Jameel, Y, Valle, D and Kay, P orcid.org/0000-0002-9997-7860 (2020) Spatial variation in the detection rates of frequently studied pharmaceuticals in Asian, European and North American rivers. Science of The Total Environment, 724. 137947. ISSN 0048-9697
Abstract
Pharmaceutical consumption has expanded rapidly during the last century and their persistent presence in the environment has become a major concern. Unfortunately, our understanding of the distribution of pharmaceuticals in surface water and their effects on aquatic biota and public health is limited. Here, we explore patterns in the detection rate of the most frequently studied pharmaceuticals in 64 rivers from 22 countries using bi-clustering algorithms and subsequently analyze the results in the context of regional differences in pharmaceutical consumption habits, social and environmental factors, and removal-efficiency of wastewater treatment plants (WWTP). We find that 20% of the pharmaceuticals included in this analysis are pervasively present in all the surface waterbodies. Several pharmaceuticals also display low overall positive detection rates; however, they exhibit significant spatial variability and their detection rates are consistently lower in Western European and North America (WEOG) rivers in comparison to Asian rivers. Our analysis suggests the important role of pharmaceutical consumption and population in governing these patterns, however the role of WWTP efficiency appeared to be limited. We were constrained in our ability to assess the role of hydrology, which most likely also plays an important role in regulating pharmaceuticals in rivers. Most importantly though, we demonstrate the ability of our algorithm to provide probabilistic estimates of the detection rate of pharmaceuticals that were not studied in a river, an exercise that could be useful in prioritizing pharmaceuticals for future study.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier B.V. All rights reserved. This is an author produced version of an article published in Science of the Total Environment. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Pharmaceuticals; Clustering; Big data; Water quality |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Geography (Leeds) > River Basin Processes & Management (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Dec 2020 15:37 |
Last Modified: | 19 Mar 2021 01:38 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.scitotenv.2020.137947 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:169053 |