Characterisation, Measurement, and Monitoring of Natural Organic Matter (NOM) in South African Water Systems

1. Characterisation, measurement and monitoring of natural organic matter (NOM) in South African water systems Water Services Forum – Water Quality 17 April 2019

2. Outline • Introduction • - What is NOM? - Why is it a problem? • Identifying the research question • NOM research in SA • - characterisation techniques • - method development • - NOM as DBP precursor • - Research needs/ gaps • Take home message

3. Introduction – Typical NOM structure

4. Introduction NOM in the environment Amino sugars Fulvic acid Humic acid D-xylose 3-Acetonedicarboxylic acid

5. Introduction – Size range of DOM and POM Humic matter HPO Aromatic (UV254) Non-humic matter HPI Aliphatic

6. Introduction – Where do we find NOM? • Occurrence of NOM In all natural water sources • Autochthonous - Inside water body • Phytoplankton/ macrophyte activity • Allochthonous- Outside water body • Terrestrial organic carbon input • Upstream water bodies

7. Introduction – NOM during water treatment Coagulants Disinfectants HPO HPI Coagulation and Flocculation Sedimentation Effluent DBPs

8. Introduction – Why is NOM a problem? NOM + free Cl2 → THMs + HAAs + other DBPs PROBLEMS

9. IntroductionDifficulty in NOM characterisation • Assessment of NOM character in SA is limited • 2007-2014 Prof Bhekie B Mamba; Prof Johannes Haarhoff Dr Thabo TI Nkambule • 2015-currently mainly by NanoWS – UNISA (CSET) • NOM techniques have various limitations → NOM complex mixture (heterogeneous) → single technique only provide partial info. → highlights a specific character of NOM • Composition of NOM changes

10. Problem statementWhat do we need to know about NOM to understand its treatability? Known: • NOM character differs (changes) • Difficult to characteriseNOM Unknown: • NOM character of the source water? • Investigate individual NOM fraction removed • Establish which NOM fraction is: more prone to form DBPs / more degradable by bacteria • Which characterisation technique/s? • Optimisewater treatment process

11. MethodologyCharacterisationof NOM • Isolate NOM within the source water and determine bulk NOM concentration • Fractionation into groups (fractions) of compounds with similar physical or chemical characteristics. - To identify which fractions dominates the NOM - To investigate the influence of these fractions on DBP formation - To determine NOM treatability – which fractions are removed where in the treatment process

12. Methodology • Bulk characterisation • DOC, UV254, SUVA • Fractionate • PRAM (polarity rapid assessment method)

13. MethodologyPolarity rapid assessment method (PRAM) TPI HPO HPI

14. Typical results Polarity rapid assessment method (PRAM)

15. MethodologyWhat does the SUVA value tell us? Characteriseindividual fractions (HPO, HPI, TPI) • Dissolved organic carbon (DOC) • Ultraviolet absorbance (UV254) • Specific ultraviolet absorbance (SUVA)

16. Typical resultsSpecific ultraviolet absorbance (SUVA) Positive correlation between source water SUVA and UV254 removal at the full scale plant

17. Methodology Characterise individual fractions (HPO, HPI, TPI) • Dissolved organic carbon (DOC) • Ultraviolet absorbance (UV254) • Specific ultraviolet absorbance (SUVA) • Biodegradable dissolved organic carbon (BDOC)

18. Methodology Characteriseindividual fractions (HPO, HPI, TPI) • Dissolved organic carbon (DOC) • Ultraviolet absorbance (UV254) • Specific ultraviolet absorbance (SUVA) • Biodegradable dissolved organic carbon (BDOC) • Fluorescence excitation emission matrix (FEEM)

19. MethodologyFluorescence excitation emission matrix (FEEM) • Composition + concentration of org. matter influences the intensity + shape of fluorescence spectra • Fluorescence intensity (FI) peaks and FEEM contour plots → predict the type of org. matter (humic-, fulvic- or protein-like material) A – Humic-like B – Protein-like Tyrosine C – Humic- / Fulvic-like T – Protein-like Tryptophan ↑ Aromaticity and MW

20. Typical resultsNOM character - FEEM HPO (before Cl2) HPO (after Cl2)

21. MethodologyHPSEC – molecular size distribution of NOM Characterize individual fractions (HPO, HPI, TPI) • Dissolved organic carbon (DOC) • Ultraviolet absorbance (UV254) • Specific ultraviolet absorbance (SUVA) • Biodegradable dissolved organic carbon (BDOC) • Fluorescence excitation emission matrix (FEEM) • High performance size exclusion chromatography (HPSEC)

22. Methodology • Bulk characterisation • DOC, UV254, SUVA • Fractionate • PRAM (polarity rapid assessment method) • Characterise individual fractions (BDOC, FEEM, HPSEC) 3. Investigate NOM treatability and influence of each fraction on THM formation • Trihalomethane formation potential (THMFP)

23. Methodology Determine thrihalomethane formation potential (THMFP) of the 3 NOM fractions Chlorinate (8 mg/L) Cl2 demand (Cl2 dosed – residual Cl2) THMf-THMi Trihalomethane formation potential (THMFP) • THMFP = THM7d – THM3omin

24. Typical resultsChlorine demand of individual fractions

25. Typical resultsNOM character and THM formation

26. Modified polarity rapid assessment method (m-PRAM) Fluorescence excitation emission matrix (FEEM) Biodegradable dissolved organic carbon (BDOC) analysis Ultraviolet absorbance (UV) at 254 nm (UV254) Specific ultraviolet absorbance (SUVA) NOM research in SA – WRC report 1883/1/12 (NOM in drinking water sources) • Method development Haarhoff J., Mamba, B., Krause, R., Van Staden, S., Nkambule, T, Dlamini, S. & Lobanga, K.P. (2012) Natural organic matter in drinking water sources: Its characterization and treatability. WRC Report No. 1883/1/12. July 2012. 109p.

27. NOM character in SA surface water varies NOM is removed mostly by coagulation Investigated treatment technology: ion exchange (IEX) resins, enhanced coagulation (EC) and granular activated carbon (GAC) filtration as alternative to ↑ NOM removal Show how different NOM character reacts to the various treatment options NOM research in SA – WRC report 1883/1/12 (NOM in drinking water sources) • Characterisation & Treatability Haarhoff J., Mamba, B., Krause, R., Van Staden, S., Nkambule, T, Dlamini, S. & Lobanga, K.P. (2012) Natural organic matter in drinking water sources: Its characterization and treatability. WRC Report No. 1883/1/12. July 2012. 109p.

28. NOM research in SA – WRC report 1883/1/12 (NOM in drinking water sources) • Gaps/ Research needs identified: - Preliminary characterisation of NOM - Seasonal variation in NOM character? - Individual fractions → Removal? Where? → Formation of DBPs? Haarhoff J., Mamba, B., Krause, R., Van Staden, S., Nkambule, T, Dlamini, S. & Lobanga, K.P. (2012) Natural organic matter in drinking water sources: Its characterization and treatability. WRC Report No. 1883/1/12. July 2012. 109p.

29. NOM research in SA – WRC report 2468/1/18 (NOM in South African waters) Vol I: NOM fractionation, characterization and formation of disinfection by-products. SS Marais, NG Ndlangamandla, DA Bopape, WF Strydom, W Moyo, N Chaukura, AT Kuvarega, L de Kock, BB Mamba, TAM Msagati and TI Nkambule. June 2018.

30. Take home message • NOM characterisation techniques have been identified, and included in a NOM characterisation and monitoring protocol.

31. NOM characterisation protocol Characterise bulk NOM Fractionate NOM Determine biodegradable NOM Investigate THM precursors and FEEM

32. Take home message • NOM characterisation techniques have been identified. Use these techniques to: • Calculate % NOM removal and NOM treatability in WTPs (individual NOM fractions) • Determine influence of individual NOM fractions on THM formation (identify specific THM precursor) • When investigating / comparing different treatment technologies (MIEX, GAC, conventional water treated, ultrafiltration) • Before optimising existing water treatment process (vital to enhance removal of specific NOM fractions in order to reduce THM formation)

33. Questions? Thank you