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Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses
Published on: October 21, 2016
Seasonal and spatial evolution of trihalomethanes in a drinking water distribution system according to the treatment
A Domínguez-Tello1,2,3, A Arias-Borrego1,2,3, Tamara García-Barrera4,5,6
1Department of Chemistry and CC.MM, Faculty of Experimental Science, University of Huelva, Campus de El Carmen, 21007, Huelva, Spain.
Abstract:
This paper comparatively shows the influence of four water treatment processes on the formation of trihalomethanes (THMs) in a water distribution system. The study was performed from February 2005 to January 2012 with analytical data of 600 samples taken in Aljaraque water treatment plant (WTP) and 16 locations along the water distribution system (WDS) in the region of Andévalo and the coast of Huelva (southwest Spain), a region with significant seasonal and population changes. The comparison of results in the four different processes studied indicated a clear link of the treatment process with the formation of THM along the WDS. The most effective treatment process is preozonation and activated carbon filtration (P3), which is also the most stable under summer temperatures. Experiments also show low levels of THMs with the conventional process of preoxidation with potassium permanganate (P4), delaying the chlorination to the end of the WTP; however, this simple and economical treatment process is less effective and less stable than P3. In this study, strong seasonal variations were obtained (increase of THM from winter to summer of 1.17 to 1.85 times) and a strong spatial variation (1.1 to 1.7 times from WTP to end points of WDS) which largely depends on the treatment process applied. There was also a strong correlation between THM levels and water temperature, contact time and pH. On the other hand, it was found that THM formation is not proportional to the applied chlorine dose in the treatment process, but there is a direct relationship with the accumulated dose of chlorine. Finally, predictive models based on multiple linear regressions are proposed for each treatment process.
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