Grey water footprint of pharmaceuticals and personal care products discharged via urban wastewater

1. Luo, Y. et al. A review on the occurrence of micropollutants in the aquatic environment and their fate and removal during wastewater treatment. Sci. Total Environ. 473–474, 619–641 (2014).

   Google Scholar 

2. EC. Impact Assessment -accompanying the document – Proposal for a Directive of the European Parliament and of the Council concerning urban wastewater treatment (recast). Commission staff working document (2022).

3. Kidd, K. A., Backhaus, T., Brodin, T., Inostroza, P. A. & McCallum, E. S. Environmental risks of pharmaceutical mixtures in aquatic ecosystems: Reflections on a decade of research. Environ. Toxicol. Chem. 43, 549–558 (2024).

   Google Scholar 

4. Paul, S. et al. Ecological problems associated with personal care products and the role of microbes in aquatic environment. Environ. Qual. Manage. 33, 487–494 (2024).

   Google Scholar 

5. aus der Beek, T. et al. Pharmaceuticals in the environment—Global occurrences and perspectives. Environ. Toxicol. Chem. 35, 823–835 (2016).

   Google Scholar 

6. Hoekstra, A. Y. & Hung, P. Q. Virtual Water Trade – A Quantification of Virtual Water Flows between Nations in Relation to International Crop Trade. 120 (2002). https://waterfootprint.org/media/downloads/Report11_1.pdf

7. Ansorge, L. & Stejskalová, L. Citation accuracy: A case study on definition of the grey water footprint. Publications 11, 8 (2023).

   Google Scholar 

8. Hoekstra, A. Y. Water footprint assessment: Evolvement of a new research field. Water Resour. Manage. 31, 3061–3081 (2017).

   Google Scholar 

9. Hoekstra, A. Y., Chapagain, A. K., Aldaya, M. M. & Mekonnen, M. M. The Water Footprint Assessment Manual: Setting the Global Standard (Earthscan, 2011).

   Google Scholar 

10. Ansorge, L., Stejskalová, L., Vološinová, D. & Dlabal, J. Limitation of water footprint sustainability assessment: A review. Eur. J. Sustainable Dev. 11, 1–14 (2022).

    Google Scholar 

11. Jamshidi, S. Grey water footprint accounting, challenges, and problem-solving In (eds Banerjee, A. et al.) (2021).

12. Ansorge, L., Stejskalova, L. & Dlabal, J. Effect of WWTP size on grey water footprint-Czech Republic case study. Environ. Res. Lett. 15, 104020 (2020).

    Google Scholar 

13. Ansorge, L., Stejskalová, L. & Dlabal, J. Grey water footprint as a tool for implementing the Water Framework Directive – Temelín nuclear power station. J. Clean. Prod. 263, 121541 (2020).

    Google Scholar 

14. Liu, C., Kroeze, C., Hoekstra, A. Y. & Gerbens-Leenes, W. Past and future trends in grey water footprints of anthropogenic nitrogen and phosphorus inputs to major world rivers. Ecol. Ind. 18, 42–49 (2012).

    Google Scholar 

15. Mekonnen, M. M. & Hoekstra, A. Y. Global anthropogenic phosphorus loads to freshwater and associated grey water footprints and water pollution levels: A high-resolution global study. Water Resour. Res. 54, 345–358 (2018).

    Google Scholar 

16. Pellicer-Martínez, F. & Martínez-Paz, J. M. The Water Footprint as an indicator of environmental sustainability in water use at the river basin level. Sci. Total Environ. 571, 561–574 (2016).

    Google Scholar 

17. Stejskalová, L., Ansorge, L., Kučera, J. & Vološinová, D. Grey water footprint as a tool for wastewater treatment plant assessment– Hostivice case study. Urban Water J. 18, 796–805 (2021).

    Google Scholar 

18. Martínez-Alcalá, I., Pellicer-Martínez, F. & Fernández-López, C. Pharmaceutical grey water footprint: Accounting, influence of wastewater treatment plants and implications of the reuse. Water Res. 135, 278–287 (2018).

    Google Scholar 

19. Wöhler, L., Niebaum, G., Krol, M. & Hoekstra, A. Y. The grey water footprint of human and veterinary pharmaceuticals. Water Res. X 7, 100044 (2020).

    Google Scholar 

20. Wöhler, L. et al. An integrated modelling approach to derive the grey water footprint of veterinary antibiotics. Environ. Pollut. 288, 117746 (2021).

    Google Scholar 

21. Dolmans, E. The grey water footprint of antimicrobials used for aquaculture production (University of Twente, 2022).

22. Ansorge, L., Stejskalová, L. & Soldán, P. Grey water footprint of contaminants of emerging concern from wasterwater in Sava River Basin. Acta Hydrotech. 35, 117–128 (2022).

    Google Scholar 

23. Ansorge, L., Stejskalová, L. & Soldán, P. Emerging contaminats in wastewater – results of Joint Danube Survey 4 evaluated via the grey water footprint. Vodohospodářské Tech.-Ekon. Inf. 2024, 38–45 (2024).

    Google Scholar 

24. Ansorge, L. & Stejskalová, L. Comparison of the grey water footprint of conventional pollution and micropollutants: a case study of the Bandung WWTP (Indonesia). Vodohospodářské Tech.-Ekon. Inf. 2024, 20–27 (2024).

    Google Scholar 

25. Onyango, J., Simaika, J. P., Kitaka, N. & Irvine, K. Assessment of combined nutrients and pesticides grey water footprint in a sub-Saharan African lake catchment. Environ. Sustain. Indic. 28, 100958 (2025).

    Google Scholar 

26. Fiala, D. et al. Denní odnosy živin z obcí prizmatem jejich velikosti a vodohospodářské infrastruktury. In Vodárenská biologie 172–178 (Ekomonitor, 2018).

    Google Scholar 

27. Liu, W., Antonelli, M., Liu, X. & Yang, H. Towards improvement of grey water footprint assessment: With an illustration for global maize cultivation. J. Clean. Prod. 147, 1–9 (2017).

    Google Scholar 

28. Miglietta, P. et al. A grey water footprint assessment of groundwater chemical pollution: Case study in Salento (Southern Italy). Sustainability 9, 799 (2017).

    Google Scholar 

29. Stejskalová, L., Ansorge, L., Kučera, J. & Čejka, E. Role of wastewater treatment plants in pollution reduction – evaluated by grey water footprint indicator. srees 31, 26–36 (2022).

    Google Scholar 

30. Rosendorf, P. Metodika hodnocení všeobecných fyzikálně-chemických složek ekologického stavu útvarů povrchových vod tekoucích. 20 (2011). https://mzp.gov.cz/system/files/2024-11/OOV-Metodika_FYZ-CHEM-20130129.pdf

31. Aldaya, M. M. et al. Grey water footprint as an indicator for diffuse nitrogen pollution: The case of Navarra, Spain. Sci. Total Environ. 698, 134338 (2020).

    Google Scholar 

32. Ansorge, L., Stejskalová, L., Dlabal, J. & Kučera, J. Šedá vodní stopa jako ukazatel udržitelného vypouštění odpadních vod – případová studie Povodí Ohře. Entecho 2, 12–18 (2019).

    Google Scholar 

33. Wang, X., Dong, Z., Wang, W., Luo, Y. & Tan, Y. Stochastic grey water footprint model based on uncertainty analysis theory. Ecol. Indic. 124, 107444 (2021).

    Google Scholar 

34. Karandish, F. Applying grey water footprint assessment to achieve environmental sustainability within a nation under intensive agriculture: A high-resolution assessment for common agrochemicals and crops. Environ. Earth Sci. 78, 200 (2019).

    Google Scholar 

35. Stejskalová, L. et al. Farmaka a vybrané mikropolutanty v surových a čištěných odpadních vodách v povodí VN Švihov. Vodní hospodářství. 71, 6–16 (2021).

    Google Scholar 

36. Szopińska, M. et al. Pharmaceuticals and other contaminants of emerging concern in Admiralty Bay as a result of untreated wastewater discharge: Status and possible environmental consequences. Sci. Total Environ. 835, 155400 (2022).

    Google Scholar 

37. Li, W., Shi, Y., Gao, L., Liu, J. & Cai, Y. Occurrence, fate and risk assessment of parabens and their chlorinated derivatives in an advanced wastewater treatment plant. J. Hazard. Mater. 300, 29–38 (2015).

    Google Scholar 

38. Penrose, M. T. & Cobb, G. P. Influences of wastewater treatment on the occurrence of parabens, p-hydroxybenzoic acid and their chlorinated and hydroxylated transformation products in the Brazos River (Texas, USA). Arch. Environ. Contam. Toxicol. 85, 105–118 (2023).

    Google Scholar 

39. Haman, C., Dauchy, X., Rosin, C. & Munoz, J. F. Occurrence, fate and behavior of parabens in aquatic environments: A review. Water Res. 68, 1–11 (2015).

    Google Scholar 

40. Ben, W. et al. Occurrence, removal and risk of organic micropollutants in wastewater treatment plants across China: Comparison of wastewater treatment processes. Water Res. 130, 38–46 (2018).

    Google Scholar 

41. Rizzo, L. et al. Best available technologies and treatment trains to address current challenges in urban wastewater reuse for irrigation of crops in EU countries. Sci. Total Environ. 710, 136312 (2020).

    Google Scholar 

42. Rizzo, L. et al. Consolidated vs new advanced treatment methods for the removal of contaminants of emerging concern from urban wastewater. Sci. Total Environ. 655, 986–1008 (2019).

    Google Scholar 

43. Jelic, A. et al. Occurrence, partition and removal of pharmaceuticals in sewage water and sludge during wastewater treatment. Water Res. 45, 1165–1176 (2011).

    Google Scholar 

44. 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. 429, 123–155 (2012).

    Google Scholar 

45. Kruglova, A. et al. Biodegradation of ibuprofen, diclofenac and carbamazepine in nitrifying activated sludge under 12°C temperature conditions. Sci. Total Environ. 499, 394–401 (2014).

    Google Scholar 

46. Behera, S. K., Kim, H. W., Oh, J.-E. & Park, H.-S. Occurrence and removal of antibiotics, hormones and several other pharmaceuticals in wastewater treatment plants of the largest industrial city of Korea. Sci. Total Environ. 409, 4351–4360 (2011).

    Google Scholar 

47. Stasinakis, A. S. et al. Contribution of primary and secondary treatment on the removal of benzothiazoles, benzotriazoles, endocrine disruptors, pharmaceuticals and perfluorinated compounds in a sewage treatment plant. Sci. Total Environ. 463–464, 1067–1075 (2013).

    Google Scholar 

48. Archer, E., Petrie, B., Kasprzyk-Hordern, B. & Wolfaardt, G. M. The fate of pharmaceuticals and personal care products (PPCPs), endocrine disrupting contaminants (EDCs), metabolites and illicit drugs in a WWTW and environmental waters. Chemosphere 174, 437–446 (2017).

    Google Scholar 

49. Al-Mashaqbeh, O., Alsafadi, D., Dalahmeh, S., Bartelt-Hunt, S. & Snow, D. Removal of selected pharmaceuticals and personal care products in wastewater treatment plant in Jordan. Water 11, 2004 (2019).

    Google Scholar 

50. Ferrando-Climent, L. et al. Comprehensive study of ibuprofen and its metabolites in activated sludge batch experiments and aquatic environment. Sci. Total Environ. 438, 404–413 (2012).

    Google Scholar 

51. Zhang, Y., Geißen, S.-U. & Gal, C. Carbamazepine and diclofenac: Removal in wastewater treatment plants and occurrence in water bodies. Chemosphere 73, 1151–1161 (2008).

    Google Scholar 

52. Zhou, S. et al. Optimization of screening-level risk assessment and priority selection of emerging pollutants – The case of pharmaceuticals in European surface waters. Environ. Int. 128, 1–10 (2019).

    Google Scholar 

53. Langenhoff, A. et al. Microbial removal of the pharmaceutical compounds ibuprofen and diclofenac from wastewater. BioMed Res. Int. 2013, 325806 (2013).

54. Stewart, S. et al. Application of anthropogenic chemical and biological markers to characterize receiving urban waterways for untreated sanitary waste. J. Water Process Eng. 71, 107207 (2025).

    Google Scholar 

55. Aguirre-Martínez, G. V. et al. Are standard tests sensitive enough to evaluate effects of human pharmaceuticals in aquatic biota? Facing changes in research approaches when performing risk assessment of drugs. Chemosphere 120, 75–85 (2015).

    Google Scholar 

56. Flippin, J. L., Huggett, D. & Foran, C. M. Changes in the timing of reproduction following chronic exposure to ibuprofen in Japanese medaka, Oryzias latipes. Aquat. Toxicol. 81, 73–78 (2007).

    Google Scholar 

57. Xia, L., Zheng, L. & Zhou, J. L. Effects of ibuprofen, diclofenac and paracetamol on hatch and motor behavior in developing zebrafish (Danio rerio). Chemosphere 182, 416–425 (2017).

    Google Scholar 

58. Jan-Roblero, J. & Cruz-Maya, J. A. Ibuprofen: Toxicology and biodegradation of an emerging contaminant. Molecules 28, 2097 (2023).

    Google Scholar 

59. Heberer, T. & Feldmann, D. Contribution of effluents from hospitals and private households to the total loads of diclofenac and carbamazepine in municipal sewage effluents—modeling versus measurements. J. Hazard. Mater. 122, 211–218 (2005).

    Google Scholar 

60. Kümmerer, K. & Henninger, A. Promoting resistance by the emission of antibiotics from hospitals and households into effluent. Clin. Microbiol. Infect. 9, 1203–1214 (2003).

    Google Scholar 

61. Quintana, J. B., Weiss, S. & Reemtsma, T. Pathways and metabolites of microbial degradation of selected acidic pharmaceutical and their occurrence in municipal wastewater treated by a membrane bioreactor. Water Res. 39, 2654–2664 (2005).

    Google Scholar 

62. Zhou, Y. et al. Which type of pollutants need to be controlled with priority in wastewater treatment plants: Traditional or emerging pollutants?. Environ. Int. 131, 104982 (2019).

    Google Scholar 

63. Minguez, L. et al. Toxicities of 48 pharmaceuticals and their freshwater and marine environmental assessment in northwestern France. Environ. Sci. Pollut. Res. 23, 4992–5001 (2016).

    Google Scholar 

64. Zind, H. et al. Occurrence of carbamazepine, diclofenac, and their related metabolites and transformation products in a French aquatic environment and preliminary risk assessment. Water Res. 196, 117052 (2021).

    Google Scholar 

65. Grabarczyk, Ł et al. Ecotoxicity screening evaluation of selected pharmaceuticals and their transformation products towards various organisms. Environ. Sci. Pollut. Res. 27, 26103–26114 (2020).

    Google Scholar 

66. Nkoom, M., Lu, G. & Liu, J. Chronic toxicity of diclofenac, carbamazepine and their mixture to Daphnia magna: A comparative two-generational study. Environ. Sci. Pollut Res. 29, 58963–58979 (2022).

    Google Scholar 

67. Mustard, J. A. The buzz on caffeine in invertebrates: Effects on behavior and molecular mechanisms. Cell. Mol. Life Sci. 71, 1375–1382 (2014).

    Google Scholar 

68. Nunes, B., Santos, J., Dionísio, R. & Dias De Alkimin, G. Investigation of potential behavioral and physiological effects of caffeine on D. magna. Environ. Sci. Pollut. Res. 29, 43237–43250 (2022).

    Google Scholar 

69. Santos, N. et al. Behavioral and biochemical effects of environmental concentrations of caffeine in zebrafish after long-term exposure. J. Environ. Sci. Health Part A 59, 453–465 (2024).

    Google Scholar 

70. Figuière, R., Waara, S., Ahrens, L. & Golovko, O. Risk-based screening for prioritisation of organic micropollutants in Swedish freshwater. J. Hazard. Mater. 429, 128302 (2022).

    Google Scholar 

71. Belanger, S. E. et al. Comparisons of PNEC derivation logic flows under example regulatory schemes and implications for ecoTTC. Regul. Toxicol. Pharmacol. 123, 104933 (2021).

    Google Scholar 

72. Hahn, T. et al. Predicted no effect concentration derivation as a significant source of variability in environmental hazard assessments of chemicals in aquatic systems: An international analysis: Sources of Variability in Aquatic Hazard Assessments. Integr. Environ. Assess. Manag. 10, 30–36 (2014).

    Google Scholar 

73. Grung, M., Källqvist, T., Sakshaug, S., Skurtveit, S. & Thomas, K. V. Environmental assessment of Norwegian priority pharmaceuticals based on the EMEA guideline. Ecotoxicol. Environ. Saf. 71, 328–340 (2008).

    Google Scholar 

74. Bergmann, A., Fohrmann, R. & Weber, F. A. Zusammenstellung von Monitoringdaten zu Umweltkonzentrationen von Arzneimitteln. 108 (2011). http://www.uba.de/uba-info-medien/4188.html

75. Bengtsson-Palme, J. & Larsson, D. G. J. Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation. Environ. Int. 86, 140–149 (2016).

    Google Scholar 

76. Vestel, J. et al. Use of acute and chronic ecotoxicity data in environmental risk assessment of pharmaceuticals. Environ. Toxicol. Chem. 35, 1201–1212 (2016).

    Google Scholar 

77. Fernández-Rubio, J. et al. Psychoactive pharmaceuticals and illicit drugs in coastal waters of North-Western Spain: Environmental exposure and risk assessment. Chemosphere 224, 379–389 (2019).

    Google Scholar 

78. Booth, A., Aga, D. S. & Wester, A. L. Retrospective analysis of the global antibiotic residues that exceed the predicted no effect concentration for antimicrobial resistance in various environmental matrices. Environ. Int. 141, 105796 (2020).

    Google Scholar 

79. Gosset, A. et al. Ecotoxicological risk assessment of contaminants of emerging concern identified by “suspect screening” from urban wastewater treatment plant effluents at a territorial scale. Sci. Total Environ. 778, 146275 (2021).

    Google Scholar 

80. Vestel, J. Default predicted no-effect target concentrations for antibiotics in the absence of data for the protection against antibiotic resistance and environmental toxicity. Integr. Environ. Assess. Manag. ieam.4560. https://doi.org/10.1002/ieam.4560 (2022).

    Google Scholar 

81. Paraiba, L. C., Pazianotto, R. A. A., Luiz, A. J. B., Maia, A. D. H. N. & Jonsson, C. M. A mathematical model to estimate the volume of grey water of pesticide mixtures. Span. J. Agric. Res. 12, 509–518 (2014).

    Google Scholar 

82. Finizio, A., Villa, S. & Vighi, M. Predicting pesticide mixtures load in surface waters from a given crop. Agric. Ecosyst. Environ. 111, 111–118 (2005).

    Google Scholar 

83. Vale, R. L., Netto, A. M., Toríbio de Lima Xavier, B., de Lâvor Paes Barreto, M. & Siqueira da Silva, J. P. Assessment of the gray water footprint of the pesticide mixture in a soil cultivated with sugarcane in the northern area of the State of Pernambuco, Brazil. J. Clean. Prod. 234, 925–932 (2019).

    Google Scholar 

84. Barreto, M. D. L. P. et al. Gray water footprint assessment for pesticide mixtures applied to a sugarcane crop in Brazil: A comparison between two models. J. Clean. Prod. 276, 124254 (2020).

    Google Scholar 

85. Feng, Y., Na, L. & Rongxiang, W. Grey water footprint model of heavy metal based on the hazard quotient. Ecol. Indic. 162, 112052 (2024).

    Google Scholar 

86. Yu, C., Yin, X., Li, H. & Yang, Z. A hybrid water-quality-index and grey water footprint assessment approach for comprehensively evaluating water resources utilization considering multiple pollutants. J. Clean. Prod. 248, 119225 (2020).

    Google Scholar 

87. Mian, H. R., Hu, G., Hewage, K., Rodriguez, M. J. & Sadiq, R. Drinking water quality assessment in distribution networks: A water footprint approach. Sci. Total Environ. 775, 145844 (2021).

    Google Scholar 

88. Lahlou, F.-Z., Mackey, H. R. & Al-Ansari, T. Towards the development of an improved mass balance and water quality index based grey water footprint model. Environ. Sustain. Indic. 18, 100236 (2023).

    Google Scholar 

89. Li, H., Liu, G. & Yang, Z. Improved gray water footprint calculation method based on a mass-balance model and on fuzzy synthetic evaluation. J. Clean. Prod. 219, 377–390 (2019).

    Google Scholar 

90. Menussi, L. R. M. et al. Linking water footprint with the sustainable development goals: a step-by-step method description and case study. J. Environ. Acc. Manage. 11, 341–352 (2023).

    Google Scholar 

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