Mikael Gustavsson , Ekaterina Sokolova , Sverker Molander , Prajwol Prajapati , Johan Kjellin , Anna Karlsson , Karin Wiberg , Erik Kristiansson
{"title":"开发和验证一种新的方法来预测在一个湖泊接收废水的有效药物成分的时空浓度动态","authors":"Mikael Gustavsson , Ekaterina Sokolova , Sverker Molander , Prajwol Prajapati , Johan Kjellin , Anna Karlsson , Karin Wiberg , Erik Kristiansson","doi":"10.1016/j.watres.2025.124256","DOIUrl":null,"url":null,"abstract":"<div><div>Human consumption of pharmaceuticals leads to continuous emissions of active pharmaceutical ingredients (APIs) to the aquatic environment, primarily via wastewater treatment plants (WWTPs). However, temporal and spatial patterns of environmental API concentrations are challenging to assess using conventional chemical measurements. Chemical risk assessments are, consequently, typically based on low-resolution data and often overlook API concentrations of environmental concern. We, therefore, developed a new method, combining emission and hydrodynamic modeling to estimate spatiotemporal variations. The method was applied in a case study in a Swedish lake receiving water from a WWTP (capacity 200,000 person equivalents), including >500 prescription APIs. The emission model was validated using ten different APIs measured monthly in the WWTP effluent, and of 103 measured API concentrations 102 were predicted within a factor of 10. The full method was validated against 321 historical measurements from the lake, covering 20 different APIs where 233 (73%) and 319 (99%) of the predicted concentrations were within a factor of 10 and 100 of the measurements. Thus, our method enables predictions of environmental concentrations of APIs, accurate enough to supplement and guide environmental monitoring, directly from human prescription data. Furthermore, we demonstrate that API concentrations vary by orders of magnitude over time and space, directly impacting risk management and monitoring.</div></div>","PeriodicalId":443,"journal":{"name":"Water Research","volume":"287 ","pages":"Article 124256"},"PeriodicalIF":12.4000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development and validation of a new method for predicting spatial and temporal concentration dynamics of active pharmaceutical ingredients in a lake receiving wastewater effluents\",\"authors\":\"Mikael Gustavsson , Ekaterina Sokolova , Sverker Molander , Prajwol Prajapati , Johan Kjellin , Anna Karlsson , Karin Wiberg , Erik Kristiansson\",\"doi\":\"10.1016/j.watres.2025.124256\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Human consumption of pharmaceuticals leads to continuous emissions of active pharmaceutical ingredients (APIs) to the aquatic environment, primarily via wastewater treatment plants (WWTPs). However, temporal and spatial patterns of environmental API concentrations are challenging to assess using conventional chemical measurements. Chemical risk assessments are, consequently, typically based on low-resolution data and often overlook API concentrations of environmental concern. We, therefore, developed a new method, combining emission and hydrodynamic modeling to estimate spatiotemporal variations. The method was applied in a case study in a Swedish lake receiving water from a WWTP (capacity 200,000 person equivalents), including >500 prescription APIs. The emission model was validated using ten different APIs measured monthly in the WWTP effluent, and of 103 measured API concentrations 102 were predicted within a factor of 10. The full method was validated against 321 historical measurements from the lake, covering 20 different APIs where 233 (73%) and 319 (99%) of the predicted concentrations were within a factor of 10 and 100 of the measurements. Thus, our method enables predictions of environmental concentrations of APIs, accurate enough to supplement and guide environmental monitoring, directly from human prescription data. Furthermore, we demonstrate that API concentrations vary by orders of magnitude over time and space, directly impacting risk management and monitoring.</div></div>\",\"PeriodicalId\":443,\"journal\":{\"name\":\"Water Research\",\"volume\":\"287 \",\"pages\":\"Article 124256\"},\"PeriodicalIF\":12.4000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0043135425011625\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0043135425011625","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
Development and validation of a new method for predicting spatial and temporal concentration dynamics of active pharmaceutical ingredients in a lake receiving wastewater effluents
Human consumption of pharmaceuticals leads to continuous emissions of active pharmaceutical ingredients (APIs) to the aquatic environment, primarily via wastewater treatment plants (WWTPs). However, temporal and spatial patterns of environmental API concentrations are challenging to assess using conventional chemical measurements. Chemical risk assessments are, consequently, typically based on low-resolution data and often overlook API concentrations of environmental concern. We, therefore, developed a new method, combining emission and hydrodynamic modeling to estimate spatiotemporal variations. The method was applied in a case study in a Swedish lake receiving water from a WWTP (capacity 200,000 person equivalents), including >500 prescription APIs. The emission model was validated using ten different APIs measured monthly in the WWTP effluent, and of 103 measured API concentrations 102 were predicted within a factor of 10. The full method was validated against 321 historical measurements from the lake, covering 20 different APIs where 233 (73%) and 319 (99%) of the predicted concentrations were within a factor of 10 and 100 of the measurements. Thus, our method enables predictions of environmental concentrations of APIs, accurate enough to supplement and guide environmental monitoring, directly from human prescription data. Furthermore, we demonstrate that API concentrations vary by orders of magnitude over time and space, directly impacting risk management and monitoring.
期刊介绍:
Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include:
•Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management;
•Urban hydrology including sewer systems, stormwater management, and green infrastructure;
•Drinking water treatment and distribution;
•Potable and non-potable water reuse;
•Sanitation, public health, and risk assessment;
•Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions;
•Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment;
•Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution;
•Environmental restoration, linked to surface water, groundwater and groundwater remediation;
•Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts;
•Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle;
•Socio-economic, policy, and regulations studies.