Environmental Risk and Risk of Resistance Selection Due to Antimicrobials’ Occurrence in Two Polish Wastewater Treatment Plants and Receiving Surface Water
Abstract
:1. Introduction
2. Results
2.1. Predicted Concentrations of Antimicrobials in WWTPs
2.2. Antimicrobial Concentrations in Influents of WWTPs
2.3. Antimicrobial Concentrations in Effluent of WWTPs
2.4. Antimicrobial Concentrations in Receiving Waters
2.5. Antimicrobials’ Removal Efficiency
2.6. Antimicrobials’ Concentrations in Sewage Sludge from WWTPs
2.7. Antimicrobial Resistance Risk Assessment
2.8. Environmental Risk Assessment
3. Materials and Methods
3.1. Description of WWTPs and Sample Collection
3.2. Analysis of Antimicrobials’ Concentrations
3.2.1. Chemicals
3.2.2. Preparation of Water and Sewage Sludge Samples
3.2.3. Antimicrobial Detection by LC-MS/MS Analysis
3.3. Calculations
3.4. Statistical Analysis
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
Sale in 2018 (kg/month) | PLoad (g/d) 1 | LoadW (g/d) 2 | LoadS (g/d) 3 | LoadW/PLoad (%) | LoadS/PLoad (%) | LoadW+S 4/PLoad(%) | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
range | S5 | A | W | S | A | W | S | A | W | S | A | W | S | A | W | S | A | W | |
AZM6 | 98–352 | 25.3 | 26.3 | 47.2 | 0.3 | 4.8 | 1.9 | 0.2 | 2.9 | 5.4 | 1 | 13 | 4 | 1 | 8 | 11 | 2 | 21 | 15 |
CIP | 601–821 | 106.5 | 128.9 | 112.8 | 58.7 | 15.6 | 27.1 | 54.2 | 26.1 | 60.1 | 55 | 12 | 24 | 51 | 20 | 53 | 106 | 32 | 77 |
CLR | 288–1509 | 68.9 | 121.1 | 145.5 | 7.9 | 11.2 | 19.4 | 0.04 | 0.27 | 0.09 | 12 | 9 | 13 | 0 | 0 | 0 | 12 | 9 | 13 |
CLI | 608–737 | 109.9 | 116.4 | 106.8 | 1.6 | 2.4 | 6.8 | 0.3 | 0.2 | 0.8 | 1 | 2 | 6 | 0 | 0 | 1 | 1 | 2 | 7 |
NOR | 179–214 | 30.9 | 35.5 | 29.9 | 5.1 | 11.2 | 3.0 | 10.3 | 18.0 | 52.7 | 16 | 31 | 10 | 33 | 51 | 176 | 49 | 82 | 186 |
OFX | 609–829 | 107.3 | 131.0 | 113.7 | 2.6 | 4.9 | 3.5 | 10.2 | 1.5 | 2.8 | 2 | 4 | 3 | 10 | 1 | 3 | 12 | 5 | 6 |
RIF | 40–48 | 7.08 | 7.19 | 6.63 | 0.26 | 0.08 | 0.08 | 4 | 1 | 1 | 0 | 0 | 0 | 4 | 1 | 1 | |||
ROX | 6–28 | 1.44 | 2.33 | 2.69 | 0.14 | 0.14 | 1.19 | 10 | 6 | 44 | 0 | 0 | 0 | 10 | 6 | 44 | |||
SXT | 606–1358 | 133.3 | 196.0 | 194.1 | 18.5 | 44.9 | 44.0 | 0.4 | 0.3 | 1.2 | 14 | 23 | 23 | 0 | 0 | 1 | 14 | 23 | 24 |
TMP | 122–272 | 26.7 | 39.7 | 38.9 | 8.1 | 5.5 | 6.8 | 0.02 | 0.02 | 0.09 | 30 | 14 | 18 | 0 | 0 | 0 | 30 | 14 | 18 |
Antimicrobial | % of Total Mass Load Sorbed to Sludge | log Kd Sludge |
---|---|---|
AZM | 73% | 7.1 ± 4.3 |
CIP | 55% | 7.3 ± 4.2 |
CLR | 18% | 5.7 ± 2.5 |
CLI | 9% | 5.7 ± 2.6 |
LCM | 7% | 5.2 ± 1.9 |
OFX | 43% | 7.7 ± 4.8 |
OTC | 62% | 9.8 ± 6.9 |
SDM | 32% | 6.8 ± 3.4 |
SXT | 2% | 5.1 ± 1.7 |
TET | 13% | 8.3 ± 5.5 |
TBZ | 23% | 5.9 ± 2.6 |
TMP | 19% | 4.8 ± 1.6 |
VAN | 24% | 6.3 ± 3.2 |
Antimicrobial (ng/g) | WWTP1-PS | WWTP1-ES | WWTP2-RS | WWTP2-FS | WWTP1-RS 1 | |||||
---|---|---|---|---|---|---|---|---|---|---|
Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | |
AZM | 1.9 | 1.3 | 0.55 | 0.50 | 0.17 | 0.14 | 2.3 | 1.6 | 0.14 | 0.13 |
CIP | 18 | 13 | 9.1 | 3.5 | 8.9 | 9.8 | 41 | 40 | 11.4 | 5.2 |
CLR | 0.42 | 0.09 | 0.03 | 0.02 | 0.03 | 0.04 | 0.33 | 0.37 | <0.01 | - |
CLI | 0.06 | 0.04 | 0.08 | 0.06 | 0.04 | 0.05 | 0.07 | 0.05 | 0.01 | 0.01 |
LCM | 0.01 | 0.01 | 0.01 | - | 0.01 | 0.01 | 0.03 | 0.04 | <0.01 | - |
NOR | 7.8 | 5.8 | 5.2 | 4.4 | 2.4 | 2.4 | 5.0 | 4.1 | - | - |
OFX | 1.2 | 1.6 | 0.94 | 0.91 | 0.44 | 0.33 | 0.70 | 0.21 | 0.05 | 0.02 |
OTC | 0.86 | 0.74 | 0.48 | 0.41 | 0.07 | 0.06 | 0.41 | 0.37 | 0.01 | 0.01 |
PEF | 0.36 | 0.25 | 0.28 | 0.20 | 0.28 | 0.22 | 0.38 | 0.15 | - | - |
ROX | 0.03 | - | <0.01 | - | <0.01 | - | <0.01 | - | <0.01 | - |
SD | <0.01 | <0.01 | <0.01 | - | 0.03 | - | <0.01 | - | ||
SDM | 0.03 | 0.03 | 0.03 | 0.03 | 0.03 | - | <0.01 | - | <0.01 | - |
SXT | <0.03 | - | 0.12 | 0.10 | <0.03 | - | <0.03 | - | 0.01 | 0.01 |
TET | 0.12 | 0.09 | 0.06 | 0.02 | 0.08 | 0.05 | 0.29 | 0.17 | 0.04 | 0.03 |
TBZ | 0.03 | 0.01 | 0.02 | 0.01 | 0.09 | 0.08 | 0.07 | 0.04 | 0.01 | 0.01 |
TMP | 0.25 | 0.19 | 0.01 | 0.01 | <0.01 | - | <0.01 | - | <0.01 | - |
VAN | 0.53 | 0.10 | 0.27 | 0.16 | 0.11 | - | <0.01 | - | 0.55 | 0.15 |
Compound | Cyanobacteria NOEC/EC50 | Cyanobacteria PNEC | Eukaryote NOEC/EC50 | Eukaryote PNEC |
---|---|---|---|---|
AZM | 0.19 | 19 | 1.8 | 180(MA) |
CIP | 5.65 | 565 | 10 | 1000(MP) |
CLR | 0.84 | 84 | 2 | 40(MA) |
ERY | 2 | 200 | 10.3 | 206(MA) |
LCM | 18 | 1800 | 548 | 10976(MA) |
MTZ | 0 | nd | 250,000 | 5000000(IN) |
NOR | 1.6 | 160 | 300 | 3000(MP) |
OFX | 5 | 500 | 31.2 | 624(MA) |
OTC | 3.1 | 310 | 183 | 3660(MA) |
ROX | nd | nd | 10 | 100(MA) |
SD | 3900 | 390,000 | 135 | 2700(MA) |
SDM | 7800 | 780,000 | 100 | 5290(MA) |
SXT | 5.9 | 590 | 10 | 1000(MP,IN) |
TET | 90 | 9000 | 300 | 6000(MP) |
TMP | 1385 | 135,800 | 1000 | 20000(MP) |
Antimicrobial | PNEC Wastewater (µg/L) 1 | PNEC Sludge (µg/kg) 2 | PNEC Soil (µg/kg) 3 |
---|---|---|---|
AZT | 0.25 | 1200 | 47 |
CIP | 0.064 | 1200 | 27,000 |
CLR | 0.25 | 140 | 66 |
CLI | 1 | 280 | - |
ER | 2 | - | 260 |
LIN | 2 | 340 | - |
METR | 0.125 | - | 0.07 |
NFL | 0.5 | - | 300 |
OFL | 0.5 | 4200 | 730 |
OTET | 0.5 | 4,200,000 | 210 |
RIF | 0.5 | - | - |
ROX | 1 | 4300 | 50 |
STH | 16 | 2000 | 9.6 |
TET | 1 | 3000 | 1100 |
TRI | 0.5 | 100 | 3.7 |
VAN | 8 | 17,000 | 2.4 |
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Sample Availability: Samples of the compounds are not available from the authors. |
WWTP1 Influent | WWTP1 Effluent | WWTP1 Leachate | River1 Upstream | River1 Downstream | WWTP2 Influent | WWTP2 Effluent | River2 Upstream | River2 Downstream | MDL 1 | MQL 1 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | |||
AZM | 87 | 71 | 230 | 110 | 320 | 290 | 25 | 15 | 441 | 249 | 360 | 450 | 650 | 680 | 5.2 | 2.7 | 36 | 21 | 10 | 33 |
CIP | 1260 | 680 | 184 | 72 | 890 | 410 | 108 | 33 | 95 | 4 | 4300 | 4300 | 312 | 73 | 12 | 12 | 182 | 182 | 2.4 | 8.1 |
CLR | 480 | 190 | 160 | 170 | 102 | 23 | 37 | 9 | 79 | 50 | 560 | 590 | 143 | 40 | 12.2 | 8.2 | 20.5 | 11.1 | 0.3 | 0.9 |
CLI | 134 | 87 | 166 | 60 | 73 | 37 | 78 | 46 | 134 | 3 | 106 | 51 | 290 | 200 | 2.3 | 1.1 | 25.4 | 3.5 | 2.9 | 9.5 |
ERY | 58 | 71 | 21 | 18 | 30 | 42 | 7 | 7 | 10 | 0 | 28 | 20 | 16 | 12 | <MDL | <MDL | 0.7 | 2.4 | ||
LCM | 20 | 15 | 48 | 52 | 24.7 | 7.8 | 3 | 3 | 9 | 4 | 102 | 46 | 56 | 19 | <MDL | 4.0 | 1.4 | 1.4 | 4.7 | |
MTZ | 250 | 160 | 69 | 82 | 11.1 | 8.4 | 9 | 3 | 21 | 11 | 7400 | 9600 | 88 | 41 | <MDL | 9.4 | 3.1 | 2.4 | 7.9 | |
NOR | 240 | 130 | 31 | 28 | 210 | 150 | 95 | 93 | <MDL | 80 | 110 | 10 | 11 | <MDL | <MDL | 6.3 | 21 | |||
OFX | 135 | 35 | 26 | 14 | 200 | 91 | 32 | 18 | 4 | 4 | 195 | 21 | 40 | 11 | 8.4 | 0.5 | 31 | 23 | 1.4 | 4.6 |
OTC | 0.7 | 0.9 | 0.1 | 0.1 | 1.1 | 1.4 | <MDL | 1 | 0 | <MDL | <MDL | <MDL | <MDL | 0.1 | 0.2 | |||||
RIF | 5.2 | 3.3 | <MDL | <MDL | <MDL | <MDL | 5.3 | 3.4 | 2.9 | 2 | <MDL | <MDL | 2.9 | 9.6 | ||||||
ROX | 18 | 19 | 6.6 | 6.9 | 1.6 | 1.6 | 4 | 4 | 5 | 2 | 6.2 | 5.3 | 6.2 | 2.1 | <MDL | <MDL | 0.5 | 1.6 | ||
SD | <MDL | 3.4 | 4.3 | 2.4 | 2.5 | <MDL | <MDL | <MDL | <MDL | <MDL | <MDL | 0.6 | 1.9 | |||||||
SDM | 4.1 | 3.2 | 3.4 | 3.5 | <MDL | <MDL | <MDL | 8.9 | 7.2 | 4.9 | 3.6 | <MDL | <MDL | 1.8 | 6.1 | |||||
SXT | 1300 | 460 | 630 | 220 | 480 | 630 | 644 | 41 | 451 | 95 | 3000 | 1900 | 770 | 280 | <MDL | 76.1 | 4.6 | 5.9 | 19 | |
ST | 94 | 46 | 21 | 14 | 136 | 54 | 7 | 6 | 29 | 19 | 180 | 110 | 36 | 16 | <MDL | <MDL | 2.4 | 8 | ||
TET | 190 | 190 | 39 | 55 | 180 | 170 | <MDL | 0 | 0 | 210 | 160 | 61 | 48 | <MDL | 7.2 | 6.4 | 0.2 | 0.7 | ||
TBZ | 18.4 | 2.8 | 22.3 | 4.5 | 18 | 11 | 12 | 7 | 16 | 0 | 11 | 2.8 | 25.5 | 3 | <MDL | 4.3 | 2.1 | 2.8 | 9.4 | |
TMP | 254 | 41 | 160 | 190 | 94 | 52 | 38 | 3 | 36 | 8 | 900 | 770 | 220 | 110 | 9.1 | 8.4 | 24.4 | 3.9 | 3 | 9.9 |
VAN | 350 | 390 | 114 | 60 | 840 | 220 | 27 | 23 | 62 | 8 | 3200 | 3600 | 162 | 62 | <MDL | 10.7 | 3.2 | 15 | 50 |
WWTP1-PS | WWTP1-ES | WWTP2-RS | WWTP2-FS | WWTP1-RS 1 | MDL | MQL | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Mean | SD | Mean | SD | Mean | SD | Mean | SD | Mean | SD | |||
AZM | 1260 | 690 | 370 | 280 | 82 | 75 | 1040 | 940 | 100 | 110 | 23 | 79 |
CIP | 12500 | 6900 | 6200 | 2000 | 6100 | 5500 | 28000 | 22000 | 7800 | 4400 | 490 | 1670 |
CLR | 289 | 52 | 18 | 14 | 18 | 23 | 150 | 180 | 3.0 | 0.8 | 2.2 | 7.4 |
CLI | 40 | 25 | 58 | 35 | 29 | 29 | 47 | 30 | 9.1 | 5.6 | 1.3 | 4.5 |
LCM | 4.3 | 3.2 | 1.5 | 2.0 | 2.5 | 2.6 | 19 | 24 | 0.13 | 0.05 | 0.2 | 0.6 |
NOR | 5300 | 3200 | 3600 | 2500 | 1600 | 1400 | 3400 | 2300 | <MDL | 370 | 1270 | |
OFX | 810 | 890 | 640 | 510 | 300 | 190 | 480 | 120 | 36 | 21 | 12 | 41 |
OTC | 590 | 410 | 320 | 230 | 50 | 35 | 190 | 200 | 4.0 | 6.5 | 0.2 | 0.7 |
PEF | 250 | 150 | 190 | 110 | 140 | 120 | 256 | 81 | <MDL | 29 | 100 | |
ROX | 11.4 | 7.8 | <MDL | <MDL | <MDL | 0.22 | 0.26 | 12 | 40 | |||
SD | <MDL | <MDL | 1.1 | 0.8 | 7.7 | 11 | 0.14 | 0.18 | 1.1 | 3.7 | ||
SDM | 12 | 14 | 13 | 14 | 7.5 | 11 | <MDL | 0.29 | - | 0.6 | 2.0 | |
SXT | <MDL | 81 | 54 | <MDL | <MDL | 5.9 | 9.4 | 41 | 140 | |||
TET | 82 | 50 | 40 | 13 | 58 | 29 | 201 | 95 | 25 | 29 | 0.7 | 2.5 |
TBZ | 19.5 | 5.2 | 15.6 | 5.8 | 43 | 43 | 49 | 22 | 8.3 | 6.2 | 0.6 | 2.2 |
TMP | 170 | 110 | 5.7 | 4.4 | <MDL | <MDL | 2.6 | 1.7 | 0.5 | 1.5 | ||
VAN | 363 | 55 | 181 | 91 | 36 | 30 | <MDL | 370 | 130 | 32 | 110 |
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Giebułtowicz, J.; Nałęcz-Jawecki, G.; Harnisz, M.; Kucharski, D.; Korzeniewska, E.; Płaza, G. Environmental Risk and Risk of Resistance Selection Due to Antimicrobials’ Occurrence in Two Polish Wastewater Treatment Plants and Receiving Surface Water. Molecules 2020, 25, 1470. https://doi.org/10.3390/molecules25061470
Giebułtowicz J, Nałęcz-Jawecki G, Harnisz M, Kucharski D, Korzeniewska E, Płaza G. Environmental Risk and Risk of Resistance Selection Due to Antimicrobials’ Occurrence in Two Polish Wastewater Treatment Plants and Receiving Surface Water. Molecules. 2020; 25(6):1470. https://doi.org/10.3390/molecules25061470
Chicago/Turabian StyleGiebułtowicz, Joanna, Grzegorz Nałęcz-Jawecki, Monika Harnisz, Dawid Kucharski, Ewa Korzeniewska, and Grażyna Płaza. 2020. "Environmental Risk and Risk of Resistance Selection Due to Antimicrobials’ Occurrence in Two Polish Wastewater Treatment Plants and Receiving Surface Water" Molecules 25, no. 6: 1470. https://doi.org/10.3390/molecules25061470