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doi:10.3808/jei.201500323
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An Approach for Estimating the Nitrobenzene (NB) Emission Effect in Frozen Rivers: A Case Study of Nitrobenzene Pollution in the Songhua River, China

W. H. Xiao1,J. H. Wang1*,Y. H. Huang2*,S. C. Sun1,3 and Y. Y. Zhou1

  1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
  2. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  3. Department of Environmental Science, Environmental Management College of China, Qinhuangdao 066004, China

*Corresponding author. Tel: +86-10-64889681 Fax: +86-10-68483367 Email: huangyh@igsnrr.ac.cn

Abstract


Clearly understanding the transport and fate of organic pollutants in frozen aquatic environments is necessary for implementing effective water quality management and public health  risk assessment during the ice-bound period. In this paper, a nitrobenzene (NB) emission model coupling a modified hydrodynamic model with a water quality model was developed and applied to simulate a NB pollution emergency in the frozen Songhua River, China, that occurred on November 13, 2005. The proposed model is capable of simulating the NB emission effect in frozen rivers. The constants of the NB transfer radio from water to ice and the ice melting speed were obtained by laboratory experiments, which indicated that 10% of the NB would transfer to ice as the water froze. The quantitative statistical tests are adopted to evaluate the model performance based on ground-measured NB concentrations from April 11th to April 27th of 2006 (the ice melting period of the study area) in the Sujiatun segment of the Songhua River. The results generally show that the modeled and detected concentrations exhibit good consistency, with a RMSE of 0.6 μg/L and an R2 of 0.877. The simulated NB released to the Amur River from the ice melt by this pollution event after April 11th is less than 12.5 μg/L, which is consistent with an absence of a negative influence on drinking water security along the River in the spring of 2006. The model performs satisfactorily for predicting the NB pollutant fate in the Songhua River and has the ability to supply the necessary information for controlling pollution events and for early warning, which could be applied to similar long frozen rivers.

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