This study investigated the degradation of sulfamonomethoxine (SMM) by pulsed plasma discharge. SMM was successfully degraded following the first-order kinetics model. The percentage removal of SMM was estimated by the total input energy of plasma discharge, which was dependent on the initial SMM concentration. In addition, three types of by-products were observed at an early reaction time, which were then degraded. In contrast, the ecotoxicity of the treated solution by plasma discharge was assessed by an acute toxicity test using the green alga Raphidocelis subcapitata. The plasma discharge in water generated hydrogen peroxide with a concentration higher than the EC50 for R. subcapitata. It is therefore necessary to remove H2O2 or prevent the generation of H2O2 for the degradation of antibiotics in solutions using plasma discharge.

  • Sulfamonomethoxine (SMM) was successfully degraded following a first-order kinetic model using pulsed plasma discharge.

  • The percentage removal of SMM was estimated by the total input energy.

  • Three types of degradation products were found at early reaction times, which were then also degraded.

  • Plasma discharge in water generated hydrogen peroxide at a concentration higher than the EC50 for R. subcapitata.

Several countries have developed action plans for antimicrobial resistance (AMR) ever since the World Health Organization (WHO) suggested the needs for global action for AMR in 2011. One action plan is to survey antibiotics in the environment, the presence of which may encourage the emergence of antimicrobial-resistant bacteria. Rodriguez-Mozaz et al. (2015) reported a positive correlation between the concentrations of antibiotics and corresponding resistance genes, such as sulfamethoxazole and sulfonamide resistance genes sul1 in the influent and effluent of wastewater treatment plants, hospital wastewater, and river water. Gao et al. (2012) also found a positive correlation between the concentrations of sulfonamides and sul1 genes. These results suggest that the presence of sulfonamide significantly affects the selection of sul1 genes in the environment.

Antibiotics are used more often in animals than in humans. The sales volume of veterinary antibiotics in Japan is 824.56 tons while that for humans is 582.2 tons in 2018 (The AMR One Health Surveillance Committee Japan 2020). Some antibiotics administered to livestock are excreted in feces and urine. Tylosin (5.8%) and sulfamonomethoxine (SMM; 5.8–15.3%) injected into sheep were excreted with urine (Ishikawa et al. 2018; Soma et al. 2019). This implies that antibiotics are transferred from animals to livestock wastewater. Wei et al. (2011) reported that up to 211 μg/L of sulfamethazine was detected in livestock wastewater, 169 μg/L in the effluent of the livestock wastewater treatment system of the farms, and 4.66 μg/L in river water near the farm in Jiangsu Province. This indicated that antibiotics spread to the aquatic environment from farms. Another concern is the adverse effects on the aquatic ecosystem through the spread of antibiotics. Antibiotics are toxic to aquatic organisms, such as green algae (Yagi et al. 2016), green and blue-green algae (Zhong et al. 2021), and goldfish (Liu et al. 2014) at the μg/L level. The removal of antibiotics from livestock wastewater to prevent the spread of antibiotics to the environment is therefore not only effective for providing AMR measures, but also for maintaining healthy aquatic ecosystems.

There have been a variety of investigations on the removal of antibiotics from wastewater. Göbel et al. (2005) reported that the activated sludge process was able to remove sulfamethoxazole, but not trimethoprim and clarithromycin. It has also been reported that trimethoprim is removed after sand filtration following the activated sludge process. Ozonation is effective in degrading tetracycline, oxytetracycline, doxycycline, and azithromycin adsorbed by activated sludge (Wang et al. 2018). On the other hand, the treated effluent of plants using the activated sludge process in sewage treatment contains several antibiotics, such as levofloxacin and sulfamethoxazole (Ishikawa et al. 2022). The activated sludge process was reported to remove several antibiotics, and it is not an applicable degradation technology for all types of antibiotics. An advanced oxidation process has been suggested for the removal of antibiotics, for example, UV or UV/persulfate for azithromycin (Sadeghi et al. 2018), Fenton and UV/H2O2 for norfloxacin (Santos et al. 2015). These advanced oxidation processes in techniques are expensive as they require reagents. In addition, Magureanu et al. (2011) found that β-lactam antibiotics such as amoxicillin, oxacillin, and ampicillin were degraded by non-thermal plasma treatment. The non-thermal plasma treatment investigated by Magureanu et al. (2011) showed that plasma discharge was generated on the liquid–gas interface. Plasma discharge in the liquid phase is more effective for the degraded antibiotics in liquid–gas interface. Therefore, we investigated plasma discharge in a liquid phase as an effective degradation process without reagent.

One of the most important aspects of the antibiotic degradation process is the characteristics of its by-products. Yan et al. (2011) demonstrated the degradation pathway of SMM in a sample solution treated with sulfate-free radicals produced from persulfate anions activated with iron oxide magnetic nanoparticles. Pi et al. (2013) also proposed a degradation pathway for SMM in a sample solution by combining the degradation process with UV and oxone. Furthermore, there are a few reports of degradation products in solutions that vary with reaction time (Magureanu et al. 2011). It is additionally necessary to understand the effects of by-products in treated water on aquatic organisms, considering that it is discharged to the receiving waterbody. Magdeburg et al. (2012) suggested that the ozonation of wastewater-generated substances is more toxic to Lumbriculus variegatus than the organic substances originally present in wastewater. Some of the by-products of antibiotics are toxic for aquatic organisms. Yuan et al. (2011) observed that the by-products had higher toxicity to Vibrio fischer than its parent antibiotics when antibiotics were degraded using UV photolysis. Furthermore, the toxicity of by-products increased with treatment time, and then decreased with UV/H2O2 treatment. It is, therefore, necessary to investigate the toxicity of treated water on aquatic organisms to maintain healthy aquatic ecosystems.

In this study, the degradation of antibiotics was investigated using pulsed power discharge. In this technique, antibiotics are degraded by the hydroxyl radicals produced by pulsed power discharge in an aquatic solution. As mentioned above, the strong oxidation process with radicals, which initially produced by-products with toxicity to organisms, finally will degrade antibiotics to harmless products. The by-products and some water quality parameters in the treated water were then analyzed and their toxicity to green algae was assessed using acute toxicity tests. In addition, plasma discharge generates not only by-products of antibiotics, but also by-products such as H2O2 as described in the next section. These effects to green algae were also assessed using acute toxicity tests.

SMM was selected as the target antibiotics in this study, as SMM is widely used for livestock, whose sale volume of SMM in Japan was 32.3 tons of SMM hydrate and 11.8 tons of SMM sodium in 2020 (National Veterinary Assay Laboratory 2020).

Reagents

Figure 1 presents the chemical structure of SMM. SMM is a sulfonamide that inhibits the synthesis of folic acid. A sulfamonomethoxine standard (Fujifilm Wako Pure Chemical Corp., Osaka, Japan) was used for the experiments. LC-MS grade methanol and formic acid were used for the analysis of SMM.
Figure 1

The chemical structure of sulfamonomethoxine.

Figure 1

The chemical structure of sulfamonomethoxine.

Close modal

SMM degradation experiment using pulsed plasma discharge

The pulsed plasma in water is assumed to undergo reactions as per the following equations:
formula
(1)
formula
(2)
formula
(3)
formula
(4)
formula
(5)
The SMM degradation experiment was performed under two experimental conditions, referred to as condition 1 and condition 2. In condition 1, an SMM standard solution was prepared to dilute the SMM stock solution with deionized water. A total of 15 mL of a 10 mg/L SMM solution was added to a 30 mL gas chromatography vial. Figure 2 presents the schematic of the plasma batch reactor. Argon gas was injected into the SMM standard solution at a gas flow rate of 30 mL/min through a vertically positioned glass tube in which the wire electrode was placed to generate bubbles in the solution. A pulsed high voltage was applied to the wire electrode to generate the plasma inside the bubble. Table 1 summarizes the plasma discharge conditions. Our preliminary experiment found that more than 70% of SMM was degraded within 4 h. Therefore, the treatment time was determined as 1.5, 3, 4, and 8.5 h. The SMM concentrations in the samples were determined using liquid chromatography-tandem mass spectrometry (LC-MS/MS; LC: Waters, Acuity UPLC H-Class, MS/MS: Waters, Xevo TQD). Table 2 summarizes the operating conditions of the LC-MS/MS. In addition, the 10 mg/L SMM standard solution and the samples treated with plasma discharge for 1.5, 4 and 8.5 h were analyzed to detect the by-products of SMM with LC-MS/MS in full scan mode. The m/z values of the target products were 94, 95, 113, 125, 126, 191, 217, 295, 297, and 311, which have been previously reported as degradation products (Yan et al. 2011; Pi et al. 2013). The electrical conductivity and pH of the samples were measured using an EC meter (Horiba, LAQUA twin EC-33, Japan) and a pH meter (Horiba, LAQUA twin pH-22B, Japan), respectively.
Table 1

Experimental conditions

Condition 1Condition 2
Solution volume (mL) 15 500 
The number of electrodes  15 
Output voltage (kV) 16 10 
Pulse repetition frequency (pps) 250 2,000 
Total gas flow rate (mL/min) 30 3,000 
Condition 1Condition 2
Solution volume (mL) 15 500 
The number of electrodes  15 
Output voltage (kV) 16 10 
Pulse repetition frequency (pps) 250 2,000 
Total gas flow rate (mL/min) 30 3,000 
Table 2

Operating conditions of LC-MS/MS

Column Waters Acquity LPLC BEH C18 (1.7 μm) 
Column size 2.1 mm I.D. × 50 mm length 
Column temp. 50 °C 
Mobile phase A: 0.005% formic acid in H2
B: Methanol 
Flow rate 0.4 mL/min 
Injection dose 1 μL 
Detection ESI, positve ions 
Precursor ion m/z 281 
Product ion m/z 92, 156 
Capillary voltage 2,000 V 
Cone gas flow 50 L/h 
Desolvation gas flow 800 L/h 
Desolvation temp. 350 °C 
Column Waters Acquity LPLC BEH C18 (1.7 μm) 
Column size 2.1 mm I.D. × 50 mm length 
Column temp. 50 °C 
Mobile phase A: 0.005% formic acid in H2
B: Methanol 
Flow rate 0.4 mL/min 
Injection dose 1 μL 
Detection ESI, positve ions 
Precursor ion m/z 281 
Product ion m/z 92, 156 
Capillary voltage 2,000 V 
Cone gas flow 50 L/h 
Desolvation gas flow 800 L/h 
Desolvation temp. 350 °C 
Figure 2

The schematic of the reactor (condition 1).

Figure 2

The schematic of the reactor (condition 1).

Close modal
The percentage of the remaining SMM (PR) was calculated as follows:
formula
(6)
where C0 (mg/L) and Ct (mg/L) denote the initial SMM concentration and the SMM concentration at time t, respectively. In addition, the percentage removal (%) was calculated by the following equation:
formula
(7)
The experimental system in condition 2 was scaled up from condition 1 to obtain enough volume of the treated water, i.e., more than 400 mL, for the acute toxicity test. In condition 2, a total of 500 mL of a 10 mg/L SMM standard solution was added to a 1 L glass medium bottle. Figure 3 and Table 1 present the schematic and experimental conditions, respectively. Plasma was injected to the SMM solution. The samples were taken for 1, 2, 4, and 8 h. The SMM concentrations were determined by LC-MS/MS. The remaining samples were used for an acute toxicity test, as described in the next section.
Figure 3

The schematic diagram of the reactor (condition 2).

Figure 3

The schematic diagram of the reactor (condition 2).

Close modal

Acute toxicity test with green algae

An acute toxicity test was carried out based on the Organisation for Economic Co-operation and Development (OECD) guideline (OECD 2006) to evaluate the ecological toxicity of the treated solution to the green alga Raphidocelis subcapitata, which is selected as a testing organism for the testing of chemicals. R. subcapitata (NIES-35) was obtained from the National Institute for Environmental Science (NIES), Japan. The alga was cultured in a C medium (NIES, n.d.) at 23 °C in accordance with the OECD Guideline 201 (OECD 2006).

Two types of test solutions were used for the acute toxicity tests. One was an SMM standard solution with concentrations of 0 (control), 0.1, 0.3, 1, 3, and 10 mg/L. The other one was the SMM solution treated using plasma discharge, as described in the previous section. The pH of all samples was adjusted to 7.5 before the acute toxic test to avoid adverse effects of acidic conditions on algae. Therefore, the acute toxicity test demonstrated the toxic effect of the by-products produced in SMM solution using plasma discharge. Each test solution was mixed with concentrated algal culture and medium in a 200 mL Erlenmeyer flask. The initial algal cell concentration in the mixed solution was approximately 5 × 103 cells/mL. The solutions were incubated under continuous fluorescent light with a capacity of approximately 110 μmol/m2/s at 23 °C. The samples were taken after 0, 12, 24, 48, and 72 h of incubation. The cell density in each sample was determined using a disposable cell counting chamber (As One, DHC-F015, Japan) and a fluorescence microscope (Olympus, BX51, Japan). The relative cell density was calculated using the following equation:
formula
(8)
where D0 and Dt denote the cell density (cells/mL) at time 0 and time t of incubation, respectively. The specific growth rate (μ) (1/min) was calculated using the following equation:
formula
(9)
where t1 and t2 are arbitrary times (min) during the log growth phase, and D1 and D2 denote the cell density (cells/mL) at t1 and t2, respectively. The inhibition rate (I) (%) was calculated using the following equation:
formula
(10)
where μc and μs are μ values for the control and treated solutions, respectively.

SMM degradation using pulsed plasma discharge

Figure 4 presents the effect of the reaction time on the pH and EC values for condition 2. The pH value decreased with the reaction time.
Figure 4

Effect of reaction time on pH and EC (condition 2).

Figure 4

Effect of reaction time on pH and EC (condition 2).

Close modal
Figure 5 presents the effect of the reaction time on the PR value. The different result between two conditions depends on input energy per treatment time and per volume, which is calculated using pulse repetition frequency and voltage shown in Table 1 and treatment time and sample volume. A first-order kinetic model (Equation (11)) fit well for the PR on the reaction time of 4 h, with a correlation coefficient (R2) of 0.99, for both experimental conditions.
formula
(11)
where k (h−1) is the kinetic constant. The k values were 0.33 and 0.74 for condition 1 and condition 2, respectively. Half-life (t1/2) was calculated as follows:
formula
(12)
where t1/2 were 0.95 h and 2.10 h for condition 1 and condition 2, respectively.
Figure 5

Effect of reaction time on the PR for each experimental condition. (□: condition 1, ○: condition 2).

Figure 5

Effect of reaction time on the PR for each experimental condition. (□: condition 1, ○: condition 2).

Close modal
Geng et al. (2020) observed that the percentage removal of bisphenol A increased with an increase in the input power of strong ionization discharge. The results of this study showed that the percentage removal of SMM degradation increased with the total input energy, which is in good agreement with that of Geng et al. (2020). Figure 6 presents the relationship between the total input energy and PR; the PR value exponentially increased with the total input energy. These relationships were explained using one equation with a high determination coefficient (R2 = 0.78) independent of the experimental conditions. This suggests that the percentage removal may be estimated using the total input energy. However, the estimated equation possibly differs from the initial SMM concentration because of the competition in active species reaction with SMM molecules and its by-products as suggested by Meiyazhagan et al. (2020) who observed the degradation percentage of dye using microplasma discharge decreased with increasing the initial dye concentration.
Figure 6

Effect of total input energy on the PR for each experimental condition. (□: condition 1, ○: condition 2).

Figure 6

Effect of total input energy on the PR for each experimental condition. (□: condition 1, ○: condition 2).

Close modal

Degradation of the products of SMM by using plasma discharge

A full scan with LC-MS/MS was carried out for the 10 types of target by-products having m/z values of 94, 95, 113, 125, 126, 191, 217, 295, 297, and 311 in the proposed reaction pathway for SMM degradation in UV/oxone oxidative processes (Pi et al. 2013) and persulfate with Fe3O4 magnetic nanoparticles (Yan et al. 2011). It was found that the peak area on the chromatogram for m/z values of 126, 297, and 311 increased with the reaction time from 0 to 4 h, as presented in Figure 7. Figure 8 shows the effects of the reaction time on the peak area at the three m/z values. These peak areas increased with the reaction time until 4 h and then disappeared at 8.5 h. These by-products could therefore be completely degraded until 8.5 h. Figure 9 presents the confirmed reaction pathway.
Figure 7

Full scan chromatograms for different reaction times. (…: 0 h, - - -: 1.5 h, —: 4 h).

Figure 7

Full scan chromatograms for different reaction times. (…: 0 h, - - -: 1.5 h, —: 4 h).

Close modal
Figure 8

Effect of reaction time on the peak area at m/z 126, 297, and 311.

Figure 8

Effect of reaction time on the peak area at m/z 126, 297, and 311.

Close modal
Figure 9

SMM reaction pathway confirmed in this study.

Figure 9

SMM reaction pathway confirmed in this study.

Close modal

Toxicity of the treated solution to R. subcapitata

Figure 10(a) depicts the time variation in the relative cell density of R. subcapitata for different SMM concentrations in the SMM standard solution. The inhibition of algal growth was observed even at the lowest concentration of SMM (0.01 mg/L). Figure 10(b) presents the time variation in the relative cell density of R. subcapitata for different plasma discharge reaction times. Although the SMM concentration decreased with the reaction time, as presented in Figure 5, the algal growth in the solution treated by plasma discharge was more inhibited than before the plasma treatment. Figure 11 shows the relationship between SMM concentration and the inhibition rate for each solution. The higher the SMM concentration in the SMM standard solution (CSMM), the higher the I value. This relationship can be explained by the following equation, with R2 > 0.99:
formula
(13)
Figure 10

Time variation in the relative cell density of R. Subcapitata at different SMM concentrations of SMM standard solution (mg/L) (a) and in treated solution at different reaction times (b).

Figure 10

Time variation in the relative cell density of R. Subcapitata at different SMM concentrations of SMM standard solution (mg/L) (a) and in treated solution at different reaction times (b).

Close modal
Figure 11

The inhibition rate of each solution in relation to SMM concentration. 〇: SMM standard solution; □: treated solution.

Figure 11

The inhibition rate of each solution in relation to SMM concentration. 〇: SMM standard solution; □: treated solution.

Close modal

The 50% effective concentration (EC50) of SMM was 0.94 mg/L which was obtained by substituting 50 to I in Equation (12). This EC50 value was close to that reported in previous studies (Fukunaga et al. 2006; Yagi et al. 2016). In contrast, the I value for the treated solution was higher than 95% even though the SMM concentration was lower than the EC50. It was assumed that the by-products of SMM may be more toxic to green algae than SMM. However, this assumption was rejected because by-products were not detected in the solution at a reaction time of 8.5 h.

This study presents two discussions as to why the I value was significantly higher than the value expected from the SMM concentration. The first is the NH4-N generated by plasma discharge. In condition 2, the NH4-N concentration linearly increased with the reaction times, which were 0.03, 2.64, and 4.51 mg/L at reaction times of 0, 2, and 4 h, respectively. Tsuji et al. (2018) also reported that ammonia was generated when atmospheric-pressure plasma was used to irradiate distilled water. Przytocka-Jusiak (1976) reported that growth inhibition and cell death were observed for the green alga, Chlorella vulgaris, at a total ammonia (NH4+ + NH3) concentration of 326–1,330 mg/L. At pH 7.5, ∼85% of total ammonia existed as NH4–N at 23 °C (United States Environmental Protection Agency 2013), which suggests ∼215 mg/L of NH4–N could have adverse effects on the green alga. This concentration was much higher than that observed in our sample. Therefore, the high I value was not attributed to the NH4-N concentration.

The second is the H2O2 generated by the plasma discharge, as described in Equation (5). Yayci et al. (2020) reported that the concentration of H2O2 linearly increased with time during plasma discharge. When H2O2 concentration in the treated solution was measured using a pack test (Kyoritsu chemical-check Lab., Corp., WAK-H2O2), 41.3 mg/L of H2O2 was detected at a reaction time of 1 h, which was much higher than the EC50 (2.9 mg/L) for R. subcapitata as reported by Chhetri et al. (2017). Therefore, H2O2 may have a significant impact on the algal growth in the treated solution.

This study investigated the degradation of SMM using a pulsed plasma discharge. SMM was successfully degraded using plasma discharge following the first-order kinetics model. The percentage removal of SMM was estimated by the total input energy of plasma discharge dependent on the initial SMM concentration. Additionally, three types of by-products of SMM were produced, which degraded with increasing reaction time. However, one concern is that the plasma discharge in water generates H2O2 at a higher concentration than the EC50 for R. subcapitata. It is therefore necessary to remove H2O2 or prevent the generation of H2O2 for the degradation of antibiotics in water using plasma discharge.

This research was partially supported by Tohoku Chiikidukuri Kyokai and the SPERC at Iwate University.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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