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In statistics, several tools are used to interpret the data. Measures of central tendency represent the characteristics of the data, such as mean, median, and mode. Additionally, measures of variance like standard deviation and range are used to find the spread of data from the mean. Relative standing measures the distance between data locations. Commonly used measures of relative standings are percentile, z score, and quartiles.
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Advanced strategies to improve nitrification process in sequencing batch reactors - A review.

Francisco Jaramillo1, Marcos Orchard1, Carlos Muñoz2

  • 1Department of Electrical Engineering, University of Chile, Av. Tupper 2007, Santiago, Chile.

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|April 22, 2018
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Summary

Researchers are optimizing biological nitrogen removal (BNR) in sequencing batch reactors by focusing on the nitrification phase. Strategies include partial nitrification, real-time monitoring, and advanced modeling for improved efficiency and cost reduction.

Keywords:
ASMBending-pointsData-driven modelsPartial nitrificationSBR

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Area of Science:

  • Environmental Engineering
  • Wastewater Treatment
  • Biotechnology

Background:

  • Biological Nitrogen Removal (BNR) is crucial for wastewater treatment efficiency and cost reduction.
  • The nitrification phase is identified as the rate-limiting step in BNR processes.
  • Optimization of BNR in sequencing batch reactors (SBRs) is a global research focus.

Purpose of the Study:

  • To analyze various strategies for optimizing the nitrification phase in BNR.
  • To discuss tools for enhancing BNR efficiency, including partial nitrification and advanced monitoring.
  • To evaluate the integration of different strategies for long-term, stable, and efficient BNR.

Main Methods:

  • Analysis of factors influencing partial nitrification.
  • Real-time control and monitoring for nitrification/denitrification endpoint detection.
  • Application of activated sludge models and data-driven modeling for variable estimation.

Main Results:

  • Identified key strategies and tools for optimizing BNR, focusing on the nitrification stage.
  • Discussed the properties, scope, advantages, and disadvantages of each strategy.
  • Highlighted the potential for integrating these strategies for improved BNR performance.

Conclusions:

  • Various strategies and tools can enhance BNR efficiency in SBRs, particularly by optimizing nitrification.
  • Data-driven modeling and real-time monitoring offer solutions for unmeasured variables.
  • Integration of discussed strategies, considering constraints, can lead to more stable and cost-effective long-term BNR.