Development of a Real-Time, Mobile Nitrate Monitoring Station for High-Frequency Data Collection

Abstract

A mobile monitoring station was developed to measure nitrate and physicochemical water quality parameters remotely, in real-time, and at very high frequencies (thirty minutes). Several calibration experiments were performed to validate the outputs of a real-time nutrient sensor, which can be affected by optical interferences such as turbidity, pH, temperature and salinity. Whilst most of these proved to play a minor role, a data-driven compensation model was developed to account for turbidity interferences. The reliability of real-time optical sensors has been questioned previously; however, this study has shown that following compensation, the readings can be more accurate than traditional laboratory-based equipment. In addition, significant benefits are offered by monitoring waterways at high frequencies, due to rapid changes in analyte concentrations over short time periods. This, combined with the versatility of the mobile station, provides opportunities for several beneficial monitoring applications, such as of fertiliser runoff in agricultural areas in rural regions, aquaculture runoff, and waterways in environmentally sensitive areas such as the Great Barrier Reef.

Electrochemical and Optical Sensors for Real-Time Detection of Nitrate in Water

“…In UV-absorbance-based optical nitrate analyzers, turbidity induces a scattering effect that influences the absorption spectrum and results in detection errors. Furthermore, many dissolved components are present in natural water that absorb the UV wavelength and influence the UV sensor response due to interference and matrix effects [ 80 , 101 ].…”

Cloud-Enabled Real-Time Monitoring and Alert System for Primary Network Resource Scheduling and Large-Scale Users

“…In this study, a real-time monitoring and forecasting system based on cloud computing technology for main network scheduling and large users is constructed, and its overall architecture is shown in Fig. 2, which operates collaboratively through five levels to realize the comprehensive collection, processing, analysis, display and service of power data [25]. Firstly, in the data acquisition layer, the system grabs key power parameters in real time from all kinds of devices in the main power network and large users, including voltage, current, power, frequency, electric energy, tariff, etc., and also covers environmental factors such as temperature, humidity, wind speed and solar radiation, etc., and transmits these diversified data to the data processing layer through wired or wireless communication technology.…”