» Articles » PMID: 34998751

Towards Citizen Science. On-site Detection of Nitrite and Ammonium Using a Smartphone and Social Media Software

Overview
Date 2022 Jan 9
PMID 34998751
Citations 2
Authors
Affiliations
Soon will be listed here.
Abstract

Citizen scientists-based water quality surveys are becoming popular because of their wide applications in environmental monitoring and public education. At present, many similar studies are reported on collecting samples for later laboratory analysis. For environmentally toxic analytes such as ammonium and nitrite, on-site detection is a promising choice. However, this approach is limited by the availability of suitable methods and instruments. Here, a simple on-site detection method for ammonium and nitrite is reported. The chemistry of this method is based on the classic Griess reaction and modified indophenol blue reaction. Digital image colorimetry is carried out using a smartphone with a custom-made WeChat mini-program or free built-in applications (APPs). Using a simple and low-cost analytical kit, the detection limit of 0.27 μmol/L and 0.84 μmol/L is achieved for nitrite and ammonium, respectively, which are comparable to those achieved with a benchtop spectrophotometer. Relative standard deviations (n = 7) for low and high concentrations of nitrite are 3.6% and 4.3% and for ammonium are 5.6% and 2.6%, respectively. Identical results with a relative error of less than 10% are obtained using different smartphones (n = 3), color extracting software (n = 6), and with multiple individual users (n = 5). These results show the robustness and applicability of the proposed method. The on-site application is carried out in an in-campus wastewater treatment plant and at a local river. A total of 40 samples are analyzed and the analytical results are compared with that obtained by a standard method and a spectrophotometer, followed by a paired t-test at a 95% confidence level. This proposed on-site analytical kit has the advantages of simplicity and portability and has the potential to be popular and useful for citizen science-based environmental monitoring.

Citing Articles

Turbidivision: a machine vision application for estimating turbidity from underwater images.

Rudy I, Wilson M PeerJ. 2024; 12:e18254.

PMID: 39346044 PMC: 11439400. DOI: 10.7717/peerj.18254.


Efficient smartphone-based measurement of phosphorus in water.

Ai H, Zhang K, Zhang H Water Res X. 2024; 22:100217.

PMID: 38831971 PMC: 11144757. DOI: 10.1016/j.wroa.2024.100217.