Non-parametric regression analysis of diuron and gabapentin degradation in Lake Constance water by ozonation and their toxicity assessment

Anuradha Goswami, Jia-Qian Jiang, Michael Petri

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2 Citations (Scopus)
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Ozone possesses high selectivity in the oxidation of organic pollutants. It actively reacts with electron donating participants which contain ¿ bonds and non-protonated amines groups. The removal efficiency of organic pollutants hugely depends upon the pollutants’ initial concentration and amount of ozone supplied. This study was conducted at Zweckverband BodenseeWasserversorgung (Lake Constance Water Supply), Germany. The prime objective of the research was to observe the performance of diuron and gabapentin ozonation for low ozone doses, therefore meeting the real application requirements of the water treatment plant. Thereby, 1 mg·L¿1 of the given organic pollutants was chosen for the treatment. The ozone with a dosage of ¿0.68–1.01 mg·L¿1 was generated and homogeneously mixed into Lake Constance water in a semi-batch reactor system. The adequate aliquots of diuron/gabapentin were spiked into the homogenous matrix to acquire the desired initial concentration. The effect of ozone dose and reaction time on the degradation of diuron and gabapentin was investigated. Low ozone doses were sufficient for the complete degradation of diuron and gabapentin, although satisfactory total organic carbon (TOC) reduction was not achieved. Nonetheless, the toxicity from ozone treated effluents can be avoided by adjusting treatment conditions. Due to that degradation data obtained did not follow normalization, the non-parametric (non-normalised) data were analysed with a generalised linear regression model for Gaussian and Poisson distribution. Statistical analysis showed that the ozonation treatment of diuron/gabapentin followed the Gaussian model distribution and the degradation data obtained was proven significant using the Kruskal–Wallis test.
Original languageEnglish
Article number852
Number of pages12
Issue number4
Publication statusPublished - 23 Apr 2019


  • drinking water treatment
  • emerging micropollutants
  • Gaussian model
  • Kruskal–Wallis test
  • ozonation


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