT-1 compared to BgT-2 (3 February 2022—30 min cycles, with and without air bubbling).
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Figure 6. Graphical determination of the overall oxidation process rate from the evolution of the DO = f(time) curves. The black dotted line represents the slope of the oxidation process rate.
Figure 6. Graphical determination of the overall oxidation process rate from the evolution of the DO = f(time) curves. The black dotted line represents the slope of the oxidation process rate.
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Figure 7. Polarization electrode extracted from BgT-2 after 5 days of operation.
Figure 7. Polarization electrode extracted from BgT-2 after 5 days of operation.
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Table 1. Comparative results of chemical analyses.
Table 1. Comparative results of chemical analyses.
0SamplingParameter
DO [mg/L]COD [mg/L]N-NH4 [mg/L]Pt [mg/L]
1Temperature [°C]5915591559155915
2Wastewater (inlet)00013401490155043.940.240.54.45.76.1
3BgT-1 exit
(reference)
1.9 2.42.912512312115.115.014.82.11.81.9
4BgT-2 exit
(ELF stimulated)
5.5 6.27.84241407.57.47.31.10.90.9
Table 2. Comparative Vox values in BgT-1 and BgT-2 (3 February 2022).
Table 2. Comparative Vox values in BgT-1 and BgT-2 (3 February 2022).
Speed of DO Decreasing—Vox = ΔDO/Δt [mg/L/min]
Minimum
(at 4.7 °C)
Medium
(at 5.2 °C)
Maximum
(at 5.7 °C)
Weighted Average
(at 5.4 °C)
BgT-1
(reference)
0.03050.04090.05040.0498
BgT-2
(ELF stimulated)
0.06200.09750.10720.1003
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Bartha, C.; Tókos, A.; Jipa, M.; Caramitu, A.; Voina, A.; Circiumaru, G.; Micu, D.-D.; Lingvay, I. Saving Energy in Biological Wastewater Treatment by Using Extremely Low-Frequency Electric Field—Pilot-Scale Study. Sustainability 2023, 15, 11670. https://doi.org/10.3390/su151511670

AMA Style

Bartha C, Tókos A, Jipa M, Caramitu A, Voina A, Circiumaru G, Micu D-D, Lingvay I. Saving Energy in Biological Wastewater Treatment by Using Extremely Low-Frequency Electric Field—Pilot-Scale Study. Sustainability. 2023; 15(15):11670. https://doi.org/10.3390/su151511670

Chicago/Turabian Style

Bartha, Csaba, Attila Tókos, Monica Jipa, Alina Caramitu, Andreea Voina, Gabriela Circiumaru, Dan-Doru Micu, and Iosif Lingvay. 2023. "Saving Energy in Biological Wastewater Treatment by Using Extremely Low-Frequency Electric Field—Pilot-Scale Study" Sustainability 15, no. 15: 11670. https://doi.org/10.3390/su151511670

APA Style

Bartha, C., Tókos, A., Jipa, M., Caramitu, A., Voina, A., Circiumaru, G., Micu, D.-D., & Lingvay, I. (2023). Saving Energy in Biological Wastewater Treatment by Using Extremely Low-Frequency Electric Field—Pilot-Scale Study. Sustainability, 15(15), 11670. https://doi.org/10.3390/su151511670

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