Rapid direct analysis of river water and machine learning assisted suspect screening of emerging contaminants in passive sampler extracts-Reference-Cited by-同舟云学术

Rapid direct analysis of river water and machine learning assisted suspect screening of emerging contaminants in passive sampler extracts

Published:2021 Issue:5 Volume:13 Page:595-606
ISSN:1759-9660
Container-title:Analytical Methods
language:en
Short-container-title:Anal. Methods

Author:

Richardson Alexandra K.¹²³⁴⁵^ORCID,Chadha Marcus⁶⁷⁸,Rapp-Wright Helena¹²³⁴⁵,Mills Graham A.⁹¹⁰¹¹⁸,Fones Gary R.⁹¹⁰¹¹⁸^ORCID,Gravell Anthony¹²¹³¹⁴⁸,Stürzenbaum Stephen¹²³⁴⁵^ORCID,Cowan David A.¹²³⁴⁵,Neep David J.⁶¹⁵⁸,Barron Leon P.¹²³⁴⁵^ORCID

Affiliation:

1. Dept. Analytical, Environmental & Forensic Sciences

2. School of Population Health & Environmental Sciences

3. Faculty of Life Sciences & Medicine

4. King's College London

5. London

6. Agilent Technologies UK Limited

7. Cheadle

8. UK

9. Faculty of Science and Health

10. University of Portsmouth

11. Portsmouth

12. Natural Resources Wales, Faraday Building

13. Swansea University

14. Swansea SA2 8PP

15. Church Stretton

Abstract

Machine-learning assisted suspect screening in passive sampler extracts and rapid direct injection LC-MS/MS of river water from the River Thames, London, UK in 2018/9.

Funder

Biotechnology and Biological Sciences Research Council

Publisher

Royal Society of Chemistry (RSC)

Subject

General Engineering,General Chemical Engineering,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2021/AY/D0AY02013C

Reference61 articles.

1. Toward a Global Understanding of Chemical Pollution: A First Comprehensive Analysis of National and Regional Chemical Inventories

2. Spatial (bio)accumulation of pharmaceuticals, illicit drugs, plasticisers, perfluorinated compounds and metabolites in river sediment, aquatic plants and benthic organisms

3. Bioaccumulation and biomagnification potential of pharmaceuticals with a focus to the aquatic environment