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Article

Antibiotics in Wastewater Treatment Plants in Tangshan: Perspectives on Temporal Variation, Residents’ Use and Ecological Risk Assessment

by
Zhuo Dong
1,
Jian Hu
2,*,
Pengjie Wang
3,
Gengtao Han
1 and
Zheng Jia
1
1
Pharmacy Teaching and Research Office, Medical Department, Tangshan Vocational and Technical College, Tangshan 063000, China
2
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, No. 18 Shuangqing Road, Beijing 100085, China
3
Heilongjiang Province Environmental Monitoring Center, Harbin 150090, China
*
Author to whom correspondence should be addressed.
Water 2024, 16(11), 1627; https://doi.org/10.3390/w16111627
Submission received: 28 April 2024 / Revised: 1 June 2024 / Accepted: 3 June 2024 / Published: 6 June 2024
(This article belongs to the Special Issue Impacts of Environmental Change and Human Activities on Aquatic Ecosystems)
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Abstract

:
In 2023, this study monitored nine types of antibiotics in the influent and effluent of wastewater treatment plants (WWTPs) in the urban and suburban areas of Tangshan. The total antibiotics concentration detected in influent WWTPs was highest in winter, followed by spring, summer, and autumn. The antibiotics concentration in influent and effluent urban WWTPs was higher than that in the suburban WWTPs in spring, summer, and winter, while the trend was reversed in autumn. Roxithromycin and oxytetracycline had a risk quotient (RQ) value of ≥0.1 in the effluent of WWTPs in winter, indicating that they are medium-risk antibiotics that pose a risk to the aquatic ecosystem after discharge. In the study area, the per capita pollution load of antibiotics was highest in spring, summer, and autumn for sulfamethoxazole, while it was highest in winter for ofloxacin. In the urban area, the use of roxithromycin, sulfamethoxazole, sulfamethoxazole, and ofloxacin was highest in spring, summer, autumn, and winter, respectively, while in suburban areas, the use of sulfamethoxazole, norfloxacin, sulfamethoxazole, and ofloxacin was highest during the same period. The use of antibiotics in the urban area was one order of magnitude higher than that in suburban areas, indicating a possible overuse of antibiotics in urban environments.

1. Introduction

Antibiotics play a crucial role in human health and are usually prioritized in drug management [1,2,3]. However, due to non-compliance with the principles of using antibiotics, there have been cases of inappropriate use and other forms of antibiotic abuse [4,5,6]. Currently, the misuse of antibiotics is a pressing public health and ecological security issue across various sectors, including medical health, food hygiene, livestock and poultry breeding, and ecological governance, not only in China but also globally [7,8,9]. China produces about 210,000 tons of antibiotic raw materials every year. Excluding the export of raw materials (about 30,000 tons), the remaining 180,000 tons are used domestically (including medical and agricultural use), with an annual per capita consumption of about 138 g [10]. As veterinary antibiotics, tetracycline antibiotics are the most commonly used, accounting for 40.5% of the total, followed by sulfonamides and macrolides. Quinolones are highly used in hospitals due to the high incidence of respiratory tract infections and mycoplasmal pneumonia in spring, autumn, and winter. Therefore, it is expected that antibiotics are widely present in urban sewage and agricultural wastewater, entering the water ecosystem through various pathways [11,12,13]. Due to the low metabolic rate of biological organisms against antibiotics, a large amount of antibiotics is excreted with urine and feces, collected by sewage networks, and entered WWTPs.
At present, the main purpose of WWTPs is to remove suspended solids, COD (chemical oxygen demand), nitrogen, phosphorus, and other substances in sewage, but they generally do not have the ability to efficiently remove antibiotics, resulting in high antibiotic concentrations in effluent wastewater [13,14]. It should be noted that sewage treatment technologies like advanced chemical oxidation, chemical precipitation, ultrafiltration, nanofiltration, and ion exchange are not effective at removing antibiotics and may be better suited for industrial wastewater treatment. In contrast, suburban wastewater treatment primarily relies on biological processes, with advanced oxidation and other sewage treatment techniques being less common, resulting in a lower capacity for treating antibiotics in wastewater. The discharge of antibiotics from WWTPs into natural water bodies can lead to a decrease in the self-purification capacity and pollution load of the receiving water bodies, affecting the ecological health of river water environments [15]. Although the mass concentration of antibiotics in surface water is generally between ng/L and mg/L, they are sufficient to have harmful effects on exposed ecosystems or organisms [16]. It is necessary to conduct an assessment of their discharge volume and ecological risks [17]. In order to better understand the temporal variation in antibiotics in WWTPs and their removal rate and potential ecological risks, this study investigated the following: (1) the temporal variation in four types of nine antibiotics in influent and effluent urban and suburban WWTPs; (2) estimating the usage and annual discharge of antibiotics in the urban and suburban environment based on per capita pollution load.

2. Materials and Methods

2.1. Experimental Reagents and Instruments

Ultra-high purity compounds (>99%) of nine antibiotics, including roxithromycin (macrolides), ofloxacin (quinolones), norfloxacin(quinolones), ciprofloxacin (quinolones), tetracycline (tetracyclines), chlortetracycline (tetracyclines), oxytetracycline (tetracyclines), sulfadiazine(sulfonamides) and sulfamethoxazole (sulfonamides), were bought from Sigma-Aldrich (St. Louis, MO, USA). The standard concentrations of each antibiotic were 1000 μg/mL, with a purity of >99% (Tianjin Alta Technology Co., Ltd., Tianjin, China). Acetonitrile, methanol, and formic acid were chromatographically pure (Thermo Fisher Corporation, MA, USA), and anhydrous sodium sulfate, sodium chloride, sodium dihydrogen phosphate dodecahydrate, disodium acetate tetraacetate, etc., were all chemically pure (Sinopharm Chemical Reagent Co., Ltd., Beijing, China). All solutions were prepared using Milli-Q water.

2.2. Sample Collection and Processing

Seasonal sampling campaigns were conducted in 2023 [January to March (winter), April to May (spring), July to August (summer), and October (autumn)] in Tangshan. Samples were collected from influent and effluent WWTPs in the urban (n = 2) and suburban areas (n = 2). The flow scheme of WWTPs is shown in Figure 1. To reduce experimental errors, instantaneous water samples were collected every 2 h for a total of 4 times within 1 day. The collected water samples were mixed evenly and stored in brown glass bottles to avoid light. They were transported back to the laboratory in an ice bath within 24 h. After filtration with a 0.45 μm glass fiber membrane, 500 mL was accurately measured, 0.25 g Na2EDTA was added, and the pH was adjusted to about 3.0 with H3PO4. The samples were stored at 4 °C, and solid phase extraction was completed within 48 h.

2.3. Qualitative and Quantitative Analysis

Take 1 L of the water sample and use a vacuum filtration device to pass it through a 0.45 μm filter membrane. Use a fully automated solid phase extraction instrument and an HLB extraction column to complete the preliminary extraction and concentration. First, activate the extraction column with 10 mL of methanol and 10 mL of ultrapure water in sequence; then extract 1 L of water sample at a rate of 10 mL/min; after completion, use high-purity nitrogen to dry the extraction column for 20 min; finally, wash the extraction column with 5 mL of dichloromethane, 5 mL of ethyl acetate, 5 mL of n-hexane, and 5 mL of methanol in sequence, repeating twice. After extraction, use a rotary evaporator to concentrate the eluent to about 1 mL and transfer it to a test tube; then, use a nitrogen-blowing instrument to blow it nearly dry and dilute it to 1 mL with methanol. The diluted sample passes through a 0.22 μm organic filter membrane and is transferred to a liquid phase vial for testing. The pretreated samples were analyzed using UPLC-MS/MS (QTRAPTM5500 LC/MS/MS system, SCIEX, MA, USA), employing a Waters Cortecs T3 column (2.1 mm × 100 mm, 2.7 μm). The injection volume for liquid chromatography was 2 μL, with a flow rate of 0.3 mL·min−1 and a column temperature of 40 °C. The mobile phase was a gradient elution of 0.1% formic acid aqueous solution and acetonitrile. The qualitative and quantitative analysis of antibiotics was carried out using the multiple reaction detection scanning mode (MRM) and electrospray ionization mass spectrometry (ESI/MS) positive and negative ion modes [18,19].

2.4. Quality Control

Using methanol as the solvent, the standard stock solution was diluted to 0.1, 2, 0.5, 1, 2, 5, 10, 20, 50, 100, and 200 μg/L. Linear regression was performed between the concentration of the antimicrobial drug and the corresponding peak area to draw a standard curve for the antibiotics. The standard curve had a good linear correlation within the corresponding linear range (correlation coefficient R2 > 0.99).

2.5. Ecological Risk Assessment Method

The ecological risk assessment is a scientific evaluation of the potential damage of toxic and harmful pollutants to the ecological environment through quantitative characterization methods [20]. In this study, the risk quotient (RQ) was used to evaluate the ecological risk of antibiotics [20,21]. The calculation method of RQ is shown in Equation (1):
RQ = MEC(PEC)/PNEC
In the formula, MEC is the measured environmental concentration of antibiotics, PEC is the predicted concentration of antibiotics, and PNEC is the predicted no-effect concentration of antibiotics. In this study, the measured concentration of antibiotics, MEC, was used to calculate their risk quotient, and the predicted no-effect concentration (PNEC) was determined using the evaluation factor method. The chronic toxicity data (ChV) of antibiotics came from the Ecological Structure Activity Relationships Program (ECOSAR) predictive analyzer developed by the US Environmental Protection Agency. In this study, the ChV values for roxithromycin, tetracycline, chlortetracycline, oxytetracycline, ciprofloxacin, norfloxacin, ofloxacin, sulfadiazine, and sulfamethoxazole were 0.6, 20, 20, 20, 116, 114, 116, 0.101, and 0.068 mg/L, respectively. An extrapolation factor of 100 was selected to determine the PNEC of each antibiotic [22]. The PNEC values of each antibiotic are shown in Table 1. When RQ < 0.1, it is low risk; when 0.1 ≤ RQ < 1, it is medium risk; and when RQ ≥ 1, it is high risk [23,24].

2.6. Estimation of Use and Emissions

The daily mass load of antibiotics per capita in the influent of WWTPs [μg/(d·person)] can reflect the use of antibiotics in the service area of WWTPs, as shown in Equation (2) [25]:
Linfluent = (Q × Cinfluent)/Ptotal
In the formula, Q is the daily sewage flow of WWTP (m3/day) (Table S1), Cinfluent is the average concentration of antibiotics detected in the influent of WWTP (ng/L), and Ptotal is the number of residents in the service area of WWTPs (Table S1). Ptotal in the urban and suburban areas of Tangshan were, respectively, provided by the Tangshan Municipal Design Institute. The usage amount of antibiotics (U, kg/year) and the mass load of antibiotics in the effluent of WWTP (M, g/year) are shown in Equations (3) and (4) [26,27,28]:
U = Linfluent × Ptotal × 365× 10−9
M = Ceffluent × Q × 365× 10−6
In the formula, Linfluent represents the per capita pollution load of antibiotics [μg/(d·person)], and Ceffluent represents the average detection concentration of target antibiotics in the effluent of WWTPs (ng/L).

3. Results and Discussion

3.1. Influent

The seasonal variation trend of the total antibiotics concentration in the inflow of WWTPs in the Tangshan area was the highest in winter, followed by spring, summer, and autumn (Figure 2 and Figure 3). In spring, summer, and winter, the concentration of antibiotics in the inflow of urban WWTPs was higher than that of suburban WWTPs, while the opposite trend was observed in autumn (Figure 2). China announced that from 8 January 2023, COVID-19 infection will be adjusted from “Class A” to “Class B”. The monitoring data released by the National Influenza Center of China shows that since January 2023, the positive rate of influenza virus testing in the southern and northern provinces of China has continued to rise, and various regions have entered a high-incidence season of respiratory infectious diseases, with a significant increase in the number of infected individuals compared to previous years [29].
This study selected the winter collection of inlet and outlet water samples from four WWTPs from January to March 2023. It is currently in a period of high incidence of respiratory diseases in the north, as represented by pneumonia. The increase in the use of antibiotic samples by urban populations has led to a much higher total concentration of antibiotics in the inlet water samples of WWTPs than in the other three seasons.
Among the quinolone antibiotics, ofloxacin had the highest concentration detected in the influent water of WWTPs in spring and autumn, followed by norfloxacin and ciprofloxacin. The concentrations of the three quinolone antibiotics detected in the influent water of urban WWTPs were higher than those in the suburban WWTPs (Table 2). In summer and winter, norfloxacin had the highest concentration detected in the influent water of WWTPs, while ofloxacin had the lowest concentration detected. Norfloxacin and ciprofloxacin had the highest concentrations detected in the influent water of urban WWTPs, while ofloxacin showed the opposite trend (Table 2). The concentrations of tetracycline antibiotics detected in the influent water of urban WWTPs were higher than those in the suburban WWTPs in all four seasons, except for oxytetracycline, which had lower concentrations detected in the influent water of urban WWTPs in spring and autumn compared to those in the suburban WWTPs. Among the three tetracycline antibiotics, tetracycline, chlortetracycline, oxytetracycline, and oxytetracycline had the highest concentrations detected in spring, summer, autumn, and winter, respectively, while chlortetracycline (suburban WWTPs), tetracycline (suburban WWTPs), tetracycline (suburban WWTPs), and chlortetracycline (suburban WWTPs) had the lowest concentrations detected (Table 2).
During the study period, the macrolide antibiotic drug, roxithromycin, had the highest concentration detected in influent urban WWTPs, which was 1.15 times higher (spring), 1.35 times higher (summer), 1.25 times higher (autumn), and 1.31 times higher (winter) than that in suburban WWTPs (Table 2). The concentrations of sulfa antibiotics, sulfadiazine, and sulfamethoxazole, detected in influent suburban WWTPs were higher than that in urban WWTPs in spring and autumn while showing an opposite trend in summer and winter (Table 2). Sulfadiazine and sulfamethoxazole are antibiotics shared by humans and animals [30,31,32]. The breeding industry in suburban Tangshan is concentrated, and the use of veterinary antibiotics is high. Most veterinary antibiotics are excreted in the form of raw drugs or metabolites through animal feces and urine after administration and eventually enter the urban drainage system after sewage treatment [33,34,35]. Despite the legitimate reasons for their use, the current standards for the dosage of various veterinary antibiotics are inconsistent and imprecise, leading to the potential overuse of these drugs in livestock farming. This, in turn, raises the concentration of antibiotics in influent wastewater treatment plants within the farming region.
In influent WWTPs, (1) the concentration ranges of the nine antibiotics selected in this study, except for aureomycin, oxytetracycline, and ciprofloxacin, were much lower than those in Beijing (2018) in winter [36]; (2) the concentration of tetracycline antibiotics in summer was lower than existing research data, while the concentration of aureomycin and oxytetracycline in summer was higher than existing research data (except for Jiulongjiang River Basin), and the concentration of ciprofloxacin in quinolone antibiotics in summer and winter was higher than existing research data (except for Urumqi and Shihezi). In summer, the concentration of norfloxacin surpassed that of the Jiulongjiang River Basin yet remained lower than that of Urumqi and Shihezi at its peak. In summer, the concentration of ofloxacin was lower than that of the Jiulongjiang River Basin yet surpassed that of Yibin, Urumqi, and Shihezi [37,38,39,40]. (3) Among the sulfa antibiotics, sulfadiazine’s concentration in summer and autumn surpassed that of the Jiulongjiang River Basin yet remained lower than that of Urumqi and Shihezi. The concentration of sulfamethoxazole in summer exceeded that of the Jiulongjiang River Basin, though its peak value was lower than that observed in Beijing (2019) [38,39,40] (Table S2).

3.2. Effluent

The removal effect of antibiotics in WWTPs in different seasons is closely related to treatment processes, operating parameters, influent properties, and types of antibiotics. Currently, most WWTPs employ biological treatment processes to degrade organic matter, including antibiotics. These processes primarily involve microorganisms in activated sludge attaching to the cell surface through adsorption and absorption. Different types of microorganisms utilize their metabolic capabilities to decompose and transform antibiotics. Ultimately, these microorganisms break down the molecular structure of the antibiotics into smaller organic compounds or CO2 through enzyme production and oxidation, releasing corresponding metabolites. The seasonal variation characteristics of the detected concentration of antibiotics in the effluent of both urban and suburban WWTPs are shown in Figure 3. The total antibiotics concentration in effluent WWTPs in the winter was the highest, followed by spring, autumn, and summer. In winter, the concentration of antibiotics detected in the wastewater from urban WWTPs was higher than that from suburban WWTPs, while the trend was reversed in the other three seasons (Figure 3).
Currently, the WWTPs in Tangshan mainly use the A2O (anaerobic–anoxic–aerobic) process for sewage treatment. The A2O method is widely used in the sewage treatment system of northern China [41]. However, northern China experiences lengthy cold seasons, making it challenging for small-scale sewage biochemical treatment processes to operate stably [42]. Low temperatures decrease the activity of nitrifying and denitrifying bacteria, leading to a decline in the nitrogen removal efficiency of the A2O process and challenges in its stable operation [43,44]. Previous studies have found that temperature has a significant impact on the nitrogen removal efficiency of the A2O process. Nitrification reactions occur at 20–30 °C and almost stop at temperatures below 5 °C; denitrification reactions occur at 20–40 °C and rapidly decrease at temperatures below 15 °C. The winter temperatures in Tangshan and the surrounding areas are low, with average temperatures below 0 °C from January to February, which is not conducive to the degradation of antibiotics by microorganisms in activated sludge. Therefore, due to the impact of low temperatures on the efficiency of the A2O process, the total concentration of antibiotics in the effluent of WWTPs in winter is one order of magnitude higher than that in spring, autumn, and summer (Figure 2).
In the effluent of both urban and suburban WWTPs, macrolide antibiotics, such as roxithromycin, have the highest detection concentration in spring, while this corresponds with quinolone antibiotics in autumn and winter (Table 3). In the effluent samples of suburban WWTPs in summer, the concentration of sulfa antibiotics in the effluent is higher than that in the influent (Table 3) [45]. Previous studies have also observed a similar phenomenon, where the concentration of sulfa antibiotics in the effluent after treatment by activated sludge processes has increased. This phenomenon may be due to the following reasons: (1) antibiotics adsorbed in activated sludge are released into the water, resulting in an increase in the concentration of these drugs in the effluent from WWTPs. (2) During the A2O process, sulfa antibiotics are converted into other substances in the aerobic stage, and these substances are converted back into sulfa antibiotics in the anaerobic stage, resulting in an increase in the concentration of sulfa antibiotics in the effluent. In this study, the removal rates of nine antibiotics in urban and suburban WWTPs increased from 8.18% and 7.30% in winter to 70.14% and 66.82% in spring, and 79.58% and 73.91% in autumn. The removal rates of tetracyclines, quinolones, and sulfonamides in urban WWTPs were higher than those of macrolides in all four seasons, while the suburban WWTPs only followed the same trend in spring, autumn, and winter.
In the effluent of WWTPs, (1) the nine antibiotics selected in this study (excluding tetracycline, aureomycin, oxytetracycline, and ciprofloxacin) exhibited lower winter concentration ranges in comparison to Beijing (2018) [36]; (2) the roxithromycin concentration in summer was lower than that in the Zijiang River Basin of central Hunan, while in spring and autumn, they were an order of magnitude higher than those in Shenyang [36,39,46,47]; (3) Quinolone and tetracycline concentrations in spring and autumn were an order of magnitude higher than those in Shenyang, while in summer, they were an order of magnitude lower than concentrations in Yibin; (4) Sulfa antibiotic concentrations in summer and autumn were higher than those reported by Beijing (2019) and Shenyang, and in summer, they were an order of magnitude higher than those in Yibin [36,46,47] (Table S3). The variation in the spatial and temporal distribution of antibiotic concentrations was significant. This variation is primarily attributed to a complex interplay of factors, including the treatment processes and surface temperatures employed by sewage treatment plants across different regions, the sources and composition of sewage within the service area, and the size of the population served by these WWTPs.

3.3. Ecological Risk Assessment

In the effluent of WWTPs in winter, the RQ values of roxithromycin, tetracycline, chlortetracycline, and oxytetracycline in urban areas were 0.22, 0.1 (0.09), 0.1 (0.08), and 0.23, while those corresponding to roxithromycin and oxytetracycline were 0.17 and 0.1 (0.09) in suburban areas. This indicates that these macrolides and tetracyclines are medium-risk antibiotics. In the other three seasons, the four categories of nine antibiotics had RQ values of ≤0.1 in the effluent of WWTPs and showed low-risk antibiotics. It is worth noting that macrolides, including roxithromycin, are medium-risk antibiotics in the effluent of urban and suburban WWTPs in winter, and there is a possibility of the overuse of these drugs by residents in Tangshan. Chen et al. used RQs to assess the ecological risks of antimicrobial drugs. The results showed that erythromycin, roxithromycin, tetracycline, chlortetracycline, sulfamethoxazole, and norfloxacin were high-risk pollutants in water bodies in China, accounting for 20.9% [48]. In winter, various respiratory diseases, including mycoplasma pneumoniae, influenza, adenovirus, and respiratory syncytial virus infections, are highly prevalent. The peak season for mycoplasma pneumoniae infection occurs from August to February of the subsequent year, with the highest incidence of around December to January of the following year [49]. Macrolide antibiotics, such as roxithromycin and clarithromycin, are stable to acidic and have a long half-life (35–48 h), a broad antibacterial spectrum, high bioavailability, are widely distributed in the body, and have significant efficacy, with minimal gastrointestinal irritation [50]. They have become the first choice for treating mycoplasma pneumoniae infection [51,52]. At present, the resistance rate of Mycoplasma pneumoniae to macrolides has been on the rise worldwide [53]. East Asia is the region with the most serious resistance to macrolide drugs for Mycoplasma pneumoniae in the world. Studies have shown that the resistance rate in some areas of China has reached over 90%.

3.4. Estimation of Usage and Sewage Discharge

The per capita pollution load, annual usage, and annual emissions of antibiotics in Tangshan are presented in Table 4 and Table 5. The per capita pollution load of antibiotics was highest in spring, summer, and autumn for sulfamethoxazole, while the highest load in winter was for ofloxacin. From spring to winter, the per capita pollution load of antibiotics for urban residents was 9.63–13.74 times that of suburban residents, suggesting that urban residents may be at risk of antibiotic abuse (Table 4). In urban areas, the usage of roxithromycin (5.87 kg/a in spring), sulfamethoxazole (8.96 kg/a in summer), sulfamethoxazole (5.77 kg/a in autumn), and ofloxacin (17.76 kg/a in winter) significantly surpasses that of other antimicrobial agents. In contrast, the usage levels in suburban areas are as follows: sulfamethoxazole (0.17 kg/ain spring), norfloxacin (0.10 kg/ain summer), sulfamethoxazole (0.12 kg/ain autumn), and ofloxacin (0.32 kg/ain winter) (Table 4). It should be noted that the usage of antibiotics in urban areas was one order of magnitude higher than that in suburban areas (Table 5). After treatment by the A2O process in the WWTPs, the four types of nine antibiotics selected in this study, including roxithromycin (3.87 kg/a), norfloxacin (0.73 kg/a), roxithromycin (1.39 kg/a), and ofloxacin (15.96 kg/a), were the highest in terms of emissions from urban WWTPs in spring, summer, autumn, and winter, respectively. Roxithromycin, sulfamethoxazole, sulfamethoxazole, and ofloxacin were the highest in terms of emissions from suburban WWTPs during the corresponding periods, respectively. The total usage of the nine antibiotics in urban and suburban WWTPs in 2023 was 32.55 and 0.75 kg/a, 30.11 and 0.58 kg/a, 24.29 and 0.57 kg/a, and 96.05 and 1.59 kg/a, respectively, while the total emissions were 9.86 and 0.25 kg/a, 3.83 and 0.33 kg/a, 4.84 and 0.15 kg/a, and 88.38 and 1.48 kg/a, respectively.

4. Conclusions

Due to the high incidence of respiratory diseases, the use of antibiotics has increased, resulting in the highest concentration of antibiotics in the winter for both influent urban and suburban WWTPs. However, due to the low-temperature environment, the removal rate of antimicrobial drugs by the A2O process in WWTPs is the lowest in winter. Based on the RQ method for evaluating the ecological risk of antibiotics, it was found that the RQ values of roxithromycin, tetracycline, aureomycin, and oxytetracycline in the winter effluent samples from urban WWTPs were 0.22, 0.1 (0.09), 0.1 (0.08), and 0.23, respectively, identifying them as medium-risk antibiotics. The RQ values of roxithromycin and oxytetracycline in the winter effluent samples from suburban WWTPs were 0.17 and 0.1 (0.09), respectively, identifying them as medium-risk antibiotics. In the other three seasons, the four categories of nine antibiotics selected in this study had RQ values ≤ 0.1 in the effluent of WWTPs, all of which were low-risk pollutants. In the study area of Tangshan, the per capita pollution load of antibiotics was highest in spring, summer, and autumn for sulfamethoxazole while the highest in winter for ofloxacin. The highest use and emissions of antibiotics in the urban in spring, summer, autumn, and winter were roxithromycin (5.87 and 3.87 kg/a), sulfamethoxazole (8.96 kg/a), and norfloxacin (0.73 kg/a), while the highest use and emissions in suburban were sulfamethoxazole (0.17 kg/a) and roxithromycin (0.09 kg/a), norfloxacin (0.10 kg/a) and sulfamethoxazole (0.11 kg/a), sulfamethoxazole (0.12 and 0.03 kg/a), and ofloxacin (0.32 and 0.30 kg/a) in the same seasons.
This study focuses solely on the temporal distribution of target antibiotics in influent and effluent WWTPs. Certain antibiotics are susceptible to hydrolysis and removal in aquatic environments. Research indicates that macrolide antibiotics are prone to hydrolysis. Tetracycline antibiotics are not stable in water; for instance, the hydrolysis rate of oxytetracycline increases with deviations from neutral pH (pH = 7) and rising temperatures, whereas sulfonamides and fluoroquinolones are resistant to hydrolysis. pH and temperature are significant factors influencing hydrolysis. Consequently, it is imperative to further investigate the impact of seasonal variations in pH and temperature at the end of the drainage systems and within the treatment units of WWTPs on the temporal distribution of antibiotics to elucidate the driving factors behind any temporal trends observed in these agents’ distribution in the influent and effluent. Moreover, the adsorption of antibiotics by sewage plant sludge is a significant factor in enhancing the removal rate of these antibiotics. For antibiotics primarily removed through sludge adsorption (such as fluoroquinolones and sulfonamides), an extension in sludge retention time concurrently enhances their removal efficiency. However, the removal of certain antibiotics may not be impacted by sludge retention time. Hence, there is an urgent need for a comprehensive assessment of the physical adsorption and biodegradation of antibiotics in WWTPs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w16111627/s1, Table S1: Waste Water Treatment Plant (WWTP); Table S2: Comparison of the concentrations of target antibiotics in effluents from WWTPs in other cities; Table S3: Comparison of the concentrations of target antibiotics in influents from WWTPs in other cities.

Author Contributions

Conceptualization, Z.D. and J.H.; Methodology, G.H.; Formal analysis, J.H.; Investigation, Z.D., P.W. and Z.J.; Resources, Z.D. and P.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wang, S.Z.; Wang, J.L. Single atom cobalt catalyst derived from co-pyrolysis of vitamin B12 and graphitic carbon nitride for PMS activation to degrade emerging pollutants. Appl. Catal. B Environ. 2023, 321, 122051. [Google Scholar] [CrossRef]
  2. Wang, S.Z.; Xu, L.J.; Wang, J.L. Iron-based dual active site-mediated peroxymonosulfate activation for the degradation of emerging organic pollutants. Environ. Sci. Technol. 2021, 55, 15412–15422. [Google Scholar] [CrossRef]
  3. Zhuang, S.T.; Wang, J.L. Magnetic COFs as catalyst for Fenton-like degradation of sulfamethazine. Chemosphere 2021, 264, 128561. [Google Scholar] [CrossRef]
  4. Atif, M.; Sadeeqa, S.; Afzal, H.; Latif, S. Knowledge, Attitude and Practices regarding Antibiotics Use among Parents for their Children. Int. J. Pharm. Sci. Res. 2018, 9, 2140–2148. [Google Scholar] [CrossRef]
  5. Li, S.N.; Ondon, B.S.; Ho, S.H.; Jiang, J.W.; Li, F.X. Antibiotic resistant bacteria and genes in wastewater treatment plants: From occurrence to treatment strategies. Sci. Total Environ. 2022, 838, 156544. [Google Scholar] [CrossRef] [PubMed]
  6. Kovalakova, P.; Cizmas, L.; McDonald, T.J.; Marsalek, B.; Feng, M.; Sharma, V.K. Occurrence and Toxicity of Antibiotics in the Aquatic Environment: A Review. Chemosphere 2020, 251, 126351. [Google Scholar] [CrossRef]
  7. Qi, L.H.; Fan, W.H.; Li, J.; Cui, H.F.; Xu, J.X.; Gu, D.M.; Meng, J.J.; Liu, J. Persistent Nocardia beijingensis infection in a patient with postoperative abscess and misuse of antibiotics in China. Infect. Med. 2023, 2, 343–348. [Google Scholar] [CrossRef]
  8. Shao, Y.T.; Wang, Y.P.; Yuan, Y.W.; Xie, Y.J. A systematic review on antibiotics misuse in livestock and aquaculture and regulation implications in China. Sci. Total Environ. 2021, 798, 149205. [Google Scholar] [CrossRef]
  9. Luo, X.Z.; Han, S.; Wang, Y.; Du, P.; Li, X.Q.; Thai, P.K. Significant differences in usage of antibiotics in three Chinese cities measured by wastewater-based epidemiology. Water Res. 2024, 254, 121335. [Google Scholar] [CrossRef] [PubMed]
  10. Xiao, Y.H.; Li, L.J. Legislation of clinical antibiotic use in China. Lancet Infect. Dis. 2013, 13, 189–191. [Google Scholar] [CrossRef]
  11. Lenart-Boron, A.; Prajsnar, J.; Guzik, M.; Boron, P.; Chmiel, M. How much of antibiotics can enter surface water with treated wastewater and how it affects the resistance of waterborne bacteria: A case study of the Białka river sewage treatment plant. Environ. Res. 2020, 191, 110037. [Google Scholar] [CrossRef] [PubMed]
  12. Huang, H.W.; Zeng, S.Y.; Dong, X.; Li, D.; Zhang, Y.; He, M.; Du, P.F. Diverse and abundant antibiotics and antibiotic resistance genes in an urban water system. J. Environ. Manag. 2019, 231, 494–503. [Google Scholar] [CrossRef] [PubMed]
  13. Perez-Bou, L.; Gonzalez-Martinez, A.; Gonzalez-Lopez, J.; Correa-Galeote, D. Promising bioprocesses for the efficient removal of antibiotics and antibiotic-resistance genes from urban and hospital wastewaters: Potentialities of aerobic granular systems. Environ. Pollut. 2024, 342, 123115. [Google Scholar] [CrossRef] [PubMed]
  14. Zou, M.Y.; Tian, W.J.; Zhao, J.; Chu, M.L.; Song, T.T. Quinolone antibiotics in WWTPs with activated sludge treatment processes: A review on source, concentration and removal. Process Saf. Environ. 2022, 160, 116–129. [Google Scholar] [CrossRef]
  15. Yin, S.Y.; Gao, L.; Fan, X.M.; Gao, S.H.; Zhou, X.; Jin, W.B.; He, Z.Q.; Wang, Q.L. Performance of sewage sludge treatment for the removal of antibiotic resistance genes: Status and prospects. Sci. Total Environ. 2024, 907, 167862. [Google Scholar] [CrossRef] [PubMed]
  16. Silva, C.; Almeida, C.M.M.; Rodrigues, J.A.; Silva, S.; Coelho, M.D.; Martins, A.; Lourinho, R.; Cardoso, E.; Cardoso, V.V.; Benoliel, M.J.; et al. Improving the control of pharmaceutical compounds in activated sludge wastewater treatment plants: Key operating conditions and monitoring parameters. J. Water Process Eng. 2023, 54, 103985. [Google Scholar] [CrossRef]
  17. Nasir, A.; Saleh, M.; Aminzai, M.T.; Alary, R.; Dizge, N.; Yabalak, E. Adverse effects of veterinary drugs, removal processes and mechanisms: A review. J. Environ. Chem. Eng. 2024, 12, 111880. [Google Scholar] [CrossRef]
  18. Omar, T.F.T.; Aris, A.Z.; Yusoff, F.M.; Mustafa, S. An improved SPE-LC-MS/MS method for multiclass endocrine disrupting compound determination in tropical estuarine sediments. Talanta 2017, 173, 51–59. [Google Scholar] [CrossRef] [PubMed]
  19. Samaras, V.G.; Thomaidis, N.S.; Stasinakis, A.S.; Lekkas, T.D. An analytical method for the simultaneous trace determination of acidic pharmaceuticals and phenolic endocrine disrupting chemicals in wastewater and sewage sludge by gas chromatography-mass spectrometry. Anal. Bioanal. Chem. 2011, 399, 2549–2561. [Google Scholar] [CrossRef]
  20. European Commission Joint Research Centre (EC-JRC). Technical Guidance Document on Risk Assessment in Support of Commission Directive 93/67/EEC on Risk Assessment for New Notified Substances, Commission Regulation (EC) No 1488/94 on Risk Assessment for Existing Substances, and Directive 98/8/EC of the European Parliament and of the Council Concerning the Placing of Biocidal Products on the Market; Part I–IV, European Chemicals Bureau (ECB), JRC-ISPRA (VA), Italy, April 2003; Part II. EUR; Institute for Health and Consumer Protection: Ispra, Italy, 2003. [Google Scholar]
  21. Shams, D.F.; Izaz, M.; Khan, W.; Nayab, S.; Tawab, A.; Baig, S.A. Occurrence of selected antibiotics in urban rivers in northwest Pakistan and assessment of ecotoxicological and antimicrobial resistance risks. Chemosphere 2024, 352, 141357. [Google Scholar] [CrossRef]
  22. Letsinger, S.; Kay, P. Comparison of prioritisation schemes for human pharmaceuticals in the aquatic environment. Environ. Sci. Pollut. Res. 2019, 26, 3479–3491. [Google Scholar] [CrossRef] [PubMed]
  23. Verlicchi, P.; Al Aukidy, M.; Zambello, E. Occurrence of pharmaceutical compounds in urban wastewater: Removal, mass load and environmental risk after a secondary treatment-a review. Sci. Total Environ. 2012, 429, 123–155. [Google Scholar] [CrossRef] [PubMed]
  24. Rodriguez-Mozaz, S.; Chamorro, S.; Marti, E.; Huerta, B.; Gros, M.; Sànchez-Melsió, A.; Borrego, C.M.; Barceló, D.; Balcázar, J.L. Occurrence of antibiotics and antibiotic resistance genes in hospital and urban wastewaters and their impact on the receiving river. Water Res. 2015, 69, 234–242. [Google Scholar] [CrossRef] [PubMed]
  25. Gan, X.M.; Yan, Q.; Gao, X.; Zhang, Y.X.; Zi, C.F.; Peng, X.Y.; Guo, J.S. Occurrence and Fate of Typical Antibiotics in a Wastewater Treatment Plant in Southwest China. Environ. Sci. 2014, 35, 1817–1823. (In Chinese) [Google Scholar]
  26. Liu, W.R.; Yang, Y.Y.; Liu, Y.S.; Zhang, L.J.; Zhao, J.L.; Zhang, Q.Q.; Zhang, M.; Zhang, J.N.; Jiang, Y.X.; Ying, G.G. Biocides in wastewater treatment plants: Mass balance analysis and pollution load estimation. J. Hazard. Mater. 2017, 329, 310–320. [Google Scholar] [CrossRef] [PubMed]
  27. Huang, Z.; Zhao, J.L.; Yang, Y.Y.; Jia, Y.W.; Zhang, Q.Q.; Chen, C.E.; Liu, Y.S.; Yang, B.; Xie, L.T.; Ying, G.G. Occurrence, mass loads and risks of bisphenol analogues in the Pearl River Delta region, South China: Urban rainfall runoff as a potential source for receiving rivers. Environ. Pollut. 2020, 263, 114361. [Google Scholar] [CrossRef] [PubMed]
  28. Lei, H.J.; Yang, B.; Ye, P.; Yang, Y.Y.; Zhao, J.L.; Liu, Y.S.; Xie, L.T.; Ying, G.G. Occurrence, fate and mass loading of benzodiazepines and their transformation products in eleven wastewater treatment plants in Guangdong province, China. Sci. Total Environ. 2021, 755, 142648. [Google Scholar] [CrossRef] [PubMed]
  29. Zhu, K.Y.; Tu, W.X.; Feng, Y.N.; Bai, W.Q.; Xie, Y.R.; Zhang, Q.; Ren, J.H.; Shi, G.Q.; Xiang, N.J.; Meng, L. Risk assessment of public health emergencies concerned in China, December 2023. Dis. Surveill. 2023, 38, 1421–1424. [Google Scholar]
  30. Zheng, H.S.; Zhang, Y.F.; Li, S.; Feng, X.C.; Wu, Q.L.; Leong, Y.K.; Chang, J.S. Antibiotic sulfadiazine degradation by persulfate oxidation: Intermediates dependence of ecotoxicity and the induction of antibiotic resistance genes. Bioresour. Technol. 2023, 368, 128306. [Google Scholar] [CrossRef]
  31. Hu, L.; Zhang, G.; Wang, Q.; Wang, X.; Wang, P. Effect of Microwave Heating on Persulfate Activation for Rapid Degradation and Mineralization of p-Nitrophenol. ACS Sustain. Chem. Eng. 2019, 7, 11662–11671. [Google Scholar] [CrossRef]
  32. Duan, W.; Cui, H.; Jia, X.; Huang, X. Occurrence and ecotoxicity of sulfonamides in the aquatic environment: A review. Sci. Total Environ. 2022, 820, 153178. [Google Scholar] [CrossRef] [PubMed]
  33. Daghrir, R.; Drogui, P. Tetracycline antibiotics in the environment: A review. Environ. Chem. Lett. 2013, 11, 20–227. [Google Scholar] [CrossRef]
  34. Xu, L.Y.; Zhang, H.; Xiong, P.; Zhu, Q.Q.; Liao, C.Y.; Jiang, G.B. Occurrence, fate, and risk assessment of typical tetracycline antibiotics in the aquatic environment: A review. Sci. Total Environ. 2020, 753, 141975. [Google Scholar] [CrossRef] [PubMed]
  35. Leichtweis, J.; Vieira, Y.; Welter, N.; Silvestri, S.; Dotto, G.L.; Carissimi, E. A review of the occurrence, disposal, determination, toxicity and remediation technologies of the tetracycline antibiotic. Process Saf. Environ. 2022, 160, 25–40. [Google Scholar] [CrossRef]
  36. Liu, X.H.; Zhang, G.D.; Liu, Y.; Lu, S.Y.; Qin, P.; Guo, X.C.; Bi, B.; Wang, L.; Xi, B.D.; Wu, F.C.; et al. Occurrence and fate of antibiotics and antibiotic resistance genes in typical urban water of Beijing, China. Environ. Pollut. 2019, 246, 163–173. [Google Scholar] [CrossRef] [PubMed]
  37. Li, Z.; Xu, H.B.; Qu, J.; Qu, L.L.; Wang, S.; Wang, N.; Zheng, X.B.; Zhang, X. Characteristics of Typical Antibiotics in Effluent from Shenyang Sewage Treatment Plant and Its Ecological Risk Assessment. Sci. Technol. Innov. 2023, 468, 87–91. (In Chinese) [Google Scholar]
  38. Li, Y.; Wang, J.; Lin, C.Y.; Lian, M.S.; He, M.C.; Liu, X.T.; Ouyang, W. Occurrence, removal efficiency, and emission of antibiotics in the sewage treatment plants of a low-urbanized basin in China and their impact on the receiving water. Sci. Total Environ. 2024, 921, 171134. [Google Scholar] [CrossRef] [PubMed]
  39. Tang, T.T.; Zhao, Z.Y.; Wang, Y.; Qiao, X.J.; Gu, B.C.; Wang, W.Q. Antibiotic Pollution Level and Ecological Risk Assessment of Township Wastewater Treatment Plants. Environ. Sci. 2024. [Google Scholar] [CrossRef]
  40. Wang, L.; Zhu, D.; Cao, Y.X.; Yu, X.D.; Hui, Y.M.; Li, W.C.; Wang, D.H. Seasonal changes and ecological risk assessment of pharmaceutical and personal care products in the effluents of wastewater treatment plants in Beijing. Acta Sci. Circumstantiae 2021, 41, 2922–2932. [Google Scholar] [CrossRef]
  41. Lan, Z.H.; Zhang, Y.P.; Liang, R.L.; Wang, Z.Q.; Sun, J.; Lu, X.W.; He, Y.; Wang, Y.J. Comprehensive comparison of integrated fixed-film activated sludge (IFAS) and AAO activated sludge methods: Influence of different operational parameters. Chemosphere 2024, 357, 142068. [Google Scholar] [CrossRef]
  42. Pu, M.; Ailijiang, N.; Mamat, A.W.; Chang, J.L.; Zhang, Q.F.; Liu, Y.F.; Li, N.X. Occurrence of antibiotics in the different biological treatment processes, reclaimed wastewater treatment plants and effluent-irrigated soils. J. Environ. Chem. Eng. 2022, 10, 107715. [Google Scholar] [CrossRef]
  43. Wang, R.M.; Ji, M.; Zhai, H.Y.; Guo, Y.J.; Liu, Y. November Occurrence of antibiotics and antibiotic resistance genes in WWTP effluent-receiving water bodies and reclaimed wastewater treatment plants. Sci. Total Environ. 2021, 796, 148919. [Google Scholar] [CrossRef]
  44. Li, W.H.; Shi, Y.L.; Gao, L.H.; Liu, J.M.; Cai, Y.Q. Occurrence, distribution and potential affecting factors of antibiotics in sewage sludge of wastewater treatment plants in China. Sci. Total Environ. 2013, 445–446, 306–313. [Google Scholar] [CrossRef]
  45. Liu, Z.G.; Zhang, Y.; Zhou, W.; Wang, W.; Dai, X.H. Comparison of Nitrogen and Phosphorus Removal between Two Typical Processes under Low Temperature in a Full-Scale Municipal Wastewater Treatment Plant. Water 2022, 14, 3874. [Google Scholar] [CrossRef]
  46. Zhang, H.; Du, M.M.; Jiang, H.Y.; Zhang, D.D.; Lin, L.F.; Yea, H.; Zhang, X. Occurrence, seasonal variation and removal efficiency of antibiotics and their metabolites in wastewater treatment plants, Jiulongjiang River Basin, South China. Environ. Sci. Process. Impacts 2015, 17, 225. [Google Scholar] [CrossRef]
  47. Liu, J.; Lu, J.J.; Tong, Y.B.; Li, C. Occurrence and elimination of antibiotics in three sewage treatment plants with different treatment technologies in Urumqi and Shihezi, Xinjiang. Water Sci. Technol. 2017, 75, 1474–1484. [Google Scholar] [CrossRef] [PubMed]
  48. Chen, L.H.; Cao, Y.; Li, Q.; Meng, T.; Zhang, S. Pollution Characteristics and Ecological Risk Assessment of Typical Antibiotics in Environmental Media in China. Environ. Sci. 2023, 44, 6894–6908. [Google Scholar] [CrossRef] [PubMed]
  49. Debnath, S.K.; Debnath, M.; Srivastava, R. Opportunistic etiological agents causing lung infections: Emerging need to transform lung-targeted delivery. Heliyon 2022, 8, e12620. [Google Scholar] [CrossRef] [PubMed]
  50. Belizário, J.; Garay-Malpartida, M.; Faintuch, J. Lung microbiome and origins of the respiratory diseases. Curr. Res. Immunol. 2023, 4, 100065. [Google Scholar] [CrossRef]
  51. Bebear, C.; Dupon, M.; Renaudin, H.; Debarbeyrac, B. Potential Improvements in Therapeutic Options for Mycoplasmal Respiratory-infections. Clin. Infect. Dis. 1993, 17, S202–S207. [Google Scholar] [CrossRef]
  52. Tsai, T.A.; Tsai, C.K.; Kuo, K.C.; Yu, H.R. Rational stepwise approach for Mycoplasma pneumoniae pneumonia in children. J. Microbiol. Immunol. 2021, 54, 557–565. [Google Scholar] [CrossRef] [PubMed]
  53. Rafei, R.; Al Iaali, R.; Osman, M.; Dabboussi, F.; Hamze, M. A global snapshot on the prevalent macrolide-resistant emm types of Group A Streptococcus worldwide, their phenotypes and their resistance marker genotypes during the last two decades: A systematic review. Infect. Genet. Evol. 2022, 99, 105258. [Google Scholar] [CrossRef] [PubMed]
Water 16 01627 g001
Figure 1. Schematic diagram of wastewater treatment plants (WWTPs) in Tangshan.
Figure 1. Schematic diagram of wastewater treatment plants (WWTPs) in Tangshan.
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Figure 2. The occurrence of antibiotics in the influent and effluent of wastewater treatment plants (WWTPs) in Tangshan.
Figure 2. The occurrence of antibiotics in the influent and effluent of wastewater treatment plants (WWTPs) in Tangshan.
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Figure 3. The occurrence of antibiotics in the influent and effluent of urban and suburban WWTPs in Tangshan.
Figure 3. The occurrence of antibiotics in the influent and effluent of urban and suburban WWTPs in Tangshan.
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Table 1. PNEC (μg/L) of the target antibiotic in effluents from wastewater treatment plants (WWTPs).
Table 1. PNEC (μg/L) of the target antibiotic in effluents from wastewater treatment plants (WWTPs).
Target AntibioticPNEC
Roxithromycin1.5
Tetracycline1.0
Aureomycin1.0
Oxytetracycline1.0
Ciprofloxacin20,000
Norfloxacin23,000
Ofloxacin22,000
Sulfadiazine15
Sulfamethoxazole6.4
Table 2. The occurrence of antibiotics (ng/L) in the influent of wastewater treatment plants (WWTPs).
Table 2. The occurrence of antibiotics (ng/L) in the influent of wastewater treatment plants (WWTPs).
UrbanSuburban
Antibiotics SpringSummerAutumnWinterSpringSummerAutumnWinter
RoxithromycinMean170.4046.2378.19353.33148.2034.1462.42270.22
SD26.7815.523.7727.3431.391.7812.5538.40
TetracyclineMean76.8318.0314.72104.2361.1914.1712.8871.22
SD9.664.293.8943.1312.341.752.4917.70
AureomycinMean50.3352.9818.5496.8528.2149.6816.1285.15
SD13.6721.242.9151.2721.5810.483.4263.47
OxytetracyclineMean40.4144.8736.22256.7042.3036.6262.33101.67
SD15.461.566.8617.961.417.7933.0110.80
CiprofloxacinMean99.83123.9679.68451.7986.73107.3168.25316.84
SD15.3222.6912.5219.7618.3731.8213.779.56
NorfloxacinMean122.10135.1797.50458.49105.76116.5684.89321.42
SD17.9117.6815.3220.0522.4124.7018.049.87
OfloxacinMean125.3747.87122.62491.53106.5387.7289.93422.56
SD64.021.1821.5714.1253.252.194.7693.96
SulfadiazineMean96.48133.3487.67145.70117.63103.14142.60110.25
SD21.4715.5719.4317.0111.3720.2442.6220.06
SulfamethoxazoleMean171.60235.80140.55275.04213.65121.98164.26217.34
SD36.3927.5349.7032.1225.0116.2353.8046.54
Table 3. Occurrence of antibiotics (ng/L) in the effluent of wastewater treatment plants (WWTPs).
Table 3. Occurrence of antibiotics (ng/L) in the effluent of wastewater treatment plants (WWTPs).
UrbanSuburban
Antibiotics SpringSummerAutumnWinterSpringSummerAutumnWinter
RoxithromycinMean107.2322.8235.68322.58104.9315.8024.75248.95
SD3.179.786.6215.0613.542.641.9138.02
TetracyclineMean9.53ND1.8593.607.512.98ND64.32
SD1.60ND2.6239.694.220.87ND15.72
AureomycinMean5.636.13ND89.746.115.27ND78.82
SD0.950.71ND50.213.071.13ND60.22
OxytetracyclineMean5.485.772.36234.566.504.909.1291.94
SD0.600.433.3414.462.190.905.4910.61
CiprofloxacinMean26.2816.1614.65418.7220.2731.2221.11297.48
SD4.351.854.1718.311.093.809.562.77
NorfloxacinMean29.7120.3821.59424.8627.5133.1325.88295.44
SD3.511.073.1618.584.258.2510.148.82
OfloxacinMean29.109.0320.78442.0834.3226.2728.48394.54
SD12.450.854.2213.3220.342.493.2881.54
SulfadiazineMean34.2212.23139.90135.1642.88133.5928.73101.28
SD7.380.751.7015.785.1614.8812.1717.56
SulfamethoxazoleMean37.1819.6021.13256.6752.20145.7339.51201.87
SD7.904.5314.2034.426.8424.766.8644.41
Note: ND: not detected.
Table 4. Estimates of per capita pollution load of antibiotics [μg/(d·person)] in Tangshan.
Table 4. Estimates of per capita pollution load of antibiotics [μg/(d·person)] in Tangshan.
UrbanSuburban
AntibioticsSpringSummerAutumnWinterSpringSummerAutumnWinter
Roxithromycin63.11 17.12 28.96 130.86 5.49 1.26 2.31 10.01
Tetracycline28.46 6.68 5.45 38.60 2.27 0.52 0.48 2.64
Aureomycin18.64 19.62 6.87 35.87 1.04 1.84 0.60 3.15
Oxytetracycline14.96 16.62 13.41 95.07 1.57 1.36 2.31 3.77
Ciprofloxacin36.98 45.91 29.51 167.30 3.21 3.97 2.53 11.73
Norfloxacin45.19 50.06 36.11 169.81 3.92 4.32 3.14 11.90
Ofloxacin46.43 17.73 45.41 182.05 3.95 3.25 3.26 15.65
Sulfadiazine35.73 49.39 32.47 53.96 4.36 3.82 5.28 4.08
Sulfamethoxazole63.56 87.33 52.06 101.87 7.91 4.52 6.08 8.05
Total353.06 310.46 250.25 975.40 33.71 24.86 25.99 70.99
Table 5. Estimates of antibiotics use and emissions (kg/a) in Tangshan.
Table 5. Estimates of antibiotics use and emissions (kg/a) in Tangshan.
UrbanSuburban
SpringSummerAutumnWinterSpringSummerAutumnWinter
Use
Roxithromycin5.87 1.49 2.90 12.540.13 0.03 0.06 0.23
Tetracycline2.93 0.60 0.49 3.250.05 0.01 0.01 0.05
Aureomycin2.01 1.66 0.64 4.20 0.03 0.04 0.01 0.09
Oxytetracycline1.28 1.66 1.23 9.60 0.04 0.03 0.06 0.09
Ciprofloxacin3.45 4.23 2.75 16.23 0.08 0.10 0.06 0.26
Norfloxacin4.22 4.71 3.36 16.48 0.09 0.10 0.08 0.26
Ofloxacin3.75 1.73 4.20 17.76 0.07 0.07 0.07 0.32
Sulfadiazine3.24 5.07 2.95 5.54 0.09 0.09 0.10 0.10
Sulfamethoxazole5.79 8.96 5.77 10.45 0.17 0.09 0.12 0.19
Emissions
Roxithromycin3.87 0.71 1.39 11.58 0.09 0.01 0.02 0.22
Tetracycline0.33 0.00 0.03 2.90 0.01 0.00 0.00 0.05
Aureomycin0.22 0.21 0.00 3.92 0.01 0.00 0.00 0.08
Oxytetracycline0.19 0.20 0.04 8.75 0.01 0.00 0.01 0.08
Ciprofloxacin0.90 0.57 0.48 15.05 0.02 0.03 0.02 0.24
Norfloxacin1.04 0.73 0.75 15.27 0.02 0.03 0.02 0.24
Ofloxacin0.90 0.32 0.70 15.96 0.02 0.02 0.02 0.30
Sulfadiazine1.15 0.44 0.49 5.14 0.03 0.11 0.02 0.09
Sulfamethoxazole1.26 0.66 0.95 9.81 0.04 0.11 0.03 0.18
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Dong, Z.; Hu, J.; Wang, P.; Han, G.; Jia, Z. Antibiotics in Wastewater Treatment Plants in Tangshan: Perspectives on Temporal Variation, Residents’ Use and Ecological Risk Assessment. Water 2024, 16, 1627. https://doi.org/10.3390/w16111627

AMA Style

Dong Z, Hu J, Wang P, Han G, Jia Z. Antibiotics in Wastewater Treatment Plants in Tangshan: Perspectives on Temporal Variation, Residents’ Use and Ecological Risk Assessment. Water. 2024; 16(11):1627. https://doi.org/10.3390/w16111627

Chicago/Turabian Style

Dong, Zhuo, Jian Hu, Pengjie Wang, Gengtao Han, and Zheng Jia. 2024. "Antibiotics in Wastewater Treatment Plants in Tangshan: Perspectives on Temporal Variation, Residents’ Use and Ecological Risk Assessment" Water 16, no. 11: 1627. https://doi.org/10.3390/w16111627

APA Style

Dong, Z., Hu, J., Wang, P., Han, G., & Jia, Z. (2024). Antibiotics in Wastewater Treatment Plants in Tangshan: Perspectives on Temporal Variation, Residents’ Use and Ecological Risk Assessment. Water, 16(11), 1627. https://doi.org/10.3390/w16111627

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