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Comparison of NOM character in selected Australian and Norwegian drinking waters
Abstract
Observations from many countries around the world during the past 10-20 years indicate increasing natural organic matter (NOM) concentration levels in water sources, due to issues such as global warming, changes in soil acidification, increased drought severity and more intensive rain events. In addition to the trend towards increasing NOM concentration, the character of NOM can vary with source and time (season). The great seasonal variability and the trend towards elevated NOM concentration levels impose challenges to the water industry and the water treatment facilities in terms of operational optimisation and proper process control. The aim of this investigation was to compare selected raw and conventionally treated drinking water sources from different hemispheres with regard to NOM character which may lead to better understanding of the impact of source water on water treatment. Results from the analyses of selected Norwegian and Australian water samples showed that Norwegian NOM exhibited greater humic nature, indicating a stronger bias of allochthonous versus autochthonous organic origin. Similarly, Norwegian source waters had higher average molecular weights than Australian waters. Following coagulation treatment, the organic character of the recalcitrant NOM in both countries was similar. Differences in organic character of these source waters after treatment were found to be related to treatment practice rather than origin of the source water. The characterisation techniques employed also enabled identification of the coagulation processes which were not necessarily optimised for dissolved organic carbon (DOC) removal. The reactivity with chlorine as well as trihalomethane formation potential (THMFP) of the treated waters showed differences in behaviour between Norwegian and Australian sources that appeared to be related to residual higher molecular weight organic material. By evaluation of changes in specific molecular weight regions and disinfection parameters before and after treatment, correlations were found that relate treatment strategy to chlorine demand and DBP formation.
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“Fabris et al. (2008) reported an empirical relation between NOM and THM-FP as ~10-40 μg THM-FP/ mg DOC.”
From Regulation, formation, exposure, and treatment of disinfection by-products (DBPs) in swimming pool waters: A critical review (2018) · cites this paper as Fabris et al., 2008
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Metadata
- Authors
- Fabris, R., Chow, C. W. K., Drikas, M., & Eikebrokk, B.
- Affiliations
- South Australian Water Corporation (AU)
- SINTEF (NO)
- Corresponding author
- Fabris, Rolando
- Venue
- Water Research
- Publisher
- Elsevier BV
- Published
- 2008-09
- Volume
- 42
- Issue
- 15
- Pages
- 4188-4196
- ISSN
- 0043-1354 (ISSN-L)
- OpenAlex
- W2164832304
- Cited by
- 266
- References
- 28
- Citations by year
- 2026: 4 · 2025: 11 · 2024: 11 · 2023: 16 · 2022: 12 · 2021: 10 · 2020: 20 · 2019: 21 · 2018: 24 · 2017: 17 · 2016: 16 · 2015: 19 · 2014: 32 · 2013: 16 · 2012: 10
- FWCI
- 6.19
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Water Research (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Water Treatment and Disinfection
- Physical Sciences › Environmental Science › Water Science and Technology › Coagulation and Flocculation Studies
- Physical Sciences › Environmental Science › Water Science and Technology › Advanced oxidation water treatment
- Keywords
- natural organic matter, drinking water, humic substances, molecular weight distribution, coagulation, dissolved organic carbon removal, trihalomethane formation potential, disinfection byproduct formation, chlorine demand, source water, seasonal variation, water treatment, Australia, Norway
- MeSH terms
- Australia, Disinfectants, Norway, Organic Chemicals, Water Pollutants, Chemical, Water Supply
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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