Statistical analysis of a large set of semi-quantitative GC-MS screening data to evaluate and prioritize organic contaminants in surface and drinking water of the Netherlands.

Clicks: 294
ID: 34236
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #318 of 637 articles by views in The Science of the total environment

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 637 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Due to anthropogenic activities in the catchments, surface waters are contaminated with a large variety of chemical compounds. Drinking water companies in the Netherlands use surface water from the rivers Rhine, and Meuse, Lake IJssel and water from a reclaimed land area as sources for the production of drinking water. Samples from the abstraction points and the produced drinking waters were investigated using chemical screening with gas chromatography coupled to mass spectrometry to detect an as wide as possible range of organic contaminants, generating enormous data sets. This study aimed to evaluate and interpret five and a half years of screening data to get insight in the variety of known and new less polar compounds in surface and drinking waters, and to investigate if there were spatial patterns in the detection of compounds. Compounds from a wide variety of applications were detected. The vast majority of detected compounds was found only in a few samples. Certain compounds, however, e.g. organophosphate flame retardants, were detected with prevalences up to 100% per location. Most compounds were detected in samples from the rivers Rhine and Meuse, less in those from Lake IJssel and the reclaimed land area and only few in drinking water. Principal component and Hierarchical Cluster Analyses helped to detect patterns in the presence of contaminants on particular locations and to prioritize compounds for further investigation of their emission sources, and -in case of unknown compounds - their identification.
Reference Key
houtman2019statisticalthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Houtman, Corine J;Kroesbergen, Jan;Baggelaar, Paul K;van Lieverloo, J Hein M;
Journal The Science of the total environment
Year 2019
DOI
S0048-9697(19)33747-7
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.