使用 PERK 预测水生环境中的药物浓度并评估风险:英格兰西南部集水区案例研究

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Water Research Pub Date : 2024-10-18 DOI:10.1016/j.watres.2024.122643
Kishore Kumar Jagadeesan, Kathryn Proctor, Richard Standerwick, Ruth Barden, Barbara Kasprzyk-Hordern
{"title":"使用 PERK 预测水生环境中的药物浓度并评估风险:英格兰西南部集水区案例研究","authors":"Kishore Kumar Jagadeesan, Kathryn Proctor, Richard Standerwick, Ruth Barden, Barbara Kasprzyk-Hordern","doi":"10.1016/j.watres.2024.122643","DOIUrl":null,"url":null,"abstract":"The aim of this study was to introduce a model to predict pharmaceuticals concentrations in the aquatic environment and their environmental impacts using the Risk Quotient (RQ) approach. The model was trained using: (i) high resolution dataset on pharmaceuticals’ concentration in wastewater and receiving environment in a river catchment, (ii) understanding of pharmaceuticals’ discharge points in the catchment, (iii) fate of pharmaceuticals during wastewater treatment and in the receiving environment, (iv) high resolution per-postcode pharmaceutical prescription data. A total of 41 pharmaceuticals were evaluated, with successful predictions achieved for concentrations falling within the range of 0.7 (influent: 37%, effluent: 39%, river: 29%) to 1% (influent: 56%, effluent: 58%, river: 48%) of the measured values. Importantly, our risk assessment demonstrates significant environmental risks associated with specific pharmaceuticals, with strong alignment (86%) between assessments based on predicted and measured data, underscoring the reliability of our model in assessing environmental risks. The observed variability in predicted and measured concentrations underscores the necessity for ongoing model refinement, particularly in regions with notable discrepancies such as wastewater treatment plant (WWTP) C. Overall, our study illustrates the intricate dynamics of pharmaceutical contamination in aquatic ecosystems, emphasizing the crucial need for continued research in this field.","PeriodicalId":443,"journal":{"name":"Water Research","volume":null,"pages":null},"PeriodicalIF":11.4000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicting Pharmaceutical Concentrations and Assessing Risks in the Aquatic Environment Using PERK: A Case Study of a Catchment Area in South-West England\",\"authors\":\"Kishore Kumar Jagadeesan, Kathryn Proctor, Richard Standerwick, Ruth Barden, Barbara Kasprzyk-Hordern\",\"doi\":\"10.1016/j.watres.2024.122643\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this study was to introduce a model to predict pharmaceuticals concentrations in the aquatic environment and their environmental impacts using the Risk Quotient (RQ) approach. The model was trained using: (i) high resolution dataset on pharmaceuticals’ concentration in wastewater and receiving environment in a river catchment, (ii) understanding of pharmaceuticals’ discharge points in the catchment, (iii) fate of pharmaceuticals during wastewater treatment and in the receiving environment, (iv) high resolution per-postcode pharmaceutical prescription data. A total of 41 pharmaceuticals were evaluated, with successful predictions achieved for concentrations falling within the range of 0.7 (influent: 37%, effluent: 39%, river: 29%) to 1% (influent: 56%, effluent: 58%, river: 48%) of the measured values. Importantly, our risk assessment demonstrates significant environmental risks associated with specific pharmaceuticals, with strong alignment (86%) between assessments based on predicted and measured data, underscoring the reliability of our model in assessing environmental risks. The observed variability in predicted and measured concentrations underscores the necessity for ongoing model refinement, particularly in regions with notable discrepancies such as wastewater treatment plant (WWTP) C. Overall, our study illustrates the intricate dynamics of pharmaceutical contamination in aquatic ecosystems, emphasizing the crucial need for continued research in this field.\",\"PeriodicalId\":443,\"journal\":{\"name\":\"Water Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":11.4000,\"publicationDate\":\"2024-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1016/j.watres.2024.122643\",\"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://doi.org/10.1016/j.watres.2024.122643","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}
引用次数: 0

摘要

本研究的目的是采用风险商数 (RQ) 方法,建立一个模型来预测水生环境中的药物浓度及其对环境的影响。该模型利用以下数据进行了训练:(i) 某集水区废水和受纳环境中药物浓度的高分辨率数据集;(ii) 对集水区药物排放点的了解;(iii) 药物在废水处理和受纳环境中的去向;(iv) 每个邮政编码药物处方的高分辨率数据。共对 41 种药物进行了评估,成功预测了浓度在测量值 0.7(进水:37%,出水:39%,河流:29%)到 1%(进水:56%,出水:58%,河流:48%)范围内的药物。重要的是,我们的风险评估显示了与特定药物相关的重大环境风险,基于预测数据和测量数据的评估结果高度一致(86%),突出表明了我们的模型在评估环境风险方面的可靠性。我们观察到的预测浓度和测量浓度之间的差异强调了对模型进行不断完善的必要性,尤其是在污水处理厂(WWTP)C 等存在明显差异的地区。总之,我们的研究说明了水生生态系统中药物污染错综复杂的动态变化,强调了在这一领域继续开展研究的迫切需要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Predicting Pharmaceutical Concentrations and Assessing Risks in the Aquatic Environment Using PERK: A Case Study of a Catchment Area in South-West England
The aim of this study was to introduce a model to predict pharmaceuticals concentrations in the aquatic environment and their environmental impacts using the Risk Quotient (RQ) approach. The model was trained using: (i) high resolution dataset on pharmaceuticals’ concentration in wastewater and receiving environment in a river catchment, (ii) understanding of pharmaceuticals’ discharge points in the catchment, (iii) fate of pharmaceuticals during wastewater treatment and in the receiving environment, (iv) high resolution per-postcode pharmaceutical prescription data. A total of 41 pharmaceuticals were evaluated, with successful predictions achieved for concentrations falling within the range of 0.7 (influent: 37%, effluent: 39%, river: 29%) to 1% (influent: 56%, effluent: 58%, river: 48%) of the measured values. Importantly, our risk assessment demonstrates significant environmental risks associated with specific pharmaceuticals, with strong alignment (86%) between assessments based on predicted and measured data, underscoring the reliability of our model in assessing environmental risks. The observed variability in predicted and measured concentrations underscores the necessity for ongoing model refinement, particularly in regions with notable discrepancies such as wastewater treatment plant (WWTP) C. Overall, our study illustrates the intricate dynamics of pharmaceutical contamination in aquatic ecosystems, emphasizing the crucial need for continued research in this field.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
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.
期刊最新文献
Hydromorphological pressure explains the status of macrophytes and phytoplankton less effectively than eutrophication but contributes to water quality deterioration A machine learning based framework to tailor properties of nanofiltration and reverse osmosis membranes for targeted removal of organic micropollutants Effects of Mono- and Multicomponent Nonaqueous-Phase Liquid on the Migration and Retention of Pollutant-degrading Bacteria in Porous Media Faecal contamination determines bacterial assemblages over natural environmental parameters within intermittently opened and closed lagoons (ICOLLs) during high rainfall The use of ammonia recovered from wastewater as a zero-carbon energy vector to decarbonise heat, power and transport – a review
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1