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Updated: Mar 26, 2026

Estimating Sediment Denitrification Rates Using Cores and N2O Microsensors
Published on: December 6, 2018
Mathematical modeling of autotrophic denitrification (AD) process with sulphide as electron donor
Guihua Xu1, Fengjun Yin2, Shaohua Chen3
1CAS Key Laboratory of Urban Pollutant Conversion, Department of Chemistry, University of Science and Technology of China, Hefei 230026, China; Key Laboratory of Reservoir Aquatic Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
Abstract:
Autotrophic denitrification (AD) plays a critical role in nitrate removal from organic carbon-deficient wastewaters with a high level of nitrogen oxides. However, the AD process is not included in the current denitrification models, which limits the application of AD technology for wastewater treatment. In this work, a kinetic model for AD process involved 4 processes and 5 components with 9 parameters is established to describe the sulphide biooxidation and nitrite removal process. In this model, 4 oxidation-reduction reactions using sulphide as electronic donor in the AD process are taken into account. The model parameters are optimized by fitting data from the experiments with different combinations of sulphide, sulphur, sulphate, nitrate and nitrite at various concentrations. Model calibration and validation results demonstrate that the developed model is able to reasonably describe the removal rates of nitrate, nitrite, sulphide and sulphur in the AD process. The model simulation results also show that the sulphur term (η(S)) in the kinetic equations of nitrate, nitrite, sulphur and sulphate remains constant, rather than being controlled by its own concentration. Furthermore, with this model the products of sulphide biooxidation in the AD process, sulphur and sulphate, and their concentrations can be accurately predicted. Therefore, this model provides a strategy to control the sulphate concentration below the discharge limits or recover sulphur as the main end product from sulphide biooxidation.
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