Shortcut nitrification–denitrification by real-time control strategies

Gao, Dawen; Peng, Yongzhen; Li, Baikun; Liang, Hong

doi:10.1016/j.jbiotec.2008.07.1511

Cited by 22 publications

(26 citation statements)

References 3 publications

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“…It is usually calculated as the change in the rise slope of the DO profile [30]. However, in this work, it has been obtained based on ORAS arrow , in order to guarantee that its value is more accurate and less sensitive to outliers: the DO value, in its rising profile, for which the ORAS arrow is a maximum.…”

Section: Wastewater Key Parameter Indicatorsmentioning

confidence: 99%

Obtaining Key Parameters and Working Conditions of Wastewater Biological Nutrient Removal by Means of Artificial Intelligence Tools

Vega

Jaramillo-Morán

2018

Water

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Abstract:The oxidation-reduction potential (ORP) and the dissolved oxygen (DO) have been monitored in a municipal wastewater treatment plant (WWTP). Three thousand two hundred aeration-non-aeration cycles were recorded. They were analyzed by defining 16 parameters to characterize each one of them. The vectors so obtained were treated with the box-plot tool to reject those with outliers (abnormally high or low values). The remaining data were processed by a neural network (self-organizing map: SOM) in order to classify them into classes and to obtain relations between parameters to identify those more representative of the system dynamics. They were: the oxygen uptake rate (OUR), the oxygen rise average slope (ORAS), and the oxidation-reduction potential "arrow" (ORP arrow , the maximum distance between the ORP curve and its linearization). Finally, the classes obtained from SOM were grouped into four macro-classes by means of the K-means algorithm in order to define four operation states related to seasonal and load characteristics, which may be taken into account, along with the key parameters, in the WWTP management with the aim of improving the nutrient removal performance by adapting their controllers to seasonal and load variations.

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Section: Wastewater Key Parameter Indicatorsmentioning

confidence: 99%

Obtaining Key Parameters and Working Conditions of Wastewater Biological Nutrient Removal by Means of Artificial Intelligence Tools

Vega

Jaramillo-Morán

2018

Water

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“…The shadowed area individuates the ''integrated biological degradation and ozonation'' phase without passing by nitrate (i.e., the so-called shortcut nitrification-denitrification process) has received great attention by researchers thanks to the possibility to save up to 25 % of oxygen and 40 % of organic carbon source (Verstraete and Philips 1998). However, it is usually difficult to achieve a stable shortcut nitrification-denitrification at neutral pH, ambient temperature and DO in the range 2-5 mg/l (Gao et al 2009); in particular, a long aeration time can gradually convert a shortcut nitrification process into full nitrification. The high biomass concentration in SBBGR can be responsible for the disappearance of nitrite oxidizing bacteria (NOB).…”

Section: Biomass Characterizationmentioning

confidence: 99%

On-site treatment of textile yarn dyeing effluents using an integrated biological–chemical oxidation process

Lotito

Sanctis

Rossetti

et al. 2013

Int. J. Environ. Sci. Technol.

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This paper reports the results of the treatment of a yarn dyeing effluent using an integrated biologicalchemical oxidation process. In particular, the biological unit was based on a sequencing batch biofilter granular sludge reactor (SBBGR), while the chemical treatment consisted of an ozonation step. Biological treatment alone was first performed as a reference for comparison. While biological treatment did not produce an effluent for direct discharge, the integrated process assured good treatment results, with satisfactory removal of chemical oxygen demand (up to 89.8 %), total nitrogen (up to 88.2 %), surfactants (up to 90.7 %) and colour (up to 99 %), with an ozone dose of 110 mg of ozone per litre of wastewater. Biomass characterization by fluorescence in situ hybridization has revealed that filamentous bacteria represented about 20 % of biomass (coherently with high sludge volume index values); thanks to its special design, SBBGR guaranteed, however, stable treatment performances and low effluent suspended solids concentrations, while conventional activated sludge systems suffer from sludge bulking and even treatment failure in such a condition. Furthermore, biomass characterization has evidenced the presence of a shortcut nitrification-denitrification process.

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“…질소제거 단축공정은 유기 탄소원의 양을 절감시키며, 알칼리도의 파괴를 줄일 수 있고 공정에 소요되는 시간을 단 축시킬 뿐만 아니라 슬러지 발생량도 적다는 장점이 있다 (Gao, et al, 2009) (Fig. 3).…”

Section: Sdb Mediaunclassified

Nitrite Removal by Autotrophic Denitrification Using Sulfur Particles

Woo-Chang¹,

Oh²

2010

Korean Journal of Environmental Agriculture

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Swine wastewater contains high amounts of organic matter and nutrients (nitrogen and phosphorus). The biological nitrogen removal can be achieved by nitrification and denitrification processes. Nitrification-denitrification can be performed via nitrite which is called as the short-cut process. This Short-cut process saves up to 25% of oxygen and 40% of external carbon during nitrification and denitrification. In this study, the batch tests were conducted to assess the different parameters for the nitrite sulfur utilizing denitrification, such as alkalinity, temperature, initial nitrite concentration, and dissolved oxygen. The experimental results showed that the nitrite removal efficiency of the reactor was found to be over 95% under the optimum condition (30℃ and sufficient alkalinity). Autotrophic nitrate denitrification was inhibited at low alkalinity condition showing only 10% removal efficiency, while nitrite denitrification was achieved over 95%. The nitrite removal rates were found similar at both 20℃ and 30℃. In addition, nitrite removal efficiencies were inhibited by increasing oxygen concentration, but sulfate concentration increased due to sulfur oxidation under an aerobic condition. Sulfate production and alkalinity consumption were decreased with nitrite compared those with nitrate.

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Shortcut nitrification–denitrification by real-time control strategies

Cited by 22 publications

References 3 publications

Obtaining Key Parameters and Working Conditions of Wastewater Biological Nutrient Removal by Means of Artificial Intelligence Tools

Obtaining Key Parameters and Working Conditions of Wastewater Biological Nutrient Removal by Means of Artificial Intelligence Tools

On-site treatment of textile yarn dyeing effluents using an integrated biological–chemical oxidation process

Nitrite Removal by Autotrophic Denitrification Using Sulfur Particles

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