Photodegradation of roxarsone in the aquatic environment: influencing factors, mechanisms, and artificial neural network modeling

Jizhong Meng, Arong, Shoujun Yuan, Wei Wang, Juliang Jin, Xinmin Zhan, Liwen Xiao, Zhen Hu Hu

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

11 Citations (Scopus)

Abstract

Roxarsone (ROX), an organoarsenic feed additive, can be discharged into aquatic environment and photodegraded into more toxic inorganic arsenics. However, the photodegradation behavior of ROX in aquatic environment is still unclear. To better understand ROX photodegradation behavior, the influencing factors, photodegradation mechanism, and process modelling of ROX photodegradation were investigated in this study. The results showed that ROX in the aquatic environment was degraded to inorganic As(III) and As(V) under light irradiation. The degradation efficiency was enhanced by 25% with the increase of light intensity from 300 to 800 μW/cm2 via indirect photolysis. The photodegradation was temperature dependence, but was only slightly affected by pH. Nitrate ion (NO3-) had an obvious influence, but sulfate, carbonate, and chlorate ions had a negligible effect on ROX degradation. Dissolved organic matter (DOM) in the solution inhibited the photodegradation. ROX photodegradation was mainly mediated by reactive oxygen species (in the form of single oxygen 1O2) generated through ROX self-sensitization under irradiation. Based on the data of factors affecting ROX photodegradation, ROX photodegradation model was built and trained by an artificial neural network (ANN), and the predicted degradation rate was in good agreement with the real values with a root mean square error of 1.008. This study improved the understanding of ROX photodegradation behavior and provided a basis for controlling the pollution from ROX photodegradation.

Original languageEnglish
Pages (from-to)7844-7852
Number of pages9
JournalEnvironmental Science and Pollution Research
Volume29
Issue number5
DOIs
Publication statusPublished - Jan 2022

Keywords

  • Artificial neural network
  • Mechanism
  • Modeling
  • Photodegradation
  • Roxarsone

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