Aspartame-Sweetened Tap Water: Transformation Products and 2,6-Dichloro-1,4-Benzoquinone Formation-Reference-Cited by-同舟云学术

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Aspartame-Sweetened Tap Water: Transformation Products and 2,6-Dichloro-1,4-Benzoquinone Formation

Published:2023-01-11 Issue:3 Volume:57 Page:1332-1341
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Wawryk Nicholas J. P.¹,Huang Guang¹²^ORCID,Craven Caley¹,Qiu Junlang¹,Jmaiff Blackstock Lindsay K.¹,Li Xing-Fang¹^ORCID

Affiliation:

1. Division of Analytical and Environmental Toxicology, Department of Laboratory Medicine and Pathology, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2G3, Canada

2. Department of Hygiene Analysis and Detection, School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, Jiangsu 211166, P.R. China

Funder

Canada Research Chairs

Alberta Health

Natural Sciences and Engineering Research Council of Canada

Alberta Innovates

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.2c07156

Reference37 articles.

1. 40 years on: what do we know about drinking water disinfection by-products (DBPs) and human health?

2. Disinfectant residual stability leading to disinfectant decay and by-product formation in drinking water distribution systems: A systematic review

3. Role of drinking water biofilms on residual chlorine decay and trihalomethane formation: An experimental and modeling study

4. Characterization of New Nitrosamines in Drinking Water Using Liquid Chromatography Tandem Mass Spectrometry

5. Analytical and Toxicity Characterization of Halo-hydroxyl-benzoquinones as Stable Halobenzoquinone Disinfection Byproducts in Treated Water

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1. Determining high priority disinfection byproducts based on experimental aquatic toxicity data and predictive models: Virtual screening and in vivo study;Science of The Total Environment;2024-11

2. Multi-step tap-water quality forecasting in South Korea with transformer-based deep learning model;Urban Water Journal;2024-09-05

3. Recognizing high-priority disinfection byproducts based on experimental and predicted endocrine disrupting data: Virtual screening and in vitro study;Chemosphere;2024-06

4. Water Analysis: Emerging Contaminants and Current Issues;Analytical Chemistry;2024-05-03

5. ChloroDBPFinder: Machine Learning-Guided Recognition of Chlorinated Disinfection Byproducts from Nontargeted LC-HRMS Analysis;Analytical Chemistry;2024-01-31

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