On-line biological oxygen demand (BOD) monitoring using a microbial membrane reactor

Abstract

An on-line biological oxygen demand (BOD) monitoring instrument, utilizing an in-situ microbial membrane reactor, automates membrane cultivation, calibration, and rapid BOD detection, eliminating reagent pollution is presented. The core instrument used was an STM32F103RCT6 microcontroller embedded in the FreeRTOS real-time operating system. A series of practical application tests were carried out by the instrument. The results demonstrate that the instrument provides good stability and accuracy in detecting multiple concentrations of glucose and glutamic acid (GGA) standards, with a relative error range and relative standard deviation range from −3.01 to 11.88% and 4.19 to 6.69%, respectively. The tested water samples had a relative error range from −4.93 to 13.37%. The on-line monitoring instrument for BOD has been tested for almost three months and has shown stable performance, high accuracy, and real-time, in-situ, and on-line BOD detection. In the past three months of application testing, the on-line biological oxygen demand monitoring instrument has shown stable performance, good accuracy, and real-time, in-situ, and on-line BOD measurements. This device has significant environmental benefits for continuous water quality monitoring and the timely monitoring of water pollution.

Keywords:

• Biological oxygen demand (BOD)
• microbial membrane reactor
• dissolved oxygen

Author contributions

Yiyuan Chen: Investigation, conceptualization, instrument manufacturing and debugging, data curation, writing–original draft. Wuping Zhou: Chemical method experiments and instrument debugging. Song Zhao: Experiment and discussion. Haowei Zhou: Experiment and discussion. Changyu Liu: Conceptualization, supervision, project administration, writing – review & editing, finalization. Xiaolong Xu: Writing – review & editing.

Disclosure statement

No potential conflicts of interest are reported by the author(s).

Additional information

Funding

This research was funded by the National Natural Science Foundation of China [No. 22274117] and the Education Department of Guangdong Province [No. 2022ZDJS027].