Pambrun V, Paul E, Spérandio M
Laboratoire d'Ingénierie des Procédés de l'Environnement (LIPE-EA833), Institut National des Sciences Appliquées de Toulouse (INSA), 135 Avenue de Rangueil, 31077 Toulouse cedex 04, France.
Biotechnol Bioeng. 2006 Sep 5;95(1):120-31. doi: 10.1002/bit.21008.
Partial nitrification has proven to be an economic way for treatment of industrial N-rich effluent, reducing oxygen and external COD requirements during nitrification/denitrification process. One of the key issues of this system is the intermediate nitrite accumulation stability. This work presents a control strategy and a modeling tool for maintaining nitrite build-up. Partial nitrification process has been carried out in a sequencing batch reactor at 30 degrees C, maintaining strong changing ammonia concentration in the reactor (sequencing feed). Stable nitrite accumulation has been obtained with the help of an on-line oxygen uptake rate (OUR)-based control system, with removal rate of 2 kg NH4 (+)-N x m(-3)/day and 90%-95% of conversion of ammonium into nitrite. A mathematical model, identified through the occurring biological reactions, is proposed to optimize the process (preventing nitrate production). Most of the kinetic parameters have been estimated from specific respirometric tests on biomass and validated on pilot-scale experiments of one-cycle duration. Comparison of dynamic data at different pH confirms that NH3 and NO2- should be considered as the true substrate of nitritation and nitratation, respectively. The proposed model represents major features: the inhibition of ammonia-oxidizing bacteria by its substrate (NH3) and product (HNO2), the inhibition of nitrite-oxidizing bacteria by free ammonia (NH3), the INFluence of pH. It appears that the model correctly describes the short-term dynamics of nitrogenous compounds in SBR, when both ammonia oxidizers and nitrite oxidizers are present and active in the reactor. The model proposed represents a useful tool for process design and optimization.
部分硝化已被证明是处理富含氮的工业废水的一种经济方法，可降低硝化/反硝化过程中的氧气和外部化学需氧量需求。该系统的关键问题之一是中间亚硝酸盐积累的稳定性。这项工作提出了一种用于维持亚硝酸盐积累的控制策略和建模工具。部分硝化过程在序批式反应器中于30℃下进行，保持反应器中氨浓度剧烈变化（序批进料）。借助基于在线氧摄取率（OUR）的控制系统获得了稳定的亚硝酸盐积累，去除率为2 kg NH4(+)-N x m(-3)/天，铵转化为亚硝酸盐的转化率为90%-95%。通过发生的生物反应确定了一个数学模型，以优化该过程（防止硝酸盐产生）。大多数动力学参数已通过对生物质的特定呼吸测定试验进行估计，并在为期一个周期的中试规模实验中得到验证。不同pH下动态数据的比较证实，NH3和NO2-应分别被视为亚硝化和硝化的真正底物。所提出的模型体现了主要特征：氨氧化细菌受到其底物（NH3）和产物（HNO2）的抑制，亚硝酸盐氧化细菌受到游离氨（NH3）的抑制，pH的影响。当氨氧化菌和亚硝酸盐氧化菌都存在且在反应器中活跃时，该模型似乎正确地描述了序批式反应器中含氮化合物的短期动态。所提出的模型是用于工艺设计和优化的有用工具。
