Numerical Analysis of a Full-Scale Thermophilic Biological System and Investigation of Nitrate and Ammonia Fates

Thermophilic biological processes proved to be effective in aqueous waste (AW) and high-strength wastewater treatment. In this work, the monitoring of a full-scale aerobic thermophilic biological plant treating various high-strength AW in continuous mode is reported. This paper aims to: (i) provide models to help the AW utility manager in predicting the load of fed pollutants and performances, and (ii) fully investigate nitrogen transformations in biological reactor. Based on the results, the thermophilic sludge in the studied plant was able to degrade Chemical Oxygen Demand (COD) and remove nitrate nitrogen with very high efficiency (79.3% and 97.1, respectively). The monitoring was conducted following a statistical approach and searched for the possible correlations between the input parameters and the efficiency of removal of the plant. Moreover, a multivariate linear regression was carried out highlighting that the yield value of the removal of COD and nitrogen forms, apart from ammonia, was well explained (R-2 = 0.9) by the linear regression against the other monitored parameters. As far as nitrification is concerned, there was, on the one hand, an increase in ammonium ions due to the hydrolysis of the organic substance that occurs in the reactor, and on the other hand, a stripping of the same ammoniacal nitrogen in the form of NH3. While nitrates were effectively removed, according to fluorescent in situ hybridization tests, sludge proved to be formed by minute flocs, where bacteria responsible for the oxidation of ammonium and nitrite seem to be unable to grow.

Automated summary

This paper reports the monitoring results of a full-scale aerobic thermophilic biological plant treating high-strength aqueous waste in continuous mode. The thermophilic sludge in the plant was found to efficiently degrade Chemical Oxygen Demand (COD) and remove nitrate nitrogen. Statistical analysis and multivariate linear regression were conducted to identify correlations between input parameters and removal efficiency. It was also observed that the structure of the sludge in the plant may affect the growth of bacteria responsible for ammonia oxidation and nitrite oxidation, based on fluorescent in situ hybridization tests.