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Research article · 2025 · Full text

International Journal of Advanced Chemistry Research

Occurrence and risk assessment of antibiotic residues in surface water sources

Saeed KarimiNiloufar Rezaei

Volume 7(6) · Pages 92–96 · DOI: 10.33545/26646781.2025.v7.i6b.529 ↗

Research areasPharmaceutical and Antibiotic Environmental ImpactsAntibiotic Use and ResistancePesticide and Herbicide Environmental Studies

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Abstract

Author-written

Widespread antibiotic consumption in human medicine and livestock husbandry has turned surface waterways into unintended reservoirs of antimicrobial residues, yet monitoring programmes in semi-arid regions of western Asia remain limited. This research quantifies the occurrence of six antibiotics—sulfamethoxazole, trimethoprim, ciprofloxacin, ofloxacin, erythromycin, and tetracycline—at five sampling stations along the Aji Chay river corridor near Tabriz, Iran, and assesses ecological risk using hazard quotient methodology. Water samples were collected monthly from March to October 2023, filtered through 0.45 μm membranes, pre-concentrated by solid-phase extraction on Oasis HLB cartridges, and analysed by liquid chromatography-tandem mass spectrometry. Detection frequencies ranged from 78.3% for erythromycin to 100% for ciprofloxacin. The highest individual concentration recorded was 3.67 μg/L for ciprofloxacin at the hospital-adjacent station (S3), while upstream reference levels stayed below 0.15 μg/L for all analytes. Risk quotients calculated as the ratio of measured environmental concentration to the predicted no-effect concentration exceeded unity for ciprofloxacin (RQ = 1.83) and ofloxacin (RQ = 1.47) at the urban and hospital stations, indicating a high probability of adverse effects on aquatic organisms. Sulfonamides and macrolides remained below the risk threshold at all stations. Seasonal patterns showed peak concentrations during summer low-flow months when dilution capacity was at its lowest. The data highlight the need for point-source controls, particularly at hospital effluent outfalls, and suggest that fluoroquinolones should be prioritised in future national monitoring frameworks for Iranian surface waters.

Summary

Source-checked

Plain-language reading of the full paper, prepared with AI and checked against the text. Each point links to the authors' own words.

  1. Why it matters

    • High levels of antibiotic use in humans and livestock have led to surface waters becoming reservoirs for antimicrobial residues. View evidence ↗

      Why it matters

      High levels of antibiotic use in humans and livestock have led to surface waters becoming reservoirs for antimicrobial residues.

      In the paper's own words

      “Widespread antibiotic consumption in human medicine and livestock husbandry has turned surface waterways into unintended reservoirs of antimicrobial residues”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Antibiotic residues in water can promote the development of antimicrobial resistance genes in microbial communities, even at very low concentrations. View evidence ↗

      Why it matters

      Antibiotic residues in water can promote the development of antimicrobial resistance genes in microbial communities, even at very low concentrations.

      In the paper's own words

      “Once in surface water, these residues exert selective pressure on microbial communities at concentrations far below therapeutic levels, accelerating the emergence of antimicrobial resistance genes”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Iran has some of the highest per capita antibiotic use in the Middle East due to prophylactic livestock dosing and over-the-counter availability. View evidence ↗

      Why it matters

      Iran has some of the highest per capita antibiotic use in the Middle East due to prophylactic livestock dosing and over-the-counter availability.

      In the paper's own words

      “In Iran, antibiotic use per capita ranks among the highest in the Middle East, driven by over-the-counter availability and a large livestock sector that relies on prophylactic dosing”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  2. What they did

    • Water samples were collected from five distinct locations along the Aji Chay river, including an upstream reference, urban areas, a hospital outfall, an agricultural zone, and a downstream confluence. View evidence ↗

      What they did

      Water samples were collected from five distinct locations along the Aji Chay river, including an upstream reference, urban areas, a hospital outfall, an agricultural zone, and a downstream confluence.

      In the paper's own words

      “Water samples were collected at five stations along the Aji Chay river corridor near Tabriz: S1 (upstream reference, 18 km north of the city), S2 (central urban reach), S3 (300 m downstream of Tabriz University Hospital outfall), S4 (agricultural zone, 6 km southeast), and S5 (downstream confluence, 12 km south).”

      Page 2

      Found in: Materials

      Read it in the full textOpen PDF at page 2 ↗
    • The sampling campaign took place monthly from March to October 2023 using 2.5 L amber glass bottles. View evidence ↗

      What they did

      The sampling campaign took place monthly from March to October 2023 using 2.5 L amber glass bottles.

      In the paper's own words

      “Grab samples (2.5 L amber glass bottles, pre-rinsed with methanol and river water) were taken monthly from March to October 2023”

      Page 2

      Found in: Materials

      Read it in the full textOpen PDF at page 2 ↗
    • Analytes were concentrated 500-fold via solid-phase extraction and analyzed using UHPLC coupled to a triple-quadrupole mass spectrometer. View evidence ↗

      What they did

      Analytes were concentrated 500-fold via solid-phase extraction and analyzed using UHPLC coupled to a triple-quadrupole mass spectrometer.

      In the paper's own words

      “Solid-phase extraction on Oasis HLB 6-cc cartridges (Waters, USA) concentrated analytes 500-fold”

      Page 2

      “Chromatographic separation and detection used an Agilent 1290 Infinity II UHPLC coupled to an Agilent 6470B triple-quadrupole mass spectrometer”

      Page 2

      Found in: Materials

      Read it in the full textOpen PDF at page 2 ↗
  3. What they found

    • Antibiotics were frequently detected, with ciprofloxacin appearing in 100% of samples and erythromycin in 78.3%. View evidence ↗

      What they found

      Antibiotics were frequently detected, with ciprofloxacin appearing in 100% of samples and erythromycin in 78.3%.

      In the paper's own words

      “Detection frequencies ranged from 78.3% for erythromycin to 100% for ciprofloxacin.”

      Page 1

      Found in: Quality Control

      Read it in the full textOpen PDF at page 1 ↗
    • The highest concentration found was 3.67 μg/L of ciprofloxacin near the hospital (S3), whereas upstream levels remained below 0.15 μg/L. View evidence ↗

      What they found

      The highest concentration found was 3.67 μg/L of ciprofloxacin near the hospital (S3), whereas upstream levels remained below 0.15 μg/L.

      In the paper's own words

      “The highest individual concentration recorded was 3.67 μg/L for ciprofloxacin at the hospital-adjacent station (S3), while upstream reference levels stayed below 0.15 μg/L for all analytes.”

      Page 1

      Found in: Quality Control

      Read it in the full textOpen PDF at page 1 ↗
    • Sulfonamides and macrolides did not exceed the ecological risk threshold at any of the sampled stations. View evidence ↗

      What they found

      Sulfonamides and macrolides did not exceed the ecological risk threshold at any of the sampled stations.

      In the paper's own words

      “Sulfonamides and macrolides remained below the risk threshold at all stations.”

      Page 1

      Found in: Conclusion

      Read it in the full textOpen PDF at page 1 ↗
    • Antibiotic concentrations were 1.6 to 2.8 times higher during the dry season compared to the wet season for all monitored compounds. View evidence ↗

      What they found

      Antibiotic concentrations were 1.6 to 2.8 times higher during the dry season compared to the wet season for all monitored compounds.

      In the paper's own words

      “Dry-season concentrations were 1.6 to 2.8-fold higher than wet-season values for all compounds”

      Page 3

      Found in: Quality Control

      Read it in the full textOpen PDF at page 3 ↗
  4. What it means

    • The authors conclude that the hospital outfall at S3 is the primary source of fluoroquinolones and recommend advanced treatments like ozonation or activated carbon. View evidence ↗

      What it means

      The authors conclude that the hospital outfall at S3 is the primary source of fluoroquinolones and recommend advanced treatments like ozonation or activated carbon.

      In the paper's own words

      “the hospital effluent outfall at S3 is the single largest contributor to fluoroquinolone loading and would benefit most from targeted advanced treatment such as ozonation or activated-carbon polishing.”

      Page 4

      Found in: Conclusion

      Read it in the full textOpen PDF at page 4 ↗
    • The authors recommend that fluoroquinolones be included in Iran's national surface water quality monitoring programs. View evidence ↗

      What it means

      The authors recommend that fluoroquinolones be included in Iran's national surface water quality monitoring programs.

      In the paper's own words

      “fluoroquinolones should be added to any future national monitoring programme for surface water quality in Iran”

      Page 4

      Found in: Conclusion

      Read it in the full textOpen PDF at page 4 ↗
    • The study did not analyze river sediments, which may act as long-term sources of antibiotics. View evidence ↗

      What it means

      The study did not analyze river sediments, which may act as long-term sources of antibiotics.

      In the paper's own words

      “One limitation of this research is the absence of sediment analysis.”

      Page 4

      Found in: Discussion

      Read it in the full textOpen PDF at page 4 ↗
    • The sampling period lasted only eight months, omitting the winter season when snowmelt might mobilize residues. View evidence ↗

      What it means

      The sampling period lasted only eight months, omitting the winter season when snowmelt might mobilize residues.

      In the paper's own words

      “A second limitation is the eight-month sampling window, which excludes the winter period when snowmelt may mobilize accumulated residues”

      Page 4

      Found in: Discussion

      Read it in the full textOpen PDF at page 4 ↗

Visual summary

3 visuals

Illustrations explain the paper; charts are replotted from the paper's own table values.

AI-generated illustration
AI-generated conceptual illustration (A river flowing through a landscape containing a hospital building and a livestock farm). It explains the idea and does not show study data.↗ Enlarge
Spatial Distribution of Contamination
AI-generated conceptual illustration (A river flowing through a landscape containing a hospital building and a livestock farm). It explains the idea and does not show study data.

AI-generated conceptual illustration (A river flowing through a landscape containing a hospital building and a livestock farm). It explains the idea and does not show study data.

Open full-size image ↗

Spatial Distribution of Contamination

AI-generated conceptual illustration (A river flowing through a landscape containing a hospital building and a livestock farm). It explains the idea and does not show study data.

View source evidence ↗
Replotted from source data
Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.↗ Enlarge
Mean (μg/L) and Max (μg/L): Sulfamethoxazole vs Trimethoprim vs Ciprofloxacin vs Ofloxacin vs Erythromycin
Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

Open full-size image ↗

Mean (μg/L) and Max (μg/L): Sulfamethoxazole vs Trimethoprim vs Ciprofloxacin vs Ofloxacin vs Erythromycin

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

View source evidence ↗
Replotted from source data
Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.↗ Enlarge
Wet Season (μg/L) and Dry Season (μg/L): Sulfamethoxazole vs Trimethoprim vs Ciprofloxacin vs Ofloxacin vs Erythromycin
Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.

Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.

Open full-size image ↗

Wet Season (μg/L) and Dry Season (μg/L): Sulfamethoxazole vs Trimethoprim vs Ciprofloxacin vs Ofloxacin vs Erythromycin

Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.

View source evidence ↗

Figures & tables

From the original paper
Summary statistics for six antibiotics monitored at five stations along the Aji Chay river corridor (March–October 2023). DF =Table 1Page 2Seasonal comparison of antibiotic concentrations (mean ±Table 2Page 3Heatmap of mean antibiotic concentrations (μg/L) across five sampling stations along the Aji Chay river corridor (March–OctoberFigure 1Page 3Risk quotients for six antibiotics at the most impacted station. The dashed red line marks the high-risk threshold (RQ = 1.0). ErrorFigure 2Page 3
FULL TEXT Original article · reflowed for reading

Introduction

The global consumption of antibiotics exceeds 100, 000 tonnes per year, and a large fraction of each administered dose is excreted in metabolically active or parent form, entering wastewater streams that eventually reach rivers, lakes, and reservoirs [1,2] . Once in surface water, these residues exert selective pressure on microbial communities at concentrations far below therapeutic levels, accelerating the emergence of antimicrobial resistance genes that can transfer to human pathogens through horizontal gene exchange [3] . The World Health Organization has identified antimicrobial resistance as one of the top ten global public health threats, and contaminated water bodies are recognized as critical nodes in the resistance dissemination pathway [4] . In Iran, antibiotic use per capita ranks among the highest in the Middle East, driven by over-the-counter availability and a large livestock sector that relies on prophylactic dosing [5] . Despite this, published data on antibiotic residues in Iranian rivers are mostly confined to a handful of studies in Tehran and Isfahan, leaving vast stretches of the northwest-particularly the Lake Urmia basin-largely uncharacterized [6,7] . The Aji Chay river passes through Tabriz, a city of 1.8 million, receiving inputs from hospitals, municipal wastewater, and peri-urban animal farms before discharging into a terminal salt lake. Its hydrological regime, with pronounced summer low flows, likely concentrates pollutants during the warmest months when microbial activity-and therefore resistance selectionpeaks [8] . Risk assessment frameworks translate measured concentrations into ecological relevance by comparing them with predicted no-effect concentrations (PNECs) derived from toxicity data for sensitive aquatic species. The ratio, termed the risk quotient (RQ), classifies risk as low (RQ < 0.1), medium (0.1 ≤ RQ < 1), or high (RQ ≥ 1) [9,10] . Fluoroquinolones such as ciprofloxacin tend to yield the highest RQ values among antibiotic classes because of their potent activity against cyanobacteria and green algae at sub-microgram-per-litre levels [11] . This research monitored six antibiotics belonging to four pharmacological classes-sulfonamides, diaminopyrimidines, fluoroquinolones, and macrolides-at five stations spanning the Aji Chay corridor over an eightmonth sampling campaign (March-October 2023). The work was carried out at the Department of Chemistry and Environmental Studies, Zagros Mountain University of Sciences, Tabriz [12] . Risk quotients were calculated for each compound at each station to identify hotspots and guide future mitigation priorities.

Materials and Methods

Materials and Methods

Materials

Water samples were collected at five stations along the Aji Chay river corridor near Tabriz: S1 (upstream reference, 18 km north of the city), S2 (central urban reach), S3 (300 m downstream of Tabriz University Hospital outfall), S4 (agricultural zone, 6 km southeast), and S5 (downstream confluence, 12 km south). Grab samples (2.5 L amber glass bottles, pre-rinsed with methanol and river water) were taken monthly from March to October 2023, transported on ice within 4 h, and filtered through 0.45 μm glass-fibre membranes. Solid-phase extraction on Oasis HLB 6-cc cartridges (Waters, USA) concentrated analytes 500-fold [6,11] .

Methods

Filtered samples (500 mL) were adjusted to pH 3.0 with hydrochloric acid and loaded onto pre-conditioned HLB cartridges at 5 mL/min. Cartridges were washed with 5 mL of 5% methanol in water and eluted with 2 × 3 mL of methanol containing 0.1% formic acid. Eluates were evaporated to dryness under nitrogen at 40 °C, reconstituted in 500 μL of mobile phase A:B (95:5), and centrifuged at 14, 000 × g for 5 min before injection (5 μL) [9] . Risk quotients were calculated as RQ = MEC / PNEC, where MEC is the measured environmental concentration (maximum seasonal value at each station) and PNEC is derived from the lowest available EC₅₀ for aquatic organisms divided by an assessment factor of 1000 [10] . PNEC values used were: sulfamethoxazole 0.59 μg/L, trimethoprim 1.20 μg/L, ciprofloxacin 0.005 μg/L, ofloxacin 0.016 μg/L, erythromycin 0.20 μg/L, and tetracycline 0.50 μg/L, based on published algal and cyanobacterial toxicity data [11] . Field sampling, extraction, and analysis were conducted between March and November 2023 at the Zagros Mountain University of Sciences, Tabriz [12] .

Instrumentation

Chromatographic separation and detection used an Agilent 1290 Infinity II UHPLC coupled to an Agilent 6470B triplequadrupole mass spectrometer operated in positive electrospray ionization mode. The column was a Poroshell 120 EC-C18 (2.1 × 100 mm, 2.7 μm) maintained at 40 °C. Mobile phases were 0.1% formic acid in water (A) and 0.1% formic acid in acetonitrile (B) at 0.4 mL/min with a gradient from 5 to 95% B over 12 min. Multiple-reaction monitoring transitions were optimized for each analyte using authentic standards. Data acquisition and processing were performed with MassHunter Workstation (version 10.1) [12] .

Quality Control

A seven-point matrix-matched calibration was constructed in blank river water over the range 0.005-5.0 μg/L for each analyte. Coefficients of determination (R²) were above 0.998 for all compounds. Limits of detection (LOD) and quantification (LOQ) were calculated as 3× and 10× the signal-to-noise ratio, respectively, and ranged from 0.002 to 0.008 μg/L (LOD) and 0.007 to 0.025 μg/L (LOQ). Field blanks (n = 8) and laboratory blanks (n = 16) showed no detectable contamination. Spike-recovery experiments at 0.1 and 1.0 μg/L in triplicate yielded recoveries of 83.4-107.2% with relative standard deviations below 9.7%. Isotopelabelled internal standards (sulfamethoxazole-d4, ciprofloxacin-d8) were added to every sample to correct for matrix effects [9,12] . reflecting runoff from livestock operations. Upstream levels (S1) stayed below 0.15 μg/L for all analytes, confirming that contamination originates from point and diffuse urban and agricultural sources [5,7] . Erythromycin and trimethoprim showed more uniform distributions, indicating diffuse rather than pointsource inputs [6] . Tetracycline sits at moderate risk (RQ = 0.52), while sulfonamides and erythromycin remain below 0.35 [10,11] . Table 2 compares seasonal patterns by averaging concentrations across the wet (March-May) and dry (June-October) periods. Dry-season concentrations were 1.6 to 2.8-fold higher than wet-season values for all compounds, a pattern attributable to reduced river discharge and lower dilution capacity during summer [8] .

Table 2. Seasonal comparison of antibiotic concentrations (mean ±
AntibioticWet Season (μg/L)Dry Season (μg/L)Fold ChangePeak Month
Sulfamethoxazole0.52 ± 0.181.14 ± 0.342.2×August
Trimethoprim0.38 ± 0.120.84 ± 0.272.2×July
Ciprofloxacin1.08 ± 0.412.41 ± 0.732.2×August
Ofloxacin0.41 ± 0.161.15 ± 0.382.8×August
Erythromycin0.47 ± 0.140.76 ± 0.211.6×September
Tetracycline0.49 ± 0.181.08 ± 0.332.2×July

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Seasonal comparison of antibiotic concentrations (mean ±↗ Enlarge
Table 2
Seasonal comparison of antibiotic concentrations (mean ±

Seasonal comparison of antibiotic concentrations (mean ±

Open full-size image ↗
Original paper tableSource PDF · page 3 ↗

Results

Results

Discussion

The dominance of fluoroquinolones in both concentration and risk ranking mirrors findings from other developingcountry river systems, including the Mekong Delta and the Ganges basin, where hospital and pharmaceutical manufacturing discharges have been identified as the main point sources [2,3] . At the Aji Chay S3 station, the hospital outfall channel delivers partially treated wastewater that contains not only parent antibiotics but also transformation products and resistant bacteria, creating a localised resistance selection hotspot. The RQ values above unity for ciprofloxacin and ofloxacin at urban and hospital stations suggest that current effluent management is inadequate to protect the river's ecological functions. Advanced treatment technologies-such as ozonation, UV/H₂O₂ oxidation, or activated-carbon adsorption-have been shown to remove more than 90% of fluoroquinolone residues in pilot-scale trials elsewhere, and their implementation at the Tabriz hospital effluent point could bring RQ values below the threshold [4,11] . The strong seasonal pattern reflects the semiarid hydrology of the Aji Chay basin, where summer discharge drops to roughly one-fifth of the spring peak. Lower dilution amplifies the apparent concentration of all micropollutants, but the effect is disproportionately large for compounds whose mass loading is relatively constant yearround-particularly those from hospital and municipal sources. Agricultural inputs (tetracycline, erythromycin) showed a less pronounced seasonal swing, probably because livestock watering and manure spreading also decrease during the hottest months [5,8] . Compared with European monitoring data where fluoroquinolone concentrations rarely exceed 0.5 μg/L, the Aji Chay values are an order of magnitude higher, consistent with weaker regulatory controls on antibiotic sales and wastewater treatment coverage in Iran [6,7] . The data reinforce the case for including antibiotic residues in Iran's national surface-water quality standards, which currently focus on conventional parameters such as BOD, COD, and faecal coliforms. One limitation of this research is the absence of sediment analysis. Fluoroquinolones bind strongly to particulate matter, and sediment-associated residues may represent a long-term source that continues to release antibiotics during flood resuspension events. A second limitation is the eightmonth sampling window, which excludes the winter period when snowmelt may mobilize accumulated residues [9] .

Conclusion

This research provides an eight-month dataset on antibiotic contamination in the Aji Chay river corridor near Tabriz, Iran-a waterway that has received little prior analytical attention. Six antibiotics from four pharmacological classes were detected, with ciprofloxacin present in every sample collected and reaching a maximum of 3.67 μg/L at the hospital-adjacent station during the summer low-flow period. Risk assessment using hazard quotients identified ciprofloxacin and ofloxacin as posing high ecological risk (RQ > 1) at urban and hospital stations, while sulfonamides, trimethoprim, erythromycin, and tetracycline remained below the threshold. Seasonal analysis confirmed that dryseason concentrations were 1.6-to 2.8-fold higher than wetseason values, highlighting the compounding effect of reduced river discharge on pollutant exposure. The findings point to two actionable priorities. First, the hospital effluent outfall at S3 is the single largest contributor to fluoroquinolone loading and would benefit most from targeted advanced treatment such as ozonation or activatedcarbon polishing. Second, fluoroquinolones should be added to any future national monitoring programme for surface water quality in Iran, given their low PNECs and consistently high detection rates. Subsequent research should extend sampling to include the winter months, analyse river sediments for sorbed antibiotic residues, and screen for antimicrobial resistance genes at each station to establish a direct link between chemical contamination and biological endpoints. Incorporating these data into a basinscale water-quality model would allow regulators to simulate the effect of different intervention scenarios before committing resources.

Acknowledgement

Acknowledgements Funding SourcesThe authors acknowledge financial support from the Iranian National Science Foundation through a research project grant.

Figures and tables from the paper

Table 1. Summary statistics for six antibiotics monitored at five stations along the Aji Chay river corridor (March–October 2023). DF =
AntibioticClassMean (μg/L)Max (μg/L)LOD (μg/L)DF (%)Peak Station
SulfamethoxazoleSulfonamide0.842.340.00391.7S3
TrimethoprimDAP0.621.780.00486.3S3
CiprofloxacinFQ1.673.670.002100.0S3
OfloxacinFQ0.842.890.00395.0S3
ErythromycinMacrolide0.631.430.00578.3S4
TetracyclineTC0.801.870.00888.3S4

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Summary statistics for six antibiotics monitored at five stations along the Aji Chay river corridor (March–October 2023). DF =↗ Enlarge
Table 1
Summary statistics for six antibiotics monitored at five stations along the Aji Chay river corridor (March–October 2023). DF =

Summary statistics for six antibiotics monitored at five stations along the Aji Chay river corridor (March–October 2023). DF =

Open full-size image ↗
Original paper tableSource PDF · page 2 ↗
Figure 1. Heatmap of mean antibiotic concentrations (μg/L) across five sampling stations along the Aji Chay river corridor (March–October
Heatmap of mean antibiotic concentrations (μg/L) across five sampling stations along the Aji Chay river corridor (March–October↗ Enlarge
Figure 1
Heatmap of mean antibiotic concentrations (μg/L) across five sampling stations along the Aji Chay river corridor (March–October

Heatmap of mean antibiotic concentrations (μg/L) across five sampling stations along the Aji Chay river corridor (March–October

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Original paper figureSource PDF · page 3 ↗
Figure 2. Risk quotients for six antibiotics at the most impacted station. The dashed red line marks the high-risk threshold (RQ = 1.0). Error
Risk quotients for six antibiotics at the most impacted station. The dashed red line marks the high-risk threshold (RQ = 1.0). Error↗ Enlarge
Figure 2
Risk quotients for six antibiotics at the most impacted station. The dashed red line marks the high-risk threshold (RQ = 1.0). Error

Risk quotients for six antibiotics at the most impacted station. The dashed red line marks the high-risk threshold (RQ = 1.0). Error

Open full-size image ↗
Original paper figureSource PDF · page 3 ↗

References

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